(lively music) >> Hello, everyone. Welcome back to the Supercloud presentation here. I'm theCUBE, I'm John Furrier, your host. What a great segment here. We're going to unpack the networking aspect of the cloud, how that translates into what Supercloud architecture and platform deployment scenarios look like. And demystify multi-cloud, hybridcloud. We've got two great experts. Amir Khan, the Co-Founder and CEO of Alkira, Atif Khan, Co-Founder and CTO of Alkira. These guys been around since 2018 with the startup, but before that story, history in the tech industry. I mean, routing early days, multiple waves, multiple cycles. >> Welcome three decades. >> Welcome to Supercloud. >> Thanks. >> Thanks for coming on. >> Thank you so much for having us. >> So, let's get your take on Supercloud because it's been one of those conversations that really galvanized the industry because it kind of highlights almost this next wave, this next side of the street that everyone's going to be on that's going to be successful. The laggards on the legacy seem to be stuck on the old model. SaaS is growing up, it's ISVs, it's ecosystems, hyperscale, full hybrid. And then multi-cloud around the corners cause all this confusion, everyone's hand waving. You know, this is a solution, that solution, where are we? What do you guys see as this supercloud dynamic? >> So where we start from is always focusing on the customer problem. And in 2018 when we identified the problem, we saw that there were multiple clouds with many diverse ways of doing things from the network perspective, and customers were struggling with that. So we delved deeper into that and looked at each one of the cloud architectures completely independent. And there was no common solution and customers were struggling with that from the perspective. They wanted to be in multiple clouds, either through mergers and acquisitions or running an application which may be more cost effective to run in something or maybe optimized for certain reasons to run in a different cloud. But from the networking perspective, everything needed to come together. So that's, we are starting to define it as a supercloud now, but basically, it's a common infrastructure across all clouds. And then integration of high lift services like, you know, security or IPAM services or many other types of services like inter-partner routing and stuff like that. So, Amir, you agree then that multi-cloud is simply a default result of having whatever outcomes, either M&A, some productivity software, maybe Azure. >> Yes. >> Amazon has this and then I've got on-premise application, so it's kinds mishmash. >> So, I would qualify it with hybrid multi-cloud because everything is going to be interconnected. >> John: Got it. >> Whether it's on-premise, remote users or clouds. >> But have CTO perspective, obviously, you got developers, multiple stacks, got AWS, Azure and GCP, other. Not everyone wants to kind of like go all in, but yet they don't want to hedge too much because it's a resource issue. And I got to learn this stack, I got to learn that stack. So then now, you have this default multi-cloud, hybrid multi-cloud, then it's like, okay, what do I do? How do you spread that around? Is it dangerous? What's the the approach technically? What's some of the challenges there? >> Yeah, certainly. John, first, thanks for having us here. So, before I get to that, I'll just add a little bit to what Amir was saying, like how we started, what we were seeing and how it, you know, correlates with the supercloud. So, as you know, before this company, Alkira, we were doing, we did the SD-WAN company, which was Viptela. So there, we started seeing when people started deploying SD-WAN at like a larger scale. We started like, you know, customers coming to us and saying they needed connectivity into the cloud from the SD-WAN. They wanted to extend the SD-WAN fabric to the cloud. So we came up with an architecture, which was like later we started calling them Cloud onRamps, where we built, you know, a transit VPC and put like the virtual instances of SD-WAN appliances extended from there to the cloud. But before we knew, like it started becoming very complicated for the customers because it wasn't just connectivity, it also required, you know, other use cases. You had to instantiate or bring in security appliances in there. You had to secure all of that stuff. There were requirements for, you know, different regions. So you had to bring up the same thing in different regions. Then multiple clouds, what did you do? You had to replicate the same thing in multiple clouds. And now if there was was requirement between clouds, how were you going to do it? You had to route traffic from somewhere, and come up with all those routing controls and stuff. So, it was very complicated. >> Like spaghetti code, but on network. >> The games begin, in fact, one of our customers called it spaghetti mess. And so, that's where like we thought about where was the industry going and which direction the industry was going into? And we came up with the Alkira where what we are doing is building a common infrastructure across multiple clouds, across in, you know, on-prem locations, be it data centers or physical sites, branches sites, et cetera, with integrated security and network networking services inside. And, you know, nowadays, networking is not only about connectivity, you have to secure everything. So, security has to be built in. Redundancy, high availability, disaster recovery. So all of that needs to be built in. So that's like, you know, kind of a definition of like what we thought at that time, what is turning into supercloud now. >> Yeah. It's interesting too, you mentioned, you know, VPCs is not, configuration of loans a hassle. Nevermind the manual mistakes could be made, but as you decide to do something you got to, "Oh, we got to get these other things." A lot of the hyper scales and a lot of the alpha cloud players now, and cloud native folks, they're kind of in that mode of, "Wow, look at what we've built." Now, they're got to maintain, how do I refresh it? Like, how do I keep the talent? So they got this similar chaotic environment where it's like, okay, now they're already already through, so I think they're going to be okay. But then some people want to bypass it completely. So there's a lot of customers that we see out there that fit the makeup of, I'm cloud first, I've lifted and shifted, I move some stuff to the cloud. But I want to bypass all that learnings from all the people that are gone through the past three years. Can I just skip that and go to a multi-cloud or coherent infrastructure? What do you think about that? What's your view? >> So yeah, so if you look at these enterprises, you know, many of them just to find like the talent, which for one cloud as far as the IT staff is concerned, it's hard enough. And now, when you have multiple clouds, it's hard to find people the talent which is, you know, which has expertise across different clouds. So that's where we come into the picture. So our vision was always to simplify all of this stuff. And simplification, it cannot be just simplification because you cannot just automate the workflows of the cloud providers underneath. So you have to, you know, provide your full data plane on top of it, fed full control plane, management plane, policy and management on top of it. And coming back to like your question, so these nowadays, those people who are working on networking, you know, before it used to be like CLI. You used to learn about Cisco CLI or Juniper CLI, and you used to work on it. Nowadays, it's very different. So automation, programmability, all of that stuff is the key. So now, you know, Ops guys, the DevOps guys, so these are the people who are in high demand. >> So what do you think about the folks out there that are saying, okay, you got a lot of fragmentation. I got the stacks, I got a lot of stove pipes, if you will, out there on the stack. I got to learn this from Azure. Can you guys have with your product abstract the way that's so developers don't need to know the ins and outs of stack's, almost like a gateway, if you will, the old days. But like I'm a developer or team develop, why should I have to learn the management layer of Azure? >> That's exactly what we started, you know, out with to solve. So it's, what we have built is a platform and the platform sits inside the cloud. And customers are able to build their own network or a virtual network on top using that platform. So the platform has its own data plane, own control plane and management plane with a policy layer on top of it. So now, it's the platform which is sitting in different clouds, but from a customer's point of view, it's one way of doing networking. One way of instantiating or bringing in services or security services in the middle. Whether those are our security services or whether those are like services from our partners, like Palo Alto or Checkpoint or Cisco. >> So you guys brought the SD-WAN mojo and refactored it for the cloud it sounds like. >> No. >> No? (chuckles) >> We cannot said. >> All right, explain. >> It's way more than that. >> I mean, SD-WAN was wan. I mean, you're talking about wide area networks, talking about connected, so explain the difference. >> SD-WAN was primarily done for one major reason. MPLS was expensive, very strong SLAs, but very low speed. Internet, on the other hand, you sat at home and you could access your applications much faster. No SLA, very low cost, right? So we wanted to marry the two together so you could have a purely private infrastructure and a public infrastructure and secure both of them by creating a common secure fabric across all those environments. And then seamlessly tying it into your internal branch and data center and cloud network. So, it merely brought you to the edge of the cloud. It didn't do anything inside the cloud. Now, the major problem resides inside the clouds where you have to optimize the clouds themselves. Take a step back. How were the clouds built? Basically, the cloud providers went to the Ciscos and Junipers and the rest of the world, built the network in the data centers or across wide area infrastructure, and brought it all together and tried to create a virtualized layer on top of that. But there were many limitations of this underlying infrastructure that they had built. So number of routes per region, how inter region connectivity worked, or how many routes you could carry to the VPCs of V nets? That all those were becoming no common policy across, you know, these environments, no segmentation across these environments, right? So the networking constructs that the enterprise customers were used to as enterprise class carry class capabilities, they did not exist in the cloud. So what did the customer do? They ended up stitching it together all manually. And that's why Atif was alluding to earlier that it became a spaghetti mess for the customers. And then what happens is, as a result, day two operations, you know, troubleshooting, everything becomes a nightmare. So what do you do? You have to build an infrastructure inside the cloud. Cloud has enough raw capabilities to build the solutions inside there. Netflix's of the world. And many different companies have been born in the cloud and evolved from there. So why could we not take the raw capabilities of the clouds and build a network cloud or a supercloud on top of these clouds to optimize the whole infrastructure and seamlessly connecting it into the on-premise and remote user locations, right? So that's your, you know, hybrid multi-cloud solution. >> Well, great call out on the SD-WAN in common versus cloud. 'Cause I think this is important because you're building a network layer in the cloud that spans out so the customers don't have to get into the, there's a gap in the system that I'm used to, my operating environment, of having lockdown security and network. >> So yeah. So what you do is you use the raw capabilities like bandwidth or virtual machines, or you know, containers, or, you know, different types of serverless capabilities. And you bring it all together in a way to solve the networking problems, thereby creating a supercloud, which is an abstraction layer which hides all the complexity of the underlying clouds from the customer, right? And it provides a common infrastructure across all environments to that customer, right? That's the beauty of it. And it does it in a way that it looks like, if they have the networking knowledge, they can apply it to this new environment and carry it forward. One way of doing security across all clouds and hybrid environments. One way of doing routing. One way of doing large-scale network address translation. One way of doing IPAM services. So people are tired of doing individual things and individual clouds and on-premise locations, right? So now they're getting something common. >> You guys brought that, you brought all that to bear and flexible for the customer to essentially self-serve their network cloud. >> Yes, yeah. Is that the wave? >> And nowadays, from business perspective, agility is the key, right? You have to move at the pace of the business. If you don't, you are losing. >> So, would it be safe to say that you guys have a network supercloud? >> Absolutely, yeah. >> We, pretty much, yeah. Absolutely. >> What does that mean to our customer? What's in it for them? What's the benefit to the customer? I got a network supercloud, it connects, provides SLA, all the capabilities I need. What do they get? What's the end point for them? What's the end? >> Atif, maybe you can talk some examples. >> The IT infrastructure is all like distributed now, right? So you have applications running in data centers. You have applications running in one cloud. Other cloud, public clouds, enterprises are depending on so many SaaS applications. So now, these are, you can call these endpoints. So a supercloud or a network cloud, from our perspective, it's a cloud in the middle or a network in the middle, which provides connectivity from any endpoint to any endpoint. So, you are able to connect to the supercloud or network cloud in one way no matter where you are. So now, whichever cloud you are in, whichever cloud you need to connect to. And also, it's not just connecting to the cloud. So you need to do a lot of stuff, a lot of networking inside the cloud also. So now, as Amir was saying, every cloud has its own from a networking, you know, the concept perspective or the construct, they are different. There are limitations in there also. So this supercloud, which is sitting on top, basically, your platform is sitting into the cloud, but the supercloud is built on top of using your platform. So that abstracts all those complexities, all those limitations. So now your limitations are whatever the limitations of that platform are. So now your platform, that platform is in our control. So we can keep building it, we can keep scaling it horizontally. Because one of the things is that, you know, in this cloud era, one of the things is autoscaling these services. So why can't the network now autoscale also, just like your other services. >> Network autoscaling is a genius idea, and I think that's a killer. I want to ask the the follow on question because I think, first of all, I love what you guys are doing. So, I think it's a great example of this new innovation. It's not obvious until you see it, right? Geographical is huge. So, you know, single instance, global instances, multiple instances, you're seeing global. How do you guys look at that global equation? Because as companies expand their clouds into geos, and then ultimately, you know, it's obviously continent, region and locales. You're going to have geographic issues. So, this is an extension of your network cloud? >> Amir: It is the extension of the network cloud because if you look at this hyperscalers, they're sitting pretty much everywhere in the globe. So, wherever their regions are, the beauty of building a supercloud is that you can by definition, be available in those regions. It literally takes a day or two of testing for our stack to run in those regions, to make sure there are no nuances that we run into, you know, for that region. The moment we bring it up in that region, all customers can onboard into that solution. So literally, what used to take months or years to build a global infrastructure, now, you can configure it in 10 minutes basically, and bring it up in less than one hour. Since when did we see any solution- >> And by the way, >> that can come up with. >> when the edge comes out too, you're going to start to see more clouds get bolted on. >> Exactly. And you can expand to the edge of the network. That's why we call cloud the new edge, right? >> John: Yeah, it is. Now, I think you guys got a good solutions, network clouds, superclouds, good. So the question on the premise side, so I get the cloud play. It's very cool. You can expand out. It's a nice layer. I'm sure you manage the SLAs between latency and all kinds of things. Knowing when not to do things. Physics or physics. Okay. Now, you've got the on-premise. What's the on-premise equation look like? >> So on-premise, the kind of customers, we are working with large enterprises, mid-size enterprises. So they have on-prem networks, they have deployed, in many cases, they have deployed SD-WAN. In many cases, they have MPLS. They have data centers also. And a lot of these companies are, you know, moving the applications from the data center into the cloud. But we still have large enterprise- >> But for you guys, you can sit there too with non server or is it a box or what is it? >> It's a software stack, right? So, we are a software company. >> Okay, so no box. >> No box. >> Okay, got it. >> No box. >> It's even better. So, we can connect any, as I mentioned, any endpoint, whether it's data centers. So, what happens is usually these enterprises from the data centers- >> John: It's a cloud endpoint for you. >> Cloud endpoint for us. And they need highspeed connectivity into the cloud. And our network cloud is sitting inside the or supercloud is sitting inside the cloud. So we need highspeed connectivity from the data centers. This is like multi-gig type of connectivity. So we enable that connectivity as a service. And as Amir was saying, you are able to bring it up in minutes, pretty much. >> John: Well, you guys have a great handle on supercloud. I really appreciate you guys coming on. I have to ask you guys, since you have so much experience in the industry, multiple inflection points you've guys lived through and we're all old, and we can remember those glory days. What's the big deal going on right now? Because you can connect the dots and you can imagine, okay, like a Lambda function spinning up some connectivity. I need instant access to a new route, throw some, I need to send compute to an edge point for process data. A lot of these kind of ad hoc services are going to start flying around, which used to be manually configured as you guys remember. >> Amir: And that's been the problem, right? The shadow IT, that was the biggest problem in the enterprise environment. So that's what we are trying to get the customers away from. Cloud teams came in, individuals or small groups of people spun up instances in the cloud. It was completely disconnected from the on-premise environment or the existing IT environment that the customer had. So, how do you bring it together? And that's what we are trying to solve for, right? At a large scale, in a carrier cloud center (indistinct). >> What do you call that? Shift right or shift left? Shift left is in the cloud native world security. >> Amir: Yes. >> Networking and security, the two hottest areas. What are you shifting? Up or down? I mean, the network's moving up the stack. I mean, you're seeing the run times at Kubernetes later' >> Amir: Right, right. It's true we're end-to-end virtualization. So you have plumbing, which is the physical infrastructure. Then on top of that, now for the first time, you have true end-to-end virtualization, which the cloud-like constructs are providing to us. We tried to virtualize the routers, we try to virtualize instances at the server level. Now, we are bringing it all together in a truly end-to-end virtualized manner to connect any endpoint anywhere across the globe. Whether it's on-premise, home, multiple clouds, or SaaS type environments. >> Yeah. If you talk about the technical benefits beyond virtualizations, you kind of see in virtualization be abstracted away. So you got end-to-end virtualization, but you don't need to know virtualization to take advantage of it. >> Exactly. Exactly. >> What are some of the tech involved where, what's the trend around on top of virtual? What's the easy button for that? >> So there are many, many use cases from the customers and they're, you know, some of those use cases, they used to deliver out of their data centers before. So now, because you, know, it takes a long time to spend something up in the data center and stuff. So the trend is and what enterprises are looking for is agility. And to achieve that agility, they are moving those services or those use cases into the cloud. So another technical benefit of like something like a supercloud and what we are doing is we allow customers to, you know, move their services from existing data centers into the cloud as well. And I'll give you some examples. You know, these enterprises have, you know, tons of partners. They provide connectivity to their partners, to select resources. It used to happen inside the data center. You would bring in connectivity into the data center and apply like tons of ACLs and whatnot to make sure that you are able to only connect. And now those use cases are, they need to be enabled inside the cloud. And the customer's customers are also, it's not just coming from the on-prem, they're coming from the cloud as well. So, if they're coming from the cloud as well as from on-prem, so you need like an infrastructure like supercloud, which is sitting inside the cloud and is able to handle all these use cases. So all of these use cases have to be, so that requires like moving those services from the data center into the cloud or into the supercloud. So, they're, oh, as we started building this service over the last four years, we have come across so many use cases. And to deliver those use cases, you have to have a platform. So you have to have your own platform because otherwise you are depending on somebody else's, you know, capabilities. And every time their capabilities change, you have to change. >> John: I'm glad you brought up the platform 'cause I want to get your both reaction to this. So Bob Muglia just said on theCUBE here at Supercloud, that supercloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. So the question is, is supercloud a platform or an architecture in your view? >> That's an interesting view on things, you know? I mean, if you think of it, you have to design or architect a solution before we turn it into a platform. >> John: It's a trick question actually. >> So it's a, you know, so we look at it as that you have to have an architectural approach end to end, right? And then you build a solution based on that approach. So, I don't think that they are mutually exclusive. I think they go hand in hand. It's an architecture that you turn into a solution and provide that agility and high availability and disaster recovery capability that it built into that. >> It's interesting that these definitions might be actually redefined with this new configuration. >> Amir: Yes. >> Because architecture and platform used to mean something, like, aight here's a platform, you buy this platform. >> And then you architecture solution. >> Architect it via vendor. >> Right, right, right. >> Okay. And they have to deal with that architecture in the place of multiple superclouds. If you have too many stove pipes, then what's the purpose of supercloud? >> Right, right, right. And because, you know, historically, you built a router and you sold it to the customer. And the poor customer was supposed to install it all, you know, and interconnect all those things. And if you have 40, 50,000 router network, which we saw in our lifetime, 'cause there used to be many more branches when we were growing up in the networking industry, right? You had to create hierarchy and all kinds of things to figure out how to solve that problem. We are no longer living in that world anymore. You cannot deploy individual virtual instances. And that's what approach a lot of people are taking, which is a pure overly network. You cannot take that approach anymore. You have to evolve the architecture and then build the solution based on that architecture so that it becomes a platform which is readily available, highly scalable, and available. And at the same time, it's very, very easy to deploy. It's a SaaS type solution, right? >> So you're saying, do the architecture to get the solution for the platform that the customer has. >> Amir: Yes. >> They're not buying a platform, they end up with a platform- >> With the platform. >> as a result of Supercloud path. All right. So that's what's, so you mentioned, that's a great point. I want to double click on what you just said. 'Cause I like that what you said. What's the deployment strategy in your mind for supercloud? I'm an architect. I'm at an enterprise in the Midwest. I'm an insurance company, got some cloud action going on. I'm mostly on-premise. I've got the mandate to transform the company. We have apps. We'll be fully transformed in five years. What's my strategy? What do I do? >> Amir: The resources. >> What's the deployment strategy? Single global instance, code in every region, on every cloud? >> It needs to be a solution which is available as a SaaS service, right? So from the customer's perspective, they are onboarding into the supercloud. And then the supercloud is allowing them to do whatever they used to do, you know, historically and in the new world, right? That needs to come together. And that's what we have built is that, we have brought everything together in a way that what used to take months or years, and now taking an hour or two hours, and then people test it for a week or so and deploy it in production. >> I want to bring up something we were talking about before we were on camera about the TCP/IP, the OSI model. That was a concept that destroyed the proprietary narcissist. Work operating systems of the mini computers, which brought in an era of tech prosperity for generations. TCP/IP was kind of the magical moment that allowed for that kind of super networking connection. Inter networking is what's called as a category. It feels like something's going on here with supercloud. The way you describe it, it feels like there's this unification idea. Like the reality is we've got multiple stuff sitting around by default, you either clean it up or get rid of it, right? Or it's almost a, it's either a nuance, a new nuisance or chaos. >> Yeah. And we live in the new world now. We don't have the luxury of time. So we need to move as fast as possible to solve the business problems. And that's what we are running into. If we don't have automated solutions which scale, which solve our problems, then it's going to be a problem. And that's why SaaS is so important in today's world. Why should we have to deploy the network piecemeal? Why can't we have a solution? We solve our problem as we move forward and we accomplish what we need to accomplish and move forward. >> And we don't really need standards here, dude. It's not that we need a standards body if you have unification. >> So because things move so fast, there's no time to create a standards body. And that's why you see companies like ours popping up, which are trying to create a common infrastructure across all clouds. Otherwise if we vent the standardization path may take long. Eventually, we should be going in that direction. But we don't have the luxury of time. That's what I was trying to get to. >> Well, what's interesting is, is that to your point about standards and ratification, what ratifies a defacto anything? In the old days there was some technical bodies involved, but here, I think developers drive everything. So if you look at the developers and how they're voting with their code. They're instantly, organically defining everything as a collective intelligence. >> And just like you're putting out the paper and making it available, everybody's contributing to that. That's why you need to have APIs and terra form type constructs, which are available so that the customers can continue to improve upon that. And that's the Net DevOps, right? So that you need to have. >> What was once sacrilege, just sayin', in business school, back in the days when I got my business degree after my CS degree was, you know, no one wants to have a better mousetrap, a bad business model to have a better mouse trap. In this case, the better mouse trap, the better solution actually could be that thing. >> It is that thing. >> I mean, that can trigger, tips over the industry. >> And that that's where we are seeing our customers. You know, I mean, we have some publicly referenceable customers like Coke or Warner Music Group or, you know, multiple others and chart industries. The way we are solving the problem. They have some of the largest environments in the industry from the cloud perspective. And their whole network infrastructure is running on the Alkira infrastructure. And they're able to adopt new clouds within days rather than waiting for months to architect and then deploy and then figure out how to manage it and operate it. It's available as a service. >> John: And we've heard from your customer, Warner, they were just on the program. >> Amir: Yes. Okay, okay. >> So they're building a supercloud. So superclouds aren't just for tech companies. >> Amir: No. >> You guys build a supercloud for networking. >> Amir: It is. >> But people are building their own superclouds on top of all this new stuff. Talk about that dynamic. >> Healthcare providers, financials, high-tech companies, even startups. One of our startup customers, Tekion, right? They have these dealerships that they provide sales and support services to across the globe. And for them to be able to onboard those dealerships, it is 80% less time to production. That is real money, right? So, maybe Atif can give you a lot more examples of customers who are deploying. >> Talk about some of the customer activity. What are they like? Are they laggards, they innovators? Are they trying to hit the easy button? Are they coming in late or are you got some high customers? >> Actually most of our customers, all of our customers or customers in general. I don't think they have a choice but to move in this direction because, you know, the cloud has, like everything is quick now. So the cloud teams are moving faster in these enterprises. So now that they cannot afford the network nor to keep up pace with the cloud teams. So, they don't have a choice but to go with something similar where you can, you know, build your network on demand and bring up your network as quickly as possible to meet all those use cases. So, I'll give you an example. >> John: So the demand's high for what you guys do. >> Demand is very high because the cloud teams have- >> John: Yeah. They're going fast. >> They're going fast and there's no stopping. And then network teams, they have to keep up with them. And you cannot keep deploying, you know, networks the way you used to deploy back in the day. And as far as the use cases are concerned, there are so many use cases which our customers are using our platform for. One of the use cases, I'll give you an example of these financial customers. Some of the financial customers, they have their customers who they provide data, like stock exchanges, that provide like market data information to their customers out of data centers part. But now, their customers are moving into the cloud as well. So they need to come in from the cloud. So when they're coming in from the cloud, you cannot be giving them data from your data center because that takes time, and your hair pinning everything back. >> Moving data is like moving, moving money, someone said. >> Exactly. >> Exactly. And the other thing is like you have to optimize your traffic flows in the cloud as well because every time you leave the cloud, you get charged a lot. So, you don't want to leave the cloud unless you have to leave the cloud, your traffic. So, you have to come up or use a service which allows you to optimize all those traffic flows as well, you know? >> My final question to you guys, first of all, thanks for coming on Supercloud Program. Really appreciate it. Congratulations on your success. And you guys have a great positioning and I'm a big fan. And I have to ask, you guys are agile, nimble startup, smart on the cutting edge. Supercloud concept seems to resonate with people who are kind of on the front range of this major wave. While all the incumbents like Cisco, Microsoft, even AWS, they're like, I think they're looking at it, like what is that? I think it's coming up really fast, this trend. Because I know people talk about multi-cloud, I get that. But like, this whole supercloud is not just SaaS, it's more going on there. What do you think is going on between the folks who get it, supercloud, get the concept, and some are who are scratching their heads, whether it's the Ciscos or someone, like I don't get it. Why is supercloud important for the folks that aren't really seeing it? >> So first of all, I mean, the customers, what we saw about six months, 12 months ago, were a little slower to adopt the supercloud kind of concept. And there were leading edge customers who were coming and adopting it. Now, all of a sudden, over the last six to nine months, we've seen a flurry of customers coming in and they are from all disciplines or all very diverse set of customers. And they're starting to see the value of that because of the practical implications of what they're doing. You know, these shadow IT type environments are no longer working and there's a lot of pressure from the management to move faster. And then that's where they're coming in. And perhaps, Atif, if you can give a few examples of. >> Yeah. And I'll also just add to your point earlier about the network needing to be there 'cause the cloud teams are like, let's go faster. And the network's always been slow because, but now, it's been almost turbocharged. >> Atif: Yeah. Yeah, exactly. And as I said, like there was no choice here. You had to move in this industry. And the other thing I would add a little bit is now if you look at all these enterprises, most of their traffic is from, even from which is coming from the on-prem, it's going to the cloud SaaS applications or public clouds. And it's more than 50% of traffic, which is leaving your, you know, what you used to call, your network or the private network. So now it's like, you know, before it used to just connect sites to data centers and sites together. Now, it's a cloud as well as the SaaS application. So it's either internet bound or the public cloud bound. So now you have to build a network quickly, which caters to all these use cases. And that's where like something- >> And you guys, your solution to me is you eliminate all that work for the customer. Now, they can treat the cloud like a bag of Legos. And do their thing. Well, I oversimplify. Well, you know I'm talking about. >> Atif: Right, exactly. >> And to answer your question earlier about what about the big companies coming in and, you know, now they slow to adopt? And, you know, what normally happens is when Cisco came up, right? There used to be 16 different protocols suites. And then we finally settled on TCP/IP and DECnet or AppleTalk or X&S or, you know, you name it, right? Those companies did not adapt to the networking the way it was supposed to be done. And guess what happened, right? So if the companies in the networking space do not adopt this new concept or new way of doing things, I think some of them will become extinct over time. >> Well, I think the force and function too is the cloud teams as well. So you got two evolutions. You got architectural relevance. That's real as impact. >> It's very important. >> Cost, speed. >> And I look at it as a very similar disruption to what Cisco's the world, very early days did to, you know, bring the networking out, right? And it became the internet. But now we are going through the cloud. It's the cloud era, right? How does the cloud evolve over the next 10, 15, 20 years? Everything's is going to be offered as a service, right? So slowly data centers go away, the network becomes a plumbing thing. Very, you know, simple to deploy. And everything on top of that is virtualized in the cloud-like manners. >> And that makes the networks hardened and more secure. >> More secure. >> It's a great way to be secure. You remember the glory days, we'll go back 15 years. The Cisco conversation was, we got to move up to stack. All the manager would fight each other. Now, what does that actually mean? Stay where we are. Stay in your lane. This is kind of like the network's version of moving up the stack because not so much up the stack, but the cloud is everywhere. It's almost horizontally scaled. >> It's extending into the on-premise. It is already moving towards the edge, right? So, you will see a lot- >> So, programmability is a big program. So you guys are hitting programmability, compatibility, getting people into an environment they're comfortable operating. So the Ops people love it. >> Exactly. >> Spans the clouds to a level of SLA management. It might not be perfectly spanning applications, but you can actually know latencies between clouds, measure that. And then so you're basically managing your network now as the overall infrastructure. >> Right. And it needs to be a very intelligent infrastructure going forward, right? Because customers do not want to wait to be able to troubleshoot. They don't want to be able to wait to deploy something, right? So, it needs to be a level of automation. >> Okay. So the question for you guys both on we'll end on is what is the enablement that, because you guys are a disruptive enabler, right? You create this fabric. You're going to enable companies to do stuff. What are some of the things that you see and your customers might be seeing as things that they're going to do as a result of having this enablement? So what are some of those things? >> Amir: Atif, perhaps you can talk through the some of the customer experience on that. >> It's agility. And we are allowing these customers to move very, very quickly and build these networks which meet all these requirements inside the cloud. Because as Amir was saying, in the cloud era, networking is changing. And if you look at, you know, going back to your comment about the existing networking vendors. Some of them still think that, you know, just connecting to the cloud using some concepts like Cloud OnRamp is cloud networking, but it's changing now. >> John: 'Cause there's apps that are depending upon. >> Exactly. And it's all distributed. Like IT infrastructure, as I said earlier, is all distributed. And at the end of the day, you have to make sure that wherever your user is, wherever your app is, you are able to connect them securely. >> Historically, it used to be about building a router bigger and bigger and bigger and bigger, you know, and then interconnecting those routers. Now, it's all about horizontal scale. You don't need to build big, you need to scale it, right? And that's what cloud brings to the customer. >> It's a cultural change for Cisco and Juniper because they have to understand that they're still could be in the game and still win. >> Exactly. >> The question I have for you, what are your customers telling you that, what's some of the anecdotal, like, 'cause you guys have a good solution, is it, "Oh my god, you guys saved my butt." Or what are some of the commentary that you hear from the customers in terms of praise and and glory from your solution? >> Oh, some even say, when we do our demo and stuff, they say it's too hard to believe. >> Believe. >> Like, too hard. It's hard, you know, it's >> I dont believe you. They're skeptics. >> I don't believe you that because now you're able to bring up a global network within minutes. With networking services, like let's say you have APAC, you know, on-prem users, cloud also there, cloud here, users here, you can bring up a global network with full routed connectivity between all these endpoints with security services. You can bring up like a firewall from a third party or our services in the middle. This is a matter of minutes now. And this is all high speed connectivity with SLAs. Imagine like before connecting, you know, Singapore to U.S. East or Hong Kong to Frankfurt, you know, if you were putting your infrastructure in columns like E-connects, you would have to go, you know, figure out like, how am I going to- >> Seal line In, connect to it? Yeah. A lot of hassles, >> If you had to put like firewalls in the middle, segmentation, you had to, you know, isolate different entities. >> That's called heavy lifting. >> So what you're seeing is, you know, it's like customer comes in, there's a disbelief, can you really do that? And then they try it out, they go, "Wow, this works." Right? It's deployed in a small environment. And then all of a sudden they start taking off, right? And literally we have seen customers go from few thousand dollars a month or year type deployments to multi-million dollars a year type deployments in very, very short amount of time, in a few months. >> And you guys are pay as you go? >> Pay as you go. >> Pay as go usage cloud-based compatibility. >> Exactly. And it's amazing once they get to deploy the solution. >> What's the variable on the cost? >> On the cost? >> Is it traffic or is it. >> It's multiple different things. It's packaged into the overall solution. And as a matter of fact, we end up saving a lot of money to the customers. And not only in one way, in multiple different ways. And we do a complete TOI analysis for the customers. So it's bandwidth, it's number of connections, it's the amount of compute power that we are using. >> John: Similar things that they're used to. >> Just like the cloud constructs. Yeah. >> All right. Networking supercloud. Great. Congratulations. >> Thank you so much. >> Thanks for coming on Supercloud. >> Atif: Thank you. >> And looking forward to seeing more of the demand. Translate, instant networking. I'm sure it's going to be huge with the edge exploding. >> Oh yeah, yeah, yeah, yeah. >> Congratulations. >> Thank you so much. >> Thank you so much. >> Okay. So this is Supercloud 2 event here in Palo Alto. I'm John Furrier. The network Supercloud is here. Checkout Alkira. I'm John Furry, the host. Thanks for watching. (lively music)

(upbeat music) >> Hello, everybody. This is Dave Vellante. Welcome back to Supercloud2, where we're exploring the intersection of data analytics and the future of cloud. In this segment, we're going to look at how the Supercloud will support a new class of applications, not just work that runs on multiple clouds, but rather a new breed of apps that can orchestrate things in the real world. Think Uber for many types of businesses. These applications, they're not about codifying forms or business processes. They're about orchestrating people, places, and things in a business ecosystem. And I'm pleased to welcome my colleague and friend, George Gilbert, former Gartner Analyst, Wiki Bond market analyst, former equities analyst as my co-host. And we're thrilled to have Tristan Handy, who's the founder and CEO of DBT Labs and Bob Muglia, who's the former President of Microsoft's Enterprise business and former CEO of Snowflake. Welcome all, gentlemen. Thank you for coming on the program. >> Good to be here. >> Thanks for having us. >> Hey, look, I'm going to start actually with the SuperCloud because both Tristan and Bob, you've read the definition. Thank you for doing that. And Bob, you have some really good input, some thoughts on maybe some of the drawbacks and how we can advance this. So what are your thoughts in reading that definition around SuperCloud? >> Well, I thought first of all that you did a very good job of laying out all of the characteristics of it and helping to define it overall. But I do think it can be tightened a bit, and I think it's helpful to do it in as short a way as possible. And so in the last day I've spent a little time thinking about how to take it and write a crisp definition. And here's my go at it. This is one day old, so gimme a break if it's going to change. And of course we have to follow the industry, and so that, and whatever the industry decides, but let's give this a try. So in the way I think you're defining it, what I would say is a SuperCloud is a platform that provides programmatically consistent services hosted on heterogeneous cloud providers. >> Boom. Nice. Okay, great. I'm going to go back and read the script on that one and tighten that up a bit. Thank you for spending the time thinking about that. Tristan, would you add anything to that or what are your thoughts on the whole SuperCloud concept? >> So as I read through this, I fully realize that we need a word for this thing because I have experienced the inability to talk about it as well. But for many of us who have been living in the Confluence, Snowflake, you know, this world of like new infrastructure, this seems fairly uncontroversial. Like I read through this, and I'm just like, yeah, this is like the world I've been living in for years now. And I noticed that you called out Snowflake for being an example of this, but I think that there are like many folks, myself included, for whom this world like fully exists today. >> Yeah, I think that's a fair, I dunno if it's criticism, but people observe, well, what's the big deal here? It's just kind of what we're living in today. It reminds me of, you know, Tim Burns Lee saying, well, this is what the internet was supposed to be. It was supposed to be Web 2.0, so maybe this is what multi-cloud was supposed to be. Let's turn our attention to apps. Bob first and then go to Tristan. Bob, what are data apps to you? When people talk about data products, is that what they mean? Are we talking about something more, different? What are data apps to you? >> Well, to understand data apps, it's useful to contrast them to something, and I just use the simple term people apps. I know that's a little bit awkward, but it's clear. And almost everything we work with, almost every application that we're familiar with, be it email or Salesforce or any consumer app, those are applications that are targeted at responding to people. You know, in contrast, a data application reacts to changes in data and uses some set of analytic services to autonomously take action. So where applications that we're familiar with respond to people, data apps respond to changes in data. And they both do something, but they do it for different reasons. >> Got it. You know, George, you and I were talking about, you know, it comes back to SuperCloud, broad definition, narrow definition. Tristan, how do you see it? Do you see it the same way? Do you have a different take on data apps? >> Oh, geez. This is like a conversation that I don't know has an end. It's like been, I write a substack, and there's like this little community of people who all write substack. We argue with each other about these kinds of things. Like, you know, as many different takes on this question as you can find, but the way that I think about it is that data products are atomic units of functionality that are fundamentally data driven in nature. So a data product can be as simple as an interactive dashboard that is like actually had design thinking put into it and serves a particular user group and has like actually gone through kind of a product development life cycle. And then a data app or data application is a kind of cohesive end-to-end experience that often encompasses like many different data products. So from my perspective there, this is very, very related to the way that these things are produced, the kinds of experiences that they're provided, that like data innovates every product that we've been building in, you know, software engineering for, you know, as long as there have been computers. >> You know, Jamak Dagani oftentimes uses the, you know, she doesn't name Spotify, but I think it's Spotify as that kind of example she uses. But I wonder if we can maybe try to take some examples. If you take, like George, if you take a CRM system today, you're inputting leads, you got opportunities, it's driven by humans, they're really inputting the data, and then you got this system that kind of orchestrates the business process, like runs a forecast. But in this data driven future, are we talking about the app itself pulling data in and automatically looking at data from the transaction systems, the call center, the supply chain and then actually building a plan? George, is that how you see it? >> I go back to the example of Uber, may not be the most sophisticated data app that we build now, but it was like one of the first where you do have users interacting with their devices as riders trying to call a car or driver. But the app then looks at the location of all the drivers in proximity, and it matches a driver to a rider. It calculates an ETA to the rider. It calculates an ETA then to the destination, and it calculates a price. Those are all activities that are done sort of autonomously that don't require a human to type something into a form. The application is using changes in data to calculate an analytic product and then to operationalize that, to assign the driver to, you know, calculate a price. Those are, that's an example of what I would think of as a data app. And my question then I guess for Tristan is if we don't have all the pieces in place for sort of mainstream companies to build those sorts of apps easily yet, like how would we get started? What's the role of a semantic layer in making that easier for mainstream companies to build? And how do we get started, you know, say with metrics? How does that, how does that take us down that path? >> So what we've seen in the past, I dunno, decade or so, is that one of the most successful business models in infrastructure is taking hard things and rolling 'em up behind APIs. You take messaging, you take payments, and you all of a sudden increase the capability of kind of your median application developer. And you say, you know, previously you were spending all your time being focused on how do you accept credit cards, how do you send SMS payments, and now you can focus on your business logic, and just create the thing. One of, interestingly, one of the things that we still don't know how to API-ify is concepts that live inside of your data warehouse, inside of your data lake. These are core concepts that, you know, you would imagine that the business would be able to create applications around very easily, but in fact that's not the case. It's actually quite challenging to, and involves a lot of data engineering pipeline and all this work to make these available. And so if you really want to make it very easy to create some of these data experiences for users, you need to have an ability to describe these metrics and then to turn them into APIs to make them accessible to application developers who have literally no idea how they're calculated behind the scenes, and they don't need to. >> So how rich can that API layer grow if you start with metric definitions that you've defined? And DBT has, you know, the metric, the dimensions, the time grain, things like that, that's a well scoped sort of API that people can work within. How much can you extend that to say non-calculated business rules or governance information like data reliability rules, things like that, or even, you know, features for an AIML feature store. In other words, it starts, you started pragmatically, but how far can you grow? >> Bob is waiting with bated breath to answer this question. I'm, just really quickly, I think that we as a company and DBT as a product tend to be very pragmatic. We try to release the simplest possible version of a thing, get it out there, and see if people use it. But the idea that, the concept of a metric is really just a first landing pad. The really, there is a physical manifestation of the data and then there's a logical manifestation of the data. And what we're trying to do here is make it very easy to access the logical manifestation of the data, and metric is a way to look at that. Maybe an entity, a customer, a user is another way to look at that. And I'm sure that there will be more kind of logical structures as well. >> So, Bob, chime in on this. You know, what's your thoughts on the right architecture behind this, and how do we get there? >> Yeah, well first of all, I think one of the ways we get there is by what companies like DBT Labs and Tristan is doing, which is incrementally taking and building on the modern data stack and extending that to add a semantic layer that describes the data. Now the way I tend to think about this is a fairly major shift in the way we think about writing applications, which is today a code first approach to moving to a world that is model driven. And I think that's what the big change will be is that where today we think about data, we think about writing code, and we use that to produce APIs as Tristan said, which encapsulates those things together in some form of services that are useful for organizations. And that idea of that encapsulation is never going to go away. It's very, that concept of an API is incredibly useful and will exist well into the future. But what I think will happen is that in the next 10 years, we're going to move to a world where organizations are defining models first of their data, but then ultimately of their business process, their entire business process. Now the concept of a model driven world is a very old concept. I mean, I first started thinking about this and playing around with some early model driven tools, probably before Tristan was born in the early 1980s. And those tools didn't work because the semantics associated with executing the model were too complex to be written in anything other than a procedural language. We're now reaching a time where that is changing, and you see it everywhere. You see it first of all in the world of machine learning and machine learning models, which are taking over more and more of what applications are doing. And I think that's an incredibly important step. And learned models are an important part of what people will do. But if you look at the world today, I will claim that we've always been modeling. Modeling has existed in computers since there have been integrated circuits and any form of computers. But what we do is what I would call implicit modeling, which means that it's the model is written on a whiteboard. It's in a bunch of Slack messages. It's on a set of napkins in conversations that happen and during Zoom. That's where the model gets defined today. It's implicit. There is one in the system. It is hard coded inside application logic that exists across many applications with humans being the glue that connects those models together. And really there is no central place you can go to understand the full attributes of the business, all of the business rules, all of the business logic, the business data. That's going to change in the next 10 years. And we'll start to have a world where we can define models about what we're doing. Now in the short run, the most important models to build are data models and to describe all of the attributes of the data and their relationships. And that's work that DBT Labs is doing. A number of other companies are doing that. We're taking steps along that way with catalogs. People are trying to build more complete ontologies associated with that. The underlying infrastructure is still super, super nascent. But what I think we'll see is this infrastructure that exists today that's building learned models in the form of machine learning programs. You know, some of these incredible machine learning programs in foundation models like GPT and DALL-E and all of the things that are happening in these global scale models, but also all of that needs to get applied to the domains that are appropriate for a business. And I think we'll see the infrastructure developing for that, that can take this concept of learned models and put it together with more explicitly defined models. And this is where the concept of knowledge graphs come in and then the technology that underlies that to actually implement and execute that, which I believe are relational knowledge graphs. >> Oh, oh wow. There's a lot to unpack there. So let me ask the Colombo question, Tristan, we've been making fun of your youth. We're just, we're just jealous. Colombo, I'll explain it offline maybe. >> I watch Colombo. >> Okay. All right, good. So but today if you think about the application stack and the data stack, which is largely an analytics pipeline. They're separate. Do they, those worlds, do they have to come together in order to achieve Bob's vision? When I talk to practitioners about that, they're like, well, I don't want to complexify the application stack cause the data stack today is so, you know, hard to manage. But but do those worlds have to come together? And you know, through that model, I guess abstraction or translation that Bob was just describing, how do you guys think about that? Who wants to take that? >> I think it's inevitable that data and AI are going to become closer together? I think that the infrastructure there has been moving in that direction for a long time. Whether you want to use the Lakehouse portmanteau or not. There's also, there's a next generation of data tech that is still in the like early stage of being developed. There's a company that I love that is essentially Cross Cloud Lambda, and it's just a wonderful abstraction for computing. So I think that, you know, people have been predicting that these worlds are going to come together for awhile. A16Z wrote a great post on this back in I think 2020, predicting this, and I've been predicting this since since 2020. But what's not clear is the timeline, but I think that this is still just as inevitable as it's been. >> Who's that that does Cross Cloud? >> Let me follow up on. >> Who's that, Tristan, that does Cross Cloud Lambda? Can you name names? >> Oh, they're called Modal Labs. >> Modal Labs, yeah, of course. All right, go ahead, George. >> Let me ask about this vision of trying to put the semantics or the code that represents the business with the data. It gets us to a world that's sort of more data centric, where data's not locked inside or behind the APIs of different applications so that we don't have silos. But at the same time, Bob, I've heard you talk about building the semantics gradually on top of, into a knowledge graph that maybe grows out of a data catalog. And the vision of getting to that point, essentially the enterprise's metadata and then the semantics you're going to add onto it are really stored in something that's separate from the underlying operational and analytic data. So at the same time then why couldn't we gradually build semantics beyond the metric definitions that DBT has today? In other words, you build more and more of the semantics in some layer that DBT defines and that sits above the data management layer, but any requests for data have to go through the DBT layer. Is that a workable alternative? Or where, what type of limitations would you face? >> Well, I think that it is the way the world will evolve is to start with the modern data stack and, you know, which is operational applications going through a data pipeline into some form of data lake, data warehouse, the Lakehouse, whatever you want to call it. And then, you know, this wide variety of analytics services that are built together. To the point that Tristan made about machine learning and data coming together, you see that in every major data cloud provider. Snowflake certainly now supports Python and Java. Databricks is of course building their data warehouse. Certainly Google, Microsoft and Amazon are doing very, very similar things in terms of building complete solutions that bring together an analytics stack that typically supports languages like Python together with the data stack and the data warehouse. I mean, all of those things are going to evolve, and they're not going to go away because that infrastructure is relatively new. It's just being deployed by companies, and it solves the problem of working with petabytes of data if you need to work with petabytes of data, and nothing will do that for a long time. What's missing is a layer that understands and can model the semantics of all of this. And if you need to, if you want to model all, if you want to talk about all the semantics of even data, you need to think about all of the relationships. You need to think about how these things connect together. And unfortunately, there really is no platform today. None of our existing platforms are ultimately sufficient for this. It was interesting, I was just talking to a customer yesterday, you know, a large financial organization that is building out these semantic layers. They're further along than many companies are. And you know, I asked what they're building it on, and you know, it's not surprising they're using a, they're using combinations of some form of search together with, you know, textual based search together with a document oriented database. In this case it was Cosmos. And that really is kind of the state of the art right now. And yet those products were not built for this. They don't really, they can't manage the complicated relationships that are required. They can't issue the queries that are required. And so a new generation of database needs to be developed. And fortunately, you know, that is happening. The world is developing a new set of relational algorithms that will be able to work with hundreds of different relations. If you look at a SQL database like Snowflake or a big query, you know, you get tens of different joins coming together, and that query is going to take a really long time. Well, fortunately, technology is evolving, and it's possible with new join algorithms, worst case, optimal join algorithms they're called, where you can join hundreds of different relations together and run semantic queries that you simply couldn't run. Now that technology is nascent, but it's really important, and I think that will be a requirement to have this semantically reach its full potential. In the meantime, Tristan can do a lot of great things by building up on what he's got today and solve some problems that are very real. But in the long run I think we'll see a new set of databases to support these models. >> So Tristan, you got to respond to that, right? You got to, so take the example of Snowflake. We know it doesn't deal well with complex joins, but they're, they've got big aspirations. They're building an ecosystem to really solve some of these problems. Tristan, you guys are part of that ecosystem, and others, but please, your thoughts on what Bob just shared. >> Bob, I'm curious if, I would have no idea what you were talking about except that you introduced me to somebody who gave me a demo of a thing and do you not want to go there right now? >> No, I can talk about it. I mean, we can talk about it. Look, the company I've been working with is Relational AI, and they're doing this work to actually first of all work across the industry with academics and research, you know, across many, many different, over 20 different research institutions across the world to develop this new set of algorithms. They're all fully published, just like SQL, the underlying algorithms that are used by SQL databases are. If you look today, every single SQL database uses a similar set of relational algorithms underneath that. And those algorithms actually go back to system R and what IBM developed in the 1970s. We're just, there's an opportunity for us to build something new that allows you to take, for example, instead of taking data and grouping it together in tables, treat all data as individual relations, you know, a key and a set of values and then be able to perform purely relational operations on it. If you go back to what, to Codd, and what he wrote, he defined two things. He defined a relational calculus and relational algebra. And essentially SQL is a query language that is translated by the query processor into relational algebra. But however, the calculus of SQL is not even close to the full semantics of the relational mathematics. And it's possible to have systems that can do everything and that can store all of the attributes of the data model or ultimately the business model in a form that is much more natural to work with. >> So here's like my short answer to this. I think that we're dealing in different time scales. I think that there is actually a tremendous amount of work to do in the semantic layer using the kind of technology that we have on the ground today. And I think that there's, I don't know, let's say five years of like really solid work that there is to do for the entire industry, if not more. But the wonderful thing about DBT is that it's independent of what the compute substrate is beneath it. And so if we develop new platforms, new capabilities to describe semantic models in more fine grain detail, more procedural, then we're going to support that too. And so I'm excited about all of it. >> Yeah, so interpreting that short answer, you're basically saying, cause Bob was just kind of pointing to you as incremental, but you're saying, yeah, okay, we're applying it for incremental use cases today, but we can accommodate a much broader set of examples in the future. Is that correct, Tristan? >> I think you're using the word incremental as if it's not good, but I think that incremental is great. We have always been about applying incremental improvement on top of what exists today, but allowing practitioners to like use different workflows to actually make use of that technology. So yeah, yeah, we are a very incremental company. We're going to continue being that way. >> Well, I think Bob was using incremental as a pejorative. I mean, I, but to your point, a lot. >> No, I don't think so. I want to stop that. No, I don't think it's pejorative at all. I think incremental, incremental is usually the most successful path. >> Yes, of course. >> In my experience. >> We agree, we agree on that. >> Having tried many, many moonshot things in my Microsoft days, I can tell you that being incremental is a good thing. And I'm a very big believer that that's the way the world's going to go. I just think that there is a need for us to build something new and that ultimately that will be the solution. Now you can argue whether it's two years, three years, five years, or 10 years, but I'd be shocked if it didn't happen in 10 years. >> Yeah, so we all agree that incremental is less disruptive. Boom, but Tristan, you're, I think I'm inferring that you believe you have the architecture to accommodate Bob's vision, and then Bob, and I'm inferring from Bob's comments that maybe you don't think that's the case, but please. >> No, no, no. I think that, so Bob, let me put words into your mouth and you tell me if you disagree, DBT is completely useless in a world where a large scale cloud data warehouse doesn't exist. We were not able to bring the power of Python to our users until these platforms started supporting Python. Like DBT is a layer on top of large scale computing platforms. And to the extent that those platforms extend their functionality to bring more capabilities, we will also service those capabilities. >> Let me try and bridge the two. >> Yeah, yeah, so Bob, Bob, Bob, do you concur with what Tristan just said? >> Absolutely, I mean there's nothing to argue with in what Tristan just said. >> I wanted. >> And it's what he's doing. It'll continue to, I believe he'll continue to do it, and I think it's a very good thing for the industry. You know, I'm just simply saying that on top of that, I would like to provide Tristan and all of those who are following similar paths to him with a new type of database that can actually solve these problems in a much more architected way. And when I talk about Cosmos with something like Mongo or Cosmos together with Elastic, you're using Elastic as the join engine, okay. That's the purpose of it. It becomes a poor man's join engine. And I kind of go, I know there's a better answer than that. I know there is, but that's kind of where we are state of the art right now. >> George, we got to wrap it. So give us the last word here. Go ahead, George. >> Okay, I just, I think there's a way to tie together what Tristan and Bob are both talking about, and I want them to validate it, which is for five years we're going to be adding or some number of years more and more semantics to the operational and analytic data that we have, starting with metric definitions. My question is for Bob, as DBT accumulates more and more of those semantics for different enterprises, can that layer not run on top of a relational knowledge graph? And what would we lose by not having, by having the knowledge graph store sort of the joins, all the complex relationships among the data, but having the semantics in the DBT layer? >> Well, I think this, okay, I think first of all that DBT will be an environment where many of these semantics are defined. The question we're asking is how are they stored and how are they processed? And what I predict will happen is that over time, as companies like DBT begin to build more and more richness into their semantic layer, they will begin to experience challenges that customers want to run queries, they want to ask questions, they want to use this for things where the underlying infrastructure becomes an obstacle. I mean, this has happened in always in the history, right? I mean, you see major advances in computer science when the data model changes. And I think we're on the verge of a very significant change in the way data is stored and structured, or at least metadata is stored and structured. Again, I'm not saying that anytime in the next 10 years, SQL is going to go away. In fact, more SQL will be written in the future than has been written in the past. And those platforms will mature to become the engines, the slicer dicers of data. I mean that's what they are today. They're incredibly powerful at working with large amounts of data, and that infrastructure is maturing very rapidly. What is not maturing is the infrastructure to handle all of the metadata and the semantics that that requires. And that's where I say knowledge graphs are what I believe will be the solution to that. >> But Tristan, bring us home here. It sounds like, let me put pause at this, is that whatever happens in the future, we're going to leverage the vast system that has become cloud that we're talking about a supercloud, sort of where data lives irrespective of physical location. We're going to have to tap that data. It's not necessarily going to be in one place, but give us your final thoughts, please. >> 100% agree. I think that the data is going to live everywhere. It is the responsibility for both the metadata systems and the data processing engines themselves to make sure that we can join data across cloud providers, that we can join data across different physical regions and that we as practitioners are going to kind of start forgetting about details like that. And we're going to start thinking more about how we want to arrange our teams, how does the tooling that we use support our team structures? And that's when data mesh I think really starts to get very, very critical as a concept. >> Guys, great conversation. It was really awesome to have you. I can't thank you enough for spending time with us. Really appreciate it. >> Thanks a lot. >> All right. This is Dave Vellante for George Gilbert, John Furrier, and the entire Cube community. Keep it right there for more content. You're watching SuperCloud2. (upbeat music)

(lively music) >> Good afternoon cloud community and welcome back to beautiful Las Vegas, Nevada. We are here at AWS re:Invent, day four of our wall to wall coverage. It is day four in the afternoon and we are holding strong. I'm Savannah Peterson, joined by my fabulous co-host Paul Gillen. Paul, how you doing? >> I'm doing well, fine Savannah. You? >> You look great. >> We're in the home stretch here. >> Yeah, (laughs) we are. >> You still look fresh as a daisy. I don't know how you do it. >> (laughs) You're too kind. You're too kind, but I'm vain enough to take that compliment. I'm very excited about the conversation that we're going to have up next. We get to get a little DevRel and we got a little swagger on the stage. Welcome, Austin. How you doing? >> Hey, great to be here. Thanks for having me. >> Savannah: Yeah, it's our pleasure. How's the show been for you so far? >> Busy, exciting. Feels a lot like, you know it used to be right? >> Yeah, I know. A little reminiscent of the before times. >> Well, before times. >> Before we dig into the technical stuff, you're the most intriguingly dressed person we've had on the show this week. >> Austin: I feel extremely underdressed. >> Well, and we were talking about developer fancy. Talk to me a little bit about your approach to fashion. Wasn't expecting to lead with this, but I like this but I like this actually. >> No, it's actually good with my PR. You're going to love it. My approach, here's the thing, I give free advice all the time about developer relations, about things that work, have worked, and don't work in community and all that stuff. I love talking about that. Someone came up to me and said, "Where do you get your fashion tips from? What's the secret Discord server that I need to go on?" I'm like, "I will never tell." >> Oh, okay. >> This is an actual trait secret. >> Top secret. Wow! Talk about. >> If someone else starts wearing the hat, then everyone's going to be like, "There's so many white guys." Look, I'm a white guy with a beard that works in technology. >> Savannah: I've never met one of those. >> Exactly, there's none of them at all. So, you have to do something to kind stand out from the crowd a little bit. >> I love it, and it's a talk trigger. We're talking about it now. Production team loved it. It's fantastic. >> It's great. >> So your DevRel for Lightstep, in case the audience isn't familiar tell us about Lightstep. >> So Lightstep is a cloud native observability platform built at planet scale, and it powers observability at some places you've heard of like Spotify, GitHub, right? We're designed to really help developers that are working in the cloud with Kubernetes, with these huge distributed systems, understand application performance and being able to find problems, fix problems. We're also part of the ServiceNow family and as we all know ServiceNow is on a mission to help the world of work work better by powering digital transformation around IT and customer experiences for their many, many, many global 2000 customers. We love them very much. >> You know, it's a big love fest here. A lot of people have talked about the collaboration, so many companies working together. You mentioned unified observability. What is unified observability? >> So if you think about a tradition, or if you've heard about this traditional idea of observability where you have three pillars, right? You have metrics, and you have logs, and you have traces. All those three things are different data sources. They're picked up by different tools. They're analyzed by different people for different purposes. What we believe and what we're working to accomplish right now is to take all that and if you think those pillars, flip 'em on their side and think of them as streams of data. If we can take those streams and integrate them together and let you treat traces and metrics and logs not as these kind of inviolate experiences where you're kind of paging between things and going between tab A to tab B to tab C, and give you a standard way to query this, a standard way to display this, and letting you kind of find the most relevant data, then it really unlocks a lot of power for like developers and SREs to spend less time like managing tools. You know, figuring out where to build their query or what dashboard to check, more just being able to like kind of ask a question, get an answer. When you have an incident or an outage that's the most important thing, right? How quickly can you get those answers that you need so that you can restore system health? >> You don't want to be looking in multiple spots to figure out what's going on. >> Absolutely. I mean, some people hear unified observability and they go to like tool consolidation, right? That's something I hear from a lot of our users and a lot of people in re:Invent. I'll talk to SREs, they're like, "Yeah, we've got like six or seven different metrics products alone, just on services that they cover." It is important to kind of consolidate that but we're really taking it a step lower. We're looking at the data layer and trying to say, "Okay, if the data is all consistent and vendor neutral then that gives you flexibility not only from a tool consolidation perspective but also you know, a consistency, reliability. You could have a single way to deploy your observability out regardless of what cloud you're on, regardless if you're using Kubernetes or Fargate or whatever else. or even just Bare Metal or EC2 Bare Metal, right? There's been so much historically in this space. There's been a lot of silos and we think that unify diversability means that we kind of break down those silos, right? The way that we're doing it primarily is through a project called OpenTelemetry which you might have heard of. You want to talk about that in a minute? . >> Savannah: Yeah, let's talk about it right now. Why don't you tell us about it? Keep going, you're great. You're on a roll. >> I am. >> Savannah: We'll just hang out over here. >> It's day four. I'm going to ask the questions and answer the questions. (Savannah laughs) >> Yes, you're right. >> I do yeah. >> Open Tele- >> OpenTelemetry . >> Explain what OpenTelemetry is first. >> OpenTelemetry is a CNCF project, Cloud Native Computing Foundation. The goal is to make telemetry data, high quality telemetry data, a builtin feature of cloud native software right? So right now if you wanted to get logging data out, depending on your application stack, depending on your application run time, depending on language, depending on your deployment environment. You might have a lot... You have to make a lot of choices, right? About like, what am I going to use? >> Savannah: So many different choices, and the players are changing all the time. >> Exactly, and a lot of times what people will do is they'll go and they'll say like, "We have to use this commercial solution because they have a proprietary agent that can do a lot of this for us." You know? And if you look at all those proprietary agents, what you find very quickly is it's very commodified right? There's no real difference in what they're doing at a code level and what's stopped the industry from really adopting a standard way to create this logs and metrics and traces, is simply just the fact that there was no standard. And so, OpenTelemetry is that standard, right? We've got dozens of companies many of them like very, many of them here right? Competitors all the same, working together to build this open standard and implementation of telemetry data for cloud native software and really any software right? Like we support over 12 languages. We support Kubernetes, Amazon. AWS is a huge contributor actually and we're doing some really exciting stuff with them on their Amazon distribution of OpenTelemetry. So it's been extremely interesting to see it over the past like couple years go from like, "Hey, here's this like new thing that we're doing over here," to really it's a generalized acceptance that this is the way of the future. This is what we should have been doing all along. >> Yeah. >> My opinion is there is a perception out there that observability is kind of a commodity now that all the players have the same set of tools, same set of 15 or 17 or whatever tools, and that there's very little distinction in functionality. Would you agree with that? >> I don't know if I would characterize it that way entirely. I do think that there's a lot of duplicated effort that happens and part of the reason is because of this telemetry data problem, right? Because you have to wind up... You know, there's this idea of table stakes monitoring that we talk about right? Table stakes monitoring is the stuff that you're having to do every single day to kind of make sure your system is healthy to be able to... When there's an alert, gets triggered, to see why it got triggered and to go fix it, right? Because everyone has the kind of work on that table stake stuff and then build all these integrations, there's very little time for innovation on top of that right? Because you're spending all your time just like working on keeping up with technology. >> Savannah: Doing the boring stuff to make sure the wheels don't fall off, basically. >> Austin: Right? What I think the real advantage of OpenTelemetry is that it really, from like a vendor perspective, like it unblocks us from having to kind of do all this repetitive commodified work. It lets us help move that out to the community level so that... Instead of having to kind of build, your Kubernetes integration for example, you can just have like, "Hey, OpenTelemetry is integrated into Kubernetes and you just have this data now." If you are a commercial product, or if you're even someone that's interested in fixing a, scratching a particular itch about observability. It's like, "I have this specific way that I'm doing Kubernetes and I need something to help me really analyze that data. Well, I've got the data now I can just go create a project. I can create an analysis tool." I think that's what you'll see over time as OpenTelemetry promulgates out into the ecosystem is more people building interesting analysis features, people using things like machine learning to analyze this large amount, large and consistent amount of OpenTelemetry data. It's going to be a big shakeup I think, but it has the potential to really unlock a lot of value for our customers. >> Well, so you're, you're a developer relations guy. What are developers asking for right now out of their observability platforms? >> Austin: That's a great question. I think there's two things. The first is that they want it to just work. It's actually the biggest thing, right? There's so many kind of... This goes back to the tool proliferation, right? People have too much data in too many different places, and getting that data out can still be really challenging. And so, the biggest thing they want is just like, "I want something that I can... I want a lot of these questions I have to ask, answered already and OpenTelemetry is going towards it." Keep in mind it's the project's only three years old, so we obviously have room to grow but there are people running it in production and it works really well for them but there's more that we can do. The second thing is, and this isn't what really is interesting to me, is it's less what they're asking for and more what they're not asking for. Because a lot of the stuff that you see people, saying around, "Oh, we need this like very specific sort of lower level telemetry data, or we need this kind of universal thing." People really just want to be able to get questions or get questions answered, right? They want tools that kind of have these workflows where you don't have to be an expert because a lot of times this tooling gets locked behind sort of is gate kept almost in a organization where there are teams that's like, "We're responsible for this and we're going to set it up and manage it for you, and we won't let you do things outside of it because that would mess up- >> Savannah: Here's your sandbox and- >> Right, this is your sandbox you can play in and a lot of times that's really useful and very tuned for the problems that you saw yesterday, but people are looking at like what are the problems I'm going to get tomorrow? We're deploying more rapidly. We have more and more intentional change happening in the system. Like it's not enough to have this reactive sort of approach where our SRE teams are kind of like or this observability team is building a platform for us. Developers want to be able to get in and have these kind of guided workflows really that say like, "Hey, here's where you're starting at. Let's get you to an answer. Let's help you find the needle in the haystack as it were, without you having to become a master of six different or seven different tools." >> Savannah: Right, and it shouldn't be that complicated. >> It shouldn't be. I mean we've certainly... We've been working on this problem for many years now, starting with a lot of our team that started at Google and helped build Google's planet scale monitoring systems. So we have a lot of experience in the field. It's actually one... An interesting story that our founder or now general manager tells BHS, Ben Sigelman, and he told me this story once and it's like... He had built this really cool thing called Dapper that was a tracing system at Google, and people weren't using it. Because they were like, "This is really cool, but I don't know how to... but it's not relevant to me." And he's like, the one thing that we did to get to increase usage 20 times over was we just put a link. So we went to the place that people were already looking for that data and we added a link that says, "Hey, go over here and look at this." It's those simple connections being able to kind of draw people from like point A to point B, take them from familiar workflows into unfamiliar ones. You know, that's how we think about these problems right? How is this becoming a daily part of someone's usage? How is this helping them solve problems faster and really improve their their life? >> Savannah: Yeah, exactly. It comes down to quality of life. >> Warner made the case this morning that computer architecture should be inherently event-driven and that we are moving toward a world where the person matters less than what the software does, right? The software is triggering events. Does this complicate observability or simplify it? >> Austin: I think that at the end of the day, it's about getting the... Observability to me in a lot of ways is about modeling your system, right? It's about you as a developer being able to say this is what I expect the system to do and I don't think the actual application architecture really matters that much, right? Because it's about you. You are building a system, right? It can be event driven, can be support request response, can be whatever it is. You have to be able to say, "This is what I expect to... For these given inputs, this is the expected output." Now maybe there's a lot of stuff that happens in the middle that you don't really care about. And then, I talk to people here and everyone's talking about serverless right? Everyone... You can see there's obviously some amazing statistics about how many people are using Lambda, and it's very exciting. There's a lot of stuff that you shouldn't have to care about as a developer, but you should care about those inputs and outputs. You will need to have that kind of intermediate information and understand like, what was the exact path that I took through this invented system? What was the actual resources that were being used? Because even if you trust that all this magic behind the scenes is just going to work forever, sometimes it's still really useful to have that sort of lower level abstraction, to say like, "Well, this is what actually happened so that I can figure out when I deployed a new change, did I make performance better or worse?" Or being able to kind of segregate your data out and say like... Doing AB testing, right? Doing canary releases, doing all of these things that you hear about as best practices or well architected applications. Observability is at the core of all that. You need observability to kind of do any of, ask any of those higher level interesting questions. >> Savannah: We are here at ReInvent. Tell us a little bit more about the partnership with AWS. >> So I would have to actually probably refer you to someone at Service Now on that. I know that we are a partner. We collaborate with them on various things. But really at Lightstep, we're very focused on kind of the open source part of this. So we work with AWS through the OpenTelemetry project, on things like the AWS distribution for OpenTelemetry which is really... It's OpenTelemetry, again is really designed to be like a neutral standard but we know that there are going to be integrators and implementers that need to package up and bundle it in a certain way to make it easy for their end users to consume it. So that's what Amazon has done with ADOT which is the shortening for it. So it's available in several different ways. You can use it as like an SDK and drop it into your application. There's Lambda layers. If you want to get Lambda observability, you just add this extension in and then suddenly you're getting OpenTelemetry data on the other side. So it's really cool. It's been a really exciting to kind of work with people on the AWS side over the past several years. >> Savannah: It's exciting, >> I've personally seen just a lot of change. I was talking to a PM earlier this week... It's like, "Hey, two years ago I came and talked to you about OpenTelemetry and here we are today. You're still talking about OpenTelemetry." And they're like, "What changes?" Our customers have started coming to us asking for OpenTelemetry and we see the same thing now. >> Savannah: Timing is right. >> Timing is right, but we see the same thing... Even talking to ServiceNow customers who are... These very big enterprises, banks, finance, healthcare, whatever, telcos, it used to be... You'd have to go to them and say like, "Let me tell you about distributed tracing. Let me tell you about OpenTelemetry. Let me tell you about observability." Now they're coming in and saying, "Yeah, so we're standard." If you think about Kubernetes and how Kubernetes, a lot of enterprises have spent the past five-six years standardizing, and Kubernetes is a way to deploy applications or manage containerized applications. They're doing the same journey now with OpenTelemetry where they're saying, "This is what we're betting on and we want partners we want people to help us go along that way." >> I love it, and they work hand in hand in all CNCF projects as well that you're talking about. >> Austin: Right, so we're integrated into Kubernetes. You can find OpenTelemetry and things like kept in which is application standards. And over time, it'll just like promulgate out from there. So it's really exciting times. >> A bunch of CNCF projects in this area right? Prometheus. >> Prometheus, yeah. Yeah, so we inter-operate with Prometheus as well. So if you have Prometheus metrics, then OpenTelemetry can read those. It's a... OpenTelemetry metrics are like a super set of Prometheus. We've been working with the Prometheus community for quite a while to make sure that there's really good compatibility because so many people use Prometheus you know? >> Yeah. All right, so last question. New tradition for us here on theCUBE. We're looking for your 32nd hot take, Instagram reel, biggest theme, biggest buzz for those not here on the show floor. >> Oh gosh. >> Savannah: It could be for you too. It could be whatever for... >> I think the two things that are really striking to me is one serverless. Like I see... I thought people were talking about servers a lot and they were talking about it more than ever. Two, I really think it is observability right? Like we've gone from observability being kind of a niche. >> Savannah: Not that you're biased. >> Huh? >> Savannah: Not that you're biased. >> Not that I'm biased. It used to be a niche. I'd have to go niche thing where I would go and explain what this is to people and nowpeople are coming up. It's like, "Yeah, yeah, we're using OpenTelemetry." It's very cool. I've been involved with OpenTelemetry since the jump, since it was started really. It's been very exciting to see and gratifying to see like how much adoption we've gotten even in a short amount of time. >> Yeah, absolutely. It's a pretty... Yeah, it's been a lot. That was great. Perfect soundbite for us. >> Austin: Thanks, I love soundbites. >> Savannah: Yeah. Awesome. We love your hat and your soundbites equally. Thank you so much for being on the show with us today. >> Thank you for having me. >> Savannah: Hey, anytime, anytime. Will we see you in Amsterdam, speaking of KubeCon? Awesome, we'll be there. >> There's some real exciting OpenTelemetry stuff coming up for KubeCon. >> Well, we'll have to get you back on theCUBE. (talking simultaneously) Love that for us. Thank you all for tuning in two hour wall to wall coverage here, day four at AWS re:Invent in fabulous Las Vegas, Nevada, with Paul Gillin. I'm Savannah Peterson and you're watching theCUBE, the leader in high tech coverage. (lively music)

(upbeat music) >> Hello, brilliant cloud community, and welcome back to AWS re:Invent. We are here in Las Vegas, Nevada. I'm Savannah Peterson, joined by my co-host Dave Vellante. Dave, how you doing? >> I'm doing well, thanks, yeah. >> Yeah, I feel like... >> I'm hanging in there. >> you've got a lot of pep in your step today for the fourth day. >> I think my voice is coming back, actually. >> (laughs) Look at you, resilient. >> I was almost lost yesterday, yeah. >> Yeah. (laughs) >> So, I actually, at a Hitachi event one time almost completely lost my voice. The production guys pulled me off. They said, "You're done." (Savannah laughing) They gave me the hook. >> You got booted? >> Dave: Yeah, yeah. >> Yeah, yeah, you actually (laughs) got the hook, wow. >> So, I have good memories of Hitachi. >> I was going to say (Dave laughing) interesting that you mentioned Hitachi. Our two guests this morning are from Hitachi. Sid and KP, welcome to the show. >> Thank you. >> Savannah: How you guys doing? Looking great for day four. >> Great. Thank you. >> Great. >> Hanging in there. >> Thank you, Dave and Savannah. (Savannah laughing) >> Dave: Yeah, cool. >> Savannah: Yeah. (laughs) >> Yeah, it was actually a Pentaho thing, right? >> Oh, Pentaho? Yeah. >> Which kind of you guys into that software edge. It was right when you announced the name change to Hitachi Vantara, which is very cool. I had Brian Householder on. You remember Brian? >> Yeah, I know. >> He was explaining the vision, and yeah (indistinct). >> Yeah. Well, look at you a little Hitachi (indistinct). >> Yeah, I've been around a long time, yeah. >> Yeah, all right. (Dave laughing) >> Just a casual flex to start us off there, Dave. I love it. I love it. Sid, we've talked a lot on the show about delivering outcomes. It's a hot theme. Everyone wants to actually have tangible business outcomes from all of this. How are customers realizing value from the cloud? What does that mean? >> See, still 2007, 2008, it was either/or kind of architecture. Either I'm going to execute my use cases on cloud or I'm going to keep my use cases and outcomes through edge. But in the last four or five years and specifically we are in re:Invent, I would talk about AWS. Lot of the power of hyperscalers has been brought to edge. If you talk about the snowball family of AWS, if you talk about monitor on edge devices, if you talk about the entire server list being brought into Lambda coupled inside snowball, now the architecture premise, if I talk about logical shift is end. Now the customers are talking about executing the use cases between edge and cloud. So, there is a continuum rather than a binary bullion decision. So, if you are talking about optimizing a factory, earlier I'll do the analytics at cloud, and I'll do machine on edge. Now it is optimization of a factory outcome at scale across my entire manufacturing where edge, private cloud, AWS, hyperscalers, everything is a continuum. And the customer is not worried about where, which part of my data ops, network ops, server ops storage ops is being executed. >> Savannah: It's like (indistinct). >> The customer is enjoying the use cases. And the orchestration is abstracted through an industrial player like Hitachi working very collaboratively with AWS. So, that is how we are working on industrial use cases right now. >> You brought up manufacturing. I don't think there's been a hotter conversation around supply chain and manufacturing than there has been the last few years. I can imagine taking that guessing game out for customers is a huge deal for you guys. >> Big because if you look at the world today, right from a safety pin, to a cell phone jacket, to a cell phone, the entire supply chain is throttled. The supply chain is throttled because there are various choke points. >> Savannah: Yeah. >> And each choke points is surrounded by different kind of supply and geopolitical issues. >> Savannah: 100%. >> Now, if we talk about the wheat crisis happening because of the Ukraine-Russia war, but the wheat crisis actually creates a multiple string of impacts which impact everything. Silicon, now we talk about silicon, but we then forget about nickel. Nickel is also controlled in one part of that geopolitical conflict. So, everything is getting conflagrated into a very big supply issue. So, if your factories are not performing beyond optimum, if they are not performing at real, I'm, we are talking about factory, hyperscale of the factory. The factory needs to perform at hyperscale to provide what the world needs today. So, we are in a very different kind of a scenario. Some of the economists call it earlier the recession was because of a demand constraint. The demand used to go down. Today's recession is because the supply is going down. The demand is there, but the supply is going down. And there is a different kind of recession in the world. The supply is what is getting throttled. >> And the demand is somewhat unpredictable too. People, you know, retailers, they've... >> Especially right now. >> kind of messed up their inventory. And so, the data is still siloed. And that's where, you know, you get to, okay, can I have the same experience across clouds, on-prem, out to the edge? Kind of bust those silos. >> Yep. >> You know, I dunno if it's, it's certainly not entirely a data problem. There's (laughs), like you say, geopolitical and social issues. >> Savannah: There's so much complexity. >> But there's a data problem too. >> Yes. >> Big. >> So, I wonder if you could talk about your sort of view of, point of view on that cross-cloud, hybrid, out to the edge, what I call super cloud? >> Absolutely. So, today, if you look at how enterprises are adopting cloud or how they're leveraging cloud, it's not just a hosting platform, right? It is the platform from where they can draw business capabilities. You heard in the re:Invent that Amazon is coming up with a supply chain service out of the box in the cloud. That's the kind of capabilities that business wants to draw from cloud today. So, the kind of multicloud or like hybrid cloud, public cloud, private cloud, those are the things which are kind of going to be behind the scenes. At the end of the day, the cloud needs to be able to support businesses by providing their services closer to their consumers. So, the challenges are going to be there in terms of like reliability, resilience, cost, security. Those are the ones that, you know, many of the enterprises are grappling with in terms of the challenges. And the way to solve that, the way how we approach our customers and work with them is to be able to bring resilience into the cloud, into the services which are running in cloud, and by driving automation, making autonomous in everything that you do, how you are monitoring your services, how we are making it available, how we are securing it, how we are making it very cost-effective as well. It cannot be manually executed; it has to be automated. So, automation is the key in terms of making the services leveraged from all of this cloud. >> That's your value add. >> Absolutely. >> And how do I consume that value add? Is it sort of embedded into infrastructure? Is it a service layer on top? >> Yeah, so everything that we do today in terms of like how these services have to be provided, how the services have to be consumed, there has to be a modern operating model, right? I think this is where Hitachi has come up with what we are calling as Hitachi Application Reliability Center and Services. That is focusing on modern operating, modern ways of like, you know, how you support these cloud workloads and driving this automation. So, whether we provide a hyper-converged infrastructure that is going to be at the edge location, or we are going to be able to take a customer through the journey of modernization or migrating onto cloud, the operating model that is going to be able to establish the foundation on cloud and then to be able to operate with the right levels of reliability, security, cost is the key. And that's the value added service that we provide. And then the way we do that is essentially by looking at three principles: one, to look at the service in totality. Gone are the days you look at infrastructure separately, applications separately, data and security separately, right? >> Savannah: No more silos. >> No more silos. You look at it as a workload, and you look at it as a service. And number two is to make sure that the DevOps that you bring and what you do at the table is totally integrated and it's end to end. It's not a product team developing a feature and then ops team trying to keep the lights on. It has to be a common backlog with the error budget that looks at you know, product releases, product functionalities, and even what ops needs to do to evolve the product as well. And then the third is to make sure that reliability and resiliency is inbuilt. Cloud offers native durability, native availability. But if your service doesn't take advantage of that, it's kind of going to still be not available. So, how do you kind of ingrain and embed all of these things as a value add that we provide? >> There's a lot of noise. We've got hybrid cloud. We've got multicloud. We've got a lot going on. It adds to the complexity. How do you help customers solve that complexity as they begin their transformation journey? I mean, I'm sure you're working with the biggest companies, making really massive change. How do you guide them through that process? >> So, it is to look at the outcome working backwards, like what AWS does, right? Like, you know, how do you look at the business outcome? What is the value that you're looking to drive? Again, it's not to be pinned through one particular cloud. I know there is lot of technology choices that you can make and lot of deployment models that you can choose from. But at the end of the day, having a common operating model which is kind of like modern, agile, and it is kind of like keeping the outcomes in the mind, that is what we do with our customers to be able to create that operating model, which completes the transformation, by the way. And cloud is just one part of the LEGO blocks which provides that overall scheme and then the view for driving that overall transformation. >> So, let's paint a picture. Let's say you've got this resilient foundation; you've kind of helped the customers build that out. How do they turn that into value for their customers? Do you have any examples that you can share? That'd be great. >> Yeah, I can start with what we're doing for one of the, you know, world's largest facility, infrastructure, power, cooling, security, monitoring company that has their products deployed in 2,000 locations across the globe. For them, and always on business means you are monitoring the temperature. You are monitoring the safety of people who are within the facility, right? A temperature shift of one to two degree can affect even the sustainability goals of NARC, our customer, but also their end consumers. So, how do you monitor these kind of like critical parameters? How do you have a platform? >> Savannah: Great example, yeah. >> How you have cloud resources that are going to be always on, that are going to be reliable, that are going to be cost-effective as well is what we are doing for one of our customers. Sid can talk about another example as well. >> Great. >> Yeah, go for it, Sid. >> So, there are examples: rail. We are working with a group in England; it's called West Coast Partnership. And they had a edge device which was increasing in size. Now, this edge device was becoming big because the parameters which go into the edge device were increasing because of regulation and because the rail is part of national security infrastructure. We have worked with West Coast Partnership and Hitachi Rail, which is a group company, to create a miniaturization of this edge device, because if the size of the edge device is increasing on the train, then the weight of the train increases, and the speed profile, velocity profile, everything goes down. So, we have miniaturized the edge device. Secondly, all the data profiles, signal control, traction control, traction motors, direction control, timetable compliance, everything has been kept uniform. And we have done analytics on cloud. So, what is the behavior of the driver? What is a big breaking parameter of the driver? If the timetable has being missed, is there an erratic behavior being demonstrated by the driver to just meet the timetable? And the timetable is a pretty important criteria in rail because if you miss one, then... So, what we have done is we have created an edge-to-cloud environment where the entire rail analytics is happening. Similarly, in another group company, Hitachi Energy, they had a problem that arguably one of the largest transformer manufacturer in the world. The transformer is a pretty common name now because you're seeing what is happening in Ukraine. Russia went after the transformers and substations before the start of the winter so that their district heating can be meddled with. Now, the transformer, it had a lead time of 17 weeks before COVID. So, if you put me an order of a three-phase transformer, I can deliver it to you in 17 weeks. After and during COVID, the entire lead time increased to 57 to 58 weeks. In cases of a complex transformer, it even went up to something like two years. >> Savannah: Ooh! >> Now, they wanted to increase the productivity of their existing plant because there is only that much sheet metal, that much copper for solenoid, that much microprocessor and silicon. So, they wanted to increase the output of their factory from 95 to 105, 10 more transformers every day, which is 500 and, which is 3,650 every- >> Savannah: Year. >> Year. Now, to do that, we went to a very complex machine; it's called a guard machine. And we increased the productivity of the guard machine by just analyzing all the throttles and all the wastages which are happening there. There are multiple case studies because, see, Hitachi is an industrial giant with 105 years of body of work. KP and I just represent the tip of the digital tip of the arrow. But what we are trying to do through HARC, through industry cloud, through partnership with AWS is basically containerizing and miniaturizing our entire body of work into a democratized environment, an industrial app store, if I may say, where people can come and take their industrial outcomes at ease without worrying about their computational and network orchestration between edge and cloud. That's what we are trying to do. >> I love that analogy of an industrial app cloud. Makes it feel easier in decreasing the complexity of all the different things that everyone's factoring into making their products, whatever they're making. So, we have a new challenge here on theCUBE at AWS re:Invent, where we are looking for your 30-second hot take, your Instagram reel, sound bite. What's the most important story or theme either for you as a team or coming out of the show? You can ponder it for a second. >> It might be different. See, for me, it is industrial security. Industrial OT security should be the theme of the Western world. Western world is on the crosshairs of multiple bad actors. And the industrial security is in the chemical plants, is in the industrial plants, is in the power grids, is in our postal networks and our rail networks. They need to be secured; otherwise, we are geopolitically very weak. Gone are the days when anyone is going to pick up a battle with America or Western world on a field. The battle is going to be pretty clandestine on an cyber world. And that is why industrial security is very important. >> Critical infrastructure and protecting it. >> Absolutely. >> Well said, Sid. KP, what's your hot take? >> My take is going to be a modern operating model, which is going to complete the transformation and to be able to tap into business services from cloud. So, a modern operating model through HARC, that is going to be my take. >> Fantastic. Well, can't wait to see what comes out of Hitachi next. Sid, KP... >> KP: Thank you. >> thank you so much for being here. >> Sid: Thank you. >> Absolutely. >> Dave: Thanks, guys. >> Savannah: This is I could talk to you all about supply chain all day long. And thank all of you for tuning in to our continuous live coverage here from AWS re:Invent in fantastic Sin City. I'm Savannah. Oh, excuse me. With Dave Vellante, I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (digital xylophone music)

(upbeat music) >> Welcome back to theCUBE's live coverage of AWS re:Invent. Friends, it's good to see you. Lisa Martin here with Dave Vellante. This is our fourth day of CUBE wall-to-wall coverage, Dave. I can't believe it. And the expo hall is still going incredibly strong. >> Yeah, it is. It feels like the biggest re:Invent ever. I'm told it's almost as big as 2019. I don't know, maybe I was half asleep at 2019. That's very possible. But I'm excited because in 2017 Andy Jassy came on theCUBE and he said if Amazon had to do it all over again, if it knew then what it had now, we would've done the whole thing in containers or using Lambda, using serverless and using containers. Didn't have that opportunity back then. And I'm excited 'cause Rafay Systems is someone we've worked with a lot as an innovator in this space. >> Yep, and we're going to be talking with Rafay again. I think it's your 10th time Haseeb on the show >> Like once or twice. >> And a great customer who's going to talk about their serverless journey. Haseeb Budhani joins us once again, the CEO of Rafay. Great to see you. Rakesh Singh is here as well, the Head of Cloud and DevOps at Regeneron. Guys, it's great to have you on the program. How you feeling on day four of re:Invent? >> Excitement is as high as ever basically. >> Isn't it amazing? >> Rakesh: That's true. >> Haseeb: I just need some sleep. >> I'm with you on that. Caffeine and sleep. >> So many parties. So many meetings, oh my God. >> But the great thing is, Haseeb, that people want to engage with you. They're loving what Rafay is doing. You guys are a great testament to that, which we're going to uncover on the show. What are some of the things that you're hearing in the booth from customers? What's been some of the feedback? >> So firstly, as I said, it feels like the biggest one ever. I've been coming to re:Invent a long time and I mean, I know the numbers say it's not, but oh my God, this is a lot of people. Every time we've spoken over the last year and the point I always make to you, and we've spoken enough time about this is that enterprises are truly adopting this idea of Kubernetes containers, serverless, et cetera. And they're all trying to figure out what is the enterprise strategy for these things? They're thinking beyond technology and thinking operationalization of these technologies. And that's not the same thing. There's a toy and then there's the real thing. And that's not the same thing. And that's the gap that every enterprise customer I talked to and the booth traffic has been just amazing. I mean, but coming here I was thinking, my God, this is really expensive. And I'm thinking, wow, this is a great investment. Because we met such amazing companies who all essentially are saying exactly the same thing, which is as we go and productize and bring our high value applications to the modern infrastructure space, like Kubernetes, Lambda, et cetera, solving for the automation governance is really, really hard because, well, at one point, I guess when the economy was doing crazy well, I could keep hiring people, but I can't do that anymore either. So they're out looking for automation strategies that allow them to do more with the teams they have. And that's exactly what Rafay is here for. >> Yeah. Lisa, Adam Selipsky in his keynote, I love the, he said, "If you want to save money, the cloud is the place to do it." >> Exactly. Yep. Let's talk about Regeneron. Everyone knows it's a household word especially over the last couple of years, but talk about, Rakesh, Regeneron as a technology company that delivers life-saving pharmaceuticals. And where does cloud and Rafay fit into your strategy? >> So cloud has been a backbone of our compute strategy within Regeneron for a very long time now. The evolution from a traditional compute structure to more serverless compute has been growing at a rapid pace. And I would say like we are seeing exponential growth within the adaption of the compute within containers and Kubernetes world. So we've been on this journey for a long time and I think it's not stopping anytime soon. So we have more and more workload, which is running on Kubernetes containers and we are looking forward to our partnership with Rafay to further enhance it, as Haseeb mentioned, the efficiency is the key. We need to do more with less. Resourcing is critical and cloud is evolved from that journey that do more things in a more efficient manner. >> That was the original catalyst as we got to help our development team, be more productive. >> That's correct. >> Eliminate the heavy lifting. And then you started presumably doing some of the less heavy, but still heavy lifting and we talked off camera and then you're increasingly moving toward serverless. >> Rakesh: That's correct. >> Can you describe that journey? What that's like? >> So I think like with the whole adoption that things are taking a much faster pace. Basically we are putting more compute onto containers and the DevOps journey is increasingly getting more, more faster. >> Go ahead. 'Cause I want to understand where Rafay sits in this whole equation. I was talking about, I'm not a developer, but I was talking to developer yesterday trying to really understand the benefits of containers and serverless and I said, take me through what you have to do when you're using containers. He said, I got to build the container image then I got to deploy an EC2 instance where I got to choose and I got to allocate memory of the fence the app in a VM then I got to run the computing instance against the app. And then, oh by the way, I got to pay 'cause all that EC2 that whole time. Depending on how you approach serverless you're going to eliminate a lot of those steps. >> That is correct. So what we do is basically like in a traditional sense, the computer is sitting idle at quite a lot basically. >> But you're paying. >> And you're still paying for that. Serverless technologies allows us to use the compute as needed basis. So whenever you need it, it is available. You run your workload on that and after that it shuts down or goes to minimal state and you don't need to pay as much as your paying. >> And then where do you guys fit in that whole equation? >> Look, serverless has a paradigm. If you step back from the idea of containers versus Lambda or whatever functions. The idea should be that the list you just read out of what developers have to do. Here's what they really should do. They should write their code, they should check it in, and they never have to think about it again. That should be the case. If they want to debug their application, there should be a nice front end where they go and they interact with their application and that's it. What is Kubernetes? I don't care. That's the right answer. And we did not start this journey as an industry there because usually the initial adopters are developers who do the heavy lifting. Developers want to learn, they want to solve these problems. But then eventually the expectation is that the platform organization and an enterprise is going to own this platform for me so I can go back to doing my job, which is writing code. And that's where Rakesh's team comes in. So Rakesh team is building the standard at Regeneron. Whether you're writing a long-lasting app, which is going to run in a container or you're going to write an event-driven application, which is going to be a function, whatever. You write your app, we will give you the necessary tooling and plumbing to take care of all these things. And this is my problem. My being Rakesh. Rakesh is my customer. He has his customers. We as Rafay, A, we have to make Rakesh's system successful because we have to give them right automation to do all these things so that he can service hundred, or in his case, thousands and thousands of different individuals. But then collectively, we have to make sure that the developer experience is optimal so that truly they just write their code and EC2, they don't want to deal with this. In fact, on Monday evening, in the Kubernetes keynote by Barry Cooks, one of the things he said was that in a CIO sort of survey they did, CIO said, 80% of the time of developers is wasted on infrastructure stuff and not on innovation. We need to bring that 80% back so that a hundred percent of the work is on innovation and today it's not. >> And that's what you do. >> That's what we do. >> In your world as a developer, I only have to worry about my writing my code and what functions I'm going to call. >> That is correct. And it is important because the efficiencies of a developer need to be focused on doing the things which business is asking for. The 80% of the work like to make sure the things are secure, they're done the right way, the standards are followed, scanning part of it, that work if we can offload to a platform, for example, Rafay, saves a lot of works, a lot of work cycles from the developers perspective. >> Thank you for that. It was nice little tutorial on the benefits. >> Absolutely. So you transform the developer experience. >> That's correct. >> How does that impact Regeneron overall business? We uplevel that. Give me that view. >> So with that, like what happens, the key thing is the developers productivity increases. We are able to do more with less. And that is the key thing to our strategy that like with the increase in business demand, with the increase in lot of compute things, which we are doing, we need to do and hiring resources is getting more difficult than ever. And we need to make sure that we are leveraging platforms and tools basically to do, enable our developers to focus on key business activity rather than doing redundant things and things which we can leverage some other tooling and platform for that business. >> Is this something in terms of improving the developer experience and their productivity faster time to market? Is this accelerating? >> That's correct. >> Is this even like accelerating drug discovery in some cases? >> So COVID is like a great example for that. Like we were able to fast track our drug discovery and like we were able to turn it into an experience where we were able to discover new drugs and get it to the market in a much faster pace. That whole process was expedited using these tools and processes basically. So we are very proud of that. >> So my understanding is you're running Rafay with EKS. A lot of choices out there. Why? Why did you choose to go in that direction? >> So Regeneron has heavily invested in cloud recently, over the years basically. And then we are focusing on hybrid cloud now that we we are like, again, these multiple cloud providers of platforms which are coming in are strategies to focus on hybrid cloud and Rafay is big leader in that particular space where we felt that we need to engage or partner with Rafay to enable those capabilities, not just on AWS, but across the board. One single tool, one single process, one single knowledge base helps us achieve more efficiencies. >> Less chaos, less complexity. >> That's correct. Let's say when you're in customer conversations, which I know you've had many this week, but you probably do that all the time. Regeneron is a great use case for Rafay. It's so tangible, life sciences. We all get that, especially coming out of the pandemic. What do you say to customers are the top three differentiators of Rafay and why they should go Rafay on top of EKS? >> What's really interesting about these conversations is that, look, we have some pretty cool features in our product. Obviously we must have something interesting otherwise nobody would buy our product. And we have access management and zero trust models and cluster provisioning, all these very nice things. But it always comes down to exactly the same thing, which is every large enterprise that started a journey, independent or Rafay because they didn't know who we were, it's fine. Last year we were a young company, now we are a larger company and they all are basically building towards a roadmap which Rafay truly understands. And in my opinion, and I'm confident when I say this, we understand their life, their journey better than any other company in the market. The reason why we have the flurry of customers we have, the reason why the product has the capacity that it does is because for whatever reason, look, it's scale lock. That's for the history books. But we have complete clarity on what a pharmaceutical company or financial customers company or a high tech company the journey they will take to the cloud and automation for modern infrastructure, we get it. And what I'm selling them is the is the why, not the what. There's a lot of great answers for the what? What do we do? Rakesh doesn't care. I mean, he's trying to solve a bigger problem. He's trying to get his researchers to go faster. So then when they want to run a model, they should be able to do it right now. That's what he cares about. Then he looks for a tool to solve the business problem. And we figured out how to have that conversation and explain why Rafay helps him, essentially multiply the bandwidth that he has in his organization. And of course to that end we have some great technology/ But that's a secondary issue, the first, to me the why is more important than the what. And then we talk about how, which he has to pay us money. That's the how. But yeah, we get there too. But look, this is the important thing. Every enterprise is on exactly the same journey, Lisa. And that if you think about it from just purely economic efficiencies perspective that is not a good investment for our industry. If everybody's solving the same problem that's a waste of resources. Let's find a way to do, what is the point of the cloud? We used to all build data centers. That was not efficient. We all went to the cloud because it's more efficient to have somebody else, AWS, solve this problem for us so we can now focus on the next level problem. And then Rafay solving that problem so that he can focus on his drug discovery, not on Kubernetes. >> That's correct. It's all about efficiencies. Like doing things, learn from each other's experience and build upon it. So the things have been solved. One way you need to leverage that, reuse it. So the principles are the same. >> So then what's next? You had done an amazing job transforming the company. You're facilitating drug discovery faster than ever before. From an infrastructure perspective, what's next on your journey? >> So right now the roadmap what we have is basically talking about making sure that the workload are running more efficient, they're more secure. As we go into these expandable serverless technology, there are more challenging opportunities for us to solve. Those challenges are coming up. We need to make sure that with the new, the world we are living in, we are more securely doing stuff what we were doing previously. More efficiencies is also the key and more distributed. Like if we can leverage the power of cloud in doing more things on demand is on our roadmap. And I think that is where we are all driving. >> And when you said hybrid, you're talking about connecting to your on-prem tools and data? How about cross cloud? >> We are invested in multiple cloud platform itself and we are looking forward to leveraging a technology, which is truly cloud native and we can leverage things together on that. >> And I presume you're helping with that, obviously. >> Last question for both of you. We're making an Instagram reel. Think of this as a sizzle reel, like a 32nd elevator pitch. Question, first one goes to you, Rakesh. If you had a bumper sticker, you put it on, I don't know, say a DeLorean, I hear those are coming back. What would it say about Regeneron as a technology company that's delivering therapeutics? >> It's a tough question, but I would try my best. The bumper sticker would say, discover drug more faster, more efficient. >> Perfect. Haseeb, question about Rafay. What's the bumper sticker? If you had a billboard in on Highway 101 in Redwood City about Rafay and what it's enabling organizations enterprises across the globe to achieve, what would it say? >> I'll tell you what our customers say. So our customers call us the vCenter for Kubernetes and we all know what a vCenter is. We all know why vCenter's so amazingly successful because it takes IT engineers and gives them superpowers. You can run a data center. What is the vCenter for this new world? It us. So vCenter is obviously a trademark with our friends at VMware, so that's why I'm, but our customers truly call us the vCenter for Kubernetes. And I think that's an incredible moniker because that truly codifies our roadmap. It codifies what we are selling today. >> There's nothing more powerful and potent in the voice of the customer. Thank you both for coming on. Thank you for sharing the Regeneron story. Great to have you back on, Haseeb. You need a pin for the number of times you've been on theCUBE. >> At least a gold star. >> We'll work on that. Guys, thank you. We appreciate your time. >> Haseeb: Thank you very much. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

(techno music) >> Welcome back to the Cube. I'm John Walls. We continue our coverage here at AWS reInvent 22. We're in the Venetian in Las Vegas, wrapping up our day one coverage here in the executive summit sponsored by Accenture and with me to talk about Accenture, couple of guys who are no strangers at all to the Cube. In fact, I think we got to give you like alumni passes or something. (Chris and Merim laugh) We got to come up with something like that. Um, Merim Becirovic is with us. Uh, Merim's a global IT at Accenture. And Chris Wegmann, who's already been on once today, as a matter of fact. >> Yeah (indistinct) >> So we're going to start charging you rent, Chris. (Chris and Merim laugh) Uh, global technology and practice lead with the AWS business group at Accenture. Good, glad to have you both back and, um, you're welcome to the Cube any time, by the way. >> So don't be scared. >> Thanks, great to be back. Let's talk about >> Sure. >> What, what you folks have been up to. So, um, you are, as we were talking earlier, you are where a lot of your clients would like to be. You, you've begun this transformation. You have fully migrated to the cloud, you've learned, right? >> Yes. You've hit all the bumps along the way. So talk about your journey. >> Yeah. >> And then how you think that experience could be translated to what your clients are going through. >> Yeah, so I'll, I'll hit it from the lessons learned and working together with our business group partners. We, so Accenture's journey to the cloud is complete. We have finished that journey, and as part of that journey, we have migrated all of the services it takes to run Accenture to the public cloud. So now that's done. That was complete. But now we are this, now it is this cloud continuum living in the cloud. And the, now, the thing we talk about, and I'd love to have Chris, you know, shine a little bit more, is we have built our digital core in a cloud, now. We're no longer dependent on data centers. And that has given us tremendous flexibility around how to enable the business as it has grown significantly since we started this journey a few years back. >> Yeah, you know, Merim, like you talk about, right? We talk about our client, we've talked to our clients about building this digital core, right? And, and we've been through that as Accenture, as a global IT organization, you know. Supporting well over 720,000 people. >> Yeah. >> Right? That growth over the last year has been tremendous. Right? So, without the strong digital core built on cloud, right? We couldn't do that, right? We couldn't add that number of people, right? We couldn't make the, the, the changes were needed during, uh, Covid to bring people home, working from home. You know, whether it being uh, the way we changed our business model or things like that, um, you know that was all enabled by cloud. It couldn't be done without that. And, you know, also the variable in our business, right? Is very tied now to our cloud consumption, right? So, you know, it goes up, it goes down, right? We've, you know, Merim and his team have completely built their, their their core with those, with those concepts uh, in mind. >> Yeah, I mean, you're talking about, you know, 700, 800,000 employees and how many countries did you say? >> 130 different countries, at least. >> 130 different countries. So, I mean, no small task, obviously, uh, to get everything done. When did you start? >> So our cloud journey, effectively, we started in 2015. And we were done, kind of right before Covid around 2019. We took a pause for a couple of different things but we could have probably done that faster. And if we were, if I was to do it again now, today we could probably do it in two to three years, flat. With everything that we've learned so far. >> So what's the application, then, to your clients' experiences that, I mean, been there, done that, right? >> You can, exactly right. I mean, you know, we always say that we want to be our best credential, right? And Merim and his team are our best credential in this space. Um, so, you know, a lot of our customers, you know, struggle making that commitment. A lot of 'em are past that struggle, now. They're committed, they're going. Uh, but I talk to a lot of my customers about, you know, do I, do I migrate? Do I modernize? You know, how do I do it? And, and it was interesting with Accenture, right? It, it started out very much as a migration program. >> Yeah. >> Right, so, we made the decision, Merim and his team made the decision to do a migration and now a modernization, right? And, and that's proven very effective. Uh, it, it's, it's, it's proven, you know, uh, we got that core in place, right? We were able to build off of that versus, you know, spending- it would've taken a lot more time just to start with a modernization approach. >> Yeah. Where, where do you draw the line between the two, between migration and modernization, then? Because just by migrating alone, you are modernizing, you know, some of your operations, so you're getting up to speed. But, but how do you draw that line and then how do you get people to jump over it? >> So I, I'll hit it from how our lessons learned. So, when we first started and we did the migrations it was literally lift and shift. And it was a lot of argument about lift and shift isn't worth it. But we found out it was, because it wasn't just about moving the work loads and keeping it like a data center. It was moving the work loads and then optimizing because everything in the cloud was significantly faster. So then I didn't have to consume all the services the same way I did in the data center. I can actually consume them smaller. But also as time went by, what we learned is, hey, now these services are working here. Which ones are actually costing us more money to run? And not that they were costing more than the data center, but it's relative to the cloud which ones cost more in the cloud? Then we looked at that and said, okay how do we want to modernize those? And then we modernized as container capabilities started the evolving, got much more mature. We shifted a lot of workloads to containers. But otherwise, the other principle we push very hard is big consumption of Lambda and uh, serverless capabilities on Amazon. So we have refactored multiple applications to give us that capability to say we no longer need the IAS capabilities, those servers, those VM's, and we run on, on serverless capability. And what's great about that is, now I don't have a server to patch, to scan, to remediate, to upgrade. I've moved away from that capability. And the teams can focus more on building the business capabilities the business wants. Um, like we did to our pricing team. I don't know if you knew this one, Chris, but all the pricing capability has been redone to be cloud native on, on AWS. >> And how, how do you deal with the folks that, that still kind of have a foot in the on-prem world that, um, that they're just not ready to give it up? You know, they, they like the control, they like the self-management. >> Yeah. >> They, they want to be in charge. >> Well, yeah. I mean, a lot of, a lot of our customers, it's, there's a reason why they need on-prem still. And there is on-prem, let's be clear. I mean, it, it is a hybrid cloud world for most of our, our customers, right? Whether they got manufacturing, whether they've got, you know, datas that are, you know, SCADA systems or, or operational IT systems that have to be close to their, their execution or to their, to their factories and things like that. So that's going to happen. I think everyone, and I shouldn't say everyone, but you know, most of our customers know they need to get there, right? And are somewhere on their journey, right? Very few have not started at all. Uh, but it's about acceleration, right? And I, I do think, um, we're going to see more and more acceleration. We saw it with Covid, right? >> Mm-hm. >> And then, you know, obviously I think we're going to see it again, right? With you know, kind of what's going on with the economy and stuff like that. It, it's, you know, it's a great way to push that change through. >> Right. >> And I, I'm really excited, to be honest what I'm really excited about, if I look at what Merim and his team's doing, is they're just leveraging that digital core and truly taking the investments that the hyper scaler's are making, the AWS's are making, and leveraging 'em. So we're not making that investment, right? We're a capital white company, right? So we don't like making good capital investments, right? And we're taking advantage of the capital investments. And we couldn't do that of the, of the hyper scales. We couldn't do that without being there. Right? >> Right. >> We just couldn't do it. >> And maybe, John, if I can build on that. >> Sure. >> Like, one of, one of the things for me when I think about the cloud is, I'm not alone. You know, because when you're in a data center when you're running a data center, you're kind of on an island. And on that island, if you've got security issues, if you got stuff you're dealing with with attackers, you know, you're, you're kind of on an island and you're alone. Whereas in this world, I am where all the investment is, where all the security capabilities are being built, and I have partners that are there with us that help us when these situations come up. So for me, I'm very uh, grateful that we pushed very hard in the beginning to get here. But I wouldn't have it any other way. For us. >> So like, do you- do you want to live outside the fort? >> Yeah. >> No >> No. (laughs) >> You're exactly right. >> Yeah. >> I don't want to live outside the fort. >> Right. >> There are a lot of bad guys out there right now. >> Yeah. >> All right, so, the journey is over. >> Right. You can unpack your bags and get comfortable, right? (Merim laughs) >> No. >> Hardly. >> No. >> So, so what is the, what has this done in terms of setting you up for your future plans? And, and >> So I'll talk about a couple different things and maybe you can build on it, Chris, from what you're seeing, like for us, we, we got very good at, I hate the concept of just FinOps but it's the way of being in the cloud. It's different than running a data center and uh, the way we think about building services, consuming services, allocating services, provisioning services. There's just so much more flexibility there that we can completely fine tune the service that we want to provide. That helps us from when we think about 360 degree value, as we talk to our clients, for ourselves to say it also helps just simply on the sustainability agenda, right, because now, as Amazon builds their capabilities to be more sustainable, those SKUs are available to us, we can naturally consume those SKUs much more effectively. Um, and then uh, the next thing to me, what I'm, what I'm especially excited about is all the stuff we're doing around network. So, you know, pre-Covid, 95% of our traffic was just straight to the internet because we had already finished the journey. So now what do you need a wide area network for anymore? >> Right. >> If you're not routing traffic between data centers what do you need it for? So, we have been working with, with AWS especially, like building these cloud land type capabilities and consuming it. So think of consuming, uh, network same way as you do the cloud. So I'm excited about that one. >> Yeah. That, that, I'm super excited about that, right? Because you know, network's at the core of everything you do, right? And there's always a lot of concern, hey, when I go to the cloud, my network costs are going to go up, right? Um, but I think we've proven, right? >> Yes. >> Being able, that those costs can come down, right? And we can have a better experience, uh, deal with the ebbs and flows of our business whether it's people working from home, people working in the office, you know, or at the client sites. We, we've, you know, we've got that cloud-based backbone that we support. You know, I, I mean Merim, I agree a hundred percent. I think you and your team have done a great job of cost management, cloud cost management, optimization, right? You didn't stop, right? >> No. >> You didn't lo- you didn't just live after the migration on VMs. Right? You know, you went serverless, you went, you know, containerization. >> Yep. >> Uh, and that's kept our cloud bill going down. >> Yes. >> Right. Versus going up, right? >> Yes. >> And I hear from a lot of customers concerned about cloud costs and that type of stuff, but you've proven right, >> Yes. >> That you can keep it flat, if not going down because you're using those last minutes. Sustainability is the other thing that I truly am, I, I love, right? Is, you know, we're all trying to become a more sustainable, sustainable organization. We're trying to help our clients become more sustainable organizations. And you know, you know, your ability to take on Gravitant processors, right? Which use less power. >> Yes. >> Right? Overnight, right? >> Yes. >> Or, hey, I'm using a, you know a, uh, serverless lambda, whatever, right? And I'm not running that server. >> Right. >> You know, so, you're able to show that sustainability gains, um, you know, very quickly. Which you could not do, right? You know, in just doing cloud basic migrations. >> Well, I tell you what I think is impressive, is that you put your money where your mouth is, right? >> Yep. (laughs) >> Is that, that it's, and, and if I'm going to be a client, not to, you know, give you guys a pat on the back, you don't need it. You're doing great without me. But I'd say you've been there, you've done that. And, and so I can learn from you. You understand my pain. >> Yes. >> You understand my reservations, my challenges and uh, you could be my, my headlights here. (Merim laughs) >> So, I think great approach. Kudos to you and certainly wish you both success and to your fourth and fifth appearances on the Cube. (Merim and Chris laugh) Um, we have slots tomorrow if you're arou- available. So, maybe we'll fill it up >> There you go. >> and bring it back again. >> Awesome. >> Guys, thanks for being here. >> Sure. >> It was very nice. >> Appreciate the time. >> All right. >> That's great. >> I've been talking, uh, about Accenture. This is the, of course, executive summit being sponsored by Accenture here at AWS reInvent 22. I'm John Walls. You're watching the Cube, the leader in tech coverage.

(upbeat music) >> Hello, beautiful cloud community, and welcome back to AWS reInvent. It is day four here in fabulous Las Vegas, Nevada. My voice can feel it, clearly. I'm Savannah Peterson with my co-host Paul Gillin. Paul, how you doing? >> Doing fine, Savannah. >> Are your feet about where my voice is? >> Well, getting little rest here as we have back to back segments. >> Yeah, yeah, we'll keep you off those. Very excited about this next segment. We get to have a chat with one of our very favorite analysts, Keith Townsend. Welcome back to theCUBE. >> Savannah Page. I'm going to use your south names, Savannah Page. Thank you for having me, Paul. Good to see you again. It's been been too long since CubeCon Valencia. >> Valencia. >> Valencia. >> Well at that beautiful lisp, love that. Keith, how's the show been for you so far? >> It has been great. I tweeted it a couple of days ago. Amazon reInvent is back. >> Savannah: Whoo! Love that. >> 50, 60 thousand people, you know? After 40 thousand, I stop countin'. It has been an amazing show. I don't know if it's just the assignment of returning, but easily the best reInvent of the four that I've attended. >> Savannah: Love that. >> Paul: I love that we have you here because, you know, we tend to get anchored to these desks, and we don't really get a sense of what's going on out there. You've been spending the last four days traversing the floor and talking to people. What are you hearing? Are there any mega themes that are emerging? >> Keith: So, a couple of mega themes is... We were in the Allen session with Adam, and Adam bought up the idea of hybrid cloud. At the 2019 show, that would be unheard of. There's only one cloud, and that's the AWS cloud, when you're at the Amazon show. Booths, folks, I was at the VMware booth and there's a hybrid cloud sign session. People are talking about multicloud. Yes, we're at the AWS show, but the reality that most customers' environments are complex. Adam mentioned that it's hybrid today and more than likely to be hybrid in the future in Amazon, and the ecosystem has adjusted to that reality. >> Paul: Now, is that because they want sell more outposts? >> You know, outpost is definitely a part of the story, but it's a tactile realization that outposts alone won't get it. So, you know, from Todd Consulting, to Capgemini, to PWC, to many of the integrations on the show floor... I even saw company that's doing HP-UX in the cloud or on-prem. The reality is these, well, we've deemed these legacy systems aren't going anywhere. AWS announced the mainframe service last year for converting mainframe code into cloud workloads, and it's just not taking on the, I think, the way that the Amazon would like, and that's a reality that is too complex for all of it to run in the cloud. >> Paul: So it sounds like the strategy is to envelop and consume then if you have mainframe conversion services and HP-UX in the cloud, I mean, you're talking about serious legacy stuff there. >> Keith: You're talking about serious legacy stuff. They haven't de-emphasized their relationship with VMware. You know, hybrid is not a place, it is a operating model. So VMware cloud on AWS allows you to do both models concurrently if you have those applications that need layer two. You have these workloads that just don't... SAP just doesn't... Sorry, AWS, SAP in the cloud and EC2 just doesn't make financial sense. It's a reality. It's accepting of that and meeting customers where they're at. >> And all the collaboration, I mean, you've mentioned so many companies in that answer, and I think it's very interesting to see how much we're all going to have to work together to make the cloud its own operating system. Cloud as an OS came up on our last conversation here and I think it's absolutely fascinating. >> Keith: Yeah, cloud is the OS I think is a thing. This idea that I'm going to use the cloud as my base layer of abstraction. I've talked to a really interesting startup... Well actually it's a open source project cross plane of where they're taking that cloud model and now I can put my VMware vsphere, my AWS, GCP, et cetera, behind that and use that operating model to manage my overall infrastructure. So, the maturity of the market has fascinated me over the past year, year and a half. >> It really feels like we're at a new inflection point. I totally agree. I want to talk about something completely different. >> Keith: Okay. >> Because I know that we both did this challenge. So one of the things that's really inspiring quite frankly about being here at AWS reInvent, and I know you all at home don't have an opportunity to walk the floor and get the experience and get as many steps as Paul gets in, but there's a real emphasis on giving back. This community cares about giving back and AWS is doing a variety of different activations to donate to a variety of different charities. And there's a DJ booth. I've been joking. It kind of feels like you're arriving at a rave when you get to reInvent. And right next to that, there is a hydrate and help station with these reusable water bottles. This is actually firm. It's not one of those plastic ones that's going to end up in the recycled bin or the landfill. And every single time that you fill up your water bottle, AWS will donate $3 to help women in Kenya get access to water. One of the things that I found really fascinating about the activation is women in sub-Saharan Africa spend 16 million hours carrying water a day, which is a wild concept to think about, and water is heavy. Keith, my man, I know that you did the activation. They had you carrying two 20 pound jugs of water. >> Keith: For about 15 feet. It's not the... >> (laughs) >> 20 pound jugs of water, 20 gallons, whatever the amount is. It was extremely heavy. I'm a fairly sizeable guy. Six four, six five. >> You're in good shape, yeah. >> Keith: Couple of a hundred pounds. >> Yeah. >> Keith: And I could not imagine spending that many hours simply getting fresh water. We take it for granted. Every time I run the water in the sink, my family gets on me because I get on them when they leave the sink water. It's like my dad's left the light on. If you leave the water on in my house, you are going to hear it from me because, you know, things like this tickle in my mind like, wow, people walk that far. >> Savannah: That's your whole day. >> Just water, and that's probably not even enough water for the day. >> Paul: Yeah. We think of that as being, like, an 18th century phenomenon, but it's very much today in parts of Sub-Saharan Africa. >> I know, and we're so privileged. For me, it was just, we work in technology. Everyone here is pretty blessed, and to do that activation really got my head in the right space to think, wow I'm so lucky. The team here, the fabulous production team, can go refill my water bottle. I mean, so simple. They've also got a fitness activation going on. You can jump on a bike, a treadmill, and if you work out for five minutes, they donate $5 to Fred Hutch up in Seattle. And that was nice. I did a little cross-training in between segments yesterday and I just, I really love seeing that emphasis. None of this matters if we're not taking care of community. >> Yeah, I'm going to go out and google Fred Hutch, and just donate the five bucks. 'Cause I'm not, I'm not. >> (laughs) >> I'll run forever, but I'm not getting on a bike. >> This from a guy who did 100 5Ks in a row last year. >> Yeah. I did 100 5Ks in a row, and I'm not doing five minutes on a bike. That's it. That's crazy, right? >> I mean there is a treadmill And they have the little hands workout thing too if you want. >> About five minutes though. >> Savannah: I know. >> Like five minutes is way longer than what you think it is. >> I mean, it's true. I was up there in a dress in sequence. Hopefully, I didn't scar any anyone on the show floor yesterday. It's still toss up. >> I'm going to take us back to back. >> Take us back Paul. >> Back to what we were talking about. I want to know what you're hearing. So we've had a lot of people on this show, a lot of vendors on the show who have said AWS is our most important cloud partner, which would imply that AWS's lead is solidifying its lead and pulling away from the pack as the number one. Do you hear that as well? Or is that lip service? >> Keith: So I always think about AWS reInvent as the Amazon victory lap. This is where they come and just thumb their noses at all the other cloud providers and just show how far ahead they're are. Werner Vogels, CTO at Amazon's keynotes, so I hadn't watched it yet, but at that keynote, this is where they literally take the victory lap and say that we're going to expose what we did four or five years ago on stage, and what we did four or five years ago is ahead of every cloud provider with maybe the exception of GCP and they're maybe three years behind. So customers are overwhelmingly choosing Amazon for these reasons. Don't get me wrong, Corey Quinn, Gardner folks, really went at Adam yesterday about Amazon had three majors outages in December last year. AWS has way too many services that are disconnected, but from the pure capability, I talked to a born in the cloud data protection company who could repatriate their data protection and storage on-prem private data center, save money. Instead, they double down on Amazon. They're using, they modernize their application and they're reduced their cost by 60 to 70%. >> Massive. >> This is massive. AWS is keeping up with customers no matter where they're at on the spectrum. >> Savannah: I love that you use the term victory lap. We've had a lot of folks from AWS here up on the show this week, and a couple of them have said they live for this. I mean, and it's got to be pretty cool. You've got 70 thousand plus people obsessed with your product and so many different partners doing so many different things from the edge to hospital to the largest companies on earth to the Israeli Ministry of Defense we were just talking about earlier, so everybody needs the cloud. I feel like that's where we're at. >> Keith: Yeah, and the next step, I think the next level opportunity for AWS is to get to that analyst or that citizen developer, being able to enable the end user to use a lambda, use these data services to create new applications, and the meanwhile, there's folks on the show floor filling that gap that enable develop... the piece of owner, the piece of parlor owner, to create a web portal that compares his prices and solutions to other vendors in his area and adjust dynamically. You go into a restaurant now and there is no price menu. There's a QR code that Amazon is powering much of that dynamic relationship between the restaurateur, the customer, and even the menu and availability. It's just a wonderful time. >> I always ask for the print menu. I'm sorry. >> Yeah. You want the printed menu. >> Look down, my phone doesn't work. >> Gimme something I could shine my light on. >> I know you didn't have have a chance to look at Vogel's keynote yet, but I mean you mentioned citizen developer. One of the things they announced this morning was essentially a low code lambda interface. So you can plug, take your lamb dysfunctions and do drag and drop a connection between them. So they are going after that market. >> Keith: So I guess I'll take my victory lap because that was my prediction. That's where Amazon's next... >> Well done, Keith. >> Because Lambda is that thing when you look at what server list was and the name of the concept of being, not having to have to worry about servers in your application development, the logical next step, I won't take too much of a leap. That logical first step is, well, code less code. This is something that Kelsey Hightower has talked about a lot. Low code, no code, the ability to empower people without having these artificial barriers, learning how to code in a different language. This is the time where I can go to Valencia, it's pronounced, where I can go to Valencia and not speak Spanish and just have my phone. Why can't we do, at business value, for people who have amazing ideas and enable those amazing ideas before I have to stick a developer in between them and the system. >> Paul: Low-code market is growing 35% a year. It's not surprising, given the potential that's out there. >> And as a non-technical person, who works in technology, I've been waiting for this moment. So keep predicting this kind of thing, Keith. 'Cause hopefully it'll keep happening. Keith, I'm going to give you the challenge we've been giving all of our guests this week. >> Keith: Okay. >> And I know you're going to absolutely crush this. So we are looking for your 32nd Instagram real, sizzle hot take, biggest takeaway from this year's show. >> So 32nd Instagram, I'll even put it on TikTok. >> Savannah: Heck yeah. >> Hybrid cloud, hybrid infrastructure. This is way bigger than Amazon. Whether we're talking about Amazon, AWS, I mean AWS's solutions, Google Cloud, Azure, OCI, on-prem. Customers want it all. They want a way to manage it all, and they need the skill and tools to enable their not-so-growing work force to do it. That is, that's AWS reInvent 2019 to 2022. >> Absolutely nailed it. Keith Townsend, it is always such a joy to have you here on theCUBE. Thank you for joining us >> Savannah Page. Great to have you. Paul, you too. You're always a great co-host. >> (laughs) We co-hosted for three days. >> We've got a lot of love for each other here. And we have even more love for all of you tuning into our fabulous livestream from AWS reInvent Las Vegas, Nevada, with Paul Gillin. I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (upbeat music)

(bright upbeat music) >> Hey, good morning from Las Vegas. It's Lisa Martin and Paul Gillin here. We are on day three of AWS re:Invent. We started Monday night, we went all day yesterday, we are going all day today and all day tomorrow. The amount of content coming at you from theCUBE, great, interesting, fascinating conversations with AWS, its customers, its ecosystem partners is incredible. Paul, what's your take so far on re:Invent? We've been here two and a half days. >> Well, it's just a fire hose. Like I've said before, this morning's keynote was about was about ML, machine learning and AI, and I stopped counting at 15 new announcements during about a 90 minute keynote, it's just one thing after another. And that's the nature of re:Invent, you know? It's always a showcase for new stuff. And they talk about customers, you talk about customers, I love it when we have a chance to talk to customers on theCUBE as we are about to do. >> We are about to talk to one of the nation's leading digital banks, you know them well, Capital One. Please welcome, Lo Li, Managing Vice President of Customer Digital Experience and Payments. Thank you so much, Lo, for joining us. >> Why, thank you, I'm glad to be here. >> Talk a little bit about your role where it fits within the organization, what it encompasses? >> Sure, yeah. So, I lead the retail bank technology organization which is a form of, you know, we have teams that lead digital experiences for our consumers. We look after agent in-person experiences with their cafes in branches, our call centers and as well as of our MarTech and payments ecosystem. >> So you're new to Capital One, in the last less than a year, you know, we all know it, we love it, we know the tagline, what's in your wallet? I think we can all recite that. It's as I said in the opening, it's one of the nation's leading digital banks and technology is really core to its business strategy and delivering value to customers. What attracted you to Capital One and talk about it really as a digital bank that delivers all that value. >> Of course. Yeah, so, you know, I spent 20 years of my career in a digital space in retail, and fashion and hospitality. And that is what I love about IT and the industry that I'm in and what I do, which is bringing really great solutions and products to consumers and getting them excited about an experience and a brand. So I knew early on in my career I was attracted to really great brands and brands that wanted to innovate and disrupt the consumer space. So when Capital One gave me an opportunity, I couldn't be happier, right? This is an incredible bank, we have an incredible story, we're a young bank and yet we are very much on the leading edge of a digital bank experience. >> And you were in an interesting place because as we know retail banking is declining or at least bank branches are in decline. More and more people want to do their banking on their mobile apps or through their computers, particularly younger customers. And so you're having to manage all this, what are you doing? How are you tracking to these demographic changes accelerated by the pandemic and recreating the customer experience through multiple channels? >> Yeah, great question. We want to give our consumers an omnichannel experience irrespective of, you know, the few that still want to go into branches or perhaps they want to experience a cafe, and while there meet with one of our branch ambassadors to talk about their banking, we have consumers that want to go digital. So what we do is that we make sure that we're looking after the consumer holistically, irrespective of the channel. So whether they call into the call center because they need servicing or if they're physically present or they want to carry that on digitally, we make sure that we create super personalized custom experiences. We also work with a bunch of designers that are thinking through, you know, the life of a consumer now and their relationship to a bank. It is, to your point, it is no longer a branch, you know? That is a ubiquitous experience that we're by large knowing that we have to figure out and rethink. So, we're very lucky to have great designers that work with us and work on what is that experience that we want our consumers to have, from the pastries and the coffee, and the experience of being with an ambassador and how we can lead them through our iPads and digital experiences to continue to stay with us and for us to service them. >> You know, if we think about how much banking has changed especially in the last couple of years, when suddenly you couldn't get into a branch, even if you wanted to, it's amazing how we have this expectation that on my phone I can do any transaction I want in real time, I'm going to be able to see my balance, I can transfer money, I can make a payment. And we don't think about the technology on the back end but it's absolutely critical to powering that experience. >> Yeah. >> Talk about how you're doing that and is there customer feedback in that process? >> There is, but that's music to my ears by the way. The fact that you don't think about it tells me we're doing something really right, right? So first and foremost, we are super hypervigilant about security, that is top of mind, we are well managed. The cloud has enabled us to create these infrastructures that are highly secure, that are scalable and that allows us to really focus on innovation. So we use our mobile platform and our apps in that way, right? We know that this is a scalable, secure platform. We create really great products, we create very custom experiences for you that are relevant to you and your family and we create these digital products that are supposed to meet you where you are. >> But we certainly have, you know, this expectation that I'm going to get what I want, it's going to be relevant, it's going to be timely. If not, I'm going to pick up, not the phone, I'm going to go on social media and make a complaint. So from a brand reputation perspective, you guys, what you're doing is clearly going in the right direction. >> Yeah, yeah. Look, we take our bank voice and the voice of the customer extremely seriously. So, we have a really large infrastructure from a bank operations perspective. We have our bank voice agents that work with us that give us kind of really real-time feedback from our customers. You know, by the time you pick up the phone and call usually something has gone really wrong, right? So, we make sure that we stay lockstep with what our first level agents are hearing. Then we also look into our feedbacks, we have obviously ways to look into our mobile app. We look at all the reviews that we have and incorporate that into how we think about our product and how we invest and innovate on them. >> Before we turned on the cameras, you said an amazing thing. Capital One doesn't have any data centers anymore, doesn't have any mainframes anymore, it is fully in the cloud. Understanding that you weren't there in those old days but how does that change the way you think about new features, about technology, new technology developments for the customer when you don't have that legacy to drag along with you? >> It's incredible, right? Our cost efficiency, our production efficiency, how we think about going to the market now is really getting us to focus on the right parts of that product. We don't have to carry a lot of the technical debt, we don't carry that old infrastructure. So the way we develop, the way we design, the way we go to market is a lot faster than it ever was. >> Well, and the culture is there, the cultural mindset is there to be able to do that. I mean, if you think about who you compete with some of these institutions that have been around for a hundred years that also have to transform and digitize 'cause the customers expect it. That has to be a seamless process but their culture also has to be there because changing from being On-prem data centers to being completely in the cloud, it's a big change. >> Yeah, actually, you hit it, right? The cloud transformation is big, and hard and sticky. You got to move these workloads, you got to make 'em native, you got to deploy. But to your point, the harder part really is the culture, right? Because the cloud will then unleash productivity, it will unleash continuous improvement. It will bring product partners along the ride because they have to think differently about what they want to go to the market with, how they think about the cost of those units, how they think about cloud. So, you know, in my opinion, Capital One has done an incredible job bringing that entire, the entire organization along this cloud transformation including our culture, our processes, and our people. >> I know Capital One is proud of the work it's been doing in AI and machine learning. Can you talk about from the retail banking perspective, how is machine learning being applied to improve the customer experience? >> Yeah, well, you know, as you know, AI and machine learning is the heart of the bank, is the heart of Capital One. When we started in the early 90s, we were the only bank that was really trying to challenge how we use data to provide better products for our consumers, and that is ingrained in our DNA and everything that we do. So if you were to look at bank, we would start with, you know, from the time you are authenticating yourself, how we think about fraud and how do we capture bad actors, all the way to if you were to call into a call center, we use a lot of natural language processing models to make sure that we assess your sentiment, we give you the support that you need, and then of course, use that to learn more about how we service you. >> Interesting, I'm just wondering, do you think about Capital One as a technology company that does banking or a bank that is powered by technology? >> We are a technology company, and we happen to also have a bank. >> Lisa: I love that. What are some of the things that you've heard and seen at the show? Obviously, we're hearing numbers between 55 and 70,000 people here. It's crazy. And we're only getting a snapshot of that because here we are at Venetian Expo and the conference is going on all over the strip. But what are some of the things that you've heard from AWS that excite you about the partnership going forward? >> You know, I'll be honest, one of my happiest, proud moments, when we're talking about Lambda SnapStart yesterday, we actually, our team that is here today was part of the first beta of bringing in Lambda SnapStart. And we're super excited because it helps propel our serverless agenda. You know, we're continued to transform into the cloud. So, we have a lot of these partnership opportunities that, you know, make me super proud. >> Well follow up on serverless because to a lot of people, it's a concept that they don't really understand how to put it to practice. How is serverless a step forward? What has it enabled you to do that you couldn't otherwise do? >> Wow, a bunch. I think first and foremost, it helps us stay, you know, very well managed, security wise, right? It allows us to create automation and it takes away a lot of the heavy lifting that our engineers would have to do otherwise. And the byproduct of that is that we get to go focus on really fun, innovative ideas, and we get to go work on product development. We're taking a lot of the grit work of the management of the servers out of the engineer's hand and automating them. >> Banking, of course, one of the most regulated industries on the planet, has Cloud been able to help you in that respect? >> Yes. Yes it has. Look, we are in a regulated space which means everything we do has a ton of scrutiny, for the right reasons. So we actually built it into our design, so our design, our products, we design our platforms with security in mind, with the regulations in mind and make it where it's less of a thought, right? So, we obviously spend a lot of time from a risk posture helping our associates understand, really respecting the responsibility that we have to look after everybody's assets, right? Like it's, what a more incredible job than that? So, we spend a lot of time thinking about what is our risk posture, where is it, you know, from what you would imagine the regular scan vulnerabilities all the way to data protection. And now that we protect that data in Fly, like they're all things that is our number one job and we spend a ton of time focused on it. >> That's good, it's very complex but security is a topic we discuss regularly. We've seen the threat landscape change so dramatically in the last couple of years. Bad actors are getting far more sophisticated. They're leveraging the technology but when it comes to banking as Paul was talking about, from a regulations perspective, from an end customer perspective, we have this expectation that you're going to keep my data secure because nobody wants to be the next headline. >> Lo: Yes, that's right. That's right, and look, we are getting, we're getting smarter as well, right? So we are able to detect and monitor and go after the bad actors faster. We're doing it in a way that allows us configurability, it gives us time, it gives us speed, but at the same time we also work as a network, right? So a lot of our banks, we, you know, in some ways share a lot of this information to make sure that we're all going after a common enemy. >> Capital One recently launched a software company, Capital One Software, which is a relatively unusual move by a financial services organization. How has that affected the thinking at the company about what the company is and what other opportunities there might be outside of pure banking? >> Yeah, absolutely. So, Capital One Software is a very exciting new line of business. I think the team that is there is doing some really incredible, innovative work. But you know what's really interesting is they were talking about our new product SlingShot, it was born out of our needs, right? We knew that we needed to have better governance around our data. We created really great tools and it was very obvious that there was a commercial applicability there. And that is how we will continue to operate, right? As a bank, we're all in the cloud, we're all in in the cloud. It will give us the ability to start sharing some of these best practices. And I think the best is yet to come, I think we got some really good stuff in the pipeline. >> Lisa: Anything you can share in the-- >> No. >> Lisa: No? Tight lips. >> Tight lips. >> Excellent, well, last couple of questions. What's the main theme here? When people walk into the Venetian Expo and they see Capital One next to all these tech companies, what's the main theme that Capital One wants to get across to the greater community? >> Yeah, look, our mission is to change banking for good, it always has been our mission. We're very fortunate to be in a position to be tech innovators, and we're fortunate to disrupt, and that's what I want people to get out of it. >> Excellent, my last question for you, kind of continuing on this theme. If you had, you were going to have the opportunity to create new branding and it's going to go in the cafes and it's going to be like a little billboard inside about Capital One being a technology company that does banking. What do you think that that billboard, that sign would say? >> I think I'm going to stick with the change banking for good. I mean, that really is at the heart of our mission. >> Paul: It's a nice double message too, yeah. >> Yeah, with technology, with disruption, ultimately that's where our hearts and minds are at. >> Awesome. Lo, it's been great to have you on the program. Thank you for sharing what you're doing at Capital One, how you're working with AWS and also emerging technologies like AI and ML to really create a seamless digital customer experience. We really appreciate your time and your insights. >> Thank you. >> All right, for our guest and for Paul Gillin I'm Lisa Martin. You're watching theCUBE, the leader in live emerging and enterprise tech coverage. (upbeat music)

(upbeat music) (background crowd chatter) >> Hello, fantastic cloud community and welcome back to Las Vegas where we are live from the show floor at AWS re:Invent. My name is Savannah Peterson. Joined for the first time. >> Yeah, Doobie. >> VIP, I know. >> All right, let's do this. >> Thanks for having me Dave, I really appreciate it. >> I appreciate you doing all the hard work. >> Yeah. (laughs) >> You, know. >> I don't know about that. We wouldn't be here without you and all these wonderful stories that all the businesses have. >> Well, when I host with John it's hard for me to get a word in edgewise. I'm just kidding, John. (Savannah laughing) >> Shocking, I've never want that experience. >> We're like knocking each other, trying to, we're elbowing. No, it's my turn to speak, (Savannah laughing) so I'm sure we're going to work great together. I'm really looking forward to it. >> Me too Dave, I feel very lucky to be here and I feel very lucky to introduce our guest this afternoon, Clint Sharp, welcome to the show. You are with Cribl. Yeah, how does it feel to be on the show floor today? >> It's amazing to be back at any conference in person and this one is just electric, I mean, there's like a ton of people here love the booth. We're having like a lot of activity. It's been really, really exciting to be here. >> So you're a re:Ieinvent alumni? Have you been here before? You're a Cube alumni. We're going to have an OG conversation about observability, I'm looking forward to it. Just in case folks haven't been watching theCUBE for the last nine years that you've been on it. I know you've been with a few different companies during that time period. Love that you've been with us since 2013. Give us the elevator pitch for Cribl. >> Yeah, so Cribl is an observability company which we're going to talk about today. Our flagship product is a telemetry router. So it just really helps you get data into the right places. We're very specifically in the observability and security markets, so we sell to those buyers and we help them work with logs and metrics and open telemetry, lots of different types of data to get it into the right systems. >> Why did observability all of a sudden become such a hot thing? >> Savannah: Such a hot topic. >> Right, I mean it just came on the scene so quickly and now it's obviously a very crowded space. So why now, and how do you guys differentiate from the crowd? >> Yeah, sure, so I think it's really a post-digital transformation thing Dave, when I think about how I interact with organizations you know, 20 years ago when I started this business I called up American Airlines when things weren't working and now everything's all done digitally, right? I rarely ever interact with a human being and yet if I go on one of these apps and I get a bad experience, switching is just as easy as booking another airline or changing banks or changing telecommunications providers. So companies really need an ability to dive into this data at very high fidelity to understand what Dave's experience with their service or their applications are. And for the same reasons on the security side, we need very, very high fidelity data in order to understand whether malicious actors are working their way around inside of the enterprise. And so that's really changed the tooling that we had, which, in prior years, it was really hard to ask arbitrary questions of that data. You really had to deal with whatever the vendor gave you or you know, whatever the tool came with. And observability is really an evolution, allowing people to ask and answer questions of their data that they really weren't planning in advance. >> Dave: Like what kind of questions are people asking? >> Yeah sure so what is Dave's performance with this application? I see that a malicious actor has made their way on the inside of my network. Where did they go? What did they do? What files did they access? What network connections did they open? And the scale of machine data of this machine to machine communication is so much larger than what you tend to see with like human generated data, transactional data, that we really need different systems to deal with that type of data. >> And what would you say is your secret sauce? Like some people come at it, some search, some come at it from security. What's your sort of superpower as Lisa likes to say? >> Yeah, so we're a customer's first company. And so one of the things I think that we've done incredibly well is go look at the market and look for problems that are not being solved by other vendors. And so when we created this category of an observability pipeline, nobody was really marketing an observability pipeline at that time. And really the problem that customers had is they have data from a lot of different sources and they need to get it to a lot of different destinations. And a lot of that data is not particularly valuable. And in fact, one of the things that we like to say about this class of data is that it's really not valuable until it is, right? And so if I have a security breach, if I have an outage and I need to start pouring through this data suddenly the data is very, very valuable. And so customers need a lot of different places to store this data. I might want that data in a logging system. I might want that data in a metric system. I might want that data in a distributed tracing system. I might want that data in a data lake. In fact AWS just announced their security data lake product today. >> Big topic all day. >> Yeah, I mean like you can see that the industry is going in this way. People want to be able to store massively greater quantities of data than they can cost effectively do today. >> Let's talk about that just a little bit. The tension between data growth, like you said it's not valuable until it is or until it's providing context, whether that be good or bad. Let's talk about the tension between data growth and budget growth. How are you seeing that translate in your customers? >> Yeah, well so data's growing in a 25% CAGR per IDC which means we're going to have two and a half times the data in five years. And when you talk to CISOs and CIOs and you ask them, is your budget growing at a 25% CAGR, absolutely not, under no circumstances am I going to have, you know, that much more money. So what got us to 2022 is not going to get us to 2032. And so we really need different approaches for managing this data at scale. And that's where you're starting to see things like the AWS security data lake, Snowflake is moving into this space. You're seeing a lot of different people kind of moving into the database for security and observability type of data. You also have lots of other companies that are competing in broad spectrum observability, companies like Splunk or companies like Datadog. And these guys are all doing it from a data-first approach. I'm going to bring a lot of data into these platforms and give users the ability to work with that data to understand the performance and security of their applications. >> Okay, so carry that through, and you guys are different how? >> Yeah, so we are this pipeline that's sitting in the middle of all these solutions. We don't care whether your data was originally intended for some other tool. We're going to help you in a vendor-neutral way get that data wherever you need to get it. And that gives them the ability to control cost because they can put the right data in the right place. If it's data that's not going to be frequently accessed let's put it in a data lake, the cheapest place we can possibly put that data to rest. Or if I want to put it into my security tool maybe not all of the data that's coming from my vendor, my vendor has to put all the data in their records because who knows what it's going to be used for. But I only use half or a quarter of that information for security. And so what if I just put the paired down results in my more expensive storage but I kept full fidelity data somewhere else. >> Okay so you're observing the observability platforms basically, okay. >> Clint: We're routing that data. >> And then creating- >> It's meta observability. >> Right, observability pipeline. When I think a data pipeline, I think of highly specialized individuals, there's a data analyst, there's a data scientist, there's a quality engineer, you know, etc, et cetera. Do you have specific roles in your customer base that look at different parts of that pipeline and can you describe that? >> Yeah, absolutely, so one of the things I think that we do different is we sell very specifically to the security tooling vendors. And so in that case we are, or not to the vendors, but to the customers themselves. So generally they have a team inside of that organization which is managing their security tooling and their operational tooling. And so we're building tooling very specifically for them, for the types of data they work with for the volumes and scale of data that they work with. And that is giving, and no other vendor is really focusing on them. There's a lot of general purpose data people in the world and we're really the only ones that are focusing very specifically on observability and security data. >> So the announcement today, the security data lake that you were talking about, it's based on the Open Cybersecurity Framework, which I think AWS put forth, right? And said, okay, everybody come on. [Savannah] Yeah, yeah they did. >> So, right, all right. So what are your thoughts on that? You know, how does it fit with your strategy, you know. >> Yeah, so we are again a customer's first neutral company. So if OCSF gains traction, which we hope it does then we'll absolutely help customers get data into that format. But we're kind of this universal adapter so we can take data from other vendors, proprietary schemas, maybe you're coming from one of the other send vendors and you want to translate that to OCSF to use it with the security data lake. We can provide customers the ability to change and reshape that data to fit into any schema from any vendor so that we're really giving security data lake customers the ability to adapt the legacy, the stuff that they have that they can't get rid of 'cause they've had it for 10 years, 20 years and nothing inside of an enterprise ever goes away. That stuff stays forever. >> Legacy. >> Well legacy is working right? I mean somebody's actually, you know, making money on top of this thing. >> We never get rid of stuff. >> No, (laughing) we just added the toolkit. It's like all the old cell phones we have, it's everything. I mean we even do it as individual users and consumers. It's all a part of our little personal library. >> So what's happened in the field company momentum? >> Yeah let's talk trends too. >> Yeah so the company's growing crazily fast. We're north of 400 employees and we're only a hundred and something, you know, a year ago. So you can kind of see we're tripling you know, year over year. >> Savannah: Casual, especially right now in a lot of companies are feeling that scale back. >> Yeah so obviously we're keeping our eye closely on the macro conditions, but we see such a huge opportunity because we're a value player in this space that there's a real flight to value in enterprises right now. They're looking for projects that are going to pay themselves back and we've always had this value prop, we're going to come give you a lot of capabilities but we're probably going to save you money at the same time. And so that's just really resonating incredibly well with enterprises today and giving us an opportunity to continue to grow in the face of some challenging headwinds from a macro perspective. >> Well, so, okay, so people think okay, security is immune from the macro. It's not, I mean- >> Nothing, really. >> No segment is immune. CrowdStrike announced today the CrowdStrike rocket ship's still growing AR 50%, but you know, stocks down, I don't know, 20% right now after our- >> Logically doesn't make- >> Okay stuff happens, but still, you know, it's interesting, the macro, because it was like, to me it's like a slingshot, right? Everybody was like, wow, pandemic, shut down. All of a sudden, oh wow, need tech, boom. >> Savannah: Yeah, digitally transformed today. >> It's like, okay, tap the brakes. You know, when you're driving down the highway and you get that slingshotting effect and I feel like that's what's going on now. So, the premise is that the real leaders, those guys with the best tech that really understand the customers are going to, you know, get through this. What are your customers telling you in terms of, you know they're spending patterns, how they're trying to maybe consolidate vendors and how does that affect you guys? >> Yeah, for sure, I mean, I think, obviously, back to that flight to value, they're looking for vendors who are aligned with their interests. So, you know, as their budgets are getting pressure, what vendors are helping them provide the same capabilities they had to provide to the business before especially from a security perspective 'cause they're going to get cut along with everybody else. If a larger organization is trimming budgets across, security's going to get cut along with everybody else. So is IT operations. And so since they're being asked to do more with less that's you know, really where we're coming in and trying to provide them value. But certainly we're seeing a lot of pressure from IT departments, security departments all over in terms of being able to live and do more with less. >> Yeah, I mean, Celip's got a great quote today. "If you're looking to tighten your belt the cloud is the place to do it." I mean, it's probably true. >> Absolutely, elastic scalability in this, you know, our new search product is based off of AWS Lambda and it gives you truly elastic scalability. These changes in architectures are what's going to allow, it's not that cloud is cheaper, it's that cloud gives you on-demand scalability that allows you to truly control the compute that you're spending. And so as a customer of AWS, like this is giving us capabilities to offer products that are scalable and cost effective in ways that we just have not been able to do in the cloud. >> So what does that mean for the customer that you're using serverless using Lambda? What does that mean for them in terms of what they don't have to do that they maybe had to previously? >> It offers us the ability to try to charge them like a truly cloud native vendor. So in our cloud product we sell a credit model whereby which you deduct credits for usage. So if you're streaming data, you pay for gigabytes. If you're searching data then you're paying for CPU consumption, and so it allows us to charge them only for what they're consuming which means we don't have to manage a whole fleet of servers, and eventually, well we go to managing our own compute quite possibly as we start to get to scale at certain customers. But Lambda allowed us to not have to launch that way, not have to run a bunch of infrastructure. And we've been able to align our charging model with something that we think is the most customer friendly which is true consumption, pay for what you consume. >> So for example, you're saying you don't have to configure the EC2 Instance or figure out the memory sizing, you don't have to worry about any of that. You just basically say go, it figures that out and you can focus on upstream, is that right? >> Yep, and we're able to not only from a cost perspective also from a people perspective, it's allowed us velocity that we did not have before, which is we can go and prototype and build significantly faster because we're not having to worry, you know, in our mature products we use EC2 like everybody else does, right? And so as we're launching new products it's allowed us to iterate much faster and will we eventually go back to running our own compute, who knows, maybe, but it's allowed us a lot faster velocity than we were able to get before. >> I like what I've heard you discuss a lot is the agility and adaptability. We're going to be moving and evolving, choosing different providers. You're very outspoken about being vendor agnostic and I think that's actually a really unique and interesting play because we don't know what the future holds. So we're doing a new game on that note here on theCUBE, new game, new challenge, I suppose I would call it to think of this as your 30 second thought leadership highlight reel, a sizzle of the most important topic or conversation that's happening theme here at the show this year. >> Yeah, I mean, for me, as I think, as we're looking, especially like security data lake, et cetera, it's giving customers ownership of their data. And I think that once you, and I'm a big fan of this concept of open observability, and security should be the same way which is, I should not be locking you in as a vendor into my platform. Data should be stored in open formats that can be analyzed by multiple places. And you've seen this with AWS's announcement, data stored in open formats the same way other vendors store that. And so if you want to plug out AWS and you want to bring somebody else in to analyze your security lake, then great. And as we move into our analysis product, our search product, we'll be able to search data in the security data lake or data that's raw in S3. And we're really just trying to give customers back control over their future so that they don't have to maintain a relationship with a particular vendor. They're always getting the best. And that competition fuels really great product. And I'm really excited for the next 10 years of our industry as we're able to start competing on experiences and giving customers the best products, the customer wins. And I'm really excited about the customer winning. >> Yeah, so customer focused, I love it. What a great note to end on. That was very exciting, very customer focused. So, yo Clint, I have really enjoyed talking to you. Thanks. >> Thanks Clint. >> Thanks so much, it's been a pleasure being on. >> Thanks for enhancing our observability over here, I feel like I'll be looking at things a little bit differently after this conversation. And thank all of you for tuning in to our wonderful afternoon of continuous live coverage here at AWS re:Ieinvent in fabulous Las Vegas, Nevada with Dave Vellante. I'm Savannah Peterson. We're theCUBE, the leading source for high tech coverage. (bright music)

>>Good afternoon and welcome back to the Classiest Show in Technology. This is the Cube we are at AWS Reinvent 2022 in Fabulous Sin City. That's why I've got my sequence on. We love a little Vegas, don't we? I'm joined by John Farer, another, another Vegas >>Fan. I don't have my sequence, I left it in my room. We're >>Gonna have to figure out how to get us 20 as soon as possible. What's been your biggest shock for you at the show so far? >>Well, I think the data story and security is so awesome. I love how that's front and center. If you look at the minutes of the keynote of Adamski, the CEO on day one, it's all bulked into data and security. All worked hand in hand. That's on top of already the innovation of their infrastructure. So I think you're gonna see a lot of interplay going on in this next segment. It's gonna tell a lot of that innovation story that's coming next. It's pretty awesome. >>It is pretty awesome, and I'm super excited. It's not only what we do here on the Cube, it's also in my show notes. We are gonna be geeking out for the next segment. Please welcome Paul and Puja. Wonderful to have you both here. Paul from Amazon, s3, glacier, and Pujan, CEO of kuo. I wanna turn to you Pujan, to start us off, just in case the audience isn't familiar, give us the Kuo pitch. >>Yeah, so basically Kuo is a, a backup as a service offering, right? Built in AWS four aws, right? And effectively going after, you know, any service that a customer uses on top of aws, right? And so a lot of the data sitting on s3, right? So that's been like our, our big use case going and basically building backup and air gap protection for, for s3. But we basically go to every other service, e c two, ebs, dynamo, you know, you name it, right? So basically do the whole thing >>And the relationship with aws. Can you guys share, I mean, you got you here together. You guys are a great partnership. Born in the cloud, operation in the cloud. Absolutely. I think talk about the partnership with aws. >>Absolutely. I think the last five years of building on AWS has been phenomenal, right? And I love the platform. It's, it's a very pure platform for us. You know, the APIs and, and the access you get and access you get to the service teams like Paul sitting here and the other teams you have gotten access to, I think has been phenomenal. But we also have, I would say, pushed the envelope in terms of how innovative we have been and how aggressive we have been in utilizing all the innovation that AWS has built in over the last few years. But it would not have happened without the fantastic partnership with the service teams. >>Paul, talk about the, AM the S3 part of this. What's the story there? >>Well, it's been great working with the CUO team over the course of the last few years. We were just upstairs diving deep into the, to the features that they're taking advantage of. They really push us hard on behalf of customers, and it's been a, it's just been a great relationship over the last years. >>That's awesome. And the ecosystem at such a, we're gonna hear tomorrow, the keynote on the, from Aruba who's gonna tend over the ecosystem. You guys are working together. There's a lot of strategic partnerships, so much collaboration between you guys that makes it very, this is the next gen cloud of cloud environment we're seeing. And you heard the, the economies around the corner. It's still gonna be challenging, but still there's more growth in the cloud. This is not stopping. This is impacts the customers. What are the customers saying to you guys when you work backwards from their needs? They want it faster, easier, cheaper. They want it more integrated. What are some of the things, all those you guys hearing from customers? >>So for us, you know, if you think about it, like, you know, as people are moving to the cloud, especially like take a use case like s3, right? So much of critical data sitting on top of S3 today. And so what folks have realized that as they're, you know, putting all of those, you know, what, over two 50 trillion objects, you know, sitting on s3, a lot of them need backup and data protection because there could be accidental deletions, there could be software bugs, there could be a ransomware type event due to which you need a second copy of the data that is outside of your security domain, right? But again, that needs to get be done at the, at the right price point, right? And that's where like a technology like Columbia comes in because since we've been built on the cloud, we've optimized it correctly. So especially for folks who are very cost conscious, given the macroeconomic conditions, we are heading into a technology that's built correctly so that, you know, you get the right architecture and the right solution at the right price point and the scale, right? Talking about trillions of objects, billions of objects within a single customer, within a single bucket sometimes. And that's where Columbia comes in. Cause we basically do that at scale without, again, impacting the, the customer's wallet more than it needs to. >>The porridge has to be the right temperature and the right size bowl. With the right spoon. You've got a lot of complexity when it comes to solving those customer challenges. You have a couple customer story examples you're allowed to share with us. Correct? Paul, do you want to kick one off? Go ahead. Oh, puja. All right. >>No, absolutely. I think there's a ton of them. I, I'll talk about, you know, want to begin with like Cox Automotive, right? A phenomenal customer that we, all of us have worked together with them. And again, looking for a solution to backup S3 to essentially go air gap protection outside of their account, right? They looked at doing it themselves, right? They thought they'll go and basically do it themselves. And then they fortunately bumped into Columbia, they looked at our architecture, looked at what it would really go and take to build it. And guess what, sitting in 2022, getting 23 right now, nobody wants to go and build this themselves. They actually want a turnkey solution that just does it, right? And so, again, we are a phenomenal joint customer of ours doing this at a pretty massive scale, right? And there are many more like that. There's Warner Brothers that are essentially going into the cloud from on premises, right? And they're going really fast accelerating the usage on aws again, looking at, you know, backup and data protection and using clum because of our extreme simplicity that we provide. >>Yeah, I think it's, you've got a, a lot of different people solving different problems that you're working with all the time. Millions of customers. Well, how do you prioritize? >>Well, for us, it really all comes down to fundamentals, right? So Amazon, s3 s unique distributed architecture delivers industry leading durability, availability, performance and security at virtually unlimited scale, right? And it's really been delivering on the fundamentals that has earned the trust of so many customers of all sizes and industries over the course of over 16 years. Now, in terms of how we prioritize on behalf of those customers, we always say that 90% of our roadmap comes directly from what customers are telling us is important. And a large number of our customers now are using S3 through lumino, which is why the relationship is so important. We're here talking about customer use cases here at the show, and we do that regularly throughout the year as well. And that's, that's how we land on a road. >>And what are the, what are the top stories from customers? What, what are they telling you? What's the number one top three things you're hearing? >>I tell you, like, again, it just comes down to the fundamentals, right? Of security, availability, durability and performance at virtually unlimited scale. Like that is the first customer first discussions that we have with customers talking about durable storage, for >>Sure. What I find interesting in, you mentioned scale, right? That comes up a lot scale with data. Yeah. That we heard data. The big theme here, security, what's in my S3 bucket? Can you find out what's in there? Is it backed up properly? How do I get it back? Where's the ransomware? Why not just target the ransomware? So how do you navigate the, the security challenges, the, the need to store all that scale data? What's the secret sauce? >>Yeah, so I think the, the big thing is we'll start with the, you know, how we have architected the product, right? If you think about it, this, you're dealing with a lot of scale, right? You get to a hundred million, a billion and billions very fast on S3 few, especially on a cloud native application. So it starts with the visibility, right? It's basically about, like we have things where you do, where you create a subset of your buckets called protection groups that you can essentially, you know, do it based on prefixes. So now you can essentially figure out what prefix you want to back up and what you don't want to back up. Maybe there's log data that you don't care about, so you don't back that up, right? And it all starts with that visibility that you give. And the prefix level data protection then comes the scale, which is where I was telling you, right? We have basically built an orchestration engine, right? It's like we call the ES for Lambdas, right? So we have a internal orchestration engine and essentially what what we have done is we have our own language internally that spawns off these lambdas, right? And they go after these S3 partitions do the right things and then you basically reel them back. So things like that that we do that are not possible if you're not built on the >>Clock. Well also, I mean, just mind blowing and go back 10 years. Yeah. I mean you got Lambda. What you're talking about here is the gift of the cloud innovation. Yeah. So the benefit of S3 is now accelerated. This is the story this year. Yeah. I mean they're highlighting it at scale, not just in the data, but like what we knew when Lambda came out and what S3 could do. But now mainstream solutions are coming in. Does that change your backup plans? Because we're gonna see a lot more end to end, lot more solutions. We heard that on the keynote. Some are saying it's more complexity. Of course it might, but you can abstract another way with the cloud that's the best part of the cloud. So these abstraction leads. So what's your view on that? But I wanna get your thoughts because you guys are perfectly positioned for this scale, but there's more coming. Yes. Yes. Exactly. What, how are you looking at that? >>So again, I think the, you know, obviously the, the S3 teams and every team in AWS is basically pushing the envelope in terms of innovation. But the key for a partner like us is to go and take that innovation. A lot of complex architectures behind the scene. But what you deliver to the customer is simple. I'll give you one more example. One of the things we launched that, you know, Paul and others are very excited about, is this ability to do instant access on the backup, right? So you could have billions of objects that you backed up. Maybe you need just 10,000 of them for a DR test. And we can basically create like an instant virtual bucket on top of that backup that you can instantly restore >>Spinning up a sandbox of temporary data to go check it >>Out. Exactly. Offer an inte application. >>Think we're geeking out right now. >>Yeah, I know. Brought that part of the segment, John. Don't worry, we're safely there. But, >>But that's the thing, right? That all that is possible because of all the, the scale and innovation and all the APIs and everything that, you know, Paul and the team gives us that we go and build on top of >>Paul, geek out on with us on this. We >>Are super excited for instant restore >>For store. I mean, automation programmability. >>It is, I mean it's the logical next step for backup in the cloud. Exactly. Yeah. But it's a super hard engineering problem to go solve for customers. I mean, the RTO benefits alone are super compelling, but then there's a cost element as well of not having to bring back all that stuff for a test restore, for example. And so it's, it's been really great to, to work with the team on that. We have some ideas on how we may help solve it from our side, and we're looking forward to collaborating on it. >>This is a great illustration of what I was writing about this week around the classic cloud, which is great. And as Adam said, and used like to use the word and, and you got this new functionality we're seeing emerge from the growth. Yes. From the companies that are built on Amazon web services that are growing. You're a partner, they have a lot of other partners and people are taking over restaurant here off action. I mean, there's real growth and new functionality on top of aws. You guys are no different. What's, are you prepared for that? Are you ready to go? >>Yeah, no, absolutely. And I think if you think about, if you think about it, right, I think it's also about doing this without impacting the primary application. Like if the customer is running a primary application at scale on s3, a backup application like ours can't come in and really mess with that. So I think being able to do things where, and this is where you solve really hard computer science problems, right? Where you're bottling yourself. If you are essentially seeing any kind of, you know, interfering with the primary, you're going to cut yourself down. You're gonna go after a different partition. So there are a lot of things you need to do behind the scenes, which is again, all the complexity, all of that, but deliver the, to the customer a very, very simple thing. >>You know, Paul, I wanna get your thoughts and I want you to chime in. Yeah. In 2014, I interviewed Steven Schmidt, my first interview with the, he was the CISO then, and now he's a CSO and, and former ciso, he's back at that time, the word was the cloud's not secure. Now we're talking about security. Just in the complexity of how you're partitioning and managing your sub portions, how you explained it, it's harder for the attackers. The cloud in its in its architecture has become a more secure environment. Yeah. Well, and getting more secure as you have laying out this, this is a new dynamic. This is good. Can you explain the, >>I mean, I, I can just tell you that at AWS security is job zero and that it will always be our number one priority, right? We have a, an infrastructure with under AWS that is vetted and approved to run even top secret workloads, which benefits all customers in all regions. >>And your, your security posture is embedded on top of that. And you got your own stuff. >>Yeah. And if you think of it as a shared responsibility model, so security of the cloud is the responsibility of the cloud provider, but then security of the data on top of it. Like you, you go and delete stuff, your software goes and does something that resiliency, the integrity of the data is your responsibility as a customer. And that's where, you know, we come in. Who >>Shared responsibility has been such a hot topic all week. Yeah. >>I gotta ask him one more question. Cause this is fascinating. And we are talking about on the cube all day today after we saw the announcement and Adam's comment on the cube, Adams LE's comment on the keynote. I mean, he said, if you're gonna tighten your belt, meaning economic cost recovery, re right sizing. If you want to tighten your belt, come to the cloud. So I have to ask you guys, Puja, if you can comment, that'd be great. There's a lot of other competitors out there that aren't born on aws. What is the customer gonna do when they tighten the build? What does that mean? They're gonna go to, to the individual contracts. They're gonna work in the marketplace. I mean this, there's a new dynamic in town. It's called AWS 2022. They weren't really around much in the recession of 2008. They were just starting to grow. Now they're an economic force. People like yourselves have embedded in there. There's a lot of competition. What's gonna happen? >>I think people are gonna just go to a place like, you know, AWS marketplace. You're going to essentially look for solutions and essentially like, and, and the right solutions built in are going to be self-service like aws. It's a very self-service thing. A hundred percent. So you go and do self-service, you figure out what's working, what's not working. Also, the model has to be consumption oriented. No longer can you expect the customer to go and pay a bunch of money for shelfware, right? It's like, like how we charge how AWS charges, which is you pay for what you consume. That and all has to be front and center, >>Right? I think that's a really, I think that's a really important >>Point. It's time >>And I think it's time. So we have a new challenge on the cube. We give you 30 seconds roughly to give us your extraordinarily hot take your shining thought leadership moment and, and highlight what you think is the most important takeaway from the show. The biggest soundbite, the juiciest announcement. Paul, I'll >>Start with an Instagram. Real basically. Yeah. Okay. >>Yeah. Hi. Go. I would just say from an S3 perspective, over the course of the last several years, we've really seen workloads shift from just backup and recovery and static images on websites to data lake analytics applications. And you continue to see that here. And I can tell you that some of these scaled applications are running at enormous mind blowing scale, right? And so, so every year we come here, we talk to customers, and it's just every year it sort of blows me away. And I've been in the storage industry for a long time and it's just is, it blows me away. Just the scale at customers are running in >>And >>Blowing scale. And when it comes to backup, let me just say that it's easy to back up and recover a single object, but doing an easy thing, a billion or 10 billion times over, that's actually quite hard. >>And just to, just to bold that a little bit, just pull out my highlighter. S3 now has over 280 trillion objects. That's a lot. >>That's a lot of objects. >>Yeah. You are not, you are not kidding. When you talk about scale, I mean, this is the most scalable. >>That's not solution's not there. Yeah. That, that's right. And we wake up every, we have a culture of durability and we wake up every single day to raise the bar on the fundamentals and make sure that every single one of those objects is protected and safe. >>Okay. You, I, >>I can't imagine worrying about two, two 80 trillion different things. >>Let's go. You're Instagram real >>For me again, you know, between S3 and us, we are two players out there that are really, you know, processing the data at the end of the day, right? And so I'm very excited about, you know, what we are going to do more and more with the instant restore capability where we can integrate third party services on top of it that can do more things with the data that is not, not passively sitting, but now becomes active data that you can analyze and do things with. So that's something where we take this to the next level is something that I'm super excited about. >>There's a lot to be excited about and, and we're excited to have you. We're excited to hear what happens next. Excited to see more collaboration like this. Paul Pon, thank you so much for joining us here on the show. Thank all of you from for tuning into our continuous wall to wall super thrilling live coverage of AWS reinvent here in fabulous Las Vegas, Nevada, with John Furrier. I'm Savannah Peterson. We're the cube, the leading source for high tech coverage.

(upbeat music) >> Hello, everyone and welcome back to fabulous Las Vegas, Nevada, where we are here on the show floor at AWS re:Invent. We are theCUBE. I am Savannah Peterson, joined with John Furrier. John, afternoon, day two, we are in full swing. >> Yes. >> What's got you most excited? >> Just got lunch, got the food kicking in. No, we don't get coffee. (Savannah laughing) >> Way to bring the hype there, John. >> No, there's so many people here just in Amazon. We're back to 2019 levels of crowd. The interest levels are high. Next gen, cloud security, big part of the keynote. This next segment, I am super excited about. CUBE Alumni, going back to 2013, 10 years ago he was on theCUBE. Now, 10 years later we're at re:Invent, looking forward to this guest and it's about security, great topic. >> I don't want to delay us anymore, please welcome Mark. Mark, thank you so much for being here with us. Massive day for you and the team. I know you oversee three different units at Amazon, Inspector, Detective, and the most recently announced, Security Lake. Tell us about Amazon Security Lake. >> Well, thanks Savannah. Thanks John for having me. Well, Security Lake has been in the works for a little bit of time and it got announced today at the keynote as you heard from Adam. We're super excited because there's a couple components that are really unique and valuable to our customers within Security Lake. First and foremost, the foundation of Security Lake is an open source project we call OCFS, Open Cybersecurity Framework Schema. And what that allows is us to work with the vendor community at large in the security space and develop a language where we can all communicate around security data. And that's the language that we put into Security Data Lake. We have 60 vendors participating in developing that language and partnering within Security Lake. But it's a communal lake where customers can bring all of their security data in one place, whether it's generated in AWS, they're on-prem, or SaaS offerings or other clouds, all in one location in a language that allows analytics to take advantage of that analytics and give better outcomes for our customers. >> So Adams Selipsky big keynote, he spent all the bulk of his time on data and security. Obviously they go well together, we've talked about this in the past on theCUBE. Data is part of security, but this security's a little bit different in the sense that the global footprint of AWS makes it uniquely positioned to manage some security threats, EKS protection, a very interesting announcement, runtime layer, but looking inside and outside the containers, probably gives extra telemetry on some of those supply chains vulnerabilities. This is actually a very nuanced point. You got Guard Duty kind of taking its role. What does it mean for customers 'cause there's a lot of things in this announcement that he didn't have time to go into detail. Unpack all the specifics around what the security announcement means for customers. >> Yeah, so we announced four items in Adam's keynote today within my team. So I'll start with Guard Duty for EKS runtime. It's complimenting our existing capabilities for EKS support. So today Inspector does vulnerability assessment on EKS or container images in general. Guard Duty does detections of EKS workloads based on log data. Detective does investigation and analysis based on that log data as well. With the announcement today, we go inside the container workloads. We have more telemetry, more fine grain telemetry and ultimately we can provide better detections for our customers to analyze risks within their container workload. So we're super excited about that one. Additionally, we announced Inspector for Lambda. So Inspector, we released last year at re:Invent and we focused mostly on EKS container workloads and EC2 workloads. Single click automatically assess your environment, start generating assessments around vulnerabilities. We've added Lambda to that capability for our customers. The third announcement we made was Macy sampling. So Macy has been around for a while in delivering a lot of value for customers providing information around their sensitive data within S3 buckets. What we found is many customers want to go and characterize all of the data in their buckets, but some just want to know is there any sensitive data in my bucket? And the sampling feature allows the customer to find out their sensitive data in the bucket, but we don't have to go through and do all of the analysis to tell you exactly what's in there. >> Unstructured and structured data. Any data? >> Correct, yeah. >> And the fourth? >> The fourth, Security Data Lake? (John and Savannah laughing) Yes. >> Okay, ocean theme. data lake. >> Very complimentary to all of our services, but the unique value in the data lake is that we put the information in the customer's control. It's in their S3 bucket, they get to decide who gets access to it. We've heard from customers over the years that really have two options around gathering large scale data for security analysis. One is we roll our own and we're security engineers, we're not data engineers. It's really hard for them to build these distributed systems at scale. The second one is we can pick a vendor or a partner, but we're locked in and it's in their schemer and their format and we're there for a long period of time. With Security Data Lake, they get the best of both worlds. We run the infrastructure at scale for them, put the data in their control and they get to decide what use case, what partner, what tool gives them the most value on top of their data. >> Is that always a good thing to give the customers too much control? 'Cause you know the old expression, you give 'em a knife they play with and they they can cut themselves, I mean. But no, seriously, 'cause what's the provisions around that? Because control was big part of the governance, how do you manage the security? How does the customer worry about, if I have too much control, someone makes a mistake? >> Well, what we finding out today is that many customers have realized that some of their data has been replicated seven times, 10 times, not necessarily maliciously, but because they have multiple vendors that utilize that data to give them different use cases and outcomes. It becomes costly and unwieldy to figure out where all that data is. So by centralizing it, the control is really around who has access to the data. Now, ultimately customers want to make those decisions and we've made it simple to aggregate this data in a single place. They can develop a home region if they want, where all the data flows into one region, they can distribute it globally. >> They're in charge. >> They're in charge. But the controls are mostly in the hands of the data governance person in the company, not the security analyst. >> So I'm really curious, you mentioned there's 60 AWS partner companies that have collaborated on the Security lake. Can you tell us a little bit about the process? How long does it take? Are people self-selecting to contribute to these projects? Are you cherry picking? What does that look like? >> It's a great question. There's three levels of collaboration. One is around the open source project that we announced at Black Hat early in this year called OCSF. And that collaboration is we've asked the vendor community to work with us to build a schema that is universally acceptable to security practitioners, not vendor specific and we've asked. >> Savannah: I'm sorry to interrupt you, but is this a first of its kind? >> There's multiple schemes out there developed by multiple parties. They've been around for multiple years, but they've been built by a single vendor. >> Yeah, that's what I'm drill in on a little bit. It sounds like the first we had this level of collaboration. >> There's been collaborations around them, but in a handful of companies. We've really gone to a broad set of collaborators to really get it right. And they're focused around areas of expertise that they have knowledge in. So the EDR vendors, they're focused around the scheme around EDR. The firewall vendors are focused around that area. Certainly the cloud vendors are in their scope. So that's level one of collaboration and that gets us the level playing field and the language in which we'll communicate. >> Savannah: Which is so important. >> Super foundational. Then the second area is around producers and subscribers. So many companies generate valuable security data from the tools that they run. And we call those producers the publishers and they publish the data into Security Lake within that OCSF format. Some of them are in the form of findings, many of them in the form of raw telemetry. Then the second one is in the subscriber side and those are usually analytic vendors, SIM vendors, XDR vendors that take advantage of the logs in one place and generate analytic driven outcomes on top of that, use cases, if you will, that highlight security risks or issues for customers. >> Savannah: Yeah, cool. >> What's the big customer focus when you start looking at Security Lakes? How do you see that planning out? You said there's a collaboration, love the open source vibe on that piece, what data goes in there? What's sharing? 'Cause a big part of the keynote I heard today was, I heard clean rooms, I've cut my antenna up. I'd love to hear that. That means there's an implied sharing aspect. The security industry's been sharing data for a while. What kind of data's in that lake? Give us an example, take us through. >> Well, this a number of sources within AWS, as customers run their workloads in AWS. We've identified somewhere around 25 sources that will be natively single click into Amazon Security Lake. We were announcing nine of them. They're traditional network logs, BBC flow, cloud trail logs, firewall logs, findings that are generated across AWS, EKS audit logs, RDS data logs. So anything that customers run workloads on will be available in data lake. But that's not limited to AWS. Customers run their environments hybridly, they have SaaS applications, they use other clouds in some instances. So it's open to bring all that data in. Customers can vector it all into this one single location if they decide, we make it pretty simple for them to do that. Again, in the same format where outcomes can be generated quickly and easily. >> Can you use the data lake off on premise or it has to be in an S3 in Amazon Cloud? >> Today it's in S3 in Amazon. If we hear customers looking to do something different, as you guys know, we tend to focus on our customers and what they want us to do, but they've been pretty happy about what we've decided to do in this first iteration. >> So we got a story about Silicon Angle. Obviously the ingestion is a big part of it. The reporters are jumping in, but the 53rd party sources is a pretty big number. Is that coming from the OCSF or is that just in general? Who's involved? >> Yeah, OCSF is the big part of that and we have a list of probably 50 more that want to join in part of this. >> The other big names are there, Cisco, CrowdStrike, Peloton Networks, all the big dogs are in there. >> All big partners of AWS, anyway, so it was an easy conversation and in most cases when we started having the conversation, they were like, "Wow, this has really been needed for a long time." And given our breadth of partners and where we sit from our customers perspective in the center of their cloud journey that they've looked at us and said, "You guys, we applaud you for driving this." >> So Mark, take us through the conversations you're having with the customers at re:Inforce. We saw a lot of meetings happening. It was great to be back face to face. You guys have been doing a lot of customer conversation, security Data Lake came out of that. What was the driving force behind it? What were some of the key concerns? What were the challenges and what's now the opportunity that's different? >> We heard from our customers in general. One, it's too hard for us to get all the data we need in a single place, whether through AWS, the industry in general, it's just too hard. We don't have those resources to data wrangle that data. We don't know how to pick schema. There's multiple ones out there. Tell us how we would do that. So these three challenges came out front and center for every customer. And mostly what they said is our resources are limited and we want to focus those resources on security outcomes and we have security engines. We don't want to focus them on data wrangling and large scale distributed systems. Can you help us solve that problem? And it came out loud and clear from almost every customer conversation we had. And that's where we took the challenge. We said, "Okay, let's build this data layer." And then on top of that we have services like Detective and Guard Duty, we'll take advantage of it as well. But we also have a myriad of ISV third parties that will also sit on top of that data and render out. >> What's interesting, I want to get your reaction. I know we don't have much time left, but I want to get your thoughts. When I see Security Data Lake, which is awesome by the way, love the focus, love how you guys put that together. It makes me realize the big thing in re:Invent this year is this idea of specialized solutions. You got instances for this and that, use cases that require certain kind of performance. You got the data pillars that Adam laid out. Are we going to start seeing more specialized data lakes? I mean, we have a video data lake. Is there going to be a FinTech data lake? Is there going to be, I mean, you got the Great Lakes kind of going on here, what is going on with these lakes? I mean, is that a trend that Amazon sees or customers are aligning to? >> Yeah, we have a couple lakes already. We have a healthcare lake and a financial lake and now we have a security lake. Foundationally we have Lake Formation, which is the tool that anyone can build a lake. And most of our lakes run on top of Lake Foundation, but specialize. And the specialization is in the data aggregation, normalization, enridgement, that is unique for those use cases. And I think you'll see more and more. >> John: So that's a feature, not a bug. >> It's a feature, it's a big feature. The customers have ask for it. >> So they want roll their own specialized, purpose-built data thing, lake? They can do it. >> And customer don't want to combine healthcare information with security information. They have different use cases and segmentation of the information that they care about. So I think you'll see more. Now, I also think that you'll see where there are adjacencies that those lakes will expand into other use cases in some cases too. >> And that's where the right tools comes in, as he was talking about this ETL zero, ETL feature. >> It be like an 80, 20 rule. So if 80% of the data is shared for different use cases, you can see how those lakes would expand to fulfill multiple use cases. >> All right, you think he's ready for the challenge? Look, we were on the same page. >> Okay, we have a new challenge, go ahead. >> So think of it as an Instagram Reel, sort of your hot take, your thought leadership moment, the clip we're going to come back to and reference your brilliance 10 years down the road. I mean, you've been a CUBE veteran, now CUBE alumni for almost 10 years, in just a few weeks it'll be that. What do you think is, and I suspect, I think I might know your answer to this, so feel free to be robust in this. But what do you think is the biggest story, key takeaway from the show this year? >> We're democratizing security data within Security Data Lake for sure. >> Well said, you are our shortest answer so far on theCUBE and I absolutely love and respect that. Mark, it has been a pleasure chatting with you and congratulations, again, on the huge announcement. This is such an exciting day for you all. >> Thank you Savannah, thank you John, pleasure to be here. >> John: Thank you, great to have you. >> We look forward to 10 more years of having you. >> Well, maybe we don't have to wait 10 years. (laughs) >> Well, more years, in another time. >> I have a feeling it'll be a lot of security content this year. >> Yeah, pretty hot theme >> Very hot theme. >> Pretty odd theme for us. >> Of course, re:Inforce will be there this year again, coming up 2023. >> All the res. >> Yep, all the res. >> Love that. >> We look forward to see you there. >> All right, thanks, Mark. >> Speaking of res, you're the reason we are here. Thank you all for tuning in to today's live coverage from AWS re:Invent. We are in Las Vegas, Nevada with John Furrier. My name is Savannah Peterson. We are theCUBE and we are the leading source for high tech coverage. (upbeat music)

>>Good morning fellow nerds and welcome back to AWS Reinvent. We are live from the show floor here in Las Vegas, Nevada. My name is Savannah Peterson, joined with my fabulous co-host John Furrier. Day two keynotes are rolling. >>Yeah. What do you thinking this? This is the day where everything comes, so the core gets popped off the bottle, all the announcements start flowing out tomorrow. You hear machine learning from swee lot more in depth around AI probably. And then developers with Verner Vos, the CTO who wrote the seminal paper in in early two thousands around web service that becames. So again, just another great year of next level cloud. Big discussion of data in the keynote bulk of the time was talking about data and business intelligence, business transformation easier. Is that what people want? They want the easy button and we're gonna talk a lot about that in this segment. I'm really looking forward to this interview. >>Easy button. We all want the >>Easy, we want the easy button. >>I love that you brought up champagne. It really feels like a champagne moment for the AWS community as a whole. Being here on the floor feels a bit like the before times. I don't want to jinx it. Our next guest, Scott Castle, from Si Sense. Thank you so much for joining us. How are you feeling? How's the show for you going so far? Oh, >>This is exciting. It's really great to see the changes that are coming in aws. It's great to see the, the excitement and the activity around how we can do so much more with data, with compute, with visualization, with reporting. It's fun. >>It is very fun. I just got a note. I think you have the coolest last name of anyone we've had on the show so far, castle. Oh, thank you. I'm here for it. I'm sure no one's ever said that before, but I'm so just in case our audience isn't familiar, tell us about >>Soy Sense is an embedded analytics platform. So we're used to take the queries and the analysis that you can power off of Aurora and Redshift and everything else and bring it to the end user in the applications they already know how to use. So it's all about embedding insights into tools. >>Embedded has been a, a real theme. Nobody wants to, it's I, I keep using the analogy of multiple tabs. Nobody wants to have to leave where they are. They want it all to come in there. Yep. Now this space is older than I think everyone at this table bis been around since 1958. Yep. How do you see Siente playing a role in the evolution there of we're in a different generation of analytics? >>Yeah, I mean, BI started, as you said, 58 with Peter Lu's paper that he wrote for IBM kind of get became popular in the late eighties and early nineties. And that was Gen one bi, that was Cognos and Business Objects and Lotus 1 23 think like green and black screen days. And the way things worked back then is if you ran a business and you wanted to get insights about that business, you went to it with a big check in your hand and said, Hey, can I have a report? And they'd come back and here's a report. And it wasn't quite right. You'd go back and cycle, cycle, cycle and eventually you'd get something. And it wasn't great. It wasn't all that accurate, but it's what we had. And then that whole thing changed in about two, 2004 when self-service BI became a thing. And the whole idea was instead of going to it with a big check in your hand, how about you make your own charts? >>And that was totally transformative. Everybody started doing this and it was great. And it was all built on semantic modeling and having very fast databases and data warehouses. Here's the problem, the tools to get to those insights needed to serve both business users like you and me and also power users who could do a lot more complex analysis and transformation. And as the tools got more complicated, the barrier to entry for everyday users got higher and higher and higher to the point where now you look, look at Gartner and Forester and IDC this year. They're all reporting in the same statistic. Between 10 and 20% of knowledge workers have learned business intelligence and everybody else is just waiting in line for a data analyst or a BI analyst to get a report for them. And that's why the focus on embedded is suddenly showing up so strong because little startups have been putting analytics into their products. People are seeing, oh my, this doesn't have to be hard. It can be easy, it can be intuitive, it can be native. Well why don't I have that for my whole business? So suddenly there's a lot of focus on how do we embed analytics seamlessly? How do we embed the investments people make in machine learning in data science? How do we bring those back to the users who can actually operationalize that? Yeah. And that's what Tysons does. Yeah. >>Yeah. It's interesting. Savannah, you know, data processing used to be what the IT department used to be called back in the day data processing. Now data processing is what everyone wants to do. There's a ton of data we got, we saw the keynote this morning at Adam Lesky. There was almost a standing of vision, big applause for his announcement around ML powered forecasting with Quick Site Cube. My point is people want automation. They want to have this embedded semantic layer in where they are not having all the process of ETL or all the muck that goes on with aligning the data. All this like a lot of stuff that goes on. How do you make it easier? >>Well, to be honest, I, I would argue that they don't want that. I think they, they think they want that, cuz that feels easier. But what users actually want is they want the insight, right? When they are about to make a decision. If you have a, you have an ML powered forecast, Andy Sense has had that built in for years, now you have an ML powered forecast. You don't need it two weeks before or a week after in a report somewhere. You need it when you're about to decide do I hire more salespeople or do I put a hundred grand into a marketing program? It's putting that insight at the point of decision that's important. And you don't wanna be waiting to dig through a lot of infrastructure to find it. You just want it when you need it. What's >>The alternative from a time standpoint? So real time insight, which is what you're saying. Yep. What's the alternative? If they don't have that, what's >>The alternative? Is what we are currently seeing in the market. You hire a bunch of BI analysts and data analysts to do the work for you and you hire enough that your business users can ask questions and get answers in a timely fashion. And by the way, if you're paying attention, there's not enough data analysts in the whole world to do that. Good luck. I am >>Time to get it. I really empathize with when I, I used to work for a 3D printing startup and I can, I have just, I mean, I would call it PTSD flashbacks of standing behind our BI guy with my list of queries and things that I wanted to learn more about our e-commerce platform in our, in our marketplace and community. And it would take weeks and I mean this was only in 2012. We're not talking 1958 here. We're talking, we're talking, well, a decade in, in startup years is, is a hundred years in the rest of the world life. But I think it's really interesting. So talk to us a little bit about infused and composable analytics. Sure. And how does this relate to embedded? Yeah. >>So embedded analytics for a long time was I want to take a dashboard I built in a BI environment. I wanna lift it and shift it into some other application so it's close to the user and that is the right direction to go. But going back to that statistic about how, hey, 10 to 20% of users know how to do something with that dashboard. Well how do you reach the rest of users? Yeah. When you think about breaking that up and making it more personalized so that instead of getting a dashboard embedded in a tool, you get individual insights, you get data visualizations, you get controls, maybe it's not even actually a visualization at all. Maybe it's just a query result that influences the ordering of a list. So like if you're a csm, you have a list of accounts in your book of business, you wanna rank those by who's priorities the most likely to churn. >>Yeah. You get that. How do you get that most likely to churn? You get it from your BI system. So how, but then the question is, how do I insert that back into the application that CSM is using? So that's what we talk about when we talk about Infusion. And SI started the infusion term about two years ago and now it's being used everywhere. We see it in marketing from Click and Tableau and from Looker just recently did a whole launch on infusion. The idea is you break this up into very small digestible pieces. You put those pieces into user experiences where they're relevant and when you need them. And to do that, you need a set of APIs, SDKs, to program it. But you also need a lot of very solid building blocks so that you're not building this from scratch, you're, you're assembling it from big pieces. >>And so what we do aty sense is we've got machine learning built in. We have an LQ built in. We have a whole bunch of AI powered features, including a knowledge graph that helps users find what else they need to know. And we, we provide those to our customers as building blocks so that they can put those into their own products, make them look and feel native and get that experience. In fact, one of the things that was most interesting this last couple of couple of quarters is that we built a technology demo. We integrated SI sensee with Office 365 with Google apps for business with Slack and MS teams. We literally just threw an Nlq box into Excel and now users can go in and say, Hey, which of my sales people in the northwest region are on track to meet their quota? And they just get the table back in Excel. They can build charts of it and PowerPoint. And then when they go to their q do their QBR next week or week after that, they just hit refresh to get live data. It makes it so much more digestible. And that's the whole point of infusion. It's bigger than just, yeah. The iframe based embedding or the JavaScript embedding we used to talk about four or five years >>Ago. APIs are very key. You brought that up. That's gonna be more of the integration piece. How does embedable and composable work as more people start getting on board? It's kind of like a Yeah. A flywheel. Yes. What, how do you guys see that progression? Cause everyone's copying you. We see that, but this is a, this means it's standard. People want this. Yeah. What's next? What's the, what's that next flywheel benefit that you guys coming out with >>Composability, fundamentally, if you read the Gartner analysis, right, they, when they talk about composable, they're talking about building pre-built analytics pieces in different business units for, for different purposes. And being able to plug those together. Think of like containers and services that can, that can talk to each other. You have a composition platform that can pull it into a presentation layer. Well, the presentation layer is where I focus. And so the, so for us, composable means I'm gonna have formulas and queries and widgets and charts and everything else that my, that my end users are gonna wanna say almost minority report style. If I'm not dating myself with that, I can put this card here, I can put that chart here. I can set these filters here and I get my own personalized view. But based on all the investments my organization's made in data and governance and quality so that all that infrastructure is supporting me without me worrying much about it. >>Well that's productivity on the user side. Talk about the software angle development. Yeah. Is your low code, no code? Is there coding involved? APIs are certainly the connective tissue. What's the impact to Yeah, the >>Developer. Oh. So if you were working on a traditional legacy BI platform, it's virtually impossible because this is an architectural thing that you have to be able to do. Every single tool that can make a chart has an API to embed that chart somewhere. But that's not the point. You need the life cycle automation to create models, to modify models, to create new dashboards and charts and queries on the fly. And be able to manage the whole life cycle of that. So that in your composable application, when you say, well I want chart and I want it to go here and I want it to do this and I want it to be filtered this way you can interact with the underlying platform. And most importantly, when you want to use big pieces like, Hey, I wanna forecast revenue for the next six months. You don't want it popping down into Python and writing that yourself. >>You wanna be able to say, okay, here's my forecasting algorithm. Here are the inputs, here's the dimensions, and then go and just put it somewhere for me. And so that's what you get withy sense. And there aren't any other analytics platforms that were built to do that. We were built that way because of our architecture. We're an API first product. But more importantly, most of the legacy BI tools are legacy. They're coming from that desktop single user, self-service, BI environment. And it's a small use case for them to go embedding. And so composable is kind of out of reach without a complete rebuild. Right? But with SI senses, because our bread and butter has always been embedding, it's all architected to be API first. It's integrated for software developers with gi, but it also has all those low code and no code capabilities for business users to do the minority report style thing. And it's assemble endless components into a workable digital workspace application. >>Talk about the strategy with aws. You're here at the ecosystem, you're in the ecosystem, you're leading product and they have a strategy. We know their strategy, they have some stuff, but then the ecosystem goes faster and ends up making a better product in most of the cases. If you compare, I know they'll take me to school on that, but I, that's pretty much what we report on. Mongo's doing a great job. They have databases. So you kind of see this balance. How are you guys playing in the ecosystem? What's the, what's the feedback? What's it like? What's going on? >>AWS is actually really our best partner. And the reason why is because AWS has been clear for many, many years. They build componentry, they build services, they build infrastructure, they build Redshift, they build all these different things, but they need, they need vendors to pull it all together into something usable. And fundamentally, that's what Cient does. I mean, we didn't invent sequel, right? We didn't invent jackal or dle. These are not, these are underlying analytics technologies, but we're taking the bricks out of the briefcase. We're assembling it into something that users can actually deploy for their use cases. And so for us, AWS is perfect because they focus on the hard bits. The the underlying technologies we assemble those make them usable for customers. And we get the distribution. And of course AWS loves that. Cause it drives more compute and it drives more, more consumption. >>How much do they pay you to say that >>Keynote, >>That was a wonderful pitch. That's >>Absolutely, we always say, hey, they got a lot of, they got a lot of great goodness in the cloud, but they're not always the best at the solutions and that they're trying to bring out, and you guys are making these solutions for customers. Yeah. That resonates with what they got with Amazon. For >>Example, we, last year we did a, a technology demo with Comprehend where we put comprehend inside of a semantic model and we would compile it and then send it back to Redshift. And it takes comprehend, which is a very cool service, but you kind of gotta be a coder to use it. >>I've been hear a lot of hype about the semantic layer. What is, what is going on with that >>Semantec layer is what connects the actual data, the tables in your database with how they're connected and what they mean so that a user like you or me who's saying I wanna bar chart with revenue over time can just work with revenue and time. And the semantic layer translates between what we did and what the database knows >>About. So it speaks English and then they converts it to data language. It's >>Exactly >>Right. >>Yeah. It's facilitating the exchange of information. And, and I love this. So I like that you actually talked about it in the beginning, the knowledge map and helping people figure out what they might not know. Yeah. I, I am not a bi analyst by trade and I, I don't always know what's possible to know. Yeah. And I think it's really great that you're doing that education piece. I'm sure, especially working with AWS companies, depending on their scale, that's gotta be a big part of it. How much is the community play a role in your product development? >>It's huge because I'll tell you, one of the challenges in embedding is someone who sees an amazing experience in outreach or in seismic. And to say, I want that. And I want it to be exactly the way my product is built, but I don't wanna learn a lot. And so you, what you want do is you want to have a community of people who have already built things who can help lead the way. And our community, we launched a new version of the SES community in early 2022 and we've seen a 450% growth in the c in that community. And we've gone from an average of one response, >>450%. I just wanna put a little exclamation point on that. Yeah, yeah. That's awesome. We, >>We've tripled our organic activity. So now if you post this Tysons community, it used to be, you'd get one response maybe from us, maybe from from a customer. Now it's up to three. And it's continuing to trend up. So we're, it's >>Amazing how much people are willing to help each other. If you just get in the platform, >>Do it. It's great. I mean, business is so >>Competitive. I think it's time for the, it's time. I think it's time. Instagram challenge. The reels on John. So we have a new thing. We're gonna run by you. Okay. We just call it the bumper sticker for reinvent. Instead of calling it the Instagram reels. If we're gonna do an Instagram reel for 30 seconds, what would be your take on what's going on this year at Reinvent? What you guys are doing? What's the most important story that you would share with folks on Instagram? >>You know, I think it's really what, what's been interesting to me is the, the story with Redshift composable, sorry. No, composable, Redshift Serverless. Yeah. One of the things I've been >>Seeing, we know you're thinking about composable a lot. Yes. Right? It's, it's just, it's in there, it's in your mouth. Yeah. >>So the fact that Redshift Serverless is now kind becoming the defacto standard, it changes something for, for my customers. Cuz one of the challenges with Redshift that I've seen in, in production is if as people use it more, you gotta get more boxes. You have to manage that. The fact that serverless is now available, it's, it's the default means it now people are just seeing Redshift as a very fast, very responsive repository. And that plays right into the story I'm telling cuz I'm telling them it's not that hard to put some analysis on top of things. So for me it's, it's a, maybe it's a narrow Instagram reel, but it's an >>Important one. Yeah. And that makes it better for you because you get to embed that. Yeah. And you get access to better data. Faster data. Yeah. Higher quality, relevant, updated. >>Yep. Awesome. As it goes into that 80% of knowledge workers, they have a consumer great expectation of experience. They're expecting that five ms response time. They're not waiting 2, 3, 4, 5, 10 seconds. They're not trained on theola expectations. And so it's, it matters a lot. >>Final question for you. Five years out from now, if things progress the way they're going with more innovation around data, this front end being very usable, semantic layer kicks in, you got the Lambda and you got serverless kind of coming in, helping out along the way. What's the experience gonna look like for a user? What's it in your mind's eye? What's that user look like? What's their experience? >>I, I think it shifts almost every role in a business towards being a quantitative one. Talking about, Hey, this is what I saw. This is my hypothesis and this is what came out of it. So here's what we should do next. I, I'm really excited to see that sort of scientific method move into more functions in the business. Cuz for decades it's been the domain of a few people like me doing strategy, but now I'm seeing it in CSMs, in support people and sales engineers and line engineers. That's gonna be a big shift. Awesome. >>Thank >>You Scott. Thank you so much. This has been a fantastic session. We wish you the best at si sense. John, always pleasure to share the, the stage with you. Thank you to everybody who's attuning in, tell us your thoughts. We're always eager to hear what, what features have got you most excited. And as you know, we will be live here from Las Vegas at reinvent from the show floor 10 to six all week except for Friday. We'll give you Friday off with John Furrier. My name's Savannah Peterson. We're the cube, the the, the leader in high tech coverage.

from the cube studios in Palo Alto in Boston bringing you data-driven insights from the cube and ETR this is breaking analysis with Dave vellante the ascendancy of AWS under the leadership of Andy jassy was marked by a tsunami of data and corresponding cloud services to leverage that data now those Services they mainly came in the form of Primitives I.E basic building blocks that were used by developers to create more sophisticated capabilities AWS in the 2020s being led by CEO Adam solipski will be marked by four high-level Trends in our opinion one A Rush of data that will dwarf anything we've previously seen two a doubling or even tripling down on the basic elements of cloud compute storage database security Etc three a greater emphasis on end-to-end integration of AWS services to simplify and accelerate customer adoption of cloud and four significantly deeper business integration of cloud Beyond it as an underlying element of organizational operations hello and welcome to this week's wikibon Cube insights powered by ETR in this breaking analysis we extract and analyze nuggets from John furrier's annual sit-down with the CEO of AWS we'll share data from ETR and other sources to set the context for the market and competition in cloud and we'll give you our glimpse of what to expect at re invent in 2022. now before we get into the core of our analysis Alibaba has announced earnings they always announced after the big three you know a month later and we've updated our Q3 slash November hyperscale Computing forecast for the year as seen here and we're going to spend a lot of time on this as most of you have seen the bulk of it already but suffice to say alibaba's cloud business is hitting that same macro Trend that we're seeing across the board but a more substantial slowdown than we expected and more substantial than its peers they're facing China headwinds they've been restructuring its Cloud business and it's led to significantly slower growth uh in in the you know low double digits as opposed to where we had it at 15 this puts our year-end estimates for 2022 Revenue at 161 billion still a healthy 34 growth with AWS surpassing 80 billion in 2022 Revenue now on a related note one of the big themes in Cloud that we've been reporting on is how customers are optimizing their Cloud spend it's a technique that they use and when the economy looks a little shaky and here's a graphic that we pulled from aws's website which shows the various pricing plans at a high level as you know they're much more granular than that and more sophisticated but Simplicity we'll just keep it here basically there are four levels first one here is on demand I.E pay by the drink now we're going to jump down to what we've labeled as number two spot instances that's like the right place at the right time I can use that extra capacity in the moment the third is reserved instances or RIS where I pay up front to get a discount and the fourth is sort of optimized savings plans where customers commit to a one or three year term and for a better price now you'll notice we labeled the choices in a different order than AWS presented them on its website and that's because we believe that the order that we chose is the natural progression for customers this started on demand they maybe experiment with spot instances they move to reserve instances when the cloud bill becomes too onerous and if you're large enough you lock in for one or three years okay the interesting thing is the order in which AWS presents them we believe that on-demand accounts for the majority of AWS customer spending now if you think about it those on-demand customers they're also at risk customers yeah sure there's some switching costs like egress and learning curve but many customers they have multiple clouds and they've got experience and so they're kind of already up to a learning curve and if you're not married to AWS with a longer term commitment there's less friction to switch now AWS here presents the most attractive plan from a financial perspective second after on demand and it's also the plan that makes the greatest commitment from a lock-in standpoint now In fairness to AWS it's also true that there is a trend towards subscription-based pricing and we have some data on that this chart is from an ETR drill down survey the end is 300. pay attention to the bars on the right the left side is sort of busy but the pink is subscription and you can see the trend upward the light blue is consumption based or on demand based pricing and you can see there's a steady Trend toward subscription now we'll dig into this in a later episode of Breaking analysis but we'll share with you a little some tidbits with the data that ETR provides you can select which segment is and pass or you can go up the stack Etc but so when you choose is and paths 44 of customers either prefer or are required to use on-demand pricing whereas around 40 percent of customers say they either prefer or are required to use subscription pricing again that's for is so now the further mu you move up the stack the more prominent subscription pricing becomes often with sixty percent or more for the software-based offerings that require or prefer subscription and interestingly cyber security tracks along with software at around 60 percent that that prefer subscription it's likely because as with software you're not shutting down your cyber protection on demand all right let's get into the expectations for reinvent and we're going to start with an observation in data in this 2018 book seeing digital author David michella made the point that whereas most companies apply data on the periphery of their business kind of as an add-on function successful data companies like Google and Amazon and Facebook have placed data at the core of their operations they've operationalized data and they apply machine intelligence to that foundational element why is this the fact is it's not easy to do what the internet Giants have done very very sophisticated engineering and and and cultural discipline and this brings us to reinvent 2022 in the future of cloud machine learning and AI will increasingly be infused into applications we believe the data stack and the application stack are coming together as organizations build data apps and data products data expertise is moving from the domain of Highly specialized individuals to Everyday business people and we are just at the cusp of this trend this will in our view be a massive theme of not only re invent 22 but of cloud in the 2020s the vision of data mesh We Believe jamachtagani's principles will be realized in this decade now what we'd like to do now is share with you a glimpse of the thinking of Adam solipsky from his sit down with John Furrier each year John has a one-on-one conversation with the CEO of AWS AWS he's been doing this for years and the outcome is a better understanding of the directional thinking of the leader of the number one Cloud platform so we're now going to share some direct quotes I'm going to run through them with some commentary and then bring in some ETR data to analyze the market implications here we go this is from solipsky quote I.T in general and data are moving from departments into becoming intrinsic parts of how businesses function okay we're talking here about deeper business integration let's go on to the next one quote in time we'll stop talking about people who have the word analyst we inserted data he meant data data analyst in their title rather will have hundreds of millions of people who analyze data as part of their day-to-day job most of whom will not have the word analyst anywhere in their title we're talking about graphic designers and pizza shop owners and product managers and data scientists as well he threw that in I'm going to come back to that very interesting so he's talking about here about democratizing data operationalizing data next quote customers need to be able to take an end-to-end integrated view of their entire data Journey from ingestion to storage to harmonizing the data to being able to query it doing business Intelligence and human-based Analysis and being able to collaborate and share data and we've been putting together we being Amazon together a broad Suite of tools from database to analytics to business intelligence to help customers with that and this last statement it's true Amazon has a lot of tools and you know they're beginning to become more and more integrated but again under jassy there was not a lot of emphasis on that end-to-end integrated view we believe it's clear from these statements that solipsky's customer interactions are leading him to underscore that the time has come for this capability okay continuing quote if you have data in one place you shouldn't have to move it every time you want to analyze that data couldn't agree more it would be much better if you could leave that data in place avoid all the ETL which has become a nasty three-letter word more and more we're building capabilities where you can query that data in place end quote okay this we see a lot in the marketplace Oracle with mySQL Heatwave the entire Trend toward converge database snowflake [ __ ] extending their platforms into transaction and analytics respectively and so forth a lot of the partners are are doing things as well in that vein let's go into the next quote the other phenomenon is infusing machine learning into all those capabilities yes the comments from the michelleographic come into play here infusing Ai and machine intelligence everywhere next one quote it's not a data Cloud it's not a separate Cloud it's a series of broad but integrated capabilities to help you manage the end-to-end life cycle of your data there you go we AWS are the cloud we're going to come back to that in a moment as well next set of comments around data very interesting here quote data governance is a huge issue really what customers need is to find the right balance of their organization between access to data and control and if you provide too much access then you're nervous that your data is going to end up in places that it shouldn't shouldn't be viewed by people who shouldn't be viewing it and you feel like you lack security around that data and by the way what happens then is people overreact and they lock it down so that almost nobody can see it it's those handcuffs there's data and asset are reliability we've talked about that for years okay very well put by solipsky but this is a gap in our in our view within AWS today and we're we're hoping that they close it at reinvent it's not easy to share data in a safe way within AWS today outside of your organization so we're going to look for that at re invent 2022. now all this leads to the following statement by solipsky quote data clean room is a really interesting area and I think there's a lot of different Industries in which clean rooms are applicable I think that clean rooms are an interesting way of enabling multiple parties to share and collaborate on the data while completely respecting each party's rights and their privacy mandate okay again this is a gap currently within AWS today in our view and we know snowflake is well down this path and databricks with Delta sharing is also on this curve so AWS has to address this and demonstrate this end-to-end data integration and the ability to safely share data in our view now let's bring in some ETR spending data to put some context around these comments with reference points in the form of AWS itself and its competitors and partners here's a chart from ETR that shows Net score or spending momentum on the x-axis an overlap or pervasiveness in the survey um sorry let me go back up the net scores on the y-axis and overlap or pervasiveness in the survey is on the x-axis so spending momentum by pervasiveness okay or should have share within the data set the table that's inserted there with the Reds and the greens that informs us to how the dots are positioned so it's Net score and then the shared ends are how the plots are determined now we've filtered the data on the three big data segments analytics database and machine learning slash Ai and we've only selected one company with fewer than 100 ends in the survey and that's databricks you'll see why in a moment the red dotted line indicates highly elevated customer spend at 40 percent now as usual snowflake outperforms all players on the y-axis with a Net score of 63 percent off the charts all three big U.S cloud players are above that line with Microsoft and AWS dominating the x-axis so very impressive that they have such spending momentum and they're so large and you see a number of other emerging data players like rafana and datadog mongodbs there in the mix and then more established players data players like Splunk and Tableau now you got Cisco who's gonna you know it's a it's a it's a adjacent to their core networking business but they're definitely into you know the analytics business then the really established players in data like Informatica IBM and Oracle all with strong presence but you'll notice in the red from the momentum standpoint now what you're going to see in a moment is we put red highlights around databricks Snowflake and AWS why let's bring that back up and we'll explain so there's no way let's bring that back up Alex if you would there's no way AWS is going to hit the brakes on innovating at the base service level what we call Primitives earlier solipsky told Furrier as much in their sit down that AWS will serve the technical user and data science Community the traditional domain of data bricks and at the same time address the end-to-end integration data sharing and business line requirements that snowflake is positioned to serve now people often ask Snowflake and databricks how will you compete with the likes of AWS and we know the answer focus on data exclusively they have their multi-cloud plays perhaps the more interesting question is how will AWS compete with the likes of Specialists like Snowflake and data bricks and the answer is depicted here in this chart AWS is going to serve both the technical and developer communities and the data science audience and through end-to-end Integrations and future services that simplify the data Journey they're going to serve the business lines as well but the Nuance is in all the other dots in the hundreds or hundreds of thousands that are not shown here and that's the AWS ecosystem you can see AWS has earned the status of the number one Cloud platform that everyone wants to partner with as they say it has over a hundred thousand partners and that ecosystem combined with these capabilities that we're discussing well perhaps behind in areas like data sharing and integrated governance can wildly succeed by offering the capabilities and leveraging its ecosystem now for their part the snowflakes of the world have to stay focused on the mission build the best products possible and develop their own ecosystems to compete and attract the Mind share of both developers and business users and that's why it's so interesting to hear solipski basically say it's not a separate Cloud it's a set of integrated Services well snowflake is in our view building a super cloud on top of AWS Azure and Google when great products meet great sales and marketing good things can happen so this will be really fun to watch what AWS announces in this area at re invent all right one other topic that solipsky talked about was the correlation between serverless and container adoption and you know I don't know if this gets into there certainly their hybrid place maybe it starts to get into their multi-cloud we'll see but we have some data on this so again we're talking about the correlation between serverless and container adoption but before we get into that let's go back to 2017 and listen to what Andy jassy said on the cube about serverless play the clip very very earliest days of AWS Jeff used to say a lot if I were starting Amazon today I'd have built it on top of AWS we didn't have all the capability and all the functionality at that very moment but he knew what was coming and he saw what people were still able to accomplish even with where the services were at that point I think the same thing is true here with Lambda which is I think if Amazon were starting today it's a given they would build it on the cloud and I think we with a lot of the applications that comprise Amazon's consumer business we would build those on on our serverless capabilities now we still have plenty of capabilities and features and functionality we need to add to to Lambda and our various serverless services so that may not be true from the get-go right now but I think if you look at the hundreds of thousands of customers who are building on top of Lambda and lots of real applications you know finra has built a good chunk of their market watch application on top of Lambda and Thompson Reuters has built you know one of their key analytics apps like people are building real serious things on top of Lambda and the pace of iteration you'll see there will increase as well and I really believe that to be true over the next year or two so years ago when Jesse gave a road map that serverless was going to be a key developer platform going forward and so lipsky referenced the correlation between serverless and containers in the Furrier sit down so we wanted to test that within the ETR data set now here's a screen grab of The View across 1300 respondents from the October ETR survey and what we've done here is we've isolated on the cloud computing segment okay so you can see right there cloud computing segment now we've taken the functions from Google AWS Lambda and Microsoft Azure functions all the serverless offerings and we've got Net score on the vertical axis we've got presence in the data set oh by the way 440 by the way is highly elevated remember that and then we've got on the horizontal axis we have the presence in the data center overlap okay that's relative to each other so remember 40 all these guys are above that 40 mark okay so you see that now what we're going to do this is just for serverless and what we're going to do is we're going to turn on containers to see the correlation and see what happens so watch what happens when we click on container boom everything moves to the right you can see all three move to the right Google drops a little bit but all the others now the the filtered end drops as well so you don't have as many people that are aggressively leaning into both but all three move to the right so watch again containers off and then containers on containers off containers on so you can see a really major correlation between containers and serverless okay so to get a better understanding of what that means I call my friend and former Cube co-host Stu miniman what he said was people generally used to think of VMS containers and serverless as distinctly different architectures but the lines are beginning to blur serverless makes things simpler for developers who don't want to worry about underlying infrastructure as solipsky and the data from ETR indicate serverless and containers are coming together but as Stu and I discussed there's a spectrum where on the left you have kind of native Cloud VMS in the middle you got AWS fargate and in the rightmost anchor is Lambda AWS Lambda now traditionally in the cloud if you wanted to use containers developers would have to build a container image they have to select and deploy the ec2 images that they or instances that they wanted to use they have to allocate a certain amount of memory and then fence off the apps in a virtual machine and then run the ec2 instances against the apps and then pay for all those ec2 resources now with AWS fargate you can run containerized apps with less infrastructure management but you still have some you know things that you can you can you can do with the with the infrastructure so with fargate what you do is you'd build the container images then you'd allocate your memory and compute resources then run the app and pay for the resources only when they're used so fargate lets you control the runtime environment while at the same time simplifying the infrastructure management you gotta you don't have to worry about isolating the app and other stuff like choosing server types and patching AWS does all that for you then there's Lambda with Lambda you don't have to worry about any of the underlying server infrastructure you're just running code AS functions so the developer spends their time worrying about the applications and the functions that you're calling the point is there's a movement and we saw in the data towards simplifying the development environment and allowing the cloud vendor AWS in this case to do more of the underlying management now some folks will still want to turn knobs and dials but increasingly we're going to see more higher level service adoption now re invent is always a fire hose of content so let's do a rapid rundown of what to expect we talked about operate optimizing data and the organization we talked about Cloud optimization there'll be a lot of talk on the show floor about best practices and customer sharing data solipsky is leading AWS into the next phase of growth and that means moving beyond I.T transformation into deeper business integration and organizational transformation not just digital transformation organizational transformation so he's leading a multi-vector strategy serving the traditional peeps who want fine-grained access to core services so we'll see continued Innovation compute storage AI Etc and simplification through integration and horizontal apps further up to stack Amazon connect is an example that's often cited now as we've reported many times databricks is moving from its stronghold realm of data science into business intelligence and analytics where snowflake is coming from its data analytics stronghold and moving into the world of data science AWS is going down a path of snowflake meet data bricks with an underlying cloud is and pass layer that puts these three companies on a very interesting trajectory and you can expect AWS to go right after the data sharing opportunity and in doing so it will have to address data governance they go hand in hand okay price performance that is a topic that will never go away and it's something that we haven't mentioned today silicon it's a it's an area we've covered extensively on breaking analysis from Nitro to graviton to the AWS acquisition of Annapurna its secret weapon new special specialized capabilities like inferential and trainium we'd expect something more at re invent maybe new graviton instances David floyer our colleague said he's expecting at some point a complete system on a chip SOC from AWS and maybe an arm-based server to eventually include high-speed cxl connections to devices and memories all to address next-gen applications data intensive applications with low power requirements and lower cost overall now of course every year Swami gives his usual update on machine learning and AI building on Amazon's years of sagemaker innovation perhaps a focus on conversational AI or a better support for vision and maybe better integration across Amazon's portfolio of you know large language models uh neural networks generative AI really infusing AI everywhere of course security always high on the list that reinvent and and Amazon even has reinforce a conference dedicated to it uh to security now here we'd like to see more on supply chain security and perhaps how AWS can help there as well as tooling to make the cio's life easier but the key so far is AWS is much more partner friendly in the security space than say for instance Microsoft traditionally so firms like OCTA and crowdstrike in Palo Alto have plenty of room to play in the AWS ecosystem we'd expect of course to hear something about ESG it's an important topic and hopefully how not only AWS is helping the environment that's important but also how they help customers save money and drive inclusion and diversity again very important topics and finally come back to it reinvent is an ecosystem event it's the Super Bowl of tech events and the ecosystem will be out in full force every tech company on the planet will have a presence and the cube will be featuring many of the partners from the serial floor as well as AWS execs and of course our own independent analysis so you'll definitely want to tune into thecube.net and check out our re invent coverage we start Monday evening and then we go wall to wall through Thursday hopefully my voice will come back we have three sets at the show and our entire team will be there so please reach out or stop by and say hello all right we're going to leave it there for today many thanks to Stu miniman and David floyer for the input to today's episode of course John Furrier for extracting the signal from the noise and a sit down with Adam solipski thanks to Alex Meyerson who was on production and manages the podcast Ken schiffman as well Kristen Martin and Cheryl Knight helped get the word out on social and of course in our newsletters Rob hoef is our editor-in-chief over at siliconangle does some great editing thank thanks to all of you remember all these episodes are available as podcasts wherever you listen you can pop in the headphones go for a walk just search breaking analysis podcast I published each week on wikibon.com at siliconangle.com or you can email me at david.valante at siliconangle.com or DM me at di vallante or please comment on our LinkedIn posts and do check out etr.ai for the best survey data in the Enterprise Tech business this is Dave vellante for the cube insights powered by ETR thanks for watching we'll see it reinvent or we'll see you next time on breaking analysis [Music]

>>Good morning and welcome back to Detroit, Michigan. My name is Savannah Peterson and I'm here on set of the cube, my co-host John Farer. How you doing this morning, John? >>Doing great. Feeling fresh. Day two of three days of coverage, feeling >>Fresh. That is that for being in the heat of the conference. I love that attitude. It's gonna >>Be a great day today. We'll see you at the end of the day. Yeah, >>Well, we'll hold him to it. All right, everyone hold 'em accountable. Very excited to start the day off with an internet, a legend as well as a cube og. We are joined this morning by Matt Klein. Matt, welcome to the show. >>Thanks for having me. Good to see you. Yep. >>It's so, what's the vibe? Day two, Everyone's buzzing. What's got you excited at the show? You've been here before, but it's been three years you >>Mentioned. I, I was saying it's been three years since I've been to a conference, so it's been interesting for me to see what is, what is the same and what is different pre and post covid. But just really great to see everyone here again and nice to not be sitting in my home by myself. >>You know, Savannah said you're an OG and we were referring before we came on camera that you were your first came on the Cub in 2017, second Cuban event. But you were, I think, on the first wave of what I call the contributor momentum, where CNCF really got the traction. Yeah. You were at Lift, Envoy was contributed and that was really hyped up and I remember that vividly. It was day zero they called it back then. Yeah. And you got so much traction. People are totally into it. Yeah. Now we've got a lot of that going on now. Right. A lot of, lot of day Zero events. They call 'em co, co-located events. You got web assembly, a lot of other hype out there. What do you see out there that you like? How would you look at some of these other Sure. Communities that are developing, What's the landscape look like as you look out? Because Envoy set the table, what is now a standard >>Practice. Yeah. What's been so interesting for me just to come here to the conference is, you know, we open source Envoy in 2016. We donated in 2017. And as you mentioned at that time, Envoy was, you know, everyone wanted to talk about Envoy. And you know, much to my amazement, Envoy is now pervasive. I mean, it's used everywhere around the world. It's like, never in my wildest dreams would I have imagined that it would be so widely used. And it's almost gotten to the point where it's become boring. You know, It's just assumed that Envoy is, is everywhere. And now we're hearing a lot about Eeb p f and Web assembly and GI ops and you know, AI and a bunch of other things. So it's, it's actually great. It's made me very happy that it's become so pervasive, but it's also fun. Yeah. We mention to, to look around all other stuff >>Like congratulate. It's just a huge accomplishment really. I think it's gonna be historic, historical moment for the industry too. But I like how it progressed. I mean, I don't mind hype cycles as long as it's some vetting. Sure. Of course. You know, use cases that are clearly defined, but you gotta get that momentum in the community, but then you start gotta get down to, to business. Yep. So, so to speak and get it deployed, get traction. Yep. What should projects look like? And, and give us the update on Envoy. Cause you guys have a, a great use case of how you got traction. Right. Take us through some of the early days of what made Envoy successful in your opinion. Great question. >>Yeah. You know, I, I think Envoy is fairly unique around this conference in the sense that Envoy was developed by Lyft, which is an end user company. And many of the projects in this ecosystem, you know, no judgment, for better or worse, they are vendor backed. And I think that's a different delivery mechanism when it's coming from an end user where you're solving a, a particular business case. So Envoy was really developed for Lyft in a, you know, very early scaling days and just, you know, trying to help Lyft solve its business problems. So I think when Envoy was developed, we were, you know, scaling, we were falling over and actually many other companies were having similar problems. So I think Envoy became very widely deployed because many companies were having similar issues. So Envoy just became pervasive among lift peer companies. And then we saw a lot of vendor uptake in the service mesh space in the API gateway space among large internet providers. So, I I I, I think it's just, it's an interesting case because I think when you're solving real problems on the ground, in some ways it's easier to actually get adoption than if you're trying to develop it from a commercial backing. >>And that's the class, I mean, almost, It's almost like open source product market fit. It is in its own way. Cause you have a problem. Absolutely. Other people have the same problem finding >>Too. I mean, it's, it's designed thinking from >>A different, When, when I talk to people about open source, I like to tell people that I do not think it's any different than starting a company. I actually think it's all the same problems finding pro product, market fit, hiring, like finding contributors and maintainers, like doing PR and marketing. Yeah. Getting team together, traction, getting, getting funding. I mean, you have to have money to do all these things. Yeah. So I think a lot of people think of open source as I, I don't know, you know, this fantastic collaborative effort and, and it is that, but there's a lot more to it. Yeah. And it is much more akin to starting a >>Company. Let's, let's just look at that for a second. Cause I think that's a good point. And I was having a conversation in the hallway two nights ago on this exact point. If the power dynamics of a startup in the open source, as you point out, is just different, it's community based. So there are things you just gotta be mindful of. It's not top down. >>Exactly. It's not like, >>Right. You know, go take that hill. It's really consensus based, but it is a startup. All those elements are in place. Absolutely. You need leadership, you gotta have debates, alignment, commit, You gotta commit to a vision. Yep. You gotta make adjustments. Build the trajectory. So based on that, I mean, do you see more end user traction? Cause I was, we were talking also about Intuit, they donated some of their tow code R goes out there. Yep. R go see the CDR goes a service. Where's the end user contributions to these days? Do you feel like it's good, still healthy? >>I, I mean, I, I'm, I'm biased. I would like to see more. I think backstage outta Spotify is absolutely fantastic. That's an area just in terms of developer portals and developer efficiency that I think has been very underserved. So seeing Backstage come outta Spotify where they've used it for years, and I think we've already seen they had a huge date, you know, day one event. And I, I think we're gonna see a lot more out of that >>Coming from, I'm an end user, pretend I'm an end user, so pretend I have some code. I want to, Oh man, I'm scared. I don't am I'm gonna lose my competitive edge. What's the, how do you talk to the enterprise out there that might be thinking about putting their project out there for whether it's the benefit of the community, developing talent, developing the product? >>Sure. Yeah. I would say that I, I would ask everyone to think through all of the pros and cons of doing that because it's not for free. I mean, doing open source is costly. It takes developer time, you know, it takes management time, it takes budgeting dollars. But the benefits if successful can be huge, right? I mean, it can be just in terms of, you know, getting people into your company, getting users, getting more features, all of that. So I would always encourage everyone to take a very pragmatic and realistic view of, of what is required to make that happen. >>What was that decision like at Lyft >>When you I I'm gonna be honest, it was very naive. I I think we've, of that we think we need to know. No, just didn't know. Yeah. I think a lot of us, myself included, had very minimal open source experience. And had we known, or had I known what would've happened, I, I still would've done it. But I, I'm gonna be honest, the last seven years have aged me what I feel like is like 70 or a hundred. It's been a >>But you say you look out in the landscape, you gotta take pride, look at what's happened. Oh, it's, I mean, it's like you said, it >>Matured fantastic. I would not trade it for anything, but it has, it has been a journey. What >>Was the biggest surprise? What was the most eye opening thing about the journey for you? >>I, I think actually just the recognition of all of the non-technical things that go into making these things a success. I think at a conference like this, people think a lot about technology. It is a technology conference, but open source is business. It really is. I mean, it, it takes money to keep it going. It takes people to keep >>It going. You gotta sell people on the concepts. >>It takes leadership to keep it going. It takes internal, it takes marketing. Yeah. So for me, what was most eyeopening is over the last five to seven years, I feel like I actually have not developed very many, if any technical skills. But my general leadership skills, you know, that would be applicable again, to running a business have applied so well to, to >>Growing off, Hey, you put it out there, you hear driving the ship. It's good to do that. They need that. It really needs it. And the results speak for itself and congratulations. Yeah. Thank you. What's the update on the project? Give us an update because you're seeing, seeing a lot of infrastructure people having the same problem. Sure. But it's also, the environments are a little bit different. Some people have different architectures. Absolutely different, more cloud, less cloud edges exploding. Yeah. Where does Envoy fit into the landscape they've seen and what's the updates? You've got some new things going on. Give the updates on what's going on with the project Sure. And then how it sits in the ecosystem vis-a-vis what people may use it for. >>Yeah. So I'm, from a core project perspective, honestly, things have matured. Things have stabilized a bit. So a lot of what we focus on now are less Big bang features, but more table stakes. We spend a lot of time on security. We spend a lot of time on software supply chain. A topic that you're probably hearing a lot about at this conference. We have a lot of software supply chain issues. We have shipped Quicken HTB three over the last year. That's generally available. That's a new internet protocol still work happening on web assembly where ha doing a lot of work on our build and release pipeline. Again, you would think that's boring. Yeah. But a lot of people want, you know, packages for their fedora or their ADU or their Docker images. And that takes a lot of effort. So a lot of what we're doing now is more table stakes, just realizing that the project is used around the world very widely. >>Yeah. The thing that I'm most interested in is, we announced in the last six months a project called Envoy Gateway, which is layered on top of Envoy. And the goal of Envoy Gateway is to make it easier for people to run Envoy within Kubernetes. So essentially as an, as an ingress controller. And Envoy is a project historically, it is a very sophisticated piece of software, very complicated piece of software. It's not for everyone. And we want to provide Envoy Gateway as a way of onboarding more users into the Envoy ecosystem and making Envoy the, the default API gateway or edge proxy within Kubernetes. But in terms of use cases, we see Envoy pervasively with service mesh, API gateway, other types of low balancing cases. I mean, honestly, it's, it's all over the place at >>This point. I'm curious because you mentioned it's expanded beyond your wildest dreams. Yeah. And how could you have even imagined what Envoy was gonna do? Is there a use case or an application that really surprised you? >>You know, I've been asked that before and I, it's hard for me to answer that. It's, it's more that, I mean, for example, Envoy is used by basically every major internet company in China. I mean, like, wow. Everyone in China uses Envoy, like TikTok, like Alibaba. I mean like everyone, all >>The large sale, >>Everyone. You know, and it's used, it's used in the, I'm just, it's not just even the us. So I, I think the thing that has surprised me more than individual use cases is just the, the worldwide adoption. You know, that something could be be everywhere. And that I think, you know, when I open my phone and I'm opening all of these apps on my phone, 80 or 90% of them are going through Envoy in some form. Yeah. You know, it's, it's just that pervasive, I blow your mind a little bit sometimes >>That does, that's why you say plumber on your Twitter handle as your title. Cause you're working on all these things that are like really important substrate issues, Right. For scale, stability, growth. >>And, you know, to, I, I guess the only thing that I would add is, my goal for Envoy has always been that it is that boring, transparent piece of technology. Kind of similar to Linux. Linux is everywhere. Right? But no one really knows that they're using Linux. It's, it's justs like Intel inside, we're not paying attention. It's just there, there's >>A core group working on, if they have pride, they understand the mission, the importance of it, and they make their job is to make it invisible. >>Right. Exactly. >>And that's really ease of use. What's some of the ease of use sways and, and simplicity that you're working on, if you can talk about that. Because to be boring, you gotta be simpler and easier. All boring complex is unique is not boring. Complex is stressful. No, >>I I think we approach it in a couple different ways. One of them is that because we view Envoy as a, as a base technology in the ecosystem, we're starting to see, you know, not only vendors, but other open source projects that are being built on top of Envoy. So things like API Gateway, sorry, Envoy Gateway or you know, projects like Istio or all the other projects that are out there. They use Envoy as a component, but in some sense Envoy is a, as a transparent piece of that system. Yeah. So I'm a big believer in the ecosystem that we need to continue to make cloud native easier for, for end users. I still think it's too complicated. And so I think we're there, we're, we're pushing up the stack a bit. >>Yeah. And that brings up a good point. When you start seeing people building on top of things, right? That's enabling. So as you look at the enablement of Envoy, what are some of the things you see out on the horizon if you got the 20 mile stare out as you check these boring boxes, make it more plumbing, Right? Stable. You'll have a disruptive enabling platform. Yeah. What do you see out there? >>I am, you know, I, again, I'm not a big buzzword person, but, so some people call it serverless functions as a service, whatever. I'm a big believer in platforms in the sense that I really believe in the next 10 to 15 years, developers, they want to provide code. You know, they want to call APIs, they want to use pub subsystems, they want to use cas and databases. And honestly, they don't care about container scheduling or networking or load balancing or any of >>These things. It's handled in the os >>They just want it to be part of the operating system. Yeah, exactly. So I, I really believe that whether it's an open source or in cloud provider, you know, package solutions, that we're going to be just moving increasingly towards systems likes Lambda and Fargate and Google Cloud Run and Azure functions and all those kinds of things. And I think that when you do that much of the functionality that has historically powered this conference like Kubernetes and Onvoy, these become critical but transparent components that people don't, they're not really aware of >>At that point. Yeah. And I think that's a great call out because one of the things we're seeing is the market forces of, of this evolution, what you just said is what has to happen Yep. For digital transformation to, to get to its conclusion. Yep. Which means that everything doesn't have to serve the business, it is the business. Right. You know it in the old days. Yep. Engineers, they serve the business. Like what does that even mean? Yep. Now, right. Developers are the business, so they need that coding environment. So for your statement to happen, that simplicity in visibility calling is invisible os has to happen. So it brings up the question in open source, the trend is things always work itself out on the wash, as we say. So when you start having these debates and the alignment has to come at some point, you can't get to those that stay without some sort of defacto or consensus. Yep. And even standards, I'm not a big be around hardcore standards, but we can all agree and have consensus Sure. That will align behind, say Kubernetes, It's Kubernetes a standard. It's not like an i e you know, but this next, what, what's your reaction to this? Because this alignment has to come after debate. So all the process contending for I am the this of that. >>Yeah. I'm a look, I mean, I totally see the value in like i e e standards and, and there's a place for that. At the same time, for me personally as a technologist, as an engineer, I prefer to let the, the market as it were sort out what are the defacto standards. So for example, at least with Envoy, Envoy has an API that we call Xds. Xds is now used beyond Envoy. It's used by gc, it's used by proprietary systems. And I'm a big believer that actually Envoy in its form is probably gonna go away before Xds goes away. So in some ways Xds has become a defacto standard. It's not an i e e standard. Yeah. We, we, we have been asked about whether we should do that. Yeah. But I just, I I think the >>It becomes a component. >>It becomes a component. Yeah. And then I think people gravitate towards these things that become de facto standards. And I guess I would rather let the people on the show floor decide what are the standards than have, you know, 10 people sitting in a room figure out >>The community define standards versus organizational institutional defined standards. >>And they both have places a >>Hundred percent. Yeah, sure. And, and there's social proof in both of them. Yep. >>Frankly, >>And we were saying on the cube that we believe that the developers will decide the standard. Sure. Because that's what you're basically saying. They're deciding what they do with their code. Right. And over time, as people realize the trade of, hey, if everyone's coding this right. And makes my life easier to get to that state of nirvana and enlightenment, as we would say. Yeah. Yeah. >>Starting strong this morning. John, I I love this. I'm curious, you mentioned Backstage by Spotify wonderful example. Do you think that this is a trend we're gonna see with more end users >>Creating open source projects? Like I, you know, I hope so. The flip side of that, and as we all know, we're entering an uncertain economic time and it can be hard to justify the effort that it takes to do it well. And what I typically counsel people when they are about to open source something is don't do it unless you're ready to commit the resources. Because opensourcing something and not supporting it. Yeah. I actually can be think, I think it'd be worse. >>It's an, it's insult that people, you're asking to commit to something. Exactly. Needs of time, need the money investment, you gotta go all in and push. >>So I, so I very much want to see it and, and I want to encourage that here, but it's hard for me to look into the crystal ball and know, you know, whether it's gonna happen more >>Or less at what point there were, are there too many projects? You know, I mean, but I'm not, I mean this in, in a, in a negative way. I mean it more in the way of, you know, you mentioned supply chain. We were riffing on the cube about at some point there's gonna be so much code open source continuing thundering away with, with the value that you're just gluing things. Right. I don't need the code, this code there. Okay. What's in the code? Okay. Maybe automation can help out on supply chain. Yeah. But ultimately composability is the new >>Right? It is. Yeah. And, and I think that's always going to be the case. Case. Good thing. It is good thing. And I, I think that's just, that's just the way of things for sure. >>So no code will be, >>I think, I think we're seeing a lot of no code situations that are working great for people. And, and, but this is actually really no different than my, than my serverless arguing from before. Just as a, as a, a slight digression. I'm building something new right now and you know, we're using cloud native technologies and all this stuff and it's still, >>What are you building? >>Even as a I'm, I'm gonna keep that, I'm gonna keep that secret. I know I'm, but >>We'll find out on Twitter. We're gonna find out now that we know it. Okay. Keep on mystery. You open that door. We're going down see in a couple weeks. >>Front >>Page is still an angle. >>But I, I was just gonna say that, you know, and I consider myself, you know, you're building something, I'm, I see myself an expert in the cloud native space. It's still difficult, It's difficult to, to pull together these technologies and I think that we will continue to make it easier for people. >>What's the biggest difficulties? Can you give us some examples? >>Well, just, I mean, we still live in a big mess of yammel, right? Is a, there's a, there's a lot of yaml out there. And I think just wrangling all of that in these systems, there's still a lot of cobbling together where I think that there can be unified platforms that make it easier for us to focus on our application logic. >>Yeah. I gotta ask you a question cuz I've talked to college kids all the time. My son's a junior in CS and he's, you know, he's coding away. What would you, how does a student or someone who's learning figure out where, who they are? Because there's now, you know, you're either into the infrastructure under the hood Yeah. Or you're, cuz that's coding there option now coding the way your infrastructure people are working on say the boring stuff so everyone else can have ease of use. And then what is just, I wanna just code, there's two types of personas. How does someone know who they are? >>My, when I give people career advice, my biggest piece of advice to them is in the first five to seven to 10 years of their career, I encourage people to do different things like every say one to two to three years. And that doesn't mean like quitting companies and changing companies, it could mean, you know, within a company that they join doing different teams, you know, working on front end versus back end. Because honestly I think people don't know. I think it's actually very, Yeah. Our industry is so broad. Yeah. That I think it's almost impossible to >>Know. You gotta get your hands dirty to jump >>In order to know what you like. And for me, in my career, you know, I've dabbled in different areas, but I've always come back to infrastructure, you know, that that's what I enjoy >>The most. Okay. You gotta, you gotta taste everything. See what you, what >>You like. Exactly. >>Right. Last question for you, Matt. It's been three years since you were here. Yep. What do you hope that we're able to say next year? That we can't say this year? Hmm. Beyond the secrets of your project, which hopefully we will definitely be discussing then. >>You know, I I, I don't have anything in particular. I would just say that I would like to see more movement towards projects that are synthesizing and making it easier to use a lot of the existing projects that we have today. So for example, I'm, I'm very bullish on backstage. Like I, I've, I've always said that we need better developer UIs that are not CLIs. Like I know it's a general perception among many people. Totally agree with you. Frankly, you're not a real systems engineer unless you type on the command line. I, I think better user interfaces are better for humans. Yep. So just for a project like Backstage to be more integrated with the rest of the projects, whether that be Envo or Kubernete or Argo or Flagger. I, I just, I think there's tremendous potential for further integration of some >>Of these projects. It just composability That makes total sense. Yep. Yep. You're, you're op you're operating and composing. >>Yep. And there's no reason that user experience can't be better. And then more people can create and build. So I think it's awesome. Matt, thank you so much. Thank you. Yeah, this has been fantastic. Be sure and check out Matt on Twitter to find out what that next secret project is. John, thank you for joining me this morning. My name is Savannah Peterson and we'll be here all day live from the cube. We hope you'll be joining us throughout the evening until a happy hour today. Thanks for coming. Thanks for coming. Thanks for watching.

>>Hello everyone. My name is Savannah Peterson, coming to you live from the Kim Con Show floor on the cube here in Detroit, Michigan. The energy is pulsing big event for the Cloud Native Foundation, and I'm joined by John Furrier on my left. John. Hello. >>Great, great, great to have you on the cube. Thanks for being our new host. You look great, Great segment coming up. I'm looking forward to this. Savannah, this is a great segment. A cube alumni, an OG in the cloud, native world or cloud aati. I, as I call it, been there, done that. A lot of respect, a lot of doing some really amazing, I call it the super cloud holy grail. But we'll see >>Your favorite word, >>This favorite word, It's a really strong segment. Looking forward to hearing from this guest. >>Yes, I am very excited and I'm gonna let him tee it up a little bit. But our guest and his project were actually mentioned in the opening keynote this morning, which is very, very exciting. Ladies and gentlemen, please welcome Baam Tobar Baam, thanks for being here with >>Us. Thank you guys. So good to be back here on the show and, and this exciting energy around us. So it was super, super awesome to be here. >>Yeah, it feels great. So let's start with the opening keynote. Did you know you were gonna get that shout out? >>No, not at all. I, it was, it was really cool to see, you know, I think Cruz was up there talking about how they were building their own platform for autonomous cars and what's running behind it. And they mentioned all these projects and you know, we were like, Wow, that sounds super familiar. And then, then, and then they said, Okay, yeah, we we're, you know, cross plane. They mentioned cross plane, they mentioned, Upbound mentioned the work that we're doing in this space to help folks effectively run, you know, their own layer on top of cloud computing. >>And then Tom, we've known each other, >>We're gonna do a bingo super cloud. So how many times is this Super cloud? So >>Super Cloud is super services, super apps around us. He enables a lot of great things that Brian Grace had a great podcast this week on super services. So it's super, super exciting, >>Super great time on the queue. Super, >>Super >>Cloud conversation. All seriously. Now we've known each other for a long time. You've been to every cub com, you've been in open source, you've seen the seen where it's been, where it is now. Super exciting that in mainstream conversations we're talking about super cloud extractions and around interoperability. Things that were once like really hard to do back, even back on the opens stack days. Now we're at a primetime spot where the control plane, the data planes are in play as a viable architectural component of all the biggest conversations. Yeah, you're in the middle of it. What's your take on it? Give some perspective of why this is so important. >>I mean, look, the key here is to standardize, right? Get to standardization, right? And, and what we saw, like early days of cloud native, it was mostly around Kubernetes, but it was Kubernetes as a, you know, essentially a container orchestrator, the container of wars, Docker, Mesos, et cetera. And then Kubernetes emerged as a, a, the winner in containers, right? But containers is a workload, one kind of workload. It's, I run containers on it, not everything's containers, right? And the, you know, what we're seeing now is the Kubernetes API is emerging as a way to standardize on literally everything in cloud. Not just containers, but you know, VMs, serverless, Lambda, et cetera, storage databases that all using a common approach, a common API layer, a common way to do access control, a common way to do policy, all built around open source projects and you know, the cloud data of ecosystem that you were seeing around here. And that's exciting cuz we've, for the first time we're arriving at some kind of standardization. >>Every major inflection point has this defacto standard evolution, then it becomes kind of commonplace. Great. I agree with Kubernetes. The question I wanted to ask you is what's the impact to the DevOps community? DevSecOps absolutely dominated the playbook, if you will. Developers we're saying we'll run companies cuz they'll be running the applications. It's not a department anymore. Yes, it is the business. If you believe the digital transformation finds its final conclusion, which it will at some point. So more developers doing more, ask more stuff. >>Look, if you, I'd be hard pressed to find somebody that's has a title of DevOps or SRE that can't at least spell Kubernetes, if not running in production, right? And so from that perspective, I think this is a welcome change. Standardize on something that's already familiar to everyone is actually really powerful. They don't have to go, Okay, we learned Kubernetes, now you guys are taking us down a different path of standardization. Or something else has emerged. It's the same thing. It's like we have what, eight years now of cloud native roughly. And, and people in the DevOps space welcome a change where they are basically standardizing on things that are working right? They're actually working right? And they could be used in more use cases, in more scenarios than they're actually, you know, become versatile. They become, you know, ubiquitous as >>You will take a minute to just explain what you guys are selling and doing. What's the product, what's the traction, why are people using you? What's the big, big mo position value statement you guys think? >>Yeah, so, so, so the, my company's called Upbound and where the, where the folks behind the, the cross plane project and cross plane is effective, takes Kubernetes and extends it to beyond containers and to ev managing everything in cloud, right? So if you think about that, if you love the model where you're like, I, I go to Kubernetes cluster and I tell it to run a bunch of containers and it does it for me and I walk away, you can do that for the rest of the surface area of cloud, including your VMs and your storage and across cloud vendors, hybrid models, All of it works in a consistent standardized way, you know, using crossline, right? And I found >>What do you solve? What do you solve or eliminate? What happens? Why does this work? Are you replacing something? Are you extracting away something? Are you changing >>Something? I think we're layering on top of things that people have, right? So, so you'll see people are organized differently. We see a common pattern now where there's shared services teams or platform teams as you hear within enterprises that are responsible for basically managing infrastructure and offering a self-service experience to developers, right? Those teams are all about standardization. They're all about creating things that help them reduce the toil, manage things in a common way, and then offer self-service abstractions to their, you know, developers and customers. So they don't have to be in the middle of every request. Things can go faster. We're seeing a pattern now where the, these teams are standardizing on the Kubernetes API or standardizing on cross plane and standardizing on things that make their life easier, right? They don't have to replace what they're doing, they just have to layer and use it. And I layer it's probably a, an opening for you that makes it sound >>More complex, I think, than what you're actually trying to do. I mean, you as a company are all about velocity as an ethos, which I think is great. Do you think that standardization is the key in increasing velocity for teams leveraging both cross claim, Kubernetes? Anyone here? >>Look, I mean, everybody's trying to achieve the same thing. Everybody wants to go faster, they want to innovate faster. They don't want tech to be the friction to innovation, right? Right. They want, they wanna go from feature to production in minutes, right? And so, or less to that extent, standardization is a way to achieve that. It's not the only way to achieve that. It's, it's means to achieve that. And if you've standardized, that means that less people are involved. You can automate more, you can st you can centralize. And by doing that, that means you can innovate faster. And if you don't innovate these days, you're in trouble. Yeah. You're outta business. >>Do you think that, so Kubernetes has a bit of a reputation for complexity. You're obviously creating a tool that makes things easier as you apply Kubernetes outside just an orchestration and container environment. Do you, what do you see those advantages being across the spectrum of tools that people are leveraging you >>For? Yeah, I mean, look, if Kubernetes is a platform, right? To build other things on top of, and as a, as a result, it's something that's used to kind of on the back end. Like you would never, you should put something in front of Kubernetes as an application model or consumption interface of portals or Right, Yeah. To give zero teams. But you should still capture all your policies, you know, automation and compliance governance at the Kubernetes layer, right? At the, or with cross plane at that layer as well, right? Right. And so if you follow that model, you can get the best of world both worlds. You standardize, you centralize, you are able to have, you know, common controls and policies and everything else, but you can expose something that's a dev friendly experience on top of as well. So you get the both, both the best of both worlds. >>So the problem with infrastructure is code you're saying is, is that it's not this new layer to go across environments. Does that? No, >>Infrastructure is code works slightly differently. I mean, you, you can, you can write, you know, infrastructures, codes using whatever tooling you like to go across environments. The problem with is that everybody has to learn a specific language or has to work with understanding the constructs. There's the beauty of the Kubernetes based approach and the cross playing best approach is that it puts APIs first, right? It's basically saying, look, kind of like the API meant that it, that led to AWS being created, right? Teams should interact with APIs. They're super strong contracts, right? They're visionable. Yeah. And if you, if you do that and that's kind of the power of this approach, then you can actually reach a really high level of automation and a really high level of >>Innovation. And this also just not to bring in the clouds here, but this might bring up the idea that common services create interoperability, but yet the hyper scale clouds could still differentiate on value very much faster processors if it's silicon to better functions if glam, right? I mean, so there's still, it's not killing innovation. >>It is not, And in fact I, you know, this idea of building something that looks like the lowest common denominator across clouds, we don't actually see that in practice, right? People want, people want to use the best services available to them because they don't have time to go, you know, build portability layers and everything else. But they still, even in that model want to standardize on how to call these services, how to set policy on them, how to set access control, how to actually invoke them. If you can standardize on that, you can still, you get the, you get to use these services and you get the benefits of standardization. >>Well Savannah, we were talking about this, about the Berkeley paper that came out in May, which is kind of a super cloud version they call sky computing. Their argument is that if you try to standardize too much like the old kind of OSI model back in the day, you actually gonna, the work innovations gonna stunt the growth. Do you agree with that? And how do you see, because standardization is not so much a spec and it it, it e f thing. It's not an i e committee. Yeah. It's not like that's kind of standard. It's more of defacto, >>I mean look, we've had standards emerge like, you know, if you look at my S SQL for example, and the Postgres movement, like there are now lots of vendors that offer interfaces that support Postgres even though they're differentiated completely on how it's implement. So you see that if you can stick to open interfaces and use services that offer them that tons of differentiation yet still, you know, some kind of open interface if you will. But there are also differentiated services that are, don't have open interfaces and that's okay too. As long as you're able to kind of find a way to manage them in a consistent way. I think you sh and it makes sense to your business, you should use >>Them. So enterprises like this and just not to get into the business model side real quick, but like how you guys making money? You got the project, you get the cross playing project, that's community. You guys charging what's, what's the business model? >>We we're in the business of helping people adopt and run controlled lanes that do all this management service managed service services and customer support and services, the, the plethora of things that people need where we're >>Keeping the project while >>Keeping the project. >>Correct. So that's >>The key. That's correct. Yeah. You have to balance both >>And you're all over the show. I mean, outside of the keynote mention looking here, you have four events on where can people find you if they're tuning in. We're just at the beginning and there's a lot of looks here. >>Upbound at IO is the place to find Upbound and where I have a lot of talks, you'll see Crossline mention and lots of talks and a number of talks today. We have a happy hour later today we've got a booth set up. So >>I'll be there folks. Just fyi >>And everyone will be there now. Yeah. Quick update. What's up? What's new with the cross plane project? Can you share a little commercial? What's the most important stories going on there? >>So cross plane is growing obviously, and we're seeing a ton of adoption of cross plane, especially actually in large enterprise, which is really exciting cuz they're usually the slow to move and cross plane is so central, so it's now in hundreds and thousands of deployments in woohoo, which is amazing to see. And so the, the project itself is adding a ton of features, reducing friction in terms of adoption, how people ride these control planes and alter them coverage of the space. As you know, controls are only useful when you connect them to things. And the space is like the amount of things you can connect control planes to is increasing on a day to day basis and the maturity is increasing. So it's just super exciting to see all of this right >>Now. How would you categorize the landscape? We were just talking earlier in another segment, we're in Detroit Motor City, you know, it's like teaching someone how to drive a car. Kubernetes pluss, okay, switch the gears like, you know, don't hit the other guy. You know? Now once you learn how to drive, they want a sports car. How do you keep them that progression going? How do you keep people to grow continuously? Where do you see the DevOps and or folks that are doing cross playing that are API hardcore? Cause that's a good IQ that shows 'em that they're advancing. Where's the IQ level of advancement relative to the industry? Is the adoption just like, you know, getting going? Are people advancing? Yeah. Sounds like your customers are heavily down the road on >>Yeah, the way I would describe it is there's a progression happening, right? It, it DevOps was make, initially it was like how do I keep things running right? And it transitioned to how do I automate things so that I don't have to be involved when things are running, running. Right now we're seeing a next turn, which is how do I build what looks like a product that offers shared services or a platform so that people consume it like a product, right? Yeah. And now I'm now transition becomes, well I'm an, I'm a developer on a product in operations building something that looks like a product and thinking about it as a, as a has a user interface. >>Ops of the new devs. >>That's correct. Yeah. There we go. >>Talk about layers. Talk about layers on layers on >>Layers. It's not confusing at all John. >>Well, you know, when they have the architecture architectural list product that's coming. Yeah. But this is what's, I mean the Debs are got so much DevOps in the front and the C I C D pipeline, the ops teams are now retrofitting themselves to be data and security mainly. And that's just guardrails, automation policy, seeing a lot of that kind of network. Like exactly. >>Function. >>Yep. And they're, they're composing, not maybe coding a little bit, but they not, they're not >>Very much. They're in the composition, you know that as a daily thing. They're, they're writing compositions, they're building things, they're putting them together and making them work. >>How new is this in your mind? Cause you, you've watching this progress, you're in the middle of it, you're in the front wave of this. Is it adopting faster now than ever before? I mean, if we talked five years ago, we were kind of saying this might happen, but it wasn't happening today. It kind, it is, >>It's kind of, it's kind of amazing. Like, like everybody's writing these cloud services now. Everybody's authoring things that look like API services that do things on top of the structure. That move is very much, has a ton of momentum right now and it's happening mainstream. It, it's becoming mainstream. >>Speaking of momentum, but some I saw both on your LinkedIn as well as on your badge today that you are hiring. This is your opportunity to shamelessly plug. What are you looking for? What can people expect in terms of your company culture? >>Yeah, so we're obviously hiring, we're hiring both on the go to market side or we're hiring on the product and engineering side. If you want to build, well a new cloud platform, I won't say the word super cloud again, but if you want to, if you're excited about building a cloud platform that literally sits on top of, you know, the other cloud platforms and offers services on top of this, come talk to us. We're building something amazing. >>You're creating a super cloud tool kit. I'll say it >>On that note, think John Farer has now managed to get seven uses of the word super cloud into this broadcast. We sawm tomorrow. Thank you so much for joining us today. It's been a pleasure. I can't wait to see more of you throughout the course of Cuban. My name is Savannah Peterson, everyone, and thank you so much for joining us here on the Cube where we'll be live from Detroit, Michigan all week.