(upbeat music) >> Welcome back. Day two of theCUBE's coverage of re:MARS in Las Vegas. Amazon re:MARS, it's part of the Re Series they call it at Amazon. re:Invent is their big show, re:Inforce is a security show, re:MARS is the new emerging machine learning automation, robotics, and space. The confluence of machine learning powering a new industrial age and inflection point. I'm John Furrier, host of theCUBE. We're here to break it down for another wall to wall coverage. We've got a great guest here, CUBE alumni from our AWS startup showcase, Krishna Gade, founder and CEO of fiddler.ai. Welcome back to theCUBE. Good to see you. >> Great to see you, John. >> In person. We did the remote one before. >> Absolutely, great to be here, and I always love to be part of these interviews and love to talk more about what we're doing. >> Well, you guys have a lot of good street cred, a lot of good word of mouth around the quality of your product, the work you're doing. I know a lot of folks that I admire and trust in the AI machine learning area say great things about you. A lot going on, you guys are growing companies. So you're kind of like a startup on a rocket ship, getting ready to go, pun intended here at the space event. What's going on with you guys? You're here. Machine learning is the centerpiece of it. Swami gave the keynote here at day two and it really is an inflection point. Machine learning is now ready, it's scaling, and some of the examples that they were showing with the workloads and the data sets that they're tapping into, you know, you've got CodeWhisperer, which they announced, you've got trust and bias now being addressed, we're hitting a level, a new level in ML, ML operations, ML modeling, ML workloads for developers. >> Yep, yep, absolutely. You know, I think machine learning now has become an operational software, right? Like you know a lot of companies are investing millions and billions of dollars and creating teams to operationalize machine learning based products. And that's the exciting part. I think the thing that that is very exciting for us is like we are helping those teams to observe how those machine learning applications are working so that they can build trust into it. Because I believe as Swami was alluding to this today, without actually building trust into AI, it's really hard to actually have your business users use it in their business workflows. And that's where we are excited about bringing their trust and visibility factor into machine learning. >> You know, a lot of us all know what you guys are doing here in the ecosystem of AWS. And now extending here, take a minute to explain what Fiddler is doing for the folks that are in the space, that are in discovery mode, trying to understand who's got what, because like Swami said on stage, it's a full-time job to keep up on all the machine learning activities and tool sets and platforms. Take a minute to explain what Fiddler's doing, then we can get into some, some good questions. >> Absolutely. As the enterprise is taking on operationalization of machine learning models, one of the key problems that they run into is lack of visibility into how those models perform. You know, for example, let's say if I'm a bank, I'm trying to introduce credit risk scoring models using machine learning. You know, how do I know when my model is rejecting someone's loan? You know, when my model is accepting someone's loan? And why is it doing it? And I think this is basically what makes machine learning a complex thing to implement and operationalize. Without this visibility, you cannot build trust and actually use it in your business. With Fiddler, what we provide is we actually open up this black box and we help our customers to really understand how those models work. You know, for example, how is my model doing? Is it accurately working or not? You know, why is it actually rejecting someone's loan application? We provide these both fine grain as well as coarse grain insights. So our customers can actually deploy machine learning in a safe and trustworthy manner. >> Who is your customer? Who you're targeting? What persona is it, the data engineer, is it data science, is it the CSO, is it all the above? >> Yeah, our customer is the data scientist and the machine learning engineer, right? And we usually talk to teams that have a few models running in production, that's basically our sweet spot, where they're trying to look for a single pane of glass to see like what models are running in their production, how they're performing, how they're affecting their business metrics. So we typically engage with like head of data science or head of machine learning that has a few machine learning engineers and data scientists. >> Okay, so those people that are watching, you're into this, you can go check it out. It's good to learn. I want to get your thoughts on some trends that I see emerging, and I want to get your reaction to those. Number one, we're seeing the cloud scale now and integration a big part of things. So the time to value was brought up on stage today, Swami kind of mentioned time to value, showed some benchmark where they got four hours, some other teams were doing eight weeks. Where are we on the progression of value, time to value, and on the scale side. Can you scope that for me? >> I mean, it depends, right? You know, depending upon the company. So for example, when we work with banks, for them to time to operationalize a model can take months actually, because of all the regulatory procedures that they have to go through. You know, they have to get the models reviewed by model validators, model risk management teams, and then they audit those models, they have to then ship those models and constantly monitor them. So it's a very long process for them. And even for non-regulated sectors, if you do not have the right tools and processes in place, operationalizing machine learning models can take a long time. You know, with tools like Fiddler, what we are enabling is we are basically compressing that life cycle. We are helping them automate like model monitoring and explainability so that they can actually ship models more faster. Like you get like velocity in terms of shipping models. For example, one of the growing fintech companies that started with us last year started with six models in production, now they're running about 36 models in production. So it's within a year, they were able to like grow like 10x. So that is basically what we are trying to do. >> At other things, we at re:MARS, so first of all, you got a great product and a lot of markets that grow onto, but here you got space. I mean, anyone who's coming out of college or university PhD program, and if they're into aero, they're going to be here, right? This is where they are. Now you have a new core companies with machine learning, not just the engineering that you see in the space or aerospace area, you have a new engineering. Now I go back to the old days where my parents, there was Fortran, you used Fortran was Lingua Franca to manage the equipment. Little throwback to the old school. But now machine learning is companion, first class citizen, to the hardware. And in fact, and some will say more important. >> Yep, I mean, machine learning model is the new software artifact. It is going into production in a big way. And I think it has two different things that compare to traditional software. Number one, unlike traditional software, it's a black box. You cannot read up a machine learning model score and see why it's making those predictions. Number two, it's a stochastic entity. What that means is it's predictive power can wane over time. So it needs to be constantly monitored and then constantly refreshed so that it's actually working in tech. So those are the two main things you need to take care. And if you can do that, then machine learning can give you a huge amount of ROI. >> There is some practitioner kind of like craft to it. >> Correct. >> As you said, you got to know when to refresh, what data sets to bring in, which to stay away from, certainly when you get to the bias, but I'll get to that in a second. My next question is really along the lines of software. So if you believe that open source will dominate the software business, which I do, I mean, most people won't argue. I think you would agree with that, right? Open source is driving everything. If everything's open source, where's the differentiation coming from? So if I'm a startup entrepreneur or I'm a project manager working on the next Artemis mission, I got to open source. Okay, there's definitely security issues here. I don't want to talk about shift left right now, but like, okay, open source is everything. Where's the differentiation, where do I have the proprietary edge? >> It's a great question, right? So I used to work in tech companies before Fiddler. You know, when I used to work at Facebook, we would build everything in house. We would not even use a lot of open source software. So there are companies like that that build everything in house. And then I also worked at companies like Twitter and Pinterest, which are actually used a lot of open source, right? So now, like the thing is, it depends on the maturity of the organization. So if you're a Facebook or a Google, you can build a lot of things in house. Then if you're like a modern tech company, you would probably leverage open source, but there are lots of other companies in the world that still don't have the talent pool to actually build, take things from open source and productionize it. And that's where the opportunity for startups comes in so that we can commercialize these things, create a great enterprise experience, so actually operationalize things for them so that they don't have to do it in house for them. And that's the advantage working with startups. >> I don't want to get all operating systems with you on theory here on the stage here, but I will have to ask you the next question, which I totally agree with you, by the way, that's the way to go. There's not a lot of people out there that are peaked. And that's just statistical and it'll get better. Data engineering is really narrow. That is like the SRE of data. That's a new role emerging. Okay, all the things are happening. So if open source is there, integration is a huge deal. And you start to see the rise of a lot of MSPs, managed service providers. I run Kubernetes clusters, I do this, that, and the other thing. So what's your reaction to the growth of the integration side of the business and this role of new services coming from third parties? >> Yeah, absolutely. I think one of the big challenges for a chief data officer or someone like a CTO is how do they devise this infrastructure architecture and with components, either homegrown components or open source components or some vendor components, and how do they integrate? You know, when I used to run data engineering at Pinterest, we had to devise a data architecture combining all of these things and create something that actually flows very nicely, right? >> If you didn't do it right, it would break. >> Absolutely. And this is why it's important for us, like at Fiddler, to really make sure that Fiddler can integrate to all varies of ML platforms. Today, a lot of our customers use machine learning, build machine learning models on SageMaker. So Fiddler nicely integrate with SageMaker so that data, they get a seamless experience to monitor their models. >> Yeah, I mean, this might not be the right words for it, but I think data engineering as a service is really what I see you guys doing, as well other things, you're providing all that. >> And ML engineering as a service. >> ML engineering as a- Well it's hard. I mean, it's like the hard stuff. >> Yeah, yeah. >> Hear, hear. But that has to enable. So you as a business entrepreneur, you have to create a multiple of value proposition to your customers. What's your vision on that? What is that value? It has to be a multiple, at least 5 to 10. >> I mean, the value is simple, right? You know, if you have to operationize machine learning, you need visibility into how these things work. You know, if you're CTO or like chief data officer is asking how is my model working and how is it affecting my business? You need to be able to show them a dashboard, how it's working, right? And so like a data scientist today struggles to do this. They have to manually generate a report, manually do this analysis. What Fiddler is doing them is basically reducing their work so that they can automate these things and they can still focus on the core aspect of model building and data preparation and this boring aspect of monitoring the model and creating reports around the models is automated for them. >> Yeah, you guys got a great business. I think it's a lot of great future there and it's only going to get bigger. Again, the TAM's going to expand as the growth rising tide comes in. I want to ask you on while we're on that topic of rising tides, Dave Malik and I, since re:Invent last year have been kind of kicked down around this term that we made up called supercloud. And supercloud was a word that came out of these clouds that were not Amazon hyperscalers. So Snowflake, Buildman Sachs, Capital One, you name it, they're building massive proprietary value on top of the CapEx of Amazon. Jerry Chen at Greylock calls it castles in the cloud. You can create these moats. >> Yeah, right. >> So this is a phenomenon, right? And you land on one, and then you go to the others. So the strategies, everyone goes to Amazon first, and then hits Azure and GCP. That then creates this kind of multicloud so, okay, so super cloud's kind of happening, it's a thing. Charles Fitzgerald will disagree, he's a platformer, he says he's against the term. I get why, but he's off base a little. We can't wait to debate him on that. So superclouds are happening, but now what do I do about multicloud, because now I understand multicloud, I have this on that cloud, integrating across clouds is a very difficult thing. >> Krishna: Right, right, right. >> If I'm Snowflake or whatever, hey, I'll go to Azure, more TAM expansion, more market. But are people actually working together? Are we there yet? Where it's like, okay, I'm going to re-operationalize this code base over here. >> I mean, the reality of it, enterprise wants optionality, right? I think they don't want to be locked in into one particular cloud vendor on one particular software. And therefore you actually have in a situation where you have a multicloud scenario where they want to have some workloads in Amazon, some workloads in Azure. And this is an opportunity for startups like us because we are cloud agnostic. We can monitor models wherever you have. So this is where a lot of our customers, they have some of their models are running in their data centers and some of their models running in Amazon. And so we can provide a universal single pan of glass, right? So we can basically connect all of those data and actually showcase. I think this is an opportunity for startups to combine the data streams come from various different clouds and give them a single pain of experience. That way, the sort of the where is your data, where are my models running, which cloud are there, is all abstracted out from the customer. Because at the end of the day, enterprises will want optionality. And we are in this multicloud. >> Yeah, I mean, this reminds me of the interoperability days back when I was growing into the business. Everything was interoperability and OSI and the standards came out, but what's your opinion on openness, okay? There's a kneejerk reaction right now in the market to go silo on your data for governance or whatever reasons, but yet machine learning gurus and experts will say, "Hey, you want to horizon horizontal scalability and have the best machine learning models, you've got to have access to data and fast in real time or near real time." And the antithesis is siloing. >> Krishna: Right, right, right. >> So what's the solution? Customers control the data plane and have a control plane that's... What do customers do? It's a big challenge. >> Yeah, absolutely. I think there are multiple different architectures of ML, right, you know? We've seen like where vendors like us used to deploy completely on-prem, right? And they still do it, we still do it in some customers. And then you had this managed cloud experience where you just abstract out the entire operations from the customer. And then now you have this hybrid experience where you split the control plane and data plane. So you preserve the privacy of the customer from the data perspective, but you still control the infrastructure, right? I don't think there's a right answer. It depends on the product that you're trying to solve. You know, Databricks is able to solve this control plane, data plane split really well. I've seen some other tools that have not done this really well. So I think it all depends upon- >> What about Snowflake? I think they a- >> Sorry, correct. They have a managed cloud service, right? So predominantly that's their business. So I think it all depends on what is your go to market? You know, which customers you're talking to? You know, what's your product architecture look like? You know, from Fiddler's perspective today, we actually have chosen, we either go completely on-prem or we basically provide a managed cloud service and that's actually simpler for us instead of splitting- >> John: So it's customer choice. >> Exactly. >> That's your position. >> Exactly. >> Whoever you want to use Fiddler, go on-prem, no problem, or cloud. >> Correct, or cloud, yeah. >> You'll deploy and you'll work across whatever observability space you want to. >> That's right, that's right. >> Okay, yeah. So that's the big challenge, all right. What's the big observation from your standpoint? You've been on the hyperscaler side, your journey, Facebook, Pinterest, so back then you built everything, because no one else had software for you, but now everybody wants to be a hyperscaler, but there's a huge CapEx advantage. What should someone do? If you're a big enterprise, obviously I could be a big insurance, I could be financial services, oil and gas, whatever vertical, I want a supercloud, what do I do? >> I think like the biggest advantage enterprise today have is they have a plethora of tools. You know, when I used to work on machine learning way back in Microsoft on Bing Search, we had to build everything. You know, from like training platforms, deployment platforms, experimentation platforms. You know, how do we monitor those models? You know, everything has to be homegrown, right? A lot of open source also did not exist at the time. Today, the enterprise has this advantage, they're sitting on this gold mine of tools. You know, obviously there's probably a little bit of tool fatigue as well. You know, which tools to select? >> There's plenty of tools available. >> Exactly, right? And then there's like services available for you. So now you need to make like smarter choices to cobble together this, to create like a workflow for your engineers. And you can really get started quite fast, and actually get on par with some of these modern tech companies. And that is the advantage that a lot of enterprises see. >> If you were going to be the CTO or CEO of a big transformation, knowing what you know, 'cause you just brought up the killer point about why it's such a great time right now, you got platform as a service and the tooling essentially reset everything. So if you're going to throw everything out and start fresh, you're basically brewing the system architecture. It's a complete reset. That's doable. How fast do you think you could do that for say a large enterprise? >> See, I think if you set aside the organization processes and whatever kind of comes in the friction, from a technology perspective, it's pretty fast, right? You can devise a data architecture today with like tools like Kafka, Snowflake and Redshift, and you can actually devise a data architecture very clearly right from day one and actually implement it at scale. And then once you have accumulated enough data and you can extract more value from it, you can go and implement your MLOps workflow as well on top of it. And I think this is where tools like Fiddler can help as well. So I would start with looking at data, do we have centralization of data? Do we have like governance around data? Do we have analytics around data? And then kind of get into machine learning operations. >> Krishna, always great to have you on theCUBE. You're great masterclass guest. Obviously great success in your company. Been there, done that, and doing it again. I got to ask you, since you just brought that up about the whole reset, what is the superhero persona right now? Because it used to be the full stack developer, you know? And then it's like, then I call them, it didn't go over very well in theCUBE, the half stack developer, because nobody wants to be a half stack anything, a half sounds bad, worse than full. But cloud is essentially half a stack. I mean, you got infrastructure, you got tools. Now you're talking about a persona that's going to reset, look at tools, make selections, build an architecture, build an operating environment, distributed computing operating. Who is that person? What's that persona look like? >> I mean, I think the superhero persona today is ML engineering. I'm usually surprised how much is put on an ML engineer to do actually these days. You know, when I entered the industry as a software engineer, I had three or four things in my job to do, I write code, I test it, I deploy it, I'm done. Like today as an ML engineer, I need to worry about my data. How do I collect it? I need to clean the data, I need to train my models, I need to experiment with what it is, and to deploy them, I need to make sure that they're working once they're deployed. >> Now you got to do all the DevOps behind it. >> And all the DevOps behind it. And so I'm like working halftime as a data scientist, halftime as a software engineer, halftime as like a DevOps cloud. >> Cloud architect. >> It's like a heroic job. And I think this is why this is why obviously these jobs are like now really hard jobs and people want to be more and more machine learning >> And they get paid. >> engineering. >> Commensurate with the- >> And they're paid commensurately as well. And this is where I think an opportunity for tools like Fiddler exists as well because we can help those ML engineers do their jobs better. >> Thanks for coming on theCUBE. Great to see you. We're here at re:MARS. And great to see you again. And congratulations on being on the AWS startup showcase that we're in year two, episode four, coming up. We'll have to have you back on. Krishna, great to see you. Thanks for coming on. Okay, This is theCUBE's coverage here at re:MARS. I'm John Furrier, bringing all the signal from all the noise here. Not a lot of noise at this event, it's very small, very intimate, a little bit different, but all on point with space, machine learning, robotics, the future of industrial. We'll back with more coverage after the short break. >> Man: Thank you John. (upbeat music)

>>on the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Hello and welcome back to the Cubes Live coverage Cube live here in Palo Alto, California, with the Virtual Cube this year because we can't be there in person. I'm your host, John Fairy year. We're kicking off Day two of the three weeks of reinvent a lot of great leadership sessions to review, obviously still buzzing from the Andy Jassy three. Our keynote, which had so many storylines, is really hard to impact. We're gonna dig that into into into that today with Jerry Chan, who has been a Cube alumni since the beginning of our AWS coverage. Going back to 2013, Jerry was wandering the hallways as a um, in between. You were in between vm ware and V C. And then we saw you there. You've been on the Cube every year at reinvent with us. So special commentary from you. Thanks for coming on. >>Hey, John, Thanks for having me and a belated happy birthday as well. If everyone out there John's birthday was yesterday. So and hardest. Howard's working man in technology he spent his entire birthday doing live coverage of Amazon re events. Happy birthday, buddy. >>Well, I love my work. I love doing this. And reinvent is the biggest event of the year because it really is. It's become a bellwether and eso super excited to have you on. We've had great conversations by looking back at our conversations over the Thanksgiving weekend. Jerry, the stuff we were talking about it was very proposed that Jassy is leaning in with this whole messaging around change and horizontal scalability. He didn't really say that, but he was saying you could disrupt in these industries and still use machine learning. This was some of the early conversations we were having on the Cube. Now fast forward, more mainstream than ever before. So big, big part of the theme there. >>Yeah, it z you Amazon reinvent Amazon evolution to your point, right, because it's both reinventing what countries are using with the cloud. But also what Amazon's done is is they're evolving year after year with their services. So they start a simple infrastructure, you know, s three and e c. Two. And now they're building basically a lot of what Andy said you actually deconstructed crm? Ah, lot of stuff they're doing around the call centers, almost going after Salesforce with kind of a deconstructed CRM services, which is super interesting. But the day you know, Amazon announces all those technologies, not to mention the AI stuff, the seminar stuff you have slack and inquired by Salesforce for $27.7 billion. So ah, lot of stuff going on in the cloud world these days, and it's funny part of it, >>you know, it really is interesting. You look up the slack acquisition by, um, by Salesforce. It's interesting, you know, That kind of takes slack out of the play here. I mean, they were doing really well again. Message board service turns into, um, or collaboration software. They hit the mainstream. They have great revenue. Is that going to really change the landscape of the industry for Salesforce? They've got to acquire it. It opens the door up from, or innovation. And it's funny you mention the contact Center because I was pressing Jassy on my exclusive one on one with him. Like they said, Andy, my my daughter and my sons, they don't use the phone. They're not gonna call. What's this? Is it a call center deal? And he goes, No, it's the It's about the contact. So think about that notion of the contact. It's not about the call center. It's the point of contact. Okay, Linked in is with Microsoft. You got slack and Salesforce Contact driven collaboration. Interesting kind of play for Microsoft to use voice and their data. What's your take on that? >>I think it's, um you know, I have this framework. As you know, I talked my friend systems of engagement over systems intelligence and systems record. Right? And so you could argue voice email slack because we're all different systems of engagement, and they sit on top of system of record like CRM customer support ticketing HR. Something like that. Now what sells first did by buying slack is they now own a system engagement, right? Not on Lee is slack. A system engagement for CRM, but also system engagement for E. R. P Service. Now is how you interact with a bunch of applications. And so if you think about sales for strategy in the space, compete against Marcus Soft or serves now or other large AARP's now they own slack of system engagement, that super powerful way to actually compete against rival SAS companies. Because if you own the layer engagement layer, you can now just intermediate what's in the background. Likewise, the context center its own voice. Email, chat messaging, right? You can just inter mediate this stuff in the back, and so they're trying to own the system engagement. And then, likewise, Facebook just bought that company customer a week ago for a billion dollars, which also Omni Channel support because it is chat messaging voice. It's again the system engagement between End User, which could be a customer or could be employees. >>You know, this really gonna make Cit's enterprise has been so much fun over the past 10 years, I gotta say, in the past five, you know, it's been even more fun, has become or the new fun area, you know, And the impact to enterprise has been interesting because and we're talking about just engaging system of record. This is now the new challenge for the enterprise. So I wanna get your thoughts, Jerry, because how you see the Sea, X O's and CSOs and the architects out there trying to reinvent the enterprise. Jassy saying Look and find the truth. Be on the right side of history here. Certainly he's got himself service interest there, but there is a true band eight with Cove it and with digital acceleration for the enterprise to change. Um, given all these new opportunities Thio, revolutionize or disrupt or radically improve, what's the C. C X's do? What's your take on? How do you see that? >>It's increasingly messy for the CXS, and I don't I don't envy them, right? Because back in the day they kind of controlled all the I t spend and kind of they had a standard of what technologies they use in the company. And then along came Amazon in cloud all of sudden, like your developers and Dio Hey, let me swipe my credit card and I'm gonna access to a bunch of a P I s around computing stories. Likewise. Now they could swipe the credit card and you strike for billing, right? There's a whole bunch of services now, so it becomes incumbent upon CSOs. They need Thio new set of management tools, right? So not only just like, um, security tools they need, they need also observe ability, tools, understanding what services are being used by the customers, when and how. And I would say the following John like CSOs is both a challenge for them. But I think if I was a C X, so I'll be pretty excited because now I have a bunch of other weapons and other bunch of services I could offer. My end users, my developers, my employees, my customers and, you know it's exciting for them is not only could they do different things, but they also changed how their business being done. And so I think both interact with their end users. Be a chat like slack or be a phone like a contact center or instagram for your for your for your kids. It's actually a new challenge if I were sick. So it's it's time to build again, you know, I think Cove it has said it is time to build again. You can build >>to kind of take that phrase from the movie Shawshank Redemption. Get busy building or get busy dying. Kinda rephrase it there. And that's kind of the theme I'm seeing here because covert kind of forced people saying, Look, this things like work at home. Who would have thought 100% people would be working at home? Who would have thought that now the workloads gonna change differently? So it's an opportunity to deconstruct or distant intermediate these services. And I think, you know, in all the trends that I've seen over my career, it's been those inflection points where breaking the monolith or breaking the proprietary piece of it has always been an opportunity for for entrepreneur. So you know, and and for companies, whether you're CEO or startup by decomposing and you can come in and create value E I think to me, snowflake going public on the back of Amazon. Basically, this is interesting. I mean, so you don't have to be. You could kill one feature and nail it and go big. >>I think we talked to the past like it's Amazon or Google or Microsoft Gonna win. Everything is winner take all winner take most, and you could argue that it's hard to find oxygen as a start up in a broad platform play. But we think Snowflake and other companies have done and comes like mongo DB, for example, elastic have shown that if you can pick a service or a problem space and either developed like I p. That's super deep or own developer audience. You can actually fight the big guys. The Big Three cloud vendors be Amazon, Google or or market soft in different markets. And I think if you're a startup founder, you should not be afraid of competing with the big cloud vendors because there there are success patterns and how you can win and you know and create a lot of value. So I have found Investor. I'm super excited by that because, you know, I don't think you're gonna find a company takedown Amazon completely because they're just the scale and the network effects is too large. But you can create a lot of value and build Valuable comes like snowflake in and around the Amazon. Google Microsoft Ecosystem. >>Yeah, I want to get your thoughts. You have one portfolio we've covered rock rock set, which does a lot of sequel. Um, one of your investments. Interesting part of the Kino yesterday was Andy Jassy kind of going after Microsoft saying Windows sequel server um, they're targeting that with this new, uh, tool, but, you know, sucks in the database of it is called the Babel Fish for Aurora for post Chris sequel. Um, well, how was your take on that? I mean, obviously Microsoft big. Their enterprise sales tactics are looking like more like Oracle, which he was kind of hinting at and commenting on. But sequel is Lingua Franca for data >>correct. I think we went to, like, kind of a no sequel phase, which was kind of a trendy thing for a while and that no sequel still around, not only sequel like mongo DB Document TV. Kind of that interface still holds true, but your point. The world speaks sequel. All your applications be sequel, right? So if you want backwards, compatibility to your applications speaks equal. If you want your tire installed base of employees that no sequel, we gotta speak sequel. So, Rock said, when the first public conversations about what they're building was on on the key with you and Me and vent hat, the founder. And what Rock said is doing their building real time. Snowflake Thio, Lack of better term. It's a real time sequel database in the cloud that's super elastic, just like Snowflake is. But unlike snowflake, which is a data warehouse mostly for dashboards and analytics. Rock set is like millisecond queries for real time applications, and so think of them is the evolution of where cloud databases air going is not only elastic like snowflake in the cloud like Snowflake. We're talking 10 15 millisecond queries versus one or two second queries, and I think what any Jassy did and Amazon with bowel officials say, Hey, Sequels, Legal frank of the cloud. There's a large installed base of sequel server developers out there and applications, and we're gonna use Babel fish to kind of move those applications from on premise the cloud or from old workload to the new workloads. And, I think, the name of the game. For for cloud vendors across the board, big and small startups thio Google markets, often Amazon is how do you reduce friction like, How do you reduce friction to try a new service to get your data in the cloud to move your data from one place to the next? And so you know, Amazon is trying to reduce friction by using Babel fish, and I think it is a great move by them. >>Yeah, by the way. Not only is it for Aurora Post Chris equal, they're also open sourcing it. So that's gonna be something that is gonna be interesting to play out. Because once they open source it essentially, that's an escape valve for locking. I mean, if you're a Microsoft customer, I mean, it ultimately is. Could be that Gateway drug. It's like it is ultimately like, Hey, if you don't like the licensing, come here. Now there's gonna be some questions on the translations. Um, Vince, um, scuttlebutt about that. But we'll see it's open source. We'll see what goes on. Um great stuff on on rocks that great. Great. Start up next. Next, uh, talk track I wanna get with you is You know, over the years, you know, we've talked about your history. We're gonna vm Where, uh, now being a venture capitalist. Successful, wanted Greylock. You've seen the waves, and I would call it the two ways pre cloud Early days of cloud. And now, with co vid, we're kind of in the, you know, not just born in the cloud Total cloud scale cloud operations. This is kind of what jazz he was going after. E think I tweeted Cloud is eating the world and on premise and the edges. What it's hungry for. It kind of goof on mark injuries since quote a software eating the world. This is where it's going. So it's a whole another chapter coming. You saw the pre cloud you saw Cloud. Now we've got basically global I t everything else >>It's cloud only I would say, You know, we saw pre cloud right the VM ware days and before that he called like, you know, data centers. I would say Amazon lawns of what, 6 4007, the Web services. So the past 14 15 years have been what I've been calling cloud transition, right? And so you had cos technologies that were either doing on migration from on premise and cloud or hybrid on premise off premise. And now you're seeing a generation of technologies and companies. Their cloud only John to your point. And so you could argue that this 15 year transitions were like, you know, Thio use a bad metaphor like amphibians. You're half in the water, half on land, you know, And like, you know, you're not You're not purely cloud. You're not purely on premise, but you can do both ways, and that's great. That's great, because that's a that's a dominant architecture today. But come just like rock set and snowflake, your cloud only right? They're born in the cloud, they're built on the cloud And now we're seeing a generation Startups and technology companies that are cloud only. And so, you know, unlike you have this transitionary evolution of like amphibians, land and sea. Now we have ah, no mammals, whatever that are Onley in the cloud Onley on land. And because of that, you can take advantage of a whole different set of constraints that are their cloud. Only that could build different services that you can't have going backwards. And so I think for 2021 forward, we're going to see a bunch of companies or cloud only, and they're gonna look very, very different than the previous set of companies the past 15 years. And as an investor, as you covering as analysts, is gonna be super interesting to see the difference. And if anything, the cloud only companies will accelerate the move of I t spending the move of mawr developers to the cloud because the cloud only technologies are gonna be so much more compelling than than the amphibians, if you will. >>Yeah, insisting to see your point. And you saw the news announcement had a ton of news, a ton of stage making right calls, kind of the democratization layer. We'll look at some of the insights that Amazon's getting just as the monster that they are in terms of size. The scope of what? Their observation spaces. They're seeing all these workloads. They have the Dev Ops guru. They launched that Dev Ops Guru thing I found interesting. They got data acquisition, right? So when you think about these new the new data paradigm with cloud on Lee, it opens up new things. Um, new patterns. Um, S o. I think I think to me. I think that's to me. I see where this notion of agility moves to a whole nother level, where it's it's not just moving fast, it's new capabilities. So how do you How do you see that happening? Because this is where I think the new generation is gonna come in and be like servers. Lambs. I like you guys actually provisioned E c. Two instances before I was servers on data centers. Now you got ec2. What? Lambda. So you're starting to see smaller compute? Um, new learnings, All these historical data insights feeding into the development process and to the application. >>I think it's interesting. So I think if you really want to take the next evolution, how do you make the cloud programmable for everybody? Right. And I think you mentioned stage maker machine learning data scientists, the sage maker user. The data scientists, for example, does not on provisioned containers and, you know, kodama files and understand communities, right? Like just like the developed today. Don't wanna rack servers like Oh, my God, Jerry, you had Iraq servers and data center and install VM ware. The generation beyond us doesn't want to think about the underlying infrastructure. You wanna think about it? How do you just program my app and program? The cloud writ large. And so I think where you can see going forward is two things. One people who call themselves developers. That definition has expanded the past 10, 15 years. It's on Lee growing, so everyone is gonna be developed right now from your white collar knowledge worker to your hard core infrastructure developer. But the populist developers expanding especially around machine learning and kind of the sage maker audience, for sure. And then what's gonna happen is, ah, law. This audience doesn't want to care about the stuff you just mentioned, John in terms of the online plumbing. So what Amazon Google on Azure will do is make that stuff easy, right? Or a starved could make it easy. And I think that the move towards land and services that moved specifically that don't think about the underlying plumbing. We're gonna make it easy for you. Just program your app and then either a startup, well, abstract away, all the all the underlying, um, infrastructure bits or the big three cloud vendors to say, you know, all this stuff would do in a serverless fashion. So I think serverless as, ah paradigm and have, quite frankly, a battlefront for the Big Three clouds and for startups is probably one in the front lines of the next generation. Whoever owns this kind of program will cloud model programming the Internet program. The cloud will be maybe the next platform the next 10 or 15 years. I still have two up for grabs. >>Yeah, I think that is so insightful. I think that's worth calling out. I think that's gonna be a multi year, um, effort. I mean, look at just how containers now, with ks anywhere and you've got the container Service of control plane built in, you got, you know, real time analytics coming in from rock set. And Amazon. You have pinned Pandora Panorama appliance that does machine learning and computer vision with sensors. I mean, this is just a whole new level of purpose built stuff software powered software operated. So you have this notion of Dev ops going to hand in the glove software and operations? Kind of. How do you operate this stuff? So I think the whole new next question was Okay, this is all great. But Amazon's always had this problem. It's just so hard. Like there's so much good stuff. Like, who do you hired operate it? It is not yet programmable. This has been a big problem for them. Your thoughts on that, >>um e think that the data illusion around Dev ops etcetera is the solution. So also that you're gonna have information from Amazon from startups. They're gonna automate a bunch of the operations. And so, you know, I'm involved to come to Kronos Fear that we talked about the past team kind of uber the Bilson called m three. That's basically next generation data dog. Next generation of visibility platform. They're gonna collect all the data from the applications. And once they have their your data, they're gonna know how to operate and automate scaling up, scaling down and the basic remediation for you. So you're going to see a bunch of tools, take the information from running your application infrastructure and automate exactly how to scale and manager your app. And so AI and machine learning where large John is gonna be, say, make a lot of plumbing go away or maybe not completely, but lets you scale better. So you, as a single system admin are used. A single SRE site reliability engineer can scale and manage a bigger application, and it's all gonna be around automation and and to your point, you said earlier, if you have the data, that's a powerful situations. Once have the data can build models on it and can start building solutions on the data. And so I think What happens is when Bill this program of cloud for for your, you know, broad development population automating all this stuff becomes important. So that's why I say service or this, You know, automation of infrastructure is the next battleground for the cloud because whoever does that for you is gonna be your virtualized back and virtualized data center virtualized SRE. And if whoever owns that, it's gonna be a very, very strategic position. >>Yeah, it's great stuff. This is back to the theme of this notion of virtualization is now gone beyond server virtualization. It's, you know, media virtualization with the Cube. My big joke here with the Q virtual. But it's to your point. It's everything can now be replicated in software and scale the cloud scale. So it's super big opportunity for entrepreneurs and companies. Thio, pivot and differentiate. Uh, the question I have for you next is on that thread Huge edge discussion going on, right. So, you know, I think I said it two years ago or three years ago. The data center is just a edges just a big fat edge. Jassy kind of said that in his keynote Hey, looks at that is just a Nedum point with his from his standpoint. But you have data center. You have re alleges you've got five G with wavelength. This local zone concept, which is, you know, Amazon in these metro areas reminds me the old wireless point of presence kind of vibe. And then you've got just purpose built devices like cameras and factory. So huge industrial innovation, robotics, meet software. I mean, whole huge edge development exploding, Which what's your view of this? And how do you look at that from? Is an investor in industry, >>I think edges both the opportunity for start ups and companies as well as a threat to Amazon, right to the reason why they have outposts and all the stuff the edges if you think about, you know, decentralizing your application and moving into the eggs from my wearable to my home to my car to my my city block edges access Super interesting. And so a couple things. One companies like Cloudflare Fastly company I'm involved with called Kato Networks that does. SAS is secure access service edge write their names and the edges In the category definition sassy is about How do you like get compute to the edge securely for your developers, for your customers, for your workers, for end users and what you know comes like Cloudflare and Kate have done is they built out a network of pops across the world, their their own infrastructure So they're not dependent upon. You know, the big cloud providers, the telco providers, you know, they're partnering with Big Cloud, their parting with the telcos. But they have their own kind of system, our own kind of platform to get to the edge. And so companies like Kato Networks in Cloud Player that have, ah, presence on the edge and their own infrastructure more or less, I think, are gonna be in a strategic position. And so Kate was seen benefits in the past year of Of of Cove it and locked down because more remote access more developers, Um, I think edge is gonna be a super great area development going forward. I think if you're Amazon, you're pushing to the edge aggressively without post. I think you're a developer startup. You know, creating your own infrastructure and riding this edge wave could be a great way to build a moat against a big cloud guy. So I'm super excited. You think edge in this whole idea of your own infrastructure. Like what Kato has done, it is gonna be super useful going forward. And you're going to see more and more companies. Um, spend the money to try to copy kind of, ah, Cloudflare Kato presence around the world. Because once you own your own kind of, um, infrastructure instead of pops and you're less depend upon them a cloud provider, you're you're in a good position because there's the Amazon outage last week and I think like twilio and a bunch of services went down for for a few hours. If you own your own set of pops, your independent that it is actually really, really secure >>if you and if they go down to the it's on you. But that was the kinesis outage that they had, uh, they before Thanksgiving. Um, yeah, that that's a problem. So on this on. So I guess the question for you on that is that Is it better to partner with Amazon or try to get a position on the edge? Have them either by you or computer, create value or coexist? How do you see that that strategy move. Do you coexist? Do you play with them? >>E think you have to co exist? I think that the partner coexist, right? I think like all things you compete with Amazon. Amazon is so broad that will be part of Amazon and you're gonna compete with and that's that's fair game, you know, like so Snowflake competes against red shift, but they also part of Amazon's. They're running Amazon. So I think if you're a startup trying to find the edge, you have to coexist in Amazon because they're so big. Big cloud, right, The Big three cloud Amazon, Google, Azure. They're not going anywhere. So if you're a startup founder, you definitely coexist. Leverage the good things of cloud. But then you gotta invest in your own edge. Both both figure early what? Your edge and literally the edge. Right. And I think you know you complement your edge presence be it the home, the car, the city block, the zip code with, you know, using Amazon strategically because Amazon is gonna help you get two different countries, different regions. You know you can't build a company without touching Amazon in some form of fashion these days. But if you're a star found or doing strategically, how use Amazon and picking how you differentiate is gonna be key. And if the differentiation might be small, John. But it could be super valuable, right? So maybe only 10 or 15%. But that could be ah Holton of value that you're building on top of it. >>Yeah, and there's a little bit of growth hack to with Amazon if you you know how it works. If you compete directly against the core building blocks like a C two has three, you're gonna get killed, right? They're gonna kill you if the the white space is interest. In the old days in Microsoft, you had a white space. They give it to you or they would roll you over and level you out. Amazon. If you're a customer and you're in a white space and do better than them, they're cool with that. They're like, basically like, Hey, if you could innovate on behalf of the customer, they let you do that as long as you have a big bill. Yeah. Snowflakes paying a lot of money to Amazon. Sure, but they also are doing a good job. So again, Amazon has been very clear on that. If you do a better job than us for, the customer will do it. But if they want Amazon Red Shift, they want Amazon Onley. They can choose that eso kind of the playbook. >>I think it is absolutely right, John is it sets from any jassy and that the Amazon culture of the customer comes first, right? And so whatever is best for the customer that's like their their mission statement. So whatever they do, they do for the customer. And if you build value for the customer and you're on top of Amazon, they'll be happy. You might compete with some Amazon services, which, no, the GM of that business may not be happy, but overall. Net Net. Amazon's getting a share of those dollars that you're that you're charging the customer getting a share of the value you're creating. They're happy, right? Because you know what? The line rising tide floats all the boats. So the Mork cloud usage is gonna only benefit the Big Three cloud providers Amazon, particularly because they're the biggest of the three. But more and more dollars go the cloud. If you're helping move more. Absolute cloud helping build more solutions in the cloud. Amazon is gonna be happy because they know that regardless of what you're doing, you will get a fraction of those dollars. Now, the key for a startup founder and what I'm looking for is how do we get mawr than you know? A sliver of the dollars. How to get a bigger slice of the pie, if you will. So I think edge and surveillance or two areas I'm thinking about because I think there are two areas where you can actually invest, own some I p owned some surface area and capture more of the value, um, to use a startup founder and, you know, are built last t to Amazon. >>Yeah. Great. Great thesis. Jerry has always been great. You've been with the Cube since the beginning on our first reinvented 2013. Um, and so we're now on our eighth year. Great to see your success. Great investment. You make your world class investor to great firm Greylock. Um great to have you on from your perspective. Final take on this year. What's your view of Jackie's keynote? Just in general, What's the vibe. What's the quick, um, soundbite >>from you? First, I'm so impressed and you can do you feel like a three Archy? No more or less by himself. Right then, that is, that is, um, that's a one man show, and I'm All of that is I don't think I could pull that off. Number one. Number two It's, um, the ability to for for Amazon to execute at so many different levels of stack from semiconductors. Right there, there there ai chips to high level services around healthcare solutions and legit solutions. It's amazing. So I would say both. I'm impressed by Amazon's ability. Thio go so broad up and down the stack. But also, I think the theme from From From Andy Jassy is like It's just acceleration. It's, you know now that we will have things unique to the cloud, and that could be just a I chips unique to the cloud or the services that are cloud only you're going to see a tipping point. We saw acceleration in the past 15 years, John. He called like this cloud transition. But you know, I think you know, we're talking about 2021 beyond you'll see a tipping point where now you can only get certain things in the cloud. Right? And that could be the underlying inference. Instances are training instances, the Amazons giving. So all of a sudden you as a founder or developer, says, Look, I guess so much more in the cloud there's there's no reason for me to do this hybrid thing. You know, Khyber is not gonna go away on Prem is not going away. But for sure. We're going to see, uh, increasing celebration off cloud only services. Um, our edge only services or things. They're only on functions that serve like serverless. That'll be defined the next 10 years of compute. And so that for you and I was gonna be a space and watch >>Jerry Chen always pleasure. Great insight. Great to have you on the Cube again. Great to see you. Thanks for coming on. >>Congrats to you guys in the Cube. Seven years growing. It's amazing to see all the content put on. So you think it isn't? Just Last point is you see the growth of the curve growth curves of the cloud. I'd be curious Johnson, The growth curve of the cube content You know, I would say you guys are also going exponential as well. So super impressed with what you guys have dealt. Congratulations. >>Thank you so much. Cute. Virtual. We've been virtualized. Virtualization is coming here, or Cubans were not in person this year because of the pandemic. But we'll be hybrid soon as events come back. I'm John for a year. Host for AWS reinvent coverage with the Cube. Thanks for watching. Stay tuned for more coverage all day. Next three weeks. Stay with us from around the globe. It's the Cube with digital coverage of aws reinvent 2020 sponsored by Intel >>and AWS. Welcome back here to our coverage here on the Cube of AWS.

[Music] [Applause] [Music] welcome to the special cube conversations here in Palo Alto cube studios I'm John Ferrier the founder of Silicon angle in the cube we're here with divest cargoes the founder and CEO of arcus Inc our curse com ar-are see us calm and Steve Herod General Partner at at General Catalyst VCU's funded him congratulations on your launch these guys launched on Monday a hot new product software OS for networking powering white boxes in a whole new generation of potentially cloud computing welcome to this cube conversation congratulations on your >> launch thank you John >> so today I should talk about this this >> startup when do you guys were founded let's get to the specifics date you were founded some of the people on the team and the funding and we were formally incorporated in February of 2016 we really got going in earnest in August of 2016 and have you know chosen to stay in stealth the the founding team consists of myself a gentleman by the name of Kop tell he's our CTO we also have a gentleman by the name of Derek Young he's our chief architect and our backgrounds are a combination of the semiconductor industry I spent a lot of time in the semiconductor industry most recently I was president of easy chip and we sold that company to Mellanox and Kher and Derek our networking protocol experts spent 20 plus years at places like Cisco and arguably some of the best protocol guys in the world so the three of us got together and basically saw an opportunity to to bring some of the insights and and architectural innovation you know we had in mind to the Mobius a pedigree in there some some top talent absolutely some of the things that they've done in the past from some notable yeah I mean you know some if you if you'd like some just high-level numbers we have 600 plus years of experience of deep networking expertise within the company our collective team has shipped over 400 products to production we have over 200 IETF RFC papers that have been filed by the team as well as 150 plus patents so we really can do something on the pedigree for sure yeah we absolutely focused on getting the best talent in the world because we felt that it would be a significant differentiation to be able to start from a clean sheet of paper and so really having people who have that expertise allowed us to kind of take a step back and you know reimagine what could be possible with an operating system and gave us the benefit of being able to you know choose >> best-in-class approaches so what's the >> cap the point that this all came >> together what was the guiding vision was it network os's are going to be cloud-based was it going to be more I owe t what was the some of the founding principles that really got this going because clearly we see a trend where you know Intel's been dominating we see what NVIDIA is doing competitively certainly on the GPU side you're seeing the white box has become a trend Google makes their own stuff apples big making their own silicon seeking the that's kind of a whole big scale world out there that has got a lot of hardware experience what was the catalyst for you guys when you found this kinda was the guiding principle yeah I would say there were three John and you hit you hit on a couple of them in your reference to Intel and NVIDIA with some of the innovation but if I start at the top level the market the networking market is a large market and it's also very strategic and foundational in a hyper-connected world that market is also dominated by a few people and there's essentially three vertically integrated OEM so that dominate that market and when you have that type of dominance it leads to ultimately high prices and muted innovations so we felt number one the market was going through tremendous change but at the same time it had been tightly controlled by a few people the other part of it was that there was a tremendous amount of innovation that was happening at the silicon component level coming from the semiconductor industry I was early at Broadcom very you know involved in some of the networking things that happened in the early stages of the company we saw tremendous amounts of innovation feature velocity that was happening at the silicon component level that in turn led to a lot of system hardware people coming into the market and producing systems based on this wide variety of choices for you know for the silicon but the missing link was really an operating system that would unleash all that innovation so Silicon Valley is back Steve you you know you're a VC now but you were the CTO at VMware one of the companies that actually changed how data centers operate certainly as it certainly as a pretext and cloud computing was seeing with micro services and the growth of cloud silicon's hot IT operations is certainly being decimated as we old knew it in the past everything's being automated away you need more function now there's a demand this is this penny how you see I mean you always see things are a little early as of technologist now VC what got you excited about these guys what's the what's the bottom line yeah maybe two points on that which so one silicon is is definitely become interesting again if you will in the in the Silicon Valley area and I think that's partly because cloud scale and web scale allows these environments where you can afford to put in new hardware and really take advantage of it I was a semiconductor I first austerity too so it's exciting for me to see that but um you know is the fish that it's kind of a straightforward story you know especially in a world of whether it's cloud or IOT or everything networking is you know like literally the core to all of us working going forward and the opportunity to rethink it in a new design and in software first mentality felt kind of perfect right now I think I I think device even sell the team a little short even is with all the numbers that are there kr for instance this co-founder was sort of everyone you talk to will call him mister BGP which is one of the main routing protocols in the internet so just a ridiculously deep team trying to take this on and there been a few companies trying to do something kind of like this and I think what do they say that the second Mouse gets the cheese and I think I think we've seen some things that didn't work the first time around and we can really I think improve on them and have a >> chance to make a major impact on the networking market you know just to kind of go on a tangent here for a second >> because you know as you're talking kind of my brain is kind of firing away because you know one of things I've been talking about on the cube a lot is ageism and if you look at the movement of the cloud that's brought us systems mindset back you look at all the best successes out there right now it's almost a old guys and gals but it's really systems people people who understand networking and systems because the cloud is an operating system you have an operating system for networking so you're seeing that trend certainly happened that's awesome the question I have for you device is what is the difference what's the impact of this new network OS because I'm almost envisioning if I think through my mind's eye you got servers and server list certainly big train seeing and cloud it's one resource pools one operating system and that needs to have cohesiveness and connectedness through services so is this how you guys are thinking about how are you guys think about the network os what's different about what you guys are doing with ARC OS versus what's out there today now that's a great question John so in terms of in terms of what we've done the the third piece you know of the puzzle so to speak when we were talking about our team I talked a little bit about the market opportunity I talked a little bit about the innovation that was happening at the semiconductor and systems level and said the missing link was on the OS and so as I said at the onset we had the benefit of hiring some of the best people in the world and what that gave us the opportunity was to look at the twenty plus years of development that had happened on the operating system side for networking and basically identify those things that really made sense so we had the benefit of being able to adopt what worked and then augment that with those things that were needed for a modern day networking infrastructure environment and so we set about producing a product we call it our Co s and the the characteristics of it that are unique are that its first of all its best-in-class protocols we have minimal dependency on open source protocols and the reason for that is that no serious network operator is going to put an open source networking protocol in the core of their network they're just not going to risk their business and the efficacy and performance of their network for something like that so we start with best-in-class protocols and then we captured them in a very open modular Services microservices based architecture and that allows us the flexibility and the extensibility to be able to compose it in a manner that's consistent with what the end-use case is going to be so it's designed from the onset to be very scalable and very versatile in terms of where it can be deployed we can deploy it you know in a physical environment we can deploy it visa via a container or we could deploy it in the cloud so we're agnostic to all of those use case scenarios and then in addition to that we knew that we had to make it usable it makes no sense to have the best-in-class protocols if our end customers can't use them so what we've done is we've adopted open config yang based models and we have programmable api's so in any environment people can leverage their existing tools their existing applications and they can relatively easily and efficiently integrate our Co s into their networking environment and then similarly we did the same thing on the hardware side we have something that we call D pal it's a data plane adaptation layer it's an intelligent how and what that allows us to do is be Hardware agnostic so we're indifferent to what the underlying hardware is and what we want to do is be able to take advantage of the advancements in the silicon component level as well as at the system level and be able to deploy our go S anywhere it's let's take a step back so you guys so the protocols that's awesome what's the value proposition for our Co S and who's the target audience you mentioned data centers in the past is a data center operators is it developers is it service providers who was your target customer yeah so so the the piece of the puzzle that wraps everything together is we wanted to do it at massive scale and so we have the ability to support internet scale with deep routing capabilities within our Co s and as a byproduct of that and all the other things that we've done architectural II were the world's first operating system that's been ported to the high-end Broadcom strata DNX family that product is called jericho plus in the marketplace and as a byproduct of that we can ingest a full internet routing table and as a byproduct of that we can be used in the highest end applications for network operators so performance is a key value public performance as measured by internet scale as measured by convergence times as measured by the amount of control visibility and access that we provide and by virtue of being able to solve that high-end problem it's very easy for us to come down so in terms of your specific question about what are the use cases we have active discussions in data center centric applications for the leaf and spine we have active discussions for edge applications we have active discussions going on for cloud centric applications arcus can be used anywhere who's the buyer those network operator so since we can go look a variety of personas network operator large telco that's right inner person running a killer app that's you know high mission-critical high scale is that Mike right yeah you're getting you're absolutely getting it right basically anybody that has a network and has a networking infrastructure that is consuming networking equipment is a potential customer for ours now the product has the extensibility to be used anywhere in the data center at the edge or in the cloud we're very focused on some of the use cases that are in the CDN peering and IP you know route reflector IP peering use cases great Steve I want to get your thoughts because I say I know how you invest you guys a great great firm over there you're pretty finicky on investments certainly team check pedigrees they're on the team so that's a good inside market tamp big markets what's the market here for you but how do you see this market what's the bet for you guys on the market side yeah it's pretty pretty straightforward as you look at the size of the networking market with you know three major players around here and you know a longer tail owning a small piece of Haitian giant market is a great way to get started and if you believe in the and the secular trends that are going on with innovation and hardware and the ability to take advantage of them I think we have identified a few really interesting starting use cases and web-scale companies that have a lot of cost and needs in the networking side but what I would love about the software architecture it reminds me a lot of things do have kind of just even the early virtualization pieces if you if you can take advantage of movement in advantages and hardware as they improve and really bring them into a company more quickly than before then those companies are gonna be able to have you know better economics on their networking early on so get a great layer in solve a particular use case but then the trends of being able to take advantage of new hardware and to be able to provide the data and the API is to programmatic and to manage it who one would that it's creative limp limitless opportunity because with custom silicon that has you know purpose-built protocols it's easy to put a box together and in a large data center or even boxes yeah you can imagine the vendors of the advances and the chips really love that there's a good company that can take advantage of them more quickly than others can so cloud cloud service refined certainly as a target audience here large the large clouds would love it there's an app coming in Broadcom as a customer they a partner of you guys in two parts first comes a partner so we we've ported arc OS onto multiple members of the Broadcom switching family so we have five or six of their components their networking system on chip components that we've ported to including the two highest end which is the jericho plus and you got a letter in the Broadcom buying CA and that's gonna open up IT operations to you guys and volge instead of applications and me to talk about what you just said extensibility of taking what you just said about boxes and tying applique and application performance you know what's going to see that vertically integrated and i think i think eloping yeah from from a semiconductor perspective since i spent a lot of time in the industry you know one of the challenges i had founded a high court count multi processor company and one of the challenges we always had was the software and at easy chip we had the world's highest and network processor challenge with software and i think if you take all the innovation in the silicon industry and couple it with the right software the combination of those two things opens up a vast number of opportunities and we feel that with our Co s we provide you know that software piece that's going to help people take advantage of all the great innovation that's happening you mentioned earlier open source people don't want to bring open source at the core the network yet the open source communities are growing really at an exponential rate you starting to see open source be the lingua franca for all developers especially the modern software developers wine not open sourcing the core the amino acids gotta be bulletproof you need security obviously answers there but that seems difficult to the trend on open source what's the what's the answer there on why not open source in the core yeah so we we take advantage of open source where it makes sense so we take advantage of open and onl open network Linux and we have developed our protocols that run on that environment the reason we feel that the protocols being developed in-house as opposed to leveraging things from the open source community are the internet scale multi-threading of bgp integrating things like open config yang based models into that environment right well it's not only proven but our the the the capabilities that we're able to innovate on and bring unique differentiation weren't really going back to a clean sheet of paper and so we designed it ground-up to really be optimized for the needs of today Steve your old boss Palmer rich used to talk about the harden top mmm-hmm similar here right you know one really no one's really gonna care if it works great it's under the under the harden top where you use open source as a connection point for services and opportunities to grow that similar concept yes I mean at the end of the day open source is great for certain things and for community and extensibility and for visibility and then on the flip side they look to a company that's accountable and for making sure it performs and as high quality and so I think I think that modern way for especially for the mission critical infrastructure is to have a mix of both and to give back to community where it makes sense to be responsible for hardening things are building them when they don't expense so how'd you how'd you how'd you land these guys you get him early and don't sit don't talk to any other VCS how did it all come together between you guys we've actually been friends for a while which has been great in it at one point we actually decided to ask hey what do you actually do I found that I was a venture investor and he is a network engineer but now I actually have actually really liked the networking space as a whole as much as people talk about the cloud or open source or storage being tough networking is literally everywhere and will be everywhere and whatever our world looks like so I always been looking for the most interesting companies in that space and we always joke like the investment world kind of San Francisco's applications mid here's sort of operating systems and the lower you get the more technical it gets and so well there's a vaccine I mean we're a media company I think we're doing things different we're team before we came on camera but I think media is undervalued I wrote just wrote a tweet on that got some traction on that but it's shifting back to silicon you're seeing systems if you look at some of the hottest areas IT operations is being automated away AI ops you know Auto machine learning starting to see some of these high-end like home systems like that's exactly where I was gonna go it's like the vid I I especially just love very deep intellectual property that is hard to replicate and that you can you know ultimately you can charge a premium for something that is that hard to do and so that's that's really something I get drugs in the deal with in you guys you have any other syndicates in the video about soda sure you know so our initial seed investor was clear ventures gentleman by the name of Chris rust is on our board and then Steve came in and led our most recent round of funding and he also was on the board what we've done beyond that institutional money is we have a group of very strategic individual investors two people I would maybe highlight amongst the vast number of advisers we have our gentleman by the name of Pankaj Patel punka JH was the chief development officer at Cisco he was basically number two at Cisco for a number of years deep operating experience across all facets of what we would need and then there's another gentleman by the name of Amarjeet Gill I've been friends with armored teeth for 30 years he's probably one of the single most successful entrepreneurs in the he's incubated companies that have been purchased by Broadcom by Apple by Google by Facebook by Intel by EMC so we were fortunate enough to get him involved and keep him busy great pedigree great investors with that kind of electoral property and those smart mines they're a lot of pressure on you as the CEO not to screw it up right I mean come on now get all those smart man come on okay you got it look at really good you know I I welcome it actually I enjoy it you know we look when you have a great team and you have as many capable people surrounding you it really comes together and so I don't think it's about me I actually think number one it's about I was just kidding by the way I think it's about the team and I'm merely a spokesperson to represent all the great work that our team has done so I'm really proud of the guys we have and frankly it makes my job easier you've got a lot of people to tap for for advice certainly the shared experiences electively in the different areas make a lot of sense in the investors certainly yeah up to you absolutely absolutely and it's not it's not just at the at the board it's just not at the investor level it's at the adviser level and also at you know at our individual team members when we have a team that executes as well as we have you know everything falls into place well we think the software worlds change we think the economics are changing certainly when you look at cloud whether it's cloud computing or token economics with blockchain and new emerging tech around AI we think the world is certainly going to change so you guys got a great team to kind of figure it out I mean you got a-you know execute in real time you got a real technology play with IP question is what's the next step what is your priorities now that you're out there congratulations on your launch thank you in stealth mode you got some customers you've got Broadcom relationships and looking out in the landscape what's your what's your plan for the next year what's your goals really to take every facet of what you said and just scale the business you know we're actively hiring we have a lot of customer activity this week happens to be the most recent IETF conference that happened in Montreal given our company launch on Monday there's been a tremendous amount of interest in everything that we're doing so that coupled with the existing customer discussions we have is only going to expand and then we have a very robust roadmap to continue to augment and add capabilities to the baseline capabilities that we brought to the market so I I really view the next year as scaling the business in all aspects and increasingly my time is going to be focused on commercially centric activities right well congratulations got a great team we receive great investment cube conversation here I'm John furry here the hot startup here launching this week here in California in Silicon Valley where silicon is back and software is back it's the cube bringing you all the action I'm John Fourier thanks for watching [Music]