>>Hello and run. Welcome back to the Cube's live coverage here. Day three of Cube's coverage, two sets, wall to wall coverage. Third set upstairs in the Executive Briefing Center. I'm John Furry, host of the Cube with Dave Alon. Two other hosts here. Lot of action. Dave. The cheer here is the CEO of MongoDB, exclusive post on Silicon Angle for your prior to the event. Thanks for doing that. Great to see >>You. Likewise. Nice to see you >>Coming on. See you David. So it's great to catch up. Prior to the event for that exclusive story on ecosystem, your perspective that resonated with a lot of the people. The traffic on that post and comments have been off the charts. I think we're seeing a ecosystem kind of surge and not change over, but like a an and ISV and new platform. So I really appreciate your perspective as a platform ISV for aws. What's it like? What's this event like? What's your learnings? What's your takeaway from your customers here this year? What's the most important story going on? >>First of all, I think being here is important for us because we have so many customers and partners here. In fact, if you look at the customers that Amazon themselves announced about two thirds of those customers or MongoDB customers. So we have a huge overlap in customers here. So just connecting with customers and partners has been important. Obviously a lot of them are thinking about their plans going to next year. So we're kind of meeting with them to think about what their priorities are and how we can help. And also we're sharing a little bit of our product roadmap in terms of where we're going and helping them think through like how they can best use Mongadi B as they think about their data strategy, you know, going to next year. So it's been a very productive end. We have a lot of people here, a lot of sales people, a lot of product people, and there's tons of customers here. So we can get a lot accomplished in a few days. >>Dave and I always talk on the cube. Well, Dave always goes to the TAM expansion question. Expanding your total stressful market, the market is changing and you guys have a great position growing positioned. How do you look at the total addressable market for Mongo changing? Where's the growth gonna come from? How do you see your role in the market and how does that impact your current business model? >>Yeah, our whole goal is to really enable developers to think about Mongo, to be first when they're building modern applications. So what we've done is first built a fir, a first class transactional platform and now we've kind expanding the platform to do things like search and analytics, right? And so we are really offering a broad set of capabilities. Now our primary focus is the developer and helping developers build these amazing applications and giving them tools to really do so in a very quick way. So if you think about customers like Intuit, customers like Canva, customers like, you know, Verizon, at and t, you know, who are just using us to really transform their business. It's either to build new applications quickly to do things at a certain level of performance of scale they've never done before. And so really enabling them to do so much more in building these next generation applications that they can build anywhere else. >>So I was listening to McDermott, bill McDermott this morning. Yeah. And you listen to Bill, you just wanna buy from the guy, right? He's amazing. But he was basically saying, look, companies like he was talking about ServiceNow that could help organizations digitally transform, et cetera, but make money or save money or in a good position. And I said, right, Mongo's definitely one of those companies. What are those conversations like here? I know you've been meeting with customers, it's a different environment right now. There's a lot of uncertainty. I, I was talking to one of your customers said, yeah, I'm up for renewal. I love Mongo. I'm gonna see if they can stage my payments a little bit. You know, things like that. Are those conversations? Yeah, you know, similar to what >>You having, we clearly customers are getting a little bit more prudent, but we haven't seen any kind of like slow down terms of deal cycles or, or elongated sales cycles. I mean, obviously different customers in different sectors are going through different issues. What we are seeing customers think about is like how can I, you know, either drive more efficiency in my business like and big part of that is modernization of my existing legacy tech stack. How can maybe consolidate to a fewer set of vendors? I think they like our broad platform story. You know, rather than using three or four different databases, they can use MongoDB to do everything. So that that resonates with customers and the fact that they can move fast, right? Developer productivity is a proxy for innovation. And so being able to move fast to either seize new opportunities or respond to new threats is really, you know, top of mind for still C level executive. >>So can your software, you're right, consolidation is the number one way in which people are save money. Can your software be deflationary? I mean, I mean that in a good way. So >>I was just meeting with a customer who was thinking about Mongo for their transactional platform, elastic for the search platform and like a graph database for a special use case. And, and we said you can do all that on MongoDB. And he is like, oh my goodness, I can consolidate everything. Have one elegant developer interface. I can keep all the data in one place. I can easily access that data. And that makes so much more sense than having to basically use a bunch of peace parts. And so that's, that's what we're seeing more and more interest from customers about. >>So one of the things I want to get your reaction to is, I was saying on the cube, now you can disagree with me if you want, but at, in the cloud native world at Cuban and Kubernetes was going through its hype cycle. The conversation went to it's getting boring. And that's good cause they want it to be boring. They don't want people to talk about the run time. They want it to be working. Working is boring. That's invisible. It's good, it's sticky, it's done. As you guys have such a great sticky business model, you got a great install base. Mongo works, people are happy, they like the product. So it's kind of working, I won't wanna say boring cuz that's, it's irrelevant. What's the exciting things that Mongo's bringing on top of the existing base of product that is gonna really get your clients and prospects enthused about the innovation from Mongo? What's what cuz it's, it's almost like electricity in a way. You guys are very utility in, in the way you do, but it's growing. But is there an exciting element coming that you see that they should pay attention to? What's, what's your >>Vision that, right, so if you look back over the last 10, 15 years, there's been big two big platform shifts, mobile and cloud. I think the next big platform shift is from what I call dumb apps to smart apps. So building more intelligence into applications. And what that means is automating human decision making and embedding that into applications. So we believe that to be a fundamentally a developer problem to solve, yes, you need data scientist to build the machine learning algorithms to train the models. Yeah. But ultimately you can't really deploy, deployed at scale unless you give developers the tools to build those smart applications that what we focused on. And a big part of that is what we call application driven analytics where people or can, can embed that intelligence into applications so that they can instead rather having humans involved, they can make decisions faster, drive to businesses more quickly, you know, shorten it's short and time to market, et cetera. >>And so your strategy to implement those smart apps is to keep targeting the developer Yes. And build on that >>Base. Correct. Exactly. So we wanna essentially democratize the ability for any customer to use our tools to build a smart applications where they don't have the resources of a Google or you know, a large tech company. And that's essentially resonating with our customer base. >>We, we were talking about this earlier after Swami's keynote, is most companies struggle to put data at the core of their business. And I don't mean centralizing it all in a single place as data's everywhere, but, but really organizing their company and democratizing data so people can make data decisions. So I think what you're saying, essentially Atlas is the platform that you're gonna inject intelligence into and allow developers to then build applications that are, you know, intelligent, smart with ai, machine intelligence, et cetera. And that's how the ones that don't have the resources of a Google or an Amazon become correct the, that kind of AI company if >>You, and that's, that's the whole purpose of a developer data platform is to enable them to have the tools, you know, to have very sophisticated analytics, to have the ability to do very sophisticated indexes, optimized for analytics, the ability to use data lakes for very efficient storage and retrieval of data to leverage, you know, edge devices to be able to capture and synchronize data. These are all critical elements to build these next generation applications. And you have to do that, but you don't want to stitch together a thousand primitives. You want to have a platform to do that. And that's where we really focus. >>You know, Dave, Dave and I, three, two days, Dave and I, Dave Ante and I have been talking a lot about developer productivity. And one observation that's now validated is that developers are setting the pace for innovation. Correct? And if you look at the how they, the language that they speak, it's not the same language as security departments, right? They speak almost like different languages, developer and security, and then you got data language. But the developers are making choices of self-service. They can accelerate, they're driving the behavior behavior into the organizations. And this is one of the things I wrote about on Friday last week was the organizational changes are changing cuz the developers set the pace. You can't force tooling down their throat. They're gonna go with what's easy, what's workable. If you believe that to be true, then all the security's gonna be in the developer pipeline. All the innovations we've driven off that high velocity developer site, we're seeing success of security being embedded there with the developers. What are you gonna bring up to that developer layer that's going to help with security, help with maybe even new things, >>Right? So, you know, it's, it's almost a cliche to say now software is in the world, right? Because every company's value props is driven by, it's either enabled to find or created through software. What that really means is that developers are eating all the work, right? And you're seeing, you saw in DevOps, right? Where developers basically enro encroach into the ops world and made infrastructure a programmable interface. You see developers, to your point, encroaching in security, embedding more and more security features into their applications. We believe the same thing's gonna happen with data scientists and business analysts where developers are gonna embed that functionality that was done by different domains in the Alex world and embed that capability into apps themselves. So these applications are just naturally smarter. So you don't need someone to look at a dashboard and say, aha, there's some insight here now I need to go make a decision. The application will do that for you and actually make that decision for you so you can move that much more quickly to run your business either more efficiently or to drive more, you know, revenue. >>Well the interesting thing about your business is cuz you know, you got a lot of transactional activity going on and the data, the way I would say what you just described is the data stack and the application stacks are coming together, right? And you're in a really good position, I think to really affect that. You think about we've, we've operationalized so many systems, we really haven't operationalized our data systems. And, and particularly as you guys get more into analytics, it becomes an interesting, you know, roadmap for Mongo and your customers. How do you see that? >>Yeah, so I wanna be clear, we're not trying to be a data warehouse, I get it. We're not trying to be like, you know, go compete. In fact, we have nice partnership with data bricks and so forth. What we are really trying to do is enable developers to instrument and build these applications that embed analytics. Like a good analogy I'd use is like Google Maps. You think about how sophisticated Google Maps has, and I use that because everyone has used Google Maps. Yeah. Like in the old, I was old enough to print out the directions, map quest exactly, put it on my lap and drive and look down. Now have this device that tells me, you know, if there's a traffic, if there's an accident, if there's something you know, going will reroute me automatically. And what that app is doing is embedding real time data into, into its decision making and making the decision for you so that you don't have to think about which road to take. Right? You, you're gonna see that happen across almost every application over the next X number of years where these applications are gonna become so much smarter and make these decisions for you. So you can just move so much more quickly. >>Yeah. Talk about the company, what status of the company, your growth plans. Obviously you're seeing a lot of news and Salesforce co CEO just resigned, layoffs at cnn, layoffs at DoorDash. You know, tech unfortunately is not impacted, thank God. I'm not that too bad. Certainly in cloud's not impacted it is impacting some of the buying behavior. We talked about that. What's going on with the company head count? What's your goals? How's the team doing? What are your priorities? >>Right? So we we're going after a big, big opportunity. You know, we recognize, obviously the market's a little choppy right now, but our long term, we're very bullish on the opportunity. We believe that we can be the modern developer data platform to build these next generation applications in terms of costs. We're obviously being a little bit more judicious about where we're investing, but we see big, big opportunities for us. And so our overall cost base will grow next year. But obviously we also recognize that there's ways to drive more efficiency. We're at a scale now. We're a 1.2 billion business. We're gonna announce our Q3 results next week. So we'll talk a little bit more about, you know, what we're seeing in the business next week. But we, we think we're a business that's growing fast. You know, we grew, you know, over 50, 50% and so, so we're pretty fast growing business. Yeah. You see? >>Yeah, Tuesday, December 6th you guys announce Exactly. Course is a big, we always watch and love it. So, so what I'm hearing is you're not, you're not stepping on the brakes, you're still accelerating growth, but not at all costs. >>Correct. The term we're using is profitable growth. We wanna, you know, you know, drive the business in a way that we think continues to seize the opportunity. But we also, we always exercise discipline. You know, I, I'm old enough where I had to deal with 2000 and 2008, so, you know, seen the movie before, I'm not 28 and have not seen these markets. And so obviously some are, you know, emerging leaders have not seen these kinds of markets before. So we're kind of helping them think about how to continue to be disciplined. And >>I like that reference to two thousand.com bubble and the financial crisis of 2008. I mentioned this to you when we chat, I'd love to get your thoughts. Now looking back for reinvent, Amazon wasn't a force in, in 2008. They weren't really that big debt yet. Know impact agility, wasn't it? They didn't hit that, they didn't hit that cruising altitude of the value pro cloud agility, time of value moving fast. Now they are. So this is the first time that they're a part of the economic equation. You're on, you're on in the middle of it with Amazon. They could be a catalyst to recover faster if plan properly. What's your CEO take on just that general and other CEOs might be watching and saying, Hey, you know, if I play this right, I could leverage the cloud. You know, Adams is leading into the cloud during a recession. Okay, I get that. But specifically there might be a tactic. What's your view on >>That? I mean, what, what we're seeing the, the hyperscalers do is really continue to kind of compete at the raw infrastructure level on storage, on compute, on network performance, on security to provide the, the kind of the building blocks for companies like Monga Beach really build on. So we're leveraging that price performance curve that they're pushing. You know, they obviously talk about Graviton three, they're talking about their training model chip sets and their inference model chip sets and their security chip sets. Which is great for us because we can leverage those capabilities to build upon that. And I think, you know, if you had asked me, you know, in 2008, would we be talking about chip sets in 2022? I'd probably say, oh, we're way beyond that. But what it really speaks to is those things are still so profoundly important. And I think that's where you can see Amazon and Google and Microsoft compete to provide the best underlying infrastructure where companies like mongadi we can build upon and we can help customers leverage that to really build the next generation. >>I'm not saying it's 2008 all over again, but we have data from 2008 that was the first major tailwind for the cloud. Yeah. When the CFO said we're going from CapEx to opex. So we saw that. Now it's a lot different now it's a lot more mature >>I think. I think there's a fine tuning trend going on where people are right sizing, fine tuning, whatever you wanna call it. But a craft is coming. A trade craft of cloud management, cloud optimization, managing the cost structures, tuning, it's a crafting, it's more of a craft. It's kind of seems like we're >>In that era, I call it cost optimization, that people are looking to say like, I know I'm gonna invest but I wanna be rational and more thoughtful about where I invest and why and with whom I invest with. Versus just like, you know, just, you know, everyone getting a 30% increase in their opex budgets every year. I don't think that's gonna happen. And so, and that's where we feel like it's gonna be an opportunity for us. We've kind of hit scap velocity. We've got the developer mind share. We have 37,000 customers of all shapes and sizes across the world. And that customer crown's only growing. So we feel like we're a place where people are gonna say, I wanna standardize among the >>Db. Yeah. And so let's get a great quote in his keynote, he said, if you wanna save money, the place to do it is in the cloud. >>You tighten the belt, which belt you tightening? The marketplace belt, the wire belt. We had a whole session on that. Tighten your belt thing. David Chair, CEO of a billion dollar company, MongoDB, continue to grow and grow and continue to innovate. Thanks for coming on the cube and thanks for participating in our stories. >>Thanks for having me. Great to >>Be here. Thank. Okay, I, Dave ante live on the show floor. We'll be right back with our final interview of the day after this short break, day three coming to close. Stay with us. We'll be right back.

>>Hi, I'm John Ferry with the Cube. We're here for a special exclusive conversation with David Geria, the CEO of Mongo MongoDB. Well established leading platform. It's been around for, I mean, decades. So continues to become the platform of choice for high performance data. This modern data stack that's emerging, a big part of the story here at a reinvent 2022 on top of an already performing a cloud with, you know, chips and silicon specialized instances, the world's gonna be getting faster, smaller, higher performance, lower cost specialized. Dave, thanks for taking the time with me today, >>John. It's great to be here. Thank you for having me. >>Do you see yourself as a ISV or you just go with that, because that's kind of a nomenclature >>When, when I think of the term isv, I think of the notion of someone building an end solution for customer to get something done. Or what we're building is essentially a developer data platform and we have thousands of ISVs who build software applications on our platform. So how could we be an isv? Because by definition I, you know, we enable people to do so many different things and you know, they can be the, you know, the largest companies of the world trying to transform their business or startups who are trying to disrupt either existing industries or create new ones. And so that's, and, and that's how our customers view MongoDB and, and the whole Atlas platform basically enables them to do some amazing things. The reason for that is, you know, you know, we believe that what we are enabling developers to do is be able to reduce the friction and the work required to build modern applications through the document model, which is really intuitive to the way developers think and code through the distributed nature of platforms. >>So, you know, things like charting no other company on the planet offers the capabilities we do to enable people to build the most highly performant and scalable applications. And also what we also do is enable people to, you know, run different types of workloads on our platform. So we have obviously transactional, we have search, we have time series, we enable people to do things like sophisticated device synchronization from Edge to the back end. We do graph, we do real time analytics. So being able to consolidate all that with developers on one elegant unified platform really makes, you know, it attractive for developers to build on long >>Db. You know, you guys are a feature partner of aws and I would speculate, I don't know if you can comment on this, but I would imagine that you probably produce a lot of revenue for Amazon because you really can't turn off EC two when you do a database work. So, you know, you kind of crank it all the time. You guys are a top partner. How long have you guys been a partner with aws? What's the relationship? >>The relationship's been strong, actually, Amazon spoke at one of our first user conferences in 2013. And since then we've been working together. We've been at reinvent since essentially 2015. And we've been a premier partner, an Emerald sponsor for the last Nu you know, I think four or five years. And so we're very committed to the relationship and I think there's some things that we have a lot, we have a lot of things in common. We care a lot about customers and for us, our customers, our developers, we care a lot about removing friction from their day to day work to move, be able to move fast and be able to, in order to seize new opportunities and respond to new threats. And so consequently, I think the partnership, obviously by nature of our, our common objectives has really come together. >>Talk about the journey of Mongo. I mean, you look back at the history, I, you go back the old lamp stack days, right? So you know, the day developer traction is just really kind of stuck at the none. I mean, it's, it's really well known. And I remember over the conversations, Dave Mongo doesn't scale. I mean, every year we heard something along those lines cuz it just kept scaling. I heard the same thing with AWS back in 2013 timeframe. You, oh, it's just, it's really not for a real prime time. It's, it's for hobbyists, not so much builders, maybe startup cloud, but that developer traction is translated. Can you take us through the journey of Mongo where it is now and, and kinda look back and, and, and take us through what's the state of the art now, >>Right? So just for those of you who, who, those, you know, those in your audience who don't know too much about Mon Be I'll just, you know, start with the background. The company was astounded by developers. It was basically the CTO and some key developers from Double Click who really saw the challenges and the limitations of the relational database architecture because they're trying to serve billions of ads per day and they constantly need to work on the constraints and relational database. And so they essentially decided, why don't we just build a database that we'd want to use? And that was a catalyst to starting MongoDB. The first thing they focused on was, rather than having a tabler data structure, they focused on a document data structure. Why documents? Because there's much more natural and intuitive to work with data and documents in terms of you can set parent child relationships and how you just think about the relationship with data is much more natural in a document than trying to connect data in a, you know, in hundreds of different tables. >>And so that enabled developers to just move so much faster. The second thing they focused on was building a truly distributed architecture, not kind of some adjunct, you know, you know, architecture that maybe made the existing architecture a little bit more scalable. They really took from the ground up a truly distributed architecture. So where you can do native replication, you can do charting and you can do it on a global basis. And so that was the, the other profound, you know, thing that they did. And then since then, what we've also done is, you know, the document model is truly a super set of other models. So we enabled other capabilities like search you can do joins, so you can do very transaction intensive use case among be where fully asset compliant. So you have the highest forms of data guarantees you can do very sophisticated things like time series, you can do device synchronization, you can do real time analytics because we can carve off read only nodes to be able to read and query data in real time rather than have to offload that data into a data warehouse. >>And so that enables developers to just build a wide variety of, of application longing to be, and they get one unified developer interface. It's highly elegant and seamless. And so essentially the cost and tax of matching multiple point tools goes away when, when I think of the term isv, I think of the notion of someone building an end solution for a customer to get something done. Or what we're building is essentially a developer data platform and we have thousands of ISVs who build software applications on our platform. So how could we be an isv? Because by definition I, you know, we enable people to do so many different things and you know, they can be the, you know, the largest companies in the world trying to transform their business or startups or trying to disrupt either existing industries or create new ones. And so that's, and and that's how our customers view MongoDB and, and the whole Atlas platform basically enables them to do some amazing things. >>Yeah, we're seeing a lot of activity on the Atlas. Do you see yourself as a ISV or you just go with that because that's kind of a nomenclature? >>No, we don't view ourselves as ISV at all. We view ourselves as a developer data platform. And the reason for that is, you know, you know, we believe that what we are enabling developers to do is be able to reduce the friction and the work required to build modern applications through the document model, which is really intuitive to the way developers think and code through the distributed nature of platforms. So, you know, things like sharding, no other company on the planet offers the capabilities we do to enable people to build the most highly performant and scalable applications. And also what we also do is enable people to, you know, run different types of workflows on our platform. So we have obviously transactional, we have search, we have time series, we enable people to do things like sophisticated device synchronization from Edge to the back end. We do graph, we do real time analytics. So being able to consolidate all that with developers on one elegant unified platform really makes, you know, it attractive for developers to build on long ndb. >>You know, the cloud adoption really is putting a lot of pressure on these systems and you're seeing companies in the ecosystem and AWS stepping up, you guys are doing great job, but we're seeing a lot more acceleration around it, on staying on premise for certain use cases. Yet you got the cloud as well growing for workloads and, and you get this hybrid steady state as an operational mode. I call that 10 of the classic cloud adoption track record. You guys are an example of multiple iterations in cloud. You're doing a lot more, we're starting to see this tipping point with others and customers coming kind of on that same pattern. Building platforms on top of aws on top of the primitives, more horsepower, higher level services, industry specific capabilities with data. I mean this is a new kind of cloud, kind of a next generation, you knows next gen you got the classic high performance infrastructure, it's getting better and better, but now you've got this new application platform, you know, reminds me of the old asp, you know, if you will. I mean, so are you seeing customers doing things differently? Can you share your, your reaction to this role of, you know, this new kind of SaaS platform that just isn't an application, it's, it's more, it's deeper than that. What's going on here? We call it super cloud, but >>Like what? Yeah, so essentially what what, you know, a lot of our customers doing, and by the way we have over 37,000 customers of all shapes and sizes from the largest companies in the world to cutting edge startups who are building applications among B, why do they choose MongoDB? Because essentially it's the, you know, the fastest way to innovate and the reason it's the fastest way to innovate is because they can work with data so much easier than working with data on other types of architecture. So the document model is profoundly a breakthrough way to work with data to make it very, very easy. So customers are essentially building these modern applications, you know, applications built on microservices, event driven architectures, you know, addressing sophisticated use cases like time series to, and then ultimately now they're getting into machine learning. We have a bunch of companies building machine learning applications on top of MongoDB. And the reason they're doing that is because one, they get the benefits of being able to, you know, build and work with, with data so much easier than any other platform. And it's highly scale and performant in a way that no other platform is. So literally they can run their, you know, workloads both locally and one, you know, autonomous zone or they can basically be or available zone or they could be basically, you know, anywhere in the world. And we also offer multicloud capabilities, which I can get into later. >>Let's talk about the performance side. I know I was speaking with some Amazon folks every year it's the same story. They're really working on the physics, they're getting the chips, they wanna squeeze as much energy out of that. I've never met a developer that said they wanna run their workload on a slower platform or slower hardware. We know said no developer, right? No one wants to do that. >>Correct. >>So you guys have a lot of experience tuning in with Graviton instances, we're seeing a lot more AWS EC two instances, we're seeing a lot more kind of integrated end to end stories. Data is now security, it's tied into data stacks or data modern kind of data hybrid stack. A lot going on around the hardware performance specialization, the role of data, kind of a modern data stack emerging. What, what's your thoughts on the that that Yeah, >>I, I think if you had asked me, you know, when the cloud started going vogue, like you know, the, you know, the, the later part of the last decade and told me, you know, sitting here 12, 15 years later, would you know, would we be talking about, you know, chip processing speeds? I'd probably thought, nah, we would've moved on by then. But what's really clear is that customers, to your point, customers care about performance, they care about price performance, right? So AWS's investments in Graviton, we have actually deployed a significant portion of our at fleet on Amazon now runs on Graviton. You know, they've built other chip sets like train and, and inferential for like, you know, training models and running inferences. They're doing things like Nitro. And so what that really speaks to is that the cloud providers are focusing on the price performance of their, as you call it, their primitives and their infrastructure and the infrastructure layer that are still very, very important. >>And, and you know, if you look at their revenue, about 60 to 70% of the revenue comes from that pure infrastructure. So to your point, they can't offer a second class solution and still win. So given that now they're seeing a lot of competition from Azure, Azure's building their own chip sets, Google's already obviously doing that and and building specialized chip sets for machine learning. You're seeing these cloud providers compete. So they have to really compete to make their platform the most performant, the most price competitive in the marketplace. Which gives us a great platform to build on to enable developers to build these incredibly highly performant applications that customers are now demand. >>I think that's a really great point. I mean, you know, it's so funny Dave, because you know, I remember those, we don't talk speeds and feeds anymore. We're not talking about boxes. I mean that's old kind of school thinking because it was a data center mentality, speeds and feeds and that was super important. But we're kind of coming back to that in the cloud now in distributed architecture, as you put your platforms out there for developers, you have to run fast. You gotta, you can't give the developer subpar or any kind of performance that's, they'll, they'll go somewhere else. I mean that's the reality of what developers, no one, again, no one says I wanna go on the slower platform unless it's some sort of policy based on price or some sort of thing. But, but for the most part it's gotta run fast. So you got the tail of two clouds going on here, you got Amazon classic ias, keep making it faster under the hood. >>And then you got the new abstraction layers of the higher level services. That's where you guys are bridging this new, new generational shift where it's like, hey, you know what? I can go, I can run a headless application, I can run a SAS app that's refactored with data. So you've seen a lot more innovation with developers, you know, running stuff in, in the C I C D pipeline that was once it, and you're seeing security and data operations kind of emerging as a structural change of how companies are, are are transforming on the business side. What's your reaction to that business transformation and the role of the developer? >>Right, so I mean I have to obviously give amazing kudos to the, you know, to AWS and the Amazon team for what they've built. Obviously they're the ones who kind of created the cloud industry and they continue to push the innovation in the space. I mean today they have over 300 services and you know, obviously, you know, no star today is building anything not on the cloud because they have so many building blocks to start with. But what we though have found from our talking to our customers is that in some ways there is still, you know, the onus is on the customer to figure out which building block to use to be able to stitch together the applications and solutions they wanna build. And what we have done is taken essentially an opinionated point of view and said we will enable you to do that. >>You know, using one data model. You know, Amazon today offers I think 17 or 18 different types of databases. We don't think like, you know, having a tool for every job makes sense because over time the tax and cost of learning, managing and supporting those different applications just don't make a lot of sense or just become cost prohibitive. And so we think offering one data model, one, you know, elegant user experience, you know, one way to address the broadest set of of use cases is that we think is a better way. But clearly customers have choice. They can use Amazon's primitives and those second layer services as you as you described, or they can use us. Unfortunately we've seen a lot of customers come to us with our approach and so does Amazon. And I have to give obviously again kudos and Amazon is very customer obsessed and so we have a great relationship with them, both technically in terms of the product integrations we do as well as working with 'em in the field, you know, on joint customer opportunities. >>Speaking of, while you mentioned that, I wanna just ask you, how is that marketplace relationship going with aws? Some of the partners are really seeing great economic and joint selling or them selling your, your stuff. So there's a real revenue pop there in that religion. Can you comment on that? >>So we had been working the partner in the marketplace for many years now, more from a field point of view where customers could leverage their existing commitments to AWS and leverage essentially, you know, using Atlas and applying in an atlas towards their commits. There was also some sales incentives for people in the field to basically work together so that, you know, everyone won should we collectively win a customer? What we recently announced is as pay as you Go initiative, where literally a customer on the Amazon marketplace can basically turn up, you know, an Alice instance with no commitment. So it's so easy. So we're just pushing the envelope to just reduce the friction for people to use Atlas on aws. And it's working really very well. The uptake has been been very strong and and we feel like we're just getting started because we're so excited about the results we're >>Seeing. You know, one of the things that's kind of not core in the keynote theme, but I think it's underlying message is clear in the industry, is the developer productivity. You said making things easy is a big deal, self-service, getting in and trying, these are what developer friendly tools are like and platform. So I have to ask you, cuz this comes up a lot in our kind of business conversation, is, is if you take digital transformation concept to its completion, assuming now you know, as a thought exercise, you completely transform a company with technology that's, that is the business transformation outcome. Take it to completion. What does that look like? I mean, if you go there you'd say, okay, the company is the app, the company is the data, it's not a department serving the business, it's the business. And so I think this is kind of what we're seeing as the next big mountain climb, which is companies that do transform there, they are technology companies, they're not a department like it. So I think a lot of companies are kind of saying, wait a minute, why would we have a department? It should be the company. What's your your your view on this because this >>Yeah, so I I've had the for good fortune of being able to talk to thousand customers all over the world. And you know, one thing John, they never tell me, they never tell me that they're innovating too quickly. In fact, they always tell me the reverse. They tell me all the obstacles and impediments they have to be able to be able to be able to move fast. So one of the reasons they gravitate to MongoDB is just the speed that they wish they can build applications to, to your point, developer productivity. And by definition, developer productivity is a proxy for innovation. The faster you can make your developers, you know, move, the faster they can push out code, the faster they can iterate and build new solutions or add more capabilities on the existing applications, the faster you can innovate either to, again, seize new opportunities or to respond to new threats in your business. >>And so that resonates with every C level executive. And to your point, the developers not some side hustle that they kind of think about once in a while. It's core to the business. So developers have amassed enormous amount of power and influence. You know, their, their, their engineering teams are front and center in terms of how they think about building capabilities and and building their business. And that's also obviously enabled, you know, to your point, every software company, every company's not becoming a software company because it all starts with softwares, software enables, defines or creates almost every company's value proposition. >>You know, it makes me smile because I love operating systems as one of my hobbies in college was, you know, systems programming and I remember those network kind of like the operating systems, the cloud. So, you know, everything's got specialized capabilities and that's a big theme here at Reinvent. If you look at the announcements Monday night with Peter DeSantis, you got, you got new instances, new chips. So this whole engine kind of specialized component is like an engine. You got a core and you got other subsystems. This is gonna be an integral part of how companies architect their platform or you know, Adam calls it the landing zone or whatever they wanna call it. But you gotta start seeing a new architectural thinking for companies. What's your, can you share your experience on how companies should look at this opportunity as a plethora of more goodness on the hardware? On hardware, but like chips and instances? Cause now you can mix and match. You've got, you've got, you got everything you need to kind of not roll your own but like really build foundational high performance capabilities. >>Yeah, so I I, so I think this is where I think Amazon is really enabling all companies, including, you know, companies like Mon db, you know, push the envelope and innovation. So for example, you know, the, the next big hurdle for us, I think we've seen two big platform shifts over the last 15 years of platform shifts, you know, to mobile and the platform shift to cloud. I believe the next big platform shift is going from dumb apps to smart apps, which you're building in, you know, machine learning and you know, AI and just very sophisticated automation. And when you start automating human decision making, rather than, you know, looking at a dashboard and saying, okay, I see the data now, now I have to do this. You can automate that into your applications and make your applications leveraging real time data become that much more smart. And that ultimately then becomes a developer challenge. And so we feel really good about our position in taking advantage of those next big trends and software leveraging the price performance curves that, you know, Amazon continues to push in terms of their hardware performance, networking performance, you know, you know, price, performance and storage to build those next generation of modern applications. >>Okay, so let me get this straight. You have next generation intelligent smart apps and you have AI generative solutions coming out around the corner. This is like pretty good position for Mongo to be in with data. I mean, this is what you do, you're in that exactly of the action. What's it like? I mean, you must be like trying to shake the world and wake up. The world's starting to wake up now through this. So what's, what's it like? >>Well, I mean we're really excited and bullish about the future. We think that we're well positioned because we know as to your point, you know, we have amassed amazing amount of developer mindshare. We are the most popular modern data platform out there in the world. There's developers in almost every corner of the planet using us to do something. And to your point, leveraging data and these advances in machine learning ai. And we think the more AI becomes democratized, not, you know, done by a bunch of data scientists sitting in some corner office, but essentially enabling developers to have the tools to build these very, very sophisticated, smart applications will, you know, will position as well. So that's, you know, obviously gonna be a focus for us over the, frankly, I think this is gonna be like a 10 year, 10 15 year run and we're just getting started in this whole >>Area. I think you guys are really well positioned. I think that's a great point. And Adam mentioned to me and, and Mike interviewed, he said on stage talk about it, the role of a data analyst kind of goes away. Everyone's a data analyst, right? You'll still see specialization on, on core data engineering, which is kind of like an SRE role for data. So data ops and data as code is a big deal making data applications. So again, exciting times and you guys are well positioned. If you had to bumper sticker the event this week here at Reinvent, what would you, how would you categorize this this point in time? I mean, Adam's great leader, he is gonna help educate customers how to use technology to, for business advantage and transformation. You know, Andy did a great job making technology great and innovative and setting the table, Adam's gotta bring it to the enterprises and businesses. So it's gonna be an interesting point in time we're in now. What, how would you categorize this year's reinvent, >>Right? I think the, the, the tech world is pivoting towards what I'd call rationalization or cost optimization. I think people obviously in, you know, the last 10 years have, you know, it's all about speed, speed, speed. And I think people still value speed, but they wanna do it at some sort of predictable cost model. And I think you're gonna see a lot more focus around cost and cost optimization. That's where we think having one platform is by definition of vendor consolidation way for people to cut costs so that they can basically, you know, still move fast but don't have to incur the tax of using a whole bunch of different point tools. And so we think we're well positioned. So the bumper sticker I think about is essentially, you know, do more for less with MongoDB. >>Yeah. And the developers on the front lines. Great stuff. You guys are great partner, a top partner at AWS and great reflection on, on where you guys been, but really where you are now and great opportunity. David Didier, thank you so much for spending the time and it's been great following Mongo and the continued rise of, of developers of the on the front lines really driving the business and that, and they are, I know, driving the business, so, and I think they're gonna continue Smart apps, intelligent apps, ai, generative apps are coming. I mean this is real. >>Thanks John. It's great speaking with >>You. Yeah, thanks. Thanks so much. Okay.

>> Welcome back to New York City everybody. This is The Cube's coverage of MongoDB World 2022, Dev Ittycheria, here is the president and CEO of MongoDB. Thanks for spending some time with us. >> It's Great to be here Dave, thanks for having me. >> You're very welcome. So your keynotes this morning, I was hearkening back to Steve Ballmer, running around the stage screaming, developers, developers, developers. You weren't jumping around like a madman, but the message was the same. And you've not deviated from that message. I remember when it was 10th Gen, so you've been consistent. >> Yes. >> Why is Mongo DB so alluring to developers? >> Yeah, because I would say the reason we're so popular Dave is that our whole business was founded on the ethos, so making developers incredibly productive. Just getting the infrastructure out of the way so that the developers is really focused on what's important and that's building great applications that transform their business. And the way you do that is you look at where they spend most of the time. and they spend most of the time working with data. How do you present data, the right data, the right time, at the right place, and the right way. And when you remove the friction of working with data, you unleash so much more productivity, which people just say, oh my goodness, I can move so much faster. Product leaders can get products out the door faster than the competitors. Senior level executives can seize new opportunities or respond to new threats. And that was so profound during COVID when everyone had to think about pivoting their business. >> When you came to MongoDB, why did you choose this company? What was it that excited you about it? >> I get that question a lot. I would say conventional wisdom would suggest that MongoDB was not a great choice. There weren't that many companies who were very successful in open source, Red Hat was the only one. No one had really built a deep technology company in New York city. They say, you got to do it in the valley. And database companies need a lot of capital. Now turns out that raising capital of this past decade was a lot easier, but it still takes a lot of time, and a lot of capitals, you have to have a lot of patience. When I did my diligence, I was actually a VC before I joined MongoDB. The whole next generation database segment was really taking off. And actually I looked at some competing investments to MongoDB, and when I did my diligence, it was clear even then. And this is circa 2012, that MongoDB is way ahead in terms of customer attraction, commercials, and even kind of developer mind share. And so I ended up passing those investments. and then lo and behold, I got a call from a very senior executive recruiter who said, Dev, you got to take a meeting with MongoDB, there's something really interesting going on. And they had raised a lot of capital and they had just not been able to kind of really execute in terms of the opportunity. And they realized they needed to make a change. And so one thing led to another. One of the things that really actually convinced me, is when I did my diligence, I realized the customers they had loved MongoDB. They just really weren't executing on all cylinders. And I always believe you never bet against a company whose customers love the product. And said, that's something here. The second thing I would say is open source. Yes, is true that open source was not very successful, but that was open source 1.0. Open source 2.0, the technology is much better than the commercial options. And so that convinced me. And then New York, I lived in New York a big part of my life. I think New York's a fabulous place to build a business. There's so much talent, your customers are right... You walk out the door, there's customers all over the place. And getting to Europe is very easy, Almost like flying to the west coast. So it's a very central place to build a business. >> And it's easier to fix execution, wouldn't you say? And maybe even go to market than it is to fix a product that customers really don't love. >> Correct, it's much easier to fix leadership issues, culture issues, execution issues. Nailing product market fit is very, very hard. And there were signs, there's still some issues, there's still some rough spots, but there a lot of signs that this company was very, very close, and that's why I took the bet. >> And this is before there was that huge influx of capital into the separating compute from storage and the whole cloud thing, which is interesting. Because you take a company like Cloudera, they got caught up in that and got kind of washed over. And I guess you could argue Hortonworks did too, and they could have dead ended both. And then that just didn't work. But it's interesting to see Mongo, the market kind of came to you. And that really does speak to the product. It wasn't a barrier for you. You guys have obviously a lot of work to get into the cloud with Atlas, but it seemed like a natural fit with the product. It wasn't like a complete fork. >> Well, I think the challenge that we had was we had a lot of adoption, but we had tough time commercializing the business. And at some point I had to tell the all employees, it's great that we have all these people who are using MongoDB, but if you don't start generating revenue, our investors are going to get tired of subsidizing this company. So I had to try and change the culture. And as you imagine, the engineers didn't really like the salespeople, the salespeople thought the engineers didn't really want to make any money. And what I said, like, let's all galvanize around customers and let's make them really excited and try and create a lot of value. And so we just put a lot more discipline in terms of how we prosecuted deals. We put a lot more discipline in terms of what are the problems we're trying to solve. And one thing led to another, we started building the business brick by brick. And one of the things that became clear for me was that the old open source model of trying to find that happy medium between what you give away and what you charge for, is always a tough game. Like because finding that where the paywall is, if you give away too much new features, you don't make any money. If you don't give away enough, you don't have any adoption. So you're caught in this catch-22. The best way to monetize open source, is open source as a service. And we saw Amazon do that frankly. We learned a lot from how Amazon did that. And one of the advantages that MongoDB had that I didn't fully appreciate when I joined the company, but I was very grateful. It is that they had a much more restrictive license. Which we ended up actually changing and made it even more restrictive, which allowed us to perfect ourselves from being cannibalized by the cloud providers, so that we could build our own business using our own IP that we had invested in and create a cloud service. >> That was a huge milestone. And of course you have great relationships with all the cloud providers, but it got contentious there for a while, but, you give the cloud providers an inch, they're going to take a mile. That's just the way, they're aggressive like that. But thank you for going through the history with me a little bit, because when you go back to the IPO, IPO was 2017, right? >> Correct. >> I always tell young investors, my kids especially, don't buy a stock at IPO, you're going to have a better chance, but the window from Mongo was very narrow. So, you didn't really get a much better chance a little bit. And then it's been a rocket ship since then. Sure, there's been some volatility, but you look at some of the big IPOs, like Facebook, or Snap, or even Snowflake, there was better opportunities. But you guys have executed really, really well. That's part of your ethos in your management team. And it came across on the earnings call recently. >> Yep. >> It was very optimistic, yet at the same time you set cautious tones and you got, I think high marks. >> Yes. >> For some of that caution but that execution. So talk about where you feel the business is today given the economic uncertainty? >> Well, what I'd say is we feel really good about the long term. We feel like the secular trends are really in our favor. Software's fundamentally transforming every industry. And people want to use modern software to either automate inefficient processes, enable new capabilities, drive better customer experiences. And the level of performance and scale you need for today's modern applications is profoundly different than applications yesterday. So we think we're well positioned for that. What we said on the earnings call was that we started seeing a moderation of growth, slight moderation of growth in our low end of the business in Europe. It was in our self-serve business and in the SMB space for the NQ1, towards the end of Q1. And we saw a little bit of that show up in the self-serve business in may in Q2. And that's why while we raised guidance, we basically quantified the impact, which is roughly about 30 to 35 million for the year, based on what we saw. And in that assumption, we assumed like... We just can't assume it's going to only be at the low in the market, probably some effect at the enterprise market. Maybe not as much, but there'll be some effect. So we need to factor that in. And we wanted to help kind of investors have some sort of framework to think about what the impact is. We don't want to be one of those companies that said absolutely nothing. And we don't want to be one of those companies that just waves the hand, but then it wasn't really that useful for investors. >> Yeah, I thought it was substantive. You talked about those market trends, you cited three things. The developers recognize that there are limits to legacy RDBMS. You talked about the, what I call point solutions creep. And then the document model is the best for developers. >> Great. >> And when the conversation turned to consumption, everybody's concerned about consumption obviously. You said... My take, somewhat insulated from that because you're running mission critical apps. It's not discretionary. My question to you is, should we rethink the definition of mission-critical? You think of Oracle mission critical running a bank. Mission -critical today in this digital world seems to be different, is that fair? >> Gosh, when's the last time you ever saw a website down? Like if you're running like any kind of digital channel, or engaging with the customers, or your partners, or your suppliers, you need to be up all the time. And so you need a very resilient, highly available data platform. It needs to be highly performance as you add more users, you need to be scale. And we saw a lot of that when COVID hit. Like companies had to completely repovit. And we talked about some examples where like a health and beauty retailer who was all kind of basically retail, had to suddenly pivot to e-commerce strategy. We've had streaming and gaming companies suddenly saw this massive influx of data that they scaled their operations very, very quickly. So I would say anytime you're engaging with customers, customers they're so used to the kind of the consumer facing applications. I almost joke like slow is the old down. If you're not performant, it doesn't matter. They're going to abandon you and go somewhere else. So if you're an e-commerce site and you're not performing well and not serving up the right skews, depending on what they're looking for, they're going to go somewhere else. >> So it's a click away. You talk about a hundred billion TAM, maybe that's even undercounted as you start to bring new capabilities in there. But there's no lack of market for you. >> Correct. >> How do you think about the market opportunity? >> Well, we believe... Again, software is transforming so many industries. IDC says that 715 million applications will be built over the next two to three years by 2025. To put that number of perspective, that's more apps that will be built the next three to four years than were built in the last 40. The rate and pace of innovation is as exploding. And people are building custom applications. Yes, Workday, Salesforce, other companies, commercial companies are great companies, but my competitors can use Workday or Salesforce, some of those commercial companies. That doesn't gimme a competitive advantage, what gives me a competitive advantage is building custom software that better engage my customers, that transforms my business in adding new capabilities or drives more efficiency. And the applications are only getting smarter. And so you're seeing that innovation explode and that plays to our strength. People need platforms like MongoDB to build the next generation of applications. >> So Atlas is now roughly 60% of your business, think is growing at 85%. So it's at least the midterm future. But my question to you is, is it the future? 'Cause when we start to think about the edge, it's not necessarily the cloud. You're not going to be able to go that round trip and the latency. And we had Verizon on earlier, talking about what they're doing with 5G, and the Mobile Edge. Is Mongo positioning for that edge? And is our definition of cloud changing? Where it's not just OnPrem and across clouds, but it's also out to the edge, this continuous experience. >> So I'll make two points. One, definitely we believe the applications of the future will be mobile first or purely mobile. Because one with the advent of 5G, the distinction between mobile and web is going to blur, with a hundred times faster networking speeds. But the second point I make is that how that shows up on our revenue on our income table will look like Atlas. Because we don't charge nothing for the end point, it's basically driving consumption of the back end. And so we've introduced a bunch of very, very sophisticated capabilities to synchronized data from the edge to the backend and vice versa with things like flexible sync. So we see so many customers now using that capability, whether you're field service technicians, whether you're a mobile first company, et cetera. So that will drive Atlas revenue. So on an income statement, it'll look like Atlas, but we're obviously addressing those broader set of mobile needs. >> You talk a lot about product market fit former VC, of course, Mark Andreen says, product market fit you kind of know when you see it, your hair's on fire, you can't buy a service. How do you know when you have product market fit? >> Well, one, we have the luxury of lots of customers. So they tell us pretty clearly when they're happy, and we can see that by usage behavior. Now the other benefit of a cloud service, is we can see the level of activity. We can see the level of engagement. We can see how much data they're consuming. We can see all the actions they're taking. So you get the fidelity of feedback you get from Atlas versus someone doing something behind their own firewall. And you kind of call 'em and check in on them is very, very different. So that level of insight gives us visibility in terms of what products and features have been used, gives us a sense how things going well, or is there something awry. Maybe they have misconfigured something or they don't know how to use some capabilities. So the level of engagement that we can have with a customer using a service is so much different. And so we've really invested in our customer success organization. So the byproduct of that is that our retention rates are also very, very strong. Because you have such better information about what's happening in terms of your customers. >> See retention in real time. You've been somewhat... Is just so hard to say this 'cause you're growing at 50% a year. But you're somewhat conservative about the pace of hiring for go to market. And I'm curious as to how you think about scaling, especially when you introduce new products. Atlas is several years ago. But as you extend your capabilities and add new products, how do you decide when to scale? >> So it's a constant process. We've been quite aggressive in scaling organization for a couple reasons. One, we have very low market share, so the market's vastly under penetrated. We still don't have reps in every NFL sitting in the United States, which just kind of crazy. There's other parts of the world that we are just still vastly under penetrated in. But we also look at how those organizations are doing. So if we see a team really killing it, we're going to deploy more resources. Because one, it tells us there's more opportunity there, and there's a strong team there. If we see a team that maybe is struggling a little bit, we'll try and uncover. Rather than just applying more resources in, we'll try and uncover what are the issues and make sure we stabilize the organization and then devote resources. It's all in the measure of like being very disciplined about where we deploy our resources, to get those kind of returns. And on the product side, we obviously go through a very iterative process and kind of do rank order all the projects and what we think the expected returns are. Obviously, we look at the customer feedback, we look at what our strategic priorities are. And that informs what projects we fund and what projects kind of are below the line. And we do that over and over again every quarter. So every quarter we revisit the business, we have a very QBR centric culture. So we're constantly checking in and seeing how the business is operating. And then we make those investment decisions. In general, we've been investing very aggressively in terms of expanding our reach around the world. >> It seems like, well, with Mongo, your product portfolios... From an outside observer standpoint, it seems like you've always had pretty good product market fit. But I was curious, in your VC days, would you ever encourage companies to scale go to market prior to having confidence in product market fit? Or did you always see those as sequential activities? >> Well, I think the challenge is this part it's analysis part is judgment. So you don't necessarily have to have perfect product market fit to start investing. But you also don't want to plow a bunch of resources and realize the product doesn't work and then how you're burning through a lot of cash. So there's a little bit of art to the process. When I joined MongoDB, I could tell that we had a strong engineering team. They knew how to build high quality products, but we just struggled with commercialization. The culture wasn't great across the company. And we had some leadership challenges. So that's when I joined, I kind of focused on those things and tried to bring the organization together. And slowly we started chipping away and making people feel like they were winners. And once you start winning, that becomes contagious. And then the nice thing is when you start winning, you get a lot more customer feedback. That feedback helps you refine your products even more, which then adds... It's like the flywheel effect that starts taking off. >> So it seems the culture's working now. Do you have a favorite product from the announcements today? >> Well, I really like our foray to analytics. And essentially what we're seeing is really two big trends. One you're seeing applications get smarter. What applications are doing is really automating a lot of processes and rather than someone having to press a button. Based on analytics, you can automate a lot of decision making. So that's one theme that we're seeing as applications get smarter. The second theme is that people want more and more insight in terms of what's happening. And the source of that is insights is your operational database. Because that's where you're having transactions, that's where you know what products are selling, that's where you know what customers are buying. So people want more and more real time data versus waiting to take that data, put it somewhere else and then run reports and then get some update at the end of the night or maybe at the week. So that's driving a lot of really interesting use cases. And especially when you marry in things like time series use cases where you're collecting a lot of data people want to see trend analysis what's happening. Which I think it's a very exciting area. We introduced a very cool feature called Queryable Encryption, which basically... The problem with encrypting data, is you can't really query it because my definition's encrypted. >> Yeah, you're right. >> But obviously data security is very important. What we announced, is we're using very sophisticated cryptography. People can query the data, but they don't have really access to the data. So it really protects you from like data breaches or malicious users accessing your data, but you still can kind of make that data usable. So that was a very interesting announcer that we made today. >> Sounds like magic without the performance hit. >> Yes. >> You can do that. Dev, thanks so much for coming in The Cube. Congratulations on all activity, bumper sticker on day one. >> Oh, it's super exciting. The energy was palpable, 3,300 people in the room, lots of customers, lots of users. We had lots of investors here as well for our investor day, have a dinner tonight with a bunch of senior execs, so it's been a busy day. >> Future is bright for MongoBD. Dev, thanks for so much for coming on The Cube. And thanks for watching, this is Dave Vellante and we'll see you next time. (upbeat music)

>> In this session, we will be reviewing the power and benefits of implementing a secure software supply chain and how we can gain a cloud like experience with the flexibility, speed and security of modern software delivering. Hi, I'm Matt Bentley and I run our technical pre-sales team here at Mirantis. I spent the last six years working with customers on their containerization journey. One thing almost every one of my customers has focused on is how they can leverage the speed and agility benefits of containerizing their applications while continuing to apply the same security controls. One of the most important things to remember is that we are all doing this for one reason and that is for our applications. So now let's take a look at how we can provide flexibility to all layers of the stack from the infrastructure on up to the application layer. When building a secure supply chain for container focused platforms, I generally see two different mindsets in terms of where their responsibilities lie between the developers of the applications and the operations teams who run the middleware platforms. Most organizations are looking to build a secure, yet robust service that fits their organization's goals around how modern applications are built and delivered. First, let's take a look at the developer or application team approach. This approach falls more of the DevOps philosophy, where a developer and application teams are the owners of their applications from the development through their life cycle, all the way to production. I would refer to this more of a self service model of application delivery and promotion when deployed to a container platform. This is fairly common, organizations where full stack responsibilities have been delegated to the application teams. Even in organizations where full stack ownership doesn't exist, I see the self service application deployment model work very well in lab development or non production environments. This allows teams to experiment with newer technologies, which is one of the most effective benefits of utilizing containers. In other organizations, there is a strong separation between responsibilities for developers and IT operations. This is often due to the complex nature of controlled processes related to the compliance and regulatory needs. Developers are responsible for their application development. This can either include dock at the development layer or be more traditional, throw it over the wall approach to application development. There's also quite a common experience around building a center of excellence with this approach where we can take container platforms and be delivered as a service to other consumers inside of the IT organization. This is fairly prescriptive in the manner of which application teams would consume it. Yeah when examining the two approaches, there are pros and cons to each. Process, controls and compliance are often seen as inhibitors to speed. Self-service creation, starting with the infrastructure layer, leads to inconsistency, security and control concerns, which leads to compliance issues. While self-service is great, without visibility into the utilization and optimization of those environments, it continues the cycles of inefficient resource utilization. And a true infrastructure as a code experience, requires DevOps, related coding skills that teams often have in pockets, but maybe aren't ingrained in the company culture. Luckily for us, there is a middle ground for all of this. Docker Enterprise Container Cloud provide the foundation for the cloud like experience on any infrastructure without all of the out of the box security and controls that our professional services team and your operations teams spend their time designing and implementing. This removes much of the additional work and worry around ensuring that your clusters and experiences are consistent, while maintaining the ideal self service model. No matter if it is a full stack ownership or easing the needs of IT operations. We're also bringing the most natural Kubernetes experience today with Lens to allow for multi-cluster visibility that is both developer and operator friendly. Lens provide immediate feedback for the health of your applications, observability for your clusters, fast context switching between environments and allowing you to choose the best in tool for the task at hand, whether it is the graphic user interface or command line interface driven. Combining the cloud like experience with the efficiencies of a secure supply chain that meet your needs brings you the best of both worlds. You get DevOps speed with all the security and controls to meet the regulations your business lives by. We're talking about more frequent deployments, faster time to recover from application issues and better code quality. As you can see from our clusters we have worked with, we're able to tie these processes back to real cost savings, real efficiency and faster adoption. This all adds up to delivering business value to end users in the overall perceived value. Now let's look and see how we're able to actually build a secure supply chain to help deliver these sorts of initiatives. In our example secure supply chain, where utilizing Docker desktop to help with consistency of developer experience, GitHub for our source control, Jenkins for our CACD tooling, the Docker trusted registry for our secure container registry and the Universal Control Plane to provide us with our secure container runtime with Kubernetes and Swarm, providing a consistent experience, no matter where our clusters are deployed. You work with our teams of developers and operators to design a system that provides a fast, consistent and secure experience. For my developers, that works for any application, Brownfield or Greenfield, Monolith or Microservice. Onboarding teams can be simplified with integrations into enterprise authentication services, calls to GitHub repositories, Jenkins access and jobs, Universal Control Plan and Docker trusted registry teams and organizations, Kubernetes namespace with access control, creating Docker trusted registry namespaces with access control, image scanning and promotion policies. So, now let's take a look and see what it looks like from the CICD process, including Jenkins. So let's start with Docker desktop. From the Docker desktop standpoint, we'll actually be utilizing visual studio code and Docker desktop to provide a consistent developer experience. So no matter if we have one developer or a hundred, we're going to be able to walk through a consistent process through Docker container utilization at the development layer. Once we've made our changes to our code, we'll be able to check those into our source code repository. In this case, we'll be using GitHub. Then when Jenkins picks up, it will check out that code from our source code repository, build our Docker containers, test the application that will build the image, and then it will take the image and push it to our Docker trusted registry. From there, we can scan the image and then make sure it doesn't have any vulnerabilities. Then we can sign them. So once we've signed our images, we've deployed our application to dev, we can actually test our application deployed in our real environment. Jenkins will then test the deployed application. And if all tests show that as good, we'll promote our Docker image to production. So now, let's look at the process, beginning from the developer interaction. First of all, let's take a look at our application as it's deployed today. Here, we can see that we have a change that we want to make on our application. So our marketing team says we need to change containerize NGINX to something more Mirantis branded. So let's take a look at visual studio code, which we'll be using for our ID to change our application. So here's our application. We have our code loaded and we're going to be able to use Docker desktop on our local environment with our Docker desktop plugin for visual studio code, to be able to build our application inside of Docker, without needing to run any command line specific tools. Here with our code, we'll be able to interact with Docker maker changes, see it live and be able to quickly see if our changes actually made the impact that we're expecting our application. So let's find our updated tiles for application and let's go ahead and change that to our Mirantis sized NGINX instead of containerized NGINX. So we'll change it in a title and on the front page of the application. So now that we've saved that changed to our application, we can actually take a look at our code here in VS code. And as simple as this, we can right click on the Docker file and build our application. We give it a name for our Docker image and VS code will take care of the automatic building of our application. So now we have a Docker image that has everything we need in our application inside of that image. So, here we can actually just right click on that image tag that we just created and do run. This will interactively run the container for us. And then once our containers running, we can just right click and open it up in a browser. So here we can see the change to our application as it exists live. So, once we can actually verify that our applications working as expected, we can stop our container. And then from here, we can actually make that change live by pushing it to our source code repository. So here, we're going to go ahead and make a commit message to say that we updated to our Mirantis branding. We will commit that change and then we'll push it to our source code repository. Again, in this case, we're using GitHub to be able to use as our source code repository. So here in VS code, we'll have that pushed here to our source code repository. And then, we'll move on to our next environment, which is Jenkins. Jenkins is going to be picking up those changes for our application and it checked it out from our source code repository. So GitHub notifies Jenkins that there's a change. Checks out the code, builds our Docker image using the Docker file. So we're getting a consistent experience between the local development environment on our desktop and then in Jenkins where we're actually building our application, doing our tests, pushing it into our Docker trusted registry, scanning it and signing our image in our Docker trusted registry and then deploying to our development environment. So let's actually take a look at that development environment as it's been deployed. So, here we can see that our title has been updated on our application, so we can verify that it looks good in development. If we jump back here to Jenkins, we'll see that Jenkins go ahead and runs our integration tests for our development environment. Everything worked as expected, so it promoted that image for our production repository in our Docker trusted registry. We're then, we're going to also sign that image. So we're assigning that yes, we've signed off that has made it through our integration tests and it's deployed to production. So here in Jenkins, we can take a look at our deployed production environment where our application is live in production. We've made a change, automated and very secure manner. So now, let's take a look at our Docker trusted registry, where we can see our name space for our application and our simple NGINX repository. From here, we'll be able to see information about our application image that we've pushed into the registry, such as the image signature, when it was pushed by who and then, we'll also be able to see the results of our image. In this case, we can actually see that there are vulnerabilities for our image and we'll actually take a look at that. Docker trusted registry does binary level scanning. So we get detailed information about our individual image layers. From here, these image layers give us details about where the vulnerabilities were located and what those vulnerabilities actually are. So if we click on the vulnerability, we can see specific information about that vulnerability to give us details around the severity and more information about what exactly is vulnerable inside of our container. One of the challenges that you often face around vulnerabilities is how exactly we would remediate that in a secure supply chain. So let's take a look at that. In the example that we were looking at, the vulnerability is actually in the base layer of our image. In order to pull in a new base layer for our image, we need to actually find the source of that and update it. One of the ways that we can help secure that as a part of the supply chain is to actually take a look at where we get our base layers of our images. Docker hub really provides a great source of content to start from, but opening up Docker hub within your organization, opens up all sorts of security concerns around the origins of that content. Not all images are made equal when it comes to the security of those images. The official images from Docker hub are curated by Docker, open source projects and other vendors. One of the most important use cases is around how you get base images into your environment. It is much easier to consume the base operating system layer images than building your own and also trying to maintain them. Instead of just blindly trusting the content from Docker hub, we can take a set of content that we find useful such as those base image layers or content from vendors and pull that into our own Docker trusted registry, using our mirroring feature. Once the images have been mirrored into a staging area of our Docker trusted registry, we can then scan them to ensure that the images meet our security requirements. And then based off of the scan result, promote the image to a public repository where you can actually sign the images and make them available to our internal consumers to meet their needs. This allows us to provide a set of curated content that we know is secure and controlled within our environment. So from here, we can find our updated Docker image in our Docker trusted registry, where we can see that the vulnerabilities have been resolved. From a developer's point of view, that's about as smooth as the process gets. Now, let's take a look at how we can provide that secure content for our developers in our own Docker trusted registry. So in this case, we're taking a look at our Alpine image that we've mirrored into our Docker trusted registry. Here, we're looking at the staging area where the images get temporarily pulled because we have to pull them in order to actually be able to scan them. So here we set up mirroring and we can quickly turn it on by making it active. And then we can see that our image mirroring, we'll pull our content from Docker hub and then make it available in our Docker trusted registry in an automatic fashion. So from here, we can actually take a look at the promotions to be able to see how exactly we promote our images. In this case, we created a promotion policy within Docker trusted registry that makes it so that content gets promoted to a public repository for internal users to consume based off of the vulnerabilities that are found or not found inside of the Docker image. So our actual users, how they would consume this content is by taking a look at the public to them, official images that we've made available. Here again, looking at our Alpine image, we can take a look at the tags that exist and we can see that we have our content that has been made available. So we've pulled in all sorts of content from Docker hub. In this case, we've even pulled in the multi architecture images, which we can scan due to the binary level nature of our scanning solution. Now let's take a look at Lens. Lens provides capabilities to be able to give developers a quick opinionated view that focuses around how they would want to view, manage and inspect applications deployed to a Kubernetes cluster. Lens integrates natively out of the box with Universal Control Plane clam bundles. So you're automatically generated TLS certificates from UCP, just work. Inside our organization, we want to give our developers the ability to see their applications in a very easy to view manner. So in this case, let's actually filter down to the application that we just employed to our development environment. Here, we can see the pod for application. And when we click on that, we get instant detailed feedback about the components and information that this pod is utilizing. We can also see here in Lens that it gives us the ability to quickly switch contexts between different clusters that we have access to. With that, we also have capabilities to be able to quickly deploy other types of components. One of those is helm charts. Helm charts are a great way to package up applications, especially those that may be more complex to make it much simpler to be able to consume and inversion our applications. In this case, let's take a look at the application that we just built and deployed. In this case, our simple NGINX application has been bundled up as a helm chart and is made available through Lens. Here, we can just click on that description of our application to be able to see more information about the helm chart. So we can publish whatever information may be relevant about our application. And through one click, we can install our helm chart. Here, it will show us the actual details of the helm charts. So before we install it, we can actually look at those individual components. So in this case, we can see this created an ingress rule. And then this will tell Kubernetes how did it create this specific components of our application. We'd just have to pick a namespace to deploy it to and in this case, we're actually going to do a quick test here because in this case, we're trying to deploy the application from Docker hub. In our Universal Control Plane, we've turned on Docker content trust policy enforcement. So this is actually going to fail to deploy. Because we're trying to employ our application from Docker hub, the image hasn't been properly signed in our environment. So the Docker content trust policy enforcement prevents us from deploying our Docker image from Docker hub. In this case, we have to go through our approved process through our secure supply chain to be able to ensure that we know where our image came from and that meets our quality standards. So if we comment out the Docker hub repository and comment in our Docker trusted registry repository and click install, it will then install the helm chart with our Docker image being pulled from our DTR, which then it has a proper signature. We can see that our application has been successfully deployed through our home chart releases view. From here, we can see that simple NGINX application and in this case, we'll get details around the actual deployed helm chart. The nice thing is, is that Lens provides us this capability here with helm to be able to see all of the components that make up our application. From this view, it's giving us that single pane of glass into that specific application, so that we know all of the components that is created inside of Kubernetes. There are specific details that can help us access the applications such as that ingress rule that we just talked about, gives us the details of that, but it also gives us the resources such as the service, the deployment and ingress that has been created within Kubernetes to be able to actually have the application exist. So to recap, we've covered how we can offer all the benefits of a cloud like experience and offer flexibility around DevOps and operations control processes through the use of a secure supply chain, allowing our developers to spend more time developing and our operators, more time designing systems that meet our security and compliance concerns.

>> So, hi, my name is Daniel Terry, I work as Lead Designer at SEB. So, today we will go through why we are why we are Mirantis' customer, why we choose Docker Enterprise, and mainly what challenges we were facing before we chose to work with Docker, and where we are today, and our keys to success. >> Hi, my name is Johan, I'm a senior developer and a Tech Lead at SEB. I was in the beginning with Docker for like, four years ago. And as Daniel was saying here, we are going to present to you our journey with Docker and the answers. >> Yeah, who are we? We are SEB group. So we are a classic, financial large institutions. So, classic and traditional banking services. In Sweden, we are quite a big bank, one of the largest. And we are on a journey of transforming the bank so it has to be online 24-seven. People can do their banking business every day, whenever they want, nothing should stop them to be online. So this is putting a lot of pressure on us on infrastructure to be able to give them that service. (drum fill) >> So our timeline here. Is look, we started out with how to facilitate the container technology it has to be. 2016. And, in 2018, we had the first Docker running in SEB in a standalone mode. You need that. We didn't have any swarm, or given up this cluster since a while. For 2019, we have our first Docker-prise enterprise cluster at SEB. And today, 2020, we have the latest and greatest version of Docker installed. We are running around approximately two and a fifth at 450 specs. Around a thousand services and around 1500 containers. So, developer challenges. As for me as a developer, previous to Docker was really, really hard to get things in production. Times. It took big things and ordering services and infrastructures was a pain in the... yeah, you know what I mean? So for me, it was all about processes. We use natural processes and meaning that I wasn't able to, to see maintaining my system in production. I was handing that over to our operations teams and operation teams in that time, they didn't know how the application works. They didn't know how to troubleshoot it and see, well, what's going wrong. They were experts on the infrastructure and the platforms, but not on our applications. We were working in silos, meaning that I as a developer, only did developing things. The operations side did their things, and the security side did their things. But we didn't work as a team. I mean, today we have a completely different way of working. We will not see shapes. I mean, we have persons that were really good in maybe MQ technologies, or in some programming language and so on, but we didn't have the knowledge in the team techs to solve things, as we should have. Long lead times. I mean, everything we were trying to do had to follow the processes as we had. I mean that we should fill in some forms, send it away, hopefully someone was getting, getting back to us and saying, yeah guys, we can help you out with these services or this infrastructure, but it takes a really long time to do that. I mean, ordering infrastructure is when you're not an expert on that really hard to do. And often the orders we made or placed were wrong. When we have forms to fill in, it wasn't possible for us to do things automatically. Meaning that we didn't have the code, or the infrastructure as code. Meaning that if we didn't get the right persons into the meetings the first time, we didn't have the possibility to do it the right way, meaning that we had to redo and redo, and hopefully sometimes we got the right. We didn't have consistent set ups between the environments. When we order, as for example, a test environment, we could maybe order it with some minor resources, less CPU, so less memory, less disc or whatever. Or actually less performance on the hardware, but then we moved up to production. We realized that we have different hardware, different discs, different memories, and that could actually cause some serious problems in applications, access-wise. I mean, everyone likes to have exercise, especially if you are the maintainer of the system. That was really, really hard to get. I mean, every system has their own services, their own service, and therefore they need to apply for access to those other services. But today there's a complete difference since we only have one class to produce. Since we don't have infrastructure as a code back then, there were really lots of human errors. I mean, everyone was doing things manually. When you're coming from the Windows perspective, everything is a UI. You tend to prefer that way of working, meaning that if you used to click something in between the environments, the environments will not look the same. Life cycles. I mean, just imagine. When we have the server installed, it's like a pet. You have everything configured all from certificates to port openings, cartels, install patches, you name it. And then imagine that Windows are terminating a version and you need to reinstall that. Everything needs to be redone from the beginning. So there was a really long time taking to, to do the LCM activities, General lack of support of Microservice architecture was really also, a thing that are driving us forward with the containers technology, since we can't scale our applications in the same way as for containers. We, for example, couldn't have two applications or two processes using the same TCP port. For example, if you'd like to scale a web server, you can't do that on the same hardware. You need to have two different servers. And just imagine replacing all the excesses, replacing all the orders again for more hardware, and then manually a setting up there. The low balancer in front is a really huge task to do. And necessarily if you don't have the knowledge how the infrastructure is where you're working, then it's also really hard for you as a developer to do things right. Traditionalist. I mean, the services for us are like pets. They were really, really hard to set up. It'd take maybe a week or so. And if something was wrong with them, we will try to fix them as a pet. I mean, we couldn't just kill them and throw them away. It will actually destroy the application as this, our, like a unit box where all our things are installed. >> So, coming in from the infrastructure part of this, we've also seen challenges. For my team, we're coming from a Windows environment. So doing like a DevOps journey, which we want to do, makes it harder due to our nature in our environments. We are not used to, maybe use API, so we are not used to giving open APIs to our developers to do changes on the servers. Since we are a bank, we don't allow users to log into the servers, which means we have to do things for them all the time. This was very time consuming. And a lot of the challenges we actually still are seeing is the existing infrastructure. You can't just put that container platform on it, and thinking you're sold and everything. One of the biggest issues for us is, has been to getting servers. Windows servers usually takes like 15 minutes, Linux servers can takes up to two week in a bad day. So we really lack like, infrastructure as code. If we want a low balancer, that is also an order form. If we want the firewall opening, that's an order form. Hopefully they will not deny it. So it will go faster. So it's a lot of old processes that we need to go through. So what we wanted to do is that we want to move all of these things to the developers, so they can do it. They can own up their problems, but with our old infrastructure, that wasn't possible. We are a heavily ITIL-based organization, meaning that everything went from a cab. Still does in some way, we have one major service window every month where we take everything down. There is a lot of people involved in everything. So it's quite hard to know what will be done during the maintenance window. We lack supporting tools, or we lacked supporting tools, like log-in, good log-in tools. We have a bunch of CI/CD tools, but the maturity level of the infrastructure team wasn't that good. Again, order form and processes. If we want to, like, procure, do our procurement on a new like, storage system, or a backup system, we talk about here. So to do it is, for us, with containers, it would solve a lot of problems, because we cause we would then move the problems, not maybe move the problems to the developer, but we would make it able for them to own their own problems. So everything that we have talked about up till now boils down to business drivers. So the management's gave- gave us some policies to, or what they, how they want to change the company, so we can be this agile and fast moving bank. So one of the biggest drivers are cloud readiness, where Containers comes in perfectly. So we can build it on premises, and then we can move it to the cloud when we are ready but we can't, but we also need an exit strategy to move it back on premises if we need, due to hard regulations. Maybe you can throw it in the air. >> Absolutely. I definitely can. You're absolutely right. We need to develop things in a certain way. So we can move from infrastructure to infrastructure depending, or regardless of the vendor. Meaning that if we are able to run it on-prem, we should be able to run it in cloud or vice versa. We should also be able to move between clouds, and not be forced into one cloud provider. So that's really important for us at SEB. Short time to market is also a thing here. I mean, we are working with the huge customers. I can't name them, but they're really huge. And they need to have us being moving forward. I mean, able to really fast switch from one technology, maybe to another, we are here for them. And it's really important to us to be really fast for us to get new things out in production. All right, maybe. Nothing else? >> I don't, don't really. From the upside, we are in a huge staff DevOps transition. So, or a forced DevOps transition, which means we need to start looking at new infrastructure solutions, maybe deploy our infrastructure parts inside of containers to be able to use it the same way in the cloud. That's what we do prior, do here on premises, we have private clouds which are built on techno- technology, container technology today. So this fits quite good to have the Docker platform being one part of that one. >> Yeah. And this is solid, we are also working really, really actively on open source platforms and open source drivers. We can see that we have a huge amount of vendors in SEB, really huge ones, but we can also see that we can, facilitate open source platforms, and open source technology as well. So container technology will bring that for us. I mean, instead of having a SaaS platform and SaaS services, we can actually instantiate our own with containers and stuff. >> Also we are, since we are quite heavily regulated, the process of going through to you as like a SaaS service can take up to two years for us to go through, and then maybe the SaaS service, is it, is it what we want to use anymore? So, also we want to develop the things in our own premises and maybe, and scale it to the cloud if we need. And also we want to be an attractive employer, where maybe it's not that, the coolest thing for a young student to work in mainframe, we have a mainframe it's, it's not going anywhere, but it's hard to get people, and we want to be an attractive employer, and everyone is talking Kubernetics and containers or, and clouds. So we need to transition into those technologies. >> Yeah, we need to be open minded and necessarily facilitate the new technologies. So we can actually attract new employees. So it's really important to us to have an open mind. Our experience with Docker Containers. I mean, as I said before, scalability is a really important thing for us today. When we are using a more microservice architecture, we need to be able to Skype. We need to be scaling horizontally instead of vertically. So for that, containers are perfect storage. As we said before, we have a huge problem with environments being differently set up, since it was often manually done. Today, as we have a infrastructure as a code, it's really, really nice to have the same things exactly configured, the same in all environments. And we also have the same tooling, meaning that if I can run it on my machine, it's the same tooling I will be using to run it for test purposes or in production. That's a huge benefit for us as a developer. Time to market. I mean, today, we don't have to order service, we are using the service approach here. So we have a container cluster that are actually just sitting there waiting for our services to be hosted. So no more forms, no more calls, no more meetings before we can set up anything. We also own our problems. I mean, before, as I said, we have the processes, meaning that we ship our applications to any server. And then the operation sites take over. That's not the case now. We are actually using this as we should in DevOps. Meaning the other teams are actually responsible for all their errors as well. Even if it's on the infrastructure part, it's completely different if it's a platform's problem, because then it's the platform's team, and we can use different windows. We can try stuff out, we have an open mind. And that says that I can download and try any container image I would like on my developer machine. It's not maybe, okay to run it in production without having the security people look at it. But normally it's really, really much faster instead of waiting maybe six months, we can maybe wait one week or so. And of course less to none LCM activities. I mean, as I said before, it will take months, maybe, to do an LCM activity on multiple servers. Today, our LCM activities more or less are just switching to a new version of the image from Docker hub. That's all we have to do. So that's actually maintained during the processes we have in CI/CD pipelines. >> And the last one. So our keys to success: you should get demanded from the managers and management that everything should be a container. All the new development has to go through a container before you start ordering servers. Everything shall go through a CI/CD pipeline. We don't actually, here at SEB. Our developers build their own CI/CD pipeline. We just provide a platform for them to use it against, and the CI/CD to systems, but they build everything for themselves. Cause they know how their application works, how it should be deployed, with what tools. We just provide them with a tool set. Build a Cross Team. So you should incorporate all the processes that you need, but you should focus on the developer part, because you are building a platform for the developers, not for operations or security. >> And then maybe >> A lot of... >> you'll be able to take flight >> Yeah. Luck has nothing to do with it? Yes, it has. Of course, luck has something to do with it, even if you're really passionate, even if you're really good at some things. I mean, we got some really nice help from Dr. Inc. We were really... Came in with the technology in the right time for us to be, and we had really engaged people with these projects and that's a really luck for us to have. >> Yeah. And also we... I want to thank our colleagues, because we have another container team who started before us. And they have actually run into a lot of organizational problems, which they have sold, so we could piggyback on that, on those solutions. Also, start small and scale it. This is where Docker swarm comes, fits perfectly. So we have actually, we started with swarm. We are moving into Kubernetics in this platform. We will not force-move anything. The developers just should show us, what their- fits their needs. Thank you! >> Thank you very much.

>>this session will be reviewing the power benefits of implementing a secure software supply chain and how we can gain a cloud like experience with flexibility, speed and security off modern software delivery. Hi, I'm Matt Bentley, and I run our technical pre sales team here. Um Iran. Tous I spent the last six years working with customers on their container ization journey. One thing almost every one of my customers is focused on how they can leverage the speed and agility benefits of contain arising their applications while continuing to apply the same security controls. One of the most important things to remember is that we are all doing this for one reason, and that is for our applications. So now let's take a look at how we could provide flexibility all layers of the stack from the infrastructure on up to the application layer. When building a secure supply chain for container focus platforms, I generally see two different mindsets in terms of where the responsibilities lie between the developers of the applications and the operations teams who run the middleware platforms. Most organizations are looking to build a secure yet robust service that fits the organization's goals around how modern applications are built and delivered. Yeah. First, let's take a look at the developer or application team approach. This approach follows Mawr of the Dev ops philosophy, where a developer and application teams are the owners of their applications. From the development through their life cycle, all the way to production. I would refer this more of a self service model of application, delivery and promotion when deployed to a container platform. This is fairly common organizations where full stack responsibilities have been delegated to the application teams, even in organizations were full stack ownership doesn't exist. I see the self service application deployment model work very well in lab development or non production environments. This allows teams to experiment with newer technologies, which is one of the most effective benefits of utilizing containers and other organizations. There's a strong separation between responsibilities for developers and I T operations. This is often do the complex nature of controlled processes related to the compliance and regulatory needs. Developers are responsible for their application development. This can either include doctorate the development layer or b'more traditional throw it over the wall approach to application development. There's also quite a common experience around building a center of excellence with this approach, where we can take container platforms and be delivered as a service to other consumers inside of the I T organization. This is fairly prescriptive, in the manner of which application teams would consume it. When examining the two approaches, there are pros and cons to each process. Controls and appliance are often seen as inhibitors to speak. Self service creation, starting with the infrastructure layer, leads to inconsistency, security and control concerns, which leads to compliance issues. While self service is great without visibility into the utilization and optimization of those environments, it continues the cycles of inefficient resource utilization and the true infrastructure is a code. Experience requires Dev ops related coding skills that teams often have in pockets but maybe aren't ingrained in the company culture. Luckily for us, there is a middle ground for all of this Doc Enterprise Container Cloud provides the foundation for the cloud like experience on any infrastructure without all of the out of the box security and controls that are professional services Team and your operations team spend their time designing and implementing. This removes much of the additional work and worry Run, ensuring that your clusters and experiences are consistent while maintaining the ideal self service model, no matter if it is a full stack ownership or easing the needs of I T operations. We're also bringing the most natural kubernetes experience today with winds to allow for multi cluster visibility that is both developer and operator friendly. Let's provides immediate feedback for the health of your applications. Observe ability for your clusters. Fast context, switching between environments and allowing you to choose the best in tool for the task at hand. Whether is three graphical user interface or command line interface driven. Combining the cloud like experience with the efficiencies of a secure supply chain that meet your needs brings you the best of both worlds. You get Dave off speed with all the security controls to meet the regulations your business lives by. We're talking about more frequent deployments. Faster time to recover from application issues and better code quality, as you can see from our clusters we have worked with were able to tie these processes back to real cost savings, riel efficiency and faster adoption. This all adds up to delivering business value to end users in the overall perceived value. Now let's look at see how we're able to actually build a secure supply chain. Help deliver these sorts of initiatives in our example. Secure Supply chain. We're utilizing doctor desktop to help with consistency of developer experience. Get hub for our source Control Jenkins for a C A C D. Tooling the doctor trusted registry for our secure container registry in the universal control playing to provide us with our secure container run time with kubernetes and swarm. Providing a consistent experience no matter where are clusters are deployed. You work with our teams of developers and operators to design a system that provides a fast, consistent and secure experience for my developers that works for any application. Brownfield or Greenfield monolith or micro service on boarding teams could be simplified with integrations into enterprise authentication services. Calls to get help repositories. Jenkins Access and Jobs, Universal Control Plan and Dr Trusted registry teams and organizations. Cooper down his name space with access control, creating doctor trusted registry named spaces with access control, image scanning and promotion policies. So now let's take a look and see what it looks like from the C I c D process, including Jenkins. So let's start with Dr Desktop from the doctor desktop standpoint, what should be utilizing visual studio code and Dr Desktop to provide a consistent developer experience. So no matter if we have one developer or 100 we're gonna be able to walk through the consistent process through docker container utilization at the development layer. Once we've made our changes to our code will be able to check those into our source code repository in this case, abusing Get up. Then, when Jenkins picks up, it will check out that code from our source code repository, build our doctor containers, test the application that will build the image, and then it will take the image and push it toward doctor trusted registry. From there, we can scan the image and then make sure it doesn't have any vulnerabilities. Then we consign them. So once we signed our images, we've deployed our application to Dev. We can actually test their application deployed in our real environment. Jenkins will then test the deployed application, and if all tests show that is good, will promote the r R Dr and Mr Production. So now let's look at the process, beginning from the developer interaction. First of all, let's take a look at our application as is deployed today. Here, we can see that we have a change that we want to make on our application. So marketing Team says we need to change containerized injure next to something more Miranda's branded. So let's take a look at visual studio coat, which will be using for I D to change our application. So here's our application. We have our code loaded, and we're gonna be able to use Dr Desktop on our local environment with our doctor desktop plug in for visual studio code to be able to build our application inside of doctor without needing to run any command line. Specific tools here is our code will be able to interact with docker, make our changes, see it >>live and be able to quickly see if our changes actually made the impact that we're expecting our application. Let's find our updated tiles for application and let's go and change that to our Miranda sized into next. Instead of containerized in genetics, so will change in the title and on the front page of the application, so that we save. That changed our application. We can actually take a look at our code here in V s code. >>And as simple as this, we can right click on the docker file and build our application. We give it a name for our Docker image and V s code will take care of the automatic building of our application. So now we have a docker image that has everything we need in our application inside of that image. So here we can actually just right click on the image tag that we just created and do run this winter, actively run the container for us and then what's our containers running? We could just right click and open it up in a browser. So here we can see the change to our application as it exists live. So once we can actually verify that our applications working as expected, weaken, stop our container. And then from here, we can actually make that change live by pushing it to our source code repository. So here we're going to go ahead and make a commit message to say that we updated to our Mantis branding. We will commit that change and then we'll push it to our source code repository again. In this case we're using get Hub to be able to use our source code repository. So here in V s code will have that pushed here to our source code repository. And then we'll move on to our next environment, which is Jenkins. Jenkins is gonna be picking up those changes for our application, and it checked it out from our source code repository. So get Hub Notifies Jenkins. That there is a change checks out. The code builds our doctor image using the doctor file. So we're getting a consistent experience between the local development environment on our desktop and then and Jenkins or actually building our application, doing our tests, pushing in toward doctor trusted registry, scanning it and signing our image. And our doctor trusted registry, then 2.4 development environment. >>So let's actually take a look at that development environment as it's been deployed. So here we can see that our title has been updated on our application so we can verify that looks good and development. If we jump back here to Jenkins, will see that Jenkins go >>ahead and runs our integration tests for a development environment. Everything worked as expected, so it promoted that image for production repository and our doctor trusted registry. Where then we're going to also sign that image. So we're signing that. Yes, we have signed off that has made it through our integration tests, and it's deployed to production. So here in Jenkins, we could take a look at our deployed production environment where our application is live in production. We've made a change automated and very secure manner. >>So now let's take a look at our doctor trusted registry where we can see our game Space for application are simple in genetics repository. From here we will be able to see information about our application image that we've pushed into the registry, such as Thean Midge signature when it was pushed by who and then we'll also be able to see the scan results of our image. In this case, we can actually see that there are vulnerabilities for our image and we'll actually take a look at that. Dr Trusted registry does binary level scanning, so we get detailed information about our individual image layers. From here, these image layers give us details about where the vulnerabilities were located and what those vulnerabilities actually are. So if we click on the vulnerability, we can see specific information about that vulnerability to give us details around the severity and more information about what, exactly is vulnerable inside of our container. One of the challenges that you often face around vulnerabilities is how, exactly we would remediate that and secure supply chain. So let's take a look at that and the example that we were looking at the vulnerability is actually in the base layer of our image. In order to pull in a new base layer of our image, we need to actually find the source of that and updated. One of the ways that we can help secure that is a part of the supply chain is to actually take a look at where we get our base layers of our images. Dr. Help really >>provides a great source of content to start from, but opening up docker help within your organization opens up all sorts of security concerns around the origins of that content. Not all images are made equal when it comes to the security of those images. The official images from Docker, However, curated by docker, open source projects and other vendors, one of the most important use cases is around how you get base images into your environment. It is much easier to consume the base operating system layer images than building your own and also trying to maintain them instead of just blindly trusting the content from doctor. How we could take a set >>of content that we find useful, such as those base image layers or content from vendors, and pull that into our own Dr trusted registry using our rearing feature. Once the images have been mirrored into a staging area of our DACA trusted registry, we can then scan them to ensure that the images meet our security requirements and then, based off the scan result, promote the image toe a public repository where we can actually sign the images and make them available to our internal consumers to meet their needs. This allows us to provide a set of curated content that we know a secure and controlled within our environment. So from here we confined our updated doctor image in our doctor trust registry, where we can see that the vulnerabilities have been resolved from a developers point of view, that's about a smooth process gets. Now let's take a look at how we could provide that secure content for developers and our own Dr Trusted registry. So in this case, we're taking a look at our Alpine image that we've mirrored into our doctor trusted registry. Here we're looking at the staging area where the images get temporarily pulled because we have to pull them in order to actually be able to scan them. So here we set up nearing and we can quickly turn it on by making active. Then we can see that our image mirroring will pull our content from Dr Hub and then make it available in our doctor trusted registry in an automatic fashion. So from here, we can actually take a look at the promotions to be able to see how exactly we promote our images. In this case, we created a promotion policy within docker trusted registry that makes it so. That content gets promoted to a public repository for internal users to consume based off of the vulnerabilities that are found or not found inside of the docker image. So are actually users. How they would consume this content is by taking a look at the public to them official images that we've made available here again, Looking at our Alpine image, we can take a look at the tags that exist. We could see that we have our content that has been made available, so we've pulled in all sorts of content from Dr Hub. In this case, we have even pulled in the multi architectural images, which we can scan due to the binary level nature of our scanning solution. Now let's take a look at Len's. Lens provides capabilities to be able to give developers a quick, opinionated view that focuses around how they would want to view, manage and inspect applications to point to a Cooper Days cluster. Lindsay integrates natively out of the box with universal control playing clam bundles so you're automatically generated. Tell certificates from UCP. Just work inside our organization. We want to give our developers the ability to see their applications and a very easy to view manner. So in this case, let's actually filter down to the application that we just deployed to our development environment. Here we can see the pot for application and we click on that. We get instant, detailed feedback about the components and information that this pot is utilizing. We can also see here in Linz that it gives us the ability to quickly switch context between different clusters that we have access to. With that, we also have capabilities to be able to quickly deploy other types of components. One of those is helm charts. Helm charts are a great way to package of applications, especially those that may be more complex to make it much simpler to be able to consume inversion our applications. In this case, let's take a look at the application that we just built and deployed. This case are simple in genetics. Application has been bundled up as a helm chart and has made available through lens here. We can just click on that description of our application to be able to see more information about the helm chart so we can publish whatever information may be relevant about our application, and through one click, we can install our helm chart here. It will show us the actual details of the home charts. So before we install it, we can actually look at those individual components. So in this case, we could see that's created ingress rule. And then it's well, tell kubernetes how to create the specific components of our application. We just have to pick a name space to to employ it, too. And in this case, we're actually going to do a quick test here because in this case, we're trying to deploy the application from Dr Hub in our universal Control plane. We've turned on Dr Content Trust Policy Enforcement. So this is actually gonna fail to deploy because we're trying to deploy application from Dr Hub. The image hasn't been properly signed in our environment. So the doctor can to trust policy enforcement prevents us from deploying our doctor image from Dr Hub. In this case, we have to go through our approved process through our secure supply chain to be able to ensure that we know our image came from, and that meets our quality standards. So if we comment out the doctor Hub repository and comment in our doctor trusted registry repository and click install, it will then install the helm chart with our doctor image being pulled from our GTR, which then has a proper signature, we can see that our application has been successfully deployed through our home chart releases view. From here, we can see that simple in genetics application, and in this case we'll get details around the actual deploy and help chart. The nice thing is that Linds provides us this capability here with home. To be able to see all the components that make up our application from this view is giving us that single pane of glass into that specific application so that we know all the components that is created inside of kubernetes. There are specific details that can help us access the applications, such as that ingress world that we just talked about gives us the details of that. But it also gives us the resource is such as the service, the deployment in ingress that has been created within kubernetes to be able to actually have the application exist. So to recap, we've covered how we can offer all the benefits of a cloud like experience and offer flexibility around dev ups and operations controlled processes through the use of a secure supply chain, allowing our developers to spend more time developing and our operators mawr time designing systems that meet our security and compliance concerns

(gentle music) >> Okay, welcome back to Supercloud 2, live here in Palo Alto, California for our live stage performance. Supercloud 2 is our second Supercloud event. We're going to get these out as fast as we can every couple months. It's our second one, you'll see two and three this year. I'm John Furrier, my co-host, Dave Vellante. A panel here to break down the Supercloud momentum, the wave, and the developer impact that we bringing back Vittorio Viarengo, who's a VP for Cross-Cloud Services at VMware. Sarbjeet Johal, industry influencer and Analyst at StackPayne, his company, Cube alumni and Influencer. Sarbjeet, great to see you. Vittorio, thanks for coming back. >> Nice to be here. >> My pleasure. >> Vittorio, you just gave a keynote where we unpacked the cross-cloud services, what VMware is doing, how you guys see it, not just from VMware's perspective, but VMware looking out broadly at the industry and developers came up and you were like, "Developers, developer, developers", kind of a goof on the Steve Ballmer famous meme that everyone's seen. This is a huge star, sorry, I mean a big piece of it. The developers are the canary in the coal mines. They're the ones who are being asked to code the digital transformation, which is fully business transformation and with the market the way it is right now in terms of the accelerated technology, every enterprise grade business model's changing. The technology is evolving, the builders are kind of, they want go faster. I'm saying they're stuck in a way, but that's my opinion, but there's a lot of growth. >> Yeah. >> The impact, they got to get released up and let it go. Those developers need to accelerate faster. It's been a big part of productivity, and the conversations we've had. So developer impact is huge in Supercloud. What's your, what do you guys think about this? We'll start with you, Sarbjeet. >> Yeah, actually, developers are the masons of the digital empires I call 'em, right? They lay every brick and build all these big empires. On the left side of the SDLC, or the, you know, when you look at the system operations, developer is number one cost from economic side of things, and from technology side of things, they are tech hungry people. They are developers for that reason because developer nights are long, hours are long, they forget about when to eat, you know, like, I've been a developer, I still code. So you want to keep them happy, you want to hug your developers. We always say that, right? Vittorio said that right earlier. The key is to, in this context, in the Supercloud context, is that developers don't mind mucking around with platforms or APIs or new languages, but they hate the infrastructure part. That's a fact. They don't want to muck around with servers. It's friction for them, it is like they don't want to muck around even with the VMs. So they want the programmability to the nth degree. They want to automate everything, so that's how they think and cloud is the programmable infrastructure, industrialization of infrastructure in many ways. So they are happy with where we are going, and we need more abstraction layers for some developers. By the way, I have this sort of thinking frame for last year or so, not all developers are same, right? So if you are a developer at an ISV, you behave differently. If you are a developer at a typical enterprise, you behave differently or you are forced to behave differently because you're not writing software.- >> Well, developers, developers have changed, I mean, Vittorio, you and I were talking earlier on the keynote, and this is kind of the key point is what is a developer these days? If everything is software enabled, I mean, even hardware interviews we do with Nvidia, and Amazon and other people building silicon, they all say the same thing, "It's software on a chip." So you're seeing the role of software up and down the stack and the role of the stack is changing. The old days of full stack developer, what does that even mean? I mean, the cloud is a half a stack kind of right there. So, you know, developers are certainly more agile, but cloud native, I mean VMware is epitome of operations, IT operations, and the Tan Zoo initiative, you guys started, you went after the developers to look at them, and ask them questions, "What do you need?", "How do you transform the Ops from virtualization?" Again, back to your point, so this hardware abstraction, what is software, what is cloud native? It's kind of messy equation these days. How do you guys grokel with that? >> I would argue that developers don't want the Supercloud. I dropped that up there, so, >> Dave: Why not? >> Because developers, they, once they get comfortable in AWS or Google, because they're doing some AI stuff, which is, you know, very trendy right now, or they are in IBM, any of the IPA scaler, professional developers, system developers, they love that stuff, right? Yeah, they don't, the infrastructure gets in the way, but they're just, the problem is, and I think the Supercloud should be driven by the operators because as we discussed, the operators have been left behind because they're busy with day-to-day jobs, and in most cases IT is centralized, developers are in the business units. >> John: Yeah. >> Right? So they get the mandate from the top, say, "Our bank, they're competing against". They gave teenagers or like young people the ability to do all these new things online, and Venmo and all this integration, where are we? "Oh yeah, we can do it", and then build it, and then deploy it, "Okay, we caught up." but now the operators are back in the private cloud trying to keep the backend system running and so I think the Supercloud is needed for the primarily, initially, for the operators to get in front of the developers, fit in the workflow, but lay the foundation so it is secure.- >> So, so I love this thinking because I love the rift, because the rift points to what is the target audience for the value proposition and if you're a developer, Supercloud enables you so you shouldn't have to deal with Supercloud. >> Exactly. >> What you're saying is get the operating environment or operating system done properly, whether it's architecture, building the platform, this comes back to architecture platform conversations. What is the future platform? Is it a vendor supplied or is it customer created platform? >> Dave: So developers want best to breed, is what you just said. >> Vittorio: Yeah. >> Right and operators, they, 'cause developers don't want to deal with governance, they don't want to deal with security, >> No. >> They don't want to deal with spinning up infrastructure. That's the role of the operator, but that's where Supercloud enables, to John's point, the developer, so to your question, is it a platform where the platform vendor is responsible for the architecture, or there is it an architectural standard that spans multiple clouds that has to emerge? Based on what you just presented earlier, Vittorio, you are the determinant of the architecture. It's got to be open, but you guys determine that, whereas the nirvana is, "Oh no, it's all open, and it just kind of works." >> Yeah, so first of all, let's all level set on one thing. You cannot tell developers what to do. >> Dave: Right, great >> At least great developers, right? Cannot tell them what to do. >> Dave: So that's what, that's the way I want to sort of, >> You can tell 'em what's possible. >> There's a bottle on that >> If you tell 'em what's possible, they'll test it, they'll look at it, but if you try to jam it down their throat, >> Yeah. >> Dave: You can't tell 'em how to do it, just like your point >> Let me answer your answer the question. >> Yeah, yeah. >> So I think we need to build an architect, help them build an architecture, but it cannot be proprietary, has to be built on what works in the cloud and so what works in the cloud today is Kubernetes, is you know, number of different open source project that you need to enable and then provide, use this, but when I first got exposed to Kubernetes, I said, "Hallelujah!" We had a runtime that works the same everywhere only to realize there are 12 different distributions. So that's where we come in, right? And other vendors come in to say, "Hey, no, we can make them all look the same. So you still use Kubernetes, but we give you a place to build, to set those operation policy once so that you don't create friction for the developers because that's the last thing you want to do." >> Yeah, actually, coming back to the same point, not all developers are same, right? So if you're ISV developer, you want to go to the lowest sort of level of the infrastructure and you want to shave off the milliseconds from to get that performance, right? If you're working at AWS, you are doing that. If you're working at scale at Facebook, you're doing that. At Twitter, you're doing that, but when you go to DMV and Kansas City, you're not doing that, right? So your developers are different in nature. They are given certain parameters to work with, certain sort of constraints on the budget side. They are educated at a different level as well. Like they don't go to that end of the degree of sort of automation, if you will. So you cannot have the broad stroking of developers. We are talking about a citizen developer these days. That's a extreme low, >> You mean Low-Code. >> Yeah, Low-Code, No-code, yeah, on the extreme side. On one side, that's citizen developers. On the left side is the professional developers, when you say developers, your mind goes to the professional developers, like the hardcore developers, they love the flexibility, you know, >> John: Well app, developers too, I mean. >> App developers, yeah. >> You're right a lot of, >> Sarbjeet: Infrastructure platform developers, app developers, yes. >> But there are a lot of customers, its a spectrum, you're saying. >> Yes, it's a spectrum >> There's a lot of customers don't want deal with that muck. >> Yeah. >> You know, like you said, AWS, Twitter, the sophisticated developers do, but there's a whole suite of developers out there >> Yeah >> That just want tools that are abstracted. >> Within a company, within a company. Like how I see the Supercloud is there shouldn't be anything which blocks the developers, like their view of the world, of the future. Like if you're blocked as a developer, like something comes in front of you, you are not developer anymore, believe me, (John laughing) so you'll go somewhere else >> John: First of all, I'm, >> You'll leave the company by the way. >> Dave: Yeah, you got to quit >> Yeah, you will quit, you will go where the action is, where there's no sort of blockage there. So like if you put in front of them like a huge amount of a distraction, they don't like it, so they don't, >> Well, the idea of a developer, >> Coming back to that >> Let's get into 'cause you mentioned platform. Get year in the term platform engineering now. >> Yeah. >> Platform developer. You know, I remember back in, and I think there's still a term used today, but when I graduated my computer science degree, we were called "Software engineers," right? Do people use that term "Software engineering", or is it "Software development", or they the same, are they different? >> Well, >> I think there's a, >> So, who's engineering what? Are they engineering or are they developing? Or both? Well, I think it the, you made a great point. There is a factor of, I had the, I was blessed to work with Adam Bosworth, that is the guy that created some of the abstraction layer, like Visual Basic and Microsoft Access and he had so, he made his whole career thinking about this layer, and he always talk about the professional developers, the developers that, you know, give him a user manual, maybe just go at the APIs, he'll build anything, right, from system engine, go down there, and then through obstruction, you get the more the procedural logic type of engineers, the people that used to be able to write procedural logic and visual basic and so on and so forth. I think those developers right now are a little cut out of the picture. There's some No-code, Low-Code environment that are maybe gain some traction, I caught up with Adam Bosworth two weeks ago in New York and I asked him "What's happening to this higher level developers?" and you know what he is told me, and he is always a little bit out there, so I'm going to use his thought process here. He says, "ChapGPT", I mean, they will get to a point where this high level procedural logic will be written by, >> John: Computers. >> Computers, and so we may not need as many at the high level, but we still need the engineers down there. The point is the operation needs to get in front of them >> But, wait, wait, you seen the ChatGPT meme, I dunno if it's a Dilbert thing where it's like, "Time to tic" >> Yeah, yeah, yeah, I did that >> "Time to develop the code >> Five minutes, time to decode", you know, to debug the codes like five hours. So you know, the whole equation >> Well, this ChatGPT is a hot wave, everyone's been talking about it because I think it illustrates something that's NextGen, feels NextGen, and it's just getting started so it's going to get better. I mean people are throwing stones at it, but I think it's amazing. It's the equivalent of me seeing the browser for the first time, you know, like, "Wow, this is really compelling." This is game-changing, it's not just keyword chat bots. It's like this is real, this is next level, and I think the Supercloud wave that people are getting behind points to that and I think the question of Ops and Dev comes up because I think if you limit the infrastructure opportunity for a developer, I think they're going to be handicapped. I mean that's a general, my opinion, the thesis is you give more aperture to developers, more choice, more capabilities, more good things could happen, policy, and that's why you're seeing the convergence of networking people, virtualization talent, operational talent, get into the conversation because I think it's an infrastructure engineering opportunity. I think this is a seminal moment in a new stack that's emerging from an infrastructure, software virtualization, low-code, no-code layer that will be completely programmable by things like the next Chat GPT or something different, but yet still the mechanics and the plumbing will still need engineering. >> Sarbjeet: Oh yeah. >> So there's still going to be more stuff coming on. >> Yeah, we have, with the cloud, we have made the infrastructure programmable and you give the programmability to the programmer, they will be very creative with that and so we are being very creative with our infrastructure now and on top of that, we are being very creative with the silicone now, right? So we talk about that. That's part of it, by the way. So you write the code to the particle's silicone now, and on the flip side, the silicone is built for certain use cases for AI Inference and all that. >> You saw this at CES? >> Yeah, I saw at CES, the scenario is this, the Bosch, I spoke to Bosch, I spoke to John Deere, I spoke to AWS guys, >> Yeah. >> They were showcasing their technology there and I was spoke to Azure guys as well. So the Bosch is a good example. So they are building, they are right now using AWS. I have that interview on camera, I will put it some sometime later on there online. So they're using AWS on the back end now, but Bosch is the number one, number one or number two depending on what day it is of the year, supplier of the componentry to the auto industry, and they are creating a platform for our auto industry, so is Qualcomm actually by the way, with the Snapdragon. So they told me that customers, their customers, BMW, Audi, all the manufacturers, they demand the diversity of the backend. Like they don't want all, they, all of them don't want to go to AWS. So they want the choice on the backend. So whatever they cook in the middle has to work, they have to sprinkle the data for the data sovereign side because they have Chinese car makers as well, and for, you know, for other reasons, competitive reasons and like use. >> People don't go to, aw, people don't go to AWS either for political reasons or like competitive reasons or specific use cases, but for the most part, generally, I haven't met anyone who hasn't gone first choice with either, but that's me personally. >> No, but they're building. >> Point is the developer wants choice at the back end is what I'm hearing, but then finish that thought. >> Their developers want the choice, they want the choice on the back end, number one, because the customers are asking for, in this case, the customers are asking for it, right? But the customers requirements actually drive, their economics drives that decision making, right? So in the middle they have to, they're forced to cook up some solution which is vendor neutral on the backend or multicloud in nature. So >> Yeah, >> Every >> I mean I think that's nirvana. I don't think, I personally don't see that happening right now. I mean, I don't see the parody with clouds. So I think that's a challenge. I mean, >> Yeah, true. >> I mean the fact of the matter is if the development teams get fragmented, we had this chat with Kit Colbert last time, I think he's going to come on and I think he's going to talk about his keynote in a few, in an hour or so, development teams is this, the cloud is heterogenous, which is great. It's complex, which is challenging. You need skilled engineering to manage these clouds. So if you're a CIO and you go all in on AWS, it's hard. Then to then go out and say, "I want to be completely multi-vendor neutral" that's a tall order on many levels and this is the multicloud challenge, right? So, the question is, what's the strategy for me, the CIO or CISO, what do I do? I mean, to me, I would go all in on one and start getting hedges and start playing and then look at some >> Crystal clear. Crystal clear to me. >> Go ahead. >> If you're a CIO today, you have to build a platform engineering team, no question. 'Cause if we agree that we cannot tell the great developers what to do, we have to create a platform engineering team that using pieces of the Supercloud can build, and let's make this very pragmatic and give examples. First you need to be able to lay down the run time, okay? So you need a way to deploy multiple different Kubernetes environment in depending on the cloud. Okay, now we got that. The second part >> That's like table stakes. >> That are table stake, right? But now what is the advantage of having a Supercloud service to do that is that now you can put a policy in one place and it gets distributed everywhere consistently. So for example, you want to say, "If anybody in this organization across all these different buildings, all these developers don't even know, build a PCI compliant microservice, They can only talk to PCI compliant microservice." Now, I sleep tight. The developers still do that. Of course they're going to get their hands slapped if they don't encrypt some messages and say, "Oh, that should have been encrypted." So number one. The second thing I want to be able to say, "This service that this developer built over there better satisfy this SLA." So if the SLA is not satisfied, boom, I automatically spin up multiple instances to certify the SLA. Developers unencumbered, they don't even know. So this for me is like, CIO build a platform engineering team using one of the many Supercloud services that allow you to do that and lay down. >> And part of that is that the vendor behavior is such, 'cause the incentive is that they don't necessarily always work together. (John chuckling) I'll give you an example, we're going to hear today from Western Union. They're AWS shop, but they want to go to Google, they want to use some of Google's AI tools 'cause they're good and maybe they're even arguably better, but they're also a Snowflake customer and what you'll hear from them is Amazon and Snowflake are working together so that SageMaker can be integrated with Snowflake but Google said, "No, you want to use our AI tools, you got to use BigQuery." >> Yeah. >> Okay. So they say, "Ah, forget it." So if you have a platform engineering team, you can maybe solve some of that vendor friction and get competitive advantage. >> I think that the future proximity concept that I talk about is like, when you're doing one thing, you want to do another thing. Where do you go to get that thing, right? So that is very important. Like your question, John, is that your point is that AWS is ahead of the pack, which is true, right? They have the >> breadth of >> Infrastructure by a lot >> infrastructure service, right? They breadth of services, right? So, how do you, When do you bring in other cloud providers, right? So I believe that you should standardize on one cloud provider, like that's your primary, and for others, bring them in on as needed basis, in the subsection or sub portfolio of your applications or your platforms, what ever you can. >> So yeah, the Google AI example >> Yeah, I mean, >> Or the Microsoft collaboration software example. I mean there's always or the M and A. >> Yeah, but- >> You're going to get to run Windows, you can run Windows on Amazon, so. >> By the way, Supercloud doesn't mean that you cannot do that. So the perfect example is say that you're using Azure because you have a SQL server intensive workload. >> Yep >> And you're using Google for ML, great. If you are using some differentiated feature of this cloud, you'll have to go somewhere and configure this widget, but what you can abstract with the Supercloud is the lifecycle manage of the service that runs on top, right? So how does the service get deployed, right? How do you monitor performance? How do you lifecycle it? How you secure it that you can abstract and that's the value and eventually value will win. So the customers will find what is the values, obstructing in making it uniform or going deeper? >> How about identity? Like take identity for instance, you know, that's an opportunity to abstract. Whether I use Microsoft Identity or Okta, and I can abstract that. >> Yeah, and then we have APIs and standards that we can use so eventually I think where there is enough pain, the right open source will emerge to solve that problem. >> Dave: Yeah, I can use abstract things like object store, right? That's pretty simple. >> But back to the engineering question though, is that developers, developers, developers, one thing about developers psychology is if something's not right, they say, "Go get fixing. I'm not touching it until you fix it." They're very sticky about, if something's not working, they're not going to do it again, right? So you got to get it right for developers. I mean, they'll maybe tolerate something new, but is the "juice worth the squeeze" as they say, right? So you can't go to direct say, "Hey, it's, what's a work in progress? We're going to get our infrastructure together and the world's going to be great for you, but just hang tight." They're going to be like, "Get your shit together then talk to me." So I think that to me is the question. It's an Ops question, but where's that value for the developer in Supercloud where the capabilities are there, there's less friction, it's simpler, it solves the complexity problem. I don't need these high skilled labor to manage Amazon. I got services exposed. >> That's what we talked about earlier. It's like the Walmart example. They basically, they took away from the developer the need to spin up infrastructure and worry about all the governance. I mean, it's not completely there yet. So the developer could focus on what he or she wanted to do. >> But there's a big, like in our industry, there's a big sort of flaw or the contention between developers and operators. Developers want to be on the cutting edge, right? And operators want to be on the stability, you know, like we want governance. >> Yeah, totally. >> Right, so they want to control, developers are like these little bratty kids, right? And they want Legos, like they want toys, right? Some of them want toys by way. They want Legos, they want to build there and they want make a mess out of it. So you got to make sure. My number one advice in this context is that do it up your application portfolio and, or your platform portfolio if you are an ISV, right? So if you are ISV you most probably, you're building a platform these days, do it up in a way that you can say this portion of our applications and our platform will adhere to what you are saying, standardization, you know, like Kubernetes, like slam dunk, you know, it works across clouds and in your data center hybrid, you know, whole nine yards, but there is some subset on the next door systems of innovation. Everybody has, it doesn't matter if you're DMV of Kansas or you are, you know, metaverse, right? Or Meta company, right, which is Facebook, they have it, they are building something new. For that, give them some freedom to choose different things like play with non-standard things. So that is the mantra for moving forward, for any enterprise. >> Do you think developers are happy with the infrastructure now or are they wanting people to get their act together? I mean, what's your reaction, or you think. >> Developers are happy as long as they can do their stuff, which is running code. They want to write code and innovate. So to me, when Ballmer said, "Developer, develop, Developer, what he meant was, all you other people get your act together so these developers can do their thing, and to me the Supercloud is the way for IT to get there and let developer be creative and go fast. Why not, without getting in trouble. >> Okay, let's wrap up this segment with a super clip. Okay, we're going to do a sound bite that we're going to make into a short video for each of you >> All right >> On you guys summarizing why Supercloud's important, why this next wave is relevant for the practitioners, for the industry and we'll turn this into an Instagram reel, YouTube short. So we'll call it a "Super clip. >> Alright, >> Sarbjeet, you want, you want some time to think about it? You want to go first? Vittorio, you want. >> I just didn't mind. (all laughing) >> No, okay, okay. >> I'll do it again. >> Go back. No, we got a fresh one. We'll going to already got that one in the can. >> I'll go. >> Sarbjeet, you go first. >> I'll go >> What's your super clip? >> In software systems, abstraction is your friend. I always say that. Abstraction is your friend, even if you're super professional developer, abstraction is your friend. We saw from the MFC library from C++ days till today. Abstract, use abstraction. Do not try to reinvent what's already being invented. Leverage cloud, leverage the platform side of the cloud. Not just infrastructure service, but platform as a service side of the cloud as well, and Supercloud is a meta platform built on top of these infrastructure services from three or four or five cloud providers. So use that and embrace the programmability, embrace the abstraction layer. That's the key actually, and developers who are true developers or professional developers as you said, they know that. >> Awesome. Great super clip. Vittorio, another shot at the plate here for super clip. Go. >> Multicloud is awesome. There's a reason why multicloud happened, is because gave our developers the ability to innovate fast and ever before. So if you are embarking on a digital transformation journey, which I call a survival journey, if you're not innovating and transforming, you're not going to be around in business three, five years from now. You have to adopt the Supercloud so the developer can be developer and keep building great, innovating digital experiences for your customers and IT can get in front of it and not get in trouble together. >> Building those super apps with Supercloud. That was a great super clip. Vittorio, thank you for sharing. >> Thanks guys. >> Sarbjeet, thanks for coming on talking about the developer impact Supercloud 2. On our next segment, coming up right now, we're going to hear from Walmart enterprise architect, how they are building and they are continuing to innovate, to build their own Supercloud. Really informative, instructive from a practitioner doing it in real time. Be right back with Walmart here in Palo Alto. Thanks for watching. (gentle music)

(light music) >> Hi everybody. Welcome to this Cube Conversation. I'm really pleased to announce a collaboration with Rob Strechay. He's a guest cube analyst, and we'll be working together to extract the signal from the noise. Rob is a long-time product pro, working at a number of firms including AWS, HP, HPE, NetApp, Snowplow. I did a stint as an analyst at Enterprise Strategy Group. Rob, good to see you. Thanks for coming into our Marlboro Studios. >> Well, thank you for having me. It's always great to be here. >> I'm really excited about working with you. We've known each other for a long time. You've been in the Cube a bunch. You know, you're in between gigs, and I think we can have a lot of fun together. Covering events, covering trends. So. let's get into it. What's happening out there? We're sort of exited the isolation economy. Things were booming. Now, everybody's tapping the brakes. From your standpoint, what are you seeing out there? >> Yeah. I'm seeing that people are really looking how to get more out of their data. How they're bringing things together, how they're looking at the costs of Cloud, and understanding how are they building out their SaaS applications. And understanding that when they go in and actually start to use Cloud, it's not only just using the base services anymore. They're looking at, how do I use these platforms as a service? Some are easier than others, and they're trying to understand, how do I get more value out of that relationship with the Cloud? They're also consolidating the number of Clouds that they have, I would say to try to better optimize their spend, and getting better pricing for that matter. >> Are you seeing people unhook Clouds, or just reduce maybe certain Cloud activities and going maybe instead of 60/40 going 90/10? >> Correct. It's more like the 90/10 type of rule where they're starting to say, Hey I'm not going to get rid of Azure or AWS or Google. I'm going to move a portion of this over that I was using on this one service. Maybe I got a great two-year contract to start with on this platform as a service or a database as a service. I'm going to unhook from that and maybe go with an independent. Maybe with something like a Snowflake or a Databricks on top of another Cloud, so that I can consolidate down. But it also gives them more flexibility as well. >> In our last breaking analysis, Rob, we identified six factors that were reducing Cloud consumption. There were factors and customer tactics. And I want to get your take on this. So, some of the factors really, you got fewer mortgage originations. FinTech, obviously big Cloud user. Crypto, not as much activity there. Lower ad spending means less Cloud. And then one of 'em, which you kind of disagreed with was less, less analytics, you know, fewer... Less frequency of calculations. I'll come back to that. But then optimizing compute using Graviton or AMD instances moving to cheaper storage tiers. That of course makes sense. And then optimize pricing plans. Maybe going from On Demand, you know, to, you know, instead of pay by the drink, buy in volume. Okay. So, first of all, do those make sense to you with the exception? We'll come back and talk about the analytics piece. Is that what you're seeing from customers? >> Yeah, I think so. I think that was pretty much dead on with what I'm seeing from customers and the ones that I go out and talk to. A lot of times they're trying to really monetize their, you know, understand how their business utilizes these Clouds. And, where their spend is going in those Clouds. Can they use, you know, lower tiers of storage? Do they really need the best processors? Do they need to be using Intel or can they get away with AMD or Graviton 2 or 3? Or do they need to move in? And, I think when you look at all of these Clouds, they always have pricing curves that are arcs from the newest to the oldest stuff. And you can play games with that. And understanding how you can actually lower your costs by looking at maybe some of the older generation. Maybe your application was written 10 years ago. You don't necessarily have to be on the best, newest processor for that application per se. >> So last, I want to come back to this whole analytics piece. Last June, I think it was June, Dev Ittycheria, who's the-- I call him Dev. Spelled Dev, pronounced Dave. (chuckles softly) Same pronunciation, different spelling. Dev Ittycheria, CEO of Mongo, on the earnings call. He was getting, you know, hit. Things were starting to get a little less visible in terms of, you know, the outlook. And people were pushing him like... Because you're in the Cloud, is it easier to dial down? And he said, because we're the document database, we support transaction applications. We're less discretionary than say, analytics. Well on the Snowflake earnings call, that same month or the month after, they were all over Slootman and Scarpelli. Oh, the Mongo CEO said that they're less discretionary than analytics. And Snowflake was an interesting comment. They basically said, look, we're the Cloud. You can dial it up, you can dial it down, but the area under the curve over a period of time is going to be the same, because they get their customers to commit. What do you say? You disagreed with the notion that people are running their calculations less frequently. Is that because they're trying to do a better job of targeting customers in near real time? What are you seeing out there? >> Yeah, I think they're moving away from using people and more expensive marketing. Or, they're trying to figure out what's my Google ad spend, what's my Meta ad spend? And what they're trying to do is optimize that spend. So, what is the return on advertising, or the ROAS as they would say. And what they're looking to do is understand, okay, I have to collect these analytics that better understand where are these people coming from? How do they get to my site, to my store, to my whatever? And when they're using it, how do they they better move through that? What you're also seeing is that analytics is not only just for kind of the retail or financial services or things like that, but then they're also, you know, using that to make offers in those categories. When you move back to more, you know, take other companies that are building products and SaaS delivered products. They may actually go and use this analytics for making the product better. And one of the big reasons for that is maybe they're dialing back how many product managers they have. And they're looking to be more data driven about how they actually go and build the product out or enhance the product. So maybe they're, you know, an online video service and they want to understand why people are either using or not using the whiteboard inside the product. And they're collecting a lot of that product analytics in a big way so that they can go through that. And they're doing it in a constant manner. This first party type tracking within applications is growing rapidly by customers. >> So, let's talk about who wins in that. So, obviously the Cloud guys, AWS, Google and Azure. I want to come back and unpack that a little bit. Databricks and Snowflake, we reported on our last breaking analysis, it kind of on a collision course. You know, a couple years ago we were thinking, okay, AWS, Snowflake and Databricks, like perfect sandwich. And then of course they started to become more competitive. My sense is they still, you know, compliment each other in the field, right? But, you know, publicly, they've got bigger aspirations, they get big TAMs that they're going after. But it's interesting, the data shows that-- So, Snowflake was off the charts in terms of spending momentum and our EPR surveys. Our partner down in New York, they kind of came into line. They're both growing in terms of market presence. Databricks couldn't get to IPO. So, we don't have as much, you know, visibility on their financials. You know, Snowflake obviously highly transparent cause they're a public company. And then you got AWS, Google and Azure. And it seems like AWS appears to be more partner friendly. Microsoft, you know, depends on what market you're in. And Google wants to sell BigQuery. >> Yeah. >> So, what are you seeing in the public Cloud from a data platform perspective? >> Yeah. I think that was pretty astute in what you were talking about there, because I think of the three, Google is definitely I think a little bit behind in how they go to market with their partners. Azure's done a fantastic job of partnering with these companies to understand and even though they may have Synapse as their go-to and where they want people to go to do AI and ML. What they're looking at is, Hey, we're going to also be friendly with Snowflake. We're also going to be friendly with a Databricks. And I think that, Amazon has always been there because that's where the market has been for these developers. So, many, like Databricks' and the Snowflake's have gone there first because, you know, Databricks' case, they built out on top of S3 first. And going and using somebody's object layer other than AWS, was not as simple as you would think it would be. Moving between those. >> So, one of the financial meetups I said meetup, but the... It was either the CEO or the CFO. It was either Slootman or Scarpelli talking at, I don't know, Merrill Lynch or one of the other financial conferences said, I think it was probably their Q3 call. Snowflake said 80% of our business goes through Amazon. And he said to this audience, the next day we got a call from Microsoft. Hey, we got to do more. And, we know just from reading the financial statements that Snowflake is getting concessions from Amazon, they're buying in volume, they're renegotiating their contracts. Amazon gets it. You know, lower the price, people buy more. Long term, we're all going to make more money. Microsoft obviously wants to get into that game with Snowflake. They understand the momentum. They said Google, not so much. And I've had customers tell me that they wanted to use Google's AI with Snowflake, but they can't, they got to go to to BigQuery. So, honestly, I haven't like vetted that so. But, I think it's true. But nonetheless, it seems like Google's a little less friendly with the data platform providers. What do you think? >> Yeah, I would say so. I think this is a place that Google looks and wants to own. Is that now, are they doing the right things long term? I mean again, you know, you look at Google Analytics being you know, basically outlawed in five countries in the EU because of GDPR concerns, and compliance and governance of data. And I think people are looking at Google and BigQuery in general and saying, is it the best place for me to go? Is it going to be in the right places where I need it? Still, it's still one of the largest used databases out there just because it underpins a number of the Google services. So you almost get, like you were saying, forced into BigQuery sometimes, if you want to use the tech on top. >> You do strategy. >> Yeah. >> Right? You do strategy, you do messaging. Is it the right call by Google? I mean, it's not a-- I criticize Google sometimes. But, I'm not sure it's the wrong call to say, Hey, this is our ace in the hole. >> Yeah. >> We got to get people into BigQuery. Cause, first of all, BigQuery is a solid product. I mean it's Cloud native and it's, you know, by all, it gets high marks. So, why give the competition an advantage? Let's try to force people essentially into what is we think a great product and it is a great product. The flip side of that is, they're giving up some potential partner TAM and not treating the ecosystem as well as one of their major competitors. What do you do if you're in that position? >> Yeah, I think that that's a fantastic question. And the question I pose back to the companies I've worked with and worked for is, are you really looking to have vendor lock-in as your key differentiator to your service? And I think when you start to look at these companies that are moving away from BigQuery, moving to even, Databricks on top of GCS in Google, they're looking to say, okay, I can go there if I have to evacuate from GCP and go to another Cloud, I can stay on Databricks as a platform, for instance. So I think it's, people are looking at what platform as a service, database as a service they go and use. Because from a strategic perspective, they don't want that vendor locking. >> That's where Supercloud becomes interesting, right? Because, if I can run on Snowflake or Databricks, you know, across Clouds. Even Oracle, you know, they're getting into business with Microsoft. Let's talk about some of the Cloud players. So, the big three have reported. >> Right. >> We saw AWSs Cloud growth decelerated down to 20%, which is I think the lowest growth rate since they started to disclose public numbers. And they said they exited, sorry, they said January they grew at 15%. >> Yeah. >> Year on year. Now, they had some pretty tough compares. But nonetheless, 15%, wow. Azure, kind of mid thirties, and then Google, we had kind of low thirties. But, well behind in terms of size. And Google's losing probably almost $3 billion annually. But, that's not necessarily a bad thing by advocating and investing. What's happening with the Cloud? Is AWS just running into the law, large numbers? Do you think we can actually see a re-acceleration like we have in the past with AWS Cloud? Azure, we predicted is going to be 75% of AWS IAS revenues. You know, we try to estimate IAS. >> Yeah. >> Even though they don't share that with us. That's a huge milestone. You'd think-- There's some people who have, I think, Bob Evans predicted a while ago that Microsoft would surpass AWS in terms of size. You know, what do you think? >> Yeah, I think that Azure's going to keep to-- Keep growing at a pretty good clip. I think that for Azure, they still have really great account control, even though people like to hate Microsoft. The Microsoft sellers that are out there making those companies successful day after day have really done a good job of being in those accounts and helping people. I was recently over in the UK. And the UK market between AWS and Azure is pretty amazing, how much Azure there is. And it's growing within Europe in general. In the states, it's, you know, I think it's growing well. I think it's still growing, probably not as fast as it is outside the U.S. But, you go down to someplace like Australia, it's also Azure. You hear about Azure all the time. >> Why? Is that just because of the Microsoft's software state? It's just so convenient. >> I think it has to do with, you know, and you can go with the reasoning they don't break out, you know, Office 365 and all of that out of their numbers is because they have-- They're in all of these accounts because the office suite is so pervasive in there. So, they always have reasons to go back in and, oh by the way, you're on these old SQL licenses. Let us move you up here and we'll be able to-- We'll support you on the old version, you know, with security and all of these things. And be able to move you forward. So, they have a lot of, I guess you could say, levers to stay in those accounts and be interesting. At least as part of the Cloud estate. I think Amazon, you know, is hitting, you know, the large number. Laws of large numbers. But I think that they're also going through, and I think this was seen in the layoffs that they were making, that they're looking to understand and have profitability in more of those services that they have. You know, over 350 odd services that they have. And you know, as somebody who went there and helped to start yet a new one, while I was there. And finally, it went to beta back in September, you start to look at the fact that, that number of services, people, their own sellers don't even know all of their services. It's impossible to comprehend and sell that many things. So, I think what they're going through is really looking to rationalize a lot of what they're doing from a services perspective going forward. They're looking to focus on more profitable services and bringing those in. Because right now it's built like a layer cake where you have, you know, S3 EBS and EC2 on the bottom of the layer cake. And then maybe you have, you're using IAM, the authorization and authentication in there and you have all these different services. And then they call it EMR on top. And so, EMR has to pay for that entire layer cake just to go and compete against somebody like Mongo or something like that. So, you start to unwind the costs of that. Whereas Azure, went and they build basically ground up services for the most part. And Google kind of falls somewhere in between in how they build their-- They're a sort of layer cake type effect, but not as many layers I guess you could say. >> I feel like, you know, Amazon's trying to be a platform for the ecosystem. Yes, they have their own products and they're going to sell. And that's going to drive their profitability cause they don't have to split the pie. But, they're taking a piece of-- They're spinning the meter, as Ziyas Caravalo likes to say on every time Snowflake or Databricks or Mongo or Atlas is, you know, running on their system. They take a piece of the action. Now, Microsoft does that as well. But, you look at Microsoft and security, head-to-head competitors, for example, with a CrowdStrike or an Okta in identity. Whereas, it seems like at least for now, AWS is a more friendly place for the ecosystem. At the same time, you do a lot of business in Microsoft. >> Yeah. And I think that a lot of companies have always feared that Amazon would just throw, you know, bodies at it. And I think that people have come to the realization that a two pizza team, as Amazon would call it, is eight people. I think that's, you know, two slices per person. I'm a little bit fat, so I don't know if that's enough. But, you start to look at it and go, okay, if they're going to start out with eight engineers, if I'm a startup and they're part of my ecosystem, do I really fear them or should I really embrace them and try to partner closer with them? And I think the smart people and the smart companies are partnering with them because they're realizing, Amazon, unless they can see it to, you know, a hundred million, $500 million market, they're not going to throw eight to 16 people at a problem. I think when, you know, you could say, you could look at the elastic with OpenSearch and what they did there. And the licensing terms and the battle they went through. But they knew that Elastic had a huge market. Also, you had a number of ecosystem companies building on top of now OpenSearch, that are now domain on top of Amazon as well. So, I think Amazon's being pretty strategic in how they're doing it. I think some of the-- It'll be interesting. I think this year is a payout year for the cuts that they're making to some of the services internally to kind of, you know, how do we take the fat off some of those services that-- You know, you look at Alexa. I don't know how much revenue Alexa really generates for them. But it's a means to an end for a number of different other services and partners. >> What do you make of this ChatGPT? I mean, Microsoft obviously is playing that card. You want to, you want ChatGPT in the Cloud, come to Azure. Seems like AWS has to respond. And we know Google is, you know, sharpening its knives to come up with its response. >> Yeah, I mean Google just went and talked about Bard for the first time this week and they're in private preview or I guess they call it beta, but. Right at the moment to select, select AI users, which I have no idea what that means. But that's a very interesting way that they're marketing it out there. But, I think that Amazon will have to respond. I think they'll be more measured than say, what Google's doing with Bard and just throwing it out there to, hey, we're going into beta now. I think they'll look at it and see where do we go and how do we actually integrate this in? Because they do have a lot of components of AI and ML underneath the hood that other services use. And I think that, you know, they've learned from that. And I think that they've already done a good job. Especially for media and entertainment when you start to look at some of the ways that they use it for helping do graphics and helping to do drones. I think part of their buy of iRobot was the fact that iRobot was a big user of RoboMaker, which is using different models to train those robots to go around objects and things like that, so. >> Quick touch on Kubernetes, the whole DevOps World we just covered. The Cloud Native Foundation Security, CNCF. The security conference up in Seattle last week. First time they spun that out kind of like reinforced, you know, AWS spins out, reinforced from reinvent. Amsterdam's coming up soon, the CubeCon. What should we expect? What's hot in Cubeland? >> Yeah, I think, you know, Kubes, you're going to be looking at how OpenShift keeps growing and I think to that respect you get to see the momentum with people like Red Hat. You see others coming up and realizing how OpenShift has gone to market as being, like you were saying, partnering with those Clouds and really making it simple. I think the simplicity and the manageability of Kubernetes is going to be at the forefront. I think a lot of the investment is still going into, how do I bring observability and DevOps and AIOps and MLOps all together. And I think that's going to be a big place where people are going to be looking to see what comes out of CubeCon in Amsterdam. I think it's that manageability ease of use. >> Well Rob, I look forward to working with you on behalf of the whole Cube team. We're going to do more of these and go out to some shows extract the signal from the noise. Really appreciate you coming into our studio. >> Well, thank you for having me on. Really appreciate it. >> You're really welcome. All right, keep it right there, or thanks for watching. This is Dave Vellante for the Cube. And we'll see you next time. (light music)

(bright upbeat music) >> Hello, wonderful Cloud community and welcome back to our wall-to-wall coverage of AWS re:Invent here in Las Vegas, Nevada. I'm Savannah Peterson, joined by the brilliant John Furrier. John, how you doing this afternoon? >> Doing great, feeling good. We've got day three here, another day tomorrow. Wall-to-wall coverage we're already over a hundred something videos, live getting up. >> You're holding up well. >> And then Cloud show is just popping. It's back to pre-pandemic levels. The audience is here, what recession? But there is one coming but apparently doesn't seem to be an unnoticed with the Cloud community. >> I think, we'll be talking a little bit about that in our next interview in the state of the union. Not just our union, but the the general global economy and the climate there with some fabulous guests from Software One. Please welcome Neil and Bernd, welcome to the show, guys. How you doing? >> Great, thank you. >> Really good. >> Yeah, like you said, just getting over the jet lag. >> Yeah, yeah. Pretty good today, yeah, (laughing loudly) glad we did it today. >> I love that Neil, set your smiling and I can feel your energy. Tell us a little bit about Software One and what you all do. >> Yeah, so Software One we're a software and Cloud solutions provider. We're in 90 countries. We have 65,000 customers. >> Savannah: Just a few. >> Yeah, and we really focus on being close to the customers and helping customers through their software and Cloud journey. So we transact, we sell software in Cloud, 10,000 different ISVs. And then on top of that we a lot of services around the spend optimization FinOps we'll talk about as well, and lots of other areas. But yeah, we're really a large scale partner in this space. >> That's awesome. FinOps, cost optimization, pretty much all we've been talking about here on the give. It's very much a hot topic. I'm actually excited about this and Bernd I'm going to throw this one to you first. We haven't actually done a proper definition of what FinOps is at the show yet. What is FinOps? >> Well, largely speaking it's Cloud cost optimization but for us it's a lot more than for others. That's our superpower. We do it all. We do the technology side but we also do the licensing side. So, we have a differentiated offering. If you would look at the six Rs of application migration we do it all, not even an Accenture as it all. And that is our differentiation. >> You know, yesterday Adams left was on the Keynote. He's like waving his hands around. It's like, "Hey, we got if you want to tighten your belt, come to the Cloud." I'm like, wait a minute. In 2008 when the last recession, Amazon wasn't a factor. They were small. Now they're massive, they're huge. They're a big part of the economic equation. What does belt tightening mean? Like what does that mean? Like do customers just go to the marketplace? Do they go, do you guys, so a lot of moving parts now on how they're buying software and they're fine tuning their Cloud too. It's not just eliminate budget, it's fine tune the machine if you will... >> 'make a smarter Cloud. >> Explain this phenomenon, how people are tackling this cost optimization, Cloud optimization. 'Cause they're not going to stop building. >> No. >> This is right sizing and tuning and cutting. >> Yeah, we see, of course with so many customers in so many countries, we have a lot of different views on maturity and we see customers taking the FinOps journey at different paces. But fundamentally what we see is that it's more of an afterthought and coming in at a panic stage rather than building it and engaging with it from the beginning and doing it continuously. And really that's the huge opportunity and AWS is a big believer in this of continued optimization of the Cloud is a confident Cloud. A confident Cloud means you'll do more with it. If you lose confidence in that bill in what how much it's costing you, you're going to retract. And so it's really about making sure all customers know exactly what's in there, how it's optimized, restocking, reformatting applications, getting more out of the microservices and getting more value out the Cloud and that will help them tighten that belt. >> So the euphoric enthusiasm of previous years of building water just fallen the pipes leaving the lights on when you go to bed. I mean that's kind of the mentality. People were not literally I won't say they weren't not paying attention but there was some just keep going we're all good now it's like whoa, whoa. We turn that service off and no one's using it or do automation. So there's a lot more of that mindset emerging. We're hearing that for the first time price performance being mindful of what's on and off common sense basically. >> Yeah, but it's not just that the lights are on and the faucets are open it's also the air condition is running. So the FinOps foundation is estimating that about a third of Cloud spend is waste and that's where FinOps comes in. We can help customers be more efficient in the Cloud and lower their Cloud spend while doing the same or more. >> So, let's dig in a little bit there. How do you apply FinOps when migrating to the Cloud? >> Well, you start with the business case and you're not just looking at infrastructure costs like most people do you ought look at software licensing costs. For example, if you run SQL on-premise you have an enterprise agreement. But if you move it to the Cloud you may actually take a different more favorable licensing agreement and save a lot of money. And these things are hidden. They're not to be seen but they need to be part of the business case. >> When you look at the modernization trend we had an analyst on our session with David Vellante and Zs (indistinct) from ZK Consulting. He had an interesting comment. He said, "Spend more in Cloud to save more." Which is a mindset that doesn't come across right. Wait a minute, spend more, save more. You can do bet right now with the Clouds kind of the the thesis of FinOps, you don't have to cut. Just kind of cut the waste out but still spend and build if you're smart, there's a lot more of that going on. What does that mean? >> I mean, yeah I've got a good example of this is, we're the largest Microsoft provider in the world. And when of course when you move Microsoft workloads to the Cloud, you don't... Maybe you don't want a server, you can go serverless, right? So you may not win a server. Bernd said SQL, right? So, it's not just about putting applications in the Cloud and workloads in the Cloud. It's about modernizing them and then really taking advantage of what you can really do in the Cloud. And I think that's where the customers are still pretty immature. They're still on that journey of throwing stuff in there and then realizing actually they can take way more advantage of what services are in there to reduce the amount and get even more in there. >> Yeah, and so the... You want to say, something? >> How much, just building on the stereotypical image of Cloud customer is the marketing person with a credit card, right? And there are many of them and they all buy their own Cloud and companies have a hard time consolidating the spend pulling it together, even within a country. But across countries across the globe, it's really, really hard. If you pull it all together, you get a better discount. You spend more to save more. >> Yeah, and also there's a human piece. We had an intern two summers ago playing with our Cloud. We're on a Cloud with our media plus stack left a service was playing around doing some tinkering and like, where's this bill? What is this extra $20,000 came from. It just, we left a service on... >> It's a really good point actually. It's something that we see almost every day right now which is customers also not understanding what they've put in the Cloud and what the implications of spikes are. And also therefore having really robust monitoring and processes and having a partner that can look after that for them. Otherwise we've got customers where they've been really shocked about not doing things the right way because they've empowered the business but also not with the maturity that the business needs to have that responsibility. >> And that's a great point. New people coming in and or people being platooned through new jobs are getting used to the Cloud. That's a great point. I got that brings up my security question 'cause this comes up a lot. So that's what's a lot of spend of people dialing up more security. Obviously people try everything with security, every tool, every platform, and throw everything at the problem. How does that impact the FinOps equation? 'Cause Dev SecOps is now part of everything. Okay, moving security at the CICD pipeline, that's cool. Check Cloud native applications, microservices event-based services check. But now you've got more security. How does that factor into the cost side? What you guys look at that can you share your thoughts on how your customers are managing their security posture without getting kind of over the barrel, if you will? >> Since we are at AWS re:Invent, right? We can talk about the well architected framework of AWS and there's six components to it. And there's reliability, there's security cost, performance quality, operational quality and sustainability. And so when we think about migrating apps to the Cloud or modernizing them in the Cloud security is always a table stakes. >> And it has to be, yeah, go ahead. >> I really like what AWS is doing with us on that. We partner very closely on that area. And to give you a parallel example of Microsoft I don't feel very good about that at the moment. We see a lot of customers right now that get hacked and normally it's... >> 'yeah that's such a topic. >> You mean on Azure? >> Yeah, and what happens is that they normally it's a crypto mining script that the customer comes in they come in as the customer get hacked and then they... We saw an incident the other day where we had 2,100 security incidents in a minute where it all like exploded on the customer side. And so that's also really important is that the customer's understanding that security element also who they're letting in and out of their organization and also the responsibility they have if things go bad. And that's also not aware, like when they get hacked, are they responsible for that? Are they not responsible? Is the provider... >> 'shared responsibility? >> Yeah. >> 'well that security data lake the open cybersecurity schema framework. That's going to be very interesting to see how that plays out to your point. >> Absolutely, absolutely. >> Yeah, it is fascinating and it does require a lot of collaboration. What other trends, what other big challenges are you seeing? You're obviously working with customers at incredible scale. What are some of the other problems you're helping them tackle? >> I think we work with customers from SMB all the way up to enterprise and public sector. But what we see is more in the enterprise space. So we see a lot of customers willing to commit a lot to the Cloud based on all the themes that we've set but not commit financially for all the PNLs that they run in all the business units of all the different companies that they may own in different countries. So it's like, how can I commit but not be responsible on the hook for the bill that comes in. And we see this all the time right now and we are working closely with AWS on this. And we see the ability for customers to commit centrally but decentralized billing, decentralized optimization and decentralized FinOps. So that's that educational layer within the business units who owns the PNL where they get that fitness and they own what they're spending but the company is alone can commit to AWS. And I think that's a big trend that we are seeing is centralized commitment but decentralized ownership in that model. >> And that's where the marketplaces kind of fit in as well. >> Absolutely. >> Yeah, yeah. Do you want to add some more on that? >> I mean the marketplace, if you're going to cut your bill you go to the marketplace right there you want single dashboard or your marketplace what's the customer going to do when they're going to tighten their belts? What do they do? What's their workflow, marketplace? What's the process? >> Well, on marketplaces, the larger companies will have a private marketplace with dedicated pricing managed service they can call off. But that's for the software of the shelf. They still have the data centers they still have all the legacy and they need to do the which ones are we going to keep which ones are we going to retire, we repurchase, we license, rehouse, relocate, all of those things. >> That's your wheelhouse. >> It's a three, yes is our wheelhouse. It's a three to five year process for most companies. >> This could be a tailwind for you guys. This is like a good time. >> I mean FinOps is super cool and super hot right now. >> Not that you're biased? (all laughing loudly) >> But look, it's great to see it because well we are the magic quadrant leader in software asset management, which is a pedigree of ours. But we always had to convince customers to do that because they're always worried, oh what you're going to find do I have an audit? Do I have to give Oracles some more money or SAP some more money? So there's always like, you know... >> 'don't, (indistinct). >> How compliant do I really want? >> Is anyone paying attention to this? >> Well FinOps it's all upside. Like it's all upside. And so it's completely flipped. And now we speak to most customers that are building FinOps internally and then they're like, hold on a minute I'm a bank. Why do I have hundred people doing FinOps? And so that's the trend that we've seen because they just get more and more value out of it all the time. >> Well also the key mindset is that the consumption based model of Cloud you mentioned Oracle 'cause they're stuck in that whoa, whoa, whoa, how many servers license and they're stuck in that extortion. And now they got Cloud once you're on a variable, what's the downside? >> Exactly and then you can look at all the applications, see where you can go serverless see where you can go native services all that sort of stuff is all upside. >> And for the major workloads like SAP and Oracle and Microsoft defined that customers save in the millions. >> Well just on that point, those VMware, SAP, these workloads they're being rolled and encapsulated into containers and Kubernetes run times moved into the Cloud, they're being refactored. So that's a whole nother ballgame. >> Yes. Lift and shift usually doesn't save you any money. So that's relocation with containers may save you money but in some cases you have to... >> 'it's more in the Cloud now than ever before. >> Yeah >> Yeah, yeah. >> Before we take him to the challenge portion we have a little quiz for you, or not a quiz, but a little prop for you in a second. I want to talk about your role. You have a very important role at the FinOps Foundation and why don't you tell me more about that? You, why don't you go. >> All right, so yeah I mean we are a founding member of the Finops organization. You can tell I'm super passionate about it as well. >> I wanted to keep that club like a poster boy for FinOps right now. It's great, I love the energy. >> You have some VA down that is going to go up on the table and dance, (all laughing loudly) >> We're ready for it. We're waiting for that performance here on theCUBE this week. I promise I would keep everyone up an alert... >> 'and it's on the post. And our value to the foundation is first of all the feedback we get from all our customers, right? We can bring that back as an organization to that also as one of the founding members. We're one of the only ones that really deliver services and platforms. So we'll work with Cloud health, Cloud ability our own platform as well, and we'll do that. And we have over 200 practitioners completely dedicated to FinOps as well. So, it's a great foundation, they're doing an amazing job and we're super proud to be part of that. >> Yeah, I love that you're contributing to the community as well as supporting it, looking after your customers. All right, so our new tradition here on theCUBE at re:Invent 'cause we're looking for your 32nd Instagram reel hot take sizzle of thought leadership on the number one takeaway most important theme of the show this year Bernd do you want to go first? >> Of the re:Invent show or whatever? >> You can interpret that however you want. We've gotten some unique interpretations throughout the week, so we're probing. >> Everybody's looking for the superpower to do more with less in the Cloud. That will be the theme of 2023. >> Perfect, I love that. 10 seconds, your mic very efficient. You're clearly providing an efficient solution based on that answer. >> I won't that much. That's... (laughing loudly) >> It's the quiz. And what about you Neil? Give us your, (indistinct) >> I'm going to steal your comment. It's exactly what I was thinking earlier. Tech is super resilient and tech is there for customers when they want to invest and modernize and do fun stuff and they're also there for when they want to save money. So we are always like a constant and you see that here. It's like this is... It's always happening here, always happening. >> It is always happening. It really can feel the energy. I hope that the show is just as energetic and fun for you guys. As the last few minutes here on theCUBE has been thank you both for joining us. >> Thanks. >> Thank you very much. >> And thank you all so much for tuning in. I hope you enjoyed this conversation about FinOps, Cloud confidence and all things AWS re:Invent. We're here in Las Vegas, Nevada with John Furrier, my name is Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (bright upbeat music)

(soft techno upbeat music) >> Hi there. Welcome back to Las Vegas. This is Dave Villante with Paul Gillon. Reinvent day one and a half. We started last night, Monday, theCUBE after dark. Now we're going wall to wall. Today. Today was of course the big keynote, Adam Selipsky, kind of the baton now handing, you know, last year when he did his keynote, he was very new. He was sort of still getting his feet wet and finding his guru swing. Settling in a little bit more this year, learning a lot more, getting deeper into the tech, but of course, sharing the love with other leaders like Peter DeSantis. Tomorrow's going to be Swamy in the keynote. Adrian Cockcroft is here. Former AWS, former network Netflix CTO, currently an analyst. You got your own firm now. You're out there. Great to see you again. Thanks for coming on theCUBE. >> Yeah, thanks. >> We heard you on at Super Cloud, you gave some really good insights there back in August. So now as an outsider, you come in obviously, you got to be impressed with the size and the ecosystem and the energy. Of course. What were your thoughts on, you know what you've seen so far, today's keynotes, last night Peter DeSantis, what stood out to you? >> Yeah, I think it's great to be back at Reinvent again. We're kind of pretty much back to where we were before the pandemic sort of shut it down. This is a little, it's almost as big as the, the largest one that we had before. And everyone's turned up. It just feels like we're back. So that's really good to see. And it's a slightly different style. I think there were was more sort of video production things happening. I think in this keynote, more storytelling. I'm not sure it really all stitched together very well. Right. Some of the stories like, how does that follow that? So there were a few things there and some of there were spelling mistakes on the slides, you know that ELT instead of ETL and they spelled ZFS wrong and something. So it just seemed like there was, I'm not quite sure just maybe a few things were sort of rushed at the last minute. >> Not really AWS like, was it? It's kind of remind the Patriots Paul, you know Bill Belichick's teams are fumbling all over the place. >> That's right. That's right. >> Part of it may be, I mean the sort of the market. They have a leader in marketing right now but they're going to have a CMO. So that's sort of maybe as lack of a single threaded leader for this thing. Everything's being shared around a bit more. So maybe, I mean, it's all fixable and it's mine. This is minor stuff. I'm just sort of looking at it and going there's a few things that looked like they were not quite as good as they could have been in the way it was put together. Right? >> But I mean, you're taking a, you know a year of not doing Reinvent. Yeah. Being isolated. You know, we've certainly seen it with theCUBE. It's like, okay, it's not like riding a bike. You know, things that, you know you got to kind of relearn the muscle memories. It's more like golf than is bicycle riding. >> Well I've done AWS keynotes myself. And they are pretty much scrambled. It looks nice, but there's a lot of scrambling leading up to when it actually goes. Right? And sometimes you can, you sometimes see a little kind of the edges of that, and sometimes it's much more polished. But you know, overall it's pretty good. I think Peter DeSantis keynote yesterday was a lot of really good meat there. There was some nice presentations, and some great announcements there. And today I was, I thought I was a little disappointed with some of the, I thought they could have been more. I think the way Andy Jesse did it, he crammed more announcements into his keynote, and Adam seems to be taking sort of a bit more of a measured approach. There were a few things he picked up on and then I'm expecting more to be spread throughout the rest of the day. >> This was more poetic. Right? He took the universe as the analogy for data, the ocean for security. Right? The Antarctic was sort of. >> Yeah. It looked pretty, >> yeah. >> But I'm not sure that was like, we're not here really to watch nature videos >> As analysts and journalists, You're like, come on. >> Yeah, >> Give it the meat >> That was kind the thing, yeah, >> It has always been the AWS has always been Reinvent has always been a shock at our approach. 100, 150 announcements. And they're really, that kind of pressure seems to be off them now. Their position at the top of the market seems to be unshakeable. There's no clear competition that's creeping up behind them. So how does that affect the messaging you think that AWS brings to market when it doesn't really have to prove that it's a leader anymore? It can go after maybe more of the niche markets or fix the stuff that's a little broken more fine tuning than grandiose statements. >> I think so AWS for a long time was so far out that they basically said, "We don't think about the competition, we are listen to the customers." And that was always the statement that works as long as you're always in the lead, right? Because you are introducing the new idea to the customer. Nobody else got there first. So that was the case. But in a few areas they aren't leading. Right? You could argue in machine learning, not necessarily leading in sustainability. They're not leading and they don't want to talk about some of these areas and-- >> Database. I mean arguably, >> They're pretty strong there, but the areas when you are behind, it's like they kind of know how to play offense. But when you're playing defense, it's a different set of game. You're playing a different game and it's hard to be good at both. I think and I'm not sure that they're really used to following somebody into a market and making a success of that. So there's something, it's a little harder. Do you see what I mean? >> I get opinion on this. So when I say database, David Foyer was two years ago, predicted AWS is going to have to converge somehow. They have no choice. And they sort of touched on that today, right? Eliminating ETL, that's one thing. But Aurora to Redshift. >> Yeah. >> You know, end to end. I'm not sure it's totally, they're fully end to end >> That's a really good, that is an excellent piece of work, because there's a lot of work that it eliminates. There's are clear pain points, but then you've got sort of the competing thing, is like the MongoDB and it's like, it's just a way with one database keeps it simple. >> Snowflake, >> Or you've got on Snowflake maybe you've got all these 20 different things you're trying to integrate at AWS, but it's kind of like you have a bag of Lego bricks. It's my favorite analogy, right? You want a toy for Christmas, you want a toy formula one racing car since that seems to be the theme, right? >> Okay. Do you want the fully built model that you can play with right now? Or do you want the Lego version that you have to spend three days building. Right? And AWS is the Lego technique thing. You have to spend some time building it, but once you've built it, you can evolve it, and you'll still be playing those are still good bricks years later. Whereas that prebuilt to probably broken gathering dust, right? So there's something about having an vulnerable architecture which is harder to get into, but more durable in the long term. And so AWS tends to play the long game in many ways. And that's one of the elements that they do that and that's good, but it makes it hard to consume for enterprise buyers that are used to getting it with a bow on top. And here's the solution. You know? >> And Paul, that was always Andy Chassy's answer to when we would ask him, you know, all these primitives you're going to make it simpler. You see the primitives give us the advantage to turn on a dime in the marketplace. And that's true. >> Yeah. So you're saying, you know, you take all these things together and you wrap it up, and you put a snowflake on top, and now you've got a simple thing or a Mongo or Mongo atlas or whatever. So you've got these layered platforms now which are making it simpler to consume, but now you're kind of, you know, you're all stuck in that ecosystem, you know, so it's like what layer of abstractions do you want to tie yourself to, right? >> The data bricks coming at it from more of an open source approach. But it's similar. >> We're seeing Amazon direct more into vertical markets. They spotlighted what Goldman Sachs is doing on their platform. They've got a variety of platforms that are supposedly targeted custom built for vertical markets. How do successful do you see that play being? Is this something that the customers you think are looking for, a fully integrated Amazon solution? >> I think so. There's usually if you look at, you know the MongoDB or data stacks, or the other sort of or elastic, you know, they've got the specific solution with the people that really are developing the core technology, there's open source equivalent version. The AWS is running, and it's usually maybe they've got a price advantage or it's, you know there's some data integration in there or it's somehow easier to integrate but it's not stopping those companies from growing. And what it's doing is it's endorsing that platform. So if you look at the collection of databases that have been around over the last few years, now you've got basically Elastic Mongo and Cassandra, you know the data stacks as being endorsed by the cloud vendors. These are winners. They're going to be around for a very long time. You can build yourself on that architecture. But what happened to Couch base and you know, a few of the other ones, you know, they don't really fit. Like how you going to bait? If you are now becoming an also ran, because you didn't get cloned by the cloud vendor. So the customers are going is that a safe place to be, right? >> But isn't it, don't they want to encourage those partners though in the name of building the marketplace ecosystem? >> Yeah. >> This is huge. >> But certainly the platform, yeah, the platform encourages people to do more. And there's always room around the edge. But the mainstream customers like that really like spending the good money, are looking for something that's got a long term life to it. Right? They're looking for a long commitment to that technology and that it's going to be invested in and grow. And the fact that the cloud providers are adopting and particularly AWS is adopting some of these technologies means that is a very long term commitment. You can base, you know, you can bet your future architecture on that for a decade probably. >> So they have to pick winners. >> Yeah. So it's sort of picking winners. And then if you're the open source company that's now got AWS turning up, you have to then leverage it and use that as a way to grow the market. And I think Mongo have done an excellent job of that. I mean, they're top level sponsors of Reinvent, and they're out there messaging that and doing a good job of showing people how to layer on top of AWS and make it a win-win both sides. >> So ever since we've been in the business, you hear the narrative hardware's going to die. It's just, you know, it's commodity and there's some truth to that. But hardware's actually driving good gross margins for the Cisco's of the world. Storage companies have always made good margins. Servers maybe not so much, 'cause Intel sucked all the margin out of it. But let's face it, AWS makes most of its money. We know on compute, it's got 25 plus percent operating margins depending on the seasonality there. What do you think happens long term to the infrastructure layer discussion? Okay, commodity cloud, you know, we talk about super cloud. Do you think that AWS, and the other cloud vendors that infrastructure, IS gets commoditized and they have to go up market or you see that continuing I mean history would say that still good margins in hardware. What are your thoughts on that? >> It's not commoditizing, it's becoming more specific. We've got all these accelerators and custom chips now, and this is something, this almost goes back. I mean, I was with some micro systems 20,30 years ago and we developed our own chips and HP developed their own chips and SGI mips, right? We were like, the architectures were all squabbling of who had the best processor chips and it took years to get chips that worked. Now if you make a chip and it doesn't work immediately, you screwed up somewhere right? It's become the technology of building these immensely complicated powerful chips that has become commoditized. So the cost of building a custom chip, is now getting to the point where Apple and Amazon, your Apple laptop has got full custom chips your phone, your iPhone, whatever and you're getting Google making custom chips and we've got Nvidia now getting into CPUs as well as GPUs. So we're seeing that the ability to build a custom chip, is becoming something that everyone is leveraging. And the cost of doing that is coming down to startups are doing it. So we're going to see many, many more, much more innovation I think, and this is like Intel and AMD are, you know they've got the compatibility legacy, but of the most powerful, most interesting new things I think are going to be custom. And we're seeing that with Graviton three particular in the three E that was announced last night with like 30, 40% whatever it was, more performance for HPC workloads. And that's, you know, the HPC market is going to have to deal with cloud. I mean they are starting to, and I was at Supercomputing a few weeks ago and they are tiptoeing around the edge of cloud, but those supercomputers are water cold. They are monsters. I mean you go around supercomputing, there are plumbing vendors on the booth. >> Of course. Yeah. >> Right? And they're highly concentrated systems, and that's really the only difference, is like, is it water cooler or echo? The rest of the technology stack is pretty much off the shelf stuff with a few tweets software. >> You point about, you know, the chips and what AWS is doing. The Annapurna acquisition. >> Yeah. >> They're on a dramatically different curve now. I think it comes down to, again, David Floyd's premise, really comes down to volume. The arm wafer volumes are 10 x those of X 86, volume always wins. And the economics of semis. >> That kind of got us there. But now there's also a risk five coming along if you, in terms of licensing is becoming one of the bottlenecks. Like if the cost of building a chip is really low, then it comes down to licensing costs and do you want to pay the arm license And the risk five is an open source chip set which some people are starting to use for things. So your dis controller may have a risk five in it, for example, nowadays, those kinds of things. So I think that's kind of the the dynamic that's playing out. There's a lot of innovation in hardware to come in the next few years. There's a thing called CXL compute express link which is going to be really interesting. I think that's probably two years out, before we start seeing it for real. But it lets you put glue together entire rack in a very flexible way. So just, and that's the entire industry coming together around a single standard, the whole industry except for Amazon, in fact just about. >> Well, but maybe I think eventually they'll get there. Don't use system on a chip CXL. >> I have no idea whether I have no knowledge about whether going to do anything CXL. >> Presuming I'm not trying to tap anything confidential. It just makes sense that they would do a system on chip. It makes sense that they would do something like CXL. Why not adopt the standard, if it's going to be as the cost. >> Yeah. And so that was one of the things out of zip computing. The other thing is the low latency networking with the elastic fabric adapter EFA and the extensions to that that were announced last night. They doubled the throughput. So you get twice the capacity on the nitro chip. And then the other thing was this, this is a bit technical, but this scalable datagram protocol that they've got which basically says, if I want to send a message, a packet from one machine to another machine, instead of sending it over one wire, I consider it over 16 wires in parallel. And I will just flood the network with all the packets and they can arrive in any order. This is why it isn't done normally. TCP is in order, the packets come in order they're supposed to, but this is fully flooding them around with its own fast retry and then they get reassembled at the other end. So they're not just using this now for HPC workloads. They've turned it on for TCP for just without any change to your application. If you are trying to move a large piece of data between two machines, and you're just pushing it down a network, a single connection, it takes it from five gigabits per second to 25 gigabits per second. A five x speed up, with a protocol tweak that's run by the Nitro, this is super interesting. >> Probably want to get all that AIML that stuff is going on. >> Well, the AIML stuff is leveraging it underneath, but this is for everybody. Like you're just copying data around, right? And you're limited, "Hey this is going to get there five times faster, pushing a big enough chunk of data around." So this is turning on gradually as the nitro five comes out, and you have to enable it at the instance level. But it's a super interesting announcement from last night. >> So the bottom line bumper sticker on commoditization is what? >> I don't think so. I mean what's the APIs? Your arm compatible, your Intel X 86 compatible or your maybe risk five one day compatible in the cloud. And those are the APIs, right? That's the commodity level. And the software is now, the software ecosystem is super portable across those as we're seeing with Apple moving from Intel to it's really not an issue, right? The software and the tooling is all there to do that. But underneath that, we're going to see an arms race between the top providers as they all try and develop faster chips for doing more specific things. We've got cranium for training, that instance has they announced it last year with 800 gigabits going out of a single instance, 800 gigabits or no, but this year they doubled it. Yeah. So 1.6 terabytes out of a single machine, right? That's insane, right? But what you're doing is you're putting together hundreds or thousands of those to solve the big machine learning training problems. These super, these enormous clusters that they're being formed for doing these massive problems. And there is a market now, for these incredibly large supercomputer clusters built for doing AI. That's all bandwidth limited. >> And you think about the timeframe from design to tape out. >> Yeah. >> Is just getting compressed It's relative. >> It is. >> Six is going the other way >> The tooling is all there. Yeah. >> Fantastic. Adrian, always a pleasure to have you on. Thanks so much. >> Yeah. >> Really appreciate it. >> Yeah, thank you. >> Thank you Paul. >> Cheers. All right. Keep it right there everybody. Don't forget, go to thecube.net, you'll see all these videos. Go to siliconangle.com, We've got features with Adam Selipsky, we got my breaking analysis, we have another feature with MongoDB's, Dev Ittycheria, Ali Ghodsi, as well Frank Sluman tomorrow. So check that out. Keep it right there. You're watching theCUBE, the leader in enterprise and emerging tech, right back. (soft techno upbeat music)

>>Welcome back everyone to the Cube and Horizon three.ai special presentation. I'm John Furrier, host of the Cube. We with Chris Hill, Sector head for strategic accounts and federal@horizonthree.ai. Great innovative company. Chris, great to see you. Thanks for coming on the Cube. >>Yeah, like I said, you know, great to meet you John. Long time listener. First time call. So excited to be here with >>You guys. Yeah, we were talking before camera. You had Splunk back in 2013 and I think 2012 was our first splunk.com. Yep. And boy man, you know, talk about being in the right place at the right time. Now we're at another inflection point and Splunk continues to be relevant and continuing to have that data driving security and that interplay. And your ceo, former CTO of Splunk as well at Horizons Neha, who's been on before. Really innovative product you guys have, but you know, Yeah, don't wait for a brief to find out if you're locking the right data. This is the topic of this thread. Splunk is very much part of this new international expansion announcement with you guys. Tell us what are some of the challenges that you see where this is relevant for the Splunk and the Horizon AI as you guys expand Node zero out internationally? >>Yeah, well so across, so you know, my role within Splunk was working with our most strategic accounts. And so I look back to 2013 and I think about the sales process like working with, with our small customers. You know, it was, it was still very siloed back then. Like I was selling to an IT team that was either using us for IT operations. We generally would always even say, yeah, although we do security, we weren't really designed for it. We're a log management tool. And you know, we, and I'm sure you remember back then John, we were like sort of stepping into the security space and in the public sector domain that I was in, you know, security was 70% of what we did. When I look back to sort of the transformation that I was, was witnessing in that digital transformation, you know when I, you look at like 2019 to today, you look at how the IT team and the security teams are, have been forced to break down those barriers that they used to sort of be silo away, would not communicate one, you know, the security guys would be like, Oh this is my BA box it, you're not allowed in today. >>You can't get away with that. And I think that the value that we bring to, you know, and of course Splunk has been a huge leader in that space and continues to do innovation across the board. But I think what we've we're seeing in the space that I was talking with Patrick Kauflin, the SVP of security markets about this, is that, you know, what we've been able to do with Splunk is build a purpose built solution that allows Splunk to eat more data. So Splunk itself, as you well know, it's an ingest engine, right? So the great reason people bought it was you could build these really fast dashboards and grab intelligence out of it, but without data it doesn't do anything, right? So how do you drive and how do you bring more data in? And most importantly from a customer perspective, how do you bring the right data in? >>And so if you think about what node zero and what we're doing in a Horizon three is that, sure we do pen testing, but because we're an autonomous pen testing tool, we do it continuously. So this whole thought of being like, Oh, crud like my customers, Oh yeah, we got a pen test coming up, it's gonna be six weeks. The wait. Oh yeah. You know, and everyone's gonna sit on their hands, Call me back in two months, Chris, we'll talk to you then. Right? Not, not a real efficient way to test your environment and shoot, we, we saw that with Uber this week. Right? You know, and that's a case where we could have helped. >>Well just real quick, explain the Uber thing cause it was a contractor. Just give a quick highlight of what happened so you can connect the >>Dots. Yeah, no problem. So there it was, I think it was one of those, you know, games where they would try and test an environment. And what the pen tester did was he kept on calling them MFA guys being like, I need to reset my password re to set my password. And eventually the customer service guy said, Okay, I'm resetting it. Once he had reset and bypassed the multifactor authentication, he then was able to get in and get access to the domain area that he was in or the, not the domain, but he was able to gain access to a partial part of the network. He then paralleled over to what would I assume is like a VA VMware or some virtual machine that had notes that had all of the credentials for logging into various domains. And so within minutes they had access. And that's the sort of stuff that we do under, you know, a lot of these tools. >>Like not, and I'm not, you know, you think about the cacophony of tools that are out there in a CTA orchestra architecture, right? I'm gonna get like a Zscaler, I'm gonna have Okta, I'm gonna have a Splunk, I'm gonna do this sore system. I mean, I don't mean to name names, we're gonna have crowd strike or, or Sentinel one in there. It's just, it's a cacophony of things that don't work together. They weren't designed work together. And so we have seen so many times in our business through our customer support and just working with customers when we do their pen test, that there will be 5,000 servers out there. Three are misconfigured. Those three misconfigurations will create the open door. Cause remember the hacker only needs to be right once, the defender needs to be right all the time. And that's the challenge. And so that's why I'm really passionate about what we're doing here at Horizon three. I see this my digital transformation, migration and security going on, which we're at the tip of the sp, it's why I joined say Hall coming on this journey and just super excited about where the path's going and super excited about the relationship with Splunk. I get into more details on some of the specifics of that. But you know, >>I mean, well you're nailing, I mean we've been doing a lot of things around super cloud and this next gen environment, we're calling it NextGen. You're really seeing DevOps, obviously Dev SecOps has, has already won the IT role has moved to the developer shift left as an indicator of that. It's one of the many examples, higher velocity code software supply chain. You hear these things. That means that it is now in the developer hands, it is replaced by the new ops, data ops teams and security where there's a lot of horizontal thinking. To your point about access, there's no more perimeter. So >>That there is no perimeter. >>Huge. A hundred percent right, is really right on. I don't think it's one time, you know, to get in there. Once you're in, then you can hang out, move around, move laterally. Big problem. Okay, so we get that. Now, the challenges for these teams as they are transitioning organizationally, how do they figure out what to do? Okay, this is the next step. They already have Splunk, so now they're kind of in transition while protecting for a hundred percent ratio of success. So how would you look at that and describe the challenges? What do they do? What is, what are the teams facing with their data and what's next? What do they, what do they, what action do they take? >>So let's do some vernacular that folks will know. So if I think about dev sec ops, right? We both know what that means, that I'm gonna build security into the app, but no one really talks about SEC DevOps, right? How am I building security around the perimeter of what's going inside my ecosystem and what are they doing? And so if you think about what we're able to do with somebody like Splunk is we could pen test the entire environment from soup to nuts, right? So I'm gonna test the end points through to it. So I'm gonna look for misconfigurations, I'm gonna, and I'm gonna look for credential exposed credentials. You know, I'm gonna look for anything I can in the environment. Again, I'm gonna do it at at light speed. And, and what we're, what we're doing for that SEC dev space is to, you know, did you detect that we were in your environment? >>So did we alert Splunk or the SIM that there's someone in the environment laterally moving around? Did they, more importantly, did they log us into their environment? And when did they detect that log to trigger that log? Did they alert on us? And then finally, most importantly, for every CSO out there is gonna be did they stop us? And so that's how we, we, we do this in, I think you, when speaking with Stay Hall, before, you know, we've come up with this boils U Loop, but we call it fine fix verify. So what we do is we go in is we act as the attacker, right? We act in a production environment. So we're not gonna be, we're a passive attacker, but we will go in un credentialed UN agents. But we have to assume, have an assumed breach model, which means we're gonna put a Docker container in your environment and then we're going to fingerprint the environment. >>So we're gonna go out and do an asset survey. Now that's something that's not something that Splunk does super well, you know, so can Splunk see all the assets, do the same assets marry up? We're gonna log all that data and think then put load that into the Splunk sim or the smoke logging tools just to have it in enterprise, right? That's an immediate future ad that they've got. And then we've got the fix. So once we've completed our pen test, we are then gonna generate a report and we could talk about about these in a little bit later. But the reports will show an executive summary the assets that we found, which would be your asset discovery aspect of that, a fixed report. And the fixed report I think is probably the most important one. It will go down and identify what we did, how we did it, and then how to fix that. >>And then from that, the pen tester or the organization should fix those. Then they go back and run another test. And then they validate through like a change detection environment to see, hey, did those fixes taste, play take place? And you know, SNA Hall, when he was the CTO of JS o, he shared with me a number of times about, he's like, Man, there would be 15 more items on next week's punch sheet that we didn't know about. And it's, and it has to do with how we, you know, how they were prioritizing the CVEs and whatnot because they would take all CVS was critical or non-critical. And it's like we are able to create context in that environment that feeds better information into Splunk and whatnot. That >>Was a lot. That brings, that brings up the, the efficiency for Splunk specifically. The teams out there. By the way, the burnout thing is real. I mean, this whole, I just finished my list and I got 15 more or whatever the list just can, keeps, keeps growing. How did Node zero specifically help Splunk teams be more efficient? Now that's the question I want to get at, because this seems like a very scalable way for Splunk customers and teams, service teams to be more efficient. So the question is, how does Node zero help make Splunk specifically their service teams be more efficient? >>So to, so today in our early interactions with building Splunk customers, what we've seen are five things, and I'll start with sort of identifying the blind spots, right? So kind of what I just talked about with you. Did we detect, did we log, did we alert? Did they stop node zero, right? And so I would, I put that at, you know, a a a more layman's third grade term. And if I was gonna beat a fifth grader at this game would be, we can be the sparring partner for a Splunk enterprise customer, a Splunk essentials customer, someone using Splunk soar, or even just an enterprise Splunk customer that may be a small shop with three people and, and just wants to know where am I exposed. So by creating and generating these reports and then having the API that actually generates the dashboard, they can take all of these events that we've logged and log them in. >>And then where that then comes in is number two is how do we prioritize those logs, right? So how do we create visibility to logs that are, have critical impacts? And again, as I mentioned earlier, not all CVEs are high impact regard and also not all are low, right? So if you daisy chain a bunch of low CVEs together, boom, I've got a mission critical AP CVE that needs to be fixed now, such as a credential moving to an NT box that's got a text file with a bunch of passwords on it, that would be very bad. And then third would be verifying that you have all of the hosts. So one of the things that Splunk's not particularly great at, and they, they themselves, they don't do asset discovery. So do what assets do we see and what are they logging from that? And then for, from, for every event that they are able to identify the, one of the cool things that we can do is actually create this low-code, no-code environment. >>So they could let, you know, float customers can use Splunk. So to actually triage events and prioritize that events or where they're being routed within it to optimize the SOX team time to market or time to triage any given event. Obviously reducing mtr. And then finally, I think one of the neatest things that we'll be seeing us develop is our ability to build glass tables. So behind me you'll see one of our triage events and how we build a lock Lockheed Martin kill chain on that with a glass table, which is very familiar to this Splunk community. We're going to have the ability, not too distant future to allow people to search, observe on those IOCs. And if people aren't familiar with an ioc, it's an incident of compromise. So that's a vector that we want to drill into. And of course who's better at drilling in into data and Splunk. >>Yeah, this is a critical, this is awesome synergy there. I mean I can see a Splunk customer going, Man, this just gives me so much more capability. Action actionability. And also real understanding, and I think this is what I wanna dig into, if you don't mind understanding that critical impact, okay. Is kind of where I see this coming. I got the data, data ingest now data's data. But the question is what not to log, You know, where are things misconfigured? These are critical questions. So can you talk about what it means to understand critical impact? >>Yeah, so I think, you know, going back to those things that I just spoke about, a lot of those CVEs where you'll see low, low, low and then you daisy chain together and you're suddenly like, oh, this is high now. But then to your other impact of like if you're a, if you're a a Splunk customer, you know, and I had, I had several of them, I had one customer that, you know, terabytes of McAfee data being brought in and it was like, all right, there's a lot of other data that you probably also wanna bring, but they could only afford, wanted to do certain data sets because that's, and they didn't know how to prioritize or filter those data sets. And so we provide that opportunity to say, Hey, these are the critical ones to bring in. But there's also the ones that you don't necessarily need to bring in because low CVE in this case really does mean low cve. >>Like an ILO server would be one that, that's the print server where the, your admin credentials are on, on like a, a printer. And so there will be credentials on that. That's something that a hacker might go in to look at. So although the CVE on it is low, if you daisy chain was something that's able to get into that, you might say, ah, that's high. And we would then potentially rank it giving our AI logic to say that's a moderate. So put it on the scale and we prioritize though, versus a, a vulner review scanner's just gonna give you a bunch of CVEs and good luck. >>And translating that if I, if I can and tell me if I'm wrong, that kind of speaks to that whole lateral movement. That's it. Challenge, right? Print server, great example, look stupid low end, who's gonna wanna deal with the print server? Oh, but it's connected into a critical system. There's a path. Is that kind of what you're getting at? >>Yeah, I used daisy chain. I think that's from the community they came from. But it's, it's just a lateral movement. It's exactly what they're doing. And those low level, low critical lateral movements is where the hackers are getting in. Right? So that's what the beauty thing about the, the Uber example is that who would've thought, you know, I've got my multifactor authentication going in a human made a mistake. We can't, we can't not expect humans to make mistakes. Were fall, were fallible, right? Yeah. The reality is is once they were in the environment, they could have protected themselves by running enough pen tests to know that they had certain exposed credentials that would've stopped the breach. Yeah. And they did not, had not done that in their environment. And I'm not poking. Yeah, >>They put it's interesting trend though. I mean it's obvious if sometimes those low end items are also not protected well. So it's easy to get at from a hacker standpoint, but also the people in charge of them can be fished easily or spear fished because they're not paying attention. Cause they don't have to. No one ever told them, Hey, be careful of what you collect. >>Yeah. For the community that I came from, John, that's exactly how they, they would meet you at a, an international event introduce themselves as a graduate student. These are national actor states. Would you mind reviewing my thesis on such and such? And I was at Adobe at the time though I was working on this and start off, you get the pdf, they opened the PDF and whoever that customer was launches, and I don't know if you remember back in like 2002, 2008 time frame, there was a lot of issues around IP being by a nation state being stolen from the United States and that's exactly how they did it. And John, that's >>Or LinkedIn. Hey I wanna get a joke, we wanna hire you double the salary. Oh I'm gonna click on that for sure. You know? Yeah, >>Right. Exactly. Yeah. The one thing I would say to you is like when we look at like sort of, you know, cuz I think we did 10,000 pen test last year is it's probably over that now, you know, we have these sort of top 10 ways that we think then fine people coming into the environment. The funniest thing is that only one of them is a, a CVE related vulnerability. Like, you know, you guys know what they are, right? So it's it, but it's, it's like 2% of the attacks are occurring through the CVEs, but yet there's all that attention spent to that. Yeah. And very little attention spent to this pen testing side. Yeah. Which is sort of this continuous threat, you know, monitoring space and, and, and this vulnerability space where I think we play such an important role and I'm so excited to be a part of the tip of the spear on this one. >>Yeah. I'm old enough to know the movie sneakers, which I love as a, you know, watching that movie, you know, professional hackers are testing, testing, always testing the environment. I love this. I gotta ask you, as we kind of wrap up here, Chris, if you don't mind the benefits to team professional services from this alliance, big news Splunk and you guys work well together. We see that clearly. What are, what other benefits do professional services teams see from the Splunk and Horizon three AI alliance? >>So if you're a, I think for, from our, our, from both of our partners as we bring these guys together and many of them already are the same partner, right? Is that first off, the licensing model is probably one of the key areas that we really excel at. So if you're an end user, you can buy for the enterprise by the enter of IP addresses you're using. But if you're a partner working with this, there's solution ways that you can go in and we'll license as to MSPs and what that business model on our MSPs looks like. But the unique thing that we do here is this c plus license. And so the Consulting Plus license allows like a, somebody a small to midsize to some very large, you know, Fortune 100, you know, consulting firms uses by buying into a license called Consulting Plus where they can have unlimited access to as many ips as they want. >>But you can only run one test at a time. And as you can imagine when we're going and hacking passwords and checking hashes and decrypting hashes, that can take a while. So, but for the right customer, it's, it's a perfect tool. And so I I'm so excited about our ability to go to market with our partners so that we underhand to sell, understand how not to just sell too or not tell just to sell through, but we know how to sell with them as a good vendor partner. I think that that's one thing that we've done a really good job building bringing into market. >>Yeah. I think also the Splunk has had great success how they've enabled partners and professional services. Absolutely. They've, you know, the services that layer on top of Splunk are multifold tons of great benefits. So you guys vector right into that ride, that wave with >>Friction. And, and the cool thing is that in, you know, in one of our reports, which could be totally customized with someone else's logo, we're going to generate, you know, so I, I used to work at another organization, it wasn't Splunk, but we, we did, you know, pen testing as a, as a for, for customers and my pen testers would come on site, they, they do the engagement and they would leave. And then another really, someone would be, oh shoot, we got another sector that was breached and they'd call you back, you know, four weeks later. And so by August our entire pen testings teams would be sold out and it would be like, wow. And in March maybe, and they'd like, No, no, no, I gotta breach now. And, and, and then when they do go in, they go through, do the pen test and they hand over a PDF and they pat you on the back and say, there's where your problems are, you need to fix it. And the reality is, is that what we're gonna generate completely autonomously with no human interaction is we're gonna go and find all the permutations that anything we found and the fix for those permutations and then once you fixed everything, you just go back and run another pen test. Yeah. It's, you know, for what people pay for one pen test, they could have a tool that does that. Every, every pat patch on Tuesday pen test on Wednesday, you know, triage throughout the week, >>Green, yellow, red. I wanted to see colors show me green, green is good, right? Not red. >>And once CIO doesn't want, who doesn't want that dashboard, right? It's, it's, it is exactly it. And we can help bring, I think that, you know, I'm really excited about helping drive this with the Splunk team cuz they get that, they understand that it's the green, yellow, red dashboard and, and how do we help them find more green so that the other guys are >>In Yeah. And get in the data and do the right thing and be efficient with how you use the data, Know what to look at. So many things to pay attention to, you know, the combination of both and then, then go to market strategy. Real brilliant. Congratulations Chris. Thanks for coming on and sharing this news with the detail around this Splunk in action around the alliance. Thanks for sharing, >>John. My pleasure. Thanks. Look forward to seeing you soon. >>All right, great. We'll follow up and do another segment on DevOps and IT and security teams as the new new ops, but, and Super cloud, a bunch of other stuff. So thanks for coming on. And our next segment, the CEO of Verizon, three AA, will break down all the new news for us here on the cube. You're watching the cube, the leader in high tech enterprise coverage.

>>Welcome back to the cubes coverage here in Seattle for AWS marketplace seller conference, the combination of the Amazon partner network, combined with the marketplace from the AWS partner organization, the APO and John Forer host of the queue, bringing you all the action and what it all means. Our next guest is Trisha kata, Malva, chief strategy officer at DataRobot. Great to have you. Thanks for coming on. >>Thank you, John. Great to be here. >>So DataRobot obviously in the big data business data is the big theme here. A lot of companies are in the marketplace selling data solutions. I just ran into snowflake person. I ran into another data analyst company, lot of, lot of data everywhere. You're seeing security. You're seeing insights a lot more going on with data than ever before. It's one of the most popular categories in the marketplace. Talk about DataRobot what you guys are doing. What's your product in there? Yeah, >>Absolutely. John. So we are an artificial intelligence machine learning platform company. We have been around for 10 years. This is this year marks our 10th anniversary and we provide a platform for data scientists and also citizen data scientists. So essentially wanna be data scientists on the business side to rapidly experiment with data and to get insights and then productionize ML models. So the 100% workflow that goes into identifying the data that you need for machine learning and then building models on top of that and operationalizing a, >>How big is the company, roughly employee count? What's the number in >>General general, about a thousand employees. And we have customers all over the world. Our biggest verticals are financial services, insurance, manufacturing, healthcare pharma, all the highly regulated, as well as our tech presence is also growing. And we have people spread across multiple geographies and I can't disclose a customer number, but needless to say, we have hundreds of customers across the >>World. A lot of customers. Yeah, yeah. You guys are well known in the industry have been following some of the recent news lately as well. Yeah. Obviously data's exploding. What in the marketplace are you guys offering? What's the pitch, someone hits the marketplace that wants to buy DataRobot what's the pitch. >>The pitch is if you're looking to get real value from your data science, personal investments and your data, then you have DataRobot that you can download from your AWS marketplace. You can do a free trial and essentially get from, get value from data in a matter of minutes and not months or quarters, that's generally associated with IML. And after that, if you want to purchase you, it's a private offer on, in the marketplace. So you need to call DataRobot representative, but AWS marketplace offers a fantastic distribution channel for us. >>Yeah. I mean, one of the things I heard Chris say, who's now heading up the marketplace and the partner network was the streamlining, a lot of the benefits for the sellers and for the buyers to have a great experience buyers. Clearly we see this as a macro trend, that's gonna only get stronger in terms of self-service buying bundling, having the console on AWS for low level services like infrastructure. But now you've got other business applications that like analytics applies to. You're seeing that work. Now he said things like than the keynote, I wanna get your reaction to like, we're gonna make this more like a C I C D pipeline. We're gonna have more native services built into AWS. What that means to me is that sounds like, oh, if I have a solution, like DataRobot, that can be more native into AWS level services. How do you see that working out for you guys is that play well for your strategy and your customers? What's the, what's the what's resonating with the >>Customers. It plays extremely well with the strategy. So I call this as a win, win, win strategy, win for DataRobot win for customers and win for AWS, which is our partner. And it's a win for DataRobot because the amount of people, the number of eyeballs that look at AWS marketplace, a significantly higher than, than the doors that we can go knock on. So it's a distribution multiplier for us. And the integration into AWS services that you're talking about. It is very important because in this day and age, we need to be interoperable with cloud player services that they offer, whether it is with SageMaker or Redshift, we support all of those. And it's a win for customers because customers, it is a very important growing buyer persona for DataRobot. Yeah. And they already have pre-committed spend with AWS and they can use the, those spend dollars for DataRobot to procure DataRobot. So it eases their procurement life cycle as >>Well. It's a forced multiplier on, on the revenue side, correct? I mean, as well as, as on the business front cost of sales, go down the cost of order dollar. Correct. This is good. Goodness. >>It's it's definitely sorry, just to finish my thought on the win for the partner for AWS. It's great win for them because they're getting the consumption from the partner side, to your point on the force multiplier. Absolutely. It is a force multiplier on the revenue side, and it's great for customers and us, because for us, we have seen that the deal size increases when there is the cloud commit that we can draw down for, for our customers, the procurement cycle shortens. And also we have multiple constituencies within the customers working together in a very seamless fashion. >>How has the procurement going through AWS helped your customers? What specific things are you seeing that are popping out as benefits to the customer? >>So from a procurement standpoint, we, we are early in our marketplace journey. We got listed about a year ago, but the amount of revenue that has gone through marketplace is pretty significant at DataRobot. We experienced like just in, by, I think this quarter until this quarter, we got like about 20 to 30 transactions that went through AWS marketplace. And that is significant within just a year of us operating on the marketplace. And the procurement becomes easier for our customers. Yeah. Because they trust AWS and we can put our legal paperwork through the AWS machine as well, which we haven't done yet. But if we do that, that'll be a further force multiplier because that's the, the less friction there is. >>I like how you say that it's a machine. Yeah. And if you think about the benefits too, like one of the things that I see happening, and I love to get your thoughts because I think this is what's happening here. Infrastructure services, I get that IAS done hardware I'm oversimplifying, but all the, all the goodness, but as customers have business apps and vertical market solutions, you got more AI involved. You need more data that's specialized for that use case. Or you need a business application. Those, you don't hear words like let's provision that app. I mean, your provision hardware and, and infrastructure, but the, the new net cloud native is that you provision turn on the apps. So you're seeing the wave of building apps are composing Lego blocks, if you will. So it seems like the customers are starting to assemble the solution, almost like deploying a service, correct. And just pressing a button. And it happens. This seems to be where the, the business apps are going. >>Yeah, absolutely. You agree for us? We are, we are a data science platform and for us being very close to the data that the customers have is very important. And where if, if the customer's data is in Redshift, we are close to there. So being very close to the hyperscale or ecosystem in that entire C I C D pipeline, and also the data platform pipeline is very important. >>You know, what's interesting is, is the data is such a big part of, I mean, DevOps infrastructure has code has been the movement for decade. Yeah. So throw security in there. It's dev SecOps. Yeah. That is the developer now. Yeah. They're running essentially what used to be it now the new ops is security and data. Yeah. You see, in those teams really level up to be highly high velocity data meshes, semantic layer. These are words I'm hearing in the industry around the big waves of data, having this mesh. Yeah. Having it connected. So you're starting to see data availability become more pervasive. And, and we see this as a way that's powering this next gen data science revolution where it's like the business person is now the data science person. >>That's exactly. That is, that is what DataRobot does the best. We were founded with the vision that we wanted to democratize the access to AI within enterprises. It shouldn't be restricted to a small group of people don't get me wrong. Data scientists also love DataRobot. They use DataRobot. But the mission is to enhance many, many hundreds of people within an organization to use data science, like how you use Tableau on a regular basis, how you use Microsoft Excel on a regular basis. We want to democratize AI. And when you want to democratize AI, you need to democratize access to data, which is, which could be stored in data marketplaces, which could be stored in data warehouses and push all the intelligence that we grab from that data into the E R P into the apps layer. Because at the end of the day, business users, customers consume predictions through applications layer. >>You know, it's interesting, you mentioned that comment about, you know, trying not to, to offend data scientists, it's actually a rising tide that the tsunami of data is actually making that population bigger too. Right. So correct. You also have data engineering, which has come out of the woodwork. We covered a lot on the cube, which is, you know, we call data as code. So infrastructure as code kind of a spoof on that. But the reality is that there's a lot more data engineering. I call that the smallest population. Those are the, those are the alphas, the alpha geeks. Yeah. Hardcore data operating systems, kind of education, data science, big pool growing. And then the users yeah. Are the new data science practitioners. Correct? Exactly. So kind of a, the landscape is you see that picture too, right? >>For sure. I mean, we, we have presence in all of those, right? Like data engineers are very important. Data scientists. Those are core users of DataRobot like, how can you develop thousands and hundreds of thousands of models without having to hand code? If you have to hand code, it takes months and years to solve one problem for one customer in one location. I mean, see how fast the microeconomic conditions are moving. And data engineers are very important because at the end of the day, yes, you do. You create the model, but you need to operationalize that model. You need to monitor that model for data drift. You need to monitor how the model is performing and you need to productionize the insights that you gain. And for that engineering effort is very important behind the scenes. Yeah. And the users at the end of the day, they are the ones who consume the predictions. >>Yeah. I mean the volume and, and the scale and scope of the data requires a lot of automation as well. Correct. Cause you had that on top of it. You gotta have a platform that's gonna do the heavy lifting. >>Correct. Exactly. The platform is we call it as an augmented platform. It augments data scientists by eliminating the tedious work that they don't want to do in their everyday life, which some of which is like feature engineering, right? It's a very high value add work. However, it takes like multiple iterations to understand which features in your data actually impact the outcome. >>This is where the SAS platform is a service is evolved and we call that super cloud, right. This new model where people can scale it out and up. So horizontally, scalable cloud, but vertically integrated into the applications. It's an integrator dilemma. Not so much correct innovators dilemma, as we say in the queue. Yeah. So I have to ask you, I'm a, I'm a buyer I'm gonna come to the marketplace. I want DataRobot why should they buy DataRobot what's in it for them? What's the key features of DataRobot for a company to hit the subscribe, buy button. >>Absolutely. Do you want to scale your data science to multiple projects? Do you want to be ahead of your competition? Do you want to make AI real? That is our pitch. We are not about doing data science for the sake of data science. We are about generating business value out of data science. And we have done it for hundreds of customers in multiple different verticals across the world, whether it is investment banks or regional banks or insurance companies or healthcare companies, we have provided real value out of data for them. And we have the knowhow in how to solve, whether it is your supply chain, forecasting, problem, demand, forecasting problem, whether it is your foreign exchange training problem, how to solve all these use cases with AI, with DataRobot. So if you want to be in the business of using your data and being ahead of your competitors, DataRobot is your tool log choice. >>Sure. Great to have you on the cube as a strategy officer, you gotta look at the chess board, right. And we're kind of in the mid game, I call it the cloud opening game was, you know, happened. Now we're in the mid game of cloud computing where you're seeing a lot of refactoring of opportunities where technologies and data is the key to success, being things secure and operationally, scalable, etcetera, et cetera. What's the key right now for the ecosystem as a strategy, look at the chessboard for data robots. Obviously marketplace is important strategy. Yeah. And bet for, for DataRobot. What else do you see for your company to be successful? And you could share with, with customers watching. >>Yeah. For us, we are in the intelligence layer, the data, the layer below us is the data layer. The layer about us is the applications and the engagement layer. DataRobot I mean, interoperability and ecosystem is important for every company, but for DataRobot it's extra important because we are in that middle of middle layer of intelligence. And we, we have to integrate with all different data warehouses out there enable our customers to pull the data out in a very, very faster way and then showcase all the predictions into, into their tool of choice. And from a chessboard perspective, I like your phrase of we are in the mid cycle of the cloud revolution. Yeah. And every cloud player has a data science platform, whether it is simple one or more complex one, or whether it has been around for quite some time or it's been latent features. And it is important for us that we have complimentary value proposition with all of them, because at the end of the day, we want to maximize our customer's choice. And DataRobot wants to be a neutral platform in supporting all the different vendors out there from a complementary standpoint, because you don't want to have a vendor lock in for your customers. So you create models in SageMaker. For example, you monitor those in DataRobot or you create models in DataRobot and monitor those in AWS so that you have to provide like a very flexible >>That's a solution architecture. >>Correct? Exactly. You have to provide a very flexible tech stack for your customers. >>Yeah. That's the choice. That's the choice. It's all good. Thank you for coming on the cube, sharing the data robot. So I really appreciate it. Thank >>You for coming. Thank you very much for the opportunity. >>Okay. Breaking it all down with the partners here, the marketplace, it's the future, obviously where people are gonna buy the buyers and sellers coming together, the partner network and marketplace, the big news here at 80 seller conference. I'm John ferry with the cube will be right back with more coverage after this short break.

(upbeat music) >> Hello, welcome everyone to "theCUBE" presentation of the AWS Startup Showcase, this is Season Two, Episode Four of the ongoing series covering exciting startups from the AWS ecosystem. Here to talk about Cyber Security. I'm your host John Furrier here joined by two great "CUBE" alumnus, Liz Rice who's the chief open source officer at Isovalent, and Mark Nunnikhoven who's the distinguished cloud strategist at Lacework. Folks, thanks for joining me today. >> Hi. Pleasure. >> You're in the U.K. Mark, welcome back to the U.S, I know you were overseas as well. Thanks for joining in this panel to talk about set the table for the Cybersecurity Showcase. You guys are experts out in the field. Liz we've had many conversations with the rise of open source, and all the innovations coming from out in the open source community. Mark, we've been going and covering the events, looking at all the announcements we're kind of on this next generation security conversation. It's kind of a do over in progress, happening every time we talk security in the cloud, is what people are are talking about. Amazon Web Services had reinforced, which was more of a positive vibe of, Hey, we're all on it together. Let's participate, share information. And they talk about incidents, not breaches. And then, you got Black Hat just happened, and they're like, everyone's getting hacked. It's really interesting as we report that. So, this is a new market that we're in. People are starting to think differently, but still have to solve the same problems. How do you guys see the security in the cloud era unfolding? >> Well, I guess it's always going to be an arms race. Isn't it? Everything that we do to defend cloud workloads, it becomes a new target for the bad guys, so this is never going to end. We're never going to reach a point where everything is completely safe. But I think there's been a lot of really interesting innovations in the last year or two. There's been a ton of work looking into the security of the supply chain. There's been a ton of new tooling that takes advantage of technology that I'm really involved with and very excited about called eBPF. There's been a continuation of this new generation of tooling that can help us observe when security issues are happening, and also prevent malicious activities. >> And it's on to of open source activity. Mark, scale is a big factor now, it's becoming a competitive advantage on one hand. APIs have made the cloud great. Now, you've got APIs being hacked. So, all the goodness of cloud has been great, but now we've got next level scale, it's hard to keep up with everything. And so, you start to see new ways of doing things. What's your take? >> Yeah, it is. And everything that's old is new again. And so, as you start to see data and business workloads move into new areas, you're going to see a cyber crime and security activity move with them. And I love, Liz calling out eBPF and open source efforts because what we've really seen to contrast that sort of positive and negative attitude, is that as more people come to the security table, as more developers, as more executives are aware, and the accessibility of these great open source tools, we're seeing that shift in approach of like, Hey, we know we need to find a balance, so let's figure out where we can have a nice security outcome and still meet our business needs, as opposed to the more, let's say to be polite, traditional security view that you see at some other events where it's like, it's this way or no way. And so, I love to see that positivity and that collaboration happening. >> You know, Liz, this brings up a good point. We were talking at our Super Cloud Event we had here when we were discussing the future of how cloud's emerging. One of the conversations that Adrian Cockcroft brought up, who's now retired from AWS, former with Netflix. Adrian being open source fan as well. He was pointing out that every CIO or CISO will buy an abstraction layer. They love the dream. And vendors sell the dream, so to speak. But the reality it's not a lot of uptake because it's complex, And there's a lot of non-standard things per vendor. Now, we're in an era where people are looking for some standardization, some clean, safe ways to deploy. So, what's the message to CSOs, and CIOs, and CXOs out there around eBPF, things like that, that are emerging? Because it's almost top down, was the old way, now as bottoms up with open source, you're seeing the shift. I mean, it's complete flipping the script of how companies are buying? >> Yeah. I mean, we've seen with the whole cloud native movement, how people are rather than having like ETF standards, we have more of a defacto collaborative, kind of standardization process going on. So, that things like Kubernetes become the defacto standard that we're all using. And then, that's helping enterprises be able to run their workloads in different clouds, potentially in their own data centers as well. We see things like EKS anywhere, which is allowing people to run their workloads in their data center in exactly the same way as they're running it in AWS. That sort of leveling of the playing field, if you like, can help enterprises apply the same tooling, and that's going to always help with security if you can have a consistent approach wherever you are running your workload. >> Well, Liz's take a minute to explain eBPF. The Berkeley packet filtering technology, people know from Trace Dumps and whatnot. It's kind of been around for a while, but what is it specifically? Can you take a minute to explain eBPF, and what does that mean for the customer? >> Yeah. So, you mentioned the packet filtering acronym. And honestly, these days, I tell people to just forget that, because it means so much more for. What eBPF allows you to do now, is to run custom programs inside the kernel. So, we can use that to change the way that the kernel behaves. And because the kernel has visibility over every process that's running across a machine, a virtual machine or a bare metal machine, having security tooling and observability tooling that's written using eBPF and sitting inside the kernel. It has this great perspective and ability to observe and secure what's happening across that entire machine. This is like a step change in the capabilities really of security tooling. And it means we don't have to rely on things like kernel modules, which traditionally people have been quite worried about with good reason. eBPF is- >> From a vulnerability standpoint, you mean, right? From a reliability. >> From a vulnerability standpoint, but even just from the point of view that kernel modules, if they have bugs in them, a bug in the kernel will bring the machine to a halt. And one of the things that's different with eBPF, is eBPF programs go through a verification process that ensures that they're safe to run that, but happens dynamically and ensures that the program cannot crash, will definitely run to completion. All the memory access is safe. It gives us this very sort of reassuring platform to use for building these kernel-based tools. >> And what's the bottom line for the customer and the benefit to the organization? >> I think the bottom line is this new generation of really powerful tools that are very high performance. That have this perspective across the whole set of workloads on a machine. That don't need to rely on things like a CCAR model, which can add to a lot of complexity that was perfectly rational choice for a lot of security tools and observability tools. But if you can use an abstraction that lives in the kernel, things are much more efficient and much easier to deploy. So, I think that's really what that enterprise is gaining, simpler to deploy, easier to manage, lower overhead set of tools. >> That's the dream they want. That's what they want. Mark, this is whether the trade offs that comes up. We were talking about the supercloud, and all kinds. Even at AWS, you're going to have supercloud, but you got super hackers as well. As innovation happens on one side, the hackers are innovating on the other. And you start to see a lot of advances in the lower level, AWS with their Silicon and strategies are continuing to happen and be stronger, faster, cheaper, better down the lower levels at the network lay. All these things are innovating, but this is where the hackers are going too, right? So, it's a double edge sword? >> Yeah, and it always will be. And that's the challenge of technology, is sort of the advancement for one, is an advancement for all. But I think, while Liz hit the technical aspects of the eBPF spot on, what I'm seeing with enterprises, and in general with the market movement, is all of those technical advantages are increasing the confidence in some of this security tooling. So, the long sort of anecdote or warning in security has always been things like intrusion prevention systems where they will look at network traffic and drop things they think bad. Well, for decades, people have always deployed them in detect-only mode. And that's always a horrible conversation to have with the board saying, "Well, I had this tool in place that could have stopped the attack, but I wasn't really confident that it was stable enough to turn on. So, it just warned me that it had happened after the fact." And with the stability and the performance that we're seeing out of things based on technologies like eBPF, we're seeing that confidence increase. So, people are not only deploying this new level of tooling, but they're confident that it's actually providing the security it promised. And that's giving, not necessarily a leg up, but at least that level of parody with that push forward that we're seeing, similar on the attack side. Because attackers are always advancing as well. And I think that confidence and that reliability on the tooling, can't be underestimated because that's really what's pushing things forward for security outcomes. >> Well, one of the things I want get your both perspective on real quick. And you kind of segue into this next set of conversations, is with DevOps success, Dev and Ops, it's kind of done, right? We're all happy. We're seeing DevOps being so now DevSecOps. So, CSOs were like kind of old school. Buy a bunch of tools, we have a vendor. And with cloud native, Liz, you mentioned this earlier, accelerating the developers are even driving the standards more and more. So, shifting left is a security paradigm. So, tooling, Mark, you're on top of this too, it's tooling versus how do I organize my team? What are the processes? How do I keep the CICD pipeline going, higher velocity? How can I keep my app developers programming faster? And as Adrian Cockcroft said, they don't really care about locking, they want to go faster. It's the ops teams that have to deal with everything. So, and now security teams have to deal with the speed and velocity. So, you're seeing a new kind of step function, ratchet game where ops and security teams who are living DevOps, are still having to serve the devs, and the devs need more help here. So, how do you guys see that dynamic in security? Because this is clearly the shift left's, cloud native trend impacting the companies. 'Cause now it's not just shifting left for developers, it has a ripple effect into the organization and the security posture. >> We see a lot of organizations who now have what they would call a platform team. Which is something similar to maybe what would've been an ops team and a security team, where really their role is to provide that platform that developers can use. So, they can concentrate on the business function that they don't have to really think about the underlying infrastructure. Ideally, they're using whatever common definition for their applications. And then, they just roll it out to a cloud somewhere, and they don't have to think about where that's operating. And then, that platform team may have remit that covers, not just the compute, but also the networking, the common set of tooling that allows people to debug their applications, as well as securing them. >> Mark, this is a big discussion because one, I love the team, process collaboration. But where's the team? We've got a skills gap going on too, right? So, in all this, there's a lot of action happening. What's your take on this dynamic of tooling versus process collaboration for security success? >> Yeah, it's tough. And I think what we're starting to see, and you called it out spot on, is that the developers are all about dynamic change and rapid change, and operations, and security tend to like stability, and considered change in advance. And the business needs that needle to be threaded. And what we're seeing is sort of, with these new technologies, and with the ideas of finally moving past multicloud, into, as you guys call supercloud, which I absolutely love is a term. Let's get the advantage of all these things. What we're seeing, is people have a higher demand for the outputs from their tooling, and to find that balance of the process. I think it's acknowledged now that you're not going to have complete security. We've gotten past that, it's not a yes or no binary thing. It's, let's find that balance in risk. So, if we are deploying tooling, whether that's open source, or commercial, or something we built ourselves, what is the output? And who is best to take action on that output? And sometimes that's going to be the developers, because maybe they can just fix their architecture so that it doesn't have a particular issue. Sometimes that's going to be those platform teams saying like, "Hey, this is what we're going to apply for everybody, so that's a baseline standard." But the good news, is that those discussions are happening. And I think people are realizing that it's not a one size-fits-all. 10 years ago was sort of like, "Hey, we've got a blueprint and everyone does this." That doesn't work. And I think that being out in the open, really helps deliver these better outcomes. And because it isn't simple, it's always going to be an ongoing discussion. 'Cause what we decide today, isn't going to be the same thing in a week from now when we're sprint ahead, and we've made a whole bunch of changes on the platform and in our code. >> I think the cultural change is real. And I think this is hard for security because you got so much current action happening that's really important to the business. That's hard to just kind of do a reset without having any collateral damage. So, you kind of got to mitigate and manage all the current situation, and then try to build a blueprint for the future and transform into a kind of the next level. And it kind of reminds me of, I'm dating myself. But back in the days, you had open source was new. And the common enemy was proprietary, non-innovative old guard, kind of mainframe mini computer kind of proprietary analysis, proprietary everything. Here, there is no enemy. The clouds are doing great, right? They're leaning in open source is at all time high and not stopping, it's it's now standard. So, open is not a rebel. It's not the rebel anymore, it's the standard. So, you have the innovation happening in open source, Liz, and now you have large scale cloud. And this is a cultural shift, right? How people are buying, evaluating product, and implementing solutions. And I when I say new, I mean like new within the decades or a couple decades. And it's not like open source is not been around. But like we're seeing new things emerge that are pretty super cool in the sense that you have projects defining standards, new things are emerging. So, the CIO decision making process on how to structure teams and how to tackle security is changing. Why IT department? I mean, just have a security department and a Dev team. >> I think the fact that we are using so much more open source software is a big part of this cultural shift where there are still a huge ecosystem of vendors involved in security tools and observability tools. And Mark and I both represent vendors in those spaces. But the rise of open source tools, means that you can start with something pretty powerful that you can grow with. As you are experimenting with the security tooling that works for you, you don't have to pay a giant sum to get a sort of black box. You can actually understand the open source elements of the tooling that you are going to use. And then build on that and get the enterprise features when you need those. And I think that cultural change makes it much easier for people to work security in from the get go, and really, do that shift left that we've been talking about for the last few years. >> And I think one of the things to your point, and not only can you figure out what's in the open source code, and then build on top of it, you can also leave it too. You can go to something better, faster. So, the switching costs are a lot lower than a lock in from a vendor, where you do all the big POCs and the pilots. And, Mark, this is changing the game. I mean, I would just be bold enough to say, IT is going to be irrelevant in the sense of, if you got DevOps and it works, and you got security teams, do you really need IT 'cause the DevOps is the IT? So, if everyone goes to the cloud operations, what does IT even mean? >> Yeah, and it's a very valid point. And I think what we're seeing, is where IT is still being successful, especially in large companies, is sort of the economy of scale. If you have enough of the small teams doing the same thing, it makes sense to maybe take one tool and scale it up because you've got 20 teams that are using it. So, instead of having 20 teams run it, you get one team to run it. On the economic side, you can negotiate one contract if it's a purchase tool. There is still a place for it, but I think what we're seeing and in a very positive way, is that smaller works better when it comes to this. Because really what the cloud has done and what open source continues to do, is reduce the barrier to entry. So, a team of 10 people can build something that it took a 1000 people, a decade ago. And that's wonderful. And that opens up all these new possibilities. We can work faster. But we do need to rethink it at reinforce from AWS. They had a great track about how they're approaching it from people side of things with their security champion's idea. And it's exactly about this, is embedding high end security talent in the teams who are building it. So, that changes the central role, and the central people get called in for big things like an incident response, right? Or a massive auditor reviews. But the day-to-day work is being done in context. And I think that's the real key, is they've got the context to make smarter security decisions, just like the developers and the operational work is better done by the people who are actually working on the thing, as opposed to somebody else. Because that centralized thing, it's just communication overhead most of the time. >> Yeah. I love chatting with you guys because here's are so much experts on the field. To put my positive hat on around IT, remember the old argument of, "Oh, automation's, technology's going to kill the bank teller." There's actually more tellers now than ever before. So, the ATM machine didn't kill that. So, I think IT will probably reform from a human resource perspective. And I think this is kind of where the CSO conversation comes full circle, Liz and Mark, because, okay, let's assume that this continues the trajectory to open source, DevOps, cloud scale, hybrid. It's a refactoring of personnel. So, you're going to have DevOps driving everything. So, now the IT team becomes a team. So, most CSOs we talk to are CXOs, is how do I deploy my teams? How do I structure things, my investment in people, and machines and software in a way that I get my return? At the end of the day, that's what they live for, and do it securely. So, this is the CISO's kind of thought process. How do you guys react to that? What's the message to CISOs? 'Cause they have a lot of companies to look at here. And in the marketplace, they got to spend some money, they got to get a return, they got to reconfigure. What's your advice? Liz, what's your take? Then we'll go to Mark. >> That's a really great question. I think cloud skills, cloud engineering skills, cloud security skills have never been more highly valued. And I think investing in training people to understand cloud that there are tons of really great resources out there to help ramp people up on these skills. The CNCF, AWS, there's tons of organizations who have really great courses and exams, and things that people can do to really level up their skills, which is fantastic right from a grassroots level, through to the most widely deployed global enterprise. I think we're seeing a lot of people are very excited, develop these skills. >> Mark, what's your take for the CSO, the CXO out there? They're scratching their head, they're going, "Okay, I need to invest. DevOps is happening. I see the open source, I'm now got to change over. Yeah, I lift and shift some stuff, now I got to refactor my business or I'm dead." What's your advice? >> I think the key is longer term thinking. So, I think where people fell down previously, was, okay, I've got money, I can buy tools, roll 'em out. Every tool you roll out, has not just an economic cost, but a people cost. As Liz said, those people with those skills are in high demand. And so, you want to make sure that you're getting the most value out of your people, but your tooling. So, as you're investing in your people, you will need to roll out tools. But they're not the answer. The answer is the people to get the value out of the tools. So, hold your tools to a higher standard, whether that's commercial, open source, or something from the CSP, to make sure that you're getting actionable insights and value out of them that your people can actually use to move forward. And it's that balance between the two. But I love the fact that we're finally rotating back to focus more on the people. Because really, at the end of the day, that's what's going to make it all work. >> Yeah. The hybrid work, people processes. The key, the supercloud brings up the conversation of where we're starting to see maturation into OPEX models where CapEx is a gift from the clouds. But it's not the end of bilk. Companies are still responsible for their own security. At the end of the day, you can't lean on AWS or Azure. They have infrastructure and software, but at the end of the day, every company has to maintain their own. Certainly, with hybrid and edge coming, it's here. So, this whole concept of IT, CXO, CIO, CSO, CSO, I mean, this is hotter than ever in terms of like real change. What's your reaction to that? >> I was just reading this morning that the cost of ensuring against data breaches is getting dramatically more expensive. So, organizations are going to have to take steps to implement security. You can't just sort of throw money at the problem, you're going to actually have to throw people and technology at the problem, and take security really seriously. There is this whole ecosystem of companies and folks who are really excited about security and here to help. There's a lot of people interested in having that conversation to help those CSOs secure their deployments. >> Mark, your reaction? >> Yeah. I think, anything that causes us to question what we're doing is always a positive thing. And I think everything you brought up really comes down to remembering that no matter what, and no matter where, your data is always your data. And so, you have some level of responsibility, and that just changes depending on what system you're using. And I think that's really shifting, especially in the CSO or the CSO mindset, to go back to the basics where it used to be information security and not just cyber security. So, whether that information and that data is sitting on my desk physically, in a system in our data center, or in the cloud somewhere. Looking holistically, and that's why we could keep coming back to people. That's what it's all about. And when you step back there, you start to realize there's a lot more trade offs. There's a lot more levers that you can work on, to deliver the outcome you want, to find that balance that works for you. 'Cause at the end of the day, security is just all about making sure that whatever you built and the systems you're working with, do what you want them to do, and only what you want them to do. >> Well, Liz and Mark, thank you so much for your expert perspective. You're in the trenches, and really appreciate your time and contributing with "theCUBE," and being part of our Showcase. For the last couple of minutes, let's dig into some of the things you're working on. I know network policies around Kubernetes, Liz, EKS anywhere has been fabulous with Lambda and Serverless, you seeing some cool things go on there. Mark, you're at Lacework, very successful company. And looking at a large scale observability, signaling and management, all kinds of cool things around native cloud services and microservices. Liz, give us an update. What's going on over there at Isovalent? >> Yeah. So, Isovalent is the company behind Cilium Networking Project. Its best known as a Kubernetes networking plugin. But we've seen huge amount of adoption of cilium, it's really skyrocketed since we became an incubating project in the CNCF. And now, we are extending to using eBPF to not just do networking, but incredibly in depth observability and security observability have a new sub project called Tetragon, that gives you this amazing ability to see out of policy behavior. And again, because it's using eBPF, we've got the perspective of everything that's happening across the whole machine. So, I'm really excited about the innovations that are happening here. >> Well, they're lucky to have you. You've been a great contributor to the community. We've been following your career for very, very long time. And thanks for everything that you do, really appreciate it. Thanks. >> Thank you. >> Mark, Lacework, we we've following you guys. What are you up to these days? You know, we see you're on Twitter, you're very prolific. You're also live tweeting all the events, and with us as well. What's going on over there at Lacework? And what's going on in your world? >> Yeah. Lacework, we're still focusing on the customer, helping deliver good outcomes across cloud when it comes to security. Really looking at their environments and helping them understand, from their data that they're generating off their systems, and from the cloud usage as to what's actually happening. And that pairs directly into the work that I'm doing, the community looking at just security as a practice. So, a lot of that pulling people out of the technology, and looking at the process and saying, "Hey, we have this tech for a reason." So, that people understand what they need in place from a skill set, to take advantage of the great work that folks like Liz and the community are doing. 'Cause we've got these great tools, they're outputting all this great insights. You need to be able to take actions on top of that. So, it's always exciting. More people come into security with a security mindset, love it. >> Well, thanks so much for this great conversation. Every board should watch this video, every CSO, CIO, CSO. Great conversation, thanks for unpacking and making something very difficult, clear to understand. Thanks for your time. >> Pleasure. >> Thank you. >> Okay, this is the AWS Startup Showcase, Season Two, Episode Four of the ongoing series covering the exciting startups from the AWS ecosystem. We're talking about cybersecurity, this segment. Every quarter episode, we do a segment around a category and we go deep, we feature some companies, and talk to the best people in the industry to help you understand that. I'm John Furrier your host. Thanks for watching. (upbeat music)

>>Okay, welcome back everyone to super cloud 22 here in our live studio performance. You're on stage in Palo Alto. I'm Sean fur. You're host with the queue with Dave ante. My co it's got a great industry ecosystem panel to discuss whether it's realer hype, David MC Janet CEO of Hashi Corp, hugely successful company as will LA forest field CTO, Colu and Victoria over yourgo from VMware guys. Thanks for coming on the queue. Appreciate it. Thanks for having us. So realer, hype, super cloud David. >>Well, I think it depends on the definition. >>Okay. How do you define super cloud start there? So I think we have a, >>I think we have a, like an inherently pragmatic view of super cloud of the idea of super cloud as you talk about it, which is, you know, for those of us that have been in the infrastructure world for a long time, we know there are really only six or seven categories of infrastructure. There's sort of the infrastructure security, networking databases, middleware, and, and, and, and really the message queuing aspects. And I think our view is that if the steady state of the world is multi-cloud, what you've seen is sort of some modicum of standardization across those different elements, you know, take, you know, take confluent. You know, I, I worked in the middleware world years ago, MQ series, and typical multicast was how you did message queuing. Well, you don't do that anymore. All the different cloud providers have their own message, queuing tech, there's, Google pub sub, and the equivalents across the different, different clouds. Kafka has provided a consistent way to do that. And they're not trying to project that. You can run everything connected. They're saying, Hey, you should standardize on Kafka for message cuing is that way you can have operational consistency. So I think to me, that's more how we think about it is sort of, there is sort of layer by layer of sort of de facto standardization for the lingo Franco. >>So a streaming super cloud is how you would think of it, or no, I just, or a component of >>Cloud that could be a super cloud. >>I just, I just think that there are like, if I'm gonna build an application message, queuing is gonna be a necessary element of it. I'm gonna use Kafka, not, you know, a native pub sub engine on one of the clouds, because operationally that's just the only way I can do it. So I think that's more, our view's much more pragmatic rather than trying to create like a single platform that you can run everywhere and deal with the networking realities of like network, you know, hops missing across those different worlds and have that be our responsibility. It's much more around, Hey, let's standardize each layer, operational >>Standardized layer that you can use to build a super cloud if that's in your, your intent or, yeah. Okay. >>And it reminds me of the web services days. You kind of go throwback there. I mean, we're kind of living the next gen of web services, the dream of that next level, because DevOps dev SecOps now is now gone mainstream. That's the big challenge we're hearing devs are doing great. Yep. But the ops teams and screen, they gotta go faster. This seems to be a core, I won't say blocker, but more of a drag to the innovation. >>Well, I I'll just get off, I'll hand it off to, to you guys. But I think the idea that like, you know, if I'm gonna have an app that's running on Amazon that needs to connect to a database that's running on, on the private data center, that's essentially the SOA notion, you know, w large that we're all trying to solve 20 years ago, but is much more complicated because you're brokering different identity models, different networking models. They're just much more complex. So that's where the ops bit is the constraint, you know, for me to build that app, not that complicated for the ops person to let it see traffic is another thing altogether. I think that's, that's the break point for so much of what looks easier to a developer is the operational reality of how you do that. And the good news is those are actually really well solved problems. They're just not broadly understood. >>Well, what's your take, you talk to customers all the time, field CTO, confluent, really doing well, streaming data. I mean, everyone's doing it now. They have to, yeah. These are new things that pop up that need solutions. You guys step up and doing more. What's your take on super cloud? >>Well, I mean, the way we address it honestly is we don't, it's gonna be honest. We don't think about super cloud much less is the fact that SAS is really being pushed down. Like if we rely on seven years ago and you took a look at SAS, like it was obvious if you were gonna build a product for an end consumer or business user, you'd do SAS. You'd be crazy not to. Right. But seven years ago, if you look at your average software company producing something for a developer that people building those apps, chances are you had an open source model. Yeah. Or, you know, self-managed, I think with the success of a lot of the companies that are here today, you know, snowflake data, bricks, Colu, it's, it's obvious that SaaS is the way to deliver software to the developers as well. And as such, because our product is provided that way to the developers across the clouds. That's, that's how they have a unifying data layer, right. They don't necessarily, you know, developers like many people don't necessarily wanna deal with the infrastructure. They just wanna consume cloud data services. Right. So that's how we help our customers span cloud. >>So we evenly that SAS was gonna be either built on a single cloud or in the case of service. Now they built their own cloud. Right. So increasingly we're seeing opportunities to build a Salesforce as well across clouds tap different, different, different services. So, so how does that evolve? Do you, some clouds have, you know, better capabilities in other clouds. So how does that all get sort of adjudicated, do you, do you devolve to the lowest common denominator? Or can you take the best of all of each? >>The whole point to that I think is that when you move from the business user and the personal consumer to the developer, you, you can no longer be on a cloud, right. There has to be locality to where applications are being developed. So we can't just deploy on a single cloud and have people send their data to that cloud. We have to be where the developer is. And our job is to make the most of each, an individual cloud to provide the same experience to them. Right. So yes, we're using the capabilities of each cloud, but we're hiding that to the developer. They don't shouldn't need to know or care. Right. >>Okay. And you're hiding that with the abstraction layer. We talked about this before Victoria, and that, that layer has what, some intelligence that has metadata knowledge that can adjudicate what, what, the best, where the best, you know, service is, or function of latency or data sovereignty. How do you see that? >>Well, I think as the, you need to instrument these applications so that you, you, you can get that data and then make the intelligent decision of where, where, where this, the deploy application. I think what Dave said is, is right. You know, the level of super cloud that they talking about is the standardization across messaging. And, and are you what's happening within the application, right? So you don't, you are not too dependent on the underlying, but then the application say that it takes the form of a, of a microservice, right. And you deploy that. There has to be a way for operator to say, okay, I see all these microservices running across clouds, and I can factor out how they're performing, how I, I, life lifecycle managed and all that. And so I think there is, there is, to me, there's the next level of the super cloud is how you factor this out. So an operator can actually keep up with the developers and make sense of all that and manage it. Like >>You guys that's time. Like its also like that's what Datadog does. So Datadog basically in allows you to instrument all those services, on-prem private data center, you know, all the different clouds to have a consistent view. I think that that's not a good example of a vendor that's created a, a sort of a level of standardization across a layer. And I think that's, that's more how we think about it. I think the notion of like a developer building an application, they can deploy and not have to worry where it exists. Yeah. Is more of a PAs kind of construct, you know, things like cloud Foundry have done a great job of, of doing that. But underneath that there's still infrastructure. There's still security. There's still networking underneath it. And I think that's where, you know, things like confluent and perhaps at the infrastructure layer have standardized, but >>You have off the shelf PAs, if I can call it that. Yeah. Kind of plain. And then, and then you have PAs and I think about, you mentioned snowflake, snowflake is with snow park, seems to be developing a PAs layer that's purpose built for their specific purpose of sharing data and governing data across multiple clouds call super paths. Is, is that a prerequisite of a super cloud you're building blocks. I'm hearing yeah. For super cloud. Is that a prerequisite for super cloud? That's different than PAs of 10 years ago. No, but I, >>But I think this is, there's just different layers. So it's like, I don't know how that the, the snowflake offering is built built, but I would guess it's probably built on Terraform and vault and cons underneath it. Cuz those are the ingredients with respect to how you would build a composite application that runs across multiple. And >>That's how Oracle that town that's how Oracle with the Microsoft announcement. They just, they just made if you saw that that was built on Terraform. Right. But, but they would claim that they, they did some special things within their past that were purpose built for, for sure. Low latency, for example, they're not gonna build that on, you know, open shift as an, as an example, they're gonna, you know, do their own little, you know, >>For sure, for sure. So I think what you're, you're pointing at and what Victoria was talking about is, Hey, can a vendor provided consistent experience across the application layer across these multiple clouds? And I would say, sure, just like, you know, you might build a mobile banking application that has a front end on Amazon in the back end running on vSphere on your private data center. Sure. But the ingredients you use to do that have to be, they can't be the cloud native aspects for how you do that. How do you think about, you know, the connectivity of, of like networking between that thing to this thing? Is it different on Amazon? Is it different on Azure? Is it different on, on Google? And so the, the, the, the companies that we all serve, that's what they're building, they're building composited applications. Snowflake is just an example of a company that we serve this building >>Composite. And, but, but, but don't those don't, you have to hide the complexity of that, those, those cloud native primitives that's your job, right. Is to actually it creates simplicity across clouds. Is it not? >>Why? Go ahead. You. >>Yeah, absolutely. I mean that in fact is what we're doing for developers that need to do event streaming, right. That need to process this data in real time. Now we're, we're doing the sort of things that Victoria was just talking about, like underneath the covers, of course, you know, we're using Kubernetes and we're managing the differences between the clouds, but we're hiding the, that, and we've become sort of a defacto standard across the cloud. So if I'm developing an app in any of those cloud, and I think we all know, and you were mentioning earlier every significant company's multi-cloud now all the large enterprises, I just got back from Brazil and like every single one of 'em have multiple clouds and on-prem right. So they need something that can span those. >>What's the challenge there. If you talk to those customers, because we're seeing the same thing, they have multiple clouds. Yeah. But it was kind of by default or they had some use case, either.net developers there with Azure, they'll do whatever cloud. And it kind of seems specialty relative to the cloud native that they're on what problems do they have because the complexity to run infrastructure risk code across clouds is hard. Right? So the trade up between native cloud and have better integration to complexity of multiple clouds seems to be a topic around super cloud. What are you seeing for, for issues that they might have or concerns? >>Yeah. I mean, honestly it is, it is hard to actually, so here's the thing that I think is kind of interesting though, by the way, is that I, I think we tend to, you know, if you're, if you're from a technical background, you tend to think of multicloud as a problem for the it organization. Like how do we solve this? How do we save money? But actually it's a business problem now, too, because every single one of these companies that have multiple clouds, they want to integrate their data, their products across these, and it it's inhibiting their innovation. It's hard to do, but that's where something like, you know, Hatchie Corp comes in right. Is to help solve that. So you can instrument it. It has to happen at each of these layers. And I suppose if it does happen at every single layer, then voila, we organically have something that amounts to Supercloud. Right. >>I love how you guys are representing each other's firms. And, but, but, and they also correct me if I'm a very similar, your customers want to, it is very similar, but your customers want to monetize, right. They want bring their tools, their software, their particular IP and their data and create, you know, every, every company's a software company, as you know, Andreesen says every company's becoming a cloud company to, to monetize in, in the future. Is that, is that a reasonable premise of super cloud? >>Yeah. I think, think everyone's trying to build composite applications to, to generate revenue. Like that's, that's why they're building applications. So yeah. One, 100%. I'm just gonna make it point cuz we see it as well. Like it's actually quite different by geography weirdly. So if you go to like different geographies, you see actually different cloud providers, more represented than others. So like in north America, Amazon's pretty dominant Japan. Amazon's pretty dominant. You go to Southeast Asia actually. It's not necessarily that way. Like it might be Google for, for whatever reason more hourly Bob. So this notion of multi's just the reality of one's everybody's dealing with. But yeah, I think everyone, everyone goes through the same process. What we've observed, they kind of go, there's like there's cloud V one and there's cloud V two. Yeah. Cloud V one is sort of the very tactical let's go build something on cloud cloud V two is like, whoa, whoa, whoa, whoa. And I have some stuff on Amazon, some stuff on Azure, some stuff on, on vSphere and I need some operational consistency. How do I think about zero trust across that way in a consistent way. And that's where this conversation comes into being. It's sort of, it's not like the first version of cloud it's actually when people step back and say, Hey, Hey, I wanna build composite applications to monetize. How am I gonna do that in an industrialized way? And that's the problem that you were for. It's >>Not, it's not as, it's not a no brainer like it was with cloud, go to the cloud, write an app. You're good here. It's architectural systems thinking, you gotta think about regions. What's the latency, you know, >>It's step back and go. Like, how are we gonna do this, this exactly. Like it's wanted to do one app, but how we do this at scale >>Zero trust is a great example. I mean, Amazon kind of had, was forced to get into the zero trust, you know, discussion that, that wasn't, you know, even a term that they used and now sort of, they're starting to talk about it, but within their domain. And so how do you do zero trust trust across cost to your point? >>I, I wonder if we're limiting our conversation too much to the, the very technical set of developers, cuz I'm thinking back at again, my example of C plus plus libraries C plus plus libraries makes it easier. And then visual BA visual basic. Right. And right now we don't have enough developers to build the software that we want to build. And so I want, and we are like now debating, oh, can we, do we hide that AI API from Google versus that SQL server API from, from Microsoft. I wonder at some point who cares? Right. You know, we, I think if we want to get really economy scale, we need to get to a level of abstraction for developers that really allows them to say, I don't need, for most of most of the procedural application that I need to build as a developer, as a, as a procedural developer, I don't care about this. Some, some propeller had, has done that for me. I just like plug it in my ID and, and I use it. And so I don't, I don't know how far we are from that, but if we don't get to that level, it fits me that we never gonna get really the, the economy or the cost of building application to the level. >>I was gonna ask you in the previous segment about low code, no code expanding the number of developers out there and you talking about propel heads. That's, that's what you guys all do. Yeah. You're the technical geniuses, right. To solve that problem so that, so you can have low code development is that I >>Don't think we have the right here. Cause I, we, we are still, you know, trying to solve that problem at that level. But, but >>That problem has to be solved first, right before we can address what you're talking about. >>Yeah. I, I worked very closely with one of my biggest mentors was Adam Bosworth that built, you know, all the APIs for visual basics and, and the SQL API to visual basic and all that stuff. And he always was on that front. In fact that his last job was at my, at AWS building that no code environment. So I'm a little detached from that. It just hit me as we were discussing this. It's like, maybe we're just like >>Creating, but I would, I would argue that you kind of gotta separate the two layers. So you think about the application platform layer that a developer interfaces to, you know, Victoria and I worked together years ago and one of the products we created was cloud Foundry, right? So this is the idea of like just, you know, CF push, just push this app artifact and I don't care. That's how you get the developer community written large to adopt something complicated by hiding all the complexity. And I think that that is one model. Yeah. Turns out Kubernetes is actually become a peer to that and perhaps become more popular. And that's what folks like Tanza are trying to do. But there's another layer underneath that, which is the infrastructure that supports it. Right? Yeah. Cause that's only needs to run on something. And I think that's, that's the separation we have to do. Yes. We're talking a little bit about the plumbing, but you know, we just easily be talking about the app layer. You need, both of them. Our point of view is you need to standardize at this layer just like you need standardize at this layer. >>Well, this is, this is infrastructure. This is DevOps V two >>Dev >>Ops. Yeah. And this is where I think the ops piece with open source, I would argue that open source is blooming more than ever. So I think there's plenty of developers coming. The automation question becomes interesting because I think what we're seeing is shift left is proving that there's app developers out there that wanna stay in their pipelining. They don't want to get in under the hood. They just want infrastructure as code, but then you got supply chain software issues there. We talked about the Docker on big time. So developers at the top, I think are gonna be fine. The question is what's the blocker. What's holding them back. And I don't see the devs piece Victoria as much. What do you guys think? Is it, is the, is the blocker ops or is it the developer experience? That's the blocker. >>It's both. There are enough people truthfully. >>That's true. Yeah. I mean, I think I sort of view the developer as sort of the engine of the digital innovation. So, you know, if you talk about creative destruction, that's, that was the economic equivalent of softwares, eating the world. The developers are the ones that are doing that innovation. It's absolutely essential that you make it super easy for them to consume. Right. So I think, you know, they're nerds, they want to deal with infrastructure to some degree, but I think they understand the value of getting a bag of Legos that they can construct something new around. And I think that's the key because honestly, I mean, no code may help for some things. Maybe I'm just old >>School, >>But I, I went through this before with like Delphy and there were some other ones and, and I hated it. Like I just wanted a code. Yeah. Right. So I think making them more efficient is, is absolutely good. >>But I think what, where you're going with that question is that the, the developers, they tend to stay ahead. They, they just, they're just gear, you know, wired that way. Right. So I think right now where there is a big bottleneck in developers, I think the operation team needs to catch up. Cuz I, I talk to these, these, these people like our customers all the time and I see them still stuck in the old world. Right. Gimme a bunch of VMs and I'll, I know how to manage well that world, you know, although as lag is gonna be there forever, so managing mainframe. But so if they, the world is all about microservices and containers and if the operation team doesn't get on top of it and the security team that then that they're gonna be a bottleneck. >>Okay. I want to ask you guys if the, if the companies can get through that knothole of having their ops teams and the dev teams work well together, what's the benefits of a Supercloud. How do you see the, the outcome if you kind of architect it, right? You think the big picture you zoom as saying what's the end game look like for Supercloud? Is that >>What I would >>Say? Or what's the Nirvana >>To me Nirvana is that you don't care. You just don't don't care. You know, you just think when you running building application, let's go back to the on-prem days. You don't care if it runs on HP or Dell or, you know, I'm gonna make some enemies here with my old, old family, but you know, you don't really care, right. What you want is the application is up and running and people can use it. Right. And so I think that Nirvana is that, you know, there is some, some computing power out there, some pass layer that allows me to deploy, build application. And I just like build code and I deploy it and I get value at a reasonable cost. I think one of the things that the super cloud for as far as we're concerned is cost. How do you manage monitor the cost across all this cloud? >>Make sure that you don't, the economics don't get outta whack. Right? How many companies we know that have gone to the cloud only to realize that holy crap, now I, I got the bill and, and you know, I, as a vendor, when I was in my previous company, you know, we had a whole team figuring out how to lower our cost on the one hyperscaler that we were using. So these are, you know, the, once you have in the super cloud, you don't care just you, you, you go with the path of least the best economics is. >>So what about the open versus closed debate will you were mentioning that we had snowflake here and data bricks is both ends of the spectrum. Yeah. You guys are building open standards across clouds. Clearly even the CLO, the walled gardens are using O open standards, but historically de facto standards have emerged and solved these problems. So the super cloud as a defacto standard, versus what data bricks is trying to do super cloud kind of as an, as an open platform, what are you, what are your thoughts on that? Can you actually have an, an open set of standards that can be a super cloud for a specific purpose, or will it just be built on open source technologies? >>Well, I mean, I, I think open source continues to be an important part of innovation, but I will say from a business model perspective, like the days, like when we started off, we were an open source company. I think that's really done in my opinion, because if you wanna be successful nowadays, you need to provide a cloud native SAS oriented product. It doesn't matter. What's running underneath the covers could be commercial closed source, open source. They just wanna service and they want to use it quite frankly. Now it's nice to have open source cuz the developers can download it and run on their laptop. But I, I can imagine in 10 years time actually, and you see most companies that are in the cloud providing SAS, you know, free $500 credit, they may not even be doing that. They'll just, you know, go whatever cloud provider that their company is telling them to use. They'll spin up their SAS product, they'll start playing with it. And that's how adoption will grow. Right? >>Yeah. I, I think, I mean my personal view is that it's, that it's infrastructure is pervasive enough. It exists at the bottom of everything that the standards emerge out of open source in my view. And you think about how something like Terraform is built, just, just pick one of the layers there's Terraform core. And then there's a plugin for everything you integrate with all of those are open source. There are over 2000 of these. We don't build them. Right. That's and it's the same way that drove Linux standardization years ago, like someone had to build the drivers for every piece of hardware in the world. The market does not do that twice. The market does that once. And so I, I I'm deeply convicted that opensource is the only way that this works at the infrastructure layer, because everybody relies on it at the application layer, you may have different kinds of databases. You may have different kind of runtime environments. And that's just the nature of it. You can't to have two different ways of doing network, >>Right? Because the stakes are so high, basically. >>Yeah. Cuz there's, there's an infinite number of the surface areas are so large. So I actually worked in product development years ago for middleware. And the biggest challenge was how do you keep the adapter ecosystem up to date to integrate with everything in the world? And the only way to do it in our view is through open source. And I think that's a fundamental philosophical view that it we're just, you know, grounded in. I think when people are making infrastructure decisions that span 20 years at the customer base, this is what they think about. They go which standard it will emerge based on the model of the vendor. And I don't think my personal view is, is it's not possible to do in a, in >>A, do you think that's a defacto standard kind of psychological perspective or is there actual material work being done or both in >>There it's, it's, it's a network effect thing. Right? So, so, you know, before Google releases a new service service on Google cloud, as part of the release checklist is does it support Terraform? They do that work, not us. Why? Because every one of their customers uses Terraform to interface with them and that's how it works. So see, so the philosophical view of, of the customers, okay, what am I making a standardize on for this layer for the next 30 years? It's kind of a no brainer. Philosophically. >>I tend, >>I think the standards are organically created based upon adoption. I mean, for instance, Terraform, we have a provider we're again, we're at the data layer that we created for you. So like, I don't think there's a board out there. I mean there are that creating standards. I think those days are kind of done to be honest, >>The, the Terraform provider for vSphere has been downloaded five and a half million times this year. Yeah. Right. Like, so, I >>Mean, these are unifying moments. This are like the de facto standards are really important process in these structural changes. I think that's something that we're looking at here at Supercloud is what's next? What has to unify look what Kubernetes has done? I mean, that's essentially the easy thing to orchestra, but people get behind it. So I see this is a big part of this next, the two. Totally. What do you guys see that's needed? What's the rallying unification point? Is it the past layer? Is it more infrastructure? I guess that's the question we're trying to, >>I think every layer will need that open source or a major traction from one of the proprietary vendor. But I, I agree with David, it's gonna be open source for the most part, but you know, going back to the original question of the whole panel, if I may, if this is reality of hype, look at the roster of companies that are presenting or participating today, these are all companies that have some sort of multi-cloud cross cloud, super cloud play. They're either public have real revenue or about to go public. So the answer to the question. Yeah, it's real. Yeah. >>And so, and there's more too, we had couldn't fit him in, but we, >>We chose super cloud on purpose cuz it kind of fun, John and I kind came up with it and, and but, but do you think it's, it hurts the industry to have this, try to put forth this new term or is it helpful to actually try to push the industry to define this new term? Or should it just be multi-cloud 2.0, >>I mean, conceptually it's different than multi-cloud right. I mean, in my opinion, right? So in that, in that respect, it has value, right? Because it's talking about something greater than just multi-cloud everyone's got multi-cloud well, >>To me multi-cloud is the, the problem I should say the opportunity. Yeah. Super cloud or we call it cross cloud is the solution to that channel. Let's >>Not call again. And we're debating that we're debating that in our cloud already panel where we're talking about is multi-cloud a problem yet that needs to get solved or is it not yet ready for a market to your point? Is it, are we, are we in the front end of coming into the true problem set, >>Give you definitely answer to that. The answer is yes. If you look at the customers that are there, they won, they have gone through the euphoria phase. They're all like, holy something, what, what are we gonna do about this? Right. >>And, but they don't know what to do. >>Yeah. And the more advanced ones as the vendor look at the end of the day, markets are created by vendors that build ed that customers wanna buy. Yeah. Because they get value >>And it's nuance. David, we were sort talking about before, but Goldman Sachs has announced they're analysis software vendor, right? Capital one is a software vendor. I've been really interested Liberty what Cerner does with what Oracle does with Cerner and in terms of them becoming super cloud vendors and monetizing that to me is that is their digital transformation. Do you guys, do you guys see that in the customer base? Am I way too far out of my, of my skis there or >>I think it's two different things. I think, I think basically it's the idea of building applications. If they monetize yeah. There and Cerner's gonna build those. And you know, I think about like, you know, IOT companies that sell that sell or, or you think people that sell like, you know, thermostats, they sell an application that monetizes those thermostats. Some of that runs on Amazon. Some of that runs a private data center. So they're basically in composite applications and monetize monetizing them for the particular vertical. I think that's what we ation every day. That's what, >>Yeah. You can, you can argue. That's not, not anything new, but what's new is they're doing that on the cloud and taking across multiple clouds. Multiple. Exactly. That's what makes >>Edge. And I think what we all participate in is, Hey, in order to do that, you need to drive standardization of how you do provisioning, how you do networking, how you do security to underpin those applications. I think that's what we're all >>Talking about, guys. It's great stuff. And I really appreciate you taking the time outta your day to help us continue the conversation to put out in the open. We wanna keep it out in the open. So in the last minute we have left, let's go down the line from a hash core perspective, confluent and VMware. What's your position on super cloud? What's the outcome that you would like to see from your standpoint, going out five years, what's it look like they will start with you? >>I just think people like sort under understanding that there is a layer by layer of view of how to interact across cloud, to provide operational consistency and decomposing it that way. Thinking about that way is the best way to enable people to build and run apps. >>We wanna help our customers work with their data in real time, regardless of where they're on primer in the cloud and super cloud can enable them to build applications that do that more effectively. That's that's great for us >>For tour you. >>I, my Niana for us is customers don't care, just that's computing out there. And it's a, it's a, it's a tool that allows me to grow my business and we make it all, all the differences and all the, the challenges, you know, >>Disappear, dial up, compute utility infrastructure, ISN >>Code. I open up the thought there's this water coming out? Yeah, I don't care. I got how I got here. I don't wanna care. Well, >>Thank you guys so much and congratulations on all your success in the marketplace, both of you guys and VMware and your new journey, and it's gonna be great to watch. Thanks for participating. Really appreciate it. Thank you, sir. Okay. This is super cloud 22, our events, a pilot. We're gonna get it out there in the open. We're gonna get the data we're gonna share with everyone out in the open on Silicon angle.com in the cube.net. We'll be back with more live coverage here in Palo Alto. After this short break.

(electronic music) >> Hello everybody, welcome back to Boston. This is Dave Vellante and you're watching theCUBE's continuous coverage of AWS re:Inforce 2022. We're here at the convention center in Boston where theCUBE got started in May of 2010. I'm really excited. Lena Smart is here, she's the chief information security officer at MongoDB rocket ship company We covered MongoDB World earlier this year, June, down in New York. Lena, thanks for coming to theCUBE. >> Thank you for having me. >> You're very welcome, I enjoyed your keynote yesterday. You had a big audience, I mean, this is a big deal. >> Yeah. >> This is the cloud security conference, AWS, putting its mark in the sand back in 2019. Of course, a couple of years of virtual, now back in Boston. You talked in your keynote about security, how it used to be an afterthought, used to be the responsibility of a small group of people. >> Yeah. >> You know, it used to be a bolt on. >> Yep. >> That's changed dramatically and that change has really accelerated through the pandemic. >> Yep. >> Just describe that change from your perspective. >> So when I started at MongoDB about three and a half years ago, we had a very strong security program, but it wasn't under one person. So I was their first CISO that they employed. And I brought together people who were already doing security and we employed people from outside the company as well. The person that I employed as my deputy is actually a third time returnee, I guess? So he's worked for, MongoDB be twice before, his name is Chris Sandalo, and having someone of that stature in the company is really helpful to build the security culture that I wanted. That's why I really wanted Chris to come back. He's technically brilliant, but he also knew all the people who'd been there for a while and having that person as a trusted second in command really, really helped me grow the team very quickly. I've already got a reputation as a strong female leader. He had a reputation as a strong technical leader. So us combined is like indestructible, we we're a great team. >> Is your scope of responsibility, obviously you're protecting Mongo, >> Yeah. >> How much of your role extends into the product? >> So we have a product security team that report into Sahir Azam, our chief product officer. I think you even spoke to him. >> Yeah, he's amazing. >> He's awesome, isn't he? He's just fabulous. And so his team, they've got security experts on our product side who are really kind of the customer facing. I'm also to a certain extent customer facing, but the product folks are the absolute experts. They will listen to what our customers need, what they want, and together we can then work out and translate that. I'm also responsible for governance risk and compliance. So there's a large portion of our customers that give us input via that program too. So there's a lot of avenues to allow us to facilitate change in the security field. And I think that's really important. We have to listen to what our customers want, but also internally. You know, what our internal groups need as well to help them grow. >> I remember last year, Re:invent 2021, I was watching a talk on security. It was the, I forget his name, but it was the individual who responsible for data center security. And one of the things he said was, you know, look it's not at the end of the day, the technology's important but it's not the technology. It's how you apply the tools and the practices and the culture- >> Right. That you build in the organization that will ultimately determine how successful you are at decreasing the ROI for the bad guys. >> Yes. >> Let's put it that way. So talk about the challenges of building that culture, how you go about that, and how you sustain that cultural aspect. >> So, I think having the security champion program, so that's just, it's like one of my babies, that and helping underrepresented groups in MongoDB kind of get on in the tech world are both really important to me. And so the security champion program is purely voluntary. We have over a hundred members. And these are people, there's no bar to join. You don't have to be technical. If you're an executive assistant who wants to learn more about security, like my assistant does, you're more than welcome. Up to, we actually people grade themselves, when they join us, we give them a little tick box. Like five is, I walk in security water. One is, I can spell security but I'd like to learn more. Mixing those groups together has been game changing for us. We now have over a hundred people who volunteer their time, with their supervisors permission, they help us with their phishing campaigns, testing AWS tool sets, testing things like queryable encryption. I mean, we have people who have such an in-depth knowledge in other areas of the business that I could never learn, no matter how much time I had. And so to have them- And we have people from product as security champions as well, and security, and legal, and HR, and every department is recognized. And I think almost every geographical location is also recognized. So just to have that scope and depth of people with long tenure in the company, technically brilliant, really want to understand how they can apply the cultural values that we live with each day to make our security program stronger. As I say, that's been a game changer for us. We use it as a feeder program. So we've had five people transfer from other departments into the security and GRC teams through this Champions program. >> Makes a lot of sense. You take somebody who walks on water in security, mix them with somebody who really doesn't know a lot about it but wants to learn and then can ask really basic questions, and then the experts can actually understand better how to communicate. >> Absolutely. >> To that you know that 101 level. >> It's absolutely true. Like my mom lives in her iPad. She worships her iPad. Unfortunately she thinks everything on it is true. And so for me to try and dumb it down, and she's not a dumb person, but for me to try and dumb down the message of most of it's rubbish, mom, Facebook is made up. It's just people telling stories. For me to try and get that over to- So she's a one, and I might be a five, that's hard. That's really hard. And so that's what we're doing in the office as well. It's like, if you can explain to my mother how not everything on the internet is true, we're golden. >> My mom, rest her soul, when she first got a- we got her a Macintosh, this was years and years and years ago, and we were trying to train her over the phone, and said, mom, just grab the mouse. And she's like, I don't like mice. (Lena laughs) There you go. I know, I know, Lena, what that's like. Years ago, it was early last decade, we started to think about, wow, security really has to become a board level item. >> Yeah. >> And it really wasn't- 2010, you know, for certain companies. But really, and so I had the pleasure of interviewing Dr. Robert Gates, who was the defense secretary. >> Yes. >> We had this conversation, and he sits on a number, or sat on a number of boards, probably still does, but he was adamant. Oh, absolutely. Here's how you know, here. This is the criticality. Now it's totally changed. >> Right. >> I mean, it's now a board level item. But how do you communicate to the C-Suite, the board? How often do you do that? What do you recommend is the right regime? And I know there's not any perfect- there's got to be situational, but how do you approach it? >> So I am extremely lucky. We have a very technical board. Our chairman of the board is Tom Killalea. You know, Amazon alum, I mean, just genius. And he, and the rest of the board, it's not like a normal board. Like I actually have the meeting on this coming Monday. So this weekend will be me reading as much stuff as I possibly can, trying to work out what questions they're going to ask me. And it's never a gotcha kind of thing. I've been at board meetings before where you almost feel personally attacked and that's not a good thing. Where, at MongoDB, you can see they genuinely want us to grow and mature. And so I actually meet with our board four times a year, just for security. So we set up our own security meeting just with board members who are specifically interested in security, which is all of them. And so this is actually off cadence. So I actually get their attention for at least an hour once a quarter, which is almost unheard of. And we actually use the AWS memo format. People have a chance to comment and read prior to the meeting. So they know what we're going to talk about and we know what their concerns are. And so you're not going in like, oh my gosh, what what's going to happen for this hour? We come prepared. We have statistics. We can show them where we're growing. We can show them where we need more growth and maturity. And I think having that level of just development of programs, but also the ear of the board has has helped me mature my role 10 times. And then also we have the chance to ask them, well what are your other CISOs doing? You know, they're members of other boards. So I can say to Dave, for example, you know, what's so-and-so doing at Datadog? Or Tom Killelea, what's the CISO of Capital One doing? And they help me make a lot of those connections as well. I mean, the CISO world is small and me being a female in the world with a Scottish accent, I'm probably more memorable than most. So it's like, oh yeah, that's the Irish girl. Yeah. She's Scottish, thank you. But they remember me and I can use that. And so just having all those mentors from the board level down, and obviously Dev is a huge, huge fan of security and GRC. It's no longer that box ticking exercise that I used to feel security was, you know, if you heated your SOC2 type two in FinTech, oh, you were good to go. You know, if you did a HERC set for the power industry. All right, right. You know, we can move on now. It's not that anymore. >> Right. It's every single day. >> Yeah. Of course. Dev is Dev at the Chario. Dev spelled D E V. I spell Dave differently. My Dave. But, Lena, it sounds like you present a combination of metrics, so, the board, you feel like that's appropriate to dig into the metrics. But also I'm presuming you're talking strategy, potentially, you know, gaps- >> Road roadmaps, the whole nine yards. Yep. >> What's the, you know, I look at the budget scenario. At the macro level, CIOs have told us, they came into the year saying, hey we're going to grow spending at the macro, around eight percent, eight and a half percent. That's dialed down a little bit post Ukraine and the whole recession and Fed tightening. So now they're down maybe around six percent. So not dramatically lower, but still. And they tell us security is still the number one priority. >> Yes. >> That's been the case for many, many quarters, and actually years, but you don't have an unlimited budget. >> Sure >> Right. It's not like, oh, here is an open checkbook. >> Right. >> Lena, so, how does Mongo balance that with the other priorities in the organization, obviously, you know, you got to spend money on product, you got to spend money and go to market. What's the climate like now, is it, you know continuing on in 2022 despite some of the macro concerns? Is it maybe tapping the brakes? What's the general sentiment? >> We would never tap the breaks. I mean, this is something that's- So my other half works in the finance industry still. So we have, you know, interesting discussions when it comes to geopolitics and financial politics and you know, Dev, the chairman of the board, all very technical people, get that security is going to be taken advantage of if we're seeing to be tapping the brakes. So it does kind of worry me when I hear other people are saying, oh, we're, you know, we're cutting back our budget. We are not. That being said, you also have to be fiscally responsible. I'm Scottish, we're cheap, really frugal with money. And so I always tell my team: treat this money as if it's your own. As if it's my money. And so when we're buying tool sets, I want to make sure that I'm talking to the CISO, or the CISO of the company that's supplying it, and saying are you giving me the really the best value? You know, how can we maybe even partner with you as a database platform? How could we partner with you, X company, to, you know, maybe we'll give you credits on our platform. If you look to moving to us and then we could have a partnership, and I mean, that's how some of this stuff builds, and so I've been pretty good at doing that. I enjoy doing that. But then also just in terms of being fiscally responsible, yeah, I get it. There's CISOs who have every tool that's out there because it's shiny and it's new and they know the board is never going to say no, but at some point, people will get wise to that and be like, I think we need a new CISO. So it's not like we're going to stop spending it. So we're going to get someone who actually knows how to budget and get us what the best value for money. And so that's always been my view is we're always going to be financed. We're always going to be financed well. But I need to keep showing that value for money. And we do that every board meeting, every Monday when I meet with my boss. I mean, I report to the CFO but I've got a dotted line to the CTO. So I'm, you know, I'm one of the few people at this level that's got my feet in both camps. You know budgets are talked at Dev's level. So, you know, it's really important that we get the spend right. >> And that value is essentially, as I was kind of alluding to before, it's decreasing the value equation for the hackers, for the adversary. >> Hopefully, yes. >> Right? Who's the- of course they're increasingly sophisticated. I want to ask you about your relationship with AWS in this context. It feels like, when I look around here, I think back to 2019, there was a lot of talk about the shared responsibility model. >> Yes. >> You know, AWS likes to educate people and back then it was like, okay, hey, by the way, you know you got to, you know, configure the S3 bucket properly. And then, oh, by the way, there's more than just, it's not just binary. >> Right, right. >> There's other factors involved. The application access and identity and things like that, et cetera, et cetera. So that was all kind of cool. But I feel like the cloud is becoming the first line of defense for the CISO but because of the shared responsibility model, CISO is now the second line of defense >> Yes. Does that change your role? Does it make it less complicated in a way? Maybe, you know, more complicated because you now got to get your DevSecOps team? The developers are now much more involved in security? How is that shifting, specifically in the context of your relationship with AWS? >> It's honestly not been that much of a shift. I mean, these guys are very proactive when it comes to where we are from the security standpoint. They listen to their customers as much as we do. So when we sit down with them, when I meet with Steve Schmidt or CJ or you know, our account manager, its not a conversation that's a surprise to me when I tell them this is what we need. They're like, yep, we're on that already. And so I think that relationship has been very proactive rather than reactive. And then in terms of MongoDB, as a tech company, security is always at the forefront. So it's not been a huge lift for me. It's really just been my time that I've taken to understand where DevSecOps is coming from. And you know, how far are we shifting left? Are we actually shifting right now? It's like, you know, get the balance, right? You can't be too much to one side. But I think in terms of where we're teaching the developers, you know, we are a company by developers for developers. So, we get it, we understand where they're coming from, and we try and be as proactive as AWS is. >> When you obviously the SolarWinds hack was a a major mile- I think in security, there's always something in the headlines- >> Yes. But when you think of things like, you know, Stuxnet, you know, Log4J, obviously Solarwinds and the whole supply chain infiltration and the bill of materials. As I said before, the adversary is extremely capable and sophisticated and you know, much more automated. It's always been automated attacks, but you know island hopping and infiltrating and self-forming malware and really sophisticated techniques. >> Yep. >> How are you thinking about that supply chain, bill of materials from inside Mongo and ultimately externally to your customers? >> So you've picked on my third favorite topic to talk about. So I came from the power industry before, so I've got a lot of experience with critical infrastructure. And that was really, I think, where a lot of the supply chain management rules and regulations came from. If you're building a turbine and the steel's coming from China, we would send people to China to make sure that the steel we were buying was the steel we were using. And so that became the H bomb. The hardware bill of materials, bad name. But, you know, we remember what it stood for. And then fast forward: President Biden's executive order. SBOs front and center, cloud first front and center. It's like, this is perfect. And so I was actually- I actually moderated a panel earlier this year at Homeland Security Week in DC, where we had a sneak CISA, So Dr. Allen Friedman from CISA, and also Patrick Weir from OWASP for the framework, CISA for the framework as well, and just the general guidance, and Snake for the front end. That was where my head was going. And MongoDB is the back-end database. And what we've done is we've taken our work with Snake and we now have a proof of concept for SBOs. And so I'm now trying to kind of package that, if you like, as a program and get the word out that SBOs shouldn't be something to be afraid of. If you want to do business with the government you're going to have to create one. We are offering a secure repository to store that data, the government could have access to that repository and see that data. So there's one source of truth. And so I think SBOs is going to be really interesting. I know that, you know, some of my peers are like, oh, it's just another box to tick. And I think it's more than that. I definitely- I've just, there's something percolating in the back of my mind that this is going to be big and we're going to be able to use it to hopefully not stop things like another Log4j, there's always going to be another Log4j, we know that. we don't know everything, the unknown unknown, but at least if we're prepared to go find stuff quicker than we were then before Log4j, I think having SBOs on hand, having that one source of truth, that one repository, I think is going to make it so much easier to find those things. >> Last question, what's the CISO's number one challenge? Either yours or the CISO, generally. >> Keeping up with the fire hose that is security. Like, what do you pick tomorrow? And if you pick the wrong thing, what's the impact? So that's why I'm always networking and talking to my peers. And, you know, we're sometimes like meerkats, you know. there's meerkats, you see like this, it's like, what do we talk about? But there's always something to talk about. And you just have to learn and keep learning. >> Last question, part B. As a hot technology company, that's, you know, rising star, you know not withstanding the tech lash and the stock market- >> Yeah. >> But Mongo's growing, you know, wonderfully. Do you find it easier to attract talent? Like many CISOs will say, you know, lack of talent is my biggest, biggest challenge. Do you find that that's not the challenge for you? >> Not at all. I think on two fronts, one, we have the champions program. So we've got a whole internal ecosystem who love working there. So the minute one of my jobs goes on the board, they get first dibs at it. So they'd already phoning their friends. So we've got, you know, there's ripple effects out from over a hundred people internally. You know, I think just having that, that's been a game changer. >> I was so looking forward to interviewing you, Lena, thanks so much for coming. >> Thank you, this was a pleasure. >> It was really great to have you. >> Thank you so much. Thank you. >> You're really welcome. All right, keep it right there. This is Dave Villante for theCUBE. We'll be right back at AWS Re:inforce22 right after this short break.

>>mhm. Welcome back to Boston. This is the cubes coverage of the Red Hat Summit 2022. The first Red Hat Summit we've done face to face in at least two years. 2019 was our last one. We're kind of rounding the far turn, you know, coming up for the home stretch. My name is Dave Valentin here with Paul Gillon. A J monger is here is a senior director of Iot. The Iot group for developer solutions and engineering at Intel. AJ, thanks for coming on the Cube. Thank you so much. We heard your colleague this morning and the keynote talking about the Dev Cloud. I feel like I need a Dev Cloud. What's it all about? >>So, um, we've been, uh, working with developers and the ecosystem for a long time, trying to build edge solutions. A lot of time people think about it. Solutions as, like, just computer the edge. But what really it is is you've got to have some component of the cloud. There is a network, and there is edge and edge is complicated because of the variety of devices that you need. And when you're building a solution, you got to figure out, like, where am I going to push the computer? How much of the computer I'm going to run in the cloud? How much of the computer? I'm gonna push it at the network and how much I need to run it at the edge. A lot of times what happens for developers is they don't have one environment where all of the three come together. And so what we said is, um, today the way it works is you have all these edge devices that customers by the instal, they set it up and they try to do all of that. And then they have a cloud environment they do to their development. And then they figure out how all of this comes together. And all of these things are only when they are integrating it at the customer at the solution space is when they try to do it. So what we did is we took all of these edge devices, put it in the cloud and gave one environment for cloud to the edge. Very good to your complete solution. >>Essentially simulates. >>No, it's not >>simulating span. So the cloud spans the cloud, the centralised cloud out to the edge. You >>know, what we did is we took all of these edge devices that will theoretically get deployed at the edge like we took all these variety of devices and putting it put it in a cloud environment. So these are non rack mountable devices that you can buy in the market today that you just have, like, we have about 500 devices in the cloud that you have from atom to call allusions to F. P. G s to head studio cards to graphics. All of these devices are available to you. So in one environment you have, like, you can connect to any of the cloud the hyper scholars, you could connect to any of these network devices. You can define your network topology. You could bring in any of your sources that is sitting in the gate repository or docker containers that may be sitting somewhere in a cloud environment, or it could be sitting on a docker hub. You can pull all of these things together, and we give you one place where you can build it where you can test it. You can performance benchmark it so you can know when you're actually going to the field to deploy it. What type of sizing you need. So >>let me show you, understand? If I want to test, uh, an actual edge device using 100 gig Ethernet versus an Mpls versus the five G, you can do all that without virtualizing. >>So all the H devices are there today, and the network part of it, we are building with red hat together where we are putting everything on this environment. So the network part of it is not quite yet solved, but that's what we want to solve. But the goal is here is you can let's say you have five cameras or you have 50 cameras with different type of resolutions. You want to do some ai inference type of workloads at the edge. What type of compute you need, what type of memory you need, How many devices do you need and where do you want to push the data? Because security is very important at the edge. So you gotta really figure out like I've got to secure the data on flight. I want to secure the data at Brest, and how do you do the governance of it. How do you kind of do service governance? So that all the services different containers that are running on the edge device, They're behaving well. You don't have one container hogging up all the memory or hogging up all the compute, or you don't have, like, certain points in the day. You might have priority for certain containers. So all of these mortals, where do you run it? So we have an environment that you could run all of that. >>Okay, so take that example of AI influencing at the edge. So I've got an edge device and I've developed an application, and I'm going to say Okay, I want you to do the AI influencing in real time. You got something? They become some kind of streaming data coming in, and I want you to persist, uh, every hour on the hour. I want to save that time stamp. Or if the if some event, if a deer runs across the headlights, I want you to persist that day to send that back to the cloud and you can develop that tested, benchmark >>it right, and then you can say that. Okay, look in this environment I have, like, five cameras, like at different angles, and you want to kind of try it out. And what we have is a product which is into, um, open vino, which is like an open source product, which does all of the optimizations you need for age in France. So you develop the like to recognise the deer in your example. I developed the training model somewhere in the cloud. Okay, so I have, like, I developed with all of the things have annotated the different video streams. And I know that I'm recognising a deer now. Okay, so now you need to figure out Like when the deer is coming and you want to immediately take an action. You don't want to send all of your video streams to the cloud. It's too expensive. Bandwidth costs a lot. So you want to compute that inference at the edge? Okay. In order to do that inference at the edge, you need some environment. You should be able to do it. And to build that solution What type of age device do you really need? What type of compute you need? How many cameras are you computing it? What different things you're not only recognising a deer, probably recognising some other objects could do all of that. In fact, one of the things happened was I took my nephew to San Diego Zoo and he was very disappointed that he couldn't see the chimpanzees. Uh, that was there, right, the gorillas and other things. So he was very sad. So I said, All right, there should be a better way. I saw, like there was a stream of the camera feed that was there. So what we did is we did an edge in friends and we did some logic to say, At this time of the day, the gorillas get fed, so there's likelihood of you actually seeing the gorilla is very high. So you just go at that point and so that you see >>it, you >>capture, That's what you do, and you want to develop that entire solution. It's based on whether, based on other factors, you need to bring all of these services together and build a solution, and we offer an environment that allows you to do it. Will >>you customise the the edge configuration for the for the developer If if they want 50 cameras. That's not You don't have 50 cameras available, right? >>It's all cameras. What we do is we have a streaming capability that we support so you can upload all your videos. And you can say I want to now simulate 50 streams. Want to simulate 30 streams? Or I want to do this right? Or just like two or three videos that you want to just pull in. And you want to be able to do the infant simultaneously, running different algorithms at the edge. All of that is supported, and the bigger challenge at the edge is developing. Solution is fine. And now when you go to actual deployment and post deployment monitoring, maintenance, make sure that you're like managing it. It's very complicated. What we have seen is over 50% 51% to be precise of developers are developed some kind of a cloud native applications recently, right? So that we believe that if you bring that type of a cloud native development model to the edge, then you're scaling problem. Your maintenance problem, you're like, how do you actually deploy it? All of these challenges can be better managed, Um, and if you run all of that is an orchestration later on kubernetes and we run everything on top of open shift, so you have a deployment ready solution already there it's everything is containerised everything. You have it as health charged Dr Composed. You have all their you have tested and in this environment, and now you go take that to the deployment. And if it is there on any standard kubernetes environment or in an open ship, you can just straight away deploy your application. >>What's that edge architecture looked like? What's Intel's and red hats philosophy around? You know what's programmable and it's different. I know you can run a S, a p a data centre. You guys got that covered? What's the edge look like? What's that architecture of silicon middleware? Describe that for us. >>So at the edge, you think about it, right? It can run traditional, Uh, in an industrial PC. You have a lot of Windows environment. You have a lot of the next. They're now in a in an edge environment. Quite a few of these devices. I'm not talking about Farage where there are tiny micro controllers and these devices I'm talking about those devices that connect to these forage devices. Collect the data. Do some analytics do some compute that type of thing. You have foraged devices. Could be a camera. Could be a temperature sensor. Could be like a weighing scale. Could be anything. It could be that forage and then all of that data instead of pushing all the data to the cloud. In order for you to do the analysis, you're going to have some type of an edge set of devices where it is collecting all this data, doing some decisions that's close to the data. You're making some analysis there, all of that stuff, right? So you need some analysis tools, you need certain other things. And let's say that you want to run like, UH, average costs or rail or any of these operating systems at the edge. Then you have an ability for you to manage all of that. Using a control note, the control node can also sit at the edge. In some cases, like in a smart factory, you have a little data centre in a smart factory or even in a retail >>store >>behind a closet. You have, like a bunch of devices that are sitting there, correct. And those devices all can be managed and clustered in an environment. So now the question is, how do you deploy applications to that edge? How do you collect all the data that is sitting through the camera? Other sensors and you're processing it close to where the data is being generated make immediate decisions. So the architecture would look like you have some club which does some management of this age devices management of this application, some type of control. You have some network because you need to connect to that. Then you have the whole plethora of edge, starting from an hybrid environment where you have an entire, like a mini data centre sitting at the edge. Or it could be one or two of these devices that are just collecting data from these sensors and processing it that is the heart of the other challenge. The architecture varies from different verticals, like from smart cities to retail to healthcare to industrial. They have all these different variations. They need to worry about these, uh, different environments they are going to operate under, uh, they have different regulations that they have to look into different security protocols that they need to follow. So your solution? Maybe it is just recognising people and identifying if they are wearing a helmet or a coal mine, right, whether they are wearing a safety gear equipment or not, that solution versus you are like driving in a traffic in a bike, and you, for safety reasons. We want to identify the person is wearing a helmet or not. Very different use cases, very different environments, different ways in which you are operating. But that is where the developer needs to have. Similar algorithms are used, by the way, but how you deploy it very, quite a bit. >>But the Dev Cloud make sure I understand it. You talked about like a retail store, a great example. But that's a general purpose infrastructure that's now customised through software for that retail environment. Same thing with Telco. Same thing with the smart factory, you said, not the far edge, right, but that's coming in the future. Or is that well, that >>extends far edge, putting everything in one cloud environment. We did it right. In fact, I put some cameras on some like ipads and laptops, and we could stream different videos did all of that in a data centre is a boring environment, right? What are you going to see? A bunch of racks and service, So putting far edge devices there didn't make sense. So what we did is you could just have an easy ability for you to stream or connect or a Plourde This far edge data that gets generated at the far edge. Like, say, time series data like you can take some of the time series data. Some of the sensor data are mostly camera data videos. So you upload those videos and that is as good as your streaming those videos. Right? And that means you are generating that data. And then you're developing your solution with the assumption that the camera is observing whatever is going on. And then you do your age inference and you optimise it. You make sure that you size it, and then you have a complete solution. >>Are you supporting all manner of microprocessors at the edge, including non intel? >>Um, today it is all intel, but the plan, because we are really promoting the whole open ecosystem and things like that in the future. Yes, that is really talking about it, so we want to be able to do that in the future. But today it's been like a lot of the we were trying to address the customers that we are serving today. We needed an environment where they could do all of this, for example, and what circumstances would use I five versus i nine versus putting an algorithm on using a graphics integrated graphics versus running it on a CPU or running it on a neural computer stick. It's hard, right? You need to buy all those devices you need to experiment your solutions on all of that. It's hard. So having everything available in one environment, you could compare and contrast to see what type of a vocal or makes best sense. But it's not >>just x 86 x 86 your portfolio >>portfolio of F. P. G s of graphics of like we have all what intel supports today and in future, we would want to open it up. So how >>do developers get access to this cloud? >>It is all free. You just have to go sign up and register and, uh, you get access to it. It is difficult dot intel dot com You go there, and the container playground is all available for free for developers to get access to it. And you can bring in container workloads there, or even bare metal workloads. Um, and, uh, yes, all of it is available for you >>need to reserve the endpoint devices. >>Comment. That is where it is. An interesting technology. >>Govern this. Correct. >>So what we did was we built a kind of a queuing system. Okay, So, schedule, er so you develop your application in a controlled north, and only you need the edge device when you're scheduling that workload. Okay, so we have this scheduling systems, like we use Kafka and other technologies to do the scheduling in the container workload environment, which are all the optimised operators that are available in an open shift, um, environment. So we regard those operators. Were we installed it. So what happens is you take your work, lord, and you run it. Let's say on an I seven device, when you're running that workload and I summon device, that device is dedicated to you. Okay, So and we've instrumented each of these devices with telemetry so we could see at the point your workload is running on that particular device. What is the memory looking like power looking like How hard is the device running? What is a compute looking like? So we capture all that metrics. Then what you do is you take it and run it on a 99 or run it on a graphic, so can't run it on an F p g a. Then you compare and contrast. And you say Huh? Okay for this particular work, Lord, this device makes best sense. In some cases, I'll tell you. Right, Uh, developers have come back and told me I don't need a bigger process that I need bigger memory. >>Yeah, sure, >>right. And some cases they've said, Look, I have I want to prioritise accuracy over performance because if you're in a healthcare setting, accuracy is more important. In some cases, they have optimised it for the size of the device because it needs to fit in the right environment in the right place. So every use case where you optimise is up to the solution up to the developer, and we give you an ability for you to do that kind >>of folks are you seeing? You got hardware developers, you get software developers are right, people coming in. And >>we have a lot of system integrators. We have enterprises that are coming in. We are seeing a lot of, uh, software solution developers, independent software developers. We also have a lot of students are coming in free environment for them to kind of play with in sort of them having to buy all of these devices. We're seeing those people. Um I mean, we are pulling through a lot of developers in this environment currently, and, uh, we're getting, of course, feedback from the developers. We are just getting started here. We are continuing to improve our capabilities. We are adding, like, virtualisation capabilities. We are working very closely with red hat to kind of showcase all the goodness that's coming out of red hat, open shift and other innovations. Right? We heard, uh, like, you know, in one of the open shift sessions, they're talking about micro shifts. They're talking about hyper shift, the talking about a lot of these innovations, operators, everything that is coming together. But where do developers play with all of this? If you spend half your time trying to configure it, instal it and buy the hardware, Trying to figure it out. You lose patience. What we have time, you lose time. What is time and it's complicated, right? How do you set up? Especially when you involve cloud. It has network. It has got the edge. You need all of that right? Set up. So what we have done is we've set up everything for you. You just come in. And by the way, not only just that what we realised is when you go talk to customers, they don't want to listen to all our optimizations processors and all that. They want to say that I am here to solve my retail problem. I want to count the people coming into my store, right. I want to see that if there is any spills that I recognise and I want to go clean it up before a customer complaints about it or I have a brain tumour segmentation where I want to identify if the tumour is malignant or not, right and I want to telehealth solutions. So they're really talking about these use cases that are talking about all these things. So What we did is we build many of these use cases by talking to customers. We open sourced it and made it available on Death Cloud for developers to use as a starting point so that they have this retail starting point or they have this healthcare starting point. All these use cases so that they have all the court we have showed them how to contain arise it. The biggest problem is developers still don't know at the edge how to bring a legacy application and make it cloud native. So they just wrap it all into one doctor and they say, OK, now I'm containerised got a lot more to do. So we tell them how to do it, right? So we train these developers, we give them an opportunity to experiment with all these use cases so that they get closer and closer to what the customer solutions need to be. >>Yeah, we saw that a lot with the early cloud where they wrapped their legacy apps in a container, shove it into the cloud. Say it's really hosting a legacy. Apps is all it was. It wasn't It didn't take advantage of the cloud. Never Now people come around. It sounds like a great developer. Free resource. Take advantage of that. Where do they go? They go. >>So it's def cloud dot intel dot com >>death cloud dot intel dot com. Check it out. It's a great freebie, AJ. Thanks very much. >>Thank you very much. I really appreciate your time. All right, >>keep it right there. This is Dave Volonte for Paul Dillon. We're right back. Covering the cube at Red Hat Summit 2022. >>Mhm. Yeah. Mhm. Mm.