>>Welcome back everyone, to the special presentation of Cloud Native at scale, the Cube and Platform nine special presentation going in and digging into the next generation super cloud infrastructure as code and the future of application development. We're here with Bickley, who's the chief architect and co-founder of Platform nine Pick. Great to see you Cube alumni. We, we met at an OpenStack event in about eight years ago, or later, earlier when OpenStack was going. Great to see you and great to see congratulations on the success of Platform nine. Thank >>You very much. >>Yeah. You guys have been at this for a while and this is really the, the, the year we're seeing the, the crossover of Kubernetes because of what happens with containers. Everyone now has realized, and you've seen what Docker's doing with the new docker, the open source Docker now just a success Exactly. Of containerization. Right? And now the Kubernetes layer that we've been working on for years is coming, Bearing fruit. This is huge. >>Exactly, Yes. >>And so as infrastructure, as code comes in, we talked to Bacar, talking about Super Cloud. I met her about, you know, the new Arlon, our, our lawn you guys just launched, the infrastructure's code is going to another level, and then it's always been DevOps infrastructure is code. That's been the ethos that's been like from day one, developers just code. Then you saw the rise of serverless and you see now multi-cloud or on the horizon. Connect the dots for us. What is the state of infrastructures code today? >>So I think, I think I'm, I'm glad you mentioned it. Everybody or most people know about infrastructures code, but with Kubernetes, I think that project has evolved at the concept even further. And these dates, it's infrastructure is configuration, right? So, which is an evolution of infrastructure as code. So instead of telling the system, here's how I want my infrastructure by telling it, you know, do step A, B, C, and D. Instead, with Kubernetes, you can describe your desired state declaratively using things called manifest resources. And then the system kind of magically figures it out and tries to converge the state towards the one that you specify. So I think it's, it's a even better version of infrastructures code. Yeah, >>Yeah. And, and that really means it's developer just accessing resources. Okay. That declare, Okay, give me some compute, stand me up some, turn the lights on, turn 'em off, turn 'em on. That's kind of where we see this going. And I like the configuration piece. Some people say composability, I mean now with open source, so popular, you don't have to have to write a lot of code, this code being developed. And so it's into integrations, configuration. These are areas that we're starting to see computer science principles around automation, machine learning, assisting open source. Cuz you've got a lot of code that's right in hearing software, supply chain issues. So infrastructure as code has to factor in these new, new dynamics. Can you share your opinion on these new dynamics of, as open source grows, the glue layers, the configurations, the integration, what are the core issues? >>I think one of the major core issues is with all that power comes complexity, right? So, you know, despite its expressive power systems like Kubernetes and declarative APIs let you express a lot of complicated and complex stacks, right? But you're dealing with hundreds if not thousands of these yamo files or resources. And so I think, you know, the emergence of systems and layers to help you manage that complexity is becoming a key challenge and opportunity in, in this space. That's, >>I wrote a LinkedIn post today, it was comments about, you know, hey, enterprise is the new breed, the trend of SaaS companies moving our consumer comp consumer-like thinking into the enterprise has been happening for a long time, but now more than ever, you're seeing it the old way used to be solve complexity with more complexity and then lock the customer in. Now with open source, it's speed, simplification and integration, right? These are the new dynamic power dynamics for developers. Yeah. So as companies are starting to now deploy and look at Kubernetes, what are the things that need to be in place? Because you have some, I won't say technical debt, but maybe some shortcuts, some scripts here that make it look like infrastructure is code. People have done some things to simulate or or make infrastructure as code happen. Yes. But to do it at scale Yes. Is harder. What's your take on this? What's your >>View? It's hard because there's a per proliferation of methods, tools, technologies. So for example, today it's very common for DevOps and platform engineering tools, I mean, sorry, teams to have to deploy a large number of Kubernetes clusters, but then apply the applications and configurations on top of those clusters. And they're using a wide range of tools to do this, right? For example, maybe Ansible or Terraform or bash scripts to bring up the infrastructure and then the clusters. And then they may use a different set of tools such as Argo CD or other tools to apply configurations and applications on top of the clusters. So you have this sprawl of tools. You, you also have this sprawl of configurations and files because the more objects you're dealing with, the more resources you have to manage. And there's a risk of drift that people call that where, you know, you think you have things under control, but some people from various teams will make changes here and there and then before the end of the day systems break and you have no idea of tracking them. So I think there's real need to kind of unify, simplify, and try to solve these problems using a smaller, more unified set of tools and methodologies. And that's something that we tried to do with this new project. Arlon. >>Yeah. So, so we're gonna get into our line in a second. I wanna get into the why Arlon. You guys announced that at our GoCon, which was put on here in Silicon Valley at the, at the community invite in two where they had their own little day over there at their headquarters. But before we get there, vascar, your CEO came on and he talked about Super Cloud at our in AAL event. What's your definition of super cloud? If you had to kind of explain that to someone at a cocktail party or someone in the industry technical, how would you look at the super cloud trend that's emerging? It's become a thing. What's your, what would be your contribution to that definition or the narrative? >>Well, it's, it's, it's funny because I've actually heard of the term for the first time today, speaking to you earlier today. But I think based on what you said, I I already get kind of some of the, the gist and the, the main concepts. It seems like super cloud, the way I interpret that is, you know, clouds and infrastructure, programmable infrastructure, all of those things are becoming commodity in a way. And everyone's got their own flavor, but there's a real opportunity for people to solve real business problems by perhaps trying to abstract away, you know, all of those various implementations and then building better abstractions that are perhaps business or application specific to help companies and businesses solve real business problems. >>Yeah, I remember that's a great, great definition. I remember, not to date myself, but back in the old days, you know, IBM had a proprietary network operating system, so of deck for the mini computer vendors, deck net and SNA respectively. But T C P I P came out of the osi, the open systems interconnect and remember, ethernet beat token ring out. So not to get all nerdy for all the young kids out there, look, just look up token ring, you'll see, you've probably never heard of it. It's IBM's, you know, connection to the internet at the, the layer too is Amazon, the ethernet, right? So if T C P I P could be the Kubernetes and the container abstraction that made the industry completely change at that point in history. So at every major inflection point where there's been serious industry change and wealth creation and business value, there's been an abstraction Yes. Somewhere. Yes. What's your reaction to that? >>I think this is, I think a saying that's been heard many times in this industry and, and I forgot who originated it, but I think the saying goes like, there's no problem that can't be solved with another layer of indirection, right? And we've seen this over and over and over again where Amazon and its peers have inserted this layer that has simplified, you know, computing and, and infrastructure management. And I believe this trend is going to continue, right? The next set of problems are going to be solved with these insertions of additional abstraction layers. I think that that's really a, yeah, it's gonna continue. >>It's interesting. I just, when I wrote another post today on LinkedIn called the Silicon Wars AMD stock is down arm has been on a rise. We've remember pointing for many years now, that arm's gonna be hugely, it has become true. If you look at the success of the infrastructure as a serviced layer across the clouds, Azure, aws, Amazon's clearly way ahead of everybody. The stuff that they're doing with the silicon and the physics and the, the atoms, the pro, you know, this is where the innovation, they're going so deep and so strong at ISAs, the more that they get that gets come on, they have more performance. So if you're an app developer, wouldn't you want the best performance and you'd want to have the best abstraction layer that gives you the most ability to do infrastructures, code or infrastructure for configuration, for provisioning, for managing services. And you're seeing that today with service MeSHs, a lot of action going on in the service mesh area in in this community of, of co con, which we will be covering. So that brings up the whole what's next? You guys just announced Arlon at ar GoCon, which came out of Intuit. We've had Mariana Tessel at our super cloud event. She's the cto, you know, they're all in the cloud. So they contributed that project. Where did Arlon come from? What was the origination? What's the purpose? Why arlon, why this announcement? Yeah, >>So the, the inception of the project, this was the result of us realizing that problem that we spoke about earlier, which is complexity, right? With all of this, these clouds, these infrastructure, all the variations around and, you know, compute storage networks and the proliferation of tools we talked about the Ansibles and Terraforms and Kubernetes itself, you can think of that as another tool, right? We saw a need to solve that complexity problem, and especially for people and users who use Kubernetes at scale. So when you have, you know, hundreds of clusters, thousands of applications, thousands of users spread out over many, many locations, there, there needs to be a system that helps simplify that management, right? So that means fewer tools, more expressive ways of describing the state that you want and more consistency. And, and that's why, you know, we built our lawn and we built it recognizing that many of these problems or sub problems have already been solved. So Arlon doesn't try to reinvent the wheel, it instead rests on the shoulders of several giants, right? So for example, Kubernetes is one building block, GI ops, and Argo CD is another one, which provides a very structured way of applying configuration. And then we have projects like cluster API and cross plane, which provide APIs for describing infrastructure. So arlon takes all of those building blocks and builds a thin layer, which gives users a very expressive way of defining configuration and desired state. So that's, that's kind of the inception of, >>And what's the benefit of that? What does that give the, what does that give the developer, the user, in this case, >>The developers, the, the platform engineer, team members, the DevOps engineers, they get a a ways to provision not just infrastructure and clusters, but also applications and configurations. They get a way, a system for provisioning, configuring, deploying, and doing life cycle management in a, in a much simpler way. Okay. Especially as I said, if you're dealing with a large number of applications. >>So it's like an operating fabric, if you will. Yes. For them. Okay, so let's get into what that means for up above and below the, the, this abstraction or thin layer below as the infrastructure. We talked a lot about what's going on below that. Yeah. Above our workloads. At the end of the day, you, I talk to CXOs and IT folks that, that are now DevOps engineers. They care about the workloads and they want the infrastructure's code to work. They wanna spend their time getting in the weeds, figuring out what happened when someone made a push that that happened or something happened to need observability and they need to, to know that it's working. That's right. And here's my workloads running effectively. So how do you guys look at the workload side of it? Cuz now you have multiple workloads on these fabric, right? >>So workloads, so Kubernetes has defined kind of a standard way to describe workloads and you can, you know, tell Kubernetes, I wanna run this container this particular way, or you can use other projects that are in the Kubernetes cloud native ecosystem, like K native, where you can express your application in more at a higher level, right? But what's also happening is in addition to the workloads, DevOps and platform engineering teams, they need to very often deploy the applications with the clusters themselves. Clusters are becoming this commodity. It's, it's becoming this host for the application and it kind of comes bundled with it. In many cases it is like an appliance, right? So DevOps teams have to provision clusters at a really incredible rate and they need to tear them down. Clusters are becoming more, >>It's coming like an EC two instance, spin up a cluster. We very, people used words like that. >>That's right. And before arlon you kind of had to do all of that using a different set of tools as, as I explained. So with Arlon you can kind of express everything together. You can say I want a cluster with a health monitoring stack and a logging stack and this ingress controller and I want these applications and these security policies. You can describe all of that using something we call a profile. And then you can stamp out your app, your applications and your clusters and manage them in a very, >>So essentially standard like creates a mechanism. Exactly. Standardized, declarative kind of configurations. And it's like a playbook, deploy it. Now what there between say a script like I'm, I have scripts, I can just automate scripts >>Or yes, this is where that declarative API and infrastructures configuration comes in, right? Because scripts, yes you can automate scripts, but the order in which they run matters, right? They can break, things can break in the middle and, and sometimes you need to debug them. Whereas the declarative way is much more expressive and powerful. You just tell the system what you want and then the system kind of figures it out. And there are these things got controllers which will in the background reconcile all the state to converge towards your desire. It's a much more powerful, expressive and reliable way of getting things done. >>So infrastructure has configuration is built kind of on it's super set of infrastructures code because it's >>An evolution. >>You need edge re's code, but then you can configure the code by just saying do it. You basically declaring it's saying Go, go do that. That's right. Okay, so, alright, so cloud native at scale, take me through your vision of what that means. Someone says, Hey, what does cloud native at scale mean? What's success look like? How does it roll out in the future as you, not future next couple years. I mean people are now starting to figure out, okay, it's not as easy as it sounds. Kubernetes has value. We're gonna hear this year coan a lot of this. What does cloud native at scale mean? >>Yeah, there are different interpretations, but if you ask me, when people think of scale, they think of a large number of deployments, right? Geographies, many, you know, supporting thousands or tens or millions of, of users there, there's that aspect to scale. There's also an equally important a aspect of scale, which is also something that we try to address with Arran. And that is just complexity for the people operating this or configuring this, right? So in order to describe that desired state, and in order to perform things like maybe upgrades or updates on a very large scale, you want the humans behind that to be able to express and direct the system to do that in, in relatively simple terms, right? And so we want the tools and the abstractions and the mechanisms available to the user to be as powerful but as simple as possible. So there's, I think there's gonna be a number and there have been a number of CNCF and cloud native projects that are trying to attack that complexity problem as well. And Arlon kind of falls in in that >>Category. Okay, so I'll put you on the spot. Rogue got Coan coming up and obviously this'll be shipping this segment series out before. What do you expect to see at this year? What's the big story this year? What's the, what's the most important thing happening? Is it in the open source community and also within a lot of the, the people jogging for leadership. I know there's a lot of projects and still there's some white space in the overall systems map about the different areas get run time, there's ability in all these different areas. What's the, where's the action? Where, where's the smoke? Where's the fire? Where's the piece? Where's the tension? >>Yeah, so I think one thing that has been happening over the past couple of cub cons and I expect to continue and, and that is the, the word on the street is Kubernetes is getting boring, right? Which is good, right? >>Boring means simple. >>Well, >>Well maybe, >>Yeah, >>Invisible, >>No drama, right? So, so the, the rate of change of the Kubernetes features and, and all that has slowed, but in, in a, in a positive way. But there's still a general sentiment and feeling that there's just too much stuff. If you look at a stack necessary for hosting applications based on Kubernetes, there are just still too many moving parts, too many components, right? Too much complexity. I go, I keep going back to the complexity problem. So I expect Cube Con and all the vendors and the players and the startups and the people there to continue to focus on that complexity problem and introduce further simplifications to, to the stack. >>Yeah. Vic, you've had an storied career, VMware over decades with them, obviously in 12 years with 14 years or something like that. Big number co-founder here at Platform now you's been around for a while at this game. We, man, we talked about OpenStack, that project you, we interviewed at one of their events. So OpenStack was the beginning of that, this new revolution. I remember the early days it was, it wasn't supposed to be an alternative to Amazon, but it was a way to do more cloud cloud native. I think we had a cloud a Rod team at that time. We would joke we, you know, about, about the dream. It's happening now, now at Platform nine. You guys have been doing this for a while. What's the, what are you most excited about as the chief architect? What did you guys double down on? What did you guys pivot from or two, did you do any pivots? Did you extend out certain areas? Cuz you guys are in a good position right now, a lot of DNA in Cloud native. What are you most excited about and what does Platform Nine bring to the table for customers and for people in the industry watching this? >>Yeah, so I think our mission really hasn't changed over the years, right? It's been always about taking complex open source software because open source software, it's powerful. It solves new problems, you know, every year and you have new things coming out all the time, right? Open Stack was an example where the Kubernetes took the world by storm. But there's always that complexity of, you know, just configuring it, deploying it, running it, operating it. And our mission has always been that we will take all that complexity and just make it, you know, easy for users to consume regardless of the technology, right? So the successor to Kubernetes, you know, I don't have a crystal ball, but you know, you have some indications that people are coming up of new and simpler ways of running applications. There are many projects around there who knows what's coming next year or the year after that. But platform will, a, platform nine will be there and we will, you know, take the innovations from the, the, the community. We will contribute our own innovations and make all of those things very consumable to customers. >>Simpler, faster, cheaper. Exactly. Always a good business model technically to make that happen. Yes. Yeah. I think the, the reigning in the chaos is key, you know, Now we have now visibility into the scale. Final question before we depart Yeah. On this segment, what is at scale, how many clusters do you see that would be a, a watermark for an at scale conversation around an enterprise? Is it workloads we're looking at or, or clusters? How would you Yeah, I would you describe that when people try to squint through and evaluate what's a scale, what's the at scale kind of threshold? >>Yeah. And, and the number of clusters doesn't tell the whole story because clusters can be small in terms of the number of nodes or they can be large. But roughly speaking when we say, you know, large scale cluster deployments, we're talking about maybe hundreds, two thousands. Yeah. >>And final final question, what's the role of the hyperscalers? You got AWS continuing to do well, but they got their core ias, they got a PAs, they're not too too much putting a SaaS out there. They have some SaaS apps, but mostly it's the ecosystem. They have marketplaces doing, doing over $2 billion billions of transactions a year. And, and it's just like, just sitting there. It hasn't really, they're now innovating on it, but that's gonna change ecosystems. What's the role the cloud play in the cloud Native at scale? >>The the hyper square? >>Yeah. Yeah. Abras, Azure, Google, >>You mean from a business perspective, they're, they have their own interests that, you know, that they're, they will keep catering to, They, they will continue to find ways to lock their users into their ecosystem of services and, and APIs. So I don't think that's gonna change, right? They're just gonna keep Well, >>They got great I performance, I mean from a, from a hardware standpoint, yes. That's gonna be key, right? >>Yes. I think the, the move from X 86 being the dominant way and platform to run workloads is changing, right? That, that, that, that, and I think the, the hyperscalers really want to be in the game in terms of, you know, the, the new risk and arm ecosystems and the >>Platforms. Yeah. Not joking aside, Paul Morritz, when he was the CEO of VMware, when he took over once said, I remember our first year doing the cube. Oh, the cloud is one big distributed computer. It's, it's hardware and you got software and you got middleware. And he kinda over, well he kind of tongue in cheek, but really you're talking about large compute and sets of services that is essentially a distributed computer. Yes, >>Exactly. >>It's, we're back in the same game. Thank you for coming on the segment. Appreciate your time. This is cloud native at scale special presentation with Platform nine. Really unpacking super cloud Arlon open source and how to run large scale applications on the cloud, Cloud native develop for developers. And John Feer with the cube. Thanks for Washington. We'll stay tuned for another great segment coming right up.

>>Welcome back everyone, to the special presentation of Cloud Native at scale, the Cube and Platform nine special presentation going in and digging into the next generation super cloud infrastructure as code and the future of application development. We're here with Bickley, who's the chief architect and co-founder of Platform nine Pick. Great to see you Cube alumni. We, we met at an OpenStack event in about eight years ago, or well later, earlier when OpenStack was going. Great to see you and great to see congratulations on the success of Platform nine. Thank >>You very much. >>Yeah. You guys have been at this for a while and this is really the, the, the year we're seeing the, the crossover of Kubernetes because of what happens with containers. Everyone now has realized, and you've seen what Docker's doing with the new docker, the open source, Docker now just the success of containerization, right? And now the Kubernetes layer that we've been working on for years is coming, Bearing fruit. This is huge. >>Exactly. Yes. >>And so as infrastructures code comes in, we talked to Basco talking about Super Cloud. I met her about, you know, the new Arlon, our R lawn, and you guys just launched the infrastructures code is going to another level, and then it's always been DevOps infrastructures code. That's been the ethos that's been like from day one, developers just code. Then you saw the rise of serverless and you see now multi-cloud or on the horizon. Connect the dots for us. What is the state of infrastructures code today? >>So I think, I think I'm, I'm glad you mentioned it. Everybody or most people know about infrastructures code, but with Kubernetes, I think that project has evolved at the concept even further. And these dates, it's infrastructure is configuration, right? So, which is an evolution of infrastructure as code. So instead of telling the system, here's how I want my infrastructure by telling it, you know, do step A, B, C, and D. Instead, with Kubernetes you can describe your desired state declaratively using things called manifest resources. And then the system kind of magically figures it out and tries to converge the state towards the one that you specified. So I think it's, it's a even better version of infrastructures code. Yeah, >>Yeah. And that really means it developer just accessing resources. Okay, not clearing, Okay, give me some compute. Stand me up some, Turn the lights on, turn 'em off, turn 'em on. That's kind of where we see this going. And I like the configuration piece. Some people say composability, I mean, now with open source, so popular, you don't have to have to write a lot of code, this code being developed. And so it's integration, it's configuration. These are areas that we're starting to see computer science principles around automation, machine learning, assisting open source. Cuz you've got a lot of code that's right in hearing software, supply chain issues. So infrastructure as code has to factor in these, these new dynamics. Can you share your opinion on these new dynamics of, as open source grows, the glue layers, the configurations, the integration, what are the core issues? >>I think one of the major core issues is with all that power comes complexity, right? So, you know, despite its expressive power systems like Kubernetes and declarative APIs let you express a lot of complicated and complex stacks, right? But you're dealing with hundreds if not thousands of these yamo files or resources. And so I think, you know, the emergence of systems and layers to help you manage that complexity is becoming a key challenge and opportunity in, in this space. The that's, >>I wrote a LinkedIn post today was comments about, you know, hey, enterprise is a new breed. The trend of SaaS companies moving our consumer comp consumer-like thinking into the enterprise has been happening for a long time, but now more than ever, you're seeing it the old way used to be solve complexity with more complexity and then lock the customer in. Now with open source, it's speed, simplification and integration, right? These are the new dynamic power dynamics for developers. Yeah. So as companies are starting to now deploy and look at Kubernetes, what are the things that need to be in place? Because you have some, I won't say technical debt, but maybe some shortcuts, some scripts here that make it look like infrastructure is code. People have done some things to simulate or or make infrastructure as code happen. Yes. But to do it at scale Yes. Is harder. What's your take on this? What's your view? >>It's hard because there's a per proliferation of methods, tools, technologies. So for example, today it's very common for DevOps and platform engineering tools, I mean, sorry, teams to have to deploy a large number of Kubernetes clusters, but then apply the applications and configurations on top of those clusters. And they're using a wide range of tools to do this, right? For example, maybe Ansible or Terraform or bash scripts to bring up the infrastructure and then the clusters. And then they may use a different set of tools such as Argo CD or other tools to apply configurations and applications on top of the clusters. So you have this sprawl of tools. You, you also have this sprawl of configurations and files because the more objects you're dealing with, the more resources you have to manage. And there's a risk of drift that people call that where, you know, you think you have things under control, but some people from various teams will make changes here and there and then before the end of the day systems break and you have no idea of tracking them. So I think there's real need to kind of unify, simplify, and try to solve these problems using a smaller, more unified set of tools and methodologies. And that's something that we try to do with this new project. Arlon. >>Yeah. So, so we're gonna get into Arlan in a second. I wanna get into the why Arlon. You guys announced that at our GoCon, which was put on here in Silicon Valley at the computer by, in two, where they had their own little day over there at their headquarters. But before we get there, Bacar, your CEO came on and he talked about Super Cloud at our in aural event. What's your definition of super cloud? If you had to kind of explain that to someone at a cocktail party or someone in the industry technical, how would you look at the super cloud trend that's emerging? It's become a thing. What's your, what would be your contribution to that definition or the narrative? >>Well, it's, it's, it's funny because I've actually heard of the term for the first time today, speaking to you earlier today. But I think based on what you said, I I already get kind of some of the, the gist and the, the main concepts. It seems like super cloud, the way I interpret that is, you know, clouds and infrastructure, programmable infrastructure, all of those things are becoming commodity in a way. And everyone's got their own flavor, but there's a real opportunity for people to solve real business problems by perhaps trying to abstract away, you know, all of those various implementations and then building better abstractions that are perhaps business or application specific to help companies and businesses solve real business problems. >>Yeah, I remember that's a great, great definition. I remember, not to date myself, but back in the old days, you know, IBM had a proprietary network operating system. So the deck for the mini computer vendors, deck net and SNA respectively. But T C P I P came out of the osi, the open systems interconnect and remember, ethernet beat token ring out. So not to get all nerdy for all the young kids out there, look, just look up token ring, you'll see, you've probably never heard of it. It's IBM's, you know, connection for the internet at the, the layer two is Amazon, the ethernet, right? So if T C P I P could be the Kubernetes and the container abstraction that made the industry completely change at that point in history. So at every major inflection point where there's been serious industry change and wealth creation and business value, there's been an abstraction Yes. Somewhere. Yes. What's your reaction to that? >>I think this is, I think a saying that's been heard many times in this industry and, and I forgot who originated it, but I think the saying goes like, there's no problem that can't be solved with another layer of indirection, right? And we've seen this over and over and over again where Amazon and its peers have inserted this layer that has simplified, you know, computing and, and infrastructure management. And I believe this trend is going to continue, right? The next set of problems are going to be solved with these insertions of additional abstraction layers. I think that that's really a, yeah, >>It's >>Gonna >>Continue. It's interesting. I just, when I wrote another post today on LinkedIn called the Silicon Wars AMD stock is down arm has been on a rise. We've remember pointing for many years now, that arm's gonna be hugely, it has become true. If you look at the success of the infrastructure as a service layer across the clouds, Azure, aws, Amazon's clearly way ahead of everybody. The stuff that they're doing with the silicon and the physics and the, the atoms, the pro, you know, this is where the innovation, they're going so deep and so strong at ISAs, the more that they get that gets come on, they have more performance. So if you're an app developer, wouldn't you want the best performance and you'd wanna have the best abstraction layer that gives you the most ability to do infrastructures, code or infrastructure for configuration, for provisioning, for managing services. And you're seeing that today with service MeSHs, a lot of action going on in the service mesh area in in this community of, of co con, which will be a covering. So that brings up the whole what's next? You guys just announced our lawn at ar GoCon, which came out of Intuit. We've had Mariana Tessel at our super cloud event. She's the cto, you know, they're all in the cloud. So they contributed that project. Where did Arlon come from? What was the origination? What's the purpose? Why our lawn, why this announcement? >>Yeah, so the, the inception of the project, this was the result of us realizing that problem that we spoke about earlier, which is complexity, right? With all of this, these clouds, these infrastructure, all the variations around and, you know, compute storage networks and the proliferation of tools we talked about the Ansibles and Terraforms and Kubernetes itself, you can think of that as another tool, right? We saw a need to solve that complexity problem, and especially for people and users who use Kubernetes at scale. So when you have, you know, hundreds of clusters, thousands of applications, thousands of users spread out over many, many locations, there, there needs to be a system that helps simplify that management, right? So that means fewer tools, more expressive ways of describing the state that you want and more consistency. And, and that's why, you know, we built Arlan and we built it recognizing that many of these problems or sub problems have already been solved. So Arlon doesn't try to reinvent the wheel, it instead rests on the shoulders of several giants, right? So for example, Kubernetes is one building block, GI ops, and Argo CD is another one, which provides a very structured way of applying configuration. And then we have projects like cluster API and cross plane, which provide APIs for describing infrastructure. So arlon takes all of those building blocks and builds a thin layer, which gives users a very expressive way of defining configuration and desired state. So that's, that's kind of the inception of, >>And what's the benefit of that? What does that give the, what does that give the developer, the user, in this case, >>The developers, the, the platform engineer, team members, the DevOps engineers, they get a a ways to provision not just infrastructure and clusters, but also applications and configurations. They get a way, a system for provisioning, configuring, deploying, and doing life cycle management in a, in a much simpler way. Okay. Especially as I said, if you're dealing with a large number of applications. >>So it's like an operating fabric, if you will. Yes. For them. Okay, So let's get into what that means for up above and below the, the, this abstraction or thin layer below as the infrastructure. We talked a lot about what's going on below that. Yeah. Above our workloads. At the end of the day, you know, I talk to CXOs and IT folks that, that are now DevOps engineers. They care about the workloads and they want the infrastructure's code to work. They wanna spend their time getting in the weeds, figuring out what happened when someone made a push that that happened or something happened. They need observability and they need to, to know that it's working. That's right. And here's my workloads running effectively. So how do you guys look at the workload side of it? Cuz now you have multiple workloads on these fabric, right? >>So workloads, so Kubernetes has defined kind of a standard way to describe workloads. And you can, you know, tell Kubernetes, I want to run this container this particular way, or you can use other projects that are in the Kubernetes cloud native ecosystem, like K native, where you can express your application in more at a higher level, right? But what's also happening is in addition to the workloads, DevOps and platform engineering teams, they need to very often deploy the applications with the clusters themselves. Clusters are becoming this commodity. It's, it's becoming this host for the application and it kind of comes bundled with it. In many cases, it's like an appliance, right? So DevOps teams have to provision clusters at a really incredible rate and they need to tear them down. Clusters are becoming more, >>It's coming like an EC two instance, spin up a cluster. We've heard people used words like that. That's >>Right. And before arlon, you kind of had to do all of that using a different set of tools as, as I explained. So with Arlon you can kind of express everything together. You can say, I want a cluster with a health monitoring stack and a logging stack and this ingress controller and I want these applications and these security policies. You can describe all of that using something we call a profile. And then you can stamp out your app, your applications, and your clusters and manage them in a very, So >>It's essentially standard, like creates a mechanism. Exactly. Standardized, declarative kind of configurations. And it's like a playbook, deploy it. Now what's there is between say a script like I have scripts, I can just automate scripts >>Or yes, this is where that declarative API and infrastructures configuration comes in, right? Because scripts, yes, you can automate scripts, but the order in which they run matters, right? They can break, things can break in the middle and, and sometimes you need to debug them. Whereas the declarative way is much more expressive and powerful. You just tell the system what you want and then the system kind of figures it out. And there are these things about controllers, which will in the background reconcile all the state to converge towards your desire. It's a much more powerful, expressive and reliable way of getting things done. >>So infrastructure has configuration is built kind of on its super set of infrastructures code because it's an evolution. You need edge retro's code, but then you can configure the code by just saying do it. You basically declaring it saying Go, go do that. That's right. Okay, So, all right, so Cloudnative at scale, take me through your vision of what that means. Someone says, Hey, what does cloudnative at scale mean? What's success look like? How does it roll out in the future as you, not future next couple years? I mean, people are now starting to figure out, okay, it's not as easy as it sounds. Kubernetes has value. We're gonna hear this year at co con a lot of this, what does cloud native at scale >>Mean? Yeah, there are different interpretations, but if you ask me, when people think of scale, they think of a large number of deployments, right? Geographies, many, you know, supporting thousands or tens or millions of, of users. There, there's that aspect to scale. There's also an equally important a aspect of scale, which is also something that we, we try to address with Arlan. And that is just complexity for the people operating this or configuring this, right? So in order to describe that desired state, and in order to perform things like maybe upgrades or updates on a very large scale, you want the humans behind that to be able to express and direct the system to do that in, in relatively simple terms, right? And so we want the tools and the abstractions and the mechanisms available to the user to be as powerful but as simple as possible. So there's, I think there's gonna be a number and there have been a number of CNCF and cloud native projects that are trying to attack that complexity problem as well. And Arlon kind of falls in in that >>Category. Okay, So I'll put you on the spot road that Coan coming up, and obviously this will be shipping this segment series out before. What do you expect to see at Coan this year? What's the big story this year? What's the, what's the most important thing happening? Is it in the open source community and also within a lot of the, the people jocking for leadership. I know there's a lot of projects and still there's some white space in the overall systems map about the different areas get run time and there's their ability in all these different areas. What's the, where's the action? Where, where's the smoke? Where's the fire? Where's the piece? Where's the tension? >>Yeah, so I think one thing that has been happening over the past couple of cub cons and I expect to continue, and, and that is the, the word on the street is Kubernetes is getting boring, right? Which is good, right? >>Boring means simple. >>Well, well >>Maybe, >>Yeah, >>Invisible, >>No drama, right? So, so the, the rate of change of the Kubernetes features and, and all that has slowed, but in, in a, in a positive way. But there's still a general sentiment and feeling that there's just too much stuff. If you look at a stack necessary for hosting applications based on Kubernetes, there're just still too many moving parts, too many components, right? Too much complexity. I go, I keep going back to the complexity problem. So I expect Cube Con and all the vendors and the players and the startups and the people there to continue to focus on that complexity problem and introduce further simplifications to, to the stack. Yeah. >>B, you've had a storied career VMware over decades with them, obviously with 12 years, with 14 years or something like that. Big number. Co-founder here, a platform. Now you guys been around for a while at this game. We, man, we talked about OpenStack, that project you, we interviewed at one of their events. So OpenStack was the beginning of that, this new revolution. And I remember the early days it was, it wasn't supposed to be an alternative to Amazon, but it was a way to do more cloud cloud native. I think we had a cloud a Rod team at that time. We to joke we, you know, about, about the dream. It's happening now, now at Platform nine. You guys have been doing this for a while. What's the, what are you most excited about as the chief architect? What did you guys double down on? What did you guys pivot from or two, did you do any pivots? Did you extend out certain areas? Cuz you guys are in a good position right now, a lot of DNA in Cloud native. What are you most excited about and what does Platform nine bring to the table for customers and for people in the industry watching this? >>Yeah, so I think our mission really hasn't changed over the years, right? It's been always about taking complex open source software because open source software, it's powerful. It solves new problems, you know, every year and you have new things coming out all the time, right? OpenStack was an example where the Kubernetes took the world by storm. But there's always that complexity of, you know, just configuring it, deploying it, running it, operating it. And our mission has always been that we will take all that complexity and just make it, you know, easy for users to consume regardless of the technology, right? So the successor to Kubernetes, you know, I don't have a crystal ball, but you know, you have some indications that people are coming up of new and simpler ways of running applications. There are many projects around there who knows what's coming next year or the year after that. But platform will a, platform nine will be there and we will, you know, take the innovations from the, the, the community. We will contribute our own innovations and make all of those things very consumable to customers. >>Simpler, faster, cheaper. Exactly. Always a good business model technically to make that happen. Yeah, I think the reigning in the chaos is key, you know, Now we have now visibility into the scale. Final question before we depart this segment. What is at scale, how many clusters do you see that would be a, a watermark for an at scale conversation around an enterprise? Is it workloads we're looking at or, or clusters? How would you Yeah, how would you describe that? When people try to squint through and evaluate what's a scale, what's the at scale kind of threshold? >>Yeah. And, and the number of clusters doesn't tell the whole story because clusters can be small in terms of the number of nodes or they can be large. But roughly speaking when we say, you know, large scale cluster deployments, we're talking about maybe hundreds, two thousands. >>Yeah. And final final question, what's the role of the hyperscalers? You got AWS continuing to do well, but they got their core ias, they got a PAs, they're not too too much putting a SaaS out there. They have some SaaS apps, but mostly it's the ecosystem. They have marketplaces doing over $2 billion tran billions of transactions a year and, and it's just like, just sitting there. It hasn't really, they're now innovating on it, but that's gonna change ecosystems. What's the role the cloud play in the cloud need of its scale? >>The, the hyperscalers? >>Yeah. A's Azure, Google >>You mean from a business perspective, technical, they're, they have their own interests that, you know, that they're, they will keep catering to, they, they will continue to find ways to lock their users into their ecosystem of services and, and APIs. So I don't think that's gonna change, right? They're just gonna keep >>Well, they got great I performance, I mean from a, from a hardware standpoint, yes. That's gonna be key, right? >>Yes. I think the, the move from X 86 being the dominant way and platform to run workloads is changing, right? That, that, that, that, and I think the, the hyperscalers really want to be in the game in terms of, you know, the, the new risk and arm ecosystems and, and platforms. >>Yeah. Not joking aside, Paul Morritz, when he was the CEO of VMware, when he took over once said, and I remember our first year doing the cube, Oh, the cloud is one big distributed computer. It's, it's hardware and you got software and you got middleware and he kind of over, well he's kind of tongue in cheek, but really you're talking about large compute and sets of services that is essentially a distributed computer. >>Yes, >>Exactly. It's, we're back in the same game. Vic, thank you for coming on the segment. Appreciate your time. This is cloud native at scale special presentation with Platform nine. Really unpacking super Cloud Arlon open source and how to run large scale applications on the cloud. Cloud Native Phil for developers and John Furrier with the cube. Thanks for Washington. We'll stay tuned for another great segment coming right up.

foreign [Music] to the special presentation of cloud native at scale the cube and Platform 9 special presentation going in and digging into the next generation super cloud infrastructure as code and the future of application development we're here with dick Lee who's the Chief Architect and co-founder of platform nine pick great to see you Cube alumni we we met at openstack event in about eight years ago or later earlier uh when openstack was going great to see you and great congratulations on the success of platform nine thank you very much yeah you guys been at this for a while and this is really the the Year we're seeing the the crossover of kubernetes because of what happens with containers everyone now was realized and you've seen what docker's doing with the new Docker the open source Docker now just the success of containerization and now the kubernetes layer that we've been working on for years is coming bearing fruit this is huge exactly yes and so as infrastructure as code comes in we talked to baskar talking about super cloud I met her about you know the new Arlo our our lawn um you guys just launched the infrastructure's code is going to another level and it's always been devops infrastructure is code that's been the ethos that's been like from day one developers just code I think you saw the rise of serverless and you see now multi-cloud or on the horizon connect the dots for us what is the state of infrastructure as code today so I think I think um I'm glad you mentioned it everybody or most people know about infrastructure as code but with kubernetes I think that project has evolved at the concept even further and these days it's um infrastructure as configuration right so which is an evolution of infrastructure as code so instead of telling the system here's how I want my infrastructure by telling it you know do step a b c and d uh instead with kubernetes you can describe your desired State declaratively using things called manifest resources and then the system kind of magically figures it out and tries to converge the state towards the one that you specify so I think it's it's a even better version of infrastructure as code yeah and that really means it's developer just accessing resources okay that declare okay give me some compute stand me up some turn the lights on turn them off turn them on that's kind of where we see this going and I like the configuration piece some people say composability I mean now with open source so popular you don't have to have to write a lot of code this code being developed and so it's integration it's configuration these are areas that we're starting to see computer science principles around automation machine learning assisting open source because you've got a lot of code that's what you're hearing software supply chain issues so infrastructure as code has to factor in these new Dynamics can you share your opinion on these new dynamics of as open source grows the glue layers the configurations the integration what are the core issues I think one of the major core issues is with all that power comes complexity right so um You know despite its expressive Power Systems like kubernetes and declarative apis let you express a lot of complicated and complex Stacks right but you're dealing with um hundreds if not thousands of these yaml files or resources and so I think you know the emergence of systems and layers to help you manage that complexity is becoming a key Challenge and opportunity in this space I wrote a LinkedIn post today those comments about you know hey Enterprise is the new breed the trend of SAS companies moving uh our consumer consumer-like thinking into the Enterprise has been happening for a long time but now more than ever you're seeing it the old way used to be solve complexity with more complexity and then lock the customer in now with open source it's speed simplification and integration right these are the new Dynam power dynamics for developers so as companies are starting to now deploy and look at kubernetes what are the things that need to be in place because you have some I won't say technical debt but maybe some shortcuts some scripts here that make it look like infrastructure as code people have done some things to simulate or or make infrastructures code happen yes but to do it at scale yes is harder what's your take on this what's your view it's hard because there's a proliferation of of methods tools Technologies so for example today it's a very common for devops and platform engineering tools I mean sorry teams to have to deploy a large number of kubernetes clusters but then apply the applications and configurations on top of those clusters and they're using a wide range of tools to do this right for example maybe ansible or terraform or bash scripts to bring up the infrastructure and then the Clusters and then they may use a different set of tools such as Argo CD or other tools to apply configurations and applications on top of the Clusters so you have this sprawl of tools you also you also have this sprawl of configurations and files because the more objects you're dealing with the more resources you have to manage and there's a risk of drift that people call that where you know you think you have things under control but some people from various teams will make changes here and there and then before the end of the day systems break and you have no idea of tracking them so I think there's real need to kind of unify simplify and try to solve these problems using a smaller more unified set of tools and methodology apologies and that's something that we try to do with this new project Arlon yeah so so we're going to get to our line in a second I want to get to the yr lawn you guys announced that at argocon which was put on here in Silicon Valley at the community meeting by Intuit they had their own little day over their headquarters but before we get there um Bhaskar your CEO came on and he talked about super cloud at our inaugural event what's your definition of super cloud if you had to kind of explain that to someone at a cocktail party or someone in the industry technical how would you look at the super cloud Trend that's emerging has become a thing what's your what would be your contribution to that definition or the narrative well it's it's uh funny because I've actually heard of the term for the first time today speaking to you earlier today but I think based on what you said I I already get kind of some of the the gist and the the main Concepts it seems like uh super cloud the way I interpret that is you know um clouds and infrastructure um programmable infrastructure all of those things are becoming commodity in a way and everyone's got their own flavor but there's a real opportunity for people to solve real business Problems by perhaps trying to abstract away you know all of those various implementations and then building uh um better abstractions that are perhaps business or application specific to help companies and businesses solve real business problems yeah I remember it's a great great definition I remember not to date myself but back in the old days you know IBM had its proprietary Network operating system so the deck for the mini computer vintage deck net and sna respectively um but tcpip came out of the OSI the open systems interconnect and remember ethernet beat token ring out so not to get all nerdy for all the young kids out there look just look up token ring you'll see if I never heard of it it's IBM's you know a connection for the internet at the layer two is Amazon the ethernet right so if TCP could be the kubernetes and containers abstraction that made the industry completely change at that point in history so at every major inflection point where there's been serious industry change and wealth creation and business value there's been an abstraction Yes somewhere yes what's your reaction to that I think um this is um I think a saying that's been heard many times in this industry and I forgot who originated it but um I think the saying goes like there's no problem that can't be solved with another layer of indirection right and we've seen this over and over and over again where Amazon and its peers have inserted this layer that has simplified you know Computing and infrastructure management and I believe this trend is going to continue right the next set of problems are going to be solved with these insertions of additional abstraction layers I think that that's really a yeah it's going to continue it's interesting just when I wrote another post today on LinkedIn called the Silicon Wars AMD stock is down arm has been on the rise we've been reporting for many years now that arm's going to be huge it has become true if you look at the success of the infrastructure as a service layer across the clouds Azure AWS Amazon's clearly way ahead of everybody the stuff that they're doing with the Silicon and the physics and the atoms the pro you know this is where the Innovation they're going so deep and so strong at is the more that they get that gets gone they have more performance so if you're an app developer wouldn't you want the best performance and you'd want to have the best abstraction layer that gives you the most ability to do infrastructures code or infrastructure for configuration for provisioning for managing services and you're seeing that today with service meshes a lot of action going on in the service mesh area in this community of kubecon which we'll be covering so that brings up the whole what's next you guys just announced our lawn at argocon which came out of Intuit we've had Mariana Tesla out our supercloud event she's a CTO you know they're all in the cloud so there contributed that project where did Arlon come from what was the origination what's the purpose why our lawn why this announcement yeah so um the the Inception of the project this was the result of um us realizing that problem that we spoke about earlier which is complexity right with all of this these clouds these infrastructure all the variations around and you know compute storage networks and um the proliferation of tools we talked about the ansibles and terraforms and kubernetes itself you can think of that as another tool right we saw a need to solve that complexity problem and especially for people and users who use kubernetes at scale so when you have you know hundreds of clusters thousands of applications thousands of users spread out over many many locations there there needs to be a system that helps simplify that management right so that means fewer tools more expressive ways of describing the state that you want and more consistency and and that's why um you know we built um Arlon and we built it um recognizing that many of these problems or sub problems have already been solved so Arlon doesn't try to reinvent the wheel it instead rests on the shoulders of several Giants right so for example kubernetes is one building block get Ops and Argo CD is another one which provides a very structured way of applying configuration and then we have projects like cluster API and cross-plane which provide apis for describing infrastructure so Arlon takes all of those building blocks and um builds a thin layer which gives users a very expressive way of defining configuration and desired state so that's that's kind of the Inception and what's the benefit of that what does that give what does that give the developer the user in this case the developers the the platform engineer team members the devops engineers they uh get a ways to provision not just infrastructure and clusters but also applications and configurations they get away a system for provisioning configuring deploying and doing life cycle Management in a in a much simpler way okay especially as I said if you're dealing with a large number of applications so it's like an operating fabric if you will yes for them okay so let's get into what that means for up above and below the the abstraction or thin layer below is the infrastructure we talked a lot about what's going on below that yeah above our workloads at the end of the day and I talked to cxos and um I.T folks that are now devops Engineers they care about the workloads and they want the infrastructure's code to work they want to spend their time getting in the weeds figuring out what happened when someone made a push that that happened or something happened they need observability and they need to to know that it's working that's right and as my workloads running if effectively so how do you guys look at the workload side because now you have multiple workloads on these fabric right so workloads so kubernetes has defined kind of a standard way to describe workloads and you can you know tell kubernetes I want to run this container this particular way or you can use other projects that are in the kubernetes cloud native ecosystem like k-native where you can express your application in more at a higher level right but what's also happening is in addition to the workloads devops and platform engineering teams they need to very often deploy the applications with the Clusters themselves clusters are becoming this commodity it's it's becoming this um host for the application and it kind of comes bundled with it in many cases it's like an appliance right so devops teams have to provision clusters at a really incredible rate and they need to tear them down clusters are becoming more extremely like an ec2 instance spin up a cluster we've heard people used words like that that's right and before Arlon you kind of had to do all of that using a different set of tools as I explained so with our own you can kind of express everything together you can say I want a cluster with a health monitoring stack and a logging stack and this Ingress controller and I want these applications and these security policies you can describe all of that using something we call the profile and then you can stamp out your app your applications and your clusters and manage them in a very essentially standard that creates a mechanism it's standardized declarative kind of configurations and it's like a Playbook you just deploy it now what's this between say a script like I have scripts I can just automate Scripts or yes this is where that um declarative API and um infrastructures configuration comes in right because scripts yes you can automate scripts but the order in which they run matters right they can break things can break in the middle and um and sometimes you need to debug them whereas the declarative way is much more expressive and Powerful you just tell the system what you want and then the system kind of uh figures it out and there are these things called controllers which will in the background reconcile all the state to converge towards your desire to say it's a much more powerful expressive and reliable way of getting things done so infrastructure as configuration is built kind of on it's a superset of infrastructures code because different Evolution you need Edge restaurant's code but then you can configure The Code by just saying do it you're basically declaring and saying go go do that that's right okay so all right so Cloud native at scale take me through your vision of what that means someone says hey what is cloud native at scale mean what's success look like how does it roll out in the future as you that future next couple years I mean people are now starting to figure out okay it's not as easy as it sounds kubernetes has value we're going to hear this year kubecon a lot of this what is cloud native at scale mean yeah there are different interpretations but if you ask me when people think of scale they think of a large number of deployments right geographies many you know supporting thousands or tens or millions of users there's that aspect to scale there's also um an equally important aspect of scale which is also something that we try to address with Arlon and that is just complexity for the people operating this or configuring this right so in order to describe that desired State and in order to perform things like maybe upgrades or updates on a very large scale you want the humans behind that to be able to express and direct the system to do that in in relatively simple terms right and so we want uh the tools and the abstractions and the mechanisms available to the user to be as powerful but as simple as possible so there's I think there's going to be a number and there have been a number of cncf and Cloud native projects that are trying to attack that complexity problem as well and Arlon kind of Falls in in that category okay so I'll put you on the spot where I've got kubecon coming up and obviously this will be shipping this seg series out before what do you expect to see at kubecon issue it's the big story this year what's the what's the most important thing happening is it in the open source community and also within a lot of the the people jockeying for leadership I know there's a lot of projects and still there's some white space on the overall systems map about the different areas get runtime and observability in all these different areas what's the where's the action where's the smoke where's the fire where's the piece where's the tension yeah so uh I think uh one thing that has been happening over the past couple of coupons and I expect to continue and and that is uh the the word on the street is kubernetes getting boring right which is good right or I mean simple well um well maybe yeah invisible no drama right so so the rate of change of the kubernetes features and and all that has slowed but in a positive way um but um there's still a general sentiment and feeling that there's just too much stuff if you look at a stack necessary for uh hosting applications based on kubernetes they're just still too many moving Parts too many uh components right too much complexity I go I keep going back to the complexity problem so I expect kubecon and all the vendors and the players and the startups and the people there to continue to focus on that complexity problem and introduce a further simplifications uh to to the stack yeah Vic you've had a storied career VMware over decades with them uh obviously 12 years for the 14 years or something like that big number co-founder here platform I think it's been around for a while at this game uh we man we'll talk about openstack that project you we interviewed at one of their events so openstack was the beginning of that this new Revolution I remember the early days was it wasn't supposed to be an alternative to Amazon but it was a way to do more cloud cloud native I think we had a Colorado team at that time I mean it's a joke we you know about about the dream it's happening now now at platform nine you guys have been doing this for a while what's the what are you most excited about as the Chief Architect what did you guys double down on what did you guys pivot from or two did you do any pivots did you extend out certain areas because you guys are in a good position right now a lot of DNA in Cloud native um what are you most excited about and what is platform nine bring to the table for customers and for people in the industry watching this yeah so I think our mission really hasn't changed over the years right it's been always about taking complex open source software because open source software it's powerful it solves new problems you know every year and you have new things coming out all the time right openstack was an example within kubernetes took the World by storm but there's always that complexity of you know just configuring it deploying it running it operating it and our mission has always been that we will take all that complexity and just make it you know easy for users to consume regardless of the technology right so the successor to kubernetes you know I don't have a crystal ball but you know you have some indications that people are coming up of new and simpler ways of running applications there are many projects around there who knows what's coming uh next year or the year after that but platform will a Platform 9 will be there and we will you know take the Innovations from the the community we will contribute our own Innovations and make all of those things uh very consumable to customers simpler faster cheaper always a good business model technically to make that happen yeah I think the reigning in the chaos is key you know now we have now visibility into the scale final question before we depart you know this segment um what is that scale how many clusters do you see that would be a high a watermark for an at scale conversation around an Enterprise um is it workloads we're looking at or or clusters how would you yeah how would you describe that and when people try to squint through and evaluate what's a scale what's the at scale kind of threshold yeah and the number of clusters doesn't tell the whole story because clusters can be small in terms of the number of nodes or they can be large but roughly speaking when we say you know large-scale cluster deployments we're talking about um maybe a hundreds uh two thousands yeah and final final question what's the role of the hyperscalers you've got AWS continuing to do well but they got their core I asked they got a pass they're not too too much putting assess out there they have some SAS apps but mostly it's the ecosystem they have marketplaces doing over two billion dollars billions of transactions a year um and and it's just like just sitting there it has really they're now innovating on it but that's going to change ecosystems what's the role the cloud play and the cloud native at scale the the hyperscale yeah Abus Azure Google you mean from a business they have their own interests that you know that they're uh they will keep catering to they they will continue to find ways to lock their users into their ecosystem of uh services and and apis um so I don't think that's going to change right they're just going to keep well they got great uh performance I mean from a from a hardware standpoint yes that's going to be key right yes I think the uh the move from x86 being the dominant away and platform to run workloads is changing right that that that and I think the the hyperscalers really want to be in the game in terms of you know the the new risk and arm ecosystems and platforms yeah that joking aside Paul maritz when he was the CEO of VMware when he took over once said I remember our first year doing the cube the cloud is one big distributed computer it's it's hardware and you've got software and you got middleware and uh he kind of over these kind of tongue-in-cheek but really you're talking about large compute and sets of services that is essentially a distributed computer yes exactly it's we're back in the same game Vic thank you for coming on the segment appreciate your time this is uh Cloud native at scale special presentation with platform nine really unpacking super cloud rlon open source and how to run large-scale applications uh on the cloud cloud native philadelph4 developers and John Furrier with the cube thanks for watching and we'll stay tuned for another great segment coming right up foreign [Music]

(bright upbeat music) >> Hello and welcome to theCUBE's coverage of International Women's Day. I'm your host, John Furrier here in Palo Alto, California Studio and remoting is a great guest CUBE alumni, co-founder, technical co-founder and she's also the VP of Product at Platform9 Systems. It's a company pioneering Kubernetes infrastructure, been doing it for a long, long time. Madhura Maskasky, thanks for coming on theCUBE. Appreciate you. Thanks for coming on. >> Thank you for having me. Always exciting. >> So I always... I love interviewing you for many reasons. One, you're super smart, but also you're a co-founder, a technical co-founder, so entrepreneur, VP of product. It's hard to do startups. (John laughs) Okay, so everyone who started a company knows how hard it is. It really is and the rewarding too when you're successful. So I want to get your thoughts on what's it like being an entrepreneur, women in tech, some things you've done along the way. Let's get started. How did you get into your career in tech and what made you want to start a company? >> Yeah, so , you know, I got into tech long, long before I decided to start a company. And back when I got in tech it was very clear to me as a direction for my career that I'm never going to start a business. I was very explicit about that because my father was an entrepreneur and I'd seen how rough the journey can be. And then my brother was also and is an entrepreneur. And I think with both of them I'd seen the ups and downs and I had decided to myself and shared with my family that I really want a very well-structured sort of job at a large company type of path for my career. I think the tech path, tech was interesting to me, not because I was interested in programming, et cetera at that time, to be honest. When I picked computer science as a major for myself, it was because most of what you would consider, I guess most of the cool students were picking that as a major, let's just say that. And it sounded very interesting and cool. A lot of people were doing it and that was sort of the top, top choice for people and I decided to follow along. But I did discover after I picked computer science as my major, I remember when I started learning C++ the first time when I got exposure to it, it was just like a light bulb clicking in my head. I just absolutely loved the language, the lower level nature, the power of it, and what you can do with it, the algorithms. So I think it ended up being a really good fit for me. >> Yeah, so it clicked for you. You tried it, it was all the cool kids were doing it. I mean, I can relate, I did the same thing. Next big thing is computer science, you got to be in there, got to be smart. And then you get hooked on it. >> Yeah, exactly. >> What was the next level? Did you find any blockers in your way? Obviously male dominated, it must have been a lot of... How many females were in your class? What was the ratio at that time? >> Yeah, so the ratio was was pretty, pretty, I would say bleak when it comes to women to men. I think computer science at that time was still probably better compared to some of the other majors like mechanical engineering where I remember I had one friend, she was the single girl in an entire class of about at least 120, 130 students or so. So ratio was better for us. I think there were maybe 20, 25 girls in our class. It was a large class and maybe the number of men were maybe three X or four X number of women. So relatively better. Yeah. >> How about the job when you got into the structured big company? How did that go? >> Yeah, so, you know, I think that was a pretty smooth path I would say after, you know, you graduated from undergrad to grad school and then when I got into Oracle first and VMware, I think both companies had the ratios were still, you know, pretty off. And I think they still are to a very large extent in this industry, but I think this industry in my experience does a fantastic job of, you know, bringing everybody and kind of embracing them and treating them at the same level. That was definitely my experience. And so that makes it very easy for self-confidence, for setting up a path for yourself to thrive. So that was it. >> Okay, so you got an undergraduate degree, okay, in computer science and a master's from Stanford in databases and distributed systems. >> That's right. >> So two degrees. Was that part of your pathway or you just decided, "I want to go right into school?" Did it go right after each other? How did that work out? >> Yeah, so when I went into school, undergrad there was no special major and I didn't quite know if I liked a particular subject or set of subjects or not. Even through grad school, first year it wasn't clear to me, but I think in second year I did start realizing that in general I was a fan of backend systems. I was never a front-end person. The backend distributed systems really were of interest to me because there's a lot of complex problems to solve, and especially databases and large scale distributed systems design in the context of database systems, you know, really started becoming a topic of interest for me. And I think luckily enough at Stanford there were just fantastic professors like Mendel Rosenblum who offered operating system class there, then started VMware and later on I was able to join the company and I took his class while at school and it was one of the most fantastic classes I've ever taken. So they really had and probably I think still do a fantastic curriculum when it comes to distributor systems. And I think that probably helped stoke that interest. >> How do you talk to the younger girls out there in elementary school and through? What's the advice as they start to get into computer science, which is changing and still evolving? There's backend, there's front-end, there's AI, there's data science, there's no code, low code, there's cloud. What's your advice when they say what's the playbook? >> Yeah, so I think two things I always say, and I share this with anybody who's looking to get into computer science or engineering for that matter, right? I think one is that it's, you know, it's important to not worry about what that end specialization's going to be, whether it's AI or databases or backend or front-end. It does naturally evolve and you lend yourself to a path where you will understand, you know, which systems, which aspect you like better. But it's very critical to start with getting the fundamentals well, right? Meaning all of the key coursework around algorithm, systems design, architecture, networking, operating system. I think it is just so crucial to understand those well, even though at times you make question is this ever going to be relevant and useful to me later on in my career? It really does end up helping in ways beyond, you know, you can describe. It makes you a much better engineer. So I think that is the most important aspect of, you know, I would think any engineering stream, but definitely true for computer science. Because there's also been a trend more recently, I think, which I'm not a big fan of, of sort of limited scoped learning, which is you decide early on that you're going to be, let's say a front-end engineer, which is fine, you know. Understanding that is great, but if you... I don't think is ideal to let that limit the scope of your learning when you are an undergrad phrase or grad school. Because later on it comes back to sort of bite you in terms of you not being able to completely understand how the systems work. >> It's a systems kind of thinking. You got to have that mindset of, especially now with cloud, you got distributed systems paradigm going to the edge. You got 5G, Mobile World Congress recently happened, you got now all kinds of IOT devices out there, IP of devices at the edge. Distributed computing is only getting more distributed. >> That's right. Yeah, that's exactly right. But the other thing is also happens... That happens in computer science is that the abstraction layers keep raising things up and up and up. Where even if you're operating at a language like Java, which you know, during some of my times of programming there was a period when it was popular, it already abstracts you so far away from the underlying system. So it can become very easier if you're doing, you know, Java script or UI programming that you really have no understanding of what's happening behind the scenes. And I think that can be pretty difficult. >> Yeah. It's easy to lean in and rely too heavily on the abstractions. I want to get your thoughts on blockers. In your career, have you had situations where it's like, "Oh, you're a woman, okay seat at the table, sit on the side." Or maybe people misunderstood your role. How did you deal with that? Did you have any of that? >> Yeah. So, you know, I think... So there's something really kind of personal to me, which I like to share a few times, which I think I believe in pretty strongly. And which is for me, sort of my personal growth began at a very early phase because my dad and he passed away in 2012, but throughout the time when I was growing up, I was his special little girl. And every little thing that I did could be a simple test. You know, not very meaningful but the genuine pride and pleasure that he felt out of me getting great scores in those tests sort of et cetera, and that I could see that in him, and then I wanted to please him. And through him, I think I build that confidence in myself that I am good at things and I can do good. And I think that just set the building blocks for me for the rest of my life, right? So, I believe very strongly that, you know, yes, there are occasions of unfair treatment and et cetera, but for the most part, it comes from within. And if you are able to be a confident person who is kind of leveled and understands and believes in your capabilities, then for the most part, the right things happen around you. So, I believe very strongly in that kind of grounding and in finding a source to get that for yourself. And I think that many women suffer from the biggest challenge, which is not having enough self-confidence. And I've even, you know, with everything that I said, I've myself felt that, experienced that a few times. And then there's a methodical way to get around it. There's processes to, you know, explain to yourself that that's actually not true. That's a fake feeling. So, you know, I think that is the most important aspect for women. >> I love that. Get the confidence. Find the source for the confidence. We've also been hearing about curiosity and building, you mentioned engineering earlier, love that term. Engineering something, like building something. Curiosity, engineering, confidence. This brings me to my next question for you. What do you think the key skills and qualities are needed to succeed in a technical role? And how do you develop to maintain those skills over time? >> Yeah, so I think that it is so critical that you love that technology that you are part of. It is just so important. I mean, I remember as an example, at one point with one of my buddies before we started Platform9, one of my buddies, he's also a fantastic computer scientists from VMware and he loves video games. And so he said, "Hey, why don't we try to, you know, hack up a video game and see if we can take it somewhere?" And so, it sounded cool to me. And then so we started doing things, but you know, something I realized very quickly is that I as a person, I absolutely hate video games. I've never liked them. I don't think that's ever going to change. And so I was miserable. You know, I was trying to understand what's going on, how to build these systems, but I was not enjoying it. So, I'm glad that I decided to not pursue that. So it is just so important that you enjoy whatever aspect of technology that you decide to associate yourself with. I think that takes away 80, 90% of the work. And then I think it's important to inculcate a level of discipline that you are not going to get sort of... You're not going to get jaded or, you know, continue with happy path when doing the same things over and over again, but you're not necessarily challenging yourself, or pushing yourself, or putting yourself in uncomfortable situation. I think a combination of those typically I think works pretty well in any technical career. >> That's a great advice there. I think trying things when you're younger, or even just for play to understand whether you abandon that path is just as important as finding a good path because at least you know that skews the value in favor of the choices. Kind of like math probability. So, great call out there. So I have to ask you the next question, which is, how do you keep up to date given all the changes? You're in the middle of a world where you've seen personal change in the past 10 years from OpenStack to now. Remember those days when I first interviewed you at OpenStack, I think it was 2012 or something like that. Maybe 10 years ago. So much changed. How do you keep up with technologies in your field and resources that you rely on for personal development? >> Yeah, so I think when it comes to, you know, the field and what we are doing for example, I think one of the most important aspect and you know I am product manager and this is something I insist that all the other product managers in our team also do, is that you have to spend 50% of your time talking to prospects, customers, leads, and through those conversations they do a huge favor to you in that they make you aware of the other things that they're keeping an eye on as long as you're doing the right job of asking the right questions and not just, you know, listening in. So I think that to me ends up being one of the biggest sources where you get tidbits of information, new things, et cetera, and then you pursue. To me, that has worked to be a very effective source. And then the second is, you know, reading and keeping up with all of the publications. You guys, you know, create a lot of great material, you interview a lot of people, making sure you are watching those for us you know, and see there's a ton of activities, new projects keeps coming along every few months. So keeping up with that, listening to podcasts around those topics, all of that helps. But I think the first one I think goes in a big way in terms of being aware of what matters to your customers. >> Awesome. Let me ask you a question. What's the most rewarding aspect of your job right now? >> So, I think there are many. So I think I love... I've come to realize that I love, you know, the high that you get out of being an entrepreneur independent of, you know, there's... In terms of success and failure, there's always ups and downs as an entrepreneur, right? But there is this... There's something really alluring about being able to, you know, define, you know, path of your products and in a way that can potentially impact, you know, a number of companies that'll consume your products, employees that work with you. So that is, I think to me, always been the most satisfying path, is what kept me going. I think that is probably first and foremost. And then the projects. You know, there's always new exciting things that we are working on. Even just today, there are certain projects we are working on that I'm super excited about. So I think it's those two things. >> So now we didn't get into how you started. You said you didn't want to do a startup and you got the big company. Your dad, your brother were entrepreneurs. How did you get into it? >> Yeah, so, you know, it was kind of surprising to me as well, but I think I reached a point of VMware after spending about eight years or so where I definitely packed hold and I could have pushed myself by switching to a completely different company or a different organization within VMware. And I was trying all of those paths, interviewed at different companies, et cetera, but nothing felt different enough. And then I think I was very, very fortunate in that my co-founders, Sirish Raghuram, Roopak Parikh, you know, Bich, you've met them, they were kind of all at the same journey in their careers independently at the same time. And so we would all eat lunch together at VMware 'cause we were on the same team and then we just started brainstorming on different ideas during lunchtime. And that's kind of how... And we did that almost for a year. So by the time that the year long period went by, at the end it felt like the most logical, natural next step to leave our job and to, you know, to start off something together. But I think I wouldn't have done that had it not been for my co-founders. >> So you had comfort with the team as you knew each other at VMware, but you were kind of a little early, (laughing) you had a vision. It's kind of playing out now. How do you feel right now as the wave is hitting? Distributed computing, microservices, Kubernetes, I mean, stuff you guys did and were doing. I mean, it didn't play out exactly, but directionally you were right on the line there. How do you feel? >> Yeah. You know, I think that's kind of the challenge and the fun part with the startup journey, right? Which is you can never predict how things are going to go. When we kicked off we thought that OpenStack is going to really take over infrastructure management space and things kind of went differently, but things are going that way now with Kubernetes and distributed infrastructure. And so I think it's been interesting and in every path that you take that does end up not being successful teaches you so much more, right? So I think it's been a very interesting journey. >> Yeah, and I think the cloud, certainly AWS hit that growth right at 2013 through '17, kind of sucked all the oxygen out. But now as it reverts back to this abstraction layer essentially makes things look like private clouds, but they're just essentially DevOps. It's cloud operations, kind of the same thing. >> Yeah, absolutely. And then with the edge things are becoming way more distributed where having a single large cloud provider is becoming even less relevant in that space and having kind of the central SaaS based management model, which is what we pioneered, like you said, we were ahead of the game at that time, is becoming sort of the most obvious choice now. >> Now you look back at your role at Stanford, distributed systems, again, they have world class program there, neural networks, you name it. It's really, really awesome. As well as Cal Berkeley, there was in debates with each other, who's better? But that's a separate interview. Now you got the edge, what are some of the distributed computing challenges right now with now the distributed edge coming online, industrial 5G, data? What do you see as some of the key areas to solve from a problem statement standpoint with edge and as cloud goes on-premises to essentially data center at the edge, apps coming over the top AI enabled. What's your take on that? >> Yeah, so I think... And there's different flavors of edge and the one that we focus on is, you know, what we call thick edge, which is you have this problem of managing thousands of as we call it micro data centers, rather than managing maybe few tens or hundreds of large data centers where the problem just completely shifts on its head, right? And I think it is still an unsolved problem today where whether you are a retailer or a telecommunications vendor, et cetera, managing your footprints of tens of thousands of stores as a retailer is solved in a very archaic way today because the tool set, the traditional management tooling that's designed to manage, let's say your data centers is not quite, you know, it gets retrofitted to manage these environments and it's kind of (indistinct), you know, round hole kind of situation. So I think the top most challenges are being able to manage this large footprint of micro data centers in the most effective way, right? Where you have latency solved, you have the issue of a small footprint of resources at thousands of locations, and how do you fit in your containerized or virtualized or other workloads in the most effective way? To have that solved, you know, you need to have the security aspects around these environments. So there's a number of challenges that kind of go hand-in-hand, like what is the most effective storage which, you know, can still be deployed in that compact environment? And then cost becomes a related point. >> Costs are huge 'cause if you move data, you're going to have cost. If you move compute, it's not as much. If you have an operating system concept, is the data and state or stateless? These are huge problems. This is an operating system, don't you think? >> Yeah, yeah, absolutely. It's a distributed operating system where it's multiple layers, you know, of ways of solving that problem just in the context of data like you said having an intermediate caching layer so that you know, you still do just in time processing at those edge locations and then send some data back and that's where you can incorporate some AI or other technologies, et cetera. So, you know, just data itself is a multi-layer problem there. >> Well, it's great to have you on this program. Advice final question for you, for the folks watching technical degrees, most people are finding out in elementary school, in middle school, a lot more robotics programs, a lot more tech exposure, you know, not just in Silicon Valley, but all around, you're starting to see that. What's your advice for young girls and people who are getting either coming into the workforce re-skilled as they get enter, it's easy to enter now as they stay in and how do they stay in? What's your advice? >> Yeah, so, you know, I think it's the same goal. I have two little daughters and it's the same principle I try to follow with them, which is I want to give them as much exposure as possible without me having any predefined ideas about what you know, they should pursue. But it's I think that exposure that you need to find for yourself one way or the other, because you really never know. Like, you know, my husband landed into computer science through a very, very meandering path, and then he discovered later in his career that it's the absolute calling for him. It's something he's very good at, right? But so... You know, it's... You know, the reason why he thinks he didn't pick that path early is because he didn't quite have that exposure. So it's that exposure to various things, even things you think that you may not be interested in is the most important aspect. And then things just naturally lend themselves. >> Find your calling, superpower, strengths. Know what you don't want to do. (John chuckles) >> Yeah, exactly. >> Great advice. Thank you so much for coming on and contributing to our program for International Women's Day. Great to see you in this context. We'll see you on theCUBE. We'll talk more about Platform9 when we go KubeCon or some other time. But thank you for sharing your personal perspective and experiences for our audience. Thank you. >> Fantastic. Thanks for having me, John. Always great. >> This is theCUBE's coverage of International Women's Day, I'm John Furrier. We're talking to the leaders in the industry, from developers to the boardroom and everything in between and getting the stories out there making an impact. Thanks for watching. (bright upbeat music)