(mellow music) >> Hello everyone, welcome to theCUBE's coverage of AWS Startup Showcase. This is the closing panel session on AI machine learning, the top startups generating generative AI on AWS. It's a great panel. This is going to be the experts talking about riding the wave in generative AI. We got Ankur Mehrotra, who's the director and general manager of AI and machine learning at AWS, and Clem Delangue, co-founder and CEO of Hugging Face, and Ori Goshen, who's the co-founder and CEO of AI21 Labs. Ori from Tel Aviv dialing in, and rest coming in here on theCUBE. Appreciate you coming on for this closing session for the Startup Showcase. >> Thanks for having us. >> Thank you for having us. >> Thank you. >> I'm super excited to have you all on. Hugging Face was recently in the news with the AWS relationship, so congratulations. Open source, open science, really driving the machine learning. And we got the AI21 Labs access to the LLMs, generating huge scale live applications, commercial applications, coming to the market, all powered by AWS. So everyone, congratulations on all your success, and thank you for headlining this panel. Let's get right into it. AWS is powering this wave here. We're seeing a lot of push here from applications. Ankur, set the table for us on the AI machine learning. It's not new, it's been goin' on for a while. Past three years have been significant advancements, but there's been a lot of work done in AI machine learning. Now it's released to the public. Everybody's super excited and now says, "Oh, the future's here!" It's kind of been going on for a while and baking. Now it's kind of coming out. What's your view here? Let's get it started. >> Yes, thank you. So, yeah, as you may be aware, Amazon has been in investing in machine learning research and development since quite some time now. And we've used machine learning to innovate and improve user experiences across different Amazon products, whether it's Alexa or Amazon.com. But we've also brought in our expertise to extend what we are doing in the space and add more generative AI technology to our AWS products and services, starting with CodeWhisperer, which is an AWS service that we announced a few months ago, which is, you can think of it as a coding companion as a service, which uses generative AI models underneath. And so this is a service that customers who have no machine learning expertise can just use. And we also are talking to customers, and we see a lot of excitement about generative AI, and customers who want to build these models themselves, who have the talent and the expertise and resources. For them, AWS has a number of different options and capabilities they can leverage, such as our custom silicon, such as Trainium and Inferentia, as well as distributed machine learning capabilities that we offer as part of SageMaker, which is an end-to-end machine learning development service. At the same time, many of our customers tell us that they're interested in not training and building these generative AI models from scratch, given they can be expensive and can require specialized talent and skills to build. And so for those customers, we are also making it super easy to bring in existing generative AI models into their machine learning development environment within SageMaker for them to use. So we recently announced our partnership with Hugging Face, where we are making it super easy for customers to bring in those models into their SageMaker development environment for fine tuning and deployment. And then we are also partnering with other proprietary model providers such as AI21 and others, where we making these generative AI models available within SageMaker for our customers to use. So our approach here is to really provide customers options and choices and help them accelerate their generative AI journey. >> Ankur, thank you for setting the table there. Clem and Ori, I want to get your take, because the riding the waves, the theme of this session, and to me being in California, I imagine the big surf, the big waves, the big talent out there. This is like alpha geeks, alpha coders, developers are really leaning into this. You're seeing massive uptake from the smartest people. Whether they're young or around, they're coming in with their kind of surfboards, (chuckles) if you will. These early adopters, they've been on this for a while; Now the waves are hitting. This is a big wave, everyone sees it. What are some of those early adopter devs doing? What are some of the use cases you're seeing right out of the gate? And what does this mean for the folks that are going to come in and get on this wave? Can you guys share your perspective on this? Because you're seeing the best talent now leaning into this. >> Yeah, absolutely. I mean, from Hugging Face vantage points, it's not even a a wave, it's a tidal wave, or maybe even the tide itself. Because actually what we are seeing is that AI and machine learning is not something that you add to your products. It's very much a new paradigm to do all technology. It's this idea that we had in the past 15, 20 years, one way to build software and to build technology, which was writing a million lines of code, very rule-based, and then you get your product. Now what we are seeing is that every single product, every single feature, every single company is starting to adopt AI to build the next generation of technology. And that works both to make the existing use cases better, if you think of search, if you think of social network, if you think of SaaS, but also it's creating completely new capabilities that weren't possible with the previous paradigm. Now AI can generate text, it can generate image, it can describe your image, it can do so many new things that weren't possible before. >> It's going to really make the developers really productive, right? I mean, you're seeing the developer uptake strong, right? >> Yes, we have over 15,000 companies using Hugging Face now, and it keeps accelerating. I really think that maybe in like three, five years, there's not going to be any company not using AI. It's going to be really kind of the default to build all technology. >> Ori, weigh in on this. APIs, the cloud. Now I'm a developer, I want to have live applications, I want the commercial applications on this. What's your take? Weigh in here. >> Yeah, first, I absolutely agree. I mean, we're in the midst of a technology shift here. I think not a lot of people realize how big this is going to be. Just the number of possibilities is endless, and I think hard to imagine. And I don't think it's just the use cases. I think we can think of it as two separate categories. We'll see companies and products enhancing their offerings with these new AI capabilities, but we'll also see new companies that are AI first, that kind of reimagine certain experiences. They build something that wasn't possible before. And that's why I think it's actually extremely exciting times. And maybe more philosophically, I think now these large language models and large transformer based models are helping us people to express our thoughts and kind of making the bridge from our thinking to a creative digital asset in a speed we've never imagined before. I can write something down and get a piece of text, or an image, or a code. So I'll start by saying it's hard to imagine all the possibilities right now, but it's certainly big. And if I had to bet, I would say it's probably at least as big as the mobile revolution we've seen in the last 20 years. >> Yeah, this is the biggest. I mean, it's been compared to the Enlightenment Age. I saw the Wall Street Journal had a recent story on this. We've been saying that this is probably going to be bigger than all inflection points combined in the tech industry, given what transformation is coming. I guess I want to ask you guys, on the early adopters, we've been hearing on these interviews and throughout the industry that there's already a set of big companies, a set of companies out there that have a lot of data and they're already there, they're kind of tinkering. Kind of reminds me of the old hyper scaler days where they were building their own scale, and they're eatin' glass, spittin' nails out, you know, they're hardcore. Then you got everybody else kind of saying board level, "Hey team, how do I leverage this?" How do you see those two things coming together? You got the fast followers coming in behind the early adopters. What's it like for the second wave coming in? What are those conversations for those developers like? >> I mean, I think for me, the important switch for companies is to change their mindset from being kind of like a traditional software company to being an AI or machine learning company. And that means investing, hiring machine learning engineers, machine learning scientists, infrastructure in members who are working on how to put these models in production, team members who are able to optimize models, specialized models, customized models for the company's specific use cases. So it's really changing this mindset of how you build technology and optimize your company building around that. Things are moving so fast that I think now it's kind of like too late for low hanging fruits or small, small adjustments. I think it's important to realize that if you want to be good at that, and if you really want to surf this wave, you need massive investments. If there are like some surfers listening with this analogy of the wave, right, when there are waves, it's not enough just to stand and make a little bit of adjustments. You need to position yourself aggressively, paddle like crazy, and that's how you get into the waves. So that's what companies, in my opinion, need to do right now. >> Ori, what's your take on the generative models out there? We hear a lot about foundation models. What's your experience running end-to-end applications for large foundation models? Any insights you can share with the app developers out there who are looking to get in? >> Yeah, I think first of all, it's start create an economy, where it probably doesn't make sense for every company to create their own foundation models. You can basically start by using an existing foundation model, either open source or a proprietary one, and start deploying it for your needs. And then comes the second round when you are starting the optimization process. You bootstrap, whether it's a demo, or a small feature, or introducing new capability within your product, and then start collecting data. That data, and particularly the human feedback data, helps you to constantly improve the model, so you create this data flywheel. And I think we're now entering an era where customers have a lot of different choice of how they want to start their generative AI endeavor. And it's a good thing that there's a variety of choices. And the really amazing thing here is that every industry, any company you speak with, it could be something very traditional like industrial or financial, medical, really any company. I think peoples now start to imagine what are the possibilities, and seriously think what's their strategy for adopting this generative AI technology. And I think in that sense, the foundation model actually enabled this to become scalable. So the barrier to entry became lower; Now the adoption could actually accelerate. >> There's a lot of integration aspects here in this new wave that's a little bit different. Before it was like very monolithic, hardcore, very brittle. A lot more integration, you see a lot more data coming together. I have to ask you guys, as developers come in and grow, I mean, when I went to college and you were a software engineer, I mean, I got a degree in computer science, and software engineering, that's all you did was code, (chuckles) you coded. Now, isn't it like everyone's a machine learning engineer at this point? Because that will be ultimately the science. So, (chuckles) you got open source, you got open software, you got the communities. Swami called you guys the GitHub of machine learning, Hugging Face is the GitHub of machine learning, mainly because that's where people are going to code. So this is essentially, machine learning is computer science. What's your reaction to that? >> Yes, my co-founder Julien at Hugging Face have been having this thing for quite a while now, for over three years, which was saying that actually software engineering as we know it today is a subset of machine learning, instead of the other way around. People would call us crazy a few years ago when we're seeing that. But now we are realizing that you can actually code with machine learning. So machine learning is generating code. And we are starting to see that every software engineer can leverage machine learning through open models, through APIs, through different technology stack. So yeah, it's not crazy anymore to think that maybe in a few years, there's going to be more people doing AI and machine learning. However you call it, right? Maybe you'll still call them software engineers, maybe you'll call them machine learning engineers. But there might be more of these people in a couple of years than there is software engineers today. >> I bring this up as more tongue in cheek as well, because Ankur, infrastructure's co is what made Cloud great, right? That's kind of the DevOps movement. But here the shift is so massive, there will be a game-changing philosophy around coding. Machine learning as code, you're starting to see CodeWhisperer, you guys have had coding companions for a while on AWS. So this is a paradigm shift. How is the cloud playing into this for you guys? Because to me, I've been riffing on some interviews where it's like, okay, you got the cloud going next level. This is an example of that, where there is a DevOps-like moment happening with machine learning, whether you call it coding or whatever. It's writing code on its own. Can you guys comment on what this means on top of the cloud? What comes out of the scale? What comes out of the benefit here? >> Absolutely, so- >> Well first- >> Oh, go ahead. >> Yeah, so I think as far as scale is concerned, I think customers are really relying on cloud to make sure that the applications that they build can scale along with the needs of their business. But there's another aspect to it, which is that until a few years ago, John, what we saw was that machine learning was a data scientist heavy activity. They were data scientists who were taking the data and training models. And then as machine learning found its way more and more into production and actual usage, we saw the MLOps become a thing, and MLOps engineers become more involved into the process. And then we now are seeing, as machine learning is being used to solve more business critical problems, we're seeing even legal and compliance teams get involved. We are seeing business stakeholders more engaged. So, more and more machine learning is becoming an activity that's not just performed by data scientists, but is performed by a team and a group of people with different skills. And for them, we as AWS are focused on providing the best tools and services for these different personas to be able to do their job and really complete that end-to-end machine learning story. So that's where, whether it's tools related to MLOps or even for folks who cannot code or don't know any machine learning. For example, we launched SageMaker Canvas as a tool last year, which is a UI-based tool which data analysts and business analysts can use to build machine learning models. So overall, the spectrum in terms of persona and who can get involved in the machine learning process is expanding, and the cloud is playing a big role in that process. >> Ori, Clem, can you guys weigh in too? 'Cause this is just another abstraction layer of scale. What's it mean for you guys as you look forward to your customers and the use cases that you're enabling? >> Yes, I think what's important is that the AI companies and providers and the cloud kind of work together. That's how you make a seamless experience and you actually reduce the barrier to entry for this technology. So that's what we've been super happy to do with AWS for the past few years. We actually announced not too long ago that we are doubling down on our partnership with AWS. We're excited to have many, many customers on our shared product, the Hugging Face deep learning container on SageMaker. And we are working really closely with the Inferentia team and the Trainium team to release some more exciting stuff in the coming weeks and coming months. So I think when you have an ecosystem and a system where the AWS and the AI providers, AI startups can work hand in hand, it's to the benefit of the customers and the companies, because it makes it orders of magnitude easier for them to adopt this new paradigm to build technology AI. >> Ori, this is a scale on reasoning too. The data's out there and making sense out of it, making it reason, getting comprehension, having it make decisions is next, isn't it? And you need scale for that. >> Yes. Just a comment about the infrastructure side. So I think really the purpose is to streamline and make these technologies much more accessible. And I think we'll see, I predict that we'll see in the next few years more and more tooling that make this technology much more simple to consume. And I think it plays a very important role. There's so many aspects, like the monitoring the models and their kind of outputs they produce, and kind of containing and running them in a production environment. There's so much there to build on, the infrastructure side will play a very significant role. >> All right, that's awesome stuff. I'd love to change gears a little bit and get a little philosophy here around AI and how it's going to transform, if you guys don't mind. There's been a lot of conversations around, on theCUBE here as well as in some industry areas, where it's like, okay, all the heavy lifting is automated away with machine learning and AI, the complexity, there's some efficiencies, it's horizontal and scalable across all industries. Ankur, good point there. Everyone's going to use it for something. And a lot of stuff gets brought to the table with large language models and other things. But the key ingredient will be proprietary data or human input, or some sort of AI whisperer kind of role, or prompt engineering, people are saying. So with that being said, some are saying it's automating intelligence. And that creativity will be unleashed from this. If the heavy lifting goes away and AI can fill the void, that shifts the value to the intellect or the input. And so that means data's got to come together, interact, fuse, and understand each other. This is kind of new. I mean, old school AI was, okay, got a big model, I provisioned it long time, very expensive. Now it's all free flowing. Can you guys comment on where you see this going with this freeform, data flowing everywhere, heavy lifting, and then specialization? >> Yeah, I think- >> Go ahead. >> Yeah, I think, so what we are seeing with these large language models or generative models is that they're really good at creating stuff. But I think it's also important to recognize their limitations. They're not as good at reasoning and logic. And I think now we're seeing great enthusiasm, I think, which is justified. And the next phase would be how to make these systems more reliable. How to inject more reasoning capabilities into these models, or augment with other mechanisms that actually perform more reasoning so we can achieve more reliable results. And we can count on these models to perform for critical tasks, whether it's medical tasks, legal tasks. We really want to kind of offload a lot of the intelligence to these systems. And then we'll have to get back, we'll have to make sure these are reliable, we'll have to make sure we get some sort of explainability that we can understand the process behind the generated results that we received. So I think this is kind of the next phase of systems that are based on these generated models. >> Clem, what's your view on this? Obviously you're at open community, open source has been around, it's been a great track record, proven model. I'm assuming creativity's going to come out of the woodwork, and if we can automate open source contribution, and relationships, and onboarding more developers, there's going to be unleashing of creativity. >> Yes, it's been so exciting on the open source front. We all know Bert, Bloom, GPT-J, T5, Stable Diffusion, that work up. The previous or the current generation of open source models that are on Hugging Face. It has been accelerating in the past few months. So I'm super excited about ControlNet right now that is really having a lot of impact, which is kind of like a way to control the generation of images. Super excited about Flan UL2, which is like a new model that has been recently released and is open source. So yeah, it's really fun to see the ecosystem coming together. Open source has been the basis for traditional software, with like open source programming languages, of course, but also all the great open source that we've gotten over the years. So we're happy to see that the same thing is happening for machine learning and AI, and hopefully can help a lot of companies reduce a little bit the barrier to entry. So yeah, it's going to be exciting to see how it evolves in the next few years in that respect. >> I think the developer productivity angle that's been talked about a lot in the industry will be accelerated significantly. I think security will be enhanced by this. I think in general, applications are going to transform at a radical rate, accelerated, incredible rate. So I think it's not a big wave, it's the water, right? I mean, (chuckles) it's the new thing. My final question for you guys, if you don't mind, I'd love to get each of you to answer the question I'm going to ask you, which is, a lot of conversations around data. Data infrastructure's obviously involved in this. And the common thread that I'm hearing is that every company that looks at this is asking themselves, if we don't rebuild our company, start thinking about rebuilding our business model around AI, we might be dinosaurs, we might be extinct. And it reminds me that scene in Moneyball when, at the end, it's like, if we're not building the model around your model, every company will be out of business. What's your advice to companies out there that are having those kind of moments where it's like, okay, this is real, this is next gen, this is happening. I better start thinking and putting into motion plans to refactor my business, 'cause it's happening, business transformation is happening on the cloud. This kind of puts an exclamation point on, with the AI, as a next step function. Big increase in value. So it's an opportunity for leaders. Ankur, we'll start with you. What's your advice for folks out there thinking about this? Do they put their toe in the water? Do they jump right into the deep end? What's your advice? >> Yeah, John, so we talk to a lot of customers, and customers are excited about what's happening in the space, but they often ask us like, "Hey, where do we start?" So we always advise our customers to do a lot of proof of concepts, understand where they can drive the biggest ROI. And then also leverage existing tools and services to move fast and scale, and try and not reinvent the wheel where it doesn't need to be. That's basically our advice to customers. >> Get it. Ori, what's your advice to folks who are scratching their head going, "I better jump in here. "How do I get started?" What's your advice? >> So I actually think that need to think about it really economically. Both on the opportunity side and the challenges. So there's a lot of opportunities for many companies to actually gain revenue upside by building these new generative features and capabilities. On the other hand, of course, this would probably affect the cogs, and incorporating these capabilities could probably affect the cogs. So I think we really need to think carefully about both of these sides, and also understand clearly if this is a project or an F word towards cost reduction, then the ROI is pretty clear, or revenue amplifier, where there's, again, a lot of different opportunities. So I think once you think about this in a structured way, I think, and map the different initiatives, then it's probably a good way to start and a good way to start thinking about these endeavors. >> Awesome. Clem, what's your take on this? What's your advice, folks out there? >> Yes, all of these are very good advice already. Something that you said before, John, that I disagreed a little bit, a lot of people are talking about the data mode and proprietary data. Actually, when you look at some of the organizations that have been building the best models, they don't have specialized or unique access to data. So I'm not sure that's so important today. I think what's important for companies, and it's been the same for the previous generation of technology, is their ability to build better technology faster than others. And in this new paradigm, that means being able to build machine learning faster than others, and better. So that's how, in my opinion, you should approach this. And kind of like how can you evolve your company, your teams, your products, so that you are able in the long run to build machine learning better and faster than your competitors. And if you manage to put yourself in that situation, then that's when you'll be able to differentiate yourself to really kind of be impactful and get results. That's really hard to do. It's something really different, because machine learning and AI is a different paradigm than traditional software. So this is going to be challenging, but I think if you manage to nail that, then the future is going to be very interesting for your company. >> That's a great point. Thanks for calling that out. I think this all reminds me of the cloud days early on. If you went to the cloud early, you took advantage of it when the pandemic hit. If you weren't native in the cloud, you got hamstrung by that, you were flatfooted. So just get in there. (laughs) Get in the cloud, get into AI, you're going to be good. Thanks for for calling that. Final parting comments, what's your most exciting thing going on right now for you guys? Ori, Clem, what's the most exciting thing on your plate right now that you'd like to share with folks? >> I mean, for me it's just the diversity of use cases and really creative ways of companies leveraging this technology. Every day I speak with about two, three customers, and I'm continuously being surprised by the creative ideas. And the future is really exciting of what can be achieved here. And also I'm amazed by the pace that things move in this industry. It's just, there's not at dull moment. So, definitely exciting times. >> Clem, what are you most excited about right now? >> For me, it's all the new open source models that have been released in the past few weeks, and that they'll keep being released in the next few weeks. I'm also super excited about more and more companies getting into this capability of chaining different models and different APIs. I think that's a very, very interesting development, because it creates new capabilities, new possibilities, new functionalities that weren't possible before. You can plug an API with an open source embedding model, with like a no-geo transcription model. So that's also very exciting. This capability of having more interoperable machine learning will also, I think, open a lot of interesting things in the future. >> Clem, congratulations on your success at Hugging Face. Please pass that on to your team. Ori, congratulations on your success, and continue to, just day one. I mean, it's just the beginning. It's not even scratching the service. Ankur, I'll give you the last word. What are you excited for at AWS? More cloud goodness coming here with AI. Give you the final word. >> Yeah, so as both Clem and Ori said, I think the research in the space is moving really, really fast, so we are excited about that. But we are also excited to see the speed at which enterprises and other AWS customers are applying machine learning to solve real business problems, and the kind of results they're seeing. So when they come back to us and tell us the kind of improvement in their business metrics and overall customer experience that they're driving and they're seeing real business results, that's what keeps us going and inspires us to continue inventing on their behalf. >> Gentlemen, thank you so much for this awesome high impact panel. Ankur, Clem, Ori, congratulations on all your success. We'll see you around. Thanks for coming on. Generative AI, riding the wave, it's a tidal wave, it's the water, it's all happening. All great stuff. This is season three, episode one of AWS Startup Showcase closing panel. This is the AI ML episode, the top startups building generative AI on AWS. I'm John Furrier, your host. Thanks for watching. (mellow music)

(energetic music) >> Everyone, welcome back to theCUBE's coverage of WiDS 2023. This is the eighth annual Women in Data Science Conference. As you know, WiDS is not just a conference or an event, it's a movement. This is going to include over 100,000 people in the next year WiDS 2023 in 200-plus countries. It is such a powerful movement. If you've had a chance to be part of the Livestream or even be here in person with us at Stanford University, you know what I'm talking about. This is Lisa Martin. I have had the pleasure all day of working with two fantastic graduate students in Stanford's Data Journalism Master's Program. Hannah Freitag has been here. Tracy Zhang, ladies, it's been such a pleasure working with you today. >> Same wise. >> I want to ask you both what are, as we wrap the day, I'm so inspired, I feel like I could go build an airplane. >> Exactly. >> Probably can't. But WiDS is just the inspiration that comes from this event. When you walk in the front door, you can feel it. >> Mm-hmm. >> Tracy, talk a little bit about what some of the things are that you heard today that really inspired you. >> I think one of the keyword that's like in my mind right now is like finding a mentor. >> Yeah. >> And I think, like if I leave this conference if I leave the talks, the conversations with one thing is that I'm very positive that if I want to switch, say someday, from Journalism to being a Data Analyst, to being like in Data Science, I'm sure that there are great role models for me to look up to, and I'm sure there are like mentors who can guide me through the way. So, like that, I feel reassured for some reason. >> It's a good feeling, isn't it? What do you, Hannah, what about you? What's your takeaway so far of the day? >> Yeah, one of my key takeaways is that anything's possible. >> Mm-hmm. >> So, if you have your vision, you have the role model, someone you look up to, and even if you have like a different background, not in Data Science, Data Engineering, or Computer Science but you're like, "Wow, this is really inspiring. I would love to do that." As long as you love it, you're passionate about it, and you are willing to, you know, take this path even though it won't be easy. >> Yeah. >> Then you can achieve it, and as you said, Tracy, it's important to have mentors on the way there. >> Exactly. >> But as long as you speak up, you know, you raise your voice, you ask questions, and you're curious, you can make it. >> Yeah. >> And I think that's one of my key takeaways, and I was just so inspiring to hear like all these women speaking on stage, and also here in our conversations and learning about their, you know, career path and what they learned on their way. >> Yeah, you bring up curiosity, and I think that is such an important skill. >> Mm-hmm. >> You know, you could think of Data Science and think about all the hard skills that you need. >> Mm, like coding. >> But as some of our guests said today, you don't have to be a statistician or an engineer, or a developer to get into this. Data Science applies to every facet of every part of the world. >> Mm-hmm. >> Finances, marketing, retail, manufacturing, healthcare, you name it, Data Science has the power and the potential to unlock massive achievements. >> Exactly. >> It's like we're scratching the surface. >> Yeah. >> But that curiosity, I think, is a great skill to bring to anything that you do. >> Mm-hmm. >> And I think we... For the female leaders that we're on stage, and that we had a chance to talk to on theCUBE today, I think they all probably had that I think as a common denominator. >> Exactly. >> That curious mindset, and also something that I think as hard is the courage to raise your hand. I like this, I'm interested in this. I don't see anybody that looks like me. >> But that doesn't mean I shouldn't do it. >> Exactly. >> Exactly, in addition to the curiosity that all the women, you know, bring to the table is that, in addition to that, being optimistic, and even though we don't see gender equality or like general equality in companies yet, we make progress and we're optimistic about it, and we're not like negative and complaining the whole time. But you know, this positive attitude towards a trend that is going in the right direction, and even though there's still a lot to be done- >> Exactly. >> We're moving it that way. >> Right. >> Being optimistic about this. >> Yeah, exactly, like even if it means that it's hard. Even if it means you need to be your own role model it's still like worth a try. And I think they, like all of the great women speakers, all the female leaders, they all have that in them, like they have the courage to like raise their hand and be like, "I want to do this, and I'm going to make it." And they're role models right now, so- >> Absolutely, they have drive. >> They do. >> Right. They have that ambition to take something that's challenging and complicated, and help abstract end users from that. Like we were talking to Intuit. I use Intuit in my small business for financial management, and she was talking about how they can from a machine learning standpoint, pull all this data off of documents that you upload and make that, abstract that, all that complexity from the end user, make something that's painful taxes. >> Mm-hmm. >> Maybe slightly less painful. It's still painful when you have to go, "Do I have to write you a check again?" >> Yeah. (laughs) >> Okay. >> But talking about just all the different applications of Data Science in the world, I found that to be very inspiring and really eye-opening. >> Definitely. >> I hadn't thought about, you know, we talk about climate change all the time, especially here in California, but I never thought about Data Science as a facilitator of the experts being able to make sense of what's going on historically and in real-time, or the application of Data Science in police violence. We see far too many cases of police violence on the news. It's an epidemic that's a horrible problem. Data Science can be applied to that to help us learn from that, and hopefully, start moving the needle in the right direction. >> Absolutely. >> Exactly. >> And especially like one sentence from Guitry from the very beginnings I still have in my mind is then when she said that arguments, no, that data beats arguments. >> Yes. >> In a conversation that if you be like, okay, I have this data set and it can actually show you this or that, it's much more powerful than just like being, okay, this is my position or opinion on this. And I think in a world where increasing like misinformation, and sometimes, censorship as we heard in one of the talks, it's so important to have like data, reliable data, but also acknowledge, and we talked about it with one of our interviewees that there's spices in data and we also need to be aware of this, and how to, you know, move this forward and use Data Science for social good. >> Mm-hmm. >> Yeah, for social good. >> Yeah, definitely, I think they like data, and the question about, or like the problem-solving part about like the social issues, or like some just questions, they definitely go hand-in-hand. Like either of them standing alone won't be anything that's going to be having an impact, but combining them together, you have a data set that illustrate a point or like solves the problem. I think, yeah, that's definitely like where Data Set Science is headed to, and I'm glad to see all these great women like making their impact and combining those two aspects together. >> It was interesting in the keynote this morning. We were all there when Margot Gerritsen who's one of the founders of WiDS, and Margot's been on the program before and she's a huge supporter of what we do and vice versa. She asked the non-women in the room, "Those who don't identify as women, stand up," and there was a handful of men, and she said, "That's what it's like to be a female in technology." >> Oh, my God. >> And I thought that vision give me goosebumps. >> Powerful. (laughs) >> Very powerful. But she's right, and one of the things I think that thematically another common denominator that I think we heard, I want to get your opinions as well from our conversations today, is the importance of community. >> Mm-hmm. >> You know, I was mentioning this stuff from AnitaB.org that showed that in 2022, the percentage of females and technical roles is 27.6%. It's a little bit of an increase. It's been hovering around 25% for a while. But one of the things that's still a problem is attrition. It doubled last year. >> Right. >> And I was asking some of the guests, and we've all done that today, "How would you advise companies to start moving the needle down on attrition?" >> Mm-hmm. >> And I think the common theme was network, community. >> Exactly. >> It takes a village like this. >> Mm-hmm. >> So you can see what you can be to help start moving that needle and that's, I think, what underscores the value of what WiDS delivers, and what we're able to showcase on theCUBE. >> Yeah, absolutely. >> I think it's very important to like if you're like a woman in tech to be able to know that there's someone for you, that there's a whole community you can rely on, and that like you are, you have the same mindset, you're working towards the same goal. And it's just reassuring and like it feels very nice and warm to have all these women for you. >> Lisa: It's definitely a warm fuzzy, isn't it? >> Yeah, and both the community within the workplace but also outside, like a network of family and friends who support you to- >> Yes. >> To pursue your career goals. I think that was also a common theme we heard that it's, yeah, necessary to both have, you know your community within your company or organization you're working but also outside. >> Definitely, I think that's also like how, why, the reason why we feel like this in like at WiDS, like I think we all feel very positive right now. So, yeah, I think that's like the power of the connection and the community, yeah. >> And the nice thing is this is like I said, WiDS is a movement. >> Yes. >> This is global. >> Mm-hmm. >> We've had some WiDS ambassadors on the program who started WiDS and Tel Aviv, for example, in their small communities. Or in Singapore and Mumbai that are bringing it here and becoming more of a visible part of the community. >> Tracy: Right. >> I loved seeing all the young faces when we walked in the keynote this morning. You know, we come here from a journalistic perspective. You guys are Journalism students. But seeing all the potential in the faces in that room just seeing, and hearing stories, and starting to make tangible connections between Facebook and data, and the end user and the perspectives, and the privacy and the responsibility of AI is all... They're all positive messages that need to be reinforced, and we need to have more platforms like this to be able to not just raise awareness, but sustain it. >> Exactly. >> Right. It's about the long-term, it's about how do we dial down that attrition, what can we do? What can we do? How can we help? >> Mm-hmm. >> Both awareness, but also giving women like a place where they can connect, you know, also outside of conferences. Okay, how do we make this like a long-term thing? So, I think WiDS is a great way to, you know, encourage this connectivity and these women teaming up. >> Yeah, (chuckles) girls help girls. >> Yeah. (laughs) >> It's true. There's a lot of organizations out there, girls who Code, Girls Inc., et cetera, that are all aimed at helping women kind of find their, I think, find their voice. >> Exactly. >> And find that curiosity. >> Yeah. Unlock that somewhere back there. Get some courage- >> Mm-hmm. >> To raise your hand and say, "I think I want to do this," or "I have a question. You explained something and I didn't understand it." Like, that's the advice I would always give to my younger self is never be afraid to raise your hand in a meeting. >> Mm-hmm. >> I guarantee you half the people weren't listening or, and the other half may not have understood what was being talked about. >> Exactly. >> So, raise your hand, there goes Margot Gerritsen, the founder of WiDS, hey, Margot. >> Hi. >> Keep alumni as you know, raise your hand, ask the question, there's no question that's stupid. >> Mm-hmm. >> And I promise you, if you just take that chance once it will open up so many doors, you won't even know which door to go in because there's so many that are opening. >> And if you have a question, there's at least one more person in the room who has the exact same question. >> Exact same question. >> Yeah, we'll definitely keep that in mind as students- >> Well, I'm curious how Data Journalism, what you heard today, Tracy, we'll start with you, and then, Hannah, to you. >> Mm-hmm. How has it influenced how you approach data-driven, and storytelling? Has it inspired you? I imagine it has, or has it given you any new ideas for, as you round out your Master's Program in the next few months? >> I think like one keyword that I found really helpful from like all the conversations today, was problem-solving. >> Yeah. >> Because I think, like we talked a lot about in our program about how to put a face on data sets. How to put a face, put a name on a story that's like coming from like big data, a lot of numbers but you need to like narrow it down to like one person or one anecdote that represents a bigger problem. And I think essentially that's problem-solving. That's like there is a community, there is like say maybe even just one person who has, well, some problem about something, and then we're using data. We're, by giving them a voice, by portraying them in news and like representing them in the media, we're solving this problem somehow. We're at least trying to solve this problem, trying to make some impact. And I think that's like what Data Science is about, is problem-solving, and, yeah, I think I heard a lot from today's conversation, also today's speakers. So, yeah, I think that's like something we should also think about as Journalists when we do pitches or like what kind of problem are we solving? >> I love that. >> Or like kind of what community are we trying to make an impact in? >> Yes. >> Absolutely. Yeah, I think one of the main learnings for me that I want to apply like to my career in Data Journalism is that I don't shy away from complexity because like Data Science is oftentimes very complex. >> Complex. >> And also data, you're using for your stories is complex. >> Mm-hmm. >> So, how can we, on the one hand, reduce complexity in a way that we make it accessible for broader audience? 'Cause, we don't want to be this like tech bubble talking in data jargon, we want to, you know, make it accessible for a broader audience. >> Yeah. >> I think that's like my purpose as a Data Journalist. But at the same time, don't reduce complexity when it's needed, you know, and be open to dive into new topics, and data sets and circling back to this of like raising your hand and asking questions if you don't understand like a certain part. >> Yeah. >> So, that's definitely a main learning from this conference. >> Definitely. >> That like, people are willing to talk to you and explain complex topics, and this will definitely facilitate your work as a Data Journalist. >> Mm-hmm. >> So, that inspired me. >> Well, I can't wait to see where you guys go from here. I've loved co-hosting with you today, thank you. >> Thank you. >> For joining me at our conference. >> Wasn't it fun? >> Thank you. >> It's a great event. It's, we, I think we've all been very inspired and I'm going to leave here probably floating above the ground a few inches, high on the inspiration of what this community can deliver, isn't that great? >> It feels great, I don't know, I just feel great. >> Me too. (laughs) >> So much good energy, positive energy, we love it. >> Yeah, so we want to thank all the organizers of WiDS, Judy Logan, Margot Gerritsen in particular. We also want to thank John Furrier who is here. And if you know Johnny, know he gets FOMO when he is not hosting. But John and Dave Vellante are such great supporters of women in technology, women in technical roles. We wouldn't be here without them. So, shout out to my bosses. Thank you for giving me the keys to theCube at this event. I know it's painful sometimes, but we hope that we brought you great stories all day. We hope we inspired you with the females and the one male that we had on the program today in terms of raise your hand, ask a question, be curious, don't be afraid to pursue what you're interested in. That's my soapbox moment for now. So, for my co-host, I'm Lisa Martin, we want to thank you so much for watching our program today. You can watch all of this on-demand on thecube.net. You'll find write-ups on siliconeangle.com, and, of course, YouTube. Thanks, everyone, stay safe and we'll see you next time. (energetic music)

(gentle upbeat music) >> Hey, friends of theCUBE. It's Lisa Martin live at Stanford University covering the Eighth Annual Women In Data Science. But you've been a Cube fan for a long time. So you know that we've been here since the beginning of WiDS, which is 2015. We always loved to come and cover this event. We learned great things about data science, about women leaders, underrepresented minorities. And this year we have a special component. We've got two grad students from Stanford's Master's program and Data Journalism joining. One of my them is here with me, Hannah Freitag, my co-host. Great to have you. And we are pleased to welcome from Intuit for the first time, Shir Meir Lador Group Manager at Data Science. Shir, it's great to have you. Thank you for joining us. >> Thank you for having me. >> And I was just secrets girl talking with my boss of theCUBE who informed me that you're in great company. Intuit's Chief Technology Officer, Marianna Tessel is an alumni of theCUBE. She was on at our Supercloud event in January. So welcome back into it. >> Thank you very much. We're happy to be with you. >> Tell us a little bit about what you're doing. You're a data science group manager as I mentioned, but also you've had you've done some cool things I want to share with the audience. You're the co-founder of the PyData Tel Aviv Meetups the co-host of the unsupervised podcast about data science in Israel. You give talks, about machine learning, about data science. Tell us a little bit about your background. Were you always interested in STEM studies from the time you were small? >> So I was always interested in mathematics when I was small, I went to this special program for youth going to university. So I did my test in mathematics earlier and studied in university some courses. And that's when I understood I want to do something in that field. And then when I got to go to university, I went to electrical engineering when I found out about algorithms and how interested it is to be able to find solutions to problems, to difficult problems with math. And this is how I found my way into machine learning. >> Very cool. There's so much, we love talking about machine learning and AI on theCUBE. There's so much potential. Of course, we have to have data. One of the things that I love about WiDS and Hannah and I and our co-host Tracy, have been talking about this all day is the impact of data in everyone's life. If you break it down, I was at Mobile World Congress last week, all about connectivity telecom, and of course we have these expectation that we're going to be connected 24/7 from wherever we are in the world and we can do whatever we want. I can do an Uber transaction, I can watch Netflix, I can do a bank transaction. It all is powered by data. And data science is, some of the great applications of it is what it's being applied to. Things like climate change or police violence or health inequities. Talk about some of the data science projects that you're working on at Intuit. I'm an intuit user myself, but talk to me about some of those things. Give the audience really a feel for what you're doing. >> So if you are a Intuit product user, you probably use TurboTax. >> I do >> In the past. So for those who are not familiar, TurboTax help customers submit their taxes. Basically my group is in charge of getting all the information automatically from your documents, the documents that you upload to TurboTax. We extract that information to accelerate your tax submission to make it less work for our customers. So- >> Thank you. >> Yeah, and this is why I'm so proud to be working at this team because our focus is really to help our customers to simplify all the you know, financial heavy lifting with taxes and also with small businesses. We also do a lot of work in extracting information from small business documents like bill, receipts, different bank statements. Yeah, so this is really exciting for me, the opportunity to work to apply data science and machine learning to solution that actually help people. Yeah >> Yeah, in the past years there have been more and more digital products emerging that needs some sort of data security. And how did your team, or has your team developed in the past years with more and more products or companies offering digital services? >> Yeah, so can you clarify the question again? Sorry. >> Yeah, have you seen that you have more customers? Like has your team expanded in the past years with more digital companies starting that need kind of data security? >> Well, definitely. I think, you know, since I joined Intuit, I joined like five and a half years ago back when I was in Tel Aviv. I recently moved to the Bay Area. So when I joined, there were like a dozens of data scientists and machine learning engineers on Intuit. And now there are a few hundreds. So we've definitely grown with the year and there are so many new places we can apply machine learning to help our customers. So this is amazing, so much we can do with machine learning to get more money in the pocket of our customers and make them do less work. >> I like both of those. More money in my pocket and less work. That's awesome. >> Exactly. >> So keep going Intuit. But one of the things that is so cool is just the the abstraction of the complexity that Intuit's doing. I upload documents or it scans my receipts. I was just in Barcelona last week all these receipts and conversion euros to dollars and it takes that complexity away from the end user who doesn't know all that's going on in the background, but you're making people's lives simpler. Unfortunately, we all have to pay taxes, most of us should. And of course we're in tax season right now. And so it's really cool what you're doing with ML and data science to make fundamental processes to people's lives easier and just a little bit less complicated. >> Definitely. And I think that's what's also really amazing about Intuit it, is how it combines human in the loop as well as AI. Because in some of the tax situation it's very complicated maybe to do it yourself. And then there's an option to work with an expert online that goes on a video with you and helps you do your taxes. And the expert's work is also accelerated by AI because we build tools for those experts to do the work more efficiently. >> And that's what it's all about is you know, using data to be more efficient, to be faster, to be smarter, but also to make complicated processes in our daily lives, in our business lives just a little bit easier. One of the things I've been geeking out about recently is ChatGPT. I was using it yesterday. I was telling everyone I was asking it what's hot in data science and I didn't know would it know what hot is and it did, it gave me trends. But one of the things that I was so, and Hannah knows I've been telling this all day, I was so excited to learn over the weekend that the the CTO of OpenAI is a female. I didn't know that. And I thought why are we not putting her on a pedestal? Because people are likening ChatGPT to like the launch of the iPhone. I mean revolutionary. And here we have what I think is exciting for all of us females, whether you're in tech or not, is another role model. Because really ultimately what WiDS is great at doing is showcasing women in technical roles. Because I always say you can't be what you can't see. We need to be able to see more role models, female role role models, underrepresented minorities of course men, because a lot of my sponsors and mentors are men, but we need more women that we can look up to and see ah, she's doing this, why can't I? Talk to me about how you stay the course in data science. What excites you about the potential, the opportunities based on what you've already accomplished what inspires you to continue and be one of those females that we say oh my God, I could be like Shir. >> I think that what inspires me the most is the endless opportunities that we have. I think we haven't even started tapping into everything that we can do with generative AI, for example. There's so much that can be done to further help you know, people make more money and do less work because there's still so much work that we do that we don't need to. You know, this is with Intuit, but also there are so many other use cases like I heard today you know, with the talk about the police. So that was really exciting how you can apply machine learning and data to actually help people, to help people that been through wrongful things. So I was really moved by that. And I'm also really excited about all the medical applications that we can have with data. >> Yeah, yeah. It's true that data science is so diverse in terms of what fields it can cover but it's equally important to have diverse teams and have like equity and inclusion in your teams. Where is Intuit at promoting women, non-binary minorities in your teams to progress data science? >> Yeah, so I have so much to say on this. >> Good. >> But in my work in Tel Aviv, I had the opportunity to start with Intuit women in data science branch in Tel Aviv. So that's why I'm super excited to be here today for that because basically this is the original conference, but as you know, there are branches all over the world and I got the opportunity to lead the Tel Aviv branch with Israel since 2018. And we've been through already this year it's going to be it's next week, it's going to be the sixth conference. And every year our number of submission to make talk in the conference doubled itself. >> Nice. >> We started with 20 submission, then 50, then 100. This year we have over 200 submissions of females to give talk at the conference. >> Ah, that's fantastic. >> And beyond the fact that there's so much traction, I also feel the great impact it has on the community in Israel because one of the reason we started WiDS was that when I was going to conferences I was seeing so little women on stage in all the technical conferences. You know, kind of the reason why I guess you know, Margaret and team started the WiDS conference. So I saw the same thing in Israel and I was always frustrated. I was organizing PyData Meetups as you mentioned and I was always having such a hard time to get female speakers to talk. I was trying to role model, but that's not enough, you know. We need more. So once we started WiDS and people saw you know, so many examples on the stage and also you know females got opportunity to talk in a place for that. Then it also started spreading and you can see more and more female speakers across other conferences, which are not women in data science. So I think just the fact that Intuits started this conference back in Israel and also in Bangalore and also the support Intuit does for WiDS in Stanford here, it shows how much WiDS values are aligned with our values. Yeah, and I think that to chauffeur that I think we have over 35% females in the data science and machine learning engineering roles, which is pretty amazing I think compared to the industry. >> Way above average. Yeah, absolutely. I was just, we've been talking about some of the AnitaB.org stats from 2022 showing that 'cause usually if we look at the industry to you point, over the last, I don't know, probably five, 10 years we're seeing the number of female technologists around like a quarter, 25% or so. 2022 data from AnitaB.org showed that that number is now 27.6%. So it's very slowly- >> It's very slowly increasing. >> Going in the right direction. >> Too slow. >> And that representation of women technologists increase at every level, except intern, which I thought was really interesting. And I wonder is there a covid relation there? >> I don't know. >> What do we need to do to start opening up the the top of the pipeline, the funnel to go downstream to find kids like you when you were younger and always interested in engineering and things like that. But the good news is that the hiring we've seen improvements, but it sounds like Intuit is way ahead of the curve there with 35% women in data science or technical roles. And what's always nice and refreshing that we've talked, Hannah about this too is seeing companies actually put action into initiatives. It's one thing for a company to say we're going to have you know, 50% females in our organization by 2030. It's a whole other ball game to actually create a strategy, execute on it, and share progress. So kudos to Intuit for what it's doing because that is more companies need to adopt that same sort of philosophy. And that's really cultural. >> Yeah. >> At an organization and culture can be hard to change, but it sounds like you guys kind of have it dialed in. >> I think we definitely do. That's why I really like working and Intuit. And I think that a lot of it is with the role modeling, diversity and inclusion, and by having women leaders. When you see a woman in leadership position, as a woman it makes you want to come work at this place. And as an evidence, when I build the team I started in Israel at Intuit, I have over 50% women in my team. >> Nice. >> Yeah, because when you have a woman in the interviewers panel, it's much easier, it's more inclusive. That's why we always try to have at least you know, one woman and also other minorities represented in our interviews panel. Yeah, and I think that in general it's very important as a leader to kind of know your own biases and trying to have defined standard and rubrics in how you evaluate people to avoid for those biases. So all of that inclusiveness and leadership really helps to get more diversity in your teams. >> It's critical. That thought diversity is so critical, especially if we talk about AI and we're almost out of time, I just wanted to bring up, you brought up a great point about the diversity and equity. With respect to data science and AI, we know in AI there's biases in data. We need to have more inclusivity, more representation to help start shifting that so the biases start to be dialed down and I think a conference like WiDS and it sounds like someone like you and what you've already done so far in the work that you're doing having so many females raise their hands to want to do talks at events is a good situation. It's a good scenario and hopefully it will continue to move the needle on the percentage of females in technical roles. So we thank you Shir for your time sharing with us your story, what you're doing, how Intuit and WiDS are working together. It sounds like there's great alignment there and I think we're at the tip of the iceberg with what we can do with data science and inclusion and equity. So we appreciate all of your insights and your time. >> Thank you very much. >> All right. >> I enjoyed very, very much >> Good. We hope, we aim to please. Thank you for our guests and for Hannah Freitag. This is Lisa Martin coming to you live from Stanford University. This is our coverage of the eighth Annual Women in Data Science Conference. Stick around, next guest will be here in just a minute.

(upbeat music) >> Hello everyone, welcome back to theCUBE's coverage of Cloud Native SecurityCon North America 2023. Obviously, CUBE's coverage with our CUBE Center Report. We're not there on the ground, but we have folks and our CUBE Alumni there. We have entrepreneurs there. Of course, we want to be there in person, but we're remote. We've got Ben Hirschberg, CTO and Co-Founder of Armo, a cloud native security startup, well positioned in this industry. He's there in Seattle. Ben, thank you for coming on and sharing what's going on with theCUBE. >> Yeah, it's great to be here, John. >> So we had written on you guys up on SiliconANGLE. Congratulations on your momentum and traction. But let's first get into what's going on there on the ground? What are some of the key trends? What's the most important story being told there? What is the vibe? What's the most important story right now? >> So I think, I would like to start here with the I think the most important thing was that I think the event is very successful. Usually, the Cloud Native Security Day usually was part of KubeCon in the previous years and now it became its own conference of its own and really kudos to all the organizers who brought this up in, actually in a short time. And it wasn't really clear how many people will turn up, but at the end, we see a really nice turn up and really great talks and keynotes around here. I think that one of the biggest trends, which haven't started like in this conference, but already we're talking for a while is supply chain. Supply chain is security. I think it's, right now, the biggest trend in the talks, in the keynotes. And I think that we start to see companies, big companies, who are adopting themselves into this direction. There is a clear industry need. There is a clear problem and I think that the cloud native security teams are coming up with tooling around it. I think for right now we see more tools than adoption, but the adoption is always following the tooling. And I think it already proves itself. So we have just a very interesting talk this morning about the OpenSSL vulnerability, which was I think around Halloween, which came out and everyone thought that it's going to be a critical issue for the whole cloud native and internet infrastructure and at the end it turned out to be a lesser problem, but the reason why I think it was understood that to be a lesser problem real soon was that because people started to use (indistinct) store software composition information in the environment so security teams could look into, look up in their systems okay, what, where they're using OpenSSL, which version they are using. It became really soon real clear that this version is not adopted by a wide array of software out there so the tech surface is relatively small and I think it already proved itself that the direction if everyone is talking about. >> Yeah, we agree, we're very bullish on this move from the Cloud Native Foundation CNCF that do the security conference. Amazon Web Services has re:Invent. That's their big show, but they also have re:Inforce, the security show, so clearly they work together. I like the decoupling, very cohesive. But you guys have Kubescape of Kubernetes security. Talk about the conversations that are there and that you're hearing around why there's different event what's different around KubeCon and CloudNativeCon than this Cloud Native SecurityCon. It's not called KubeSucSecCon, it's called Cloud Native SecurityCon. What's the difference? Are people confused? Is it clear? What's the difference between the two shows? What are you hearing? >> So I think that, you know, there is a good question. Okay, where is Cloud Native Computing Foundation came from? Obviously everyone knows that it was somewhat coupled with the adoption of Kubernetes. It was a clear understanding in the industry that there are different efforts where the industry needs to come together without looking be very vendor-specific and try to sort out a lot of issues in order to enable adoption and bring great value and I think that the main difference here between KubeCon and the Cloud Native Security Conference is really the focus, and not just on Kubernetes, but the whole ecosystem behind that. The way we are delivering software, the way we are monitoring software, and all where Kubernetes is only just, you know, maybe the biggest clog in the system, but, you know, just one of the others and it gives great overview of what you have in the whole ecosystem. >> Yeah, I think it's a good call. I would add that what I'm hearing too is that security is so critical to the business model of every company. It's so mainstream. The hackers have a great business model. They make money, their costs are lower than the revenue. So the business of hacking in breaches, ransomware all over the place is so successful that they're playing offense, everyone's playing defense, so it's about time we can get focus to really be faster and more nimble and agile on solving some of these security challenges in open source. So I think that to me is a great focus and so I give total props to the CNC. I call it the event operating system. You got the security group over here decoupled from the main kernel, but they work together. Good call and so this brings back up to some of the things that are going on so I have to ask you, as your startup as a CTO, you guys have the Kubescape platform, how do you guys fit into the landscape and what's different from your tools for Kubernetes environments versus what's out there? >> So I think that our journey is really interesting in the solution space because I think that our mode really tries to understand where security can meet the actual adoption because as you just said, somehow we have to sort out together how security is going to be automated and integrated in its best way. So Kubescape project started as a Kubernetes security posture tool. Just, you know, when people are really early in their adoption of Kubernetes systems, they want to understand whether the installation is is secure, whether the basic configurations are look okay, and giving them instant feedback on that, both in live systems and in the CICD, this is where Kubescape came from. We started as an open source project because we are big believers of open source, of the power of open source security, and I can, you know I think maybe this is my first interview when I can say that Kubescape was accepted to be a CNCF Sandbox project so Armo was actually donating the project to the CNCF, I think, which is a huge milestone and a great way to further the adoption of Kubernetes security and from now on we want to see where the users in Armo and Kubescape project want to see where the users are going, their Kubernetes security journey and help them to automatize, help them to to implement security more fast in the way the developers are using it working. >> Okay, if you don't mind, I want to just get clarification. What's the difference between the Armo platform and Kubescape because you have Kubescape Sandbox project and Armo platform. Could you talk about the differences and interaction? >> Sure, Kubescape is an open source project and Armo platform is actually a managed platform which runs Kubescape in the cloud for you because Kubescape is part, it has several parts. One part is, which is running inside the Kubernetes cluster in the CICD processes of the user, and there is another part which we call the backend where the results are stored and can be analyzed further. So Armo platform gives you managed way to run the backend, but I can tell you that backend is also, will be available within a month or two also for everyone to install on their premises as well, because again, we are an open source company and we are, we want to enable users, so the difference is that Armo platform is a managed platform behind Kubescape. >> How does Kubescape differ from closed proprietary sourced solutions? >> So I can tell you that there are closed proprietary solutions which are very good security solutions, but I think that the main difference, if I had to pick beyond the very specific technicalities is the worldview. The way we see that our user is not the CISO. Our user is not necessarily the security team. From our perspective, the user is the DevOps and the developers who are working on the Kubernetes cluster day to day and we want to enable them to improve their security. So actually our approach is more developer-friendly, if I would need to define it very shortly. >> What does this risk calculation score you guys have in Kubscape? That's come up and we cover that in our story. Can you explain to the folks how that fits in? Is it Kubescape is the platform and what's the benefit, what's the purpose? >> So the risk calculation is actually a score we are giving to clusters in order for the users to understand where they are standing in the general population, how they are faring against a perfect hardened cluster. It is based on the number of different tests we are making. And I don't want to go into, you know, the very specifics of the mathematical functions, but in general it takes into account how many functions are failing, security tests are failing inside your cluster. How many nodes you are having, how many workloads are having, and creating this number which enables you to understand where you are standing in the global, in the world. >> What's the customer value that you guys pitching? What's the pitch for the Armo platform? When you go and talk to a customer, are they like, "We need you." Do they come to you? Is it word of mouth? You guys have a strategy? What's the pitch? What's so appealing to the customers? Why are they enthusiastic about you guys? >> So John, I can tell you, maybe it's not so easy to to say the words, but I nearly 20 years in the industry and though I've been always around cyber and the defense industry and I can tell you that I never had this journey where before where I could say that the the customers are coming to us and not we are pitching to customers. Simply because people want to, this is very easy tool, very very easy to use, very understandable and it very helps the engineers to improve security posture. And they're coming to us and they're saying, "Well, awesome, okay, how we can like use it. Do you have a graphical interface?" And we are pointing them to the Armor platform and they are falling in love and coming to us even more and we can tell you that we have a big number of active users behind the platform itself. >> You know, one of the things that comes up every time at KubeCon and Cloud NativeCon when we're there, and we'll be in Amsterdam, so folks watching, you know, we'll see onsite, developer productivity is like the number one thing everyone talks about and security is so important. It's become by default a blocker or anchor or a drag on productivity. This is big, the things that you're mentioning, easy to use, engineering supporting it, developer adoption, you know we've always said on theCUBE, developers will be the de facto standards bodies by their choices 'cause developers make all the decisions. So if I can go faster and I can have security kind of programmed in, I'm not shifting left, it's just I'm just having security kind of in there. That's the dream state. Is that what you guys are trying to do here? Because that's the nirvana, everyone wants to do that. >> Yeah, I think your definition is like perfect because really we had like this, for a very long time we had this world where we decoupled security teams from developers and even for sometimes from engineering at all and I think for multiple reasons, we are more seeing a big convergence. Security teams are becoming part of the engineering and the engineering becoming part of the security and as you're saying, okay, the day-to-day world of developers are becoming very tangled up in the good way with security, so the think about it that today, one of my developers at Armo is creating a pull request. He's already, code is already scanned by security scanners for to test for different security problems. It's already, you know, before he already gets feedback on his first time where he's sharing his code and if there is an issue, he already can solve it and this is just solving issues much faster, much cheaper, and also you asked me about, you know, the wipe in the conference and we know no one can deny the current economic wipe we have and this also relates to security teams and security teams has to be much more efficient. And one of the things that everyone is talking, okay, we need more automation, we need more, better tooling and I think we are really fitting into this. >> Yeah, and I talked to venture capitalists yesterday and today, an angel investor. Best time for startup is right now and again, open source is driving a lot of value. Ben, it's been great to have you on and sharing with us what's going on on the ground there as well as talking about some of the traction you have. Just final question, how old's the company? How much funding do you have? Where you guys located? Put a plug in for the company. You guys looking to hire? Tell us about the company. Were you guys located? How much capital do you have? >> So, okay, the company's here for three years. We've passed a round last March with Tiger and Hyperwise capitals. We are located, most of the company's located today in Israel in Tel Aviv, but we have like great team also in Ukraine and also great guys are in Europe and right now also Craig Box joined us as an open source VP and he's like right now located in New Zealand, so we are a really global team, which I think it's really helps us to strengthen ourselves. >> Yeah, and I think this is the entrepreneurial equation for the future. It's really great to see that global. We heard that in Priyanka Sharma's keynote. It's a global culture, global community. >> Right. >> And so really, really props you guys. Congratulations on Armo and thanks for coming on theCUBE and sharing insights and expertise and also what's happening on the ground. Appreciate it, Ben, thanks for coming on. >> Thank you, John. >> Okay, cheers. Okay, this is CUB coverage here of the Cloud Native SecurityCon in North America 2023. I'm John Furrier for Lisa Martin, Dave Vellante. We're back with more of wrap up of the event after this short break. (gentle upbeat music)

>> Good afternoon everyone, and welcome back to theCUBE where we're coming to you live from Detroit, Michigan at KubeCon and Cloud Native Con. We're going to keep theCUBE puns coming this afternoon because we have the pleasure of being joined by not one but two guests from Kubiya. John Furrier, my wonderful co-host. You're familiar with these guys. You just chatted with them last week. >> We broke the story of their launch and featured them on theCUBE in our studio conversation. This is a great segment. Real innovative company with lofty goals, and they're really good ones. Looking forward to it. >> If that's not a tease to keep watching I don't know what is. (John laughs) Without further ado, on that note, allow me to introduce Amit and Shaked who are here to tell us all about Kubiya. And I'm going to blow the pitch for you a little bit just because this gets me excited. (all laugh) They're essentially the Siri of DevOps, but that means you can, you can create using voice or chat or any medium. Am I right? Is this? Yeah? >> You're hired. >> Excellent. (all laugh) >> Okay. >> We'll take it. >> Who knows what I'll tell the chat to do or what I'll, what I will control with my voice, but I love where you're. >> Absolutely. I'll just give the high level. Conversational AI for the world of DevOps. Kind of redefining how self-service DevOps is supposed to be essentially accessed, right? As opposed to just having siloed information. You know, having different platforms that require an operator or somebody who's using it to know exactly how they're accessing what they're doing and so forth. Essentially, the ability to express your intent in natural language, English, or any language I use. >> It's quite literally the language barrier sometimes. >> Precisely. >> Both from the spoken as well as code language. And it sounds like you're eliminating that as an obstacle. >> We're essentially saying, turn simple, complex cast into simple conversations. That's, that's really what we're saying here. >> So let's get into the launch. You just launched a fresh startup. >> Yeah, yeah, yeah. >> Yeah. >> So you guys are going to take on the world. Lofty goals if that. I had the briefing. Where's the origination story come from? What, how did you guys get here? Was it a problem that you saw, you were experiencing, an itch you were scratching? What was the motivation and what's the origination story? >> Shaked: So. >> Amit: Okay, go first please. >> Essentially everything started with my experience as being an operator. I used to be a DevOps engineer for a few years for a large (indistinct) company. On later stages I even managed an SRE team. So all of these access requires Q and A staff is something that I experience nonstop on Slack or Teams, all of these communication channels. And usually I find out that everything happens from the chat. So essentially back then I created a chat bot. I connect this chat bot to the different organizational tools, and instead of the developers approaching to me or the team using the on call channel or directly they will just approach the bot. But essentially the bot was very naive, and they still needed to know what they, they want to do inside the bot. But it's still managed to solve 70% of the complexity and the toil on us as a team so we could focus on innovation. So Kubiya's a more advanced version of it. Basically with Kubiya you can define what we call workflows, and we convert all of these complexity of access request into simple conversations that the end users, which could be developers, but not only, are having with a DevOps team. So that's essentially how it works, and we're very excited about it. >> So you were up all night answering the same question over and over again. (all laugh) And you said, Hey, screw it. I'm going to just create a bot, bot myself up. (Shaked laughs) But it gets at something important. I mean, I'm not just joking. It probably happened, right? That was probably the case. You were up all night telling. >> Yeah, I mean it was usually stuff that we didn't need to maintain. It was training requests and questions that just keep on repeating themselves. And actually we were in Israel, but we sell three different time zones of developers. So all of these developers, as soon as the day finishes in Israel, the day in the US started. So they will approach us from the US. So we didn't really sleep. (all laugh) As with these requests non-stop. >> It's that 24 hour. >> Yeah, yeah. 24 hours for a single team. >> So the world clock global (indistinct) catches you a little sometimes. Yeah. >> Yeah, exactly. >> So you basically take all the things that you know that are common and then make a chat bot answering as if you're you. But this brings up the whole question of chat bot utilization. There's been a lot of debate in the AI circles that chat bots really haven't made it. They're not, they haven't been good enough. So 'cause NLP and other trivial, >> Amit: Sure. or things that haven't really clicked. What's different now? How do you guys see your approach cracking the code to go that kind of reasoning level? Bots can reason? Now we're in business. >> Yeah. Most of the chat bots are general purpose, right? We're coming with the domain expertise. We know the pain from the inside. We know how the operators want to define such conversations that users might have with the virtual assistant. So we combined all of the technical tools that are needed in order to get it going. So we have a a DSL, domain specific language, where the operators can define these easy conversations and combine all of the different organizational tools which can be done using DSDK. Besides this fact, we have a no code, for less technical people to create such workflows even with no code interface. And we have a CLI, which you could use to leverage the power of the virtual assist even right from your terminal. So that's how I see the domain expertise coming in that we have different communication channels for everyone that needs to be inside the loop. >> That's awesome. >> And I, and I can add to that. So that's one element, which is the domain expertise. The other one is really our huge differentiator, the ability to let the end users influence the system itself. So essentially. >> John: Like how? Give me an example. >> Sure. We call it teach me feature, but essentially if you have any type of a request and the system hasn't created an automation or hasn't, doesn't recognize it, you can go ahead and bind that into your intent and next time, and you can define the scope for yourself only, for the team, or even for the entire organization that actually has to have permission to access the request and control and so on. >> Savannah: That's something. Yeah, I love that as a knowledge base. I mean a custom tool kit. >> Absolutely. >> And I like that you just said for the individual. So let's say I have some crazy workflows that I don't need anybody else to know about. >> 100 percent. >> I can customize my experience. >> Mm hmm. >> Do you see your, this is really interesting, and I'm, it's surprising to me we haven't seen a lot of players in this space before because what you're doing makes a lot of sense to me, especially as someone who is less technical. >> Yeah. >> Do you view yourselves as a gateway tool for more folks to be involved in more complex technology? >> So, so I'll take that. It's not that we haven't seen advanced virtual assistants. They've existed in different worlds. >> Savannah: Right. >> Up until now they've existed more in CRM tools. >> Savannah: Right. >> Call centers, right? >> Shaked: Yeah. >> You go on to Ralph Lauren, Calvin Klein, you go and chat with. Now imagine you can bring that into a world of dev tools that has high domain expertise, high technical amplitude, and now you can go and combine the domain expertise with the accessibility of conversational AI. That's, that's a unique feature here. >> What's the biggest thing that's surprised you with the launch so far? The reaction to the name, Kubiya, which is Cube in Hebrew. >> Amit: Yes. >> Apparently. >> Savannah: Which I love. >> Which by the way, you know, we have a TM and R on our Cube. (all laugh) So we can talk, you know, license rights. >> Let's drop the trademark rules today, John, here. We're here to share information. Confuse the audience. Sorry about that, by the way. (all laugh) >> We're an open source, inclusive culture. We'll let it slide this time. >> The KubeCon, theCUBE, and Kubiya. (John laughs) In the Hebrew we have this saying, third time we all have ice cream. So. (all laugh) >> I think there's some ice cream over there actually. >> There is. >> Yeah, yeah. There you go. >> All kidding aside, all fun. What's, what's been the reaction? Got some press coverage. We had the launch. You guys launched with theCUBE in here, big reception. What's been the common feedback? >> And really, I think I expected this, but I didn't expect this much. Really, the fact that people really believe in our thesis, really expect great things from us, right? We've starting to working with. >> Savannah: Now the pressure's on. >> Rolling out dozens of POCs, but even that requires obviously a lot of attention to the detail, which we're rolling out. This is effectively what we're seeing. People love the fact that you have a unique and fresh way to approaching the self-service which really has been stalled for a while. And we've recognized that. I think our thesis is where we. >> Okay, so as a startup you have lofty goals, you have investors now. >> Amit: Yeah. >> Congratulations. >> Amit: Thank you. >> They're going to want to keep the traction going, but as a north star, what's your, what are you going to, what are you going to take? What territory are you going to take? Is it new territory? Are you eating someone's lunch? Who are you going to be competing with? What's the target? What's the, what's the? >> Sure, sure. >> I'm sure you guys have it. Who are you takin' over? >> I think the gateway, the entry point to every organization is a bottleneck. You solve the hard problem first. That's where you can go into other directions, and you can imagine where other operational workflows and pains that we can help solve once we have essentially the DevOps. >> John: So you see this as greenfield, new opportunity? >> I believe so. >> Is there any incumbent you see out there? An old stodgy? >> Today we're on internal developer platform service catalog type of, you know, use cases. >> John: Yeah. >> But that's kind of where we can grow from there and have the ecosystem essentially embrace us. >> John: How about the technology platform? >> Amit: Yeah. >> What's the vision for the innovation? >> Essentially want to be able to integrate with all of the different cloud providers, cloud solutions, SaaS platforms, and take the atlas approach that they were using right to the chats from everywhere to anywhere. So essentially we want in the end that users will be able to do anything that they need inside all of these complicated platforms, which some of them are totally complicated, with plain English. >> So what's the biggest challenge for you then on that front leading the technology side of the team? >> So I would say that the conversational AI part is truly complicated because it requires to extract many types of intentions from different types of users and also integrate with so many tools and solutions. >> Savannah: Yeah. So it requires a lot of thinking, a lot of architecture, but we are doing it just fine. >> Awesome. What do you guys think about KubeCon this week? What's, what's the top story that you see emerging out of this? Just generally as an industry observer, what's the most important? >> Savannah: Maybe it's them. Announcement halo. >> What's the cover story that you see? (all laugh) I mean you guys are in the innovation intent-based infrastructure. I get that. >> So obviously everyone's looking to diversify their engineering, diversify their platforms to make sure they're as decoupled from the main CSPs as possible. So being able to build their own, and we're really helping enable a lot of that in there. We're really helping improve upon that open source together with managed platforms can really play a very nice game together. So. >> Awesome. So are you guys hiring, recruiting? Tell us about the team DNA. Now you're in Tel Aviv. You're in the bay. >> Shaked: Check our openings on LinkedIn. (all laugh) >> We have a dozen job postings on our website. Obviously engineering and sales then go to market. >> So when theCUBE comes to Tel Aviv, and we have a location there. >> Yeah. >> Will you be, share some space? >> Savannah: Is this our Tel Aviv office happening right now? I love this. >> Amit: We will be hosting you. >> John: theCube with a C and Kube with a K over there. >> Yeah. >> All one happy family. >> Would love that. >> Get some ice cream. >> Would love that. >> All right, so last question for you all. You just had a very big exciting announcement. It's a bit of a coming out party for you. What do you hope to be able to say in a year that you can't currently say right now? When you join us on theCUBE next time? >> No, no, it's absolutely. I think our thesis that you can turn conversations into operations. It's, it sounds obvious to you when you think about it, but it's not trivial when you look into the workflows, into the operations. The fact that we can actually go a year from today and say we got hundreds of customers, happy customers who've proven the thesis or sharing knowledge between themselves, that would be euphoric for us. >> All right. >> You really are about helping people. >> Absolutely. >> It doesn't seem like it's a lip service from both of you. >> No. (all laugh) >> Is there going to be levels of bot, like level one bot level two, level three, and then finally the SRE gets on the phone? Is that like some point? >> Is there going to be bot singularity? Is that, is that what we're exploring right now? (overlapping chatter) >> Some kind of escalation bot. >> Enlightenment with bots. >> We actually planning a feature we want to call a handoff where a human in the loop is required, which often is needed. Machine cannot do it alone. We'll just. >> Yeah, I think it makes total sense for geos, ops at the same. >> Shaked: Yeah. >> But not exactly the same. Really good, good solution. I love the direction. Congratulations on the launch. >> Shaked: Thank you so much. >> Amit: Thank you very much. >> Yeah, that's very exciting. You can obviously look, check out that news on Silicon Angle since we had the pleasure of breaking it. >> Absolutely. >> If people would like to say hi, stalk you on the internet, where's the best place for them to do that? >> Be on our Twitter and LinkedIn handles of course. So we have kubiya.ai. We also have a free trial until the end of the year, and we also have free forever tier, that people can sign up, play, and come say hi. I mean, we'd love to chat. >> I love it. Well, Amit, Shaked, thank you so much for being with us. >> Shaked: Thank you so much. >> John, thanks for sitting to my left for the entire day. I sincerely appreciate it. >> Just glad I can help out. >> And thank you all for tuning in to this wonderful edition of theCUBE Live from Detroit at KubeCon. Who knows what my voice will be controlling next, but either way, I hope you are there to find out. >> Amit: Love it.

(upbeat music) >> Hello everyone, welcome to this special Cube conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE in theCUBE Studios. We've got a special video here. We love when we have startups that are launching. It's an exclusive video of a hot startup that's launching. Got great reviews so far. You know, word on the street is, they got something different and unique. We're going to' dig into it. Amit Govrin who's the CEO and co-founder of Kubiya, which stands for Cube in Hebrew, and they're headquartered in Bay Area and in Tel Aviv. Amit, congratulations on the startup launch and thanks for coming in and talk to us in theCUBE >> Thank you, John, very nice to be here. >> So, first of all, a little, 'cause we love the Cube, 'cause theCUBE's kind of an open brand. We've never seen the Cube in Hebrew, so is that true? Kubiya is? >> Kubiya literally means cube. You know, clearly there's some additional meanings that we can discuss. Obviously we're also launching a KubCon, so there's a dual meaning to this event. >> KubCon, not to be confused with CubeCon. Which is an event we might have someday and compete. No, I'm only kidding, good stuff. I want to get into the startup because I'm intrigued by your story. One, you know, conversational AI's been around, been a category. We've seen chat bots be all the rage and you know, I kind of don't mind chat bots on some sites. I can interact with some, you know, form based knowledge graph, whatever, knowledge database and get basic stuff self served. So I can see that, but it never really scaled or took off. And now with Cloud Native kind of going to the next level, we're starting to see a lot more open source and a lot more automation, in what I call AI as code or you know, AI as a service, machine learning, developer focused action. I think you guys might have an answer there. So if you don't mind, could you take a minute to explain what you guys are doing, what's different about Kubiya, what's happening? >> Certainly. So thank you for that. Kubiya is what we would consider the first, or one of the first, advanced virtual assitants with a domain specific expertise in DevOps. So, we respect all of the DevOps concepts, GitOps, workflow automation, of those categories you've mentioned, but also the added value of the conversational AI. That's really one of the few elements that we can really bring to the table to extract what we call intent based operations. And we can get into what that means in a little bit. I'll save that maybe for the next question. >> So the market you're going after is kind of, it's, I love to hear starters when they, they don't have a Gartner Magic quadrant, they can fit nicely, it means they're onto something. What is the market you're going after? Because you're seeing a lot of developers driving a lot of the key successes in DevOps. DevOps has evolved to the point where, and DevSecOps, where developers are driving the change. And so having something that's developer focused is key. Are you guys targeting the developers, IT buyers, cloud architects? Who are you looking to serve with this new opportunity? >> So essentially self-service in the world of DevOps, the end user typically would be a developer, but not only, and obviously the operators, those are the folks that we're actually looking to help augment a lot of their efforts, a lot of the toil that they're experiencing in a day to day. So there's subcategories within that. We can talk about the different internal developer tools, or platforms, shared services platforms, service catalogs are tangential categories that this kind of comes on. But on top of that, we're adding the element of conversational AI. Which, as I mentioned, that's really the "got you". >> I think you're starting to see a lot of autonomous stuff going on, autonomous pen testing. There's a company out there doing I've seen autonomous AI. Automation is a big theme of it. And I got to ask, are you guys on the business side purely in the cloud? Are you born in the cloud, is it a cloud service? What's the product choice there? It's a service, right? >> Software is a service. We have the classic, Multi-Tenancy SAAS, but we also have a hybrid SAAS solution, which allows our customers to run workflows using remote runners, essentially hosted at their own location. >> So primary cloud, but you're agnostic on where they could consume, how they want to' consume the product. >> Technology agnostic. >> Okay, so that's cool. So let's get into the problem you're solving. So take me through, this will drive a lot of value here, when you guys did the company, what problems did you hone in on and what are you guys seeing as the core problem that you solve? >> So we, this is a unique, I don't know how unique, but this is a interesting proposition because I come from the business side, so call it the top down. I've been in enterprise sales, I've been in a CRO, VP sales hat. My co-founder comes from the bottom up, right? He ran DevOps teams and SRE teams in his previous company. That's actually what he did. So, we met each other halfway, essentially with me seeing a lot of these problems of self-service not being so self-service after all, platforms hitting walls with adoption. And he actually created his own self-service platform, within his last company, to address his own personal pains. So we essentially kind of met with both perspectives. >> So you're absolutely hardcore on self-service. >> We're enabling self-service. >> And that basically is what everybody wants. I mean, the developers want self-service. I mean, that's kind of like, you know, that's the nirvana. So take us through what you guys are offering, give us an example of use cases and who's buying your product, why, and take us through that whole piece. >> Do you mind if I take a step back and say why we believe self-service has somewhat failed or not gotten off. >> Yeah, absolutely. >> So look, this is essentially how we're looking at it. All the analysts and the industry insiders are talking about self-service platforms as being what's going to' remove the dependency of the operator in the loop the entire time, right? Because the operator, that scarce resource, it's hard to hire, hard to train, hard to retain those folks, Developers are obviously dependent on them for productivity. So the operators in this case could be a DevOps, could be a SecOps, it could be a platform engineer. It comes in different flavors. But the common denominator, somebody needs an access request, provisioning a new environment, you name it, right? They go to somebody, that person is operator. The operator typically has a few things on their plate. It's not just attending and babysitting platforms, but it's also innovating, spinning up, and scaling services. So they see this typically as kind of, we don't really want to be here, we're going to' go and do this because we're on call. We have to take it on a chin, if you may, for this. >> It's their child, they got to' do it. >> Right, but it's KTLOs, right, keep the lights on, this is maintenance of a platform. It's not what they're born and bred to do, which is innovate. That's essentially what we're seeing, we're seeing that a lot of these platforms, once they finally hit the point of maturity, they're rolled out to the team. People come to serve themselves in platform, and low and behold, it's not as self-service as it may seem. >> We've seen that certainly with Kubernetes adoption being, I won't say slow, it's been fast, but it's been good. But I think this is kind of the promise of what SRE was supposed to be. You know, do it once and then babysit in the sense of it's working and automated. Nothing's broken yet. Don't call me unless you need something, I see that. So the question, you're trying to make it easier then, you're trying to free up the talent. >> Talent to operate and have essentially a human, like in the loop, essentially augment that person and give the end users all of the answers they require, as if they're talking to a person. >> I mean it's basically, you're taking the virtual assistant concept, or chat bot, to a level of expertise where there's intelligence, jargon, experience into the workflows that's known. Not just talking to chat bot, get a support number to rebook a hotel room. >> We're converting operational workflows into conversations. >> Give me an example, take me through an example. >> Sure, let's take a simple example. I mean, not everyone provisions EC2's with two days (indistinct). But let's say you want to go and provision new EC2 instances, okay? If you wanted to do it, you could go and talk to the assistant and say, "I want to spin up a new server". If it was a human in the loop, they would ask you the following questions: what type of environment? what are we attributing this to? what type of instance? security groups, machine images, you name it. So, these are the questions that typically somebody needs to be armed with before they can go and provision themselves, serve themselves. Now the problem is users don't always have these questions. So imagine the following scenario. Somebody comes in, they're in Jira ticket queue, they finally, their turn is up and the next question they don't have the answer to. So now they have to go and tap on a friend, or they have to go essentially and get that answer. By the time they get back, they lost their turn in queue. And then that happens again. So, they lose a context, they lose essentially the momentum. And a simple access request, or a simple provision request, can easily become a couple days of ping pong back and forth. This won't happen with the virtual assistant. >> You know, I think, you know, and you mentioned chat bots, but also RPA is out there, you've seen a lot of that growth. One of the hard things, and you brought this up, I want to get your reaction to, is contextualizing the workflow. It might not be apparent, but the answer might be there, it disrupts the entire experience at that point. RPA and chat bots don't have that contextualization. Is that what you guys do differently? Is that the unique flavor here? Is that difference between current chat bots and RPA? >> The way we see it, I alluded to the intent based operations. Let me give a tangible experience. Even not from our own world, this will be easy. It's a bidirectional feedback loop 'cause that's actually what feeds the context and the intent. We all know Waze, right, in the world of navigation. They didn't bring navigation systems to the world. What they did is they took the concept of navigation systems that are typically satellite guided and said it's not just enough to drive down the 280, which typically have no traffic, right, and to come across traffic and say, oh, why didn't my satellite pick that up? So they said, have the end users, the end nodes, feed that direction back, that feedback, right. There has to be a bidirectional feedback loop that the end nodes help educate the system, make the system be better, more customized. And that's essentially what we're allowing the end users. So the maintenance of the system isn't entirely in the hands of the operators, right? 'Cause that's the part that they dread. And the maintenance of the system is democratized across all the users that they can teach the system, give input to the system, hone in the system in order to make it more of the DNA of the organization. >> You and I were talking before you came on this camera interview, you said playfully that the Siri for DevOps, which kind of implies, hey infrastructure, do something for me. You know, we all know Siri, so we get that. So that kind of illustrates kind of where the direction is. Explain why you say that, what does that mean? Is that like a NorthStar vision that you guys are approaching? You want to' have a state where everything's automated in it's conversational deployments, that kind of thing. And take us through why that Siri for DevOps is. >> I think it helps anchor people to what a virtual assistant is. Because when you hear virtual assistant, that can mean any one of various connotations. So the Siri is actually a conversational assistant, but it's not necessarily a virtual assistant. So what we're saying is we're anchoring people to that thought and saying, we're actually allowing it to be operational, turning complex operations into simple conversations. >> I mean basically they take the automate with voice Google search or a query, what's the score of the game? And, it also, and talking to the guy who invented Siri, I actually interviewed on theCUBE, it's a learning system. It actually learns as it gets more usage, it learns. How do you guys see that evolving in DevOps? There's a lot of jargon in DevOps, a lot of configurations, a lot of different use cases, a lot of new technologies. What's the secret sauce behind what you guys do? Is it the conversational AI, is it the machine learning, is it the data, is it the model? Take us through the secret sauce. >> In fact, it's all the above. And I don't think we're bringing any one element to the table that hasn't been explored before, hasn't been done. It's a recipe, right? You give two people the same ingredients, they can have complete different results in terms of what they come out with. We, because of our domain expertise in DevOps, because of our familiarity with developer workflows with operators, we know how to give a very well suited recipe. Five course meal, hopefully with Michelin stars as part of that. So a few things, maybe a few of the secret sauce element, conversational AI, the ability to essentially go and extract the intent of the user, so that if we're missing context, the system is smart enough to go and to get that feedback and to essentially feed itself into that model. >> Someone might say, hey, you know, conversational AI, that was yesterday's trend, it never happened. It was kind of weak, chat bots were lame. What's different now and with you guys, and the market, that makes a redo or a second shot at this, a second bite at the apple, as they say. What do you guys see? 'Cause you know, I would argue that it's, you know, it's still early, real early. >> Certainly. >> How do you guys view that? How would you handle that objection? >> It's a fair question. I wasn't around the first time around to tell you what didn't work. I'm not afraid to share that the feedback that we're getting is phenomenal. People understand that we're actually customizing the workflows, the intent based operations to really help hone in on the dark spots. We call it last mile, you know, bottlenecks. And that's really where we're helping. We're helping in a way tribalize internal knowledge that typically hasn't been documented because it's painful enough to where people care about it but not painful enough to where you're going to' go and sit down an entire day and document it. And that's essentially what the virtual assistant can do. It can go and get into those crevices and help document, and operationalize all of those toils. And into workflows. >> Yeah, I mean some will call it grunt work, or low level work. And I think the automation is interesting. I think we're seeing this in a lot of these high scale situations where the talented hard to hire person is hired to do, say, things that were hard to do, but now harder things are coming around the corner. So, you know, serverless is great and all this is good, but it doesn't make the complexity go away. As these inflection points continue to drive more scale, the complexity kind of grows, but at the same time so is the ability to abstract away the complexity. So you're starting to see the smart, hired guns move to higher, bigger problems. And the automation seems to take the low level kind of like capabilities or the toil, or the grunt work, or the low level tasks that, you know, you don't want a high salaried person doing. Or I mean it's not so much that they don't want to' do it, they'll take one for the team, as you said, or take it on the chin, but there's other things to work on. >> I want to add one more thing, 'cause this goes into essentially what you just said. Think about it's not the virtual system, what it gives you is not just the intent and that's one element of it, is the ability to carry your operations with you to the place where you're not breaking your workflows, you're actually comfortable operating. So the virtual assistant lives inside of a command line interface, it lives inside of chat like Slack, and Teams, and Mattermost, and so forth. It also lives within a low-code editor. So we're not forcing anyone to use uncomfortable language or operations if they're not comfortable with. It's almost like Siri, it travels in your mobile phone, it's on your laptop, it's with you everywhere. >> It makes total sense. And the reason why I like this, and I want to' get your reaction on this because we've done a lot of interviews with DevOps, we've met at every CubeCon since it started, and Kubernetes kind of highlights the value of the containers at the orchestration level. But what's really going on is the DevOps developers, and the CICD pipeline, with infrastructure's code, they're basically have a infrastructure configuration at their disposal all the time. And all the ops challenges have been around that, the repetitive mundane tasks that most people do. There's like six or seven main use cases in DevOps. So the guardrails just need to be set. So it sounds like you guys are going down the road of saying, hey here's the use cases you can bounce around these use cases all day long. And just keep doing your jobs cause they're bolting on infrastructure to every application. >> There's one more element to this that we haven't really touched on. It's not just workflows and use cases, but it's also knowledge, right? Tribal knowledge, like you asked me for an example. You can type or talk to the assistant and ask, "How much am I spending on AWS, on US East 1, on so and so customer environment last week?", and it will know how to give you that information. >> Can I ask, should I buy a reserve instances or not? Can I ask that question? 'Cause there's always good trade offs between buying the reserve instances. I mean that's kind of the thing that. >> This is where our ecosystem actually comes in handy because we're not necessarily going to' go down every single domain and try to be the experts in here. We can tap into the partnerships, API, we have full extensibility in API and the software development kit that goes into. >> It's interesting, opinionated and declarative are buzzwords in developer language. So you started to get into this editorial thing. So I can bring up an example. Hey cube, implement the best service mesh. What answer does it give you? 'Cause there's different choices. >> Well this is actually where the operator, there's clearly guard rails. Like you can go and say, I want to' spin up a machine, and it will give you all of the machines on AWS. Doesn't mean you have to get the X one, that's good for a SAP environment. You could go and have guardrails in place where only the ones that are relevant to your team, ones that have resources and budgetary, you know, guidelines can be. So, the operator still has all the control. >> It was kind of tongue in cheek around the editorialized, but actually the answer seems to be as you're saying, whatever the customer decided their service mesh is. So I think this is where it gets into as an assistant to architecting and operating, that seems to be the real value. >> Now code snippets is a different story because that goes on to the web, that goes onto stock overflow, and that's actually one of the things. So inside the CLI, you could actually go and ask for code snippets and we could actually go and populate that, it's a smart CLI. So that's actually one of the things that are an added value of that. >> I was saying to a friend and we were talking about open source and how when I grew up, there was no open source. If you're a developer now, I mean there's so much code, it's not so much coding anymore as it is connecting and integrating. >> Certainly. >> And writing glue layers, if you will. I mean there's still code, but it's not, you don't have to build it from scratch. There's so much code out there. This low-code notion of a smart system is interesting 'cause it's very matrix like. It can build its own code. >> Yes, but I'm also a little wary with low-code and no code. I think part of the problem is we're so constantly focused on categories and categorizing ourselves, and different categories take on a life of their own. So low-code no code is not necessarily, even though we have the low-code editor, we're not necessarily considering ourselves low-code. >> Serverless, no code, low-code. I was so thrown on a term the other day, architecture-less. As a joke, no we don't need architecture. >> There's a use case around that by the way, yeah, we do. Show me my AWS architecture and it will build the architect diagram for you. >> Again, serverless architect, this is all part of infrastructure's code. At the end of the day, the developer has infrastructure with code. Again, how they deploy it is the neuron. That's what we've been striving for. >> But infrastructure is code. You can destroy, you know, terraform, you can go and create one. It's not necessarily going to' operate it for you. That's kind of where this comes in on top of that. So it's really complimentary to infrastructure. >> So final question, before we get into the origination story, data and security are two hot areas we're seeing fill the IT gap, that has moved into the developer role. IT is essentially provisioned by developers now, but the OP side shifted to large scale SRE like environments, security and data are critical. What's your opinion on those two things? >> I agree. Do you want me to give you the normal data as gravity? >> So you agree that IT is now, is kind of moved into the developer realm, but the new IT is data ops and security ops basically. >> A hundred percent, and the lines are so blurred. Like who's what in today's world. I mean, I can tell you, I have customers who call themselves five different roles in the same day. So it's, you know, at the end of the day I call 'em operators 'cause I don't want to offend anybody because that's just the way it is. >> Architectural-less, we're going to' come back to that. Well, I know we're going to' see you at CubeCon. >> Yes. >> We should catch up there and talk more. I'm looking forward to seeing how you guys get the feedback from the marketplace. It should be interesting to hear, the curious question I have for you is, what was the origination story? Why did you guys come together, was it a shared problem? Was it a big market opportunity? Was it an itch you guys were scratching? Did you feel like you needed to come together and start this company? What was the real vision behind the origination? Take a take a minute to explain the story. >> No, absolutely. So I've been living in Palo Alto for the last couple years. Previous, also a founder. So, you know, from my perspective, I always saw myself getting back in the game. Spent a few years in AWS essentially managing partnerships for tier one DevOps partners, you know, all of the known players. Some in public, some of them not. And really the itch was there, right. I saw what everyone's doing. I started seeing consistency in the pains that I was hearing back, in terms of what hasn't been solved. So I already had an opinion where I wanted to go. And when I was visiting actually Israel with the family, I was introduced by a mutual friend to Shaked, Shaked Askayo, my co-founder and CTO. Amazing guy, unbelievable technologists, probably one the most, you know, impressive folks I've had a chance to work with. And he actually solved a very similar problem, you know, in his own way in a previous company, BlueVine, a FinTech company where he was head of SRE, having to, essentially, oversee 200 developers in a very small team. The ratio was incongruent to what the SRE guideline would tell. >> That's more than 10 x rate developer. >> Oh, absolutely. Sure enough. And just imagine it's four different time zones. He finishes day shift and you already had the US team coming, asking for a question. He said, this is kind of a, >> Got to' clone himself, basically. >> Well, yes. He essentially said to me, I had no day, I had no life, but I had Corona, I had COVID, which meant I could work from home. And I essentially programed myself in the form of a bot. Essentially, when people came to him, he said, "Don't talk to me, talk to the bot". Now that was a different generation. >> Just a trivial example, but the idea was to automate the same queries all the time. There's an answer for that, go here. And that's the benefit of it. >> Yes, so he was able to see how easy it was to solve, I mean, how effective it was solving 70% of the toil in his organization. Scaling his team, froze the headcount and the developer team kept on going. So that meant that he was doing some right. >> When you have a problem, and you need to solve it, the creativity comes out of the woodwork, you know, invention is the mother of necessity. So final question for you, what's next? Got the launch, what are you guys hope to do over the next six months to a year, hiring? Put a plug in for the company. What are you guys looking to do? Take a minute to share the future vision and get a plug in. >> A hundred percent. So, Kubiya, as you can imagine, announcing ourselves at CubeCon, so in a couple weeks. Opening the gates towards the public beta and NGA in the next couple months. Essentially working with dozens of customers, Aston Martin, and business earn in. We have quite a few, our website's full of quotes. You can go ahead. But effectively we're looking to go and to bring the next operator, generation of operators, who value their time, who value the, essentially, the value of tribal knowledge that travels between organizations that could be essentially shared. >> How many customers do you guys have in your pre-launch? >> It's above a dozen. Without saying, because we're actually looking to onboard 10 more next week. So that's just an understatement. It changes from day to day. >> What's the number one thing people are saying about you? >> You got that right. I know it's, I'm trying to be a little bit more, you know. >> It's okay, you can be cocky, startups are good. But I mean they're obviously, they're using the product and you're getting good feedback. Saving time, are they saying this is a dream product? Got it right, what are some of the things? >> I think anybody who doesn't feel the pain won't know, but the folks who are in the trenches, or feeling the pain, or experiencing this toil, who know what this means, they said, "You're doing this different, you're doing this right. You architected it right. You know exactly what the developer workflows," you know, where all the areas, you know, where all the skeletons are hidden within that. And you're attending to that. So we're happy about that. >> Everybody wants to clone themselves, again, the tribal knowledge. I think this is a great example of where we see the world going. Make things autonomous, operationally automated for the use cases you know are lock solid. Why wouldn't you just deploy? >> Exactly, and we have a very generous free tier. People can, you know, there's a plugin, you can sign up for free until the end of the year. We have a generous free tier. Yeah, free forever tier, as well. So we're looking for people to try us out and to give us feedback. >> I think the self-service, I think the point is, we've talked about it on the Cube at our events, everyone says the same thing. Every developer wants self-service, period. Full stop, done. >> What they don't say is they need somebody to help them babysit to make sure they're doing it right. >> The old dashboard, green, yellow, red. >> I know it's an analogy that's not related, but have you been to Whole Foods? Have you gone through their self-service line? That's the beauty of it, right? Having someone in a loop helping you out throughout the time. You don't get confused, if something's not working, someone's helping you out, that's what people want. They want a human in the loop, or a human like in the loop. We're giving that next best thing. >> It's really the ratio, it's scale. It's a scaling. It's force multiplier, for sure. Amit, thanks for coming on, congratulations. >> Thank you so much. >> See you at KubeCon. Thanks for coming in, sharing the story. >> KubiyaCon. >> CubeCon. Cube in Hebrew, Kubiya. Founder, co-founder and CEO here, sharing the story in the launch. Conversational AI for DevOps, the theory of DevOps, really kind of changing the game, bringing efficiency, solving a lot of the pain points of large scale infrastructure. This is theCUBE, CUBE conversation, I'm John Furrier, thanks for watching. (upbeat electronic music)

>>Hi, everyone. Welcome to the Cube's presentation of the AWS startup showcase. This is season two, episode four of our ongoing series, where we're talking with exciting partners in the AWS ecosystem. This topic on this episode is cybersecurity detect and protect against threats. I have two guests here with me today from hunters, please. Welcome. Laal Asher Doan, the CMO and Oprah. Geier the VP of product management. Thank you both so much for joining us today. >>Thank you for having us, Lisa, >>Our pleasure. Laal let's go ahead and start with you. Give the audience an overview of hunters. What does it do? When was it founded? What's the vision, all that good stuff. >>So hunters was founded in 20 18 2. Co-founders coming out of unit 8,200 in the Israeli defense force, the founders and people in engineering and R and D are mostly coming from both offensive cybersecurity, as well as defensive threat hunting, advanced operations, or, or being able to see in response to advanced attack and with the knowledge that they came with. They wanted to enable security teams in organizations, not just those that are coming from, you know, military background, but those that actually need to defend day in and day out against the growing cyber attacks that are growing in sophistication in the numbers of attacks. And we all know that every organization nowaday is being targeted, is it run somewhere more sophisticated attacks. So this thing has become a real challenge and we all know those challenges that the industry is facing with talent scarcity, with lack of the knowledge and expertise needing to address this. >>So came in with this mindset of, we wanna bring our expertise into the field, build it into a platform into a tool that will actually serve security teams in organizations around the world to defend against cyber attacks. So born and raised in Tel Aviv became a global company. Recently raised a serious CEO of funding funded by the world's rated VCs from stripes, wild benches, supported by snowflake data breaks and Microsoft M 12 also as strategic partners. And we now have broad variety of customers from all industries around the world, from tech to retail, to eCommerce, to banks that we work closely with. So very exciting times, and we are very excited to share today how we work with AWS customers to support the environments. >>Yeah, we're gonna unpack that. So really solid foundation, the company was built on only a few years ago. Laal was there, why a new approach was there a compelling event? Obviously we've seen dramatic changes in the threat landscape in recent years, ransomware becoming a, when it happens to us, not if, but any sort of compelling event that really led the founders to go, ah, this new approach. We gotta go this direction. >>Absolutely. We've seen a tremendous shift of organizations from cloud adoption to adoption of more security tools, both create a scenario, which the tool sets that are currently being used by security organizations. The security teams are not sufficient anymore. They cannot deal with the plethora of the variety of data. They cannot deal with the scale that is needed. And the security teams are really under a tremendous burden of tweaking tools that they have in their environment without too much of automation with a lot of manual work processes. So we've seen a lot of points where the current technology is not supporting the people and the processes that need to support security operations. And with that offer and his product team kind of set a vision of what a new platform should come to replace and enhance what teams are using these days. >>Excellent. Oprah, that's a perfect segue to bring you into the conversation. Talk about that vision and some of those really key challenges and problems that hunters are solving for organizations across any industry. >>Yeah. So as Lial mentioned, and it was very rightful, the problem with the, with the SIM space, that's the, the space that we're disrupting is the well known secret around is it's a broken space. There's a lot of competitors. There's a lot of vendors out there. It's one of the most mature, presumably mature markets in cybersecurity. But it seems like that every single customer and organization we talk to, they don't really like their existing solution. It doesn't really fit what they need. It's a very painful process and it's painful all across their workflow from the time they ingest the data. Everybody knows if you ever had a SIM solution or a soft platform, just getting the data into your environment can take the most amount of your time. The, the, the lion share of whatever your engineers are working on will go to getting the data into the system. >>And then, then keeping it there. It's this black hole that you have to keep feeding with more and more resources as you go along. It's an endless task with a lot of moving pieces, and it's very, very painful before you even get a single moment of value of security use case from your product. That's a big, painful piece. What you then see is once they set it up, their detection engineering is so far behind the curve because of all the different times of things they need to take care of. It used to be limited attack surface. We all know the attack surface here today is enormous. Especially when you talk about something like AWS, there's new services, new things, all the time, more accounts, more things. It keeps moving a lot and keeping track of that. And having someone that can actually look into a new threat when it's released, look into a new attack service, analyze it, deploying the detections in time, test and tweaked and all those things. >>Most organizations don't, don't even how to start approaching this problem. And, and, and that's a big pain for them. When they finally get to investigating something, they lack the context and the knowledge of how to investigate. They have very limited information coming to them and they go on this hunting chase of not hunting the attackers, but hunting the data, looking for the bits and pieces they're missing to complete the picture. It's like this bad boss that gives you very little instructions or, or guidelines. And then you need to kind of try to figure out what is it that they asked, right? That's the same thing with trying to do triaging with very minimal context. You look at the IP and then you try to figure out, you look at the hash, you look at all these different artifacts and you try to figure out yourself, you have very limited insights. And the worst is when you're under the gun, when there's a new emerging threat, that happens like a log for shell. And now you're under the gun and the entire company's looking at you and saying, are we impacted? What's going on? What should we doing? So from, from start to finish, it's a very painful process that impacts everybody in the security organization. A lot of, a lot of cumbersome work with a lot of frustration >>And it's comp companies in any industry over don't have time. You talked about some of the, the time involved here in the lag, and there isn't time in the very dynamic threat landscape that customers are living in. Let's all question for you is your primary target audience, existing SIM customers, cause over mentioned the disruption of the SIM market. I'm just wanting to understand in terms of who you're targeting, what does that look like? >>Definitely looking for customers that have a SIM and don't like, it don't find that it helps them improve the security posture. We also have organizations that are young emerging, have a lot of data, a lot of tech companies that have grown in the last 10, 15 years, or even five years, we have snowflake as a customer. They're booming. They have so much data that going the direction of traditional tools to aggregate the logs, cross correlate them doesn't make any sense with the scale that they need. They need the cloud based approach, SaaS approach that is capable of taking care of the environment. So we both cater to those organizations that we're shifting from on-prem to cloud and need visibility into those two environments and into those cloud natives wanted the cloud don't want to even think of a traditional SIM. >>You mentioned snowflake. We were just at snowflake summit a couple of months ago. I think that was and tremendous company that massive growth, massive growth in data across the board though. So I'm curious, Oprah, if we go back to you, we can dig into some of these data challenges. Obviously data volume and variety is only gonna continue to grow and proliferate and expand data in silos is still a problem. What are some of those main data challenges that hunters helps customers to just eliminate? >>Definitely. So the data challenge starts with getting the right data in the fact that you have so many different products across so many different environments, and you need to try to get them in a, in some location to try to use them for running your queries, your rules, your, your correlation. It's a big prompt. There's no unified standard for anyone. Even if there was, you have a lot of legacy things on premises, as well as your AWS environment, you need to combine all these. You can keep things only OnPrem you can own. Mostly a lot of most organizations are still in hybrid mode. They have they're shifting most of the things to AWS. You still have a lot of things OnPrem that they're gonna shift in the next 3, 4, 5 years. So that hybrid approach is definitely a problem for gathering the data. And when they gather the data, a lot of the times their existing solutions are very cross prohibitive and scale prohibitive from pushing all the data and essential location. >>So they have these data silos. They'll put some of it there. Some of it here, some of them different location, hot storage called storage, long term storage. They don't really, they end up not knowing really where the data is, especially when they need it. The most becomes a huge problem for them. Now with analytics, it's very hard to know upfront what data I'll need, not tomorrow, but maybe in three months to look back and query making these decisions very hard. Changing them later is even harder. Keeping track of all these moving pieces. You know, you have a device, you have some vendor sending you some logs. They changed their APIs. Who's in charge of, of fixing it. Who's in charge of changing your schema. You move from one EDR vendor to the other. How are you making sure that you keep the same level of protection? All these data challenges are very problematic for most customers. The most important thing is to be able to gather as much data as possible, putting in a centralized location and having good monitoring in a continuous flow of, I know what data I'm getting in. I know how much I'm using, and I'm making sure that it's working and flowing. It's going to a central life central place where I can use it at any time that I want. >>We've seen. So sorry. Yes, please. We wanted to add on that. We've seen too much compromise on data that because of prohibitive costs, structure of tools, or because of, in inability to manage the scale teams are compromising or making choices and that paying a price of the latency of being able to then go search. If an incident happened, if you are impacted by something, it all means money and time at the end of the day, when you actually need to answer yourself, am I breached or not? We wanna break out from this compromise. We think that data is something that should not be compromised. It's a commodity today. Everything should be retained, kept and used as appropriately without the team needing to ration what they're gonna use versus what they're not gonna use. >>Correct. That's >>A great point. Go ahead. >>Yeah. And we've seen customers either having entire teams dedicated to just doing this and, or leveraging products and companies that actually build a business around helping you filter the data that you need to put in different data silos, which to me is, is shows how much problem pain and how much this space is broken with what it provides with customers that you have these makeshift solutions to go around the problem instead of facing it head on and saying, okay, let's, let's build something that you're put all your data as much as you want, not have to compromise insecurity. >>You guys both bring up such a great point where data and security is concerned. No business can afford to compromise. Usually compromise is a good thing, but in that case, it's really not companies can't afford that. We know with the, with the threat landscape, the risk, all of the incentives for bad actors that companies need to ensure that they're doing the right things in Aly manner. LA I'm curious, you mentioned the target markets that you're going after. Where are the customer conversations? Is this C conversation from a datasecurity perspective? I would, this is more than the, the CSO. >>It's a CSO conversation, as well as we, we talk on a daily basis with those that lead security operations, head of socks. Those that actually see how the analyst are being overworked are tired, have so many false positives that they need to deal with noise day in, day out, becoming enslaved with the tools that they need to work on and, and tweak. So we have seen that the ones that are most enlightened by a solution like hunters are actually the ones that have to stop reporting to them. They know the daily pain and how much the process is broken. And this is probably one of we, we all talk about, you know, job satisfaction or dissatisfaction, the greatest, the great resignation people are living. This is the real problem in security. And the, so is one of these places that we see this alert, fatigue, people are struggling. It's a stressful work. And if there is anything that we can do to offload the work that is less appealing and have them work on what they sign up for, which is dealing with real threat, solving them, instead of dealing with false positives, this is where we can actually help. >>Can you add a little bit on that? Laal and you mentioned the cybersecurity skills gap, which is massive. We talk about that a lot because it's a huge problem. How is hunters a facilitator of companies that might be experiencing that? >>Absolutely. So we come with approach of, we call it the 80 20 of detection and response. Basically there are about 80% probably. Whoa, it's actually something like 95% of the threats are shared across all organizations in the world. Also 80 to 90% of the environments are similar. People are using similar tools. They're on similar cloud services. We think that everything that goes around detection of threats around those common attacks, scenarios in common attack landscape should come out of the box from a vendor like hunters. So we automate, we write the rules, we cross correlate. We provide those services out of the box. Once you sign to use our solution, your data flows in, and we basically do the processing and the analysis of all the data so that your team can actually focus on the 20% or the, you know, the 5% that are very unique to your organization. >>If you are developing a specific app and you have the knowledge of about the dev SecOps that needs to take place to defend it. Great. Have your team focus on that? If you are a specific actor in a specific space and specific threats that are unique to you, you build your own detections into our tool. But the whole idea that we have, the knowledge, we see attacks across industries and across industries, we have the researchers and the capabilities to be on top of those things. So your team doesn't need to do it on a daily basis because new attacks come almost on a daily basis. Now we read them in the news, we see them. So we do it. So your team doesn't have to, >>And nobody wants to be that next headline where a breach is concerned. I'll close this out here with outcomes. I noticed some big stats on your website. I always gravitate towards that. What are some of the key outcomes that hunters customers are achieving and then specifically AWS customers? >>Absolutely. Well, we already talked a lot about data and being able to ingest it. So we give our customers the predictability, the ability to ingest the data, knowing what the cost is going to be in a very simple cost model. So basically you can ingest everything that you have across all it tools that you have in your environment. And that helped companies reduce up to 75% of the data cost. We we've seen with large customer how much it change when they moved from traditional Sims to using hunters specifically, AWS customers can actually use the AWS credits to buy hunters. If they're interested, just go to AWS marketplace, search for hunters and come to a website. You can use your credits for that. I think we talked also about the security burden. The time spent on writing rules plus correlating incidents. We have seen sometimes a change in, instead of investigating an incident for two days, it is being cut for 20 minutes because we give them the exact story of the entire attack. What are the involved assets? What are the users that are involved, that they can just go see what's happening and then immediately go and remediate it. So big shift in meantime, to detect meantime, to respond. And I'm sure often has a more kind of insights that he's seen with some of our customers around that. >>Yeah. So, so some, some great examples recently there. So there's two things that I've, I've been chatting to customers about. One thing they really get a benefit of is we talked, you talked about the, the, the prong with talent and where that really matters the most is that under the gun mode, we have a service that is, we see it as, as the, the natural progression of the service that we provide called team axon. What team axon does for you is when you are under the gun, when something like log for shell happens, and everybody's looking at you, and time is ticking. Instead of trying to figure out on yourself, team axon will come in, figure out the, the threat will devise a report for all the customers, run queries on your behalf, on your data and give it to you. Within 24 hours, you'll have something to show your CEO or your executive team, your board, even this is where we got impacted or not impacted. >>This is what we did. Here's the mitigation thing. Step that we need to take from world class experts that you might not get access to for every single attack out there that really helps customers kind of feel like they they're, they're safe. There's someone there to help them. There's a big broader there. I call it sometimes the bad signal when we need the most. The other thing is on the day to day, a lot of a lot of solution will, will, will kind of talk about out of the box security. Now, the problem with out of the box security is keeping an up to date. That's what a lot of people miss. You have to think that you installed a year ago, but security doesn't stay put, you need to keep updating it. And you need to keep that updated pretty, pretty frequently to, to stay ahead of the curve. >>If you, if you're behind couple of months on your security updates, you know, what happens, same thing with your, your stock platform or your SIM rule base. What the reason that customers don't update is because if they usually do, then it might blow up the amount of alerts they're getting, cuz they need to tweak them with the approach that we take, that we tested on our customer's data transparently for them and make sure to release them without false positives. We're just allowing them to push the updates transparently directly to their account. They don't need to do anything. And one customer, one of our biggest accounts, they have dozens of subsidiaries and multiple songs. And, and one of the largest eCommerce companies in the world and the person running security. He said, if I had to do what hunters gives me out of the box myself, I have to hire 20 people and put them to work eight for 18 months for what you give me out of the box. So for me, it's a first, that's huge, kinda what we give customers and the kind of challenges that we're able to solve for them. >>Big challenges laal and over, thank you so much for joining us on the cube today. As part of this AWS startup showcase, talking about what hunters does, why the vision and the value in it for customers, we appreciate your time and your insights. Thank you so much for having us, my pleasure for my guests. I'm Lisa Martin. Thank you for watching this episode of the AWS startup showcase. We'll see us in.

(upbeat music) >> Hey everyone. And welcome to this CUBE Conversation which is part of the AWS startup showcase. Season two, episode four of our ongoing series. The theme of this episode is cybersecurity, detect and protect against threats. I'm your host, Lisa Martin, and I'm pleased to be joined by the founder and CEO of Hunters.AI, Uri May. Uri, welcome to theCUBE. It's great to have you here. >> Thank you, Lisa. It's great to be here. >> Tell me a little bit about your background and the founders story. This company was only founded in 2018, so you're quite young. But gimme that backstory about what you saw in the market that really determined, this is needed. >> Yeah, absolutely. So, I mean, I think the biggest thing for us was the understanding that significant things have happened in the cybersecurity landscape for customers and technology stayed the same. I mean, we tried on solving the same... We tried on solving a big problem with the same old tools when we actually noticed that the problem has changed significantly. And we saw that change happening in two different dimensions. The first is the types of attacks that we're defending against. A decade ago, we were mostly focused on these highly sophisticated nation state efforts that included unknown techniques and tactics and highly sophisticated kind of methods. Nowadays, we're talking a lot about cyber crime gangs, whoops of people that are financially motivated or using off the shelf tools, of the shelf malware, coordinating in the dark web, attacking for money and ransom basically, versus sophisticated intelligence kind of objectives. And in the same time of that happening, we also saw what we like to refer to as explosion of the securities stack. So some of our customers are using more than 60 or 70 different security tools that are generating sometimes tens of terabytes a day of flows. That explosion of data, together with a very persistent and consistent threat that is continuously affecting customers, create a very different environment, where you need to analyze a big variety of data and you need to constantly defend yourself against stuff that are happening all the time. And that was kind of like our wake moment when we understand that the tools that are out there now might have been the right tools a decade ago, they are probably not the right tools to solve the problem now. So yeah, I think that that was kind of what led us to Hunters. And in the same time, and I think that that's my personal kind of story behind it. We used to talk a lot about the fact that we want to solve a fundamental problem. And we, as part of the ideation around Hunters and us zooming in on exactly the areas that we want to focus on in security, we talked with a lot of CSOs, we talked with a lot of industry experts, everyone directed us to the security operation center. I mean the notion that there's a lot of tools and there's always going to be a lot of tools, but eventually decisions are being made by people that are running security operation center, that are actually acting as the first line of defense. And that's where you feel that the processes are woke. That's where you feel that that technology doesn't really meet the rabel, and the rabel doesn't really meet the hold. And for us, it was a very clear sign that this is where we need to focus on. And that set us on a journey to explore red hunting and then understand that we can solve something bigger than that. And then eventually get to where we are today, which is go to market around. So holistic a platform that can help SOC analysts doing the day to day job defending the organizations. >> So you saw back in 2018, probably even before that that the SIEM market was prime and right for disruption. And only in a four year time period, there's been some pretty significant milestones and accomplishment that the team at Hunters has made in that short timeframe. Talk to me about some of those big milestones that the company has reached in just four years. >> Yeah, I think that the biggest thing and I know that it's going to sound like a cliche, but we're actually believing that I think it's the team. I mean, we're able to go to an organization of around 150 employees. All over the world, the course, I think I mean the last time that I checked, like 15 countries. That's the most amazing feeling that you can have. That ability to attract people to a single mission from all over the world and to get them collaborate and do amazing things and achieve unbelievable accomplishment. I think that's the biggest thing. The other thing for us was customers. I mean, think about it like, SIEM it's such a central and critical system. So for us as a young startup from Tel Aviv to go out to Enterprise America and convince the biggest enterprise around the world to rip and replace the the existing solutions that are being built by the biggest software brands out there and install Hunters instead, that's a huge leap of trust, that we are very grateful for, and we're trying to handle with a lot of care and a lot of responsibility. And obviously, I think that other than that, is all of the investors that we were able to attract that basically enabled all of that customer acquisition and team building and product development. And we're very fortunate to work with the biggest names out there, both from a strategic perspective and also from tier one VCs from mainly from the U.S., but from all over the world, actually that are backing us. >> Great customers, solid foundation. Hunters is built for the clouds, is powered by Snowflake. This is AWS built. Talk to me about what's in it for me from an AWS customer perspective. What's that value in it for them? >> Yeah, so I think that the most important thing, in my opinion, at least, is the security value that you're getting from it. Other than the fact that Hunters is a multi-tenant SaaS application running in AWS, it's also a system that is highly tuned and specifically built to be very effective against detecting threats inside AWS environments. So we invested a lot of time in research, in analyzing the way attackers are operating inside cloud environments, specifically in AWS. And then we model these techniques and tactics and procedures into the system. We're leveraging data sets like AWS CloudRail and CloudWatch and VPC Flow Logs, obviously AWS GuardDuty which is an amazing detection system that AWS offer to its customer, and we're able to leverage it, correlate it with other signals. And at the same time, there's also the commercial aspect and the business aspect. I mean, we're allowing AWS customers to leverage the AWS credits to the marketplace to fund same projects like Hunters that comes with a lot of efficiencies also. And with a lot of additional capabilities like I mentioned earlier. >> So let's crack open Hunters.AI. What makes this approach different? You talked about the challenges that you guys saw in the market that were gaps there, and why technology needed to come in from a disruption standpoint. But describe the differentiators. When you're talking to perspective customers, what are those key differentiators that Hunters brings to the table? >> Yeah, absolutely. So we like to divide it into three main pillars. The first pillar is everything that we do with data, that is very different from our competitors. We believe that data should be completely liberated from the analytical layer. And that's why we're storing data in a dedicated data warehouse. Snowflake, as you mentioned earlier, is one of our go to data warehouses. And that give customers the ability to own their own data. So you as a customer can opt in into using Hunters on top of your Snowflake. It's not the only way. You can also get Snowflake bundled as part of that, your Hunter subscription, but for some customers that ability to reduce vendor lock risk on data on your own and also level security data for other kind of workflows is something that is really huge. So that's the first thing that is very different. The second thing is what we like to call security engineering as a service. So when you buy Hunters, you don't just buy a data platform. You actually buy a system, a SOC platform that is already populated with use cases. So what we are saying is that in today's world the threats that we're handling as a SOC, as security operations center professionals are actually shared by 80% of the customers out there. So 80% of the customers share around 80% of the threat. And what we're basically saying is let us as a vendor, solve the detection response around that 80%. So you as a customer could focus on the 20% that is unique to your environment. Then in a lot of cases generate 80% of the impact. So that means that you are getting a lot of rebuilt tools and detections, data modeling to your integrations, automatic investigations, scoring correlations. All of these things are being continuously deployed and delivered by us because we're multi tenant SaaS. And also allowing you again to get this effortless tail key kind of solution that is very different from your experience with your current SIEM tools that usually involves a lot of tuning, professional services, configuration, et cetera. And the last aspect of it, is everything that we're doing around automation. We're leveraging very unique graph technology and what we call automatic investigation enrichments that allows us to take all of these signals that we're extracting from all over the attacks, of say AWS included, but also the endpoint and the email and the network and IOT environments and whatever automatically investigate them, load them into a graph and then automatically correlate them to what we call stones, which are basically representation of incidents that are happening across your tax office. And that's a very unique capability that we bring into the table that demonstrates our focus on the analytical lens. So it's not just log aggregation, and querying and dashboarding kind of system. It's actually a security analytic system that is able to drive real insights on top of the data that you're plugging into it. >> So talk to me, Uri, when you're in customer conversations these days the market is there's so many dynamics and flux that customers are dealing with. Obviously, the threat landscape continues to expand and really become quite amorphous as that perimeter blends. What are some of the specific challenges that security operation center or SOC teams come to you saying, help us eliminate this. We have so many tools, we've probably got limited resources. What are those challenges and how does Hunters really wipe those off the plate? >> Yeah, so I think the first and foremost has to do with the second pillar that I mentioned earlier and that's security engineering. So for most security operations centers and most organizations around the world, the feeling is that they're kind of like stuck on this third wheel. They keep on buying tools and then implementing these tools and then writing rules and then generating noise and then fine tuning the rules. And then testing the rules and understanding that the fine tuning actually generated misdetections. And they're kind of like stuck on this vicious side. And no one can really help because a lot of the stuff that they're building, they're building it in their environment. And what we're saying is that, let us do it for you. Well, that 80% that we've mentioned earlier and allows you to really focus on the stuff that you're doing and even offset your talent. So, we're not talking about really a talent reduction. Because everyone needs more talent in cybersecurity nowadays but we're talking a lot about offset. I mean, if we had a team of five people investing efforts in building walls, building automation, and now three or four of these people can go and do advanced investigations, instant response, threat hunting interval, that's meaningful. For a lot of SOCs, in a lot of cases that means either identifying and analyzing a threat in time or missing it. So, I mean, I think that that's the biggest thing. And the other thing has to do with the first thing that I mentioned earlier, and these are the data challenges. Data challenges in terms of cost, performance, the ability to absorb data sets that today's tools can't really support. I mean, for example, one of the biggest data sets that we're loading that is tremendously helpful is raw data for EDR products. Raw data for EDR products in large enterprises can get to 10, 15, 20 terabytes a day. In today's SIEMs and SOC platforms that the customers are using, this thing is just as prohibited from SOC. They can't really analyze it because it's so costly. So what we're saying is a lot of what we're seeing is a lot of customers, either not analyzing it at all, or saving it for a very little amount of time, account of days. Because they can't support the retention around it. So the ability to store huge data sets for longer period of time makes it something that a lot of big enterprises need. And to be honest, I think that in the next couple of years they would also be forced to have these kind of capabilities, even from a compliance perspective. >> So in terms of outcomes, I'm hearing reduction in costs really helping security teams utilize their resources, the ability to analyze growing volumes of data. That's only going to continue to increase as we know. Is there a customer story, Uri that you have that really, where the value proposition of Hunters really shines through? >> Yeah, I think that one thing comes to mind from those hospitality vertical and actually it's a reference customer. I mean, we can share the name. His name is booking.com. It's also publicly shown on our website. And they think the coolest thing that we were able to do with booking is give them that capability to stay up to date with the threats that they're facing. So it's not just that we saved a lot of efforts from them because we came with a lot of out of the box capabilities that they can use. We also kept them up to date with everything that they were facing. And there was a couple of cases, where we were able to detect threats that were very recently from threat perspective. Based on our ability to invest research time and efforts in everything that is going on in the ecosystem and the feedback that we got from the customer, and it's not a single of feedback. Like we're getting it a lot, is that, without you guys we wouldn't be able to do the effective research and then the implementation of this and the threat modeling and the implementation of these things in time. And walking with you kind of like made the difference between analyzing it and reacting in time and potentially blocking like a very serious bridge versus maybe finding out when it's too late. >> Huge impact there. And I'm kind of thinking, Hunters aim, might be one of the reasons that booking.com's tagline it's booking.com, booking.yeah. Yeah, we're secure. We know if we can demonstrate that to everyone that uses our service. I noticed kind of wrapping things up here, Uri. I noticed that back in I think it was January of 2022, Hunters raised about 60 million in series C. You talked about kind of being in the GTM phase, where are some of those strategic investments? What have you been doing, focusing on this year and what's to come as we round out 22? >> Yeah, absolutely. So, I mean, there's a lot of building going on. Yeah. Still, right. I mean, we're getting into that scale mode and scale phase but we're very much also building our capabilities, building our infrastructure, building our teams, building our business processes. So there's a lot of efforts going into that, but in the same time, I mean, we've being able to vary, to depending our relationship with DataBlitz which is a very important partner of us. And we got some big news coming up on that. And they were a strategic investor that participated in our series C. And in the same time we're walking in the air market which is a very interesting market for us. And we get a lot of support from one other strategic investor that joined the series C, Deutsche Telekom. And they are a huge provider in IT and security in email, other than doing a lot of other things and including T-systems and T-Mobile and everything that has to do with that. So we're getting a lot of support from them. And regardless, I think, and that ties back to what we've mentioned earlier, the ability for us to come to really big customers with the quality of investors that we have is a very important external validation. It's basically saying like this company is here to stay. We're aiming at disrupting the market. We're building something big. You can count on us by replacing this critical system that we're talking about. And sometimes it makes a difference, like sometimes for some of the customers, it means that this is something that I can rely on. Like it's not a startup that is going to be sold two months after I'm deploying it. And it's not a founder that is going to disappear on me. And for a lot of customers, these things happen, especially in an ecosystem like cybersecurity, that is so big with such a huge variety of different systems. So, yeah, I think that we're getting ready for that scale mode and hopefully it'll happen sooner than what we think. >> A lot of growth already as we mentioned in the beginning of the program. Since just 2018 it sounds like from a foundation perspective, you guys are strong, you're rocking away and ready to really take things into 2023 with such force. Uri, thank you so much for joining me on the program, talking about what Hunters.AI is up to and how you're different and why you're disrupting the SIEM market. We appreciate your insights and your time. >> Absolutely. Lisa, the pleasure was all mine. Thank you for having me. >> Likewise. For Uri May, I'm Lisa Martin. Thank you for watching our CUBE Conversation as part of the AWS startup showcase. Keep it right here for more actions on theCUBE, your leader in tech coverage. (upbeat music)

(upbeat music) >> Hi, everyone. Welcome to theCUBE's presentation of the AWS Startup Showcase. This is season two, episode four of our ongoing series, where we're talking with exciting partners in the AWS ecosystem. This topic on this episode is cybersecurity. Detect and protect against threats. I have two guests here with me today from Hunters. Please welcome Lital Asher-Dotan, the CMO. And Ofer Gayer, the VP of product management. Thank you both so much for joining us today. >> Thank you for having us, Lisa. >> Our pleasure. Lital, let's go ahead and start with you. Give the audience an overview of Hunters. What does it do, when was it founded, what's the vision? All that good stuff. >> So Hunters was founded in 2018. Two co-founders coming out of Unit 8200 in the Israeli Defense Force. The founders and our people in engineering and R&D are mostly coming from both offensive cybersecurity as well as defensive threat hunting, advanced operations, or being able to see and response to advance attack. And with the knowledge that they came with, they wanted to enable security teams in organizations, not just those that are coming from, you know, military background but those that actually need to defend day in and day out against the growing cyber-attacks that are growing in sophistication, in the numbers of attacks. And we all know that every organization nowaday is being targeted, is it ransomware, more sophisticated attacks. So this thing has become a real challenge. And we all know those challenges that the industry is facing with talent scarcity, with lack of the knowledge and expertise needed to address this. So came in with this mindset of we want to bring our expertise into the field, build it into a platform, into a tool that will actually serve security teams in organizations around the world to defend against cyber attacks. So born and raised in Tel Aviv, became a global company. Recently raised a serious CO funding. Funded by the world's greatest VCs, from Stripes, Wild Ventures, supported by Snowflake data breaks and Microsoft M12, also as strategic partners. And we now have broad variety of customers from all industries around the world, from tech to retail to e-commerce to banks that we work closely with. So very exciting times. And we're very excited to share today how we work with AWS customers to support the environments. >> Yeah, we're going to unpack that. So really solid foundation the company was built on, only a few years ago. Lital was there, why a new approach? Was there a compelling event? Obviously, we've seen dramatic changes in the threat landscape in recent years. Ransomware becoming a, when it happens to us, not if. But any sort of compelling event that really led the founders to go, "Ah! This new approach, we got to go this direction." >> Absolutely. We've seen a tremendous shift of organizations from cloud adoption to adoption of more security tools. Both create a scenario which the toolsets that are currently being used by security organizations, the security teams are not efficient anymore. They cannot deal with the plethora of a variety of data. They cannot deal with the scale that is needed. And the security teams are really under a tremendous burden of tweaking tools that they have in their environment without too much of automation, with a lot of manual work processes. So we've seen a lot of points where the current technology is not supporting the people and the processes that need to support security operations. And with that, Ofer, and his product team kind of set a vision of what a new platform should come to replace and enhance what teams are using these days. >> Excellent. Ofer, that's a perfect segue to bring you into the conversation. Talk about that vision and some of those really key challenges and problems that Hunters is solving for organizations across any industry. >> Yeah. So as Lital mentioned, it was very rightful. The problem with the SIM space, that the space that we're disrupting is the well-known secret around is it's a broken space. There's a lot of competitors. There's a lot of vendors out there. It's one of the most mature, presumably mature markets in cybersecurity. But it seems like that every single customer and organization we talk to, they don't really like their existing solution. It doesn't really fit what they need. It's a very painful process and it's painful all across their workflow from the time they ingest the data. Everybody knows if you ever had a SIM solution or a SOC platform, just getting the data into your environment can take the most amount of your time, the lion's share of whatever your engineers are working on will go to getting the data into the system, and then keeping it there. It's this black hole that you have to keep feeding with more and more resources as you go along. It's an endless task with a lot of moving pieces, and it's very very painful before you even get a single moment of value of security use case from your product. That's a big, painful piece. What you then see is, once they set it up, their detection engineering is so far behind the curve because of all the different times of things they need to take care of. It used to be a limited attack surface. We all know the attack surface here today is enormous, especially when you talk about something like AWS, there's new services, new things all the time, more accounts, more things. It keeps moving a lot, and keeping track of that and having someone that can actually look into a new threat when it's released, look into a new attack surface, analyze it, deploying the detections in time, test and tweak, and all those things. Most organizations don't even how to start approaching this problem, and that's a big pain for them. When they finally get to investigating something, there lacks the context and the knowledge of how to investigate. They have very limited information coming to them and they go on this hunting chase of not hunting the attackers but hunting the data, looking for the bits and pieces they're missing to complete the picture. It's like this bad boss that gives you very little instructions or guidelines, and then you need to kind of try to figure out what is it that they asked, right? That's the same thing with trying to do triaging with very minimal context. You look at the IP and then you try to figure out, you look at the Hash, you look at all these different artifacts and you try to figure out yourself. You have very limited insights. And the worst is when you're under the gun, when there's a new emerging threat that happens like a Log4Shell, and now you're under the gun and the entire company's looking at you and saying, "Are we impacted? What's going on? What should we doing?" So from start to finish, it's a very painful process that impacts everybody in the security organization. A lot of cumbersome work with a lot of frustration. >> And it's companies in any industry, Ofer, don't have time. You talked about some of the time involved here in the lag. And there isn't time in the very dynamic threat landscape that customers are living in. Lital, question for you, is your primary target audience existing SIM customers? 'Cause Ofer mentioned the disruption of the SIM market. I'm just wanting to understand in terms of who you're targeting, what does that look like? >> Definitely looking for customers that have a SIM and don't like it, don't find that it helps them improve the security posture. We also have organizations that are young, emerging, have a lot of data, a lot of tech companies that have grown in the last 10, 15 years, or even five years. With Snowflake as a customer, they're booming. They have so much data that going the direction of traditional tools to aggregate the logs, cross-correlate them doesn't make any sense with the scale that they need. They need the cloud-based approach, SaaS approach that is capable of taking care of the environment. So we both cater to those organizations that we're shifting from on-prem to cloud and need visibility into those two environments and into those cloud natives. Born to the cloud don't want to even think of a traditional SIM. >> You mentioned Snowflake. We were just at Snowflake Summit a couple of months ago, I think that was. And tremendous company that massive growth, massive growth in data across the board though. So I'm curious, Ofer, if we go back to you, if we can dig into some of these data challenges. Obviously, data volume and variety, it's only going to continue to grow and proliferate and expand. Data in silos is still a problem. What are some of those main data challenges that Hunters helps customers to just eliminate? >> Definitely. So the data challenge starts with getting the right data in. The fact that you have so many different products across so many different environments and you need to try to get them in some location to try to use them for running your queries, your rules, your correlation. It's a big prompt. There's no unified standard for anyone, even if there was, you would have a lot of legacy things on-premises, as well as your AWS environment. You need to combine all these. You can keep things only on-prem. You can own... Mostly a lot of, most organizations are still in hybrid mode. They have, they're shifting most of their things to AWS. You still have a lot of things on-prem that they're going to shift in the next 3, 4, 5 years. So that hybrid approach is definitely a problem for gathering the data. And when they gather the data, a lot of the times their existing solutions are very cost prohibitive and scale prohibitive from pushing all the data in essential location. So they have these data silos. They'll put some of it there, some of it here, some of that in a different location, hot storage, cold storage, long-term storage. They don't really, they end up not knowing really where the data is especially when they need it the most becomes a huge problem for them. Now with analytics, it's very hard to know upfront what data I'll need not tomorrow, but maybe in three months to look back and query. Making these decisions is very hard. Changing them later is even harder. Keeping track of all these moving pieces. You know, you have a device, you have some vendor sending you some logs, they changed their APIs. Who's in charge of fixing it? Who's in charge of changing your schema? You move from one EDR vendor to the other. How are you making sure that you keep the same level of protection? All these data challenges are very problematic for most customers. The most important thing is to be able to gather as much data as possible, putting it in a centralized location, and having good monitoring in a continuous flow of, I know what data I'm getting in. I know how much I'm using, and I'm making sure that it's working and flowing. It's going to a central place where I can use it at any time that I want. >> We've seen, if I can add- >> So, Lital- >> Sorry. >> Yes, please. >> You wanted to add on that? We've seen too much compromise on data that because of prohibitive costs, structure of tools, or because of inability to manage the scale, teams are compromising or making choices and are paying a price of the latency of being able to then go search if an incident happened, that if you are impacted by something. It all means money and time at the end of the day when you actually need to answer yourself, am I breached or not? We want to break out from this compromise. We think that data is something that should not be compromised. It's a commodity today. Everything should be retained, kept, and used as appropriately without the team needing to ration what they're going to use versus what they're not going to use. >> Correct (faintly speaking). >> That's a great point. >> Go ahead. >> Yeah. And we've seen customers either having entire teams dedicated to just doing this and, or leveraging products and companies that actually build a business around helping you filter the data that you need to put in different data silos, which to me is, shows how much problem, pain, and how much this space is broken with what it provides with customers that you have these makeshift solutions to go around the problem instead of facing it head on and saying, "Okay, let's build something that you're put all your data as much as you want, not have to compromise on security." >> You both bring up such a great point where data and security is concerned. No business can afford to compromise. Usually compromise is a good thing, but in that case, it's really not. Companies can't afford that. We know with the threat landscape, the risk, all of the incentives for bad actors that companies need to ensure that they're doing the right things in a timely manner. Lital, I'm curious, you mentioned the target markets that you're going after. Where were customer conversations? Is this a C-suite conversation from a data security perspective? I would this is more than the CISO. >> It's a CISO conversation, as well as we talk on a daily basis with those that lead security operations, head of SOCs. Those that actually see how the analyst are being overworked, are tired, have so many false positives that they need to deal with, noise day in, day out, becoming enslaved with the tools that they need to work on and tweak. So we have seen that the ones that are most enlightened by a solution like Hunters are actually the ones that have the SOC reporting to them. They know the daily pain and how much the process is broken. And this is probably one of the... We all talk about, you know, job satisfaction or dissatisfaction, the greatest, the great resignation, people are living. This is the real problem in security. And the SOC is one of these places that we see this alert, fatigue, people are struggling. It's a stressful work. And if there is anything that we can do to offload the work that is less appealing and have them work on what they sign up for, which is dealing with real threat, solving them, instead of dealing with false positives. This is where we can actually help. >> Can you add a little bit on that, Lital? And you mentioned the cybersecurity skills gap, which is massive. We talked about that a lot because it's a huge problem. How is Hunters a facilitator of companies that might be experiencing that? >> Absolutely. So we come with approach of, we call it the 80/20 of detection and response. Basically, there are about 80%, probably more, it's actually something like 95% of the threats are shared across all organizations in the world. Also, 80 to 90% of the environments are similar. People are using similar tools. They're on similar cloud services. We think that everything that goes around detection of threats, around those common attacks, scenarios in common attack landscape should come out of the box from the vendor like Hunters. So we automate, we write the rules, we cross-correlate. We provide those services out of the box once you sign in to use our solution. Your data flows in and we basically do the processing and the analysis of all the data, so that your team can actually focus on the 20%, or the 15, or the 5% that are very unique to your organization. If you are developing a specific app and you have the knowledge about the DevSecOps that needs to take place to defend it. Great, have your team focus on that. If you are a specific actor in a specific space and specific threats that are unique to you, you build your own detections into our tool. But the whole idea that we have the knowledge, we see attacks across industries and across industries we have the researchers and the capabilities to be on top of those things, so your team doesn't need to do it on a daily basis because new attacks come almost on a daily basis. Now, we read them in the news, we see them. So we do it, so your team doesn't have to. >> And nobody wants to be that next headline where a breach is concerned. Lital, close this out here with outcomes. I noticed some big stats on your website. I always gravitate towards that. What are some of the key outcomes that Hunters customers are achieving and then specifically AWS customers? >> Absolutely. Well, we already talked a lot about data and being able to ingest it. So we give our customers the predictability, the ability to ingest the data knowing what the cost is going to be in a very simple cost model. So basically you can ingest everything that you have across all IT tools that you have in your environment. And that helped companies reduce up to 75% of the data cost. We've seen with large customer, how much it change when they moved from traditional SIMs to using Hunters. Specifically, AWS customers can actually use the AWS Credits to buy Hunters if they're interested. Just go to AWS Marketplace, search for Hunters and come to a website, you can use your credits for that. I think we talked also about the security burden, the time spent on writing rules plus correlating incidents. We have seen sometimes a change in, instead of investigating an incident for two days, it is being cut for 20 minutes because we give them the exact story of the entire attack. What are the involved assets? What are the users that are involved, that they can just go see what's happening and then immediately go and remediate it. So big shift in meantime to detect meantime to respond. And I'm sure Ofer has a more kind of insights that he's seen with some of our customers around that. >> Yeah. So some great examples recently there. So there's two things that I've been chatting to customers about. One thing they really get a benefit of is we talked about the problem with talent. And where that really matters the most is that under the gun mode, we have a service that is, we see it as the natural progression of the service that we provide called Team Axon. What Team Axon does for you is when you're under the gun, when something like Log4Shell happens and everybody's looking at you, and time is ticking, instead of trying to figure out on yourself, Team Axon will come in, figure out the threat, will devise a report for all the customers, run queries on your behalf on your data, and give it to you within 24 hours. You'll have something to show your CEO or your executive team, your board even, this is where we got impacted or not impacted. This is what we did. Here's the mitigation thing, step that we need to take from world-class experts that you might not get access to for every single attack out there. That really helps customers kind of feel like they're safe. There's someone there to help them. There's a big brother there. I call it sometimes the Bat-Signal when we need it the most. The other thing is on the day-to-day, a lot of solution, we'll kind of talk about out-of-the-box security. Now, the problem with out-of-the-box security is keeping it up to date, that's what a lot of people miss. You have to think that you installed a year ago, but security doesn't stay put, you need to keep updating it. And you need to keep the updated pretty pretty frequently to stay ahead of the curve. If you're behind couple of months on your security updates, you know what happens. Same thing with your SOC platform on your SIM rule base. The reason that customers don't update is because if they usually do, then it might blow up the amount of alerts they're getting 'cause they need to tweak them. With the approach that we take that we tested on our customer's data transparently for them, and make sure to release them without false positives. We're just allowing them to push the updates transparently directly to their account. They don't need to do anything. And one customer, one of our biggest accounts, they have dozens of subsidiaries and multiple SOCs and one of the largest e-commerce companies in the world. And the person running security, he said, "If I had to do what Hunters gives me out of the box myself, I have to hire 20 people and put them to work for 18 months for what you give me out of the box." So for me, it's a very- >> That's huge. >> What we give customers and the kind of challenges that we're able to solve for them. >> Big challenges. Lital and Ofer, thank you so much for joining us on theCUBE today as part of this AWS Startup Showcase, talking about what Hunters does, why the vision and the value in it for customers. We appreciate your time and your insights. >> Thank you so much. >> For having us. >> My pleasure. For my guests, I'm Lisa Martin. Thank you for watching this episode of the AWS Startup Showcase. We'll see you soon. (cheerful music)

(bright music) >> Okay, welcome back everyone. It's theCUBE's coverage here in San Francisco, California. We're live on the show floor of AWS Summit 2022. I'm John Furrier, your host of theCUBE. And remember AWS Summit in New York city coming up this summer. We'll be there as well. And of course, re:Invent at the end of the year for all theCUBE coverage on cloud computing and AWS. The two great guests here from the APN, Global APN, Serge Shevchenko and Jeff Grimes Partner Leader. Jeff and Serge is doing partnerships. Global APN >> AWS Global Startup Program. >> Okay, say that again. >> AWS Global Startup Program. >> That's the official name. >> I love it >> Too long for me. Thanks for coming on. >> Yeah, of course. >> Yeah, appreciate it. >> Tell us about what's going on with you guys? How was you guys organized? You guys, we're obviously we're in San Francisco bay area, Silicon Valley, zillions of startups here. New York has got another one we're going to be at. Tons of startups, a lot of them getting funded, big growth in cloud, big growth in data, security, hot in all sectors. >> Jeff: Absolutely. >> So maybe we could just start with the global startup program. It's essentially a white glove service that we provide to startups that are built on AWS. And the intention there is to help identify use cases that are being built on top of AWS. And for these startups, we want to provide white glove support in co building products together, co-marketing and co-selling. Essentially, the use cases that our customers need solved that either they don't want to build themselves or perhaps more innovative. So the AWS Global Startup Program provides white glove support, dedicated headcount for each one of those pillars. And within our program, we've also provided incentives, programs, go to market activities like the AWS Startup Showcase that we've built for these startups. >> Yeah, by the way, awsstartups.com is the URL. Check it out. Okay, so your partnerships are key. Jeff, what's your role? >> So I'm responsible for leading the overall effort for the AWS Global Startup Program. So I've got a team of partner managers that are located throughout the US managing a few hundred startup ISVs right now. >> Yeah, you got a lot. >> We've got a lot. There's a lot. >> I got to ask a tough question. I'm a startup founder. I got a team. I just got my series A. We're grown and I'm trying to hire people. I'm super busy. What's in it for me? What do you guys bring to the table? I love the white glove service but translate that. What's in it for me? What do I get out of it? What's the story? >> That's a good question. Focus, I think. >> Jeff: Yeah. >> Because we get to see a lot of partners building their businesses on AWS. So from our perspective, helping these partners focus on what do we truly need to build by working backwards from customer feedback. How do we effectively go to market? Because we've seen startups do various things through trial and error and also just messaging. Because oftentimes partners or rather startups try to boil the ocean with many different use cases. So we really help them sort of laser focus on what are you really good at and how can we bring that to the customer as quickly as possible? >> Yeah, it's truly about helping that founder accelerate the growth of their company. And there's a lot that you can do with AWS but focus is truly the key word there because they're going to be able to find their little piece of real estate and absolutely deliver incredible outcomes for our customers and then they can start their growth curve there. >> What are some of the coolest things you've seen with the APN that you can share publicly? I know you got a lot going on there, a lot of confidentiality, but we're here, a lot of great partners on the floor here. I'm glad we're back at events, a lot of stuff going on, digitally with virtual stuff and hybrid. What are some of the cool things you guys have seen in the APN that you can point to? >> Yeah, absolutely. I can point to few, you can take them. So I think what's been fun over the years for me personally, I came from a startup, ran sales at an early stage startup and I went through the whole thing. So I have a deep appreciation for what these guys are going through. And what's been interesting to see for me is taking some of these early stage guys, watching them progress, go public, get acquired, and see that big day. And being able to point to very specific items that we help them to get to that point. And it's just a really fun journey to watch. >> Yeah, and part of the reason why I really love working at the AWS Global Startup Program is working with passionate founders. I just met with a founder today, he's going to build a very big business one day and watching them grow through these stages and supporting that growth, I like to think of our program as a catalyst for enterprise sort of scale. And through that we provide visibility, credibility and growth opportunities. >> A lot of partners too, what I found, talking to staff founders is when they have that milestone, they worked so hard for it. whether it's a B round, C round, or public or get bought. Then they take a deep breath and they look back at, wow what a journey it's been. So it's kind of emotional for sure, but still it's a grind. When you get funding, it's still day one. You don't stop. It's no celebrate, you got a big round or valuation. You still got to execute. >> And look it's hypercompetitive and it's brutally difficult. And our job is to try to make that a little less difficult and navigate those waters where everyone's going after similar things. >> Yeah, and I think as a group element too. I observe that startups that I meet through the APN has been interesting because they feel part of AWS. >> Serge: Totally. >> As a group of community, as a vibe there. I know they're hustling. They're trying to make things happen. But at the same time, Amazon throws a huge halo effect. That's a huge factor. You guys are the number one cloud in the business. The growth and every sector is booming. And if you're a startup, you don't have that luxury yet. And look at companies like Snowflake that built on top of AWS. People are winning by building on AWS. >> Our program really validates their technology first. So we have what's called a foundation's technical review that we put all of our startups through before we go to market. So that when enterprise customers are looking at startup technology, they know that it's already been vetted. And to take that a step further and help these partners differentiate, we use programs like the competency programs, the DevOps competency, the security competency which continues to help provide a platform for these startups, help them differentiate, and also there's go to market benefits that are associated with that. >> So let me ask the question that's probably on everyone's mind who's watching us. Actually, I asked this a lot. There's a lot of companies startups out there. Who makes the cut? Is there a criteria? God, that's not like it's sports team or anything. >> Sure. >> There's activate program, which is like there's hundreds of thousands of startups out there. Not everyone is at the APN. >> Serge: Correct. >> So ISVs, again, that's a whole nother. That's a more mature partner that might have huge market cap or growth. How do you guys focus? How do you guys focus? >> Serge: Good question. >> A thousand flowers blooming all the time. Is there a new way you guys are looking at it? I know there's been some talk about restructure or new focus. What's the focus? >> It's definitely not an easy task by any means but I recently took over this role and we're really trying to establish focus areas. So obviously a lot of the ISVs that we look after are infrastructure ISVs. That's what we do and so we have very specific pods that look after different type of partners. So we've got a security pod, we've got a DevOps pod, we've got core infrastructure, et cetera. And really we're trying to find these ISVs that can solve really interesting AWS customer challenges. >> Do you guys have a deliberate focus on these pillars? So one, infrastructure. >> Security, DevOps and data and analytics and then line of business. >> Line of business, like web marketing solutions. (group chattering) >> Yeah, exactly. >> So solutions there. >> Yeah. More solutions and the other ones are like hardcore. So infrastructure as well like storage, backup, ransomware, kind of stuff. >> Storage, networking. >> Okay, yeah, the classic. >> Database, et cetera. >> And so there's teams on each pillar. >> Yep. So I think what's fascinating for the startups that we cover is that they truly have support from a build market sell perspective. So you've got someone who's technical to really help them get the technology figured out, someone to help them get the marketing message dialed and spread, and then someone to actually do the co-sell day to day activities to help them get in front of customers. >> Probably the number one request that we always ask for Amazon is can we wish that SOC report, oh download it on the console, which we use all the time. >> Exactly. >> But security's a big deal. SREs are evolve in that role of DevOps is taking on DevSecOps. I could see a lot of customers having that need for a relationship to move things faster. Do you guys provide like escalation or is that a part of a service or not part of? >> So the partner development manager can be an escalation point, absolutely. Think of them as an extension of your business inside of AWS. >> Great and you guys, how is that partner managers measured? >> On those three pillars. >> Got it, okay. >> Are we building valuable use cases? So product development. Go to market, so go to market activities. Think blog posts, webinars, case studies, so on and so forth. And then co-sell. Not only are we helping these partners win their current opportunities that they are sourcing, but can we also help them source net new deals? >> Jeff: Yeah. >> That's very important. Top ask from the partners is get me in front of customers. Not an easy task, but that's a huge goal of ours to help them grow their top line. >> In fact, we have some interviews here on theCUBE earlier talking about that dynamic of how enterprise customers are buying. And it's interesting, a lot more POCs. I have one partner here that you guys work with on observability. They got a huge POC with Capital One and the enterprises are engaging the startups and bringing them in. So the combination of open source software, enterprises are leaning into that hard and bringing young growing startups in. So I could see that as a huge service that you guys can bring people in. >> Right and they're bringing massively differentiated technology to the table. The challenge is they just might not have the brand recognition that the big guys have. And so that's our job is how do you get that great tech in front of the right situations. >> So my next question is about the show here and then we'll talk globally. So here in San Francisco, Silicon Valley, bay area, San Francisco bay area, a lot of startups, a lot of VCs, a lot of action. So probably a big marker for you guys. So what's exciting here in SF? And then outside of SF, you guys have a global program. You see any trends that are geography-based or is it areas more mature? There's certain regions that are better. And I just interviewed a company here that's doing AWS Edge really well. It's interesting that the partners are filling a lot of holes and gaps in the opportunities with AWS. So what's exciting here, and then what's the global perspective? >> Yeah, totally. So obviously, a ton of partners from the bay area that we support, but we're seeing a lot of really interesting technology coming out of EMEA specifically. And making a lot of noise here in the United States, which is great. And so we definitely have that global presence and starting to see super differentiated technology come out of those regions. >> Yeah, especially Tel Aviv. >> Yeah. >> EMEA real quick before you get into surge. It's interesting. The VC market in Europe is hot. They've got a lot of unicorns coming in. We've seen a lot of companies coming in. They're kind of rattling their own cage right now. Hey, look at us. Let's see if they crash, but we don't see that happening. I mean, people have been predicting a crash now in the startup ecosystem for at least a year. It's not crashing. In fact, funding's up. >> The pandemic was hard on a lot of startups for sure. >> Jeff: Yeah. >> But what we've seen is many of these startups, as quickly as they can grow, they can also pivot as well. And so I've actually seen many of our startups grow through the pandemic because their use cases are helping customers either save money, become more operationally efficient, and provide value to leadership teams that need more visibility into their infrastructure during a pandemic. >> It's an interesting point. I talked to Andy Jassy and Adam Selipsky both say the same thing during the pandemic. Necessity is the mother of all invention. And startups can move fast. So with that, you guys are there to assist. If I'm a startup and I got to pivot, 'cause remember iterate and pivot, iterate and pivot so you get your economics. That's the playbook of the ventures and the models. >> Yeah, exactly. >> How do you guys help me do that? Give an example, walk me through. Pretend me I'm a startup. Hey, I am on the cloud. Oh my God, pandemic. They need video conferencing. Hey CUBE, what do I need? Serge, what do I do? >> That's a good question. First thing is just listen. I think what we have to do is a really good job of listening to the partner. What are their needs? What is their problem statement and where do they want to go at the end of the day? And oftentimes because we've worked with so many successful startups that have come out of our program, we of either through intuition or a playbook determine what is going to be the best path forward and how do we get these partners to stop focusing on things that will eventually just be a waste of time and or not provide or bring any fruit to the table, which essentially revenue. >> Well, we love startups here in theCUBE because one, they have good stories, they're on cutting edge, always pushing the envelope, and they're kind of disrupting someone else. And so they usually have an opinion they don't mind sharing on camera. So love talking to startups. We love working with you guys on our Startup Showcase, awsstartups.com. Check out awsstartups.com and check out the showcases. Final word, I'll give you guys the last word. What's the bottom line, bumper sticker for the global APN program? Summarize the opportunity for startups, what you guys bring to the table and we'll close it out. Jeff, we'll start with you. >> Totally, yeah. I think the AWS Global Startup Program's here to help companies truly accelerate their business, full stop. And that's what we're here for. >> I love it. It's a good way to put it. >> Ditto? >> Yeah. >> All right. Serge, Jeff, thanks for coming on. >> Thanks John. >> Great to see you. Love working with you guys. Hey, startups need help and the growing and huge market opportunities, the shift cloud scale, data engineering, security, infrastructure, all the markets are exploding in growth because of the digital transformation of realities here, open source and cloud. All making it happen here in theCUBE in San Francisco, California. I'm John Furrier your host. Thanks for watching. >> Let's go, John. (soft music)

More bottoms up and have more technical early adopters. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software and it starts with great technical founders with great products and great bottoms of emotions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background, super smart, but Myer of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is all companies there's no, I mean, consumer is enterprise now, everything is what was once a niche. No, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. <laugh> but remember, like right now there's also a tech and VC conference in Miami <laugh> and it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, >>Ts is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. >>Well, and, and I think all of us here that are, uh, may maybe students of history and have been involved in open source in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three >>Movement. The hype is definitely one web three. Yeah. >>But, >>But you know, >>For sure. Yeah, no, but now you're taking us further east of Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case now? And maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many measures over, uh, $500 billion in growing, you know, 20 to 30% a year. So it it's a, it's a just incredibly fast, well, >>Let's get, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant <laugh> but there's also the hype of like the web three, for instance, but you know, for, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Luman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, higher, a direct sales force and SAS kind of crushed that now SAS is being redefined, right. So what is SAS is snowflake assassin or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, they own all my data and you know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of common across all successful startups and the overall adoption of technology. Um, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually like growth, right. They're one and the same. So sometimes people think the product, uh, is what is driving growth. >>You just pull the product >>Through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this, but maybe started with open source where users were contributors, you know, contributors were users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing. It's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the, and they're really the, the beneficiaries and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a gen Xer technically. So for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I have what been saying on the cube for probably about eight years now that we are gonna hit digital hippie revolution, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one other group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. You, we hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>During the mainframe days, those renegades were breaking into Stanford, starting the home group. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on. Well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal it'll trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion yeah. Around the way in which a product is built. Right. And we can use open source, one example of that religion. Some people will say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? Yeah. It's so it's something that people just believe to be true almost without, uh, necessarily caring >>About data. Data drives all decision making. Let me ask you this next question. As a VC. Now you look at pitch, well, you've been a VC for many years, but you also have the founder entrepreneurial mindset, but you can get empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of it's about believing in the person. So faking it till you make it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. >>Oh, AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur. Right. And the persona of the entrepreneur would be, you know, so somebody who was a great salesperson or somebody who tell a great story, and I still think that that's important, right. It still is a human need for people to believe in narratives and stories. Yeah. But having said that you're right. The proof is in the pudding, right. At some point you click download and you try the product and it does what it says it gonna it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in the new economy that we live in, really, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative of because their product begins exactly >>The volume you back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song is the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, like the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with. Right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the it's gotta speak to the, >>Speak to the user, but let me ask a question now that for the people watching, who are maybe entrepreneurial entre, preneurs, um, masterclass here in session. So I have to ask you, do you prefer, um, an entrepreneur come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine with you an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do, do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think something will become. Right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way. And we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be the, of more likely somebody is gonna align with your vision and, and wanna invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I, you gotta >>Show the >>Path. I think the single most important thing for any founder and VC relationship is that they have the same vision. Uh, if you have the same vision, you can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle. The journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the latest trends because it's over before you can get there. >>Exactly. I think many people that, that do what we do for a living, we'll say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. <laugh> so you, you know, you sort of have to balance the, you know, we, we know that the world is going in this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but some times it happens in six months. Sometimes it takes six years. Sometimes it takes 16 years. Uh, >>What's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Bel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There's three big trends that we invest in. And the they're the only things we do day in, day out one is the explosion and open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen, an alwa timeline >>Happening forever. >>But, uh, it is, it is accelerating faster than we've ever seen. So I, I think it's, it's one big, massive wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now, a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a market as any of the other markets that we invest in. Uh, and finally, it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is underinvested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a dessert do over, right? I mean, do we need you do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cybersecurity as an add-on. Yeah. But if you think about it, the whole economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is run $150 billion. And it still is a fraction of what we're, >>What we're and national security even boom is booming now. So you get the convergence of national security, geopolitics, internet digital that's >>Right. You mean arguably, right? I mean, arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say, you gotta love your firm. Love. You're doing we're big supporters, your mission. Congratulations on your entrepreneurial venture. And, uh, we'll be, we'll be talking and maybe see a Cuban. Uh, absolutely not. Certainly EU maybe even north Americans in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for helping me on the show. >>Guess be VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California. After this short break, stay with us. Everyone. Welcome to the cue here. Live in San Francisco. K warn you for AWS summit 2022 we're live we're back with events. Also we're virtual. We got hybrid all kinds of events. This year, of course, summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube. Got a great guest here, Justin Kobe owner, and CEO of innovative solutions. Their booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us the story. What do you guys do? What's the elevator pitch. >>Yeah. <laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to mid-size businesses that are moving to the cloud, or have already moved to the cloud and really trying to understand how to best control security, compliance, all the good stuff that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is, but now we have offices down in Austin, Texas, up in Toronto, uh, Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago. And it's been a great ride. >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by a of us. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization, but obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? >>Yeah. It's a great question. Every CEO I talk to, that's a small mids to size business. They're all trying to understand how to leverage technology better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech is really at the, at the forefront and the center of that. So most customers are coming to us and they're of like, listen, we gotta move to the cloud or we move some things to the cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then so, uh, progressively working through a modernization strategy is always the better approach. And so we spend a lot of time with small to mid-size businesses who don't have the technology talent on staff to be able to do >>That. Yeah. And they want to get set up. But the, the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is not it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem. And you guys solve >>In the SMB space. The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and our hardened solutions. And so, um, what we try to do with, to technology staff that has traditional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether that's, we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to yeah. Feel like, listen, at the end of the day, I'm gonna be spending money in one place or another, whether that's on primer in the cloud, I just want know that I'm doing that way. That helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. Good. >>How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I think there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start down your journey in one way and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's a, gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning, the projects that early, not worrying about it, you got it mean most people don't abandon stuff cuz they're like, oh, I own it. >>Exactly. >>And they get, they get used to it. Like, and then they wait too long. >>That's exactly. >>Yeah. Frog and boiling water, as we used to say, oh, it's a great analogy. So I mean, this, this is a dynamic. That's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you guys come in. I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talked to at reinvent, that's a customer. Well, how many announcements did Andy jazzy announcer Adam? You know, the 5,000 announcement or whatever. They did huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just processes. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are >>Values. >>Our mission is, is very simple. We want to help every small to midsize business leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a 10 a company in the process of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning they know that we have their back and we're the safety net. So when a customer is saying, right, I'm gonna spend a couple thousand and dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going in alone. Who's there to help protect that. Number two, if you have a security posture and let's just say your high profile and you're gonna potentially be more vulnerable to security attacks. If you have a partner that's offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products, uh, that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own. It, it would cost 'em a four, >>The training alone would be insane. A risk factor. I mean the cost. Yes, absolutely opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018. When, uh, when we, he made the decision to go all in on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious, it wasn't requirement. It still isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front >>Desk and she could be running the Kubernetes clusters. I >>Love it. It's >>Amazing. >>But I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get >>The right people with. And that's a cultural factor that you guys have. So, so again, this is back to my whole point out SMBs and businesses in general, small and large it staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the buildout, um, uh, return factor, ROI piece. At what point in time as an owner, SMB, do I get to ROI? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cyber security issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one in the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Like critical issues. >>This is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about this, >>That's, that's what, at least a million in loading, if not three or more Just to get that app going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side. No. And they remind AI and ML. >>That's right. That's right. So to try to go it alone, to me, it's hard. It it's incredibly difficult. And the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll do all that exactly. In the it department. >>Exactly. >>So like, can we just call up, uh, you know, our old vendor that's >>Right. <laugh> right. Our old vendor. I like it, >>But that's so true. I mean, when I think about how, if I was a business owner starting a business today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. It's something that we talk about every, with every one of our small to mid-size >>Businesses. So just, I want get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative yeah. Award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, I was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduced other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. Yeah. I came in, I did an internship for six months and I loved it. I learned more in those six months than I probably did in my first couple of years at, uh, at RT long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2000 and I was like, Hey, I'm growing the value of this business. And who knows where you guys are gonna be another five years? What do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner. But if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that were gonna also buy the business with me. >>And they were the owners, no outside capital, >>None zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons. They all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like, if we're own, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015 and, uh, we made the decision that I was gonna buy the three partners out, um, go through an earn out process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the BI cuz they cared very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting all going all in on the cloud was important for us. And we haven't looked back. >>And at that time, the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly the, uh, and those kinds of big enterprises. The GA I don't wanna say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to midsize business to migrate completely to the cloud is as infrastructure was considered, that just didn't happen as often. Um, what we were seeing where the, a lot of our small to midsize business customers, they wanted to leverage cloud based backup, or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration. The, the Microsoft suite to the cloud. And a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on AWS at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is the app modernization? Is it data? What's the hot product and then put a plugin for the company. Awesome. >>So, uh, there's no question. Every customer is looking migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating into the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customer is not to be cash strapped and gives them an opportunity to move forward in a controlled, contained way so they can modernize. So >>Like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers and being empathetic to where they are in their journey. >>And that's the cloud upside is all about doubling down on the variable win that's right. Seeing the value and ING down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate >>It. Thank you very much for having me. >>Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching. We're back with more great coverage for two days after this short break >>Live on the floor in San Francisco for Aus summit. I'm John for host of the cube here for the next two days, getting all the actual back in person we're at AWS reinvent a few months ago. Now we're back events are coming back and we're happy to be here with the cube. Bring all the action. Also virtual. We have a hybrid cube, check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticking off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad to be here. >>So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to be back through events. It's >>Amazing. This is the first, uh, summit I've been to, to in what two, three >>Years. That's awesome. We'll be at the, uh, a AWS summit in New York as well. A lot of developers and the big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything devs sec ops, everyone kind of sees that you got containers, you got Benet, he's got cloud native. So the, the game is pretty much laid out. Mm-hmm <affirmative> and the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's >>Right. Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions. The at our around, especially the edge public cloud for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give >>An example, >>Uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech data and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running or FinTech on top of AWS services inside Panama. >>You know, what's interesting, Matthew is that we've been covering Aw since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and became the CEO. Now Adam slaps in charge, but the edge has always been that thing they've been trying to avoid. I don't wanna say trying to avoid, of course, Amazon would listens to the customer. They work backwards from the customer. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does >>Computing. >>It >>Does. That's not centralized in the public cloud now they got regions. So what is the issue with the edge what's driving? The behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see with the data at the edge, you got five GM having. So it's pretty obvious, but there was a slow transition. What was the driver for the edge? What's the driver now for edge action for AWS >>Data in is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation. Whereas today we have over 15 AWS edge services and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always use the riff on the cube, uh, cause it's basically Amazon in a box, pushed in the data center, running native, all this stuff, but now cloud native operations are kind of becoming standard. You're starting to see some standard. Deepak syncs group is doing some amazing work with opensource Raul's team on the AI side, obviously, uh, you got SW who's giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see local zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my datas center, do I want to manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outpost. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone now happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware can go deploy EKS anywhere in your VMware environment. And it's increasing the speed of adoption >>For sure. Right? So you guys are making a lot of good business decisions around managed cloud service. That's right. Innovative. Does that get the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in these new areas that you're helping out are they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their availability zones or their regions that you guys are delivering. What's the key is that they don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on what's making them money as a business. They wanna focus on their applications. They wanna focus on their customers. So they look towards AWS cloud and a AWS. You take the infrastructure, you take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. Uh, we help build out these things in local data centers for 32 plus year old company. We have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're that gap in helping deploy these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. So >>Basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it >>Works? Right. And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy fin in the Caribbean, we're gonna talk about hurricanes. And we're gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where now have data and you have applications that are tapping into that, that requirement. It makes total sense. We're seeing that across the board. So it's not like it's a, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech. And in, in the islands there a lot of, lot of, lot of web three happening. What's your, what your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto to underlie parts of their central banks. Yeah. Um, so it's, it's up and coming. Uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a, uh, technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure, because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on >>It's interesting. I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, project going on. But if you look talk to all the crypto people that say, look, we do a smart contract, we use the blockchain. It's kind of over a lot of overhead and it's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain just for like smart contracts, for instance, or certain transactions. And they go to Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service. Well, what happened to decentralized? >>Yeah. And that's, and that's the conversation performance issue. Yeah. And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through, uh, a use case of a customer Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my a, I also want all the benefit of the cloud. So I want the modern, and I wanna migrate to the cloud for all those cloud benefits and the goodness of the cloud. What's the answer. >>Yeah. Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment that, that manufacturing plant can be hooked up, they don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with a regular commercially available hardware running VMware, and we deploy EKS anywhere on that. Inside of that manufacturing plant, we can do pre-procesing on things coming out of the robotics, depending on what we're manufacturing. Right. And then we can take those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard >>For data, data lake, or whatever, >>To the data lake. Yeah. Data lake house, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but a lot of that, uh, just in time business decisions, just time manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going to the data that saves that cost yeah. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data unless you have to. Um, but those new things are developing. So I wanna ask you what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacturing, industrial, whatever, the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? There's a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe, maybe this decision can wait. Right. And then how do I visualize that? By >>The way, it could be a bot tube doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture on the back. So there's new things developing. You've got more benefit. There >>Are, there are, and we have more and more people that, that want to talk less about databases and want to talk about data lakes because of this. They want to talk more about customers are starting to talk about throwing away data. Uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And well, >>I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session this, but the one pattern we're seeing come of the past year is that throwing away data's bad. Even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retrain their machine learning algorithms. Yep. So as data becomes co as we call it in our last showcase, we did a whole whole an event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw away. It's not just business benefits. Yeah. There's all kinds of new scale. There >>Are. And, and we have, uh, many customers that are running petabyte level. Um, they're, they're essentially data factories on, on, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move petabytes of data to AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a, kind of a, um, fun, I was told to ask you about your personal background on premise architect, Aus cloud, and skydiving instructor. How does that all work together? What tell, what does this mean? >>Yeah. Uh, I, >>You jumped out a plane and got a job. You got a customer to jump >>Out kind of. So I was, you jumped out. I was teaching Scott eing, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a Scott I instructor. Uh, I was teaching Scott eing and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and how his customers are working. And he can't find enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, I was living in a tent in the woods, teaching skydiving. I was like, I'd love to not live in a tent in the woods. So, uh, I started in the first day there, we had a, and, uh, EC two had just come out <laugh> um, and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that, and through being in on premises, migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services to premises. >>So it's such a great story. You know, I was gonna, you know, you know, the, the, the, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early days was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, uh, when that was coming out, it was, I mean, it was, it was still, and I, maybe it does still feel like that to some people, right. Yeah. But, uh, it was, it was the same kind of feeling that we had in the early days of AWS, the same feeling we have when we >>It's much now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting stuff like jumping out of an airplane. Yeah. You guys, the right equipment, you gotta do the right things. Exactly. >>Right. >>Matthew, thanks for coming on the cube. Really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here, lot in San Francisco for AWS summit, I'm John for your host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. Look at this calendar for all the cube, actually@thecube.net. We'll right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube, a summit 2022. We're back in person. I'm John furry host of the cube. We'll be at the, a us summit in New York city this summer, check us out then. But right now, two days in San Francisco getting all coverage, what's going on in the cloud, we got a cube alumni and friend of the cube, my dos car CEO, investor, a Sierra, and also an investor and a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you, Pam. Cool. How are you? Good. >>How are you? >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah so give us the update. How much cash have you guys raised? What's the status of the company product what's going on? First >>Of all, thank you for having me. We're back to be business with you never while after. Great to see you. Um, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. Um, we have raised close to a hundred million there. Uh, the investors are people like nor west Menlo, true ventures, coast, lo ventures, Ram Shera, and all those people, all known guys that Antibe chime Paul Mayard web. So a whole bunch of operating people and, uh, Silicon valley vs are involved. >>And has it gone? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISR is going after is what I call the applying AI for customer service. It operations, it help desk the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and ServiceNow to take it to the next stage? Well, >>I love having you on the cube, Dave and I, and Dave Valenti as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a, you're like a guest analyst. <laugh>, >>You know, >>You >>Get, the comment is fun to talk to you though. >>You get the commentary, you, your, your finger on the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud out scale. You predicted that we talked about in the cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing Docker just raised a hundred million on our $2 billion valuation back from the dead after they pivoted from an enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control, plane emerging, AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded observability there's 10 million observability companies. Data is the key. This is what's your angle on this. What's your take. Yeah, >>No, look, I think I'll give you the view that I see, right? I, from my side, obviously data is very clear. So the things that room system of record that you and me talked about, the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud native, it'll be called AI. NA NA is a new buzzword and using the AI for customer service, it operations. You talk about observability. I call it AI ops, applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and AI service desk. What needs to be helped desk with ServiceNow BMC <inaudible> you see a new ALA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflows, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with AI workflows. So you'll see AI going >>Off is RPA a company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI S one will be at their event this summer? Um, or is it a product company? I mean, I mean, RPA is almost, should be embedded in everything. >>It's a feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company also, but that automation should be a, in every area. Yeah. Like we call cloud NA and AI NATO it'll become automation. NA yeah. And that's your thinking. >>It's almost interesting me. I think about the, what you're talking about what's coming to mind is I'm kind having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it was middleware. It sat between two things and then the middle and it was software was action. Now you have all kinds of workflows abstractions everywhere. Right? So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed or they integrated. I mean, these are the challenges. This is crazy. What's the, >>So don't about the databases become all polyglot databases. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area, like, as you were talking about, it should be part of ServiceNow. It should be part of ISRA, like every company, every Salesforce. So that's why you see MuleSoft and Salesforce buying RPA companies. So you'll see all the SaaS companies could cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also will have an automation as a layer <inaudible> inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind us, you got the expo hall. You got, um, we're back to vents, but you got, you know, am Clume Ove, uh, Dynatrace data dog, innovative all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right. Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Deibel later today. He's a former NEA guy and we always talk to Jerry, Jen, we know all the, the VCs. What does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation. Cloud's bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's. Yes. Basically. Data's everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders, how Amazon created the startups 15 years back, everybody built on Amazon now, Azure and GCP. The next layer would be is people don't just build on Amazon. They're gonna build it on top of snowflake. Companies are snowflake becomes a data platform, right? People will build on snowflake. Right? So I see my old boss flagman try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer. Right? So I think that's the next level of <inaudible> trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis of a couple months ago called castles in the cloud where your Mo is what you do in the cloud. Not necessarily in, in the, in the IP. Um, Dave LAN and I had last reinvent, coined the term super cloud, right? He's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage, and guys, Charles Fitzgerald out there who we like was kind of shitting on us saying, Hey, you guys terrible, they didn't get it. Like, yeah, I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> cause he's cool. Um, but snowflake is on Amazon. Now. They say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist. And, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. It >>Is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer. Remember the middle layer pass will be snowflake so I can build it on snowflake. I can use them for data layer if I really need to size build it on force.com Salesforce. Yeah. Right. So I think that's where you'll see. So >>Basically the, if you're an entrepreneur, the, the north star in terms of the, the outcome is be a super cloud. >>It is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. Yeah. >>Yeah. How are, how is Amazon and the clouds dealing with these big whales, the snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think they had Redshift. Amazon has got Redshift. Um, but Snowflake's a big customer in the, they're probably paying AWS, I think big bills too. So >>Joe on very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-optation will be there. So Amazon will have Redshift, but Amazon is also partnering with, uh, snowflake to have native snowflake data warehouses or data layer. So I think depending on the application use case, you have to use each of the above. I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that it comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, you know, foreclose, your, you that's right with some sort of internal hack. Uh, but I think, I think the general question that I have is that I, I think it's okay to have a super cloud like that because the rising tide is still happening at some point, when does the rising tide stop and do the people shopping up their knives, it gets more competitive or is it just an infinite growth? So >>I think it's growth. You call it cloud scale, you invented the word cloud scale. So I think look, cloud will continually agree, increase. I think there's as long as there more movement from on, uh, OnPrem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations. It helpless, even the customer service service now and, uh, ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go >>Made. I wanna get your thoughts for the folks watching that are, uh, enterprise buyers are practitioners, not suppliers to the more market, feel free to text me or DMing. The next question's really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products, cuz you know, the big enterprises now and you know, small, medium, large and large enterprise are all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or growing startup selling to an enterprise? Um, have you seen changes there? I mean I'm seeing some stuff, but why don't get your thoughts on that? What, >>No, it is. If I growing by or 2007 or eight, when I used to talk to you back then and Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or 1% today. Most companies are already spending 20, 30% with startups. Like if I look at a CIO or line of business, it's gone. Yeah. Can it go more? I think it can in the next four, five years. Yeah. Spending on the startups. >>Yeah. And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I reference the URL cause it's like, there's like a bunch of companies we've been promoting because the solutions that startups have actually are new stuff. Yes. It's bending, it's shifting for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there. Um, and goes back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure is code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share >>Yourself a lot of first is I see the AIOP solutions in the future should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app Dyna, right? Dynatrace, all this solution. We will go future towards predict to proactive solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service desk. Customers are give the data, share the data because we thought the data algorithms are useless. I can them, but I gotta train them, modify them, tweak them, make them >>Better, >>Make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to big data days back in 2009, you know, >>Look at, look how much data Rick has grown. >>It is. They doubled the >>Key cloud air kinda went private. So good stuff, man. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking at that growing customers and my customers are some of them, you like it's zoom auto desk McAfee, uh, grand to so all the top customers, um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on predict is one area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service. >>Great stuff, man. Great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of Aish summit 2022. And we're gonna be at Aus summit in San, uh, in New York in the summer. So look for that on this calendar, of course go to eight of us, startups.com. I mentioned that it's decipher all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This the cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back, little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit in new York's coming in the summer. We'll be there too with the cube on the set. We're getting back in the groove psych to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're can see a lot of virtual cube outta hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economists with bill group. He's the founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank >>You. Thanks. Coming on. Sure is a lot of words to describe is shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at mark, Andrew's been doing a lot of shit posting lately. All a billionaires are shit hosting, but they don't know how to do it. Like they're not >>Doing it right? So there's something opportunity there. It's like here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a midsize island, do begin doing this from, oh, then we're having fun. >>This shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on this side I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what is shit posting? >>It's more or less talking about the world of enter prize technology, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream. But it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a jackass or more prosaically are worried about getting fired for better or worse. I don't don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, coupons coming up in Spain, which they're having a physical event, you see the growth of cloud native Amazon's of all the Adams, especially new CEO. Andy's move on to be the chief of all Amazon. Just so I'm the cover of was it time met magazine? Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything. These folks do. They're they're effectively in a fishbowl, but I have trouble imagining the logistics. It takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. And it's, it's sprawling immense that dominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. >>Well, there's a lot of force for good conversations. Seeing a lot of that going on, Amazon's trying to port eight of us is trying to portray themselves as you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. <laugh> either way, sounds like more exciting. Like I better >>Have a replacement ready <laugh> I, in case something goes wrong on the track, highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula one is they have these new rigs out. Yeah. Where you can actually race in east sports with other people in pure simulation of the race car. You gotta get the latest and videographic card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. >>Oh, it's great too. And I can see the appeal of these tech companies getting into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going on in your world. I know you have a lot of great success. We've been following you in the queue for many, many years. Got a great newsletter, check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's the blowback, any blowback late? Has there been uptick? What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's high. I'm emailing an awful lot of people at last week in AWS every week and okay. They must not have heard me it. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do >>That. We should do that. Actually. I think you're people would call in, oh, >>I, I think >>I guarantee we had that right now. People would call in and say, Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised about anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the >>Customer. You know, I always joke with Dave Alane about how John Fort's always at, uh, um, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0, 0 5, or we can't call, we >>Have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And then there you go. Yeah. >>It's and the old joke at HP was if they, if they invented SU sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish. That's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their >>Producting. So they're going in different directions. When they named Amazon Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonused on number of words, they can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, session manager is a great one. I love the service ridiculous name. They have a systems manager, parameter store, which is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage your parameter store does not. It's fun. >>What's your, what's your favorite combination of acronyms >>Combination >>Of gots. You got EMR, you got EC two, you got S3 SQS. Well, RedShift's not an acronym you >>Gets is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation, they >>Shook up bean stock or is that still around? Oh, >>They never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, well, we built this thing in 2005 and everyone hates it, but while we certainly can't change it, now it has three customers on it. John three <laugh>. Okay. Simple BV still haunts our dreams. >>I, I actually got an email on, I saw one of my, uh, servers, all these C twos were being deprecated and I got an email I'm I couldn't figure out. Why can you just like roll it over? Why, why are you telling me? Just like, give me something else. All right. Okay. So let me talk about, uh, the other things I want to ask you, is that like, okay. So as Amazon better in some areas where do they need more work in your opinion? Because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database Snowflake's got out database service. So Redshift, snowflake data breach is out there. So you got this co-op petition. Yes. How's that going? And what do you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with, and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want. And they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multicloud. Cause obviously the other cloud shows are coming up. Amazon hated that word multicloud. Um, a lot of people though saying, you know, it's not a real good marketing word. Like multicloud sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multicloud? >>Multiple single >>Cloudant loves that term. Yeah. >>You know, you're building in multiple single points of failure, do it for the right reasons or don't do it as a default. I believe not doing it is probably the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about my multi-cloud either as the industry leader, let's talk about other clouds, bad direction to go in from a market cap perspective. It doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of forms. Some brilliant, some brain dead. It depends a lot on, but my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing because it solves problems. That's when I shut up and listen. >>Yeah, course. Awesome. Corey, I gotta ask you a question cause I know you we've been, you know, fellow journeyman and the, and the cloud journey going to all the events and then the pandemic hit. We now in the third year, who knows what it's gonna gonna end. Certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations. Community's gonna emerge. You've got a pretty big community growing and it's growing like crazy. What's the weirdest or coolest thing or just big changes you've seen with the pandemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece, come in, you're commentating, you're calling balls and strikes in the industry. You got a great team developing over there. Duck build group. What's the big aha moment that you saw with the pandemic. Weird, funny, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who can pony up two grand and a week in Las Vegas and get to Las Vegas from wherever they happen to be by moving virtually suddenly it, it embraces the reality that talent is evenly. Distributed. Opportunity is not. And that means that suddenly these things are accessible to a wide swath of audience and potential customer base and the rest that hadn't been invited to the table previously, it's imperative that we not lose that. It's nice to go out and talk to people and have people come up and try and smell my hair from time to time, I smelled delightful. Let me assure you. But it was, but it's also nice to be. >>I have a product for you if you want, you know? Oh, >>Oh excellent. I look forward to it. What is it? Pudding? Why not? <laugh> >>What else have you seen? So when accessibility for talent. Yes. Which by the way is totally home run. What weird things have happened that you've seen? Um, that's >>Uh, it's, it's weird, but it's good that an awful lot of people giving presentation have learned to tighten their message and get to the damn point because most people are not gonna get up from a front row seat in a conference hall, midway through your Aing talk and go somewhere else. But they will change a browser tab and you won't get them back. You've gotta be on point. You've gotta be compelling if it's going to be a virtual discussion. Yeah. >>And you turn off your iMessage too. >>Oh yes. It's always fun in the, in the meetings when you're ho to someone and their colleague is messaging them about, should we tell 'em about this? And I'm sitting there reading it and it's >>This guy is really weird. Like, >>Yes I am and I bring it into the conversation and then everyone's uncomfortable. It goes, wow. Why >>Not? I love when my wife yells at me over I message. When I'm on a business call, like, do you wanna take that about no, I'm good. >>No, no. It's better off. I don't the only entire sure. It's >>Fine. My kids text. Yeah, it's fine. Again, that's another weird thing. And, and then group behavior is weird. Now people are looking at, um, communities differently. Yes. Very much so, because if you're fatigued on content, people are looking for the personal aspect. You're starting to see much more of like yeah. Another virtual event. They gotta get better. One and two who's there. >>Yeah. >>The person >>That's a big part of it too is the human stories are what are being more and more interesting. Don't get up here and tell me about your product and how brilliant you are and how you built it. That's great. If I'm you, or if I wanna work with you or I want to compete with you or I want to put on my engineering hat and build it myself. Cause why would I buy anything? That's more than $8. But instead, tell me about the problem. Tell me about the painful spot that you specialize in. Yeah. Tell me a story there. >>I, I think >>That gets a glimpse in a hook and makes >>More, more, I think you nailed it. Scaling storytelling. Yes. And access to better people because they don't have to be there in person. I just did a thing. I never, we never would've done the queue. We did. Uh, Amazon stepped up in sponsors. Thank you, Amazon for sponsoring international women's day, we did 30 interviews, APAC. We did five regions and I interviewed this, these women in Asia, Pacific eight, PJ, they call for in this world. And they're amazing. I never would've done those interviews cuz I never, would've seen 'em at an event. I never would've been in pan or Singapore, uh, to access them. And now they're in the index, they're in the network. They're collaborating on LinkedIn. So a threads are developing around connections that I've never seen before. Yes. Around the content. >>Absolutely >>Content value plus and >>Effecting. And that is the next big revelation of this industry is going to realize you have different companies. And, and I Amazon's case different service teams all competing with each other, but you have the container group and you have the database group and you have the message cuing group. But customers don't really want to build things from spare parts. They want a solution to a problem. I want to build an app that does Twitter for pets or whatever it is I'm trying to do. I don't wanna basically have to pick and choose and fill my shopping cart with all these different things. I want something that's gonna basically give me what I'm trying to get as close to turnkey as possible. Moving up the stack. That is the future. And just how it gets here is gonna be >>Well we're here at Corey Quinn, the master of the master of content here in the a ecosystem. Of course we we've been following up from the beginning. His great guy, check out his blog, his site, his newsletter screaming podcast. Corey, final question for, uh, what are you here doing? What's on your agenda this week in San Francisco and give a plug for the duck build group. What are you guys doing? I know you're hiring some people what's on the table for the company. What's your focus this week and put a plug in for the group. >>I'm here as a customer and basically getting outta my cage cuz I do live here. It's nice to actually get out and talk to folks who are doing interesting things at the duck bill group. We solved one problem. We fixed the horrifying AWS bill, both from engineering and architecture, advising as well as negotiating AWS contracts because it turns out those things are big and complicated. And of course my side media projects last week in aws.com, we are, it it's more or less a content operation where I in my continual and ongoing love affair with the sound of my own voice. >><laugh> and you're good. It's good content it's on, on point fun, Starky and relevant. So thanks for coming to the cube and sharing with us. Appreciate it. No >>Thank you button. >>You. Okay. This the cube covers here in San Francisco, California, the cube is back going to events. These are the summits, Amazon web services summits. They happen all over the world. We'll be in New York and obviously we're here in San Francisco this week. I'm John fur. Keep, keep it right here. We'll be back with more coverage after this short break. Okay. Welcome back everyone. This's the cubes covers here in San Francisco, California, we're live on the show floor of AWS summit, 2022. I'm John for host of the cube and remember AWS summit in New York city coming up this summer, we'll be there as well. And of course reinvent the end of the year for all the cube coverage on cloud computing and AWS two great guests here from the APN global APN Sege chef Jenko and Jeff Grimes partner lead Jeff and Sege is doing partnerships global APN >>AWS global startup program. Yeah. >>Okay. Say that again. >>AWS. We'll start >>Program. That's the official name. >>I love >>It too long, too long for me. Thanks for coming on. Yeah, >>Of course. >>Appreciate it. Tell us about what's going on with you guys. What's the, how was you guys organized? You guys we're obviously we're in San Francisco bay area, Silicon valley, zillions of startups here, New York. It's got another one we're gonna be at tons of startups. A lot of 'em getting funded, big growth and cloud big growth and data secure hot in all sectors. >>Absolutely. >>So maybe, maybe we could just start with the global startup program. Um, it's essentially a white glove service that we provide to startups that are built on AWS. And the intention there is to help identify use cases that are being built on top of AWS. And for these startups, we want to pro vibe white glove support in co building products together. Right. Um, co-marketing and co-selling essentially, um, you know, the use cases that our customers need solved, um, that either they don't want to build themselves or are perhaps more innovative. Um, so the, a AWS global startup program provides white glove support. Dedicat at headcount for each one of those pillars. Um, and within our program, we've also provided incentives, programs go to market activities like the AWS startup showcase that we've built for these startups. >>Yeah. By the way, AWS startup, AWS startups.com is the URL, check it out. Okay. So partnerships are key. Jeff, what's your role? >>Yeah. So I'm responsible for leading the overall effort for the AWS global startup program. Um, so I've got a team of partner managers that are located throughout the us, uh, managing a few hundred startup ISVs right now. <laugh> >>Yeah, you got a >>Lot. We've got a lot. >>There's a lot. I gotta, I gotta ask a tough question. Okay. I'm I'm a startup founder. I got a team. I just got my series a we're grown. I'm trying to hire people. I'm super busy. What's in it for me. Yeah. What do you guys bring to the table? I love the white glove service, but translate that what's in it for what do I get out of it? What's >>A story. Good question. I focus, I think. Yeah, because we get, we get to see a lot of partners building their businesses on AWS. So, you know, from our perspective, helping these partners focus on what, what do we truly need to build by working backwards from customer feedback, right? How do we effectively go to market? Because we've seen startups do various things, um, through trial and error, um, and also just messaging, right? Because oftentimes partners or rather startups, um, try to boil the ocean with many different use cases. So we really help them, um, sort of laser focus on what are you really good at and how can we bring that to the customer as quickly as possible? >>Yeah. I mean, it's truly about helping that founder accelerate the growth of their company, right. And there's a lot that you can do with AWS, but focus is truly the key word there because they're gonna be able to find their little piece of real estate and absolutely deliver incredible outcomes for our customers. And then they can start their growth curve there. >>What are some of the coolest things you've seen with the APN that you can share publicly? I know you got a lot going on there, a lot of confidentiality. Um, but you know, we're here a lot of great partners on the floor here. I'm glad we're back at events. Uh, a lot of stuff going on digitally with virtual stuff and, and hybrid. What are some of the cool things you guys have seen in the APN that you can point to? >>Yeah, absolutely. I mean, I can point to few, you can take them. So, um, I think what's been fun over the years for me personally, I came from a startup brand sales at an early stage startup and, and I went through the whole thing. So I have a deep appreciation for what these guys are going through. And what's been interesting to see for me is taking some of these early stage guys, watching them progress, go public, get acquired and see that big day mm-hmm <affirmative>, uh, and being able to point to very specific items that we help them to get to that point. Uh, and it's just a really fun journey to watch. >>Yeah. I, and part of the reason why I really, um, love working at the AWS, uh, global startup program is working with passionate founders. Um, I just met with a founder today that it's gonna, he's gonna build a very big business one day, um, and watching them grow through these stages and supporting that growth. Um, I like to think of our program as a catalyst for enterprise is sort of scale. Yeah. Um, and through that we provide visibility, credibility and growth opportunities. >>Yeah. A lot, a lot of partners too. What I found talking to staff founders is when they have that milestone, they work so hard for it. Whether it's a B round C round Republic or get bought. Yeah. Um, then they take a deep breath and they look back at wow, what a journey it's been. So it's kind of emotional for sure. But still it's a grind. Right? You gotta, I mean, when you get funding, it's still day one. You don't stop. It's no celebrate, you got a big round or valuation. You still gotta execute >>And look it's hypercompetitive and it's brutally difficult. And our job is to try to make that a little less difficult and navigate those waters. Right. Where ever everyone's going after similar things. >>Yeah. And I think as a group element too, I observe that startups that I, I meet through the APN has been interesting because they feel part of AWS. Yeah, totally. As a group of community, as a vibe there. Um, I know they're hustling, they're trying to make things happen. But at the same time, Amazon throws a huge halo effect. I mean, that's a huge factor. I mean, you guys are the number one cloud in the business, the growth in every sector is booming. Yeah. And if you're a startup, you don't have that luxury yet. And look at companies like snowflake that built on top of AWS. I mean, people are winning by building on AWS. >>Yeah. And our, our, our program really validates their technology first. So we have, what's all the foundation's technical review that we put all of our startups through before we go to market. So that when enterprise customers are looking at startup technology, they know that it's already been vetted. And, um, to take that a step further and help these partners differentiate, we use programs like the competency programs, the DevOps competencies, the security competency, which continues to help, um, provide sort of a platform for these startups, help them differentiate. And also there's go to market benefits that are associated with that. >>Okay. So let me ask the, the question that's probably on everyone's mind, who's watching, certainly I asked this a lot. There's a lot of companies startups out there who makes the cut, is there a criteria cut? It's not like it's sports team or anything, but like sure. Like there's activate program, which is like, there's hundreds of thousands of startups out there. Not everyone is at the APN. Right? Correct. So ISVs again, that's a whole nother, that's a more mature partner that might have, you know, huge market cap or growth. How, how do you guys focus? How do you guys focus? I mean, you got a good question, you know, thousand flowers blooming all the time. Is there a new way you guys are looking at it? I know there's been some talk about restructure or, or new focus. What's the focus. >>Yeah. It's definitely not an easy task by any means. Um, but you know, I recently took over this role and we're really trying to establish focus areas, right. So obviously a lot of the ISVs that we look after are infrastructure ISVs. That's what we do. Uh, and so we have very specific pods that look after different type of partners. So we've got a security pod, we've got a DevOps pod, we've got core infrastructure, et cetera. And really, we're trying to find these ISVs that can solve, uh, really interesting AWS customer. >>You guys have a deliberate, uh, focus on these pillars. So what infrastructure, >>Security, DevOps, and data and analytics, and then line of business >>Line, business line business, like web >>Marketing, business apps, >>Owner type thing. Exactly. >>Yeah, exactly. >>So solutions there. Yeah. More solutions and the other ones are like hardcore. So infrastructure as well, like storage back up ransomware kind of stuff, or, >>Uh, storage, networking. >>Okay. Yeah. The classic >>Database, et cetera. Right. >>And so there's teams on each pillar. >>Yep. So I think what's, what's fascinating for the startups that we cover is that they've got, they truly have support from a build market sell perspective, right. So you've got someone who's technical to really help them get the technology, figured out someone to help them get the marketing message dialed and spread, and then someone to actually do the co-sell, uh, day to day activities to help them get in front of customers. >>Probably the number one request that we always ask for Amazon is can wish that sock report, oh, download it on the console, which we use all the time. <laugh> exactly. But security's a big deal. I mean, you know, ask the res are evolving, that role of DevOps is taking on dev SecOps. Um, I, I can see a lot of customers having that need for a relationship to move things faster. Do you guys provide like escalation or is that a part of a service or that not part of, uh, uh, >>Yeah, >>So the partner development manager can be an escalation for absolutely. Think of that. 'em as an extension of your business inside of AWS. >>Great. And you guys, how is that partner managers, uh, measure >>On those three pillars? Right. Got it. Are we billing, building valuable use cases? So product development go to market, so go to market activities, think blog, posts, webinars, case studies, so on and so forth. And then co-sell not only are we helping these partners win their current opportunities that they are sourcing, but can we also help them source net new deals? Yeah. Right. That's very, >>I mean, top asked from the partners is get me in front of customers. Right. Um, not an easy task, but that's a huge goal of ours to help them grow their top line. >>Right. Yeah. In fact, we had some interviews here on the cube earlier talking about that dynamic of how enterprise customers are buying. And it's interesting, a lot more POCs. I have one partner here that you guys work with, um, on observability, they got a huge POC with capital one mm-hmm <affirmative> and the enterprises are engaging the star ups and bringing them in. So the combination of open source software enterprises are leaning into that hard and bringing young growing startups in mm-hmm <affirmative>. Yep. So I could see that as a huge service that you guys can bring people in. >>Right. And they're bringing massively differentiated technology to the table. The challenge is they just might not have the brand recognition. The, at the big guys have mm-hmm <affirmative>. And so that's, our job is how do you get that great tech in front of the right situations? >>Okay. So my next question is about the show here, and then we'll talk globally. So here in San Francisco sure. You know, Silicon valley bay area, San Francisco bay area, a lot of startups, a lot of VCs, a lot of action. Mm-hmm <affirmative> so probably a big market for you guys. Yeah. So what's exciting here in SF. And then outside of SF, you guys have a global pro, have you see any trends that are geography based or is it sure areas more mature? There's certain regions that are better. I mean, I just interviewed a company here. That's doing, uh, a AWS edge really well in these cases. It's interesting that these, the partners are filling a lot of holes and gaps in the opportunities with a AWS. So what's exciting here. And then what's the global perspective. >>Yeah, totally. So obviously see a ton of partners from the bay area that we support. Um, but we're seeing a lot of really interesting technology come out of AMEA specifically. Yeah. Uh, and making a lot of noise here in the United States, which is great. Um, and so, you know, we definitely have that global presence and, and starting to see super differentiated technology come out of those regions. >>Yeah. Especially Tel Aviv. Yeah. >>Amy and real quick before you get into surge. It's interesting. The VC market in, in Europe is hot. They've got a lot of unicorns coming in. We've seen a lot of companies coming in. They're kind of rattling their own, you know, cage right now. Hey, look at us. Let's see if they crash, you know, but we don't see that happening. I mean, people have been predicting a crash now in, in the startup ecosystem for least a year. It's not crashing. In fact, funding's up. >>Yeah. The pandemic was hard on a lot of startups for sure. Yeah. Um, but what we've seen is many of these startups, they, as quickly as they can grow, they can also pivot as, as, as well. Um, and so I've actually seen many of our startups grow through the demo because their use cases are helping customers either save money, become more operationally efficient and provide value to leadership teams that need more visibility into their infrastructure during a pandemic. >>It's an interesting point. I talked to Andy jazzy and Adam Celski both say the same thing during the pandemic. Necessity's the mother of all invention. Yep. And startups can move fast. So with that, you guys are there to assist if I'm a startup and I gotta pivot cuz remember iterate and pivot, iterate and pivot. So you get your economics, that's the playbook of the ventures and the models. >>Exactly. How >>Do you guys help me do that? Give me an example of what me through. Pretend me, I'm a start up. Hey, I'm on the cloud. Oh my God. Pandemic. They need video conferencing. Hey cube. Yeah. What do I need? Search? What, what do >>I do? That's a good question. First thing is just listen. Yeah. I think what we have to do is a really good job of listening to the partner. Um, what are their needs? What is their problem statement? Where do they want to go at the end of the day? Um, and oftentimes because we've worked with, so how many successful startups that have come out of our program, we have, um, either through intuition or a playbook determined what is gonna be the best path forward and how do we get these partners to stop focusing on things that will eventually, um, just be a waste of time. Yeah. And, or not provide, or, you know, bring any fruit to the table, which, you know, essentially revenue. >>Well, we love startups here in the cube because one, um, they have good stories, they're oil and cutting edge, always pushing the envelope and they're kind of disrupting someone else. Yeah. And so they, they have an opinion. They don't mind sharing on camera. So love talking to startups. We love working with you guys on our startups. Showcases startups.com. Check out AWS startups.com and she got the showcase. So is, uh, final word. I'll give you guys the last word. What's the bottom line bumper sticker for AP globe. The global APN program summarize the opportunity for startups, what you guys bring to the table and we'll close it out. Totally. We'll start >>With you. Yeah. I think the AWS global startup programs here to help companies truly accelerate their business full stop. Right. And that's what we're here for. Love it. >>It's a good way to, it's a good way to put it. Dato yeah. >>All right. Thanks for coming out. Thanks John. Great to see you love working with you guys. Hey, startups need help. And the growing and huge market opportunities, the shift cloud scale data engineering, security infrastructure, all the markets are exploding in growth because of the digital transformation of realities here, open source and cloud. I'll making it happen here in the cube in San Francisco, California. I'm John furrier, your host. Thanks for >>Watching Cisco, John. >>Hello and welcome back to the Cube's live coverage here in San Francisco, California for AWS summit, 2022. I'm John for host of the cube. Uh, two days of coverage, AWS summit, 2022 in New York city coming up this summer will be there as well. Events are back. The cube is back of course, with the cube virtual cube hybrid, the cube.net. Check it out a lot of content this year more than ever a lot more cloud data cloud native, modern applic is all happening. Got a great guest here. Jeremy Burton, Cub alumni, uh, CEO of observe Inc in the middle of all the cloud scale, big data observability, Jeremy. Great to see you. Thanks. >>Coming on. Always great to come and talk to you on the queue, man. It's been been a few years, so, >>Um, well you, you got your hands. You're in the trenches with great startup, uh, good funding, great board, great people involved in the observability Smith hot area, but also you've been a senior executive president of Dell EMC. Um, 11 years ago you had a vision and you actually had an event called cloud meets big data. Um, yeah. And it's here, you predicted it 11 years ago. Um, look around it's cloud meets big data. >>Yeah. I mean the, the cloud thing I think, you know, was, was probably already a thing, but the big data thing I do claim credit for, for sort of catching that bus early, um, you know, we, we were on the, the, the bus early and, and I think it was only inevitable. Like, you know, if you could bring the economics and the compute of cloud to big data, you, you could find out things you could never possibly imagine. >>So you're close to a lot of companies that we've been covering deeply snowflake, obviously you involved, uh, at the board level, the other found, you know, the people there, uh, cloud, you know, Amazon, you know, what's going on here? Yeah. You're doing a startup as the CEO at the helm, uh, chief of observ, Inc, which is an observability, which is to me in the center of this confluence of data engineering, large scale integrations, um, data as code integrating into applications. I mean, it's a whole nother world developing, like you see with snowflake, it means snowflakes is super cloud as we call it. So a whole nother wave is here. What's your, what's this wave we're on what's how would you describe the wave? >>Well, a couple of things, I mean, people are, I think right in more software than, than ever before are why? Because they've realized that if, if you don't take your business online and offer a service, then you become largely irrelevant. And so you you've got a whole set of new applications. I think, I think more applications now than any point. Um, not, not just ever, but the mid nineties, I always looked at as the golden age of application development. Now, back then people were building for windows. Well, well now they're building for things like AWS is now the platform. Um, so you've got all of that going on. And then at the same time, the, the side effect of these applications is they generate data and lots of data. And the, you know, there's sort of the transactions, you know, what you bought today are something like that. But then there's what we do, which is all the telemetry, all the exhaust fumes. And I think people really are realizing that their differentiation is not so much their application. It's their understanding of the data. Can, can I understand who my best customers are, what I sell today. If people came to my website and didn't buy, then why not? Where did they drop off all of that? They wanna analyze. And, and the answers are all in the data. The question is, can you understand it >>In our last startup showcase, we featured data as code one of the insights that we got out of that, and I wanna get your opinion on our reaction to is, is that data used to be put into a data lake and turns into a data swamp or throw into the data warehouse. And then we'll do some queries, maybe a report once in a while. And so data, once it was done, unless it was real time, even real time was not good anymore after real time. That was the old way. Now you're seeing more and more, uh, effort to say, let's go look at the data, cuz now machine learning is getting better. Not just train once mm-hmm <affirmative> they're iterating. Yeah. This notion of iterating and then pivoting, iterating and pivoting. Yeah, that's a Silicon valley story. That's like how startups work, but now you're seeing data being treated the same way. So now you have another, this data concept that's now yeah. Part of a new way to create more value for the apps. So this whole, this whole new cycle of >>Yeah. >>Data being reused and repurposed and figured out and yeah, >>Yeah. I'm a big fan of, um, years ago. Uh, uh, just an amazing guy, Andy McAfee at the MIT C cell labs I spent time with and he, he had this line, which still sticks to me this day, which is look I'm I'm. He said I'm part of a body, which believes that everything is a matter of data. Like if you have enough data, you can answer any question. And, and this is going back 10 years when he was saying these kind of things and, and certainly, you know, research is on the forefront. But I think, you know, starting to see that mindset of the, the sort of MIT research be mainstream, you know, in enterprises, they they're realizing that. Yeah, it is about the data. You know, if I can better understand my data better than my competitor, then I've got an advantage. And so the question is is, is how, what, what technologies and what skills do I need in my organization to, to allow me to do that. >>So let's talk about observing you the CEO of, okay. Given you've seen the ways before you're in the front lines of observability, which again is in the center of all this action what's going on with the company. Give a quick minute to explain, observe for the folks who don't know what you guys do. What's the company doing? What's the funding status, what's the product status and what's the customer status. Yeah. >>So, um, we realized, you know, a handful of years ago, let's say five years ago that, um, look, the way people are building applications is different. They they're way more functional. They change every day. Uh, but in some respects they're a lot more complicated. They're distributed. They, you know, microservices architectures and when something goes wrong, um, the old way of troubleshooting and solving problems was not gonna fly because you had SA so much change going into production on a daily basis. It was hard to tell like where the problem was. And so we thought, okay, it's about time. Somebody looks at the exhaust fumes from this application and all the telemetry data and helps people troubleshoot and make sense of the problems that they're seeing. So, I mean, that's observability, it's actually a term that goes back to the 1960s. It was a guy called, uh, Rudolph like, like everything in tech, you know, it's, it's a reinvention of something from years gone by. >>Um, there's a guy called, um, Rudy Coleman in 1960s coiner term and, and, and the term was being able to determine the state of a system by looking at its external outputs. And so we've been going on this for, uh, the best part of four years now. Um, it took us three years just to build the product. I think, I think what people don't appreciate these days often is the barrier to entry in a lot of these markets is quite high. You, you need a lot of functionality to have something that's credible with a customer. Um, so yeah, this last year we, we, we did our first year selling, uh, we've got about 40 customers now. Um, we just we've got great investors for the hill ventures. Uh, I mean, Mike SP who was, you know, the, the guy who was the, really, the first guy in it snowflake and the, the initial investor were fortunate enough to, to have Mike and our board. And, um, you know, part of the observed story is closely knit with snowflake all of that time with your data, you know, we, we store in there. >>So I want to get, uh, yeah. Pivot to that. Mike SP snowflake, Jeremy Burton, the cube kind of, kind of same thinking this idea of a super cloud or what snowflake became. Yeah. Snowflake is massively successful on top of AWS. Mm-hmm <affirmative> and now you're seeing startups and companies build on top of snowflake. Yeah. So that's become an entrepreneurial story that we think that to go big in the cloud, you can have a cloud on a cloud, uh, like as Jerry, Jerry Chan and Greylock calls it, castles in the cloud where there are moats in the cloud. So you're close to it. I know you, you're doing some stuff with snowflake. So as a startup, what's your view on building on top of say a snowflake or an AWS, because again, you gotta go where the data is. You need all the data. >>Yeah. So >>What's your take on that? I mean, >>Having enough gray hair now, um, you know, again, in tech, I think if you wanna predict the future, look at the past. And, uh, you know, 20 years ago, 25 years ago, I was at a, a smaller company called Oracle and an Oracle was the database company. And, uh, their, their ambition was to manage all of the world's transactional data. And they built on a platform or a couple of platforms, one, one windows, and the other main one was Solaris. And so at that time, the operating system was the platform. And, and then that was the, you know, ecosystem that you would compete on top of. And then there were companies like SAP that built applications on top of Oracle. So then wind the clock forward 25 years gray hairs. <laugh> the platform, isn't the operating system anymore. The platform is AWS, you know, Google cloud. I gotta probably look around if I say that in. Yeah, >>It's okay. Columbia, but hyperscale. Yeah. CapX built out >>That is the new platform. And then snowflake comes along. Well, their aspiration is to manage all of the, not just human generated data, but machine generated data in the world of cloud. And I think they they've done an amazing job are doing for the, I'd say, say the, the big data world, what Oracle did for the relational data world, you know, way back 25 years ago. And then there are folks like us come along and, and of course my ambition would be, look, if, if we can be as successful as an SAP building on top of snowflake, uh, as, as they were on top of Oracle, then, then we'd probably be quite happy, >>Happy. So you're building on top of snowflake, >>We're building on top of snowflake a hundred percent. And, um, you know, I've had folks say to me, well, aren't you worried about that? Isn't that a risk? It's like, well, that that's a risk. You're >>Still on the board. >>Yeah. I'm still on the board. Yeah. That's a risk I'm prepared to take. I am more on snowing. >>It sounds well, you're in a good spot. Stay on the board, then you'll know what's going on. Okay. No, yeah. Serious one. But the, this is a real dynamic. It is. It's not a one off its >>Well, and I do believe as well that the platform that you see now with AWS, if you look at the revenues of AWS is in order of magnitude, more than Microsoft was 25 years ago with windows mm-hmm <affirmative>. And so I've believe the opportunity for folks like snowflake and, and folks like observe it. It's an order of magnitude more than it was for the Oracle and the SAPs of the old world. >>Yeah. And I think this is really, I think this is something that this next generation of entrepreneurship is the go big scenario is you gotta be on a platform. Yeah. >>It's quite easy >>Or be the platform, but it's hard. There's only like how seats were at that table left >>Well value migrates up over time. So, you know, when the cloud thing got going, there were probably 10, 20, 30, you know, rack space and there's 1,000,001 infrastructure, a service platform as a service. My, my old, uh, um, employee EMC, we had pivotal, you know, pivotal was a platform as a service. Don't hear so much about it these days, but initially there's a lot of players and then it consolidates. And then to, to like extract, uh, a real business, you gotta move up, you gotta add value, you gotta build databases, then you gotta build applications. So >>It's interesting. Moving from the data center of the cloud was a dream for starters within if the provision, the CapEx. Yeah. Now the CapEx is in the cloud. Then you build on, on top of that, you got snowflake. Now you got on top of that. >>The assumption is almost that compute and storage is free. I know it's not quite free. Yeah. It's almost free, but you can, you know, as an application vendor, you think, well, what can I do if I assume compute and storage is free, that's the mindset you've gotta get >>Into. And I think the platform enablement to value. So if I'm an entrepreneur, I'm gonna get a series us multiple of value in what I'm paying. Yeah. Most people don't even blanket their Avis pills unless they're like massively huge. Yeah. Then it's a repatriation question or whatever discount question, but for most startups or any growing company, the Amazon bill should be a small factor. >>Yeah. I mean, a lot of people, um, ask me, uh, like, look you build in on snowflake. Um, you, you know, you, you, you're gonna be, you're gonna be paying their money. How, how, how, how does that work with your business model? If you're paying their money, you know, do, do you have a viable business? And it's like, well, okay. I, we could build a database as well and observe, but then I've got half the development team working on something that will never be as good as snowflake. And so we made the call early on that. No, no, we, we want a eight above the database. Yeah. Right. Snowflake are doing a great job of innovating on the database and, and the same is true of something like Amazon, like, like snowflake could have built their own cloud and their own platform, but they didn't. >>Yeah. And what's interesting is that Dave <inaudible> and I have been pointing this out and he's obviously a more on snowflake. I've been looking at data bricks, um, and the same dynamics happening, the proof is the ecosystem. Yeah. I mean, if you look at Snowflake's ecosystem right now and data bricks it's exploding. Right. I mean, the shows are selling out the floor. Space's book. That's the old days at VMware. Yeah. The old days at AWS. >>Well, and for snowflake and, and any platform from VI, it's a beautiful thing because, you know, we build on snowflake and we pay them money. They don't have to sell to us. Right. And we do a lot of the support. And so the, the economics work out really, really well. If you're a platform provider and you've got a lot of >>Ecosystems. Yeah. And then also you get, you get a, um, a trajectory of, uh, economies of scale with the institutional knowledge of snowflake integrations, right. New product, you're scaling a step function with them. >>Yeah. I mean, we manage 10 petabytes of data right now. Right. When I, when I, when I arrived at EMC in 2010, we had, we had one petabyte customer. And, and so at observe, we've been only selling the product for a year. We have 10 petabytes of data under management. And so been able to rely on a platform that can manage that is inve >>You know, well, Jeremy great conversation. Thanks for sharing your insights on the industry. Uh, we got a couple minutes left, um, put a plug in for observe. What do you guys know? You got some good funding, great partners. I don't know if you can talk about your, your, your POC customers, but you got a lot of high ends folks that are working with you. You getting in traction. >>Yeah. Yeah. Scales >>Around the corner. Sounds like, are you, is that where you are scale? >>We've got a big that that's when coming up in two or three weeks, we've got, we've got new funding, um, which is always great. Um, the product is, uh, really, really close. I think, as a startup, you always strive for market fit, you know, which is at which point can you just start hiring salespeople? And the revenue keeps going. We're getting pretty close to that right now. Um, we've got about 40 SaaS companies that run on the platform. They're almost all AWS Kubernetes, uh, which is our sweet spot to begin with, but we're starting to get some really interesting, um, enterprise type customers. We're, we're, you know, F five networks we're POC in right now with capital one, we got some interest in news around capital one coming up. I, I can't share too much, but it's gonna be exciting. And, and like I said, so hill continue to, to, >>I think capital one's a big snowflake customer as well. Right. >>They were early in one of the things that attracted me to capital one was they were very, very good with snowflake early on. And, and they put snowflake in a position in the bank where they thought that snowflake could be successful. And, and today that, that is one of Snowflake's biggest accounts, >>Capital, one, very innovative cloud, obviously Atos customer, and very innovative, certainly in the CISO and CIO, um, on another point on where you're at. So you're, Prescale meaning you're about to scale, >>Right? >>So you got POCs, what's that trajectory look like? Can you see around the corner? What's, what's going on? What's on, around the corner. That you're, that you're gonna hit this straight and narrow and, and gas it fast. >>Yeah. I mean, the, the, the, the key thing for us is we gotta get the product. Right. Um, the nice thing about having a guy like Mike Pfizer on the board is he doesn't obsess about revenue at this stage. His questions that the board are always about, like is the product, right? Is the product right? Is the product right? Have you got the product right? And cuz we know when the product's right, we can then scale the sales team and, and the revenue will take care of itself. Yeah. So right now all the attention is on the product. Um, the, this year, the exciting thing is we we're, we're adding all the tracing visualizations. So people will be able to the kind of things that by in the day you could do with the new relics and AppDynamics, the last generation of, of APM tools, you're gonna be able to do that within observe. And we've already got the logs and the metrics capability in there. So for us this year is a big one, cuz we sort of complete the trifecta, you know, the, the >>Logs, what's the secret sauce observe. What if you had the, put it into a, a, a sentence what's the secret sauce? >>I, I, I think, you know, an amazing founding engineering team, uh, number one, I mean, at the end of the day, you have to build an amazing product and you have to solve a problem in a different way. And we've got great long term investors and, and the biggest thing our investors give is it actually, it's not just money. It gives us time to get the product, right. Because if we get the product right, then we can get the growth. >>Got it. Final question. While I got you here, you've been on the enterprise business for a long time. What's the buyer landscape out there. You got people doing POCs on capital one scale. So we know that goes on. What's the appetite at the buyer side for startups and what are their requirements that you're seeing? Uh, obviously we're seeing people go in and dip into the startup pool because new ways to refactor their, this restructure. So, so a lot of happening in cloud, what's the criteria. How are enterprises engaging in with startups? >>Yeah. I mean, enterprises, they know they've gotta spend money transforming the business. I mean, this was, I almost feel like my old Dell or EMC self there, but, um, what, what we were saying five years ago is happening. Um, everybody needs to figure out a way to take their business to this digital world. Everybody has to do it. So the nice thing from a startup standpoint is they know at times they need to risk or, or take a bet on new technology in order to, to help them do that. So I think you've got buyers that a have money, uh, B it prepared to take risks and it's, it's a race against time to you'll get their, their offerings in this, a new digital footprint. >>Final, final question. What's the state of AWS. Where do you see them going next? Obviously they're continuing to be successful. How does cloud 3.0, or they always say it's day one, but it's more like day 10, but what's next for Aw. Where do they go from here? Obviously they're doing well. They're getting bigger and bigger. Yeah, >>Better. It's an amazing story. I mean, you know, we're, we're on AWS as well. And so I, I think if they keep nurturing the builders and the ecosystem, then that is their superpower. They, they have an early leads. And if you look at where, you know, maybe the likes of Microsoft lost the plot in the, in the late nineties, it was, they stopped, uh, really caring about developers in the folks who were building on top of their ecosystem. In fact, they started buying up their ecosystem and competing with people in their ecosystem. And I see with AWS, they, they have an amazing headstart and if they did more, you know, if they do more than that, that's, what's gonna keep this juggernaut rolling for many years to come. >>Yeah. They got the Silicon and got the stack. They're developing Jeremy Burton inside the cube, great resource for commentary, but also founding with the CEO of a company called observing in the middle of all the action on the board of snowflake as well. Um, great startup. Thanks for coming on the cube. Always a pleasure. Okay. Live from San Francisco. It's to cube. I'm John for your host. Stay with us more coverage from San Francisco, California after the short break. >>Hello. Welcome back to the cubes coverage here live in San Francisco, California. I'm John furrier, host of the cubes cube coverage of AWS summit 2022 here in San Francisco. We're all the developers are the bay air at Silicon valley. And of course, AWS summit in New York city is coming up in the summer. We'll be there as well. SF and NYC cube coverage. Look for us. Of course, reinforcing Boston and re Mars with the whole robotics, AI. They all coming together. Lots of coverage stay with us today. We've got a great guest from Bel VC. John founding partner, entrepreneurial venture is a venture firm. Your next act, welcome to the cube. Good to see you. >>Good to see you, man. I feel like it's been forever since we've been able to do something in person. Well, >>I'm glad you're here because we run into each other all the time. We've known each other for over decade. Um, >>It's been at least 10 years, >>At least 10 years more. And we don't wanna actually go back as bring back the old school web 1.0 days. But anyway, we're in web three now. So we'll get to that in a second. We, >>We are, it's a little bit of a throwback to the path though, in my opinion, >>It's all the same. It's all distributed computing and software. We ran each other in cube con. You're investing in a lot of tech startup founders. Okay. This next level, next gen entrepreneurs have a new makeup and it's software. It's hardcore tech in some cases, not hardcore tech, but using software to take an old something old and make it better new, faster. So tell us about Bel what's the firm. I know you're the founder, uh, which is cool. What's going on. Explain >>What you, I mean, you remember I'm a recovering entrepreneur, right? So of course I, I, >>No, you're never recovering. You're always entrepreneur >>Always, but we are also always recovering. So I, um, started my first company when I was 24. If you remember, before there was Facebook and friends, there was instant messaging. People were using that product at work every day, they were creating a security vulnerability between their network and the outside world. So I plugged that hole and built an instant messaging firewall. It was my first company. The company was called IM logic and we were required by Symantec. Uh, then spent 12 years investing in the next generation of software companies, uh, early investor in open source companies and cloud companies and spent a really wonderful years, uh, at a firm called NEA. So I, I feel like my whole life I've been either starting enterprise software companies or helping founders start enterprise software companies. And I'll tell you, there's never been a better time than right now to start an enterprise software company. >>So, uh, the passion for starting a new firm was really a recognition that founders today that are starting an enterprise software company, they, they tend to be, as you said, a more technical founder, right? Usually it's a software engineer or a builder mm-hmm <affirmative>, uh, they are building that are serving a slightly different market than what we've traditionally seen in enterprise software. Right? I think traditionally we've seen it buyers or CIOs that have agendas and strategies, which, you know, purchase software that is traditionally bought and sold tops down. But you know, today I think the most successful enterprise software companies are the ones that are built more bottoms up and have more technical early adopters. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software. And it starts with great technical founders with great products and great bottoms of motions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background. You're super smart admire of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is, is all companies there's no, I mean, consumer is enterprise now. Everything is what was once a niche, not, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. But remember, like right now, there's also a giant tech in VC conference in Miami <laugh> and it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, well, >>MFTs is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. >>Well, and, and I think all of us here that are of may, maybe students of his stream have been involved in open source in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three >>Movement. The hype is definitely web >>Three. Yeah. But, >>But you know, >>For sure. Yeah, no, but now you're taking us further east to Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case and maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many measures over, uh, $500 billion in growing, you know, 20 to 30 a year. So it it's a, it's a just incredibly fast >>Let's getting, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant <laugh> but there's also the hype of like the web three, for instance, but you know, for, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Lutman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, hire a direct sales force and sass kind of crushed that now SAS is being redefined, right. So what is SAS? Is snowflake a SAS or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, and they own all my data. And you know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of commonalities across all six of startups and the overall adoption of technology. Uh, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually user like growth, right. They're one in the same. So sometimes people think the product, uh, is what is driving. >>You just pull the product >>Through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this movement may be started with open source where users were contributors, you know, contributors were users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing and it's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the users. And they're really the, the offic and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a gen Xer technically. So for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I've, I've been saying on the cube for probably about eight years now that we are gonna hit a digital hippie Revolut, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one of group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. We hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>During the mainframe days, those renegades were breaking into Stanford, starting the home brew club. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on like, well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion around the way in which a product is built. Right. And we can use open source. One example of that religion. Some people say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? It's, it's something that people just believe to be true almost without, uh, necessarily. I mean, >>The data drives all decision making. Let me ask you this next question. As a VC. Now you look at pitch, well, you've been a VC for many years, but you also have the founder entrepreneurial mindset, but you can empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of is about believing in the first. So faking it till you make it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. Oh, >>AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur, right. And the persona of the entrepreneur would be, you know, somebody who was a great salesperson or somebody who tell a great story. And I still think that that's important, right. It still is a human need for people to believe in narratives and stories. Yeah. But having said that you're right. The proof is in the pudding, right. At some point you click download and you try the product and it does what it says it's gonna, it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in this new economy, that're, we live in really, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative because their product begin for exactly >>The volume you back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song is the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, like the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with for right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the it's gotta speak to the, >>Exactly. Speak to the user. But let me ask a question now that for the people watching, who are maybe entrepreneurial entre entrepreneurs, um, masterclass here is in session. So I have to ask you, do you prefer, um, an entrepreneur to come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine. Whether you're an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think will become, right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way, and we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be, the more likely somebody is gonna to align with your vision and, and want to invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I, you gotta show the path. I think the single most important thing for any founder and VC relationship is that they have the same vision. Uh, if you have the same vision, you can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle of the journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the, the latest trends because it's over before you even get there. >>Exactly. I think many people that, that do what we do for a living will say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. So you, you know, you sort of have to balance the, you know, we, we know that the world is going this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but sometimes it happens ins six months. Sometimes it takes six years. Sometimes it takes 16 years. Uh, >>What's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Tebel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There there's three big trends that we invest in. And then the, the only things we do day in day out one is the explosion at open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen an alwa timeline happening forever, but it is, it is accelerating faster than we've ever seen. So I, I think it's its one big mass of wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a market as any of the other markets that we invest in. Uh, and finally it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is underinvested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a do over, right? I mean, do we need a do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cyber security as an add-on. Yeah. But if you think about it, the whole like economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is around 150 billion and it still is a fraction of what >>We're, what we're and even boom is booming now. So you get the convergence of national security, geopolitics, internet digital >>That's right. You mean arguably, right. Arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say you gotta love your firm. Love who you're doing. We're big supporters of your mission. Congrat is on your entrepreneurial venture. And uh, we'll be, we'll be talking and maybe see a Cuban. Uh, >>Absolutely >>Not. Certainly EU maybe even north America's in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for helping me on the show. >>Des bell VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California, after the short break, stay with us. Hey everyone. Welcome to the cue here. Live in San Francisco, California for AWS summit, 2022 we're live we're back with events. Also we're virtual. We got hybrid all kinds of events. This year, of course, 80% summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube. Got a great guest here. Justin Colby, owner and CEO of innovative solutions they booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us the story. What do you guys do? What's the elevator pitch. Yeah. >><laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to midsize businesses that are moving to the cloud or have already moved to the cloud and really trying to understand how to best control, cost, security, compliance, all the good stuff, uh, that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is. But now we have offices down in Austin, Texas up in Toronto, uh, Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago. And it's been a great ride. >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by AWS. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization and obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? Yeah. >>It's a great question. Every CEO I talk to, that's a small to mid-size business. I'll try and understand how to leverage technology better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech is really at the, at the forefront and the center of that. So most customers are coming to us and they're like, listen, we gotta move to the out or we move some things to the cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then, uh, progressively working through a modernization strategy is always the better approach. And so we spend a lot of time with small to midsize businesses who don't have the technology talent on staff to be able to do >>That. Yeah. They want to get set up. But the, the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is. And it's not, it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem you guys solve >>The SMB space. The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and are hardened solutions. And so, um, what we try to do with technology staff that has additional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether that's, we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to, yeah, they're like, listen, the end of the day, I'm gonna be spending money in one place or another, whether that's OnPrem or in the cloud. I just want to know that I'm doing that in a way that helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. Good. >>How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I think there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start the, on your journey in one way, and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's a, gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning, the projects that early and not worrying about it, you got it. I mean, most people don't abandon stuff cuz they're like, oh, I own it. >>Exactly. >>And they get, they get used to it. Like, and then they wait too long. >>That's exactly. Yeah. >>Frog and boiling water as we used to say so, oh, it's a great analogy. So I mean this, this is a dynamic that's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you guys come in. I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talk to at reinvent, that's a customer. Well, how many announcements did Andy jazzy announcer Adam, you know, five, a thousand announcement or whatever they did with huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just product. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are >>The values. >>Our mission is, is very simple. We want to help every small to mid-size business, leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a tech company in the pro of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning know that we have their back and we're the safety net. So when a customer is saying, all right, I'm gonna spend a couple thousand dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going on loan. Who's there to help protect that. Number two, if you have a security posture and let's just say you're high profile and you're gonna potentially be more vulnerable to security attack. If you have a partner that's offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own, it would cost 'em a fortune. If >>It's training alone would be insane. A risk factor not mean the cost. Yes, absolutely. Opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. Yeah. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018, when, uh, when we made the decision to go all on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious decision. It wasn't requirement isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front desk >>And she could be running the Kubernetes clusters. I >>Love it. It's amazing. So I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get the right >>People involved. And that's a cultural factor that you guys have. So, so again, this is back to my whole point about SMBs and BIS is in general, small and large. It staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the build out, um, uh, return factor, ROI piece. At what point in time as an owner or SMB, do I get the why? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cyber security issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one in the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Like critical issues. This >>Is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about this, that's, >>That's what, at least a million in bloating, if not three or more Just to get that going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side now. Yeah. No. And nevermind AI and ML. That's >>Right. That's right. So to try to go it alone, to me, it's hard. It's incredibly difficult. And the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll do all that exactly. In the it department. >>Exactly. >>Like, can we just call up, uh, you know, our old vendor that's >>Right. <laugh> right. Our old vendor. I like >>It, >>But that's so true. I mean, when I think about how, if I were a business owner starting a business today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. And it's something that we tell, talk about every, with every one of our small to mid-size >>Businesses. So just, I wanna get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative yeah. Award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, I was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduce other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. And I came in, I did an internship for six months and I loved it. I learned more in those six months that I probably did in my first couple of years at, uh, at RT long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2010 and I was like, Hey, on the value of this business and who knows where you guys are gonna be another five years, what do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner, but if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that were gonna also buy into the business with me. >>And they were the owners, no outside capital, none >>Zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons, they all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like if we're owners, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015, and, uh, we made the decision that I was gonna buy the three partners out, um, go through an early now process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the business, cuz they cared very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting going all in on the cloud was important for us and we haven't looked back. >>And at that time the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly. And those kinds of big enterprises, the GA I don't wanna say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to mid-size business, to migrate completely to the cloud as, as infrastructure was considered. That just didn't happen as often. Um, what we were seeing where a lot of our small to mid-size as customers, they wanted to leverage cloud-based backup or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration, the Microsoft suite to the cloud. And a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on AWS at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is it the app modernization? Is it data? What's the hot product and then put a plug in for the company. Awesome. >>So, uh, there's no question. Every customer is looking to migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating to the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customers not to be cash strap and gives them an opportunity to move forward in a controlled, contained way so that they can modernize. >>So like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers and being empathetic to where they are in their journey. >>And that's the cloud upside is all about doubling down on the variable wind. That's right. Seeing the value and Ling down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate it. >>Thank you very much for having me. >>Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching. We're back with more great coverage for two days after this short break, >>Live on the floor and see San Francisco for a AWS summit. I'm John ferry, host of the cube here for the next two days, getting all the action we're back in person. We're at a AWS reinvent a few months ago. Now we're back. Events are coming back and we're happy to be here with the cube. Bring all the action. Also virtual. We have a hybrid cube. Check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticking off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad to be >>Here. So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to have to be back through events. >>It's amazing. This is the first, uh, summit I've been to and what two, three years. >>It's awesome. We'll be at the UHS summit in New York as well. A lot of developers and a big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything dev sec ops, everyone kind of sees that you got containers, you got Kubernetes, you got cloud native. So the game is pretty much laid out mm-hmm <affirmative> and the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's right. >>Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions that are around, especially the edge public cloud for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give an example, uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running their FinTech on top of AWS services inside Panama. >>You know, it's interesting, Matthew is that we've been covering a, since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and became the CEO. Now Adam's in charge, but the edge has always been that thing they've been trying to avoid. I don't wanna say trying to avoid, of course, Amazon would listen to the customers. They work backwards from the customer. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does computing. It >>Does. That's not centralized in the public cloud now they got regions. So what is the issue at the edge what's driving the behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see that the data at the edge, you got 5g having. So it's pretty obvious, but there's a slow transition. What was the driver for the edge? What's the driver now for edge action for AWS >>Data is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation where today we have over 15 AWS edge services and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always used to riff on the cube cause it's basically Amazon and a box pushed in the data center, running native, all the stuff, but now cloud native operations are kind of becoming standard. You're starting to see some standard Deepak syncs. Group's doing some amazing work with open source Rauls team on the AI side, obviously, uh, you got SW, he was giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see local zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my data center, do I want to manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outposts. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone. Now what's happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware. We can go deploy EKS anywhere or in your VMware environment. And it's increasing the speed of adoption >>For sure. Right? So you guys are making a lot of good business decisions around managed cloud service. That's right. Innovative as that you get the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in, in these new areas that you're helping out are, they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their availability zones or their regions that you guys are delivering. What's the key is it. They don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on, what's making them money as a business. They want on their applications. They want to focus on their customers. So they look towards AWS cloud and say, AWS, you take the infrastructure. You take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. Uh, we help build out these things in local data centers for 32 plus year old company. We have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're filling that gap in helping of these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. So >>Basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it works? Right. >>And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy FinTech in the Caribbean, we talk about hurricanes and we're gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where you now have data and you have applications that are tapping into that, that required. It makes total sense. We're seeing that across the board. So it's not like it's, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech. And in, in the islands there a lot of, lot of, lot of web three happening. What's your, what's your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto to underlie parts of their central banks. Yeah. Um, so it's, it's up and coming a, uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a, uh, technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure, because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on it's >>Interesting. I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, projects going on. But if you look talk to all the crypto people that say, look, we do a smart concept. We use the blockchain. It's kind of over a lot of overhead and it's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain, just for this like smart contracts for instance, or certain transactions. And they go into Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service, but what happened to decentralized. >>Yeah. And that's, and that's the conversation performance issue. Yeah. And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through, uh, a use case of a customer, um, Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud. Um, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my ad. And I also want all the benefit of the cloud. So I want the modernization and I wanna migrate to the cloud for all those cloud benefits and the goodness of the cloud. What's the answer. Yeah. >>Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment inside that, that manufacturing plant can be hooked up. They don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with, uh, regular commercial available hardware running VMware, and we deploy EKS anywhere on that. Uh, inside of that manufacturing plant, uh, we can do pre-procesing on things coming out of the, uh, the robotics that depending on what we're manufacturing, right. Uh, and then we can take those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard for >>Data, data lake, or whatever, to >>The data lake. Yeah. Data lake house, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but a lot of that, uh, just in time business decisions, just in time, manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going to the data that saves that cost yep. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data, unless you have to, um, those new things are developing. So I wanna ask you what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacturing, industrial, whatever, the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? This is a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud out? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe maybe decision can wait. Right? Yeah. Uh, and then how do I visualize that? By >>The way, it could be a bot too, doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture on the back. So there's new things developing. You've got more benefit. There >>Are, there are. And, and we have more and more people that, that want to talk less about databases and want to talk more about data lakes because of this. They want to talk more about customers are starting to talk about throwing away data, uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And >>Well, I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session on this, but the one pattern was income of the past year is that throwing away data's bad. Even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retrain their machine learning algorithms. Yep. So as data becomes code, as we call it our lab showcase, we did a whole, whole, that event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw away. It's not just business benefits. Yeah. There's all kinds of new scale. There >>Are. And, and we have, uh, many customers that are run petabyte level. Um, they're, they're essentially data factories on, on, uh, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move petabytes of data to the AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a kind of a, um, fun note. I was told to ask you about your personal background on premise architect, a cloud and skydiving instructor. <laugh> how does that all work together? What tell, what does this mean? Yeah. >>Uh, you >>Jumped out a plane and got a job. You, you got a customer to jump out >>Kind of. So I was jump, I was teaching Scott eing, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a Scott I instructor. Yeah. Uh, I was teaching Scott eing and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and, and how his cus customers are working. And he can't find enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, uh, I was living in a tent in the woods teaching scout. I think I was like, I'd love to not live in a tent in the woods. So, uh, uh, I started in the first day there, uh, we had a, a discussion, uh, EC two, just come out <laugh> um, and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that and through being an on premises migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services to >>It's. So it's such a great story, you know, I was gonna, you know, you know, the, the, the, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early day was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, um, when that was coming out, it was, I mean, it was, it was still, and I, maybe it does still feel like that to some people. Right. But, uh, it was, it was the same kind of feeling that we had in the early days, AWS, the same feeling we have when we >>It's pretty much now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting edge stuff, like jumping out of an airplane. Yeah. You guys, the right equipment, you gotta do the right things. Exactly. >>Right. >>Matthew, thanks for coming on the cube. Really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here live and San Francisco for summit. I'm John Forry host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. look@thiscalendarforallthecubeactionatthecube.net. We'll be right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube a be summit 2022. We're back in person. I'm John fury host to the cube. We'll be at the eight of his summit in New York city. This summer, check us out then. But right now, two days in San Francisco, getting all the coverage what's going on in the cloud, we got a cube alumni and friend of the cube, my dudes, car CEO, investor, a Sierra, and also an investor and a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you, sir. Chris. Cool. How are, are you >>Good? How are you? >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah. So give us the update. How much cash have you guys raised? What's the status of the company product what's going on? First >>Of all, thank you for having me back to be business with you. Never great to see you. Um, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. Um, we have raised close to a hundred million there. Uh, the investors are people like Norwes Menlo, Tru ventures, coast, lo ventures, Ram Sheam and all those people, all well known guys. The Andy Beckel chime, Paul Mo uh, main web. So a whole bunch of operating people and, uh, Silicon valley VCs are involved >>And has it come? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISR is going after is what I call the applying AI for customer service. It operations, it help desk, uh, the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and ServiceNow to take it to the next stage? >>Well, I love having you on the cube, Dave and I, Dave Valenti as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a GE, you're like a guest analyst. <laugh> >>You know who you >>Get to call this fun to talk. You though, >>You got the commentary, you, your, your finger on the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud scale. You predicted that we talked about on cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing DACA just raised a hundred million on a 2 billion valuation back from the dead after they pivoted from an enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control, plane emerging, AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded, observability there's 10 million observability companies. Data is the key. What's your angle on this? What's your take. Yeah, >>No, look, I think I'll give you the view that I see right from my side. Obviously data is very clear. So the things that remember system of recorded you and me talked about the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud NA it'll be called AI, NA AI native is a new buzzword and using the AI customer service it operations. You talk about observability. I call it, AIOps applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and service desk. What needs to be helped us with ServiceNow BMC G you see a new ELA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflow, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with a AI workflows. So you'll see AI going >>Off is RPA a company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI pass? One will be at their event this summer? Um, is it a product company? I mean, I mean, RPA is almost, should be embedded in everything. It's >>A feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company, or, but that automation should be embedded in every area. Yeah. Like we call cloud NA and AI NATO it'll become automation. NA yeah. And that's your thinking. >>It's almost interesting me. I think about the, what you're talking about what's coming to mind is I'm kinda having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it. It was middleware. It sat between two things and then the middle, and it was software abstraction. Now you have all, all kinds of workflows, abstractions everywhere. So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed or they integrated. I mean, these are the challenges. This is crazy. What's the, >>So don't about the databases become called poly databases. Yeah. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area like you were talking about. It should be part of service. Now it should be part of ISRA, like every company, every Salesforce. So that's why you see MuleSoft and Salesforce buying RPA companies. So you'll see all the SaaS companies, cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also have an automation as a layer <inaudible> inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind us, you've got the expo hall. We got, um, we're back to vents, but you got, you know, AMD, Clum, Ove, uh, Dynatrace data, dog, innovative, all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right. Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Bel later today. He's a former NEA guy and we always talk to Jerry, Jen. We know all the, the VCs. What does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation, clouds bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's code. Yes. Basically data is everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders of Amazon created the startups 15 years back. Everybody built on Amazon now, Azure and GCP. The next layer would be is people don't just build on Amazon. They're going to build it on top of snowflake. Companies are snowflake becomes a data platform, right? People will build on snowflake. Right? So I see my old boss flagman try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer. Right? So I think that's in the of, <inaudible> trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis a couple months ago called castles in the cloud where your moat is, what you do in the cloud. Not necessarily in the, in the IP. Um, Dave LAN and I had last reinvent, coined the term super cloud, right? He's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage. And guys like Charles Fitzgeral out there, who we like was kind of shit on us saying, Hey, you guys terrible, they didn't get it. Like, yeah. I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> if he's cool. Um, but snowflake is on Amazon. Yes. Now they say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist. And, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. >>It is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer. Remember the middle layer pass will be snowflake. So can build it on snowflake. I can use them for data layer. If I really need to size, I'll build it on four.com Salesforce. So I think that's where you'll see. So >>Basically if you're an entrepreneur, the north star in terms of the outcome is be a super cloud. >>It is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. >>Yeah. Yeah. How are, how is Amazon and the clouds dealing with these big whales? The snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think got Redshift. Amazon has got red, um, but Snowflake's a big customer. They're probably paying AWS think big bills too. >>So John, very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-option will be there. So Amazon will have Redshift, but Amazon is also partnering with, uh, snowflake to have native snowflake data warehouse as a data layer. So I think depending on the application use case, you have to use each of the above. I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, You know, foreclose your value that's right. But some sort of internal hack, but I think, I think the general question that I have is that I think it's okay to have a super cloud like that because the rising tide is still happening at some point. When does the rising tide stop >>And >>Do the people shopping up their knives, it gets more competitive or is it just an infinite growth cycle? I >>Think it's growth. You call it cloud scale. You invented the word cloud scale. So I think look, cloud will continually agree, increase. I think there's, as long as there are more movement from on, uh, OnPrem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations. It helpless, even the customer service service now and, uh, ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go made. >>I wanna get your thoughts for the folks watching that are, uh, enterprise buyers or practitioners, not suppliers to the market, feel free to, to XME or DMing. Next question's really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products. Cause you know, the big enterprises now and, you know, small, medium, large, and large enterprise are all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or a growing startup selling to an enterprise? Um, have you seen changes there? I mean I'm seeing some stuff, but why don't we get your thoughts on that? What, no, it is. >>If I remember going back to our 2007 or eight, it, when I used to talk to you back then when Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or 1% today. Most companies are already spending 20, 30% with startups. Like if I look at a CIO line business, it's gone. Yeah. Can it go more? I think it can double in the next four, five years. Yeah. Spending on the startups. >>Yeah. And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I reference the URL cause it's like, there's like a bunch of companies we've been promoting because the solutions that startups have actually are new stuff. Yes. It's bending, it's shifting left for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there, um, and gives back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure as code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share >>Yourself? No, I have a lot of thoughts that plus I see AIOP solutions in the future should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app Dyna, right? Dynatrace, all this solution will go future towards to proactive solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service that customers are give the data, share the data because we thought the data algorithms are useless. I can come the best algorithm, but I gotta train them, modify them, tweak them, make them better, make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to our big data days back in 2009, you know, >>Look at, look how much data bricks has grown. >>It is uh, double, the key >>Cloud kinda went private, so good stuff. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking at that growing customers and my customers are some of them, you like it's zoom auto desk, Mac of fee, uh, grandchildren, all the top customers. Um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on predict S one area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service, >>Great stuff, man. Doing great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of 80 summit, 2022. And we're gonna be at 80 summit in San, uh, in New York and the summer. So look for that on this calendar, of course go to eight of us, startups.com. I mentioned that it's a site for all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This to cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back a little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit new York's coming in the summer. We'll be there too with the cube on the set. We're getting back in the groove, psyched to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're gonna see a lot of virtual cube, a lot of hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economists with duck, bill groove, he founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank you. >>Thanks. Coming on. Sure is a lot of words to describe as shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at Mark's been doing a lot of shit posting lately, all a billionaires are shit posting, but they don't know how to do it. Like they're not >>Doing it right. Something opportunity there. It's like, here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a mid-size island to begin doing this from, oh, then we're having fun. This >>Shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on the other side, I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what is shit posting? >>It's more or less talking about the world of enterprise tech, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream. But it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a jackass or more prosaically are worried about getting fired for better or worse. I don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, coupons coming up in Spain, which they're having a physical event, you can see the growth of cloud native Amazons, all, all the Adams let see new CEO, Andy move on to be the chief of all. Amazon just saw him. The cover of was it time magazine. Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything these folks do. They they're effectively in a fishbowl, but I have trouble imagining the logistics. It takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. It's, it's sprawling, immense that dominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. Well, >>There's a lot of force for good conversations, seeing a lot of that going on, Amazon's trying to port and he was trying to portray themselves as you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now it same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. Either way, sounds like more exciting >>Replacement ready <laugh> in case something goes wrong. I, the track highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula one is they have these new rigs out. Yeah. Where you can actually race in e-sports with other, in pure simulation of the race car. You gotta get the latest and video graphics card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. >>Oh, it's great too. And I can see the appeal of these tech companies getting into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going in your world. I know you have a lot of great success. We've been following you in the queue for many, many years. Got a great newsletter. Check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's back any blow back late there been uptick. What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's high. I'm emailing an awful lot of people at last week in AWS every week and okay. They must not have heard me it. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do that. >>We should do that. Actually. I think sure would call in. Oh, I, >>I think >>Chief, we had that right now. People would call in and say, Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the customer. >>You know, I always joke with Dave ante about how John Fort's always at, uh, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0 5, or we can't, >>We have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And there you go. Yeah. >>It's and the old joke at HP was if they, if they invented sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish. That's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their >>Producting, they're going in different directions. When they named Amazon Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonused on a number of words. They can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, session manager is a great one. I love the service, ridiculous name. They have systems manager, parameter store, which is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage your parameter store does not. It's >>Fun. What's your, what's your favorite combination of acronyms >>Combination of you >>Got Ks. You got EMR, you got EC two. You got S three SQS. Well, Redshift the on an acronym, you >>Gots is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation. >>They still up bean stalk. Or is that still around? Oh, >>They never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, wow, we built this thing in 2005 and everyone hates it. But while we certainly can't change it, now it has three customers on it. John three <laugh>. >>Okay. >>Simple BV still haunts our dreams. >>I, I actually got an email. I saw one of my, uh, servers, all these C two S were being deprecated and I got an email I'm like, I couldn't figure out. Why can you just like roll it over? Why, why are you telling me just like, give me something else. Right. Okay. So let me talk about, uh, the other things I want to ask you is that like, okay. So as Amazon gets better in some areas, where do they need more work in your opinion? Because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database, Snowflake's got a database service. So Redshift, snowflake database is, so you got this co-op petition. Yes. How's that going? And what are you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with Amazon and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want and they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multi-cloud cause obviously the other cloud shows are coming up. Amazon hated that word. Multi-cloud um, a lot of people are saying, you know, it's not a real good marketing word, like multi sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multi-cloud >>Multiple single points? >>Dave loves that term. Yeah. >>Yeah. You're building in multiple single points of failure. Do it for the right reasons or don't do it as a default. I believe not doing it is probably the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about multi-cloud either as the industry leader, talk about other clouds, bad direction to go in from a market cap perspective, it doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of forms. Some brilliant, some brain dead. It depends a lot on context. But my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing, because it solves problems. That's when I shut up and listen. Yeah. >>Cool. Awesome. Corey, I gotta ask you a question, cause I know you, we you've been, you know, fellow journeymen and the, and the cloud journey going to all the events and then the pandemic hit where now in the third year, who knows what it's gonna gonna end. Certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations. Community's gonna emerge. You got a pretty big community growing and it's throwing like crazy. What's the weirdest or coolest thing, or just big chain angels. You've seen with the pandemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece, come in, you're commentating. You're calling balls and strikes in the industry. You got a great team developing over there. Duck bill group. What's the big aha moment that you saw with the pandemic. Weird, fun, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who can pony up two grand and a week in Las Vegas and get to Las Vegas from wherever they happen to be by moving virtually suddenly it, it embraces the reality that talent is even distributed. Opportunity is not. And that means that suddenly these things are accessible to a wide swath of audience and potential customer base and the rest that hadn't been invited to the table previously, it's imperative that we not lose that. It's nice to go out and talk to people and have people come up and try and smell my hair from time to time, I smell delightful. Let make assure you, but it was, but it's also nice to be. >>I have a product for you if you want, you know. >>Oh, excellent. I look forward to it. What is it putting? Why not? <laugh> >>What else have you seen? So when accessibility for talent, which by the way is totally home run. What weird things have happened that you've seen? Um, that's >>Uh, it's, it's weird, but it's good that an awful lot of people giving presentations have learned to tighten their message and get to the damn point because most people are not gonna get up from a front row seat in a conference hall, midway through your Aing talk and go somewhere else. But they will change a browser tab and you won't get them back. You've gotta be on point. You've gotta be compelling if it's going to be a virtual discussion. >>Yeah. And also turn off your IMEs too. >>Oh yes. It's always fun in the, in the meetings when you're talking to someone and their co is messaging them about, should we tell 'em about this? And I'm sitting there reading it and it's >>This guy is really weird. Like, >>Yes I am and I bring it into the conversation and then everyone's uncomfortable. It goes, wow. >>Why not? I love when my wife yells at me over I message. When I'm on a business call, like, do you wanna take that about no, I'm good. >>No, no. It's better off. I don't. No, the only encourager it's fine. >>My kids. Excellent. Yeah. That's fun again. That's another weird thing. And, and then group behavior is weird. Now people are looking at, um, communities differently. Yes. Very much so, because if you're fatigued on content, people are looking for the personal aspect. You're starting to see much more of like yeah. Another virtual event. They gotta get better. One and two who's there. >>Yeah. >>The person >>That's a big part of it too is the human stories are what are being more and more interesting. Don't get up here and tell me about your product and how brilliant you are and how you built it. That's great. If I'm you, or if I wanna work with you or I want to compete with you, or I wanna put on my engineering hat and build it myself. Cause why would I buy anything? That's more than $8. But instead, tell me about the problem. Tell me about the painful spot that you specialize in. Tell me a story there. >>I, I >>Think that gets a glimpse in a hook and >>Makes more, more, I think you nailed it. Scaling storytelling. Yes. And access to better people because they don't have to be there in person. I just did it thing. I never, we never would've done the queue. We did. Uh, Amazon stepped up in sponsors. Thank you, Amazon for sponsoring international women's day, we did 30 interviews, APAC. We did five regions and I interviewed this, these women in Asia, Pacific eight, PJ, they called for in this world. And they're amazing. I never would've done those interviews cuz I never, would've seen 'em at an event. I never would've been in Japan or Singapore to access them. And now they're in the index. They're in the network. They're collaborating on LinkedIn. So a threads are developing around connections that I've never seen before. Yes. Around the content, >>Absolutely >>Content value plus >>The networking. And that is the next big revelation of this industry is going to realize you have different companies. And in Amazon's case, different service teams, all, all competing with each other, but you have the container group and you have the database group and you have the message cuing group. But customers don't really want to build things from spare parts. They want a solution to a problem. I want to build an app that does Twitter for pets or whatever it is I'm trying to do. I don't wanna basically have to pick and choose and fill my shopping cart with all these different things. I want something that's gonna give me what I'm trying to get as close to turnkey as possible. Moving up the stack. That is the future. And just how it gets here is gonna be >>Well we're here with Corey Quinn, the master of the master of content here in the a ecosystem. Of course we we've been following up in the beginnings. Great guy. Check out his blog, his site, his newsletter screaming podcast. Cory, final question for you. Uh, what do you hear doing what's on your agenda this week in San Francisco and give a plug for the duck build group. What are you guys doing? I know you're hiring some people what's on the table for the company. What's your focus this week and put a plug in for the group. >>I'm here as a customer and basically getting outta my cage cuz I do live here. It's nice to actually get out and talk to folks who are doing interesting things at the duck build group. We solve one problem. We fixed the horrifying AWS bill, both from engineering and architecture, advising as well as negotiating AWS contracts because it turns out those things are big and complicated. And of course my side media projects last week in aws.com, we are, it it's more or less a content operation where I indulge my continual and ongoing law of affair with the sound of my own voice. >><laugh> and you good. It's good content. It's on, on point fun, Starky and relevant. So thanks for coming to the cube and sharing with us. Appreciate it. No, thank you. Fun. You. Okay. This the cube covers here in San Francisco, California, the cube is back at to events. These are the summits, Amazon web services summits. They happen all over the world. We'll be in New York and obviously we're here in San Francisco this week. I'm John furry. Keep, keep it right here. We'll be back with more coverage after this short break. Okay. Welcome back everyone. This's the cubes covers here in San Francisco, California, we're live on the show floor of AWS summit, 2022. I'm John for host of the cube and remember AWS summit in New York city coming up this summer, we'll be there as well. And of course reinvent the end of the year for all the cube coverage on cloud computing and AWS. The two great guests here from the APN global APN se Jenko and Jeff Grimes partner leader, Jeff and se is doing partnerships global APN >>AWS global startup program. Yeah. >>Okay. Say that again. >>AWS global startup program. >>That's the official name. >>I love >>It too long, too long for me. Thanks for coming on. Yeah, of course. Appreciate it. Tell us about what's going on with you guys. What's the, how was you guys organized? You guys we're obviously were in San Francisco bay area, Silicon valley, zillions of startups here, New York. It's got another one we're gonna be at tons of startups. Lot of 'em getting funded, big growth and cloud big growth and data security, hot and sectors. >>Absolutely. >>So maybe, maybe we could just start with the global startup program. Um, it's essentially a white glove service that we provide to startups that are built on AWS. And the intention there is to help identify use cases that are being built on top of AWS. And for these startups, we want to provide white glove support in co building products together. Right. Um, co-marketing and co-selling essentially, um, you know, the use cases that our customers need solved, um, that either they don't want to build themselves or are perhaps more innovative. Um, so the, a AWS global startup program provides white glove support, dedicated headcount for each one of those pillars. Um, and within our program, we've also provided incentives, programs go to market activities like the AWS startup showcase that we've built for these startups. >>Yeah. By the way, start AWS startups.com is the URL, check it out. Okay. So partnerships are key. Jeff, what's your role? >>Yeah. So I'm responsible for leading the overall F for, for the AWS global startup program. Um, so I've got a team of partner managers that are located throughout the us, uh, managing a few hundred startup ISVs right now. <laugh> >>Yeah, I got >>A lot. We've got a lot. >>There's a lot. I gotta, I gotta ask the tough question. Okay. I'm I'm a startup founder. I got a team. I just got my series a we're grown. I'm trying to hire people. I'm super busy. What's in it for me. Yeah. What do you guys bring to the table? I love the white glove service, but translate that what's in it. What do I get out of it? What's >>A good story. Good question. I focus, I think. Yeah, because we get, we get to see a lot of partners building their businesses on AWS. So, you know, from our perspective, helping these partners focus on what, what do we truly need to build by working backwards from customer feedback, right? How do we effectively go to market? Because we've seen startups do various things, um, through trial and error, um, and also just messaging, right? Because oftentimes partners or rather startups, um, try to boil the ocean with many different use cases. So we really help them, um, sort of laser focus on what are you really good at and how can we bring that to the customer as quickly as possible? >>Yeah. I mean, it's truly about helping that founder accelerate the growth of their company. Yeah. Right. And there's a lot that you can do with AWS, but focus is truly the key word there because they're gonna be able to find their little piece of real estate and absolutely deliver incredible outcomes for our customers. And then they can start their growth curve there. >>What are some of the coolest things you've seen with the APN that you can share publicly? I know you got a lot going on there, a lot of confidentiality. Um, but you know, we're here lot of great partners on the floor here. I'm glad we're back at events. Uh, a lot of stuff going on digitally with virtual stuff and, and hybrid. What are some of the cool things you guys have seen in the APN that you can point to? >>Yeah, absolutely. I mean, I can point to few, you can take them. Sure. So, um, I think what's been fun over the years for me personally, I came from a startup, ran sales at an early stage startup and, and I went through the whole thing. So I have a deep appreciation for what these guys are going through. And what's been interesting to see for me is taking some of these early stage guys, watching them progress, go public, get acquired, and see that big day mm-hmm <affirmative>, uh, and being able to point to very specific items that we help them to get to that point. Uh, and it's just a really fun journey to watch. >>Yeah. I, and part of the reason why I really, um, love working at the AWS, uh, global startup program is working with passionate founders. Um, I just met with a founder today that it's gonna, he's gonna build a very big business one day, um, and watching them grow through these stages and supporting that growth. Um, I like to think of our program as a catalyst for enterprise sort of scale. Yeah. Um, and through that we provide visibility, credibility and growth opportunities. >>Yeah. A lot, a lot of partners too. What I found talking to staff founders is when they have that milestone, they work so hard for it. Whether it's a B round C round Republic or get bought. Yeah. Um, then they take a deep breath and they look back at wow, what a journey it's been. So it's kind of emotional for sure. Yeah. Still it's a grind. Right? You gotta, I mean, when you get funding, it's still day one. You don't stop. It's no celebrate, you got a big round or valuation. You still gotta execute >>And look it's hypercompetitive and it's brutally difficult. And our job is to try to make that a little less difficult and navigate those waters right. Where everyone's going after similar things. >>Yeah. I think as a group element too, I observe that startups that I, I meet through the APN has been interesting because they feel part of AWS. Yeah, totally. As a group of community, as a vibe there. Um, I know they're hustling, they're trying to make things happen. But at the same time, Amazon throws a huge halo effect. I mean, that's a huge factor. I mean, yeah. You guys are the number one cloud in the business, the growth in every sector is booming. Yeah. And if you're a startup, you don't have that luxury yet. And look at companies like snowflake, they're built on top of AWS. Yeah. I mean, people are winning by building on AWS. >>Yeah. And our, our, our program really validates their technology first. So we have, what's called a foundation's technical review that we put all of our startups through before we go to market. So that when enterprise customers are looking at startup technology, they know that it's already been vetted. And, um, to take that a step further and help these partners differentiate, we use programs like the competency programs, the DevOps compet, the, the security competency, which continues to help, um, provide sort of a platform for these startups, help them differentiate. And also there's go to market benefits that are associated with that. >>Okay. So let me ask the, the question that's probably on everyone's mind, who's watching. Certainly I asked this a lot. There's a lot of companies startups out there who makes the, is there a criteria? Oh God, it's not like his sports team or anything, but like sure. Like there's activate program, which is like, there's hundreds of thousands of startups out there. Not everyone is at the APN. Right? Correct. So ISVs again, that's a whole nother, that's a more mature partner that might have, you know, huge market cap or growth. How do you guys focus? How do you guys focus? I mean, you got a good question, you know, a thousand flowers blooming all the time. Is there a new way you guys are looking at it? I know there's been some talk about restructure or, or new focus. What's the focus. >>Yeah. It's definitely not an easy task by any means. Um, but you know, I recently took over this role and we're really trying to establish focus areas, right. So obviously a lot of the fees that we look after our infrastructure ISVs, that's what we do. Uh, and so we have very specific pods that look after different type of partners. So we've got a security pod, we've got a DevOps pod, we've got core infrastructure, et cetera. And really we're trying to find these ISVs that can solve, uh, really interesting AWS customer challenges. >>So you guys have a deliberate, uh, focus on these pillars. So what infrastructure, >>Security, DevOps, and data and analytics, and then line of business >>Line of business line, like web marketing >>Solutions, business apps, >>Business, this owner type thing. Exactly. >>Yeah, exactly. >>So solutions there. Yeah. More solutions and the other ones are like hardcore. So infrastructure as well, like storage, backup, ransomware of stuff, or, >>Uh, storage, networking. >>Okay. Yeah. The classic >>Database, et cetera. Right. >>And so there's teams on each pillar. >>Yep. So I think what's, what's fascinating for the startup that we cover is that they've got, they truly have support from a build market sell perspective. Right. So you've got someone who's technical to really help them get the technology, figured out someone to help them get the marketing message dialed and spread, and then someone to actually do the co-sell, uh, day to day activities to help them get in front of customers. >>Probably the number one request that we always ask for Amazon is can we waste that sock report? Oh, download it, the console, which we use all the time. Exactly. But security's a big deal. I mean, you know, SREs are evolving, that role of DevOps is taking on dev SecOps. Um, I, I could see a lot of customers having that need for a relationship to move things faster. Do you guys provide like escalation or is that a part of a service or not, not part of a, uh, >>Yeah, >>So the partner development manager can be an escalation point. Absolutely. Think of them as an extension of your business inside of AWS. >>Great. And you guys how's that partner managers, uh, measure >>On those three pillars. Right. Got it. Are we billing, building valuable use cases? So product development go to market, so go to market activities, think blog, posts, webinars, case studies, so on and so forth. And then co-sell not only are we helping these partners win their current opportunities that they are sourcing, but can we also help them source net new deals? Yeah. Right. That's >>Very important. I mean, top asked from the partners is get me in front of customers. Right. Um, not an easy task, but that's a huge goal of ours to help them grow their top >>Line. Right. Yeah. In fact, we had some interviews here on the cube earlier talking about that dynamic of how enterprise customers are buying. And it's interesting, a lot more POCs. I have one partner here that you guys work with, um, on observability, they got a huge POC with capital one mm-hmm <affirmative> and the enterprises are engaging the startups and bringing them in. So the combination of open source software enterprises are leaning into that hard and bringing young growing startups in mm-hmm <affirmative>. Yep. So I could see that as a huge service that you guys can bring people in. >>Right. And they're bringing massively differentiated technology to the table. Mm-hmm <affirmative> the challenge is they just might not have the brand recognition that the big guys have. And so that it's our job is how do you get that great tech in front of the right situations? >>Okay. So my next question is about the show here, and then we'll talk globally. So here in San Francisco sure. You know, Silicon valley bay area, San Francisco bay area, a lot of startups, a lot of VCs, a lot of action. Mm-hmm <affirmative> so probably a big market for you guys. Yeah. So what's exciting here in SF and then outside SF, you guys have a global program, you see any trends that are geography based or is it sure areas more mature? There's certain regions that are better. I mean, I just interviewed a company here that's doing, uh, AWS edge really well in these cases. It's interesting that these, the partners are filling a lot of holes and gaps in the opportunities with AWS. So what's exciting here. And then what's the global perspective. >>Yeah, totally. So obviously a ton of partners, I, from the bay area that we support. Um, but we're seeing a lot of really interesting technology coming out of AMEA specifically. Yeah. Uh, and making a lot of noise here in the United States, which is great. Um, and so, you know, we definitely have that global presence and, and starting to see super differentiated technology come out of those regions. >>Yeah. Especially Tel Aviv. Yeah. >>Amy real quick, before you get in the surge. It's interesting. The VC market in, in Europe is hot. Yeah. They've got a lot of unicorns coming in. We've seen a lot of companies coming in. They're kind of rattling their own, you know, cage right now. Hey, look at us. We'll see if they crash, you know, but we don't see that happening. I mean, people have been projecting a crash now in, in the startup ecosystem for at least a year. It's not crashing. In fact, funding's up. >>Yeah. The pandemic was hard on a lot of startups for sure. Yeah. Um, but what we've seen is many of these startups, they, as quickly as they can grow, they can also pivot as, as, as well. Um, and so I've actually seen many of our startups grow through the pandemic because their use cases are helping customers either save money, become more operationally efficient and provide value to leadership teams that need more visibility into their infrastructure during a pandemic. >>It's an interesting point. I talked to Andy jazzy and Adam Leski both say the same thing during the pandemic necessity, the mother of all invention. Yep. And startups can move fast. So with that, you guys are there to assist if I'm a startup and I gotta pivot cuz remember iterate and pivot, iterate and pivot. So you get your economics, that's the playbook of the ventures and the models. >>Exactly. How >>Do you guys help me do that? Give me an example of walk me through, pretend me I'm a startup. Hey, I am on the cloud. Oh my God. Pandemic. They need video conferencing. Hey cube. Yeah. What do I need? Surge? What, what do I do? >>That's a good question. First thing is just listen. Yeah. I think what we have to do is a really good job of listening to the partner. Um, what are their needs? What is their problem statement and where do they want to go at the end of the day? Um, and oftentimes because we've worked with so many successful startups, they have come out of our program. We have, um, either through intuition or a playbook, determined what is gonna be the best path forward and how do we get these partners to stop focusing on things that will eventually, um, just be a waste of time yeah. And, or not provide, or, you know, bring any fruit to the table, which, you know, essentially revenue. >>Well, we love star rights here in the cube because one, um, they have good stories. They're oil and cutting edge, always pushing the envelope and they're kind of disrupting someone else. Yeah. And so they have an opinion. They don't mind sharing on camera. So love talking to startups. We love working with you guys on our startup showcases startups.com. Check out AWS startups.com and you got the showcases, uh, final. We I'll give you guys the last word. What's the bottom line bumper sticker for AP the global APN program. Summarize the opportunity for startups, what you guys bring to the table and we'll close it out. Totally start >>With you. Yeah. I think the AWS global startup program's here to help companies truly accelerate their business full stop. Right. And that's what we're here for. I love it. >>It's a good way to, it's a good way to put it Dito. >>Yeah. All right, sir. Thanks for coming on. Thanks John. Great to see you love working with you guys. Hey, startups need help. And the growing and huge market opportunities, the shift cloud scale data engineering, security infrastructure, all the markets are exploding in growth because of the digital transformation of the realities here. Open source and cloud all making it happen here in the cube in San Francisco, California. I'm John furrier, your host. Thanks for watching >>John. >>Hello and welcome back to the cubes live coverage here in San Francisco, California for AWS summit, 2022. I'm John for host of the cube. Uh, two days of coverage, AWS summit, 2022 in New York city. Coming up this summer, we'll be there as well at events are back. The cube is back of course, with the cube virtual cube hybrid, the cube.net, check it out a lot of content this year, more than ever, a lot more cloud data cloud native, modern applic is all happening. Got a great guest here. Jeremy Burton, Cub alumni, uh, CEO of observe Inc in the middle of all the cloud scale, big data observability Jeremy. Great to see you. Thanks >>Always great to come and talk to you on the queue, man. It's been been a few years, so, >>Um, well you, you got your hands. You're in the trenches with great startup, uh, good funding, great board, great people involved in the observability hot area, but also you've been a senior executive president of Dell, uh, EMC, uh, 11 years ago you had a, a vision and you actually had an event called cloud meets big data. Um, yeah. And it's here. You predicted it 11 years ago. Um, look around it's cloud meets big data. >>Yeah. I mean the, the cloud thing I think, you know, was, was probably already a thing, but the big data thing I do claim credit for, for, for sort of catching that bus out, um, you know, we, we were on the, the, the bus early and, and I think it was only inevitable. Like, you know, if you could bring the economics and the compute of cloud to big data, you, you could find out things you could never possibly imagine. >>So you're close to a lot of companies that we've been covering deeply. Snowflake obviously are involved, uh, the board level, you know, the founders, you know, the people there cloud, you know, Amazon, you know, what's going on here? Yeah. You're doing a startup as the CEO at the helm, uh, chief of observ, Inc, which is an observability, which is to me in the center of this confluence of data engineering, large scale integrations, um, data as code integrating into applic. I mean, it's a whole nother world developing, like you see with snowflake, it means snowflake is super cloud as we call it. So a whole nother wave is here. What's your, what's this wave we're on what's how would you describe the wave? >>Well, a couple of things, I mean, people are, I think riding more software than, than ever fall. Why? Because they've realized that if, if you don't take your business online and offer a service, then you become largely irrelevant. And so you you've got a whole set of new applications. I think, I think more applications now than any point. Um, not, not just ever, but the mid nineties, I always looked at as the golden age of application development. Now back then people were building for windows. Well, well now they're building for things like AWS is now the platform. Um, so you've got all of that going on. And then at the same time, the, the side effect of these applications is they generate data and lots of data and the, you know, the sort of the transactions, you know, what you bought today or something like that. But then there's what we do, which is all the telemetry data, all the exhaust fumes. And I think people really are realizing that their differentiation is not so much their application. It's their understanding of the data. Can, can I understand who my best customers are, what I sell today. If people came to my website and didn't buy, then I not, where did they drop off all of that they wanna analyze. And, and the answers are all in the data. The question is, can you understand it >>In our last startup showcase, we featured data as code. One of the insights that we got out of that I wanna get your opinion on our reaction to is, is that data used to be put into a data lake and turns into a data swamp or throw into the data warehouse. And then we'll do some query, maybe a report once in a while. And so data, once it was done, unless it was real time, even real time was not good anymore after real time. That was the old way. Now you're seeing more and more, uh, effort to say, let's go look at the data cuz now machine learning is getting better. Not just train once mm-hmm <affirmative> they're iterating. Yeah. This notion of iterating and then pivoting, iterating and pivoting. Yeah, that's a Silicon valley story. That's like how startups work, but now you're seeing data being treated the same way. So now you have another, this data concept that's now yeah. Part of a new way to create more value for the apps. So this whole, this whole new cycle of >>Yeah. >>Data being reused and repurposed and figured out and >>Yeah, yeah. I'm a big fan of, um, years ago. Uh, uh, just an amazing guy, Andy McAfee at the MIT C cell labs I spent time with and he, he had this line, which still sticks to me this day, which is look I'm I'm. He said I'm part of a body, which believes that everything is a matter of data. Like if you, of enough data, you can answer any question. And, and this is going back 10 years when he was saying these kind of things and, and certainly, you know, research is on the forefront. But I, I think, you know, starting to see that mindset of the, the sort of MIT research be mainstream, you know, in enterprises, they they're realizing that yeah, it is about the data. You know, if I can better understand my data better than my competitor than I've got an advantage. And so the question is is, is how, what, what technologies and what skills do I need in my organization to, to allow me to do that. So >>Let's talk about observing you the CEO of, okay. Given you've seen the wave before you're in the front lines of observability, which again is in the center of all this action what's going on with the company. Give a quick minute to explain, observe for the folks who don't know what you guys do. What's the company doing? What's the funding status, what's the product status and what's the customer status. Yeah. >>So, um, we realized, you know, a handful of years ago, let's say five years ago that, um, look, the way people are building applications is different. They they're way more functional. They change every day. Uh, but in some respects they're a lot more complicated. They're distributed. They, you know, microservices architectures and when something goes wrong, um, the old way of troubleshooting and solving problems was not gonna fly because you had SA so much change going into production on a daily basis. It was hard to tell like where the problem was. And so we thought, okay, it's about time. Somebody looks at the exhaust fumes from this application and all the telemetry data and helps people troubleshoot and make sense of the problems that they're seeing. So, I mean, that's observability, it's actually a term that goes back to the 1960s. It was a guy called, uh, Rudolph like, like everything in tech, you know, it's, it's a reinvention of, of something from years gone by. >>But, um, there's a guy called, um, Rudy Coleman in 1960s, kinder term. And, and, and the term was been able to determine the state of a system by looking at its external outputs. And so we've been going on this for, uh, the best part of the all years now. Um, it took us three years just to build the product. I think, I think what people don't appreciate these days often is the barrier to entry in a lot of these markets is quite high. You, you need a lot of functionality to have something that's credible with a customer. Um, so yeah, this last year we, we, we did our first year selling, uh, we've got about 40 customers now. <affirmative> um, we just we've got great investors for the hill ventures. Uh, I mean, Mike SP who was, you know, the, the guy who was the, really, the first guy in it snowflake and the, the initial investor were fortunate enough to, to have Mike on our board. And, um, you know, part of the observed story yeah. Is closely knit with snowflake because all of that time data know we, we still are in there. >>So I want to get, uh, >>Yeah. >>Pivot to that. Mike Pfizer, snowflake, Jeremy Burton, the cube kind of, kind of same thinking this idea of a super cloud or what snowflake became snowflake is massively successful on top of AWS. Mm-hmm <affirmative> and now you're seeing startups and companies build on top of snowflake. Yeah. So that's become an entrepreneurial story that we think that to go big in the cloud, you can have a cloud on a cloud, uh, like as Jerry, Jerry Chan and Greylock calls it castles in the cloud where there are moats in the cloud. So you're close to it. I know you're doing some stuff with snowflake. So a startup, what's your view on building on top of say a snowflake or an AWS, because again, you gotta go where the data is. You need all the data. >>Yeah. So >>What's your take on that? >>I mean, having enough gray hair now, um, you know, again, in tech, I think if you wanna predict the future, look at the past. And, uh, you know, to many years ago, 25 years ago, I was at a, a smaller company called Oracle and an Oracle was the database company. And, uh, their, their ambition was to manage all of the world's transactional data. And they built on a platform or a couple of platforms, one, one windows, and the other main one was Solaris. And so at that time, the operator and system was the platform. And, and then that was the, you know, ecosystem that you would compete on top of. And then there were companies like SAP that built applications on top of Oracle. So then wind the clock forward 25 years gray hairs. <laugh> the platform, isn't the operating system anymore. The platform is AWS, you know, Google cloud. I gotta probably look around if I say that in. Yeah. It's >>Okay. But hyperscale, yeah. CapX built out >>That is the new platform. And then snowflake comes along. Well, their aspiration is to manage all of the, not just human generator data, but machine generated data in the world of cloud. And I think they they've done an amazing job doing for the, I'd say, say the, the big data world, what Oracle did for the relational data world, you know, way back 25 years ago. And then there are folks like us come along and, and of course my ambition would be, look, if, if we can be as successful as an SAP building on top of snow snowflake, uh, as, as they were on top of Oracle, then, then we'd probably be quite happy. >>So you're building on top of snowflake. >>We're building on top of snowflake a hundred percent. And, um, you know, I've had folks say to me, well, aren't you worried about that? Isn't that a risk? It's like, well, that that's a risk. You >>Still on the board. >>Yeah. I'm still on the board. Yeah. That that's a risk I'm prepared to take <laugh> I am long on snowflake you, >>Well, you're in a good spot. Stay on the board, then you'll know what's going on. Okay. No know just doing, but the, this is a real dynamic. It is. It's not a one off it's. >>Well, and I do believe as well that the platform that you see now with AWS, if you look at the revenues of AWS is an order of magnitude more than Microsoft was 25 years ago with windows mm-hmm <affirmative>. And so I believe the opportunity for folks like snowflake and folks like observe it's an order of magnitude more than it was for the Oracle and the SAPs of the old >>World. Yeah. And I think this is really, I think this is something that this next generation of entrepreneurship is the go big scenario is you gotta be on a platform. Yeah. >>It's quite >>Easy or be the platform, but it's hard. There's only like how many seats are at that table left. >>Well, value migrates up over time. So, you know, when the cloud thing got going, there were probably 10, 20, 30, you know, Rackspace and there's 1,000,001 infrastructure, a service platform as a service, my, my old, uh, um, employee EMC, we had pivotal, you know, pivotal was a platform as a service. You don't hear so much about it, these, but initially there's a lot of players and then it consolidates. And then to, to like extract, uh, a real business, you gotta move up, you gotta add value, you gotta build databases, then you gotta build applications. So >>It's interesting. Moving from the data center of the cloud was a dream for starters. Cause then if the provision, the CapEx, now the CapEx is in the cloud. Then you build on top of that, you got snowflake you on top of that, the >>Assumption is almost that compute and storage is free. I know it's not quite free. Yeah. It's >>Almost free, >>But, but you can, you know, as an application vendor, you think, well, what can I do if I assume compute and storage is free, that's the mindset you've gotta get into. >>And I think the platform enablement to value. So if I'm an entrepreneur, I'm gonna get a serious, multiple of value in what I'm paying. Yeah. Most people don't even blanket their Avis pills unless they're like massively huge. Yeah. Then it's a repatriation question or whatever discount question, but for most startups or any growing company, the Amazon bill should be a small factor. >>Yeah. I mean, a lot of people, um, ask me like, look, you're building on snowflake. Um, you, you know, you are, you are, you're gonna be, you're gonna be paying their money. How, how, how, how does that work with your business model? If you're paying them money, you know, do, do you have a viable business? And it's like, well, okay. I, we could build a database as well in observe, but then I've got half the development team working on in that will never be as good as snowflake. And so we made the call early on that. No, no, we, we wanna innovate above the database. Yeah. Right. Snowflake are doing a great job of innovating on the database and, and the same is true of something like Amazon, like, like snowflake could have built their own cloud and their own platform, but they didn't. >>Yeah. And what's interesting is that Dave <inaudible> and I have been pointing this out and he's actually more on snowflake. I I've been looking at data bricks, um, and the same dynamics happening, the proof is the ecosystem. Yeah. I mean, if you look at Snowflake's ecosystem right now and data bricks it's exploding. Right. I mean, the shows are selling out the floor. Space's book. That's the old days at VMware. Yeah. The old days at AWS >>One and for snowflake and, and any platform provider, it's a beautiful thing. You know, we build on snowflake and we pay them money. They don't have to sell to us. Right. And we do a lot of the support. And so the, the economics work out really, really well. If you're a platform provider and you've got a lot of ecosystems. >>Yeah. And then also you get, you get a, um, a trajectory of, uh, economies of scale with the institutional knowledge of snowflake integrations, right. New products. You're scaling that function with the, >>Yeah. I mean, we manage 10 petabytes of data right now. Right. When I, when I, when I arrived at EMC in 2010, we had, we had one petabyte customer. And, and so at observe, we've been only selling the product for a year. We have 10 petabytes of data under management. And so been able to rely on a platform that can manage that is invaluable, >>You know, but Jeremy Greek conversation, thanks for sharing your insights on the industry. Uh, we got a couple minutes left. Um, put a plug in for observe. What do you guys, I know you got some good funding, great partners. I don't know if you can talk about your, your, your POC customers, but you got a lot of high ends folks that are working with you. You getting traction. Yeah. >>Yeah. >>Scales around the corner. Sounds like, are you, is that where you are scale? >>Got, we've got a big announcement coming up in two or weeks. We've got, we've got new funding, um, which is always great. Um, the product is, uh, really, really close. I think, as a startup, you always strive for market fit, you know, which is at which point can you just start hiring salespeople? And the revenue keeps going. We're getting pretty close to that right now. Um, we've got about 40 SaaS companies run on the platform. They're almost all AWS Kubernetes, uh, which is our sweet spot to begin with, but we're starting to get some really interesting, um, enterprise type customers. We're, we're, you know, F five networks we're POC in right now with capital one, we got some interest in news around capital one coming up. I, I can't share too much, uh, but it's gonna be exciting. And, and like I saids hill continued to, to, to stick, >>I think capital one's a big snowflake customer as well. Right. They, >>They were early in one of the things that attracted me to capital one was they were very, very good with snowflake early on. And, and they put snowflake in a position in the bank where they thought that snowflake could be successful. Yeah. And, and today that, that is one of Snowflake's biggest accounts. >>So capital one, very innovative cloud, obviously AIOS customer and very innovative, certainly in the CISO and CIO, um, on another point on where you're at. So you're, Prescale meaning you're about to scale, right? So you got POCs, what's that trick GE look like, can you see around the corner? What's, what's going on? What's on, around the corner. That you're, that you're gonna hit the straight and narrow and, and gas it >>Fast. Yeah. I mean, the, the, the, the key thing for us is we gotta get the product. Right. Um, the nice thing about having a guy like Mike Pfizer on the board is he doesn't obsess about revenue at this stage is questions that the board are always about, like, is the product, right? Is the product right? Is the product right? If you got the product right. And cuz we know when the product's right, we can then scale the sales team and, and the revenue will take care of itself. Yeah. So right now all the attention is on the product. Um, the, this year, the exciting thing is we were, we're adding all the tracing visualizations. So people will be able to the kind of things that back in the day you could do with the new lakes and, and AppDynamics, the last generation of, of APM tools, you're gonna be able to do that within observe. And we've already got the logs and the metrics capability in there. So for us, this year's a big one, cuz we sort of complete the trifecta, you know, the, the logs, >>What's the secret sauce observe. What if you had the, put it into a, a sentence what's the secret sauce? I, >>I, I think, you know, an amazing founding engineering team, uh, number one, I mean, at the end of the day, you have to build an amazing product and you have to solve a problem in a different way. And we've got great long term investors. And, and the biggest thing our investors give is actually it's not just money. It gives us time to get the product, right. Because if we get the product right, then we can get the growth. >>Got it. Final question. Why I got you here? You've been on the enterprise business for a long time. What's the buyer landscape out there. You got people doing POCs on capital one scale. So we know that goes on. What's the appetite at the buyer side for startups and what are their requirements that you're seeing? Uh, obviously we're seeing people go in and dip into the startup pool because new ways to refactor their business restructure. So a lot happening in cloud. What's the criteria. How are enterprises engaging in with startups? >>Yeah. I mean, enterprises, they know they've gotta spend money transforming the business. I mean, this was, I almost feel like my old Dell or EMC self there, but, um, what, what we were saying five years ago is happening. Um, everybody needs to figure out out a way to take their, this to this digital world. Everybody has to do it. So the nice thing from a startup standpoint is they know at times they need to risk or, or take a bet on new technology in order to, to help them do that. So I think you've got buyers that a have money, uh, B prepared to take risks and it's, it's a race against time to, you know, get their, their offerings in this. So a new digital footprint, >>Final, final question. What's the state of AWS. Where do you see them going next? Obviously they're continuing to be successful. How does cloud 3.0, or they always say it's day one, but it's more like day 10. Uh, but what's next for Aw. Where do they go from here? Obviously they're doing well. They're getting bigger and bigger. >>Yeah. They're, they're, it's an amazing story. I mean, you know, we we're, we're on AWS as well. And so I, I think if they keep nurturing the builders in the ecosystem, then that is their superpower. They, they have an early leads. And if you look at where, you know, maybe the likes of Microsoft lost the plot in the, in the late it was, they stopped, uh, really caring about developers and the folks who were building on top of their ecosystem. In fact, they started buying up their ecosystem and competing with people in their ecosystem. And I see with AWS, they, they have an amazing head start and if they did more, you know, if they do more than that, that's, what's gonna keep the jut rolling for many years to come. Yeah, >>They got the silicone and they got the staff act, developing Jeremy Burton inside the cube, great resource for commentary, but also founding with the CEO of a company called observing in the middle of all the action on the board of snowflake as well. Um, great start. Thanks for coming on the cube. >>Always a pleasure. >>Okay. Live from San Francisco to cube. I'm John for your host. Stay with us more coverage from San Francisco, California after the short break. >>Hello. Welcome back to the cubes coverage here live in San Francisco, California. I'm John furrier, host of the cubes cube coverage of AWS summit 2022 here in San Francisco. We're all the developers of the bay area at Silicon valley. And of course, AWS summit in New York city is coming up in the summer. We'll be there as well. SF and NYC cube coverage. Look for us. Of course, reinforcing Boston and re Mars with the whole robotics AI thing, all coming together. Lots of coverage stay with us today. We've got a great guest from Deibel VC. John Skoda, founding partner, entrepreneurial venture is a venture firm. Your next act, welcome to the cube. Good to see you. >>Good to see you, Matt. I feel like it's been forever since we've been able to do something in person. Well, >>I'm glad you're here because we run into each other all the time. We've known each other for over a decade. Um, >><affirmative>, it's been at least 10 years now, >>At least 10 years more. And we don't wanna actually go back as frees back, uh, the old school web 1.0 days. But anyway, we're in web three now. So we'll get to that in >>Second. We, we are, it's a little bit of a throwback to the path though, in my opinion, >><laugh>, it's all the same. It's all distributed computing and software. We ran each other in cube con you're investing in a lot of tech startup founders. Okay. This next level, next gen entrepreneurs have a new makeup and it's software. It's hardcore tech in some cases, not hardcore tech, but using software is take old something old and make it better, new, faster. <laugh>. So tell us about Deibel what's the firm. I know you're the founder, uh, which is cool. What's going on. Explain >>What you're doing. I mean, you remember I'm a recovering entrepreneur, right? So of course I, I, I, >>No, you're never recovering. You're always entrepreneur >>Always, but we are also always recovering. So I, um, started my first company when I was 24. If you remember, before there was Facebook and friends, there was instant messaging. People were using that product at work every day, they were creating a security vulnerability between their network and the outside world. So I plugged that hole and built an instant messaging firewall. It was my first company. The company was called, I am logic and we were required by Symantec. Uh, then spent 12 years investing in the next generation of our companies, uh, early investor in open source companies and cloud companies and spent a really wonderful 12 years, uh, at a firm called NEA. So I, I feel like my whole life I've been either starting enterprise software companies or helping founders start enterprise software companies. And I'll tell you, there's never been a better time than right now to start enter price software company. >>So, uh, the passion for starting a new firm was really a recognition that founders today that are starting in an enterprise software company, they, they tend to be, as you said, a more technical founder, right? Usually it's a software engineer or a builder mm-hmm <affirmative>, uh, they are building products that are serving a slightly different market than what we've traditionally seen in enterprise software. Right? I think traditionally we've seen it buyers or CIOs that have agendas and strategies, which, you know, purchased software that has traditionally bought and sold tops down. But, you know, today I think the most successful enterprise software companies are the ones that are built more bottoms up and have more technical early opts. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software. And it starts with great technical founders with great products and great and emotions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background, super smart admire of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is all companies. The is no, I mean, consumer is enterprise. Now everything is what was once a niche. No, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. But remember, like right now, there's also a giant tech in VC conference in Miami <laugh> it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, >>Ts is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. Well, and, >>And I think all of us here that are, uh, maybe students of history and have been involved in, open in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three movement. >>The hype is definitely that three. >>Yeah. But, but >>You know, for >>Sure. Yeah, no, but now you're taking us further east to Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case now? And maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many men over, uh, 500 billion in growing, you know, 20 to 30% a year. So it it's a, it's a just incredibly fast, >>Let's getting, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant, but it's also the hype of like the web three, for instance. But you know, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Luman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, higher direct sales force and SAS kind of crushed the, at now SAS is being redefined, right. So what is SAS? Is snowflake a SAS or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, they own all my data. You know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of commonalities across all successful startups and the overall adoption of technology. Uh, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually user like growth, right. They're one in the same. So sometimes people think the product, uh, is what is driving. You >>Just pull the >>Product through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this movement maybe started with open source where users were, are contributors, you know, contributors, we're users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing and it's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the users. And they're really the, the beneficiaries and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a GenXer technically, so for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I've, I've been staying on the cube for probably about eight years now that we are gonna hit a digital hippie revolution, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one other group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. We hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>It's the main for days, those renegades were breaking into Stanford, starting the home brew club. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on. Well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion around the way in which a product is built. Right. And we can use open source, one example of that religion. Some people will say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? It's, it's something that people just believe to be true almost without, uh, necessarily. I mean >>The decision making, let me ask you this next question. As a VC. Now you look at pitch, well, you've made a VC for many years, but you also have the founder, uh, entrepreneurial mindset, but you can get empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of is about believing in the person. So fing, so you make, it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. Oh, >>AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur, right. And the persona of the entrepreneur would be, you know, somebody who was a great salesperson or somebody who tell a great story. You, I still think that that's important, right? It still is a human need for people to believe in narratives and stories. But having said that you're right, the proof is in the pudding, right? At some point you click download and you try the product and it does what it says it it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in this new economy that we live in, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative because their products exactly >>The volume back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song was the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with. Right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the, you know, it's gotta speak to >>The, speak to the user, but let me ask a question now that the people watching who are maybe entrepreneurial entrepreneur, um, masterclass here is in session. So I have to ask you, do you prefer, um, an entrepreneur to come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine. Whether you're an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage, engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think something will become. Right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way, and we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be, the more likely somebody is gonna align with your vision and, and want to invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I >>Show >>The path. I think the single most important thing for any founder and VC relationship is that they have the same vision, uh, have the same vision. You can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle of the journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the latest trends because it's over before you can get there. >>Exactly. I think many people that, that do what we do for a living will say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. So you, you know, you sort of have to balance the, you know, we, we know that the world is going this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but sometimes it happens in six months. Sometimes it takes six years is sometimes like 16 years. >>Uh, what's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Desel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There, there's three big trends that we invest in. And they're the, they're the only things we do day in, day out. One is the explosion and open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen and on what timeline happening >>Forever. >>But it is, it is accelerating faster than we've ever seen. So I, I think it's, it's one big, massive wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now, a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a, a market as any of the other markets that we invest in. Uh, and finally, it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is under invested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a dessert do over, right? I mean, do we need a do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cyber security as an add-on. Yeah. But if you think about it, the whole economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is around 150 billion. And it still is a fraction of what we're, what >>We're and security even boom is booming now. So you get the convergence of national security, geopolitics, internet digital >>That's right. You mean arguably, right? I mean, arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say, you gotta love your firm. Love. You're doing we're big supporters of your mission. Congratulations on your entrepreneurial venture. And, uh, we'll be, we'll be talking and maybe see a Cub gone. Uh, >>Absolutely. >>Certainly EU maybe even north America's in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for having me on >>The show. Guess bell VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California. After the short break, stay with us. Everyone. Welcome to the queue here. Live in San Francisco, California for AWS summit, 2022 we're live we're back with the events. Also we're virtual. We got hybrid all kinds of events. This year, of course, 80% summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube got a great guest here. Justin Coby owner and CEO of innovative solutions. Their booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us a story. What do you guys do? What's the elevator pitch. >>Yeah. <laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to midsize businesses that are moving into the cloud or have already moved to the cloud and really trying to understand how to best control, cost, security, compliance, all the good stuff, uh, that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is, but now we have offices down in Austin, Texas up in Toronto, uh, key Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago and it's been a great ride. It >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by AWS. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization and obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? >>Yeah. It's a great question. Every CEO I talk to, that's a small to midsize business. They're trying to understand how to leverage technology. It better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech ISNT really at the, at the forefront and the center of that. So most customers are coming to us and they're like, listen, we gotta move to the cloud or we move some things to cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then, uh, progressively working through a modernization strateg, always the better approach. And so we spend a lot of time with small to midsize businesses who don't have the technology talent on staff to be able to do >>That. Yeah. They want get set up. But then the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is. And it's not, it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem you guys solve >>In the SMB space? The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and are hardened solutions. And so, um, what we try to do with technology staff that has traditional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to, yeah, they're like, listen, the end of the day, I'm gonna be spending money in one place or another, whether that's OnPrem or in the cloud. I just want to know that I'm doing that in a way that helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. >>Good. How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I, there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start down your journey in one way and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning the projects that early and not worrying about it, you got it. I mean, most people don't abandon cause like, oh, I own it. >>Exactly. And >>They get, they get used to it. Like, and then they wait too long. >>That's exactly. Yeah. >>Frog and boiling water as we used to say. So, oh, it's a great analogy. So I mean, this is a dynamic that's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you, I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talked to at reinvent, that's a customer. Well, how many announcements did am jazzy announce or Adam, you know, the 5,000 announcement or whatever. They do huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just processes. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are, >>What's the values. >>Our mission is, is very simple. We want to help every small to midsize business leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a tech company in the process of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your, or it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning they know that we have their back Andre or the safety net. So when a customer is saying, all right, I'm gonna spend a couple thousand dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going in alone. Who's there to help protect that. Number two, if you have a security posture and let's just say you're high profile and you're gonna potentially be more vulnerable to security attack. If you have a partner, that's all offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products, uh, that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own. It, it would cost 'em a fortune. If >>Training alone would be insane, a factor and the cost. Yes, absolutely. Opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. Yeah. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018, when, uh, when we made the decision to go all in on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious decision. It wasn't requirement and still isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front desk >>And she could be running the Kubernetes clusters. I love it. It's amazing. >>But I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get >>The right people involved. And that's a cultural factor that you guys have. So, so again, this is back to my whole point about SMBs and businesses in general, small en large, it staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the build out, um, uh, return factor, ROI piece. At what point in time as an owner or SMB, do I get the ROI? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cybersecurity issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one and the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Critical issues. This >>Is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about. So that's, >>That's what, at least a million in bloating, if not three or more Just to get that going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side though. Yeah. No. And nevermind AI and ML. That's >>Right. That's right. So to try to go it alone, to me, it's hard. It it's incredibly difficult. And, and the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll >>Do all that >>Exactly. In it department. >>Exactly. >>Like, can we just call up, uh, you know, <laugh> our old vendor. That's >>Right. <laugh> right. Our old vendor. I like it, but that's so true. I mean, when I think about how, if I was a business owner, starting a business to today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. And it's something that we talk about every, with every one of our small to midsize business. >>So just, I want to get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduce other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. And I came in, I did an internship for six months and I loved it. I learned more in those six months that I probably did in my first couple of years at, uh, at R I T long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2010 and I was like, Hey, I'm growing the value of this business. And who knows where you guys are gonna be another five years? What do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner, but if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that we're gonna also buy the business with >>Me. And they were the owners, no outside capital, >>None zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons. They all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like if we're owners, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015, and, uh, we made the decision that I was gonna buy the three partners out, um, go through an earn out process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the business, cuz they care very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting all going all in on the cloud was important for us and we haven't looked back. >>And at that time, the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly the, uh, and those kinds of big enterprises. The game don't, won't say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to midsize business, to migrate completely to the cloud as, as infrastructure was considered. That just didn't happen as often. Um, what we were seeing were a lot of our small to midsize business customers, they wanted to leverage cloud based backup, or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration. The, the Microsoft suite to the cloud and a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on eight at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is the app modernization? Is it data? What's the hot product and then put a plug in for the company. Awesome. >>So, uh, there's no question. Every customer is looking to migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating to the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customers not to be cash strapped and gives them an opportunity to move forward in a controlled, contained way so that they can modernize. >>So like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers, empathetic to where they are in their journey. And >>That's the cloud upside is all about doubling down on the variable wind. That's right. Seeing the value and doubling down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate it. Thank >>You very much for having >>Me. Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching with back with more great coverage for two days after this short break >>Live on the floor in San Francisco for 80 west summit, I'm John ferry, host of the cube here for the next two days, getting all the action we're back in person. We're at AWS reinvent a few months ago. Now we're back events are coming back and we're happy to be here with the cube, bringing all the action. Also virtual, we have a hybrid cube, check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticketing off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad >>To be here. So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to have to be back through events. >>It's amazing. This is the first, uh, summit I've been to and what two, three years. >>It's awesome. We'll be at the, uh, New York as well. A lot of developers and a big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything dev sec ops, everyone kind of sees that you got containers, you got Kubernetes, you got cloud native. So the, the game is pretty much laid out. Mm. And the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's right. >>Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions that are around, especially the edge public cloud out for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give >>An example, >>Uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech data and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running their FinTech on top of AWS services inside Panama. >>You know, what's interesting, Matthew is that we've been covering Aw since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and then became the CEO. Now Adam Slosky is in charge, but the edge has always been that thing they've been trying to, I don't wanna say, trying to avoid, of course, Amazon would listen to customers. They work backwards from the customers. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does >>Computing. It >>Does. >>That's not central lies in the public cloud. Now they got regions. So what is the issue with the edge what's driving? The behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see with the data at the edge, you got five GM having. So it's pretty obvious, but there was a slow transition. What was the driver for the <affirmative> what's the driver now for edge action for AWS >>Data is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation. Whereas today we have over fit 15 AWS edge services, and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always used to riff on the cube, uh, cuz it's basically Amazon in a box, pushed in the data center, uh, running native, all the stuff, but now cloud native operations are kind of become standard. You're starting to see some standard Deepak sings group is doing some amazing work with open source Rauls team on the AI side, obviously, uh, you got SW who's giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see low the zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my data center, do I wanna manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outpost. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone. Now what's happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware. We can go deploy EKS anywhere in your VMware environment and it's increasing the speed of adoption >>For sure. So you guys are making a lot of good business decisions around managed cloud service. Innovative does that. You have the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in, in these new areas that you're helping out are they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their available ability zones or their regions that you guys are delivering. What's the key is it. They don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on, what's making them money as a business. They wanna focus on their applications. They want focus on their customers. So they look towards AWS cloud and say, AWS, you take the infrastructure. You take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. We help build out these things in local data centers for 32 plus year old company, we have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're filling that gap in helping deploy these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. >>So basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it works? Right. >>And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy FinTech in the Caribbean, we're gonna talk about hurricanes and gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where now have data, you have applications that are tapping into that, that requirement. It makes total sense. We're seeing across the board. So it's not like it's, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech in, in the islands. There are a lot of, lot of, lot of web three happening. What's your, what's your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto underly parts of their central banks. Yeah. Um, so it's, it's up and coming. Uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a tech technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on it's >>Interesting. And I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, projects going on. But if you look talk to all the crypto people that say, look, we do a smart contract, we use the blockchain. It's kind of over a lot of overhead. It's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain, just for this like smart contracts for instance, or certain transactions. And they go into Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service, but what happened to decent centralized. >>Yeah. And that's, and that's the conversation performance. >>Yeah. >>And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through a, a use case of a customer, um, Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud. Um, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my a and I also want all the benefits of the cloud. So I want the modernization and I wanna migrate to the cloud for all those cloud benefits and the good this of the cloud. What's the answer. Yeah. >>Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment inside that, that manufacturing plant can be hooked up. They don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with, uh, regular commercially available hardware running VMware, and we deploy EKS anywhere on that. Uh, inside of that manufacturing plant, uh, we can do pre-processing on things coming out of the, uh, the robotics that depending on what we're manufacturing, right. Uh, and then we can take the, those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard >>For data lake or whatever, >>To the data lake. Yeah. Data Lakehouse, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but I'll lot of that, uh, just in time business decisions, just in time, manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going of the data that saves that cost yep. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data unless you have to. Um, but those new things are developing. So I wanna ask you, what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacture, industrial, whatever the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? There's a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe, maybe this decision can wait. Yeah. Uh, and then how do I visualize that? By >>The way, it could be a bot tube doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture in the back. So there's new things developing. You've got more benefit. There >>Are, there are. And, and we have more and more people that, that want to talk less about databases and want to talk more about data lakes because of this. They want to talk more about out. Customers are starting to talk about throwing away data, uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And well, >>I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session on this, but the one pattern we're seeing of the past year is that throwing away data's bad, even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retraining their machine learning algorithms. Yep. So as data becomes code, as we call it in our last showcase, we did a whole whole event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw it away. It's not just business better. Yeah. There's all kinds of new scale. >>There are. And, and we have, uh, many customers that are running pay Toby level. Um, they're, they're essentially data factories on, on, uh, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move Aytes of data to the AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a kind of a, um, fun note. I was told to ask you about your personal background, OnPrem architect, Aus cloud, and skydiving instructor. <laugh> how does that all work together? What tell, what does this mean? Yeah. >>Uh, you >>Jumped out a plane and got a job. You got a customer to jump out >>Kind of. So I was, you jumped out. I was teaching having, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a sky. I instructor, uh, I was teaching skydiving and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and, and how his customers are working. And he can't find an enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, uh, I was living in a tent in the woods, teaching skydiving. I was like, I'd love to not live in a tent in the woods. So, uh, uh, I started and the first day there, uh, we had a, a discussion, uh, EC two had just come out <laugh> and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that, and through being in on premises, migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services tore >>It's. So it's such a great story, you know, was gonna, you know, you know, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early days was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, uh, when that was coming out, it was, I mean, it was, it was still, and maybe it does still feel like that to some people. Right. But, uh, it was, it was the same kind of feeling that we had in the early days of AWS, the same feeling we have when we >>It's now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting edge stuff, like jumping out of an airplane. Yeah. You got the right equipment. You gotta do the right things. Exactly. >>Right. >>Yeah. Thanks for coming. You really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here live in San Francisco for eight of us summit. I'm John for host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. Look up this calendar for all the cube, actually@thecube.net. We'll right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube a be summit 2022. We're back in person. I'm John fury host of the cube. We'll be at the eighties summit in New York city this summer, check us out then. But right now, two days in San Francisco, getting all the coverage what's going on in the cloud, we got a cube alumni and friend of the cube, my dos car CEO, investor, a Sierra, and also an investor in a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you. Cool. How are you? Good. >>How hello you. >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah. So give us the update. How much cash have you guys raised? What's the status of the company product what's going on? >>First of all, thank you for having me. We're back to be business with you, never after to see you. Uh, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. We have raised close to a hundred million there. The investors are people like Norwes Menlo ventures, coastal ventures, Ram Shera, and all those people, all well known guys. And Beckel chime Paul me Mayard web. So whole bunch of operating people and, uh, Silicon valley VCs are involved >>And has it gone? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISRA is going after is what I call the applying AI for customer service. It operations, it help desk, uh, the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and service now to take you to the next stage? Well, >>I love having you on the cube, Dave and I, Dave LAN as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a, you're like a guest analyst. <laugh> >>You know, who does >>You, >>You >>Get the call fund to talk to you though. You >>Get the commentary, your, your finger in the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud scale. You predicted that we talked about in the cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing Docker just raised a hundred million on a $2 billion valuation back from the dead after they pivoted from enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control plan? Emerging AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded, observability there's 10 billion observability companies. Data is the key. This is what's your end on this. What's your take. >>Yeah, look, I think I'll give you the few that I see right from my side. Obviously data is very clear. So the things that rumor system of recorded you and me talked about the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud native, it'll be called AI. NA AI enable is a new buzzword and using the AI for customer service. It, you talk about observability. I call it, AIOps applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and AI services. What used to be desk with ServiceNow BMC GLA you see a new ALA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflows, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with AI workflows. So you, you see AI going >>Off is RPA. A company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI S one will be at their event this summer? Um, is it a product company? I mean, or I mean, RPA is, should be embedded in everything. It's a >>Feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company also, but that automation should be embedded in every area. Yeah. Like we call cloud NATO and AI. They it'll become automation data. Yeah. And that's your, thinking's >>Interesting me. I think about the, what you're talking about what's coming to mind is I'm kinda having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it was middleware. It sat between two things and then the middle, and it was software abstraction. Now you have all kinds of workflows, abstractions everywhere. So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed. Are they integrated? I mean, these are the challenges. This is crazy. What's the, >>So remember the databases became called polyglot databases. Yeah. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area like you, you were talking about, it should be part of service. Now it should be part of ISRA. Like every company, every Salesforce. So that's why you see it MuleSoft and sales buying RPA companies. So you'll see all the SaaS companies, cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also have an automation as a layer embedded inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind, as you got the XPO hall got, um, we're back to vis, but you got, you know, AMD, Clum, Dynatrace data, dog, innovative, all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right? Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Deibel later. He's a former NEA guy and we always talk to Jerry, Jen, we know all the, the VCs, what does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation. Cloud's bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's code. Yes. Basically. Data's everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders of Amazon created the startups 15 years back. Everybody built on Amazon now, Azure and GCP. The next layer would be people don't just build on Amazon. They're going to build it on top of snow. Flake companies are snowflake becomes a data platform, right? People will build on snowflake, right? So I see my old boss playing ment, try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer, right? So I think that's the next level of companies trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis a couple months ago called castles in the cloud where your moat is, what you do in the cloud. Not necessarily in the, in the IP. Um, Dave LAN and I had last re invent, coined the term super cloud, right? It's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You're starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage. And guys like Charles Fitzgeral out there, who we like was kind of hitting on us saying, Hey, you guys terrible, they didn't get him. Like, yeah, I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> cause he's cool. Um, but snowflake is on Amazon. Yes. Now they say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist and, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. >>It is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer room. The middle layer pass will be snowflake. So I cannot build it on snowflake. I can use them for data layer if I really need to size, I'll build it on force.com Salesforce. Yeah. Right. So I think that's where you'll >>See. So basically the, the, if you're an entrepreneur, the, the north star in terms of the, the outcome is be a super cloud. It >>Is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. Yeah. >>Yeah. How are, how is Amazon and the clouds dealing with these big whales, the snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think got Redshift. Amazon has got Redshift. Um, but snowflake big customer. The they're probably paying AWS big, >>I >>Think big bills too. >>So John, very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-option will be there. So Amazon will have Redshift, but Amazon is also partnering with the snowflake to have native snowflake data warehouse as a data layer. So I think depending on the use case you have to use each of the above, I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, you know, foreclose your value. That's right. With some sort of internal hack, but I've think, I think the general question that I have is that I think it's okay to have a super cloud like that because the rising tide is still happening at some point, when does the rising tide stop and the people shopping up their knives, it gets more competitive or is it just an infinite growth cycle? I >>Think it's growth. You call it closed skill you the word cloud scale. So I think look, cloud will continually agree, increase. I think there's as long as there more movement from on, uh, on-prem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations, it helpless. Even the customer service service. Now the ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go made. >>I wanna get your thoughts for the folks watching that are, uh, enterprise buyers are practitioners, not suppliers to the market. Feel free to text me or DMing. Next question is really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products. Cause you know, the big enterprises now and you know, small, medium, large, and large enterprise, they're all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or growing startup selling to an enterprise? Um, have you seen changes there? I mean seeing some stuff, but why don't we get your thoughts on that? What it >>Is you, if I remember going back to our 2007 or eight, when I used to talk to you back then when Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or one person today. Most companies are already spending 20, 30% with startups. Like if I look at a C I will line our business, it's gone. Yeah. Can it go more? I think it can double in the next four, five years. Yeah. Spending on the startups. Yeah. >>And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I, I reference the URL causes like there's like a bunch of companies we've been promoting because the solution that startups have actually are new stuff. Yes. It's bending, it's shifting left for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there. Um, and goes back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure as code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share? >>I, a lot of thoughts that Fu I see the AI op solutions in the futures should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app dynamic, right? Dynatrace, all this solution will go future towards predict to pro so solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service that customers give the data, share the data because we thought the data algorithms are useless. I can give the best algorithm, but I gotta train them, modify them, make them better, make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to big data days back in 2009, you know that >>Look at, look how much data bricks has grown. >>It is doubled. The key cloud >>Air kinda went private, so good stuff. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking year that growing customers and my customers, or some of them, you like it's zoom auto desk, McAfee, uh, grand <inaudible>. So all the top customers, um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on, predict ours. One area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service, >>Great stuff, man. Doing great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of a us summit 2022. And we're gonna be at Aus summit in San, uh, in New York in the summer. So look for that on the calendar, of course, go to a us startups.com. That's a site for all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This the cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back, little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit in new York's coming in the summer. We'll be two with the cube on the set. We're getting back in the Groove's psych to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're gonna see a lot of virtual cube outta hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economist with duck bill groove, he's the founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank you. >>Thanks. Coming on. Sure is a lot of words to describe is shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at mark, Andrew's been doing a lot of shit posting lately. All a billionaires are shit posting, but they don't know how to do it. They're >>Doing it right. There's something opportunity there. It's like, here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a mid-size island to begin doing this from, oh, then we're having fun. >>This shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on this side I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what, what is shitposting >>It's more or less talking about the world of enterprise technology, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream, but it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a Jack ass or more prosaically are worried about getting fired for better or worse. I don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, Cuban coming up in Spain, which they're having a physical event, you see the growth of cloud native Amazon's evolving Atos, especially new CEO. Andy move on to be the chief of all. Amazon just saw him the cover of was it time magazine. Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything. These folks do. They're they're effectively in a fishbowl, but I have trouble. Imagine the logistics, it takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. And it's, it's sprawling immense, the nominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. >>Well, there's a lot of force for good conversations. Seeing a lot of that going on, Amazon's trying to a, is trying to portray themselves, you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now it's same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car, our driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. Either way, it sounds like more exciting. Like they >>Better have a replacement ready in case something goes wrong on the track, highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula, the one is they have these new rigs out. Yeah. Where you can actually race in e-sports with other people in pure simulation of the race car. You gotta get the latest and video graphics card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. Oh, >>It's great too. And I can see the appeal of these tech companies getting it into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going on in your world. I know you have a lot of great SA we've been following you in the queue for many, many years. Got a great newsletter. Check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's the blowback, any blowback late leads there been tick? What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's hi, I'm emailing an awful lot of people at last week in AWS every week and okay. They not have heard me. It. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do that. >>We should do that. Actually. I think sure would call in. Oh, I, I >>Think >>I guarantee if we had that right now, people would call in and Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the customer. >>You know, I always joke with Dave Avante about how John Fort's always at, uh, um, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0, 0 5, or we can't, we >>Have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And then there you go. Yeah. >>It's and the old joke at HP was if they, if they invented sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish, but that's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their product >>They're going in different directions. When they named Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonus on number of words, they can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, a session manager is a great one. I love the service ridiculous name. They have a systems manager, parameter store with is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage through parameter store does not. It's fun. >>What's your, what's your favorite combination of acronyms >>Combination of you >>Got Ks. You got EMR, you got EC two. You got S three SQS. Well, RedShift's not an acronym. You got >>Gas is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation, >>They still got bean stock or is that still >>Around? Oh, they never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, wow, we built this thing in 2005 and everyone hates it. But while we certainly can't change it, now it has three customers on it, John. >>Okay. >>Simple BV still haunts our >>Dreams. I, I actually got an email on, I saw one of my, uh, servers, all these C twos were being deprecated and I got an email I'm like, I couldn't figure out. Why can you just like roll it over? Why, why are you telling me just like, gimme something else. Right. Okay. So let me talk about, uh, the other things I want to ask you is that like, okay, so as Amazon gets better in some areas where do they need more work? And you, your opinion, because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database Snowflake's got out database service. So, you know, Redshift, snowflake database is out there. So you've got this optician. Yes. How's that going? And what are you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with Amazon and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want. And they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multi-cloud cause obviously the other cloud shows are coming up. Amazon hated that word. Multi-cloud um, a lot of people are saying, you know, it's not a real good marketing word. Like multicloud sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multicloud? >>Multiple single >>Loves that term. Yeah. >>You're building in multiple single points of failure. Do it for the right reasons or don't do it as a default. I believe not doing it is probably the, the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about multi-cloud either as the industry leader, let's talk about other clouds, bad direction to go in from a market cap perspective. It doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of some brilliant, some brain dead. It depends a lot on context. But my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing because it solves problems. That's when I shut up and listen. >>Yeah. Cool. Awesome. Corey, I gotta ask you a question cause I know you we've been, you know, fellow journey mean in the, in the cloud journey, going to all the events and then the pandemic hit where now in the third year, who knows what it's gonna end, certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations community's gonna emerge. You've got a pretty big community growing and it's growing like crazy. What's the weirdest or coolest thing, or just big changes you've seen with the pan endemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece come in, you're commentating, you're calling balls and strikes in the industry. You got a great team developing over there. Duck bill group. What's the big aha moment that you saw with the pandemic. Weird, funny, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who >>Can pony. >>Hello and welcome back to the live cube coverage here in San Francisco, California, the cube live coverage. Two days, day two of a summit, 2022 Aish summit, New York city coming up in summer. We'll be there as well. Events are back. I'm the host, John fur, the Cub got great guest here. Johnny Dallas with Ze. Um, here is on the queue. We're gonna talk about his background. Uh, little trivia here. He was the youngest engineer ever worked at Amazon at the age. 17 had to get escorted into reinvent in Vegas cause he was underage <laugh> with security, all good stories. Now the CEO of company called Z know DevOps kind of focus, managed service, a lot of cool stuff, Johnny, welcome to the cube. >>Thanks John. Great. >>So tell a story. You were the youngest engineer at AWS. >>I was, yes. So I used to work at a company called Bebo. I got started very young. I started working when I was about 14, um, kind of as a software engineer. And when I, uh, it was about 16. I graduated out of high school early, um, working at this company Bebo, still running all of the DevOps at that company. Um, I went to reinvent in about 2018 to give a talk about some of the DevOps software I wrote at that company. Um, but you know, as many of those things were probably familiar with reinvent happens in a casino and I was 16. So was not able to actually go into the, a casino on my own. Um, so I'd have <inaudible> security as well as casino security escort me in to give my talk. >>Did Andy jazzy, was he aware of >>This? Um, you know, that's a great question. I don't know. <laugh> >>I'll ask him great story. So obviously you started a young age. I mean, it's so cool to see you jump right in. I mean, I mean you never grew up with the old school that I used to grew up in and loading package software, loading it onto the server, deploying it, plugging the cables in, I mean you just rocking and rolling with DevOps as you look back now what's the big generational shift because now you got the Z generation coming in, millennials on the workforce. It's changing like no one's putting and software on servers. Yeah, >>No. I mean the tools keep getting better, right? We, we keep creating more abstractions that make it easier and easier. When I, when I started doing DevOps, I could go straight into E two APIs. I had APIs from the get go and you know, my background was, I was a software engineer. I never went through like the CIS admin stack. I, I never had to, like you said, rack servers, myself. I was immediately able to scale. I was managing, I think 2,500 concurrent servers across every Ables region through software. It was a fundamental shift. >>Did you know what an SRE was at that time? >>Uh, >>You were kind of an SRE on >>Yeah, I was basically our first SRE, um, was familiar with the, with the phrasing, but really thought of myself as a software engineer who knows cloud APIs, not a SRE. All >>Right. So let's talk about what's what's going on now as you look at the landscape today, what's the coolest thing that's going on in your mind in cloud? >>Yeah, I think the, I think the coolest thing is, you know, we're seeing the next layer of those abstraction tools exist and that's what we're doing with Z is we've basically gone and we've, we're building an app platform that deploys onto your cloud. So if you're familiar with something like Carku, um, where you just click a GitHub repo, uh, we actually make it that easy. You click a GI hub repo and it will deploy on ALS using a AWS tools. So, >>Right. So this is Z. This is the company. Yes. How old's the company about >>A year and a half old now. >>All right. So explain what it does. >>Yeah. So we make it really easy for any software engineer to deploy on a AWS. It's not SREs. These are the actual application engineers doing the business logic. They don't really want to think about Yamo. They don't really want to configure everything super deeply. They want to say, run this API on S in the best way possible. We've encoded all the best practices into software and we set it up for you. Yeah. >>So I think the problem you're solving is that there's a lot of want be DevOps engineers. And then they realize, oh shit, I don't wanna do this. Yeah. And some people want to do it. They loved under the hood. Right. People love to have infrastructure, but the average developer needs to actually be as agile on scale. So that seems to be the problem you solve. Right? >>Yeah. We, we, we give way more productivity to each individual engineer, you know? >>All right. So let me ask you a question. So let me just say, I'm a developer. Cool. I build this new app. It's a streaming app or whatever. I'm making it up cube here, but let's just say I deploy it. I need your service. But what happens about when my customers say, Hey, what's your SLA? The CDN went down from this it's flaky. Does Amazon have, so how do you handle all that SLA reporting that Amazon provides? Cuz they do a good job with sock reports all through the console. But as you start getting into DevOps <affirmative> and sell your app, mm-hmm <affirmative> you have customer issues. How do you, how do you view that? Yeah, >>Well, I, I think you make a great point of AWS has all this stuff already. AWS has SLAs. AWS has contract. Aw has a lot of the tools that are expected. Um, so we don't have to reinvent the wheel here. What we do is we help people get to those SLAs more easily. So Hey, this is AWS SLA as a default. Um, Hey, we'll fix you your services. This is what you can expect here. Um, but we can really leverage S's reliability of you. Don't have to trust us. You have to trust ALS and trust that the setup is good there. >>Do you handle all the recovery or mitigation between, uh, identification say downtime for instance? Oh, the server's not 99% downtime. Uh, went down for an hour, say something's going on? And is there a service dashboard? How does it get what's the remedy? Do you have a, how does all that work? >>Yeah, so we have some built in remediation. You know, we, we basically say we're gonna do as much as we can to keep your endpoint up 24 7 mm-hmm <affirmative>. If it's something in our control, we'll do it. If it's a disc failure, that's on us. If you push bad code, we won't put out that new version until it's working. Um, so we do a lot to make sure that your endpoint stay is up, um, and then alert you if there's a problem that we can't fix. So cool. Hey S has some downtime, this thing's going on. You need to do this action. Um, we'll let you know. >>All right. So what do you do for fun? >>Yeah, so, uh, for, for fun, um, a lot of side projects. <laugh> uh, >>What's your side hustle right now. You got going on >>The, uh, it's >>A lot of tools playing tools, serverless. >>Yeah, painless. A lot of serverless stuff. Um, I think there's a lot of really cool WAM stuff as well. Going on right now. Um, I love tools is, is the truest answer is I love building something that I can give to somebody else. And they're suddenly twice as productive because of it. Um, >>It's a good feeling, isn't it? >>Oh yeah. There's >>Nothing like tools were platforms. Mm-hmm <affirmative>, you know, the expression, too many tools in the tool. She becomes, you know, tools for all. And then ultimately tools become platforms. What's your view on that? Because if a good tool works and starts to get traction, you need to either add more tools or start building a platform platform versus tool. What's your, what's your view on a reaction to that kind of concept debate? >>Yeah, it's a good question. Uh, we we've basically started as like a, a platform. First of we've really focused on these, uh, developers who don't wanna get deep into the DevOps. And so we've done all of the pieces of the stacks. We do C I C D management. Uh, we do container orchestration, we do monitoring. Um, and now we're, spliting those up into individual tools so they can be used. Awesome in conjunction more. >>All right. So what are some of the use cases that you see for your service? It's DevOps basically nano service DevOps. So people who want a DevOps team, do clients have a DevOps person and then one person, two people what's the requirements to run >>Z. Yeah. So we we've got teams, um, from no DevOps is kind of when they start and then we've had teams grow up to about, uh, five, 10 men DevOps teams. Um, so, you know, as is more infrastructure people come in because we're in your cloud, you're able to go in and configure it on top you're we can't block you. Uh, you wanna use some new AWS service. You're welcome to use that alongside the stack that we deploy >>For you. How many customers do you have now? >>So we've got about 40 companies that are using us for all of their infrastructure, um, kind of across the board, um, as well as >>What's the pricing model. >>Uh, so our pricing model is we, we charge basically similar to an engineering salary. So we charge a monthly rate. We have plans at 300 bucks a month, a thousand bucks a month, and then enterprise plan for >>The requirement scale. Yeah. So back into the people cost, you must have her discounts, not a fully loaded thing, is it? >>Yeah, there's a discounts kind of asking >>Then you pass the Amazon bill. >>Yeah. So our customers actually pay for the Amazon bill themselves. So >>Have their own >>Account. There's no margin on top. You're linking your, a analyst account in, um, got it. Which is huge because we can, we are now able to help our customers get better deals with Amazon. Um, got it. We're incentivized on their team to drive your costs down. >>And what's your unit main unit of economics software scale. >>Yeah. Um, yeah, so we, we think of things as projects. How many services do you have to deploy as that scales up? Um, awesome. >>All right. You're 20 years old now you not even can't even drink legally. <laugh> what are you gonna do when you're 30? We're gonna be there. >>Well, we're, uh, we're making it better, better, >>Better the old guy on the queue here. <laugh> >>I think, uh, I think we're seeing a big shift of, um, you know, we've got these major clouds. ALS is obviously the biggest cloud and it's constantly coming out with new services, but we're starting to see other clouds have built many of the common services. So Kubernetes is a great example. It exists across all the clouds and we're starting to see new platforms come up on top that allow you to leverage tools for multiple times. At the same time. Many of our customers actually have AWS as their primary cloud and they'll have secondary clouds or they'll pull features from other clouds into AWS, um, through our software. I think that's, I'm very excited by that. And I, uh, expect to be working on that when I'm 30. <laugh> awesome. >>Well, you gonna have a good future. I gotta ask you this question cuz uh, you know, I always, I was a computer science undergrad in the, in the, and um, computer science back then was hardcore, mostly systems OS stuff, uh, database compiler. Um, now there's so much compi, right? Mm-hmm <affirmative> how do you look at the high school college curriculum experience slash folks who are nerding out on computer science? It's not one or two things. You've got a lot of, lot of things. I mean, look at Python, data engineering and emerging as a huge skill. What's it, what's it like for college kids now and high school kids? What, what do you think they should be doing if you had to give advice to your 16 year old self back a few years ago now in college? Um, I mean Python's not a great language, but it's super effective for coding and the datas were really relevant, but it's, you've got other language opportunities you've got tools to build. So you got a whole culture of young builders out there. What should, what should people gravitate to in your opinion and stay away from or >>Stay away from? That's a good question. I, I think that first of all, you're very right of the, the amount of developers is increasing so quickly. Um, and so we see more specialization. That's why we also see, you know, these SREs that are different than typical application engineering. You know, you get more specialization in job roles. Um, I think if, what I'd say to my 16 year old self is do projects, um, the, I learned most of my, what I've learned just on the job or online trying things, playing with different technologies, actually getting stuff out into the world, um, way more useful than what you'll learn in kind of a college classroom. I think classroom's great to, uh, get a basis, but you need to go out and experiment actually try things. >>You know? I think that's great advice. In fact, I would just say from my experience of doing all the hard stuff and cloud is so great for just saying, okay, I'm done, I'm banning the project. Move on. Yeah. Cause you know, it's not gonna work in the old days. You have to build this data center. I bought all this, you know, people hang on to the old, you know, project and try to force it out there. Now you >>Can launch a project now, >>Instant gratification, it ain't working <laugh> or this is shut it down and then move on to something new. >>Yeah, exactly. Instantly you should be able to do that much more quickly. Right. So >>You're saying get those projects and don't be afraid to shut it down. Mm-hmm <affirmative> that? Do you agree with that? >>Yeah. I think it's ex experiment. Uh, you're probably not gonna hit it rich on the first one. It's probably not gonna be that idea is the genius idea. So don't be afraid to get rid of things and just try over and over again. It's it's number of reps >>That'll win. I was commenting online. Elon Musk was gonna buy Twitter, that whole Twitter thing. And someone said, Hey, you know, what's the, I go look at the product group at Twitter's been so messed up because they actually did get it right on the first time. And we can just a great product. They could never change it because people would freak out and the utility of Twitter. I mean, they gotta add some things, the added button and we all know what they need to add, but the product, it was just like this internal dysfunction, the product team, what are we gonna work on? Don't change the product so that you kind of have there's opportunities out there where you might get the lucky strike right outta the gate. Yeah. Right. You don't know. >>It's almost a curse too. It's you're not gonna hit curse Twitter. You're not gonna hit a rich the second time too. So yeah. >><laugh> Johnny Dallas. Thanks for coming on the cube. Really appreciate it. Give a plug for your company. Um, take a minute to explain what you're working on. What you're look looking for. You hiring funding. Customers. Just give a plug, uh, last minute and kind the last word. >>Yeah. So, um, John Dallas from Ze, if you, uh, need any help with your DevOps, if you're a early startup, you don't have DevOps team, um, or you're trying to deploy across clouds, check us out z.com. Um, we are actively hiring. So if you are a software engineer excited about tools and cloud, or you're interested in helping getting this message out there, hit me up. Um, find us on z.co. >>Yeah. LinkedIn Twitter handle GitHub handle. >>Yeah. I'm the only Johnny on a LinkedIn and GitHub and underscore Johnny Dallas underscore on Twitter. All right. Um, >>Johnny Dallas, the youngest engineer working at Amazon, um, now 20 we're on great new project here in the cube. Builders are all young. They're growing into the business. They got cloud at their, at their back it's tailwind. I wish I was 20. Again, this is a I'm John for your host. Thanks for watching. Thanks. >>Welcome >>Back to the cubes. Live coverage of a AWS summit in San Francisco, California events are back, uh, ADAS summit in New York cities. This summer, the cube will be there as well. Check us out there lot. I'm glad we have events back. It's great to have everyone here. I'm John furry host of the cube. Dr. Matt wood is with me cube alumni now VP of business analytics division of AWS. Matt. Great to see you. Thank >>You, John. Great to be here. >>Appreciate it. I always call you Dr. Matt wood, because Andy jazzy always says Dr. Matt, we >>Would introduce you on the he's the one and only the one and >>Only Dr. Matt wood >>In joke. I love it. >>Andy style. And I think you had walkup music too on, you know, >>Too. Yes. We all have our own personalized walk. >>So talk about your new role. I not new role, but you're running up, um, analytics, business or AWS. What does that consist of right now? >>Sure. So I work, I've got what I consider to be the one of the best jobs in the world. Uh, I get to work with our customers and, uh, the teams at AWS, uh, to build the analytics services that millions of our customers use to, um, uh, slice dice, pivot, uh, better understand their day data, um, look at how they can use that data for, um, reporting, looking backwards and also look at how they can use that data looking forward. So predictive analytics and machine learning. So whether it is, you know, slicing and dicing in the lower level of, uh Hado and the big data engines, or whether you're doing ETR with glue or whether you're visualizing the data in quick side or building models in SageMaker. I got my, uh, fingers in a lot of pies. >>You know, one of the benefits of, uh, having cube coverage with AWS since 2013 is watching the progression. You were on the cube that first year we were at reinvent 2013 and look at how machine learning just exploded onto the scene. You were involved in that from day one is still day one, as you guys say mm-hmm <affirmative>, what's the big thing now. I mean, look at, look at just what happened. Machine learning comes in and then a slew of services come in and got SageMaker became a hot seller, right outta the gate. Mm-hmm <affirmative> the database stuff was kicking butt. So all this is now booming. Mm-hmm <affirmative> that was the real generational changeover for <inaudible> what's the perspective. What's your perspective on, yeah, >>I think how that's evolved. No, I think it's a really good point. I, I totally agree. I think for machine machine learning, um, there was sort of a Renaissance in machine learning and the application of machine learning machine learning as a technology has been around for 50 years, let's say, but, uh, to do machine learning, right? You need like a lot of data, the data needs to be high quality. You need a lot of compute to be able to train those models and you have to be able to evaluate what those mean as you apply them to real world problems. And so the cloud really removed a lot of the constraints. Finally, customers had all of the data that they needed. We gave them services to be able to label that data in a high quality way. There's all the compute. You need to be able to train the models <laugh> and so where you go. >>And so the cloud really enabled this Renaissance with machine learning, and we're seeing honestly, a similar Renaissance with, uh, with data, uh, and analytics. You know, if you look back, you know, five, 10 years, um, analytics was something you did in batch, like your data warehouse ran a analysis to do, uh, reconciliation at the end of the month. And then was it? Yeah. And so that's when you needed it, but today, if your Redshift cluster isn't available, uh, Uber drivers don't turn up door dash deliveries, don't get made. It's analytics is now central to virtually every business and it is central to every virtually every business is digital transformation. Yeah. And be able to take that data from a variety of sources here, or to query it with high performance mm-hmm <affirmative> to be able to actually then start to augment that data with real information, which usually comes from technical experts and domain experts to form, you know, wisdom and information from raw data. That's kind of, uh, what most organizations are trying to do when they kind of go through this analytics journey. It's >>Interesting, you know, Dave LAN and I always talk on the cube, but out, you know, the future and, and you look back, the things we were talking about six years ago are actually happening now. Yeah. And it's not a, a, a, you know, hyped up statement to say digital transformation. It actually's happening now. And there's also times where we bang our fist on the table, say, I really think this is so important. And Dave says, John, you're gonna die on that hill <laugh>. >>And >>So I I'm excited that this year, for the first time I didn't die on that hill. I've been saying data you're right. Data as code is the next infrastructure as code mm-hmm <affirmative>. And Dave's like, what do you mean by that? We're talking about like how data gets and it's happening. So we just had an event on our 80 bus startups.com site mm-hmm <affirmative>, um, a showcase with startups and the theme was data as code and interesting new trends emerging really clearly the role of a data engineer, right? Like an SRE, what an SRE did for cloud. You have a new data engineering role because of the developer on, uh, onboarding is massively increasing exponentially, new developers, data science, scientists are growing mm-hmm <affirmative> and the, but the pipelining and managing and engineering as a system. Yeah. Almost like an operating system >>And as a discipline. >>So what's your reaction to that about this data engineer data as code, because if you have horizontally scalable data, you've gotta be open that's hard. <laugh> mm-hmm <affirmative> and you gotta silo the data that needs to be siloed for compliance and reasons. So that's got a very policy around that. So what's your reaction to data as code and data engineering and >>Phenomenon? Yeah, I think it's, it's a really good point. I think, you know, like with any, with any technology, uh, project inside an organization, you know, success with analytics or machine learning is it's kind of 50% technology and then 50% cultural. And, uh, you have often domain experts. Those are, could be physicians or drug experts, or they could be financial experts or whoever they might be got deep domain expertise. And then you've got technical implementation teams and it's kind of a natural often repulsive force. I don't mean that rudely, but they, they just, they don't talk the same language. And so the more complex the domain and the more complex the technology, the stronger that repulsive force, and it can become very difficult for, um, domain experts to work closely with the technical experts, to be able to actually get business decisions made. And so what data engineering does and data engineering is in some cases team, or it can be a role that you play. >>Uh, it's really allowing those two disciplines to speak the same language it provides. You can think of it as plumbing, but I think of it as like a bridge, it's a bridge between like the technical implementation and the domain experts. And that requires like a very disparate range of skills. You've gotta understand about statistics. You've gotta understand about the implementation. You've gotta understand about the, it, you've gotta understand and understand about the domain. And if you could pull all of that together, that data engineering discipline can be incredibly transformative for an organization, cuz it builds the bridge between those two >>Groups. You know, I was advising some, uh, young computer science students at the sophomore junior level, uh, just a couple weeks ago. And I told 'em, I would ask someone at Amazon, this questions I'll ask you since you're, you've been in the middle of of it for years, they were asking me and I was trying to mentor them on. What, how do you become a data engineer from a practical standpoint, uh, courseware projects to work on how to think, um, not just coding Python cause everyone's coding in Python mm-hmm <affirmative> but what else can they do? So I was trying to help them and I didn't really know the answer myself. I was just trying to like kind of help figure it out with them. So what is the answer in your opinion or the thoughts around advice to young students who want to be data engineers? Cuz data scientists is pretty clear in what that is. Yeah. You use tools, you make visualizations, you manage data, you get answers and insights and apply that to the business. That's an application mm-hmm <affirmative>, that's not the, you know, sta standing up a stack or managing the infrastructure. What, so what does that coding look like? What would your advice be to >>Yeah, I think >>Folks getting into a data engineering role. >>Yeah. I think if you, if you believe this, what I said earlier about like 50% technology, 50% culture, like the, the number one technology to learn as a data engineer is the tools in the cloud, which allow you to aggregate data from virtually any source into something which is incrementally more valuable for the organization. That's really what data engineering is all about. It's about taking from multiple sources. Some people call them silos, but silos indicates that the, the storage is kind of fungible or UND differentiated. That that's really not the case. Success requires you to really purpose built well crafted high performance, low cost engines for all of your data. So understanding those tools and understanding how to use 'em, that's probably the most important technical piece. Um, and yeah, Python and programming and statistics goes along with that, I think. And then the most important cultural part, I think is it's just curiosity. >>Like you want to be able to, as a data engineer, you want to have a natural curiosity that drives you to seek the truth inside an organization, seek the truth of a particular problem and to be able to engage, cuz you're probably, you're gonna have some choice as you go through your career about which domain you end up in, like maybe you're really passionate about healthcare. Maybe you're really just passionate about your transportation or media, whatever it might be. And you can allow that to drive a certain amount of curiosity, but within those roles, like the domains are so broad, you kind of gotta allow your curiosity to develop and lead, to ask the right questions and engage in the right way with your teams. So because you can have all the technical skills in the world, but if you're not able to help the team's truths seek through that curiosity, you simply won't be successful. >>We just had a guest on 20 year old, um, engineer, founder, Johnny Dallas, who was 16 when he worked at Amazon youngest engineer at >>Johnny Dallas is a great name by the that's fantastic. It's his real name? >>It sounds like a football player. Rockstar. I should call Johnny. I have Johnny Johnny cube. Uh it's me. Um, so, but he's young and, and he, he was saying, you know, his advice was just do projects. >>Yeah. That's get hands on. >>Yeah. And I was saying, Hey, I came from the old days though, you get to stand stuff up and you hugged onto the assets. Cause you didn't wanna kill the cause you spent all this money and, and he's like, yeah, with cloud, you can shut it down. If you do a project that's not working and you get bad data, no one's adopting it or you don't want like it anymore. You shut it down. Just something >>Else. Totally >>Instantly abandoned it. Move onto something new. >>Yeah. With progression. Totally. And it, the, the blast radius of, um, decisions is just way reduced, gone. Like we talk a lot about like trying to, you know, in the old world trying to find the resources and get the funding. And it's like, right. I wanna try out this kind of random idea that could be a big deal for the organization. I need 50 million in a new data center. Like you're not gonna get anywhere. You, >>You do a proposal working backwards, document >>Kinds, all that, that sort of stuff got hoops. So, so all of that is gone, but we sometimes forget that a big part of that is just the, the prototyping and the experimentation and the limited blast radius in terms of cost. And honestly, the most important thing is time just being able to jump in there, get fingers on keyboards, just try this stuff out. And that's why at AWS, we have part of the reason we have so many services because we want, when you get into AWS, we want the whole toolbox to be available to every developer. And so, as your ideas developed, you may want to jump from, you know, data that you have, that's already in a database to doing realtime data. Yeah. And then you can just, you have the tools there. And when you want to get into real time data, you don't just have kineses, but you have real time analytics and you can run SQL again, that data is like the, the capabilities and the breadth, like really matter when it comes to prototyping and, and >>That's culture too. That's the culture piece, because what was once a dysfunctional behavior, I'm gonna go off the reservation and try something behind my boss's back or cause now as a side hustle or fun project. Yeah. So for fun, you can just code something. Yeah, >>Totally. I remember my first Haddo project, I found almost literally a decommissioned set of servers in the data center that no one was using. They were super old. They're about to be literally turned off. And I managed to convince the team to leave them on for me for like another month. And I installed her DUP on them and like, got them going. It's like, that just seems crazy to me now that I, I had to go and convince anybody not to turn these service off, but what >>It was like for that, when you came up with elastic map produce, because you said this is too hard, we gotta make it >>Easier. Basically. Yes. <laugh> I was installing Haddo version, you know, beta nor 0.9 or whatever it was. It's like, this is really hard. This is really hard. >>We simpler. All right. Good stuff. I love the, the walk down memory lane and also your advice. Great stuff. I think culture's huge. I think. And that's why I like Adam's keynote to reinvent Adam. Lesky talk about path minds and trail blazers because that's a blast radius impact. Mm-hmm <affirmative> when you can actually have innovation organically just come from anywhere. Yeah, that's totally cool. Totally. Let's get into the products. Serverless has been hot mm-hmm <affirmative> uh, we hear a lot about EKS is hot. Uh, containers are booming. Kubernetes is getting adopted. There's still a lot of work to do there. Lambda cloud native developers are booming, serverless Lambda. How does that impact the analytics piece? Can you share the hot, um, products around how that translates? Sure, absolutely. Yeah, the SageMaker >>Yeah, I think it's a, if you look at kind of the evolution and what customers are asking for, they're not, you know, they don't just want low cost. They don't just want this broad set of services. They don't just want, you know, those services to have deep capabilities. They want those services to have as lower operating cost over time as possible. So we kind of really got it down. We got built a lot of muscle, lot of services about getting up and running and experimenting and prototyping and turning things off and turn turning them on and turning them off. And like, that's all great. But actually the, you really only most projects start something once and then stop something once. And maybe there's an hour in between, or maybe there's a year, but the real expense in terms of time and, and complexity is sometimes in that running cost. Yeah. And so, um, we've heard very loudly and clearly from customers that they want, that, that running cost is just undifferentiated to them and they wanna spend more time on their work and in analytics that is, you know, slicing the data, pivoting the data, combining the data, labeling the data, training their models, uh, you know, running inference against their models, uh, and less time doing the operational pieces. >>So is that why the servers focus is there? >>Yeah, absolutely. It, it dramatically reduces the skill required to run these, uh, workloads of any scale. And it dramatically reduces the UND differentiated, heavy lifting, cuz you get to focus more of the time that you would've spent on the operation on the actual work that you wanna get done. And so if you look at something just like Redshift serverless that we launched a reinvent, you know, there's a kind of a, we have a lot of customers that want to run like a, uh, the cluster and they want to get into the, the weeds where there is benefit. We have a lot of customers that say, you know, I there's no benefit for me though. I just wanna do the analytics. So you run the operational piece, you're the experts we've run. You know, we run 60 million instant startups every single day. Like we do this a lot. Exactly. We understand the operation. I >>Want the answers come on. So >>Just give the answers or just let, give me the notebook or just give the inference prediction. So today for example, we announced, um, you know, serverless inference. So now once you've trained your machine learning model, just, uh, run a few, uh, lines of code or you just click a few buttons and then yeah, you got an inference endpoint that you do not have to manage. And whether you're doing one query against that endpoint, you know, per hour or you're doing, you know, 10 million, but we'll just scale it on the back end. You >>Know, I know we got not a lot of time left, but I want, wanna get your reaction to this. One of the things about the data lakes, not being data swamps has been from what I've been reporting and hearing from customers is that they want to retrain their machine learning algorithm. They want, they need that data. They need the, the, the realtime data and they need the time series data, even though the time has passed, they gotta store in the data lake mm-hmm <affirmative>. So now the data lakes main function is being reusing the data to actually retrain. Yeah, >>That's >>Right. It worked properly. So a lot of, lot of postmortems turn into actually business improvements to make the machine learning smarter, faster. You see that same way. Do you see it the same way? Yeah, >>I think it's, I think it's really interesting. No, I think it's really interesting because you know, we talk it's, it's convenient to kind of think of analytics as a very clear progression from like point a point B, but really it's, you are navigating terrain for which you do not have a map and you need a lot of help to navigate that terrain. Yeah. And so, you know, being, having these services in place, not having to run the operations of those services, being able to have those services be secure and well governed, and we added PII detection today, you know, something you can do automatically, uh, to be able to use their, uh, any unstructured data run queries against that unstructured data. So today we added, you know, um, text extract queries. So you can just say, well, uh, you can scan a badge for example, and say, well, what's the name on this badge? And you don't have to identify where it is. We'll do all of that work for you. So there's a often a, it's more like a branch than it is just a, a normal, uh, a to B path, a linear path. Uh, and that includes loops backwards. And sometimes you gotta get the results and use those to make improvements further upstream. And sometimes you've gotta use those. And when you're downstream, you'll be like, ah, I remember that. And you come back and bring it all together. So awesome. It's um, it's, uh, uh, it's a wonderful >>Work for sure. Dr. Matt wood here in the queue. Got just take the last word and give the update. Why you're here. What's the big news happening that you're announcing here at summit in San Francisco, California, and update on the, the business analytics >>Group? Yeah, I think, you know, one of the, we did a lot of announcements in the keynote, uh, encouraged everyone to take a look at that. Uh, this morning was Swami. Uh, one of the ones I'm most excited about, uh, is the opportunity to be able to take, uh, dashboards, visualizations. We're all used to using these things. We see them in our business intelligence tools, uh, all over the place. However, what we've heard from customers is like, yes, I want those analytics. I want their visualization. I want it to be up to date, but you know, I don't actually want to have to go my tools where I'm actually doing my work to another separate tool to be able to look at that information. And so today we announced, uh, one click public embedding for quick side dashboards. So today you can literally, as easily as embedding a YouTube video, you can take a dashboard that you've built inside, quick site cut and paste the HTML, paste it into your application and that's it. That's all you have to do. It takes seconds and >>It gets updated in real time. >>Updated in real time, it's interactive. You can do everything that you would normally do. You can brand it like this is there's no power by quick site button or anything like that. You can change the colors, make it fit in perfectly with your, with your applications. So that's sitting incredibly powerful way of being able to take a, uh, an analytics capability that today sits inside its own little fiefdom and put it just everywhere. It's, uh, very transformative. >>Awesome. And the, the business is going well. You got the serverless and your tailwind for you there. Good stuff, Dr. Matt with thank you. Coming on the cube >>Anytime. Thank >>You. Okay. This is the cubes cover of eight summit, 2022 in San Francisco, California. I'm John host cube. Stay with us with more coverage of day two after this short break.

>>Hello, everyone. Welcome to this cube conversation. I'm here in Palo Alto, California. I'm John furrier, host of the cube, and we have a great guest here. Barack Shuster. Who's in Tel-Aviv senior director of chief architect at bridge crew, a part of Palo Alto networks. He was formerly the co-founder of the company, then sold to Palo Alto networks Brock. Thanks for coming on this cube conversation. >>Thanks John. Great to be here. >>So one of the things I love about open source, and you're seeing a lot more of the trend now that talking about, you know, people doing incubators all over the world, having open source and having a builder, people who are starting companies, it's coming more and more, you you're one of them. And you've been part of this security open source cloud infrastructure infrastructure as code going back a while, and you guys had a lot of success. Now, open source infrastructure as code has moved up to the stack, certainly lot going down at the network layer, but developers just want to build security from day one, right? They don't want to have to get into the, the, the waiting game of slowing down their pipelining of code in the CIC D they want to move faster. And this has been one of the core conversations this year is how to make developers more productive and not just a cliche, but actually more productive and not have to wait to implement cloud native. Right. So you're in the middle of it. And you've got you're in, tell us, tell us what you guys are dealing with that, >>Right? Yeah. So I hear these needles working fast, having a large velocity of releases from many of my friends, the SRAs, the DevOps, and the security practitioners in different companies. And the thing that we asked ourselves three years ago was how can we simplify the process and make the security teams an enabler instead of a gatekeeper that blocks the releases? And the thing that we've done, then we understood that we should do is not only doing runtime scanning of the cloud infrastructure and the cloud native clusters, but also shift left the findings and fixings the remediation of security issues to the level of the code. So we started doing infrastructure is good. We Terraform Kubernetes manifests cloud formation, server less, and the list goes on and we created an open source product around it, named checkup, which has an amazing community of hundreds of contributors. Not all of them are Palo Alto employees. Most of them are community users from various companies. And we tried to and succeeded to the democratic side is the creation of policy as code the ability to inspect your infrastructure as code and tell you, Hey, this is the best practice that you should use consider using it before applying a misconfigured S3 bucket into production, or before applying a misconfigured Kubernetes cluster into your production or dev environment. And the goal, >>The goal, >>The goal is to do that from the ID from the moment that you write code and also to inspect your configuration in CGI and CD and in runtime. And also understand that if there is any drift out there and the ability to fix that in the source code, in the blueprint itself. >>So what I hear you saying is really two problems you're solving. One is the organizational policies around how things were done in a environment before all the old way. You know, the security teams do a review, you send a ticket, things are waiting, stop, wait, hurry up and wait kind of thing. And then there's the technical piece of it, right? Is that there's two pieces to that. >>Yeah, I think that one thing is the change of the methodologies. We understood that we should just work differently than what we used to do. Tickets are slow. They have priorities. You have a bottleneck, which is a small team of security practitioners. And honestly, a lot of the work is repetitive and can be democratized into the engineering teams. They should be able to understand, Hey, I wrote the code piece that provision this instance, I am the most suitable person as a developer to fix that piece of code and reapply it to the runtime environment. >>And then it also sets the table for our automation. It sets the table for policies, things that make things more efficient scaling. Cause you mentioned SRS are a big part of this to dev ops and SRE. Those, those folks are, are trying to move as fast as possible at scale, huge scale challenge. How does that impact the scale piece become into here? >>So both themes Esri's and security teams are about a link to deploying application, but new application releases into the production environment. And the thing that you can do is you can inspect all kinds of best practices, not only security, best practices, but also make sure that you have provision concurrencies on your serverless functions or the amount of auto-scaling groups is what you expect it to be. And you can scan all of those things in the level of your code before applying it to production. >>That's awesome. So good, good benefits scales a security team. It sounds like too as well. You could get that policy out there. So great stuff. I want to really quickly ask you about the event. You're hosting code two cloud summit. What are we going to see there? I'm going to host a panel. Of course, I'm looking forward to that as well. You get a lot of experts coming in there. Why are you having this event and what topics will be covered? >>So we wanted to talk on all of the shifts, left movement and all of the changes that have happened in the cloud security market since inception till today. And we brought in great people and great practitioners from both the dev ops side, the chaos engineering and the security practitioners, and everybody are having their opinion on what's the current status state, how things should be implemented in a mature environment and what the future might hold for the code and cloud security markets. The thing that we're going to focus on is all of the supply chain from securing the CCD itself, making sure your actions are not vulnerable to a shut injection or making sure your version control system are configured correctly with single sign-on MFA and having branch protection rules, but also open source security like SCA software composition analysis infrastructure as code security. Obviously Ron thinks security drifts and Kubernetes security. So we're going to talk on all of those different aspects and how each and every team is mitigating. The different risks that come with. >>You know, one of the things that you bring up when you hear you talking is that's the range of, of infrastructure as code. How has infrastructure as code changed? Cause you're, you know, there's dev ops and SRS now application developers, you still have to have programmable infrastructure. I mean, if infrastructure code is real realize up and down the stack, all aspects need to be programmable, which means you got to have the data, you got to have the ability to automate. How would you summarize kind of the state of infrastructure as code? >>So a few years ago, we started with physical servers where you carried the infrastructure on our back. I, I mounted them on the rack myself a few years ago and connected all of the different cables then came the revolution of BMS. We didn't do that anymore. We had one beefy appliance and we had 60 virtual servers running on one appliance. So we didn't have to carry new servers every time into the data center then came the cloud and made everything API first. And they bill and enabled us to write the best scripts to provision those resources. But it was not enough because he wanted to have a reproducible environment. The is written either in declarative language like Terraform or CloudFormation or imperative like CDK or polluted, but having a consistent way to deploy your application to multiple environments. And the stage after that is having some kind of a service catalog that will allow application developer to get the new releases up and running. >>And the way that it has evolved mass adoption of infrastructure as code is already happening. But that introduces the ability for velocity in deployment, but also new kinds of risks that we haven't thought about before as security practitioners, for example, you should vet all of the open source Terraform modules that you're using because you might have a leakage. Our form has a lot of access to secrets in your environment. And the state really contains sensitive objects like passwords. The other thing that has changed is we today we rely a lot on cloud infrastructure and on the past year we've seen the law for shell attack, for example, and also cloud providers have disclosed that they were vulnerable to log for shell attack. So we understand today that when we talk about cloud security, it's not only about the infrastructure itself, but it's also about is the infrastructure that we're using is using an open source package that is vulnerable. Are we using an open source package that is vulnerable, is our development pipeline is configured and the list goes on. So it's really a new approach of analyzing the entire software bill of material also called Asbell and understanding the different risks there. >>You know, I think this is a really great point and great insight because new opera, new solutions for new problems are new opportunities, right? So open source growth has been phenomenal. And you mentioned some of those Terraform and one of the projects and you started one checkoff, they're all good, but there's some holes in there and it's open source, it's free, everyone's building on it. So, you know, you have, and that's what it's for. And I think now is open source goes to the next level again, another generational inflection point it's it's, there's more contributors there's companies are involved. People are using it more. It becomes a really strong integration opportunity. So, so it's all free and it's how you use it. So this is a new kind of extension of how open source is used. And if you can factor in some of the things like, like threat vectors, you have to know the code. >>So there's no way to know it all. So you guys are scanning it doing things, but it's also huge system. It's not just one piece of code. You talking about cloud is becoming an operating system. It's a distributed computing environment, so whole new area of problem space to solve. So I love that. Love that piece. Where are you guys at on this now? How do you feel in terms of where you are in the progress bar of the solution? Because the supply chain is usually a hardware concept. People can relate to, but when you bring in software, how you source software is like sourcing a chip or, or a piece of hardware, you got to watch where it came from and you gotta track track that. So, or scan it and validate it, right? So these are new, new things. Where are we with? >>So you're, you're you're right. We have a lot of moving parts. And really the supply chain terms of came from the automobile industry. You have a car, you have an engine engine might be created by a different vendor. You have the wheels, they might be created by a different vendor. So when you buy your next Chevy or Ford, you might have a wheels from continental or other than the first. And actually software is very similar. When we build software, we host it on a cloud provider like AWS, GCP, Azure, not on our own infrastructure anymore. And when we're building software, we're using open-source packages that are maintained in the other half of the war. And we don't always know in person, the people who've created that piece. And we do not have a vetting process, even a human vetting process on these, everything that we've created was really made by us or by a trusted source. >>And this is where we come in. We help you empower you, the engineer, we tools to analyze all of the dependency tree of your software, bill of materials. We will scan your infrastructure code, your application packages that you're using from package managers like NPM or PI. And we scan those open source dependencies. We would verify that your CIC is secure. Your version control system is secure. And the thing that we will always focus on is making a fixed accessible to you. So let's say that you're using a misconfigured backup. We have a bot that will fix the code for you. And let's say that you have a, a vulnerable open-source package and it was fixed in a later version. We will bump the version for you to make your code secure. And we will also have the same process on your run time environment. So we will understand that your environment is secure from code to cloud, or if there are any three out there that your engineering team should look at, >>That's a great service. And I think this is cutting edge from a technology perspective. What's what are some of the new cloud native technologies that you see in emerging fast, that's getting traction and ultimately having a product market fit in, in this area because I've seen Cooper. And you mentioned Kubernetes, that's one of the areas that have a lot more work to do or being worked on now that customers are paying attention to. >>Yeah, so definitely Kubernetes is, has started in growth companies and now it's existing every fortune 100 companies. So you can find anything, every large growler scale organization and also serverless functions are, are getting into a higher adoption rate. I think that the thing that we seeing the most massive adoption off is actually infrastructure as code during COVID. A lot of organization went through a digital transformation and in that process, they have started to work remotely and have agreed on migrating to a new infrastructure, not the data center, but the cloud provider. So at other teams that were not experienced with those clouds are now getting familiar with it and getting exposed to new capabilities. And with that also new risks. >>Well, great stuff. Great to chat with you. I want to ask you while you're here, you mentioned depth infrastructure as code for the folks that get it right. There's some significant benefits. We don't get it. Right. We know what that looks like. What are some of the benefits that can you share personally, or for the folks watching out there, if you get it for sure. Cause code, right? What does the future look like? What does success look like? What's that path look like when you get it right versus not doing it or getting it wrong? >>I think that every engineer dream is wanting to be impactful, to work fast and learn new things and not to get a PagerDuty on a Friday night. So if you get infrastructure ride, you have a process where everything is declarative and is peer reviewed both by you and automated frameworks like bridge and checkoff. And also you have the ability to understand that, Hey, once I re I read it once, and from that point forward, it's reproducible and it also have a status. So only changes will be applied and it will enable myself and my team to work faster and collaborate in a better way on the cloud infrastructure. Let's say that you'd done doing infrastructure as code. You have one resource change by one team member and another resource change by another team member. And the different dependencies between those resources are getting fragmented and broken. You cannot change your database without your application being aware of that. You cannot change your load Bonser without the obligation being aware of that. So infrastructure skullduggery enables you to do those changes in a, in a mature fashion that will foes Le less outages. >>Yeah. A lot of people getting PagerDuty's on Friday, Saturday, and Sunday, and on the old way, new way, new, you don't want to break up your Friday night after a nice dinner, either rock, do you know? Well, thanks for coming in all the way from Tel-Aviv really appreciate it. I wish you guys, everything the best over there in Delhi, we will see you at the event that's coming up. We're looking forward to the code to cloud summit and all the great insight you guys will have. Thanks for coming on and sharing the story. Looking forward to talking more with you Brock thanks for all the insight on security infrastructures code and all the cool things you're doing at bridge crew. >>Thank you, John. >>Okay. This is the cube conversation here at Palo Alto, California. I'm John furrier hosted the cube. Thanks for watching.

(upbeat music) >> Okay, welcome back everyone to theCUBE's coverage of AWS re:Invent 2021. This is theCUBE. I'm John Furrier, my host Lisa Martin here, with some keynote guests who are on the big stage here at re:Invent, Linda Jojo, Chief Digital Officer at United Airlines. Thanks for coming on. >> Hey, great to be here. Thanks for having me. >> So up on the big stage, big transformation story in front of 27,000 people, on the virginity, >> Linda: That many? >> that's the number, >> It's a big room >> pretty small for Amazon web services, nearly 60,000, but you know, pandemic and all but great presentation. What was the, what was the transformation story for United? >> Well, I think there's two parts of the story. One is just how fast everything happened, you know. February of 2020, we're having a kickoff meeting with AWS about how we're going to really transform the airline and a month later the world shut down. And so it changed, we went from thinking about the future to really just trying to make it through the next few weeks. But as soon as that happened, we knew that we had to take advantage of the crisis and think about everything from what can we do with our onboard products, we've changed out a lot of things about our airplanes, we've doubled down on sustainability. We're really focused on the diversity of our workforce, but also we really said, what can we do about transforming our technology? And that's where AWS came in because one of the silver linings for our tech team was that we didn't always have a plane in the air. And so when that happens, we had no time to make a change and back it out, if it doesn't work or heaven forbid have an outage. We a little bit longer. So we got aggressive and we made a lot of changes and made a lot of move to AWS Cloud. >> Talk to me a little bit about the cultural shift involved. I mean, you talked about, you know, everybody was just scrambling. >> Yeah. So quickly, there was this instant, what do we do? How do we pivot? How do we survive mode? But from a cultural perspective, it sounds like you took, you leveraged the situation to be able to make a lot of improvements across the United, but culturally that's, that's challenging to get all those folks on board at the same time. How did you facilitate that? >> Well, you know what, the story I'm going to tell isn't all just about me. It's about the incredible team that we have, but you know, folks got focused and Amazon talks about having a two pizza team about how if your team should be no bigger than what can be fed by two pizzas, and that really keeps the decision-making streamlined and fast. For us since we were now all working from home, we called it a one screen team. And so the idea was no more than a number of people that could fit on that video call was the idea. So that was the number of people that we had on our teams. We branded them even call them scrappy teams, which was really kind of fun. And those are the groups that just kind of got their job done. And you know, the first part of their job was every week or every day it seemed like we were getting new rules from the U.S government about what countries you couldn't fly to. And it was chaotic. It was confusing for customers and frankly, our, that one screen team, they were up like every night making modifications to who could check in online and who couldn't. And we said when it's time to open back up, we can't, we got to do this better. And so that group came up with something we now call the Travel-Ready Center. Which is really pretty incredible. What you can do now is first of all, when you book your flight, we'll tell you what you need to fly. You need this type of a COVID test, this many days in advance. This is what fully vaccinated means in the country you're going to. And so this was the kind of vaccine card we need to see. You upload it all. We use Amazon SageMaker and we have machine learning models that actually now will within seven seconds validate that you're ready to fly. And what that means is just like always, you can get your boarding pass before you get to the airport. Now, if you guys travel a lot, I hope you still do, >> Yeah. what that means is that you can actually bypass the lobby of the airport and all the document checking that's going on because your travel ready. So customers love it. Gate agents love it too, because gate agents, the rules are changing so fast. They don't, you know, and they work the flight to Tel Aviv one day and the flight to Paris the next and the rules are different. And maybe in between, they changed. So having the software actually figured that out is what helps. >> So very dynamic and new innovations popped out of this pandemic. What else did Amazon help you with? Was there other Amazon innovations that you guys gravitated to SageMaker was one, what were some of the other? >> Yeah. You know, honestly, the team uses a lot of the tools and a lot of different ways. I would say the other big one was DynamoDB, and some of the things that we did to actually migrate some of our core systems to Amazon and actually, you know, instead of making phoning home to data centers all the time, we're now going right to the Cloud and getting some, some really great performance out of that. >> And, and, and the travel thing that you guys did that was came out of the innovation from the teams. >> Yeah. >> is there any other, other examples that popped out from you guys? >> Yeah. Well, I think another one is something that we call Agent on Demand. Agent on Demand is where you used it when you had to talk to an agent in the airport, you'd go get in line somewhere. And sometimes it was a long line, right? Because there's only two people there. And so the first thing we did was we made sure the technologies they used worked on a phone or an iPad. So now we weren't limited by the number of, of stations at the gate. The next thing we is that we made it QR code enabled. And now what customers can do is they can scan the QR code and they get a live agent, like a FaceTime call on their, on their phone. They can do it from anywhere from their seat at the gate or in line for a coffee, and they can solve their problem right there. And those agents, by the way, now maybe there's a snowstorm going on in Chicago, but the agents are in Houston where it's sunny. And so we can actually leverage the fact that those agents are there to help our customers. >> So you've got the user experience, you did some innovation. How about the operational things, I noticed when I traveled the United, the packaging's different ,the greetings are different. I get why all these operational impacts happened to the whole supply chain.(laughing) >> Yeah. Well, you know, the technology's great, but what makes you remember United are the people that you're going to interact with. And so we really focused on service for our, for our employees. And how do we give them information in the palm of their hand to, to treat you in a very personal way. We know that you flew last week and where you went. We know that you just made a million miles. And so we can give that information to our flight attendant and they can provide a really great experience. >> That experience is key. These days. One of the things that's been in short supply, during the pandemic is patience. And obviously you guys have to be very cognizant of that with some of the things that have happened across all the airlines and passengers not having the patience that they normally would have. >> Oh yeah. That is a real kudos to our flight attendants. And what we did with them, you know, wearing a mask is required on the aircraft and, you know, some folks don't like to be told what to do anywhere, right? And so people don't like that. Our flight attendants learned how to deescalate the situation and deal with it on the ground. So it's very simple. If you're not wearing a mask, flight attendant asked you nicely, you still don't put your mask on. They just give you a little card that says, by the way, if you don't put your mask on, this is going to be your last United flight. And the vast majority of customers put their masks on. So we have not seen some of that level of stress that's happened on some of other, other airlines. >> That's key. Cause it's been pretty rampant. But the fact that you're, you're making things much more accessible. And in real time, I think another thing we learned during the pandemic is that real time is no longer a nice to have. It's essential. We have this expectation as consumers, whether we're flying or we're buying something from an online retailer that we're going to be able to get whatever we want in the palm of our hand. >> Yeah. Well, you know what we like to say, we're very proud of our mobile app. We're very proud of it. But we like to say that are not comparing our mobile app to another airline mobile app. You're, you're comparing it to the last app you probably used. And that might've been the Amazon app. So we have to be as good as the Amazon app, but we have a lot of legacy technology behind it. And so we have really focused on that. >> Good, I want to ask you cause you're a Chief Digital Officer, because this comes up in a lot of our CUBE conversations and around the digital side is that obviously with the virtual now hybrid things, new innovations have happened. So I have to ask you what's changed for the better that's going to be around and what might not be around that you've learned from the pandemic, because these new things are emerging. New standards, new protocols, new digital experiences. What have you learned that's going to stay around and what kind of went away? >> Yeah. >> Well, I think nothing tells you about how important your customers are if you're standing in the middle of O'Hare and not seeing any. And that's what happened in April of 2020, when we actually, there was a day that year, that month that we had more pilots than passengers. It was just, you know, so you realize it's really all about the customer. And what we have to do is make sure that customers choose us. There might be less reasons to fly to certain places all the time, but when you do fly, we want you to pick United. And so it's got to be more than just where we fly. It's got to be the experiences you have with the people. And we have to use the technology to make it easier. I mean, Touchless, wasn't really a thing. QR codes are back. I mean, they were gone, right. And we have QR codes on everything now. Cause you want to get through that airport without having to touch anything, and you do that with your mobile app. >> Yeah. Great innovations. >> It is a great innovation. That contact list is key. You talk about QR cuts coming back. And just some of the things that we've, that we've, some of the silver linings and frankly there have been some the last 22 months or so, but being able to have that experience, that's tailored to me as a consumer. >> Right. I don't need to know what's under the hood enabling it. I just know I want to be able to make transactions or find whatever I need to in the palm of my hand, 24/7. >> Yeah. And you know, for airlines, it usually comes back to something went wrong and frankly, there's always something that going quite right. There's a, there's a weather delay somewhere or maybe your bag didn't get on the same flight you did. And so we want to give you transparency in that and control over what you can do. And so how make it, make it easier to rebook, make you understand what the situation is, be very transparent about it. And we even have something called Connection Saver. And what we do with that is we actually use real time data analytics. And what we do is we say, there's a person that's arriving late. And then we say with real-time weather, real-time connection data. We say, can we hold that flight for Lisa? And we, and we, yeah.(laughing) The worst thing is when that door closed, you run all the way through the airport and they closed the door. Right? We don't want to do, gate agents don't like doing that either. And so we use calculations that say, you know, the wind is blowing in the right direction. The pilots can make up the time. There isn't anybody on the other side, that's going to miss a connection. And so about 2000 times a day, we hold a connection for our customer. >> That's key. If you missed, sometimes just stay overnight. If you miss that connection. >> Especially on the last flight of the day we'll be, we'll be very generous because that doesn't do anybody any good. >> Well, great, great story. I love the keynote, Cloud has changed. I have to ask you this year at re:Invent, what's your observation on the Cloud as the cloud continues to expand, as Adam is talking about, how do you guys see the Cloud evolving for United? >> Well, you know, I, I think what's really impressive here is everybody is coming from every industry. It's not one or two industries that are here, are early adopters in the industry. It really is what you have to do to survive. But I probably would be remiss not to say that, which was really great was that there were two women on the, on the keynote stage and two men. So we were at 50 50 now there are 51% women in the world, but we'll take it. And I, in all seriousness, I do think that there is, there's a lot more diversity here and I think that's good. Not just for AWS. That's good for everybody. >> I couldn't agree more. That was one of the first things I noticed this morning when you took the keynote stage was a strong female leader before you even started telling the story. And that's something from an optics perspective. I know that Amazon is really keen on, but it's nice to hear from your perspective as well that there's, there's that diversity. There's also that thought diversity when you have different perspectives come into play because there's so many dynamics going on these days. But I have to ask you one question. We know we talked to, we, we, we talk about every company, these days being a data company, being a digital company needing to be, to be competitive. >> Right. Do you think of United, should, should we be thinking about United as a digital first company? >> Well, we, we, we connect people, right? And so we are physically moving people from one destination to another and they really want to get there. So we're not going to always be digital, but I would tell you that I often speak with our Chief Customer Officer and our Chief Operating Officer. And it's really hard for us to talk about anything without talking about technology or how it impacts the operation or how it impacts our customer. It's really, really meshing together for sure. >> Great stuff, Linda, thanks for coming on theCUBE. Really appreciate it. United Airlines, Chief Digital Officer on the main stage here at re:Invent and now on theCUBE. I'm John Furrier, Lisa Martin. You're watching theCUBE, the tech leader in event coverage. Thanks for watching. (upbeat music)

(upbeat music) >> Hello and welcome today's session for the AWS Startup Showcase, the next big thing in AI, Security and Life Sciences featuring Coralogix for the AI track. I'm your host, John Furrier with theCUBE. We're here we're joined by Ariel Assaraf, CEO of Coralogix. Ariel, great to see you calling in from remotely, videoing in from Tel Aviv. Thanks for coming on theCUBE. >> Thank you very much, John. Great to be here. >> So you guys are features a hot next thing, start next big thing startup. And one of the things that you guys do we've been covering for many years is, you're into the log analytics, from a data perspective, you guys decouple the analytics from the storage. This is a unique thing. Tell us about it. What's the story? >> Yeah. So what we've seen in the market is that probably because of the great job that a lot of the earlier generation products have done, more and more companies see the value in log data, what used to be like a couple rows, that you add, whenever you have something very important to say, became a standard to document all communication between different components, infrastructure, network, monitoring, and the application layer, of course. And what happens is that data grows extremely fast, all data grows fast, but log data grows even faster. What we always say is that for sure data grows faster than revenue. So as fast as a company grows, its data is going to outpace that. And so we found ourselves thinking, how can we help companies be able to still get the full coverage they want without cherry picking data or deciding exactly what they want to monitor and what they're taking risk with. But still give them the real time analysis that they need to make sure that they get the full insight suite for the entire data, wherever it comes from. And that's why we decided to decouple the analytics layer from storage. So instead of ingesting the data, then indexing and storing it, and then analyzing the stored data, we analyze everything, and then we only store it matters. So we go from the insights backwards. That allowed us to reduce the amount of data, reduce the digital exhaust that it creates, and also provide better insights. So the idea is that as this world of data scales, the need for real time streaming analytics is going to increase. >> So what's interesting is we've seen this decoupling with storage and compute be a great success formula and cloud scale, for instance, that's a known best practice. You're taking a little bit different. I love how you're coming backwards from it, you're working backwards from the insights, almost doing some intelligence on the front end of the data, probably sees a lot of storage costs. But I want to get specifically back to this real time. How do you do that? And how did you come up with this? What's the vision? How did you guys come up with the idea? What was the magic light bulb that went off for Coralogix? >> Yes, the Coralogix story is very interesting. Actually, it was no light bulb, it was a road of pain for years and years, we started by just you know, doing the same, maybe faster, a couple more features. And it didn't work out too well. The first few years, the company were not very successful. And we've grown tremendously in the past three years, almost 100X, since we've launched this, and it came from a pain. So once we started scaling, we saw that the side effects of accessing the storage for analytics, the latency it creates, the the dependency on schema, the price that it poses on our customers became unbearable. And then we started thinking, so okay, how do we get the same level of insights, because there's this perception in the world of storage. And now it started to happen in analytics, also, that talks about tiers. So you want to get a great experience, you pay a lot, you want to get a less than great experience, you pay less, it's a lower tier. And we decided that we're looking for a way to give the same level of real time analytics and the same level of insights. Only without the issue of dependencies, decoupling all the storage schema issues and latency. And we built our real time pipeline, we call it Streama. Streama is a Coralogix real time analysis platform that analyzes everything in real time, also the stateful thing. So stateless analytics in real time is something that's been done in the past and it always worked well. The issue is, how do you give a stateful insight on data that you analyze in real time without storing and I'll explain how can you tell that a certain issue happened that did not happen in the past three months if you did not store the past three months? Or how can you tell that behavior is abnormal if you did not store what's normal, you did not store to state. So we created what we call the state store that holds the state of the system, the state of data, were a snapshot on that state for the entire history. And then instead of our state being the storage, so you know, you asked me, how is this compared to last week? Instead of me going to the storage and compare last week, I go to the state store, and you know, like a record bag, I just scroll fast, I find out one piece of state. And I say, okay, this is how it looked like last week, compared to this week, it changed in ABC. And once we started doing that we on boarded more and more services to that model. And our customers came in and say, hey, you're doing everything in real time. We don't need more than that. Yeah, like a very small portion of data, we actually need to store and frequently search, how about you guys fit into our use cases, and not just sell on quota? And we decided to basically allow our customers to choose what is the use case that they have, and route the data through different use cases. And then each log records, each log record stops at the relevant stops in our data pipeline based on the use case. So just like you wouldn't walk into the supermarket, you fill in a bag, you go out, they weigh it and they say, you know, it's two kilograms, you pay this amount, because different products have different costs and different meaning to you. That same way, exactly, We analyze the data in real time. So we know the importance of data, and we allow you to route it based on your use case and pay a different amount per use case. >> So this is really interesting. So essentially, you guys, essentially capture insights and store those, you call them states, and then not have to go through the data. So it's like you're eliminating the old problem of, you know, going back to the index and recovering the data to get the insights, did we have that? So anyway, it's a round trip query, if you will, you guys are start saving all that data mining cost and time. >> We call it node zero side effects, that round trip that you that you described is exactly it, no side effects to an analysis that is done in real time. I don't need to get the latency from the storage, a bit of latency from the database that holds the model, a bit of latency from the cache, everything stays in memory, everything stays in stream. >> And so basically, it's like the definition of insanity, doing the same thing over and over again and expecting a different result. Here, that's kind of what that is, the old model of insight is go query the database and get something back, you're actually doing the real time filtering on the front end, capturing the insights, if you will, storing those and replicating that as use case. Is that right? >> Exactly. But then, you know, there's still the issue of customer saying, yeah, but I need that data. Someday, I need to really frequently search, I don't know, you know, the unknown unknowns, or some of the day I need for compliance, and I need an immutable record that stays in my compliance bucket forever. So we allowed customers, we have this some that screen, we call the TCO optimizer, that allows them to define those use cases. And they can always access the data by creating their remote storage from Coralogix, or carrying the hot data that is stored with Coralogix. So it's all about use cases. And it's all about how you consume the data because it doesn't make sense for me to pay the same amount or give the same amount of attention to a record that is completely useless. It's just there for the record or for a compliance audit, that may or may not happen in the future. And, you know, do the same with the most critical exception in my application log that has immediate business impact. >> What's really good too, is you can actually set some policy up if you want a certain use cases, okay, store that data. So it's not to say you don't want to store it, but you might want to store it on certain use cases. So I can see that. So I got to ask the question. So how does this differ from the competition? How do you guys compete? Take us through a use case of a customer? How do you guys go to the customer and you just say, hey, we got so much scar tissue from this, we learned the hard way, take it from us? How does it go? Take us through an example. >> So an interesting example of actually a company that is not the your typical early adopter, let's call it this way. A very advanced in technology and smart company, but a huge one, one of the largest telecommunications company in India. And they were actually cherry picking about 100 gigs of data per day, and sending it to one of the legacy providers which has a great solution that does give value. But they weren't even thinking about sending their entire data set because of cost because of scale, because of, you know, just a clutter. Whenever you search, you have to sift through millions of records that many of them are not that important. And we help them actually ask analyze their data and work with them to understand these guys had over a terabyte of data that had incredible insights, it was like a goldmine of insights. But now you just needed to prioritize it by their use case, and they went from 100 gig with the other legacy solution to a terabyte, at almost the same cost, with more advanced insights within one week, which isn't in that scale of an organization is something that is is out of the ordinary, took them four months to implement the other product. But now, when you go from the insights backwards, you understand your data before you have to store it, you understand the data before you have to analyze it, or before you have to manually sift through it. So if you ask about the difference, it's all about the architecture. We analyze and only then index instead of indexing and then analyzing. It sounds simple. But of course, when you look at this stateful analytics, it's a lot more, a lot more complex. >> Take me through your growth story, because first of all, I'll get back to the secret sauce in the same way. I want to get back to how you guys got here. (indistinct) you had this problem? You kind of broke through, you hit the magic formula, talking about the growth? Where's the growth coming from? And what's the real impact? What's the situation relative to the company's growth? >> Yeah, so we had a first rough three years that I kind of mentioned, and then I was not the CEO at the beginning, I'm one of the co founders. I'm more of the technical guy, was the product manager. And I became CEO after the company was kind of on the verge of closing at the end of 2017. And the CTO left the CEO left, the VP of R&D became the CTO, I became the CEO, we were five people with $200,000 in the bank that you know, you know that that's not a long runway. And we kind of changed attitudes. So we kind of, so we first we launched this product, and then we understood that we need to go bottoms up, you can go to enterprises and try to sell something that is out of the ordinary, or that changes how they're used to working or just, you know, sell something, (indistinct) five people will do under $1,000 in the bank. So we started going from bottoms up, and the earlier adopters. And it's still until today, you know, the the more advanced companies, the more advanced teams. This is our Gartner friend Coralogix, the preferred solution for Advanced, DevOps and Platform Teams. So they started adopting Coralogix, and then it grew to the larger organization, and they were actually pushing, there are champions within their organizations. And ever since. So until the beginning of 2018, we raised about $2 million and had sales or marginal. Today, we have over 1500, pink accounts, and we raised almost $100 million more. >> Wow, what a great pivot. That was great example of kind of getting the right wave here, cloud wave. You said in terms of customers, you had the DevOps kind of (indistinct) initially. And now you said expanded out to a lot more traditional enterprise, you can take me through the customer profile. >> Yeah, so I'd say it's still the core would be cloud native and (indistinct) companies. These are typical ones, we have very tight integration with AWS, all the services, all the integrations required, we know how to read and write back to the different services and analysis platforms in AWS. Also for Asia and GCP, but mostly AWS. And then we do have quite a few big enterprise accounts, actually, five of the largest 50 companies in the world use Coralogix today. And it grew from those DevOps and platform evangelists into the level of IT, execs and even (indistinct). So today, we have our security product that already sells to some of the biggest companies in the world, it's a different profile. And the idea for us is that, you know, once you solve that issue of too much data, too expensive, not proactive enough, too couple with the storage, you can actually expand that from observability logging metrics, now into tracing and then into security and maybe even to other fields, where the cost and the productivity are an issue for many companies. >> So let me ask you this question, then Ariel, if you don't mind. So if a customer has a need for Coralogix, is it because the data fall? Or they just got data kind of sprawled all over the place? Or is it that storage costs are going up on S3 or what's some of the signaling that you would see, that would be like, telling you, okay, okay, what's the opportunity to come in and either clean house or fix the mess or whatnot, Take us through what you see. What do you see is the trend? >> Yeah. So like the tip customer (indistinct) Coralogix will be someone using one of the legacy solution and growing very fast. That's the easiest way for us to know. >> What grows fast? The storage, the storage is growing fast? >> The company is growing fast. >> Okay. And you remember, the data grows faster than revenue. And we know that. So if I see a company that grew from, you know, 50 people to 500, in three years, specifically, if it's cloud native or internet company, I know that their data grew not 10X, but 100X. So I know that that company that might started with a legacy solution at like, you know, $1,000 a month, and they're happy with it. And you know, for $1,000 a month, if you don't have a lot of data, those legacy solutions, you know, they'll do the trick. But now I know that they're going to get asked to pay 50, 60, $70,000 a month. And this is exactly where we kick in. Because now, when it doesn't fit the economic model, when it doesn't fit the unit economics, and he started damaging the margins of those companies. Because remember, those internet and cloud companies, it's not costs are not the classic costs that you'll see in an enterprise, they're actually damaging your unit economics and the valuation of the business, the bigger deal. So now, when I see that type of organization, we come in and say, hey, better coverage, more advanced analytics, easier integration within your organization, we support all the common open source syntaxes, and dashboards, you can plug it into your entire environment, and the costs are going to be a quarter of whatever you're paying today. So once they see that they see, you know, the Dev friendliness of the product, the ease of scale, the stability of the product, it makes a lot more sense for them to engage in a PLC, because at the end of the day, if you don't prove value, you know, you can come with 90% discount, it doesn't do anything, not to prove the value to them. So it's a great door opener. But from then on, you know, it's a PLC like any other. >> Cloud is all about the PLC or pilot, as they say. So take me through the product, today, and what's next for the product, take us through the vision of the product and the product strategy. >> Yeah, so today, the product allows you to send any log data, metric data or security information, analyze it a million ways, we have one of the most extensive alerting mechanism to market, automatic anomaly detection, data flustering. And all the real law, you know, the real time pipeline, things that help companies make their data smarter, and more readable, parsing, enriching, getting external sources to enrich the data, and so on, so forth. Where we're stepping in now is actually to make the final step of decoupling the analytics from storage, what we call the datalist data platform in which no data will sit or reside within the Coralogix cloud, everything will be analyzed in real time, stored in a storage of choice of our customers, then we'll allow our customers to remotely query that incredible performance. So that'll bring our customers away, to have the first ever true SaaS experience for observability. Think about no quota plans, no retention, you send whatever you want, you pay only for what you send, you retain it, how long you want to retain it, and you get all the real time insights much, much faster than any other product that keeps it on a hot storage. So that'll be our next step to really make sure that, you know, we're kind of not reselling cloud storage, because a lot of the times when you are dependent on storage, and you know, we're a cloud company, like I mentioned, you got to keep your unit economics. So what do you do? You sell storage to the customer, you add your markup, and then you you charge for it. And this is exactly where we don't want to be. We want to sell the intelligence and the insights and the real time analysis that we know how to do and let the customers enjoy the, you know, the wealth of opportunities and choices their cloud providers offer for storage. >> That's great vision in a way, the hyper scalars early days showed that decoupling compute from storage, which I mentioned earlier, was a huge category creation. Here, you're doing it for data. We call hyper data scale, or like, maybe there's got to be a name for this. What do you see, about five years from now? Take us through the trajectory of the next five years, because certainly observability is not going away. I mean, it's data management, monitoring, real time, asynchronous, synchronous, linear, all the stuffs happening, what's the what's the five year vision? >> Now add security and observability, which is something we started preaching for, because no one can say I have observability to my environment when people you know, come in and out and steal data. That's no observability. But the thing is that because data grows exponentially, because it grows faster than revenue what we believe is that in five years, there's not going to be a choice, everyone are going to have to analyze the data in real time. Extract the insights and then decide whether to store it on a you know long term archive or not, or not store it at all. You still want to get the full coverage and insights. But you know, when you think about observability, unlike many other things, the more data you have many times, the less observability you get. So you think of log data unlike statistics, if my system was only in recording everything was only generating 10 records a day, I have full, incredible observability I know everything that I've done. what happens is that you pay more, you get less observability, and more uncertainty. So I think that you know, with time, we'll start seeing more and more real time streaming analytics, and a lot less storage based and index based solutions. >> You know, Ariel, I've always been saying to Dave Vellante on theCUBE, many times that there needs to be insights as to be the norm, not the exception, where, and then ultimately, it would be a database of insights. I mean, at the end of the day, the insights become more plentiful. You have the ability to actually store those insights, and refresh them and challenge them and model update them, verify them, either sunset them or add to them or you know, saying that's like, when you start getting more data into your organization, AI and machine learning prove that pattern recognition works. So why not grab those insights? >> And use them as your baseline to know what's important, and not have to start by putting everything in a bucket. >> So we're going to have new categories like insight, first, software (indistinct) >> Go from insights backwards, that'll be my tagline, if I have to, but I'm a terrible marketing (indistinct). >> Yeah, well, I mean, everyone's like cloud, first data, data is data driven, insight driven, what you're basically doing is you're moving into the world of insights driven analytics, really, as a way to kind of bring that forward. So congratulations. Great story. I love the pivot love how you guys entrepreneurially put it all together and had the problem your own problem and brought it out and to the to the rest of the world. And certainly DevOps in the cloud scale wave is just getting bigger and bigger and taking over the enterprise. So great stuff. Real quick while you're here. Give a quick plug for the company. What you guys are up to, stats, vitals, hiring, what's new, give the commercial. >> Yeah, so like mentioned over 1500 being customers growing incredibly in the past 24 months, hiring, almost doubling the company in the next few months. offices in Israel, East Center, West US, and UK and Mumbai. Looking for talented engineers to join the journey and build the next generation of data lists data platforms. >> Ariel Assaraf, CEO of Coralogix. Great to have you on theCUBE and thank you for participating in the AI track for our next big thing in the Startup Showcase. Thanks for coming on. >> Thank you very much John, really enjoyed it. >> Okay, I'm John Furrier with theCUBE. Thank you for watching the AWS Startup Showcase presented by theCUBE. (calm music)