(light airy music) >> Hello, everyone, welcome to theCUBE's presentation of the AWS Startup Showcase, AI and machine learning. "Top Startups Building Generative AI on AWS." This is season three, episode one of the ongoing series covering the exciting startups from the AWS ecosystem, talking about AI machine learning. We have three great guests Bratin Saha, VP, Vice President of Machine Learning and AI Services at Amazon Web Services. Tom Mason, the CTO of Stability AI, and Aidan Gomez, CEO and co-founder of Cohere. Two practitioners doing startups and AWS. Gentlemen, thank you for opening up this session, this episode. Thanks for coming on. >> Thank you. >> Thank you. >> Thank you. >> So the topic is hype versus reality. So I think we're all on the reality is great, hype is great, but the reality's here. I want to get into it. Generative AI's got all the momentum, it's going mainstream, it's kind of come out of the behind the ropes, it's now mainstream. We saw the success of ChatGPT, opens up everyone's eyes, but there's so much more going on. Let's jump in and get your early perspectives on what should people be talking about right now? What are you guys working on? We'll start with AWS. What's the big focus right now for you guys as you come into this market that's highly active, highly hyped up, but people see value right out of the gate? >> You know, we have been working on generative AI for some time. In fact, last year we released Code Whisperer, which is about using generative AI for software development and a number of customers are using it and getting real value out of it. So generative AI is now something that's mainstream that can be used by enterprise users. And we have also been partnering with a number of other companies. So, you know, stability.ai, we've been partnering with them a lot. We want to be partnering with other companies as well. In seeing how we do three things, you know, first is providing the most efficient infrastructure for generative AI. And that is where, you know, things like Trainium, things like Inferentia, things like SageMaker come in. And then next is the set of models and then the third is the kind of applications like Code Whisperer and so on. So, you know, it's early days yet, but clearly there's a lot of amazing capabilities that will come out and something that, you know, our customers are starting to pay a lot of attention to. >> Tom, talk about your company and what your focus is and why the Amazon Web Services relationship's important for you? >> So yeah, we're primarily committed to making incredible open source foundation models and obviously stable effusions been our kind of first big model there, which we trained all on AWS. We've been working with them over the last year and a half to develop, obviously a big cluster, and bring all that compute to training these models at scale, which has been a really successful partnership. And we're excited to take it further this year as we develop commercial strategy of the business and build out, you know, the ability for enterprise customers to come and get all the value from these models that we think they can get. So we're really excited about the future. We got hugely exciting pipeline for this year with new modalities and video models and wonderful things and trying to solve images for once and for all and get the kind of general value and value proposition correct for customers. So it's a really exciting time and very honored to be part of it. >> It's great to see some of your customers doing so well out there. Congratulations to your team. Appreciate that. Aidan, let's get into what you guys do. What does Cohere do? What are you excited about right now? >> Yeah, so Cohere builds large language models, which are the backbone of applications like ChatGPT and GPT-3. We're extremely focused on solving the issues with adoption for enterprise. So it's great that you can make a super flashy demo for consumers, but it takes a lot to actually get it into billion user products and large global enterprises. So about six months ago, we released our command models, which are some of the best that exist for large language models. And in December, we released our multilingual text understanding models and that's on over a hundred different languages and it's trained on, you know, authentic data directly from native speakers. And so we're super excited to continue pushing this into enterprise and solving those barriers for adoption, making this transformation a reality. >> Just real quick, while I got you there on the new products coming out. Where are we in the progress? People see some of the new stuff out there right now. There's so much more headroom. Can you just scope out in your mind what that looks like? Like from a headroom standpoint? Okay, we see ChatGPT. "Oh yeah, it writes my papers for me, does some homework for me." I mean okay, yawn, maybe people say that, (Aidan chuckles) people excited or people are blown away. I mean, it's helped theCUBE out, it helps me, you know, feed up a little bit from my write-ups but it's not always perfect. >> Yeah, at the moment it's like a writing assistant, right? And it's still super early in the technologies trajectory. I think it's fascinating and it's interesting but its impact is still really limited. I think in the next year, like within the next eight months, we're going to see some major changes. You've already seen the very first hints of that with stuff like Bing Chat, where you augment these dialogue models with an external knowledge base. So now the models can be kept up to date to the millisecond, right? Because they can search the web and they can see events that happened a millisecond ago. But that's still limited in the sense that when you ask the question, what can these models actually do? Well they can just write text back at you. That's the extent of what they can do. And so the real project, the real effort, that I think we're all working towards is actually taking action. So what happens when you give these models the ability to use tools, to use APIs? What can they do when they can actually affect change out in the real world, beyond just streaming text back at the user? I think that's the really exciting piece. >> Okay, so I wanted to tee that up early in the segment 'cause I want to get into the customer applications. We're seeing early adopters come in, using the technology because they have a lot of data, they have a lot of large language model opportunities and then there's a big fast follower wave coming behind it. I call that the people who are going to jump in the pool early and get into it. They might not be advanced. Can you guys share what customer applications are being used with large language and vision models today and how they're using it to transform on the early adopter side, and how is that a tell sign of what's to come? >> You know, one of the things we have been seeing both with the text models that Aidan talked about as well as the vision models that stability.ai does, Tom, is customers are really using it to change the way you interact with information. You know, one example of a customer that we have, is someone who's kind of using that to query customer conversations and ask questions like, you know, "What was the customer issue? How did we solve it?" And trying to get those kinds of insights that was previously much harder to do. And then of course software is a big area. You know, generating software, making that, you know, just deploying it in production. Those have been really big areas that we have seen customers start to do. You know, looking at documentation, like instead of you know, searching for stuff and so on, you know, you just have an interactive way, in which you can just look at the documentation for a product. You know, all of this goes to where we need to take the technology. One of which is, you know, the models have to be there but they have to work reliably in a production setting at scale, with privacy, with security, and you know, making sure all of this is happening, is going to be really key. That is what, you know, we at AWS are looking to do, which is work with partners like stability and others and in the open source and really take all of these and make them available at scale to customers, where they work reliably. >> Tom, Aidan, what's your thoughts on this? Where are customers landing on this first use cases or set of low-hanging fruit use cases or applications? >> Yeah, so I think like the first group of adopters that really found product market fit were the copywriting companies. So one great example of that is HyperWrite. Another one is Jasper. And so for Cohere, that's the tip of the iceberg, like there's a very long tail of usage from a bunch of different applications. HyperWrite is one of our customers, they help beat writer's block by drafting blog posts, emails, and marketing copy. We also have a global audio streaming platform, which is using us the power of search engine that can comb through podcast transcripts, in a bunch of different languages. Then a global apparel brand, which is using us to transform how they interact with their customers through a virtual assistant, two dozen global news outlets who are using us for news summarization. So really like, these large language models, they can be deployed all over the place into every single industry sector, language is everywhere. It's hard to think of any company on Earth that doesn't use language. So it's, very, very- >> We're doing it right now. We got the language coming in. >> Exactly. >> We'll transcribe this puppy. All right. Tom, on your side, what do you see the- >> Yeah, we're seeing some amazing applications of it and you know, I guess that's partly been, because of the growth in the open source community and some of these applications have come from there that are then triggering this secondary wave of innovation, which is coming a lot from, you know, controllability and explainability of the model. But we've got companies like, you know, Jasper, which Aidan mentioned, who are using stable diffusion for image generation in block creation, content creation. We've got Lensa, you know, which exploded, and is built on top of stable diffusion for fine tuning so people can bring themselves and their pets and you know, everything into the models. So we've now got fine tuned stable diffusion at scale, which is democratized, you know, that process, which is really fun to see your Lensa, you know, exploded. You know, I think it was the largest growing app in the App Store at one point. And lots of other examples like NightCafe and Lexica and Playground. So seeing lots of cool applications. >> So much applications, we'll probably be a customer for all you guys. We'll definitely talk after. But the challenges are there for people adopting, they want to get into what you guys see as the challenges that turn into opportunities. How do you see the customers adopting generative AI applications? For example, we have massive amounts of transcripts, timed up to all the videos. I don't even know what to do. Do I just, do I code my API there. So, everyone has this problem, every vertical has these use cases. What are the challenges for people getting into this and adopting these applications? Is it figuring out what to do first? Or is it a technical setup? Do they stand up stuff, they just go to Amazon? What do you guys see as the challenges? >> I think, you know, the first thing is coming up with where you think you're going to reimagine your customer experience by using generative AI. You know, we talked about Ada, and Tom talked about a number of these ones and you know, you pick up one or two of these, to get that robust. And then once you have them, you know, we have models and we'll have more models on AWS, these large language models that Aidan was talking about. Then you go in and start using these models and testing them out and seeing whether they fit in use case or not. In many situations, like you said, John, our customers want to say, "You know, I know you've trained these models on a lot of publicly available data, but I want to be able to customize it for my use cases. Because, you know, there's some knowledge that I have created and I want to be able to use that." And then in many cases, and I think Aidan mentioned this. You know, you need these models to be up to date. Like you can't have it staying. And in those cases, you augmented with a knowledge base, you know you have to make sure that these models are not hallucinating. And so you need to be able to do the right kind of responsible AI checks. So, you know, you start with a particular use case, and there are a lot of them. Then, you know, you can come to AWS, and then look at one of the many models we have and you know, we are going to have more models for other modalities as well. And then, you know, play around with the models. We have a playground kind of thing where you can test these models on some data and then you can probably, you will probably want to bring your own data, customize it to your own needs, do some of the testing to make sure that the model is giving the right output and then just deploy it. And you know, we have a lot of tools. >> Yeah. >> To make this easy for our customers. >> How should people think about large language models? Because do they think about it as something that they tap into with their IP or their data? Or is it a large language model that they apply into their system? Is the interface that way? What's the interaction look like? >> In many situations, you can use these models out of the box. But in typical, in most of the other situations, you will want to customize it with your own data or with your own expectations. So the typical use case would be, you know, these are models are exposed through APIs. So the typical use case would be, you know you're using these APIs a little bit for testing and getting familiar and then there will be an API that will allow you to train this model further on your data. So you use that AI, you know, make sure you augmented the knowledge base. So then you use those APIs to customize the model and then just deploy it in an application. You know, like Tom was mentioning, a number of companies that are using these models. So once you have it, then you know, you again, use an endpoint API and use it in an application. >> All right, I love the example. I want to ask Tom and Aidan, because like most my experience with Amazon Web Service in 2007, I would stand up in EC2, put my code on there, play around, if it didn't work out, I'd shut it down. Is that a similar dynamic we're going to see with the machine learning where developers just kind of log in and stand up infrastructure and play around and then have a cloud-like experience? >> So I can go first. So I mean, we obviously, with AWS working really closely with the SageMaker team, do fantastic platform there for ML training and inference. And you know, going back to your point earlier, you know, where the data is, is hugely important for companies. Many companies bringing their models to their data in AWS on-premise for them is hugely important. Having the models to be, you know, open sources, makes them explainable and transparent to the adopters of those models. So, you know, we are really excited to work with the SageMaker team over the coming year to bring companies to that platform and make the most of our models. >> Aidan, what's your take on developers? Do they just need to have a team in place, if we want to interface with you guys? Let's say, can they start learning? What do they got to do to set up? >> Yeah, so I think for Cohere, our product makes it much, much easier to people, for people to get started and start building, it solves a lot of the productionization problems. But of course with SageMaker, like Tom was saying, I think that lowers a barrier even further because it solves problems like data privacy. So I want to underline what Bratin was saying earlier around when you're fine tuning or when you're using these models, you don't want your data being incorporated into someone else's model. You don't want it being used for training elsewhere. And so the ability to solve for enterprises, that data privacy and that security guarantee has been hugely important for Cohere, and that's very easy to do through SageMaker. >> Yeah. >> But the barriers for using this technology are coming down super quickly. And so for developers, it's just becoming completely intuitive. I love this, there's this quote from Andrej Karpathy. He was saying like, "It really wasn't on my 2022 list of things to happen that English would become, you know, the most popular programming language." And so the barrier is coming down- >> Yeah. >> Super quickly and it's exciting to see. >> It's going to be awesome for all the companies here, and then we'll do more, we're probably going to see explosion of startups, already seeing that, the maps, ecosystem maps, the landscape maps are happening. So this is happening and I'm convinced it's not yesterday's chat bot, it's not yesterday's AI Ops. It's a whole another ballgame. So I have to ask you guys for the final question before we kick off the company's showcasing here. How do you guys gauge success of generative AI applications? Is there a lens to look through and say, okay, how do I see success? It could be just getting a win or is it a bigger picture? Bratin we'll start with you. How do you gauge success for generative AI? >> You know, ultimately it's about bringing business value to our customers. And making sure that those customers are able to reimagine their experiences by using generative AI. Now the way to get their ease, of course to deploy those models in a safe, effective manner, and ensuring that all of the robustness and the security guarantees and the privacy guarantees are all there. And we want to make sure that this transitions from something that's great demos to actual at scale products, which means making them work reliably all of the time not just some of the time. >> Tom, what's your gauge for success? >> Look, I think this, we're seeing a completely new form of ways to interact with data, to make data intelligent, and directly to bring in new revenue streams into business. So if businesses can use our models to leverage that and generate completely new revenue streams and ultimately bring incredible new value to their customers, then that's fantastic. And we hope we can power that revolution. >> Aidan, what's your take? >> Yeah, reiterating Bratin and Tom's point, I think that value in the enterprise and value in market is like a huge, you know, it's the goal that we're striving towards. I also think that, you know, the value to consumers and actual users and the transformation of the surface area of technology to create experiences like ChatGPT that are magical and it's the first time in human history we've been able to talk to something compelling that's not a human. I think that in itself is just extraordinary and so exciting to see. >> It really brings up a whole another category of markets. B2B, B2C, it's B2D, business to developer. Because I think this is kind of the big trend the consumers have to win. The developers coding the apps, it's a whole another sea change. Reminds me everyone use the "Moneyball" movie as example during the big data wave. Then you know, the value of data. There's a scene in "Moneyball" at the end, where Billy Beane's getting the offer from the Red Sox, then the owner says to the Red Sox, "If every team's not rebuilding their teams based upon your model, there'll be dinosaurs." I think that's the same with AI here. Every company will have to need to think about their business model and how they operate with AI. So it'll be a great run. >> Completely Agree >> It'll be a great run. >> Yeah. >> Aidan, Tom, thank you so much for sharing about your experiences at your companies and congratulations on your success and it's just the beginning. And Bratin, thanks for coming on representing AWS. And thank you, appreciate for what you do. Thank you. >> Thank you, John. Thank you, Aidan. >> Thank you John. >> Thanks so much. >> Okay, let's kick off season three, episode one. I'm John Furrier, your host. Thanks for watching. (light airy music)

(gentle music) >> Welcome back to our coverage here on theCUBE of AWS re:Invent 22. We are on day three, starting to wind down, but still a lot of exciting topics to cover here on the AWS Global Showcase, part of the startup program there at AWS. Joining us now, two representatives from LTI Mindtree. You say LTI Mindtree? I thought they were two different companies. Well, they're actually one and the same. Been together just a mere two weeks now. We'll hear more about that from Sid Bohra, who is the Chief Business Officer at LTI Mindtree and Ashish Varerkar, who is the Vice President of Cloud Success at LTI Mindtree. Gentlemen, thanks for being with us here on theCUBE. >> Pleasures all ours. >> Thank you. >> And congratulations. So two weeks in the making in its infancy, still in the honeymoon period, but how's the two weeks been? Everything all right? >> Well, two weeks have been very exciting. >> I'll bet. >> Well, I would say the period prior to that was just as exciting as you can imagine. >> John: Oh, sure. And we are super excited about what the future holds for this company because we truly believe that we have a remarkable opportunity to create value for our clients as one company. >> Well let's talk about LTI Mind tree then a little bit. Ashish, I'll let you carry the ball on this. Tell us about your services, about your core focus, and about those opportunities that Siddharth was just telling us about. >> So I think with the two companies coming together, we have a larger opportunity to like go to market with our end to end business transformation services and leveraging cloud platforms, right? So, and that's what we do. My responsibility particularly is to see to it that what customers are deploying on cloud is aligned to their business outcomes and then take it forward from there. >> Yeah, Vice President of Cloud Success, that gives you a lot of runway, right? Does it not? I mean, how do you define success in the cloud? Because there are a lot of different areas of complexity with which companies are dealing. >> So I think you would agree that in today's scenario, customers are not looking for a platform, right? But they're looking for a platform which can deliver business value. They're looking at business value and resiliency and then at the end, the cost, right? So if you're able to deliver these three things to the customer through the cloud implementation, I think that's success for us. >> Right. We've talked about transformation a lot this week and modernization, right, which is those are two pretty key buzzwords right now we're hearing a lot of. So when you see said, you know, companies come to you and they say, okay, it's time for us to make this commitment. Do they make it generally wholeheartedly? Is there still some trepidation of the unknown? Because there's a lot of, as we've said, complexity to this, it's multidimensional. We can go public, we can go hybrid, we can go multicloud. I mean, we got a lot of flavors. >> Yeah >> Absolutely. >> No, we see a spectrum. There are customers who are very early in the journey of getting onto cloud and are a little uncertain about what value they can get out of it. And on the other end of the spectrum, there are companies who are well into the journey who have understood what are the benefits of truly leveraging cloud who also understand what are the challenges they will face in getting onto the journey. So we get to meet a spectrum of customers, I would say. If you ask me where do bulk of them lie, I would say early in their journey. I would say there are only a handful who have that maturity where they can predict what's exactly going to happen on the cloud journey, what value they will accumulate through the process. So there's a lot of hand holding to be done, a lot of, you know, solving together to be done with our clients. >> You know, it is such a dynamic environment too, right? You have new opportunities that seem to be developed and released on a daily basis, almost, right? There's a large amount of flexibility, I would think, that has to be in place because where you think you're going to go today might not be where you wind up in six months. >> That's true. >> Is that fair? >> Absolutely fair. And I think from that perspective, if you look at the number of services that AWS provides, right? And what customers are looking for is how can they compose their business processes using this multiple services in a very seamless manner. And most of the announcements that we have seen during the re:Invent as well, they're talking about seamless connectivity between their services. They're talking about security, they're talking about creating a data fabric, the data zone that they announced. I think all these things put together, if you're able to kind of connect the dots and drive the business processes, I think that's what we want to do for our customers. >> And the value to AWS, it just can't be underscored enough I would assume, because there's comfort there, there's confidence there. When you bring that to the table as well along with your services, what kind of magnitude are we talking about here? What kind of force do you think? How would you characterize that? >> Well I think, you know, firstly, I would say that most of our engagements are not just services. Ashish and team and the company have invested heavily in building IP that we pair with our services so that we bring non-linearity and more, I would say, certainty to the outcomes that our customers get. And I can share some examples in the course of the conversation, but to answer your question in terms of magnitude, what we are collaborating with AWS on for our clients ranges from helping customers build more resiliency. And I'm talking about life sciences companies build more resiliency in the manufacturing R and D processes. That's so critical. It was even more critical during the pandemic times because we were working with some of the pharma companies who were contributing to the efforts in the pandemic. That's one end of the spectrum. On the other side, we are helping streaming companies and media companies digitize their supply chain, and their supply chains, the media supply chain, so that it is more effective, it's more efficient, it's more real time, again, using the power of the cloud. We are helping pharmaceutical companies drive far greater speed in the R and D processes. We are helping banking companies drive far more compliance in their anti-money laundering efforts and all of those things. So if you look at the magnitude, we judge the magnitude by the business impact that it's creating and we are very excited about what AWS, LTI Mindtree, and the customer are able to create in terms of those business impacts. >> And these are such major decisions. >> That's right. >> For a company, right, to make, and there are a number of factors that come into play here. What are you hearing from the C-Suite with regard to what weighs the most in their mind and is there, is it a matter of, you know, fear missing out? Or is it about trying to stay ahead of your competition, catching up the competition? I mean, generally speaking, you know, where are the, where's the C-Suite weighing in on this? >> I think in the current times, I think there is a certain level of adoption of cloud that's already happened in most enterprises. So most CIOs in the C-suite- >> They already get it. They already get it. >> They kind of get it, but I would say that they're very cagey about a bunch of things. They're very cagey about, am I going to end up spending too much for too little? Am I going to be able to deliver this transformation at the speed that I'm hoping to achieve? What about security? Compliance? What about the cost of running in the cloud? So those are some really important factors that sometimes end up slowing the cloud transformation journeys down because customers end up solving for them or not knowing for them. So while there is a decent amount of awareness about what cloud can do, there are some, a whole bunch of important factors that they continue to solve for as they go down that journey. >> And so what kind of tools do you provide them then? >> Primarily, what we do is, to Siddharth's point, right? So on one end, we want to see to it that we are doing the business transformation and all our cloud journeys start with a business North Star. So we align, we have doubled down on, say, five to six business domains. And for each of these business domains industries, we have created business North Star. For these business North Star, we define the use cases. And these use cases then get lit up through our platform. So what we have done is we have codified everything onto our platform. We call it Infinity. So primarily business processes from level one, level two, level three, level, and then the KPIs which are associated with these business processes, the technical KPIs and the business KPIs, and then tying it back to what you have deployed on cloud. So we have end to end cloud transformation journeys enabled for customers through the business North Star. >> And Infinity is your product. >> Can I add something? >> Please do. Yeah, please. >> Yeah so, you know, Ashish covered the part about demystifying if I were to do this particular cloud initiative, it's not just modernizing the application. This is about demystifying what business benefit will accrue to you. Very rare to find unless you do a very deep dive assessment. But what the platform we built also accelerates, you talked about modernization early in the conversation, accelerates the modernization process by automating a whole bunch of activities that are often manual. It bakes insecurity and compliance into everything it does. It automates a whole bunch of cloud operations including things like finops. So this is a life cycle platform that essentially codifies best practices so that you are not getting success by coincidence, you're getting success by design. So that's really what, that's really how we've approached the topic of realizing the true power of cloud by making sure that it's repeatedly delivered. >> Right. You know, I want to hit on security too because you brought that up just a few moments ago. Obviously, you know, we all, and I'd say we, we can do a better job, right? I mean, there's still problems, there's still challenges, there are a lot of bad actors out there that are staying ahead of the game. So as people come to you, clients come to you, and they raise these security concerns, what's your advice to them in terms of, you know, what kind of environment they're going into and what precautions or protections they can put in place to try to give themselves a little bit of peace of mind about how they're going to operate? >> You want to take it? >> So I think primarily, if you are going to cloud, you are going with an assumption that you are moving out of your firewalls, right? You're putting something out of your network area. So and from that perspective, the parameter security from the cloud perspective is very, very important. And then each and every service or the interactions between the services and what you integrate out of your organization, everything needs to be secured through the right guard rates. And we integrate all those things into our platform so that whatever new apps that get deployed or build or any cost product that gets deployed on cloud, everything is secure from a 360 degree perspective. So primarily, maintaining a good security posture, which on a hybrid cloud, I would not say only cloud, but extending your on-prem security posture to cloud is very, very important to when you go to implementing anything on could. >> If you had a crystal ball and we were sitting down here a year from now, you know, what do you think we'd be talking about with regard to, you know, developing these end-to-end opportunities that you are, what's the, I wouldn't say missing piece, but a piece that you would like to have refined to the point where you come back next year and say, John, guess what we did? Look what we were able to accomplish. Anything that you're looking at that you want to tackle here in 2023? Or is there some fine tuning somewhere that you think could even tighten your game even more than it is already? >> We have a long, long way to go, I would say. I think my core takeaway in terms of where the world of technology is headed because cloud is, you know, is essentially a component of what customers want to achieve. It's a medium through which they want to achieve. I think we live in a highly change oriented economy. Every industry is what I call getting re-platformed, right? New processes, new experiences, new products, new efficiency. So a year from now, and I can tell you even for few years from now, we would be constantly looking at our success in terms of how did cloud move the needle on releasing products faster? How did cloud move the needle on driving better experience and better consumer loyalty, for example. How did cloud move the needle on a more efficient supply chain? So increasingly, the technology metrics like, you know, keeping the lights on, or solving tickets, or releasing code on time, would move towards business metrics because that's really the ultimate goal of technology or cloud. So I would say that my crystal ball says we will increasingly be talking business language and business outcomes. Jeff Bezos is an incredible example, right? One of his annual letters, he connected everything back into how much time did consumers save by using Amazon. And I think that's really where in the world, that's the world we are headed towards. >> Ashish, any thoughts on that? >> I think Siddharth put it quite well. I would say if you are able to make a real business impact for our customers in next one year, helping them in driving some of their newer services on cloud through cloud, that would be a success factor for us. >> Well gentlemen, congratulations on the merger. I said two weeks. Still very much in the honeymoon phase and I'm sure it's going to go very well and I look forward to seeing you back here in a year. We'll sit down, same spot, let's remember, fifth floor, and we'll give it a shot and see how accurate you were on that. >> Absolutely. >> Wonderful. It's been a pleasure. >> Thank you gentlemen. >> Thank you for joining us. >> Thank you. >> Very good. Ashish, good to see you, sir. >> Thank you. >> A pleasure. We'll continue here. We're at the Venetian at AWS re:Invent 22, continue at the AWS Global Showcase startup. I'm John Walls. You're watching theCUBE, the leader in high tech coverage. (gentle music)

>>Welcome back to the Cube, as a continued coverage here from AWS Reinvent 22. It's day three of our coverage here at the Venetian in Las Vegas, and we're part of the AWS Global Startup Showcase. With me to talk about what Kong's to in that regard is Marco Palladino, who's the, the CTO and the co-founder of Con Marco. Good >>To see you. Well, thanks for having me >>Here. Yeah, I was gonna say, by the way, I, I, you've got a beautiful exhibit down on the show floor. How's the week been for you so far as an exhibitor here? >>It's been very busy. You know, to this year we made a big investment at the WS reinvent. You know, I think this is one of the best conferences in the industry. There is technology developers, but it's also business oriented. So you can learn about all the business outcomes that our, you know, customers or, you know, people are trying to make when, when adopting these new technologies. So it's very good so far. >>Good, good, good to hear. Alright, so in your world, the API world, you know, it used to be we had this, you know, giant elephant. Now we're cutting down the little pieces, right? That's right. We're all going micro now these days. That's right. Talk about that trend a little bit, what you're seeing, and we'll jump in a little deeper as to how you're addressing that. >>Well, I think the industry learned a long time ago that running large code bases is actually quite problematic when it comes to scaling the organization and capturing new opportunities. And so, you know, we're transitioning to microservices because we want to get more opportunities in our business. We want to be able to create new products, fasters, we want to be able to leverage existing services or data that we have built, like an assembly line of software, you know, picking up APIs that other developers are building, and then assemble them together to create new experiences or new products, enter new markets. And so microservices are fantastic for that, except microservices. They also introduce significant concerns on the networking layer, on the API layer. And so this is where Kong specializes by providing API infrastructure to our customers. >>Right. So more about the problems, more about the challenges there, because you're right, it, opportunities always create, you know, big upside and, and I, I don't wanna say downside, but they do introduce new complexities. >>That's right. And introducing new complexity. It's a little bit the biggest enemy of any large organization, right? We want to reduce complexity, we want to move faster, we want to be more agile, and, and we need an API vision to be able to do that. Our teams, you know, I'm speaking with customers here at Reinvent, they're telling me that in the next five years, the organization is going to be creating more APIs than all the APIs they've created up until now. Right? So how do you >>Support, that's a mind boggling number, right? >>It's mind boggling. Yeah, exactly. How do you support that type of growth? And things have been moving so fast. I feel like there is a big dilemma in, you know, with certain organizations where, you know, we have not taught a long term strategy for APIs, whereas we do have a long term strategy for our business, but APIs are running the business. We must have a long term strategy for our APIs, otherwise we're not gonna be able to execute. And that's a big dilemma right now. Yeah. >>So, so how do we get the horse back in front of the cart then? Because it's like you said, it's almost as if we've, we're, we're reprioritizing, you know, incorrectly or inaccurately, right? You're, you're getting a little bit ahead of ourselves. >>Well, so, you know, whenever we have a long-term strategy for pretty much anything in the organization, right? We know what we want to do. We know the outcome that we want to achieve. We work backwards to, you know, determine what are the steps that are gonna bring us there. And, and the responsibility for thinking long term in, in every organization, including for APIs at the end of the day, always falls on the leaders and the should on the shoulders of the leadership and, and to see executives of the organization, right? And so we're seeing, you know, look at aws by the way. Look at Amazon. This conference would not have been possible without a very strong API vision from Amazon. And the CEO himself, Jeff Bezos, everybody talks about wanting to become an API first organization. And Amazon did that with the famous Jeff Bezos mandate today, aws, it's a hundred billion revenue for Amazon. You see, Amazon was not the first organization with, with an e-commerce, but if it was the first one that married a very strong e-commerce business execution with a very strong API vision, and here we are. >>So yeah, here we are putting you squarely in, in, in a pretty good position, right? In terms of what you're offering to the marketplace who has this high demand, you see this trend starting to explode. The hockey sticks headed up a little bit, right? You know, how are you answering that call specifically at how, how are you looking at your client's needs and, and trying to address what they need and when they need it, and how they need it. Because everybody's in a kind of a different place right now. >>Right? That's exactly right. And so you have multiple teams at different stages of their journey, right? With technology, some of them are still working on legacy, some of them are moving to the cloud. Yep. Some of them are working in containers and in microservices and Kubernetes. And so how do you, how do we provide an API vision that can fulfill the needs of the entire organization in such a way that we reduce that type of fragmentation and we don't introduce too much complexity? Well, so at con, we do it by essentially splitting the API platform in three different components. Okay. One is API management. When, whenever we want to expose APIs internally or to an ecosystem of partners, right? Or to mobile, DRA is a service mesh. You know, as we're splitting these microservices into smaller parts, we have a lot of connectivity, all, you know, across all the services that the teams are building that we need to, to manage. >>You know, the network is unreliable. It's by default, not secure, not observable. There is nothing that that works in there. And so how do we make that network reliable without asking our teams to go and build these cross-cut concerns whenever they create a new service. And so we need a service match for that, right? And then finally, we could have the best AP infrastructure in the world, millions of APIs and millions of microservices. Everything is working great. And with no API consumption, all of that would be useless. The value of our APIs and the value of our infrastructure is being driven by the consumption that we're able to drive to all of these APIs. And so there is a whole area of API productivity and discovery and design and testing and mocking that enables the application teams to be successful with APIs, even when they do have a, the proper API infrastructure in place that's made of meshes and management products and so on and so forth. Right. >>Can you gimme some examples? I mean, at least with people that you've been working with in terms of addressing maybe unique needs. Cuz again, as you've addressed, journeys are in different stages now. Some people are on level one, some people are on level five. So maybe just a couple of examples Yeah. Of clients with whom you've been working. Yeah, >>So listen, I I was talking with many organizations here at AWS Reinvent that are of course trying to migrate to the cloud. That's a very common common transformation that pretty much everybody's doing in the world. And, and how do you transition to the cloud by de-risking the migration while at the same time being able to get all the benefits of, of running in the cloud? Well, we think that, you know, we can do that in two, two ways. One, by containerizing our workloads so that we can make them portable. But then we also need to lift and shift the API connectivity in such a way that we can determine how much traffic goes to the legacy and how much traffic goes to the new cloud infrastructure. And by doing that, we're able to deal with some of these transformations that can be quite complex. And then finally, API infrastructure must support every team in the organization. >>And so being able to run on a single cloud, multi-cloud, single cluster, multi cluster VMs containers, that's important and essential because we want the entire organization to be on board. Because whenever we do not do that, then the developers will make short term decisions that are not going to be fitting into the organizational outcomes that we want to achieve. And we look at any outcome that your organization wants to achieve the cloud transformation, improving customer retention, creating new products, being more agile. At the end of the day, there is an API that's powering that outcome. >>Right? Right. Well, and, and there's always a security component, right? That you have to be concerned about. So how are you raising that specter with your clients to make them aware? Because sometimes it, I wouldn't say it's an afterthought, but sometimes it's not the first thought. And, and obviously with APIs and with their integral place, you know, in, in the system now security's gotta be included in that, right? >>API security is perhaps the biggest, biggest request that we're hearing from customers. You know, 83% of the world's internet traffic at the end of the day runs on APIs, right? That's a lot of traffic. As a matter of fact, APIs are the first attack vector for any, you know, malicious store party. Whenever there is a breach, APIs must be secured. And we can secure APIs on different layers of our infrastructure. We can secure APIs at the L four mesh layer by implementing zero trust security, for example, encrypting all the traffic, assigning an identity to every service, removing the concept of trust from our systems because trust is exploitable, right? And so we need to remove the cut zero trust, remove the concept of trust, and then once we have that underlying networking that's being secure and encrypted, we want to secure access to our APIs. >>And so this is the typical authentication, authorization concerns. You know, we can use patterns like op, op or opa open policy agent to create a security layer that does not rely on the team's writing code every time they're creating a new service. But the infrastructure is enforcing the type of layer. So for example, last week I was in Sweden, as a matter of fact speaking with the largest bank in Sweden while our customers, and they were telling us that they are implementing GDPR validation in the service mesh on the OPPA layer across every service that anybody's building. Why? Well, because you can embed the GDPR settings of the consumer into a claim in a gel token, and then you can use OPPA to validate in a blanket way that Jo Token across every service in the mesh, developers don't have to do that. It just comes out of the box like that. And then finally, so networking, security, API security for access and, and management of those APIs. And then finally we have deep inspection of our API traffic. And here you will see more exotic solutions for API security, where we essentially take a subset of our API traffic and we try to inspect it to see if there is anybody doing anything that they shouldn't be doing and, and perhaps block them or, you know, raise, raise, raise the flag, so to speak. >>Well, the answer is probably yes, they are. Somebody's trying to, somebody's trying to, yeah, you're trying to block 'em out. Before I let you go, you've had some announcements leading up here to the show that's just to hit a few of those highlights, if you would. >>Well, you know, Kong is an organization that you know, is very proud of the technology that we create. Of course, we started with a, with the API gateway Con Gateway, which was our first product, the most adopted gateway in the world. But then we've expanded our platform with service mesh. We just announced D B P F support in the service mesh. For example, we made our con gateway, which was already one of the fastest gateway, if not the fastest gateway out there, 30% faster with Con Gateway 3.0. We have shipped an official con operator for Kubernetes, both community and enterprise. And then finally we're doubling down on insomnia, insomnia's, our API productivity application that essentially connects the developers with the APIs that are creating and allows them to create a discovery mechanism for testing, mocking the bagging, those APIs, all of this, we of course ship it OnPrem, but then also on the cloud. And you know, in a cloud conference right now, of course, cloud, right? Right. Is a very important part of our corporate strategy. And our customers are asking us that. Why? Because they don't wanna manage the software, they want the API platform, they don't, don't wanna manage it. >>Well, no, nobody does. And there are a few stragglers, >>A few, a few. And for them there is the on-prem >>Platform. Fine, let 'em go. Right? Exactly. But if you wanna make it a little quick and dirty, hand it off, right? Oh, >>That's exactly right. Yes. >>Let Con do the heavy lifting for you. Hey Marco, thanks for the time. Yeah, thank you so much. We appreciate, and again, congratulations on what appears to be a pretty good show for you guys. Yeah, thank you. Well done. All right, we continue our discussions here at aws. Reinvent 22. You're watching the Cube, the leader in high tech coverage. >>Okay.

>>Oh, welcome back to the Cube here at aws Reinvent 22. As we continue our coverage here, the AWS Global Showcase, the Startup Showcase, John Wall is here hosting for the Cube as we've been here all week. Hope you're enjoying our coverage here. This is day three, by the way. We're wrapping it up shortly with us to talk about what's going on in the, kind of the hotel world in it and what's going on in the cloud, especially at I hg is Eric Norman, head of infrastructure, architecture, and innovation at I H G Hotels and Resorts. Eric, good to see you, >>Sir. Oh, thank you. And thank you for inviting me. Yeah, >>You bet. Glad to have you board here on the queue. First time, I think too, by the way, right? >>It is. And can I just tell you who IHG is >>Real quick? Yeah, wait a second. First I want another rest. I got Introduc to Rod Stuller, who is the Vice president and of Solutions marketing at Aviatrix and Rod. Good to see you, sir. Thanks a lot. Now let's talk about I ih. >>Great. Well, IHGs a a hospitality company, it's been around for 200 years, that has 17 brands globally in over a hundred countries. We sleek, you know, up could up to 888,000 people a night. So it's a pretty large company that we compete with, you know, all the hotel companies globally. >>So let's talk about your, your footprint right now in, in terms of what your needs are, because you've mentioned obviously a lot of, you have a lot of customers needs, you have a lot of internal stakeholder needs. Yeah. So just from that perspective, how are you balancing out, you know, the products you wanna launch as opposed to the, on the development side and the maintenance side? >>Yeah, I mean we, we have focused our, our attention to our, our guests and our hotels globally and, and taking technology and from a foundation, getting it at, at the edge so that way the consumer and the hotel owner can deliver a quality product to a guest experience. You know, we've have moved larger, a large deployment of our mission critical applications over the last five years really, of moving into more SaaS and infrastructure like AWS and GCP and, and leveraging their global scale to be able to deliver at the edge or get closer to the edge. And so we've, you know, I'm pretty sure you've seen, you know, kind of people building, you know, mission critical apps. You know, probably in the last three years it's probably escalating and more of like a hockey stick of moving stuff. I'd love to hear what AVIA is seeing. Oh >>Yeah. Now we're, we're seeing that quite a bit, right? As people move into the cloud, it's now business critical applications that are going there. So good enough isn't good enough anymore, right? It has to be, you know, a powerful capability that's business critical, can support that, give people the ability to troubleshoot it when something goes wrong. And then multi-cloud, you mentioned a couple different cloud companies, a lot of enterprises are moving to multiple clouds and you don't want to have to do it differently in every cloud. You want a infrastructure management layer that allows you to do that across >>Clouds. So how do you go about that, you know, deciding what goes where. I mean, it sounds like a simple question, but, but if you are dealing in a lot of different kinds of environments, different needs and different requirements, whatever, you know, how are you sorting out, delegating, you know, you know, you're, you're you're gonna be working here, you're gonna be >>Working there. Yeah. So we built some standards base that says, you know, certain types of apps, you know, transactional base, you know, go to this cloud provider and data analytics that's gonna go to another, another cloud provider based on our decision of key capability, native capability, and, and also coverage. You know, cuz we are in China, right? You know, you know, I, I've gotta be able to get into China and, and build not only a network that can support that, but also business apps locally to meet, compete with compliance, regulatory type activities. I mean, even in, in the US market, I got, you know, California privacy laws, you know, you have globally, you've gotta deal with getting data applications into compliance for those globally, right? >>Yeah. So, so you got that compliance slash governance Yeah. Issue. Huge issue. Yeah. I would think for you, you gotta decide who's gonna get to what when, and also we have to meet certain regulatory standards as you pointed out. And not just there, but you got European footprint, right? I mean, you're global. Yeah. So, so you know, handling that kind of scope or scale, what kind of nightmares or challenges does that provide you and how's Aviatrix helping you solve >>That? Yeah, in the early days, you know, we were using cloud native, you know, constructs for networking and a little bit of a security type angle to it. What we found was, you know, you can't get the automation you need. You can't get the, the scalability, you know, cuz we're, we're trying to shift left our, you know, our DevOps and our ability to deploy infrastructure. Aviatrix had come in and, and provided a, a solution that gets us there quicker than anybody else. It's allow us to, you know, build a mesh network across all our regions globally. I'm able to deploy, you know, new landing zones or, you know, public cloud fairly quickly with my, you know, networking construct. We also, we found that because we are a multi hybrid cloud, we, we introduced on the edge a a new network. We had to introduce a performance hub architecture that's using Equinix that sits in every region in every public cloud and partner. Cuz all our partners, you know, we, we've moved a lot of stuff to sas. You know, Amadeus is our centralized reservation system. That's our key, you know? Sure. You know, reservation tool, it's so sourced out. I need to bring them in and I need to get data that's closer to where, in a region to where it needs the land so I can process it. Right. >>And it's a big world out there too. I mean, you're, you're not in your head Rod. So talk about if you would share some of the, the aviatrix experience in that regard. When you have a client like this that has these, you know, multinational locations and, and yet you're looking for some consistency and some uniformity. You don't, you know, you can't be reinventing the wheel every time something pops up, right? >>Right. No. And then, and it's about agility and speed and, you know, being able to do it with less people than you used to have to do things, right? You, you want to be able to give the developers what they need when they need it. There was a time when people were going around it, swiping their credit card and, and saying, it doesn't give me what I need. And so cloud is supposed to change that. So we're trying to deliver the ability to do that for the developers a lot faster than had been done in the past. But at the same time, giving the enterprise the controls, the security, the compliance that they need. And sometimes those things got in the way, but now we're building systems that allow that to happen at, at the piece that developers needed to happen. >>But what Rod said about, you know, one of the big things you sparked my thinking is it also, you know, building a overlay of the cloud native construct allows for visibility that, you know, you didn't have, you know, from a developer or even a operations day two operations, now you get that visibility into the network space and controls and management of that space a lot easier now, you know? >>Yeah. I mean, business critical applications, right? People, the people, the business does not care about networking, right? They see it as electricity and if it's down somebody else's problem to fix it. But the people who do need to keep it up, they need the telemetry. They need the ability to understand, are we trending in the wrong direction? Should we be doing something so that we don't get to the point where it goes down? And that's the kind of information that we're providing in this multi-cloud environment. You mentioned Equinix, we, we just have a partnership with Equinix where we're extending the cloud operational model that Aviatrix delivers all the way out to Equinix and that global fabric that you're talking about. So this is allowing the, the comp companies to have that visibility, that operational ability all the way globally. >>Yeah. Because you know, when you start building all these clouds now and multi regions, multiple AZs or different cloud providers or SaaS providers, you're moving data all over the place. And if you, if you don't have a single pane of glass to see that entire network and be able to route stuff accordingly, it's gonna be a zoo. It's not gonna >>Work. We were, I was talking earlier with, with another guest and we were just talking about companies in your case, I, I IHG kind of knowing what you have and it's not like such a basic thing he said, but yeah, you'd be surprised how many people don't know what they have. Oh, yeah. And so they're trying to provide that visibility and, and, and awareness. So, so I'm kind of curious because you were just the next interview up, so sorry Ken, but, but do you know what you have, I mean, are you learning what you have or is how do you identify, prioritize? How valuable is this asset as opposed to this can wait? I mean, is that still an ongoing process for >>You? It, it's definitely an ongoing process. I mean, we've done over the last three years of constantly assessing all our inventory of what we have, making sure we have the right mo roadmaps for each of the apps and products that we have. Cause we've turned to more of a product driven organization and a DevOps and we're, we're moving more and more product teams onto that DevOps process. Yep. So we can shift left a lot of the activities that developer in the past had to go over a fence to ask for help and, and, you know, kind of the automation of the network and the security built in allows us to be able to shift that left. >>Did that, I, you were saying too three years, right? You've been on, on this path Yep. Going back then to 2019 right. Pandemic hits, right. The world changes. How has that affected this three year period for you? And where are you in terms of where you expected to be and, and Yep. And then what's your, what are your headlights seeing down the road as to what your, your eventual journey, how you want that to end? >>I probably, the biggest story that we have a success story is when the pandemic did happen, you know, all our call centers, all agents had to go home. We were able within 30 days be able to bring up remote desktops, you know, workspaces an a uws and give access to globally in China and in Singapore and in the Americas. There's >>No small task there, >>That's for sure. So we built a desktop, certified it, and, and agents were able to answer calls for guests, you know, you know, so it was a huge success to us. Sure. It did slow down. I mean, during the pandemic it did slow us down from what gets migrated. You know, our focus is, you know, again, back to what I was saying earlier is around our guests and our loyalty and, you know, how do we give value back to our hotel owners and our guests? >>And how do you measure that? I mean, how do you know that what you're doing is working with, with that key audience? >>We'd measured by, you know, one occupa >>There so many, how many people do we have in the rooms? Right? But in terms of the interface, in terms of the effectiveness, the applications, in terms of what you're offering. Yeah. >>It gets back to uptime of our systems and you know, being able to deploy an application in multiple regions elevates the availability of the product to our guest. You know, the longer I'm up, the more revenue I can produce. Right. So, you know, so we, we try to, you know, we measure also guest satisfaction at the properties, you know, them using our tech and that kind of stuff to >>Be so you surveying just to find out what, how they feel about, so some, >>Cause we have a lot of tech inside of our hotels that allow for, we have ISG connect, which allows for people to go from one hotel another and not ask for passwords and, you know, that kind of stuff. >>That would not be made by the way. I'd be begging for help. Let's talk about skills, because I hear that a lot. Talk a lot about that this week. Hearing that, that, you know, the advancement of knowledge is obviously a very powerful thing, but it's also a bit of a shortcoming right now in terms of, of having a need for skills and not having that kind of firepower horsepower on your bench. What, what do you see in that regard? And, and first off, what did you see about it? And then I'll follow >>Up with Yeah, I mean, over our journey, it started off where you didn't have the skills, you know, you didn't have the skill from an operations engineering architecture. So we went on a, you know, you know, how do we build training programs? How do we get, you know, tools to, to either virtual training, bringing teachers, we built, you know, daily, our weekly calls where we bring our experts from our vendors in there to be able to ask questions to help engineering people or architecture people or operations to ask questions and get answers. You know, we, we've been on a role of, you know, upscaling over the last three years and we continue to drive that, you know, we have lunch and learns that we bring people to. Yep. You know, and, and we, and we, we ta tailor the, the content for that training based on what we are consuming and what we're using as opposed to just a, you know, a broad stroke of, of public cloud or, it's >>Almost like you don't have to be holistic about it. You just need to, what do you need to know to >>Make >>Them successful, to be better at what you're doing here? Right. Sure. >>And that's been huge. And, >>And yeah, we, and we have a program called ace, which is AVIATRIX certified engineer. And there's a bunch of different types of classes. So if you're a networking person in the past it's like A C C I E, but we have about 18,000 people over the last three years who have gone through that training. One of them. One of them, right? Is that right? Yeah. Yeah. And, and this is not necessarily about aviatrix. What we're doing is trying to give multi-cloud, you know, networking expertise because a lot of the people that we're talking about are coming from the data center world. And networking is so different in the cloud. We're helping them understand it's not as scary as they might think. Right. If your whole career has been networking in the data center and all of a sudden there's this cloud thing that you don't really understand, you need somebody to help you sort of get there. And we're doing that in a multi-cloud way. And we have all kinds of different levels to teach people how to do, do infrastructure as code. That's another thing, you know, data center guys, they never did infrastructure as code. It was, you had to bolt it in and plug stuff in. Right. But now things are being done much faster with infrastructure as code. And we're teaching people how >>To do that. Yeah. I mean, yesterday, one of the keynotes is about the partner in the, the marketplace. And they use the image imagery of, of marathon runner, you know, a marathon runner. Yeah. You could do a marathon by yourself, but if you want to improve and become a, a great marathon runner, you need a coach, you need nutritionist, you need people running with you to, to make that engine go faster a little bit. Yeah, exactly. And you know, having a partner like Aviatrix helps you know the team to be successful. >>Well, it is, it is a marathon, not a sprint. That's for sure. And you've been on this kind of three year jog. You might feel like you've been running a marathon a little bit, but it sounds like you're really off to a great start and, and have a pretty good partnership here. So thank you. Congratulations on that, Eric. Thank you for being with us. And Rod, same to you. Thank you. Appreciate the time here on the AWS Global Showcase. I'm John Wal, you're watching The Cube. We're out in Las Vegas and of course the cube, as you well know, is the leader in high tech coverage.

(gentle music) >> Now welcome back to theCUBE, everyone. I'm John Walls, and once again, we're glad to have you here for AWS re:Invent 22. Our coverage continues here on Thursday, day three, of what has been a jam-packed week of tech and AWS, of course, has been the great host for this. It's now a pleasure to welcome in Anurag Gupta, who is the founder and CEO of Shoreline, joining us here as part of the AWS Global Showcase Startup Program, and Anurag, good to see you, sir. Thanks for joining us. >> Thank you so much. >> Tell us about Shoreline, about what you're up to. >> So we're a DevOps company. We're really focused on repairing issues. If you think about it, there are a ton DevOps companies and we all went to the cloud in order to gain faster innovation and by and large check. Then all of the things involved in getting things into production, artifact generation, testing, configuration management, deployment, also by and large, automated. Now pity the poor SRE who's getting the deluge of stuff on them, every week, every two days, sometimes multiple times a day, and it's complicated, right? Kubernetes, VMs, lots of services, multiple clouds, sometimes, and you know, they need to know a little bit about everything. And you know what, there are a ton of companies that actually help you with what we call Day-2 Ops. It's just that most of them help you with observability, telling you what's gone wrong, or incident management, routing something to someone. But you know, back when I was at AWS, I never got really that excited about one more dashboard to look at or one more like better ticket routing. What used to really excite me was having some issue extinguished forever. And if you think about it, like the first five minutes of an incident are detecting and routing. The next hour, two hours, is some human being going in and fixing it, so that feels like the big opportunity to reduce, so hopefully we can talk a little bit about different ways that one can do that. >> What about Day-2 Ops? Just tell me about how you define that. >> So I basically define it as once the software goes into a production, just making sure things stay up and are healthy and you're resilient and you don't get errors and all of those sorts of things because everything breaks sooner or later, you know, to a greater or lesser degree. >> Especially that SRE you're talking about, right? >> Yeah. >> So let's go back to that scenario. Yeah, you pity the poor soul because they do have to be a little expert in everything. >> Exactly. >> And that's really challenging and we all know that, that's really hard. So how do you go about trying to lighten that burden, then? >> So when you look at the numbers, about somewhere between 40% to even 95% of the alarms that fire, the alerts that fire, are false positives and that's crazy. Why is someone waking up just to deal with? >> It's a lot of wasted time, isn't it? >> A lot of wasted time. And you know, you're also training someone into what I call ClickOps, just to go in and click the button and resolve it and you don't actually know if it was the false positive or it's the rare real positive, and so that's a challenge, right? And so the first thing to do is to figure out where the false positives are. Like, let's say Datadog tells you that CPU is high and alarms. Is that a good thing or a bad thing? It's hard for them to tell, right? But you have to then introspect it into something precise like, oh, CPU is high, but response times are standard and the request rate is high. Okay, that's a good thing. I'm going to ignore this. Or CPU is high, but it kind of resolves itself, so I'm going to not wake anybody up. Or CPU is high and oh, it's the darn JVM starting to garbage collect again, so let me go and take a heap dump and give that to my dev team and then bounce the JVM and you know, without waking anybody up, or CPU is high, I have no idea what's going on. Now it's time to wake somebody up. You know, what you want to use humans for is the ability to think about novel stuff, not to do repetitive stuff, so that's the first step. The second step is, about 40% of what remains is repetitive and straightforward. So like a disk is full, I'd better clean up the garbage on the disk or maybe grow the disk. People shouldn't wake up to deal to grow a disk. And so for that, what you want to do is just have those sorts of things get automated away. One of the nice things about Shoreline is, is that we take the experience in what we build for one company, and if they're willing, provide it to everybody else. Our belief is, a central tenant is, if someone somewhere fixes something, everyone everywhere should gain the benefit because we all sit on the same three clouds, we all sit on the same set of database infrastructure, et cetera. We should all get the same benefits. Why do we have to scar our own backs rather than benefiting from somebody else's scar tissue, so that's the second thing. The third thing is, okay, let's say it's not straightforward, not something I've seen before, then in that case, what often happens is on average like eight people get involved. You know, it initially goes to L1 support or L1 ops and, but they don't necessarily know because, as you say, the environment's complex. And so, you know, they go into Slack and they say, "At here, can somebody help me with this?" And those things take a much longer time, so wouldn't it be better that if your best SRE is able to say, "Hey, check these 20 things and then run these actions." We could convert that into like a Jupyter Notebook where you could say the incident got fired I pre-populated all the diagnostics, and then I tell people very precisely, "If you see this, run this, et cetera." Like a wiki, but actually something you could run right in this product. And then, you know, last piece of the puzzle, the smaller piece, is sometimes new things happen and when something new happens, what you want is sort of the central tech of Shoreline, which is parallel distributed, real-time debugging. And so the ability to do, you know, execute a command across your fleet rather than individual boxes so that you can say something like, "I'm hearing that my credit card app is slow. For everything tagged as being part of my credit card app, please run for everything that's running over 90% CPU, please run a top command." And so, you know, then you can run in the same time on one host as you can on 30,000 and that helps a lot. So that's the core of what we do. People use us for all sorts of things, also preventative maintenance, you know, just the proactive regular things. You know, like your car, you do an oil change, well, you know, you need to rotate your certs, certificates. You need to make sure that, you know, there isn't drift in your configurations, there isn't drift in your software. There's also security elements to it, right? You want to make sure that you aren't getting weird inbound/outbound traffic across to ports you don't expect to be open. You don't want to have these processes running, you know, maybe something's bad. And so that's all the kind of weird anomaly detection that's easy to do if you run things in a distributed parallel way across everything. That's super hard to do if you have to go and Whac-A-Mole across one box after the next. >> Well, which leads to a question just in terms of setting priorities then, which is what you're talking about helping companies establish priorities, this hierarchy of level one warning, level two, level three, level four. Sounds like that should be a basic, right? But you're saying that's not, that's not really happening in the enterprise. >> Well, you know, I would say that if you hadn't automated deployments, you should do that first. If you haven't automated your testing pipeline, shame on you, you should do that like a year ago. But now it's time to help people in production because you've done that other work and people are suffering. You know, the crazy thing about the cloud is, is that companies spend about three times more on the human beings to operate their cloud infrastructure as on the cloud infrastructure itself. I've yet to hear anybody say that their cloud bill is too low, you know, so, you know, there's a clearer savings also available. And you know, back when I was at AWS, obviously I had to keep the lights on too, but you know, I had to do that, but it's kind of a tax on my engineers and I'd really spend, prefer to spend the head count on innovation, on doing things that delight my customers. You never delight your customers by keeping the lights on, you just avoid irritating them by turning 'em off, right? >> So why are companies so fixed in on spending so much time on manually repairing things and not looking for these kinds of little, much more elegant solution and cost-efficient, time-saving, so on so forth. >> Yeah, I think there just hasn't been very much in this space as yet because it's a hard, hard problem to solve. You know, automation's a little bit scary and that's the reality of it and the way you make it less scary is by proving it out, by doing the simple things first, like reducing the alert fatigue, you know, that's easy. You know, providing notebooks to people so that they can click things and do things in a straightforward way. That's pretty easy. The full automation, that's kind of the North Star, that's what we aspire to do. But you know, people get there over time and one of our customers had 700 instances of this particular incident solved for them last week. You imagine how many human beings would've been doing it otherwise, you know? >> Right. >> That's just one thing, you know? >> How many did it take the build a pyramid? How many decades did that take, right? You had an announcement this week. I don't think we've talked about that. >> No, yeah, so we just announced Incident Insights, which is a free product that lets people plug into initially PagerDuty and pretty soon the Opsgenie ServiceNow, et cetera. And what you can do is, is you give us an API key read-only and we will suck your PagerDuty data out. We apply some lightweight ML unsupervised learning, and in a couple of minutes, we categorize all of your incidents so that you can understand which are the ones that happen most often and are getting resolved really quickly. That's ClickOps, right? Those alarms shouldn't fire. Which are the ones that involve a lot of people? Those are good candidates to build a notebook. Which are the ones that happen again and again and again? Those are good candidates for automation. And so, I think one of the challenges people have is, is that they don't actually know what their teams are doing and so this is intended to provide them that visibility. One of our very first customers was doing the beta test for us on it. He used to tell us he had about 100 tickets, incidents a week. You know, he brought this tool in and he had 2,100 last week and was all, you know, like these false alarms, so while he's giving us- >> That was eye opening for him to see that, sure. >> And why he's, you know, looking at it, you know, he's just like filing Jiras to say, "Oh, change this threshold, cancel this alarm forever." You know, all of that kind of stuff. Before you get to do the fancy work, you got to clean your room before you get to do anything else, right? >> Right, right, dinner before dessert, basically. >> There you go. >> Hey, thanks for the insights on this and again the name of the new product, by the way, is... >> Incident Insights. >> Incident Insights. >> Totally free. >> Free. >> Yeah, it takes a couple of minutes to set up. Go to the website, Shoreline.io/insight and you can be up and running in a couple of minutes. >> Outstanding, again, the company is Shoreline. This is Anurag Gupta, and thank you for being with us. We appreciate it. >> Appreciate it, thank you. >> Glad to have to here on theCUBE. Back with more from AWA re:Invent 22. You're watching theCUBE, the leader in high-tech coverage. (gentle music)

well hello everybody John Wallace here on thecube he's continuing our segments here on the AWS Global startup showcase we are at day three of Reinventing irking Zhang is joining us now he is the CEO co-founder of Jupiter one um first off before we get going talking about you know security and big world for you guys I know what's your take on the show what's been going on out here at re invent yeah yeah ring event has been one of my favorite shows there's a lot of people here there's a lot of topics of course it's not just cyber security a lot of cloud infrastructure and just technology in general so you get a lot you know if you go walk the floor you see a lot of vendors you look at us go into sessions you can learn a lot but you're the Hot Topic right everybody's focused on Cyber yeah big time and with good reason right because as we know the Bad actors are getting even smarter and even faster and even more Nimble so just paint the landscape for me here in general right now as you see uh security Cloud Security in particular and and kind of where we are in that battle well we are clearly not winning so I think that in itself is a bit of a uh interesting problem right so as a it's not just Cloud security if you think about cyber security in general as an industry it has it has not been around for that long right but if you just look at the history of it uh we haven't done that while so uh pick another industry say medicine which has been around forever and if you look at the history of Medicine well I would argue you has done tremendously well because people live longer right when you get sick you get access to health care and yeah exactly you have Solutions and and you can see the trend even though there are problems in healthcare of course right but the trend is is good it's going well but not in cyber security more breaches more attacks more attackers we don't know what the hell we're doing with that many solutions and you know that's been one of my struggles as a former CSO and security practitioner for many years you know why is it that we're not getting better all right so I'm going to ask you the question yeah okay why aren't we getting better you know how come we can't stay ahead of the curve on this thing that for some reason it's like whack-a-mole times a hundred every time we think we solve one problem we have a hundred more that show up over here exactly and we have to address that and and our attention keeps floating around yeah I think you said it right so because we're taking this guacamole approach and we're looking for the painkiller of the day and you know we're looking for uh the Band-Aids right so and then we ended up well I I think to be fair to be fair to your industry the industry moves so quickly technology in general moves so quickly and security has been playing catch-up over time we're still playing catch-up so when you're playing catch-up you you can almost only uh look at you know what's the painkiller of what's the band name of the day so I can stop the bleeding right but I do think that we're we're to a point or we have enough painkillers and Band-Aids and and we need to start looking at how can we do better fundamentally with the basics and do the basics well because a lot of times the basics that get you into trouble so fundamentally the foundation I if I hear you right what you're saying is um you know quick changing industry right things are moving rapidly but we're not blocking and tackling we're not doing the X's and O's and so forget changing and we we got to get back to the basis and do those things right exactly you can only seem so simple it seems so simple but it's so hard right so you can you can think about you know uh even in case of building a starter building a company and and in order at one point right so we're blocking uh blocking tackling and then when we grow to a certain size we have to scale we have to figure out how to scale the business this is the same problem that happens in security as an industry we've been blocking happening for so long you know we're the industry is so young but we're to a point that we got to figure out how to scale this scale this in a fundamentally different way and I'll give you some example right so so what when we say the basics now it's easy to to think that say users should have MFA enabled is one of the basics right or another Basics will be you have endpoint protection on your devices you know maybe it's Cloud strike or Sentinel one or carbon black or whatever but the question being how do you know it is working 100 of the time right how do you know that how do you know right you find out too exactly that's right and how do you know that you have 100 coverage on your endpoints those Solutions are not going to tell you because they don't know what they don't know right if it's not enabled if it's not you know what what's the negative that you are not seeing so that's one of the things that you know that's in the basic state that you're now covering so the fundamentals it really goes to these five questions that I think that nobody has a really good answer for until now so the five questions goes what do I have right is it important what's important out of all the things I have you have a lot right you could have millions of things what important now for those that are important does it have a problem and if it has a problem who can fix it because the reality is in most cases security teams are not the ones fixing the problems they're they're the ones identical they're very good at recognizing but not so good exactly identifying the owner who can fix it right right could be could be business owner could be Engineers so the the asset ownership identification right so so these four questions and and then over time you know whether it's over a week or a month or a quarter or a year am I getting better right and then you just keep asking these questions in different areas in different domains with a different lens right so maybe that's endpoints maybe that's Cloud maybe that's you know users maybe that's a product and applications right but it really boils down to these five questions that's the foundation for any good security program if you can do that well I think we cover a lot of bases and we're going to be in much better shape than we have been all right so where do you come in man Jupiter one in terms of what you're providing because obviously you've identified this kind of pyramid yes this hierarchy of addressing needs and I assume obviously knowing you as I do and knowing the company as I do you've got Solutions that's exactly right right and and we precisely answer those five questions right for uh any organization uh from a asset perspective right because all the the answers to all those these five questions are based in assets it starts with knowing what I have right right so the the overall challenge of cyber security being broke broken I I believe is fundamentally that people do not understand and cannot uh probably deal with the complexity that we have within our own environments so again like you know using uh medicine as an example right so in order to come up with the right medicine for either it's a vaccine for covid-19 or whether it is a treatment for cancer or whatever that case may be you have to start with the foundations of understanding both the pathogen and to the human body like DNA sequencing right without those you cannot effectively produce the right medicine in modern uh you know Medicine sure right so that is the same thing that's happening in cyber security you know we spend a lot of times you know putting band days in patches right and then we spend a lot of time doing attacker research from the outside but we don't fundamentally understand in a complete way what's the complexity within our own environment in terms of digital assets and that's that's almost like the DNA of your own work what is that kind of mind-blowing in a way that if again hearing you what you're talking about is saying that the first step is to identify what you have that's right so it seems just so basic that that I should know what I what's under my hood I should know what is valuable and what is not I should prioritize what I really need to protect and what maybe can go on the second shelf yeah it has been a tough problem since the beginning of I.T not just the beginning of cyber security right so in the history of I.T we have this thing called cmdb configuration management database it is supposed to capture the configurations of it assets now over time that has become a lot more complex and and there's a lot more than just it asset that we have to understand from a security and attack service perspective right so we have to understand I.T environments we have to understand Cloud environments and applications and users and access and data and as and all of those things then then we have to take a different approach of sort of a modern cmdb right so what is the way that we can understand all of those complexity within all of those assets but not just independently within those silos but rather in a connected way so we can not only understand the attack surface but only but also understand the attack path that connect the dots from one thing to another right because everything in the organization is actually connected if if there's any one thing that sits on an island right so if you say you have a a a a server or a device or a user that is on an island that is not connected to the rest of the organization then why have it right and it doesn't matter so it's the understanding of that connect connected tissue this entire map where this you know DNA sequencing equivalent of a digital organization is what Jupiter one provides right so that visibility of the fundamental you know very granular uh level of assets and resources to answer those five questions and how does that how do I get better at that then I mean I have you to help me but but internally within our organization um I mean I don't want to be rude but I mean do I have do I have the skill for that do I have um do I have the the internal horsepower for that or or is there some need to close that Gap and how do I do it you know I'll tell you two things right so so one you mentioned the worst skills right so let me start there so because this one is very interesting we also have a huge skills shortage in cyber security we will we've all heard that for years and and and and for a long time but if you dig deeper into it why is that why is that and you know we have a lot of you know talented people right so why do we still have a skills shortage now what's interesting is if you think about what we're asking security people to do is mind-boggling so if you if you get a security analyst to say hey I want to understand how to protect something or or how to deal with an incident and what you're asking the person to do is not only to understand the security concept and be a domain expert in security you're also asking the person to and understand at the same time AWS or other clouds or endpoints or code or applications so that you can properly do the analysis and the in the response it's it's impossible it's like you know if you have you have to have a person who's an expert in everything know everything about everything that's right it's impossible so so so that's that's one thing that we have to to resolve is how do we use technology like Jupiter one to provide an abstraction so that there's Automation in place to help the security teams be better at their jobs without having to be an expert in deep technology right just add the abstract level of understanding because you know we can we can model the data and and provide the analysis and visual visualization out of the box for them so they can focus on just the security practices so that's one and the second thing is we have to change the mindset like take vulnerability management as an example right so the mindset for vulnerability management has been how do I manage findings now we have to change it to the concept of more proactive and how to manage assets so let's think about uh you know say log4j right that that happened and uh you know when it happened everybody scrambles and said hey which which devices or which you know uh systems have log4j and you know it doesn't matter what's the impact we can fix it right going back to those questions that that I mentioned before right and then um and then they try to look for a solution at a time say well where's that silver bullet that can give me the answers now what what what we struggle with though is that you know I want to maybe ask the question where were you six months ago where were you six months ago where you could have done the due diligence and put something in place that help you understand all of these assets and connections so you can go to one place and just ask for that question when something like that you know hit the fan so so if we do not fundamentally change the mindset to say I have to look at things not from a reactive findings perspective but really starting from an asset-centric you know day one perspective to look at that and have this Foundation have this map build we can't get there right so it's like you know if I need direction I go to Google Maps right but the the reason that it works is because somebody has done the work of creating the map right right if you haven't if you don't have the map and you just at you know when the time you say I gotta go somewhere and you expect the map to magically happen to show you the direction it's not going to work right right I imagine there are a lot of people out there right now are listening to thinking oh boy you know and that's what Jupiter one's all about they're there to answer your oh boy thanks for the time of course I appreciate the insights as well it's nice to know that uh at least somebody is reminding us to keep the front door locked too that's just the back door the side doors keep that front door and that garage locked up too definitely um all right we'll continue our coverage here at AWS re invent 22 this is part of the AWS Global startup showcase and you're watching the cube the leader in high-tech coverage foreign

>>Well, hello everybody. John Walls here and continuing our coverage here at AWS Reinvent 22 on the queue. We continue our segments here in the Global Startup program, which of course is sponsored by AWS Startup Showcase, and with us to talk about any scale as the co-founder and CEO of the company, Robert and n, you are Robert. Good to see you. Thanks for joining us. >>Yeah, great. And thank you. >>You bet. Yeah. Glad to have you aboard here. So let's talk about Annie Scale, first off, for those at home and might not be familiar with what you do. Yeah. Because you've only been around for a short period of time, you're telling me >>Company's about >>Three years now. Three >>Years old, >>Yeah. Yeah. So tell us all about it. Yeah, >>Absolutely. So one of the biggest things happening in computing right now is the proliferation of ai. AI is just spreading throughout every industry has the potential to transform every industry. But the thing about doing AI is that it's incredibly computationally intensive. So if you wanna do do ai, you're not, you're probably not just doing it on your laptop, you're doing it across many machines, many gpu, many compute resources, and that's incredibly hard to do. It requires a lot of software engineering expertise, a lot of infrastructure expertise, a lot of cloud computing expertise to build the software infrastructure and distributed systems to really scale AI across all of the, across the cloud. And to do it in a way where you're really getting value out of ai. And so that is the, the problem statement that AI has tremendous potential. It's incredibly hard to do because of the, the scale required. >>And what we are building at any scale is really trying to make that easy. So trying to get to the point where, as a developer, if you know how to program on your laptop, then if you know how to program saying Python on your laptop, then that's enough, right? Then you can do ai, you can get value out of it, you can scale it, you can build the kinds of, you know, incredibly powerful applica AI applications that companies like Google and, and Facebook and others can build. But you don't have to learn about all of the distributed systems and infrastructure. It just, you know, we'll handle that for you. So that's, if we're successful, you know, that's what we're trying to achieve here. >>Yeah. What, what makes AI so hard to work with? I mean, you talk about the complexity. Yeah. A lot of moving parts. I mean, literally moving parts, but, but what is it in, in your mind that, that gets people's eyes spinning a little bit when they, they look at great potential. Yeah. But also they look at the downside of maybe having to work your way through Pike mere of sorts. >>So, so the potential is definitely there, but it's important to remember that a lot of AI initiatives fail. Like a lot of initiative AI initiatives, something like 80 or 90% don't make it out of, you know, the research or prototyping phase and inter production. Hmm. So, some of the things that are hard about AI and the reasons that AI initiatives can fail, one is the scale required, you know, moving. It's one thing to develop something on your laptop, it's another thing to run it across thousands of machines. So that's scale, right? Another is the transition from development and prototyping to production. Those are very different, have very different requirements. Absolutely. A lot of times it's different teams within a company. They have different tech stacks, different software they're using. You know, we hear companies say that when they move from develop, you know, once they prototype and develop a model, it could take six to 12 weeks to get that model in production. >>And that often involves rewriting a lot of code and handing it off to another team. So the transition from development to production is, is a big challenge. So the scale, the development to production handoff. And then lastly, a big challenge is around flexibility. So AI's a fast moving field, you see new developments, new algorithms, new models coming out all the time. And a lot of teams we work with, you know, they've, they've built infrastructure. They're using products out there to do ai, but they've found that it's sort of locking them into rigid workflows or specific tools, and they don't have the flexibility to adopt new algorithms or new strategies or approaches as they're being developed as they come out. And so they, but their developers want the flexibility to use the latest tools, the latest strategies. And so those are some of the main problems we see. It's really like, how do you scale scalability? How do you move easily from development and production and back? And how do you remain flexible? How do you adapt and, and use the best tools that are coming out? And so those are, yeah, just those are and often reasons that people start to use Ray, which is our open source project in any scale, which is our, our product. So tell >>Me about Ray, right? Yeah. Opensource project. I think you said you worked on it >>At Berkeley. That's right. Yeah. So before this company, I did a PhD in machine learning at Berkeley. And one of the challenges that we were running into ourselves, we were trying to do machine learning. We actually weren't infrastructure or distributed systems people, but we found ourselves in order to do machine learning, we found ourselves building all sorts of tools, ad hoc tools and systems to scale the machine learning, to be able to run it in a reasonable amount of time and to be able to leverage the compute that we needed. And it wasn't just us people all across, you know, machine learning researchers, machine learning practitioners were building their own tooling and infrastructure. And that was one of the things that we felt was really holding back progress. And so that's how we slowly and kind of gradually got into saying, Hey, we could build better tools here. >>We could build, we could try to make this easier to do so that all of these people don't have to build their own infrastructure. They can focus on the actual machine learning applications that they're trying to build. And so we started, Ray started this open source project for basically scaling Python applications and scaling machine learning applications. And, well, initially we were running around Berkeley trying to get all of our friends to try it out and, and adopt it and, you know, and give us feedback. And if it didn't work, we would debug it right away. And that slow, you know, that gradually turned into more companies starting to adopt it, bigger teams starting to adopt it, external contributors starting to, to contribute back to the open source project and make it better. And, you know, before you know it, we were hosting meetups, giving to talks, running tutorials, and the project was just taking off. And so that's a big part of what we continue to develop today at any scale, is like really fostering this open source community, growing the open source user base, making sure Ray is just the best way to scale Python applications and, and machine learning applications. >>So, so this was a graduate school project That's right. You say on, on your way to getting your doctorate and now you commercializing now, right? Yeah. I mean, so you're being able to offer it, first off, what a journey that was, right? I mean, who would've thought Absolutely. I guess you probably did think that at some point, but >>No, you know, when we started, when we were working on Ray, we actually didn't anticipate becoming a company, or we at least just weren't looking that far ahead. We were really excited about solving this problem of making distributed computing easy, you know, getting to the point where developers just don't have to learn about infrastructure and distributed systems, but get all the benefits. And of course, it wasn't until, you know, later on as we were graduating from Berkeley and we wanted to continue really taking this project further and, and really solving this problem that it, we realized it made sense to start a company. >>So help me out, like, like what, what, and I might have missed this, so I apologize if I did, but in terms of, of Ray's that building block and essential for your, your ML or AI work down the road, you know, what, what is it doing for me or what, what will it allow me to do in either one of those realms that I, I can't do now? >>Yeah. And so, so like why use Ray versus not using Ray? Yeah, I think the, the answer is that you, you know, if you're doing ai, you need to scale. It's becoming, if you don't find that to be the case today, you probably will tomorrow, you know, or the day after that. And so it's really increasingly, it's a requirement. It's not an option. And so if you're scaling, if you're trying to build these scalable applications you are building, you're either going to use Ray or, or something like Ray or you're going to build the infrastructure yourself and building the infrastructure yourself, that's a long journey. >>So why take that on, right? >>And many of the companies we work with don't want to be in the business of building and managing infrastructure. No. Because, you know, if they, they want their their best engineers to build their product, right? To, to get their product to market faster. >>I want, I want you to do that for me. >>Right? Exactly. And so, you know, we can really accelerate what these teams can do and, you know, and if we can make the infrastructure something they just don't have to think about, that's, that's why you would choose to use Ray. >>Okay. You know, between a and I and ml are, are they different animals in terms of what you're trying to get done or what Ray can do? >>Yeah, and actually I should say like, it's not just, you know, teams that are new teams that are starting out, that are using Ray, many companies that have built, already built their own infrastructure will then switch to using Ray. And to give you a few examples, like Uber runs all their deep learning on Ray, okay. And, you know, open ai, which is really at the frontier of training large models and, and you know, pushing the boundaries of, of ai, they train their largest models using Ray. You know, companies like Shopify rebuilt their entire machine learning platform using Ray, >>But they started somewhere else. >>They had, this is all, you know, like, it's not like the v1, you know, of their, of their machine learning infrastructure. This is like, they did it a different way before, this is like the second version or the third iteration of of, of how they're doing it. And they realize often it's because, you know, I mean in the case of, of Uber, just to give you one example, they built a system called hova for scaling deep learning on a bunch of GPUs. Right Now, as you scale deep learning on GPUs for them, the bottleneck shifted away from, you know, as you scale GPU's training, the bottleneck shifted away from training and to the data ingest and pre-processing. And they wanted to scale data ingest and pre-processing on CPUs. So now Hova, it's a deep learning framework. It doesn't do the data ingest and pre-processing on CPUs, but you can, if you run Hova on top of Ray, you can scale training on GPUs. >>And then Ray has another library called Ray Data you can, that lets you scale the ingest and pre-processing on CPUs. You can pipeline them together. And that allowed them to train larger models on more data before, just to take one example, ETA prediction, if you get in an Uber, it tells you what time you're supposed to arrive. Sure. That uses a deep learning model called d eta. And before they were able to train on about two weeks worth of data. Now, you know, using Ray and for scaling the data, ingestive pre-processing and training, they can train on much more data. You know, you can get more accurate ETA predictions. So that's just one example of the kind of benefit they were able to get. Right. Also, because it's running on top of, of Ray and Ray has this ecosystem of libraries, you know, they can also use Ray's hyper parameter tuning library to do hyper parameter tuning for their deep learning models. >>They can also use it for inference and you know, because these are all built on top of Ray, they inherit the like, elasticity and fault tolerance of running on top of Ray. So really it simplifies things on the infrastructure side cuz there's just, if you have Ray as common infrastructure for your machine learning workloads, there's just one system to, to kind of manage and operate. And if you are, it simplifies things for the end users like the developers because from their perspective, they're just writing a Python application. They don't have to learn how to use three different distributed systems and stitch them together and all of this. >>So aws, before I let you go, how do they come into play here for you? I mean, are you part of the showcase, a startup showcase? So obviously a major partner and major figure in the offering that you're presenting >>People? Yeah, well you can run. So any scale is a managed ray service. Like any scale is just the best way to run Ray and deploy Ray. And we run on top of aws. So many of our customers are, you know, using Ray through any scale on aws. And so we work very closely together and, and you know, we have, we have joint customers and basically, and you know, a lot of the value that any scale is adding on top of Ray is around the production story. So basically, you know, things like high availability, things like failure handling, retry alerting, persistence, reproducibility, these are a lot of the value, the values of, you know, the value that our platform adds on top of the open source project. A lot of stuff as well around collaboration, you know, imagine you are, you, something goes wrong with your application, your production job, you want to debug it, you can just share the URL with your, your coworker. They can click a button, reproduce the exact same thing, look at the same logs, you know, and, and, and figure out what's going on. And also a lot around, one thing that's, that's important for a lot of our customers is efficiency around cost. And so we >>Support every customer. >>Exactly. A lot of people are spending a lot of money on, on aws. Yeah. Right? And so any scale supports running out of the box on cheaper like spot instances, these preempt instances, which, you know, just reduce costs by quite a bit. And so things like that. >>Well, the company is any scale and you're on the show floor, right? So if you're having a chance to watch this during reinvent, go down and check 'em out. Robert Ashihara joining us here, the co-founder and ceo and Robert, thanks for being with us. Yeah. Here on the cube. Really enjoyed it. Me too. Thanks so much. Boy, three years graduate program and boom, here you are, you know, with off to the enterprise you go. Very nicely done. All right, we're gonna continue our coverage here on the Cube with more here from Las Vegas. We're the Venetian, we're AWS Reinvent 22 and you're watching the Cube, the leader in high tech coverage.

>>Good afternoon everybody. I'm John Walls and welcome back to our coverage here on the cube of AWS Reinvent 22. We are bringing you another segment with the Global Startup Program, which is part of the AWS Start Showcase, and it's a pleasure to welcome two new guests here to the showcase. First, immediately to my right Han w lre. Good to see you Han. Good to see you. The leader of the Enterprise Solutions Architecture at aws. And on the far right, Rolin Lee, who is the co-founder and CEO of Heim Doll Data. Roland, good to see you. Great >>To be here. >>All right, good. Thanks for joining us. Well first off, for those at home, I may not be familiar with Heim Doll. What do you do? Why are you here? But I'll let you take it from there. >>Well, we're one of the sponsors here at AWS and great to be here. We offer a data access layer in the form of a proxy, and what it does is it provides complete visibility and the capability to enhance the interaction between the application and one's current database. And as a result, you'll, the customer will improve database scale, database security and availability. And all these features don't require any application changes. So that's sort of our marketing pitch, if you will, all these types of features to improve the experience of managing a database without any application >>Changes. And, and where's the cloud come into play then, for you then, where, where did it come into play for you? >>So we started out actually helping out customers on premise, and a lot of enterprise customers are moving over to the cloud, and it was just a natural progression to do that. And so aws, which is a key part of ours, partners with us to help solve customer problems, especially on the database side, as the application being application performance tends to have issues between the interaction between the application database and we're solving that issue. >>Right. Sohan, I mean, Roan just touched on it about OnPrem, right? There's still some kickers and screamers out there that, that don't, haven't bought in or, or they're about to, but you're about to get 'em. I, I'm sure. But talk about that, that conversion or that transition, if you would, from going OnPrem into a hybrid environment or to into the, the bigger cloud environment and and how difficult that is sometimes. Yes. Maybe to get people to, to make that kind of a leap. >>Well, I would say that a lot of customers are wanting to focus more on product innovation experimentation, and also in terms of having to manage servers and patching, you know, it's to take away from that initiative that they're trying to do. So with aws, we provide undifferentiated heavy lifting so that they can focus on product innovation. And one of the areas talking about Heim is that from the database side, we do provide Amazon rds, which is database and also Aurora, to give them that lift so they don't have to worry about patching servers and setting up provisioning servers as well. >>Right. So Roland, can you get the idea across to people very simply, let us take care of the, the hard stuff and, and that will free you up to do your product innovations, to do your experimentations to, to really free up your team, basically to do the fun stuff and, and let us sweat over the, the, the details basically. Right? >>Exactly. Our, our motto is not only why build when, when you can buy. So a lot of it has to do with offering the, the value in terms of price and the features such as it's gonna benefit a team. Large companies like amazon.com, Google, they have huge teams that can build data access layers and proxies. And what we're trying to do here is commercialize those cuz those are built in house and it's not readily available for customers to use. And you'd need some type of interface between the application and the database. And we provide that sort of why build when you can buy. >>Well, I was gonna say why h right? I mean what's your special sauce? Because everybody's got something, obviously a market differentiator that you're bringing into place here. So you started to touch on a little bit there for me, but, but dive a little deeper there. I mean, what, what is it that, that you're bringing to the table with AWS that you think puts you above the crowd? >>Well, lemme give you a use case here. In typical events like let's say Black Friday where there's a surge traffic that can overwhelm the database, the Heim doll data access layer database proxy provides an auto scaling distributed architecture such that it can absorb those surges and traffic and help scale the database while keeping the data fresh and up to date. And so basically traffic based on season time of day, we can, we can adjust automatically and all these types of features that we offer, most notably automated query caching, ReadWrite split for asset compliance don't require any code changes, which typically requires the application developer to make those changes. So we're saving months, maybe years of development and maintenance. >>Yeah, a lot of gray hairs too, right? Yeah, you're, you're solving a lot of problems there. What about database trends in just in general Hunt, if you will. I mean, this is your space, right? I mean, what we're hearing about from Heindel, you know, in terms of solutions they're providing, but what are you seeing just from the macro level in terms of what people are doing and thinking about the database and how it relates to the cloud? Right. >>And some of the things that we're seeing is that we're seeing an explosion of data, relevant data that customers need to be able to consume and also process as well. So with the explosion of data, there's also, we see customers trying to modernize their application as well through microservices, which does change the design patterns of like the applications we call the access data patterns as well. So again, going back to that, a differentiated heavy lifting, we do have something called purpose built databases, right? It's the right tool for the right purpose. And so it depends on what their like rpo, rto their access to data pattern. Is it a base, is it an acid? So we want to be able to provide them the options to build and also innovate. So with that, that's why we have the Amazon rds, the also the, we also have Redshift, we also have Aurora and et cetera. The Rediff is more of the BI side, but usually when you ingest the data, you have some level of processing to get more insight. So with that, that's why customers are moving more of towards the managed service so that they can give that lift and then focusing on that product and innovation. Yeah. >>Have we kind of caught up or are we catching up to this just the tsunami of data to begin with, right? Because I mean, that was it, you know, what, seven, eight years ago when, when that data became kind of, or becoming king and, and reams and reams and reams and all, you know, can't handle it, right? And, and are we now able to manage that process and manage that flow and get the right data into the right hands at the right time? We're doing better with that. >>I would say that it, it definitely has grown in size of the amount of data that we're ingesting. And so with the scalability and agility of the cloud, we're able to, I would say, adapt to the rapid changes and ingestions of the data. So, so that's why we have things like Aurora servers to have that or auto scale so they can do like MySQL or Postgres and then they can still, like what you know, I'm trying to do is basically don't have to co do like any code changes. It would be a data migration. They still use the same underlying database on also mechanisms, but here we're providing them at scale on the cloud. >>Yeah. Our proxies, they must have for all databases. I mean, is that, is that essential these days? >>Well, good question John. I would say yes. And this is often built in house, as I mentioned, for large companies, they do build some type of data access layer or proxy and, or some utilize some orm, some object relational map to do it. And what again, what we're trying to do is offer this, put this out into the market commercially speaking, such that it can be readily used for, for all the customers to use rather than building it from scratch all the time. >>You know what I didn't ask you was Roy, how does AWS come into play for you then? And, and as in the startup mode, the focus that they've had in startups in general, but in you in particular, I mean, talk about that partnership or that relationship and the value that you're extracting from that. >>The ad AWS partnership has been absolutely wonderful. The collaboration, they have one of the best managed service databases. The value that it that adds in terms of the durability, the manageability, what the Heim doll data does is it compliments Amazon rds, Amazon Redshift very well in the sense that we're not replacing the database. What we're doing is we are allowing the customer to get the most out of the managed service database, whether it be Redshift or Aurora Serverless, rds, all without code changes. And or the analogy that I would give John is a car, a race car may be very fast, but it takes a driver to get to those fast speeds. We're the driver, the Hyundai proxy provides that intelligence so that you can get the most out of that database engine. >>And, and Hfi would then touch on, first off AWS and the emphasis that you have put on startups and are obviously, you know, kind of putting your money where your mouth is, right? With, with the way you've encouraged and nurtured that environment. And they would be about Heim doll in general about where you see this going or what you would like to have, where you want to take this in the next say 12 months, 18 months. >>I think it's more of a better together story of how we can basically coil with our partners, right? And, and basically focusing on helping our customers drive that innovation and be collaboration. So as Heim, as a independent service vendor isv, most customers can leverage that through a marketplace where basically it integrates very nicely with aws. So that gives 'em that lift and it goes back to the undifferentiated heavy lifting on the Hein proxy side, if you will, because then you have this proxy in the middle where then it helps them with their SQL performance. And I've seen use cases where customers were, have some legacy system that they may not have time to modernize the application. So they use this as a lift to keep, keep going as they try to modernize. But also I've seen customers who use are trying to use it as a, a way to give that performance lift because they may have a third party software that they cannot change the code by putting this in there that helps optimize their lines of business or whatever that is, and maybe can be online store or whatever. So I would say it was a better together type of story. >>Yeah. Which is, there's gotta be a song in there somewhere. So peek around the corner and if you wanna be headlights here right now in terms of 12, 18 months, I mean, what, you know, what what next to solve, right? You've already taken, you've slayed a few dragons along the way, but there are others I'm sure is it always happens in innovation in this space. Just when you solve a problem you've just dealt or you have to deal with others that pop up as maybe unintended consequences or at least a new challenge. So what would that be in your world right now? What, what do you see, you know, occupying your sleepless nights here for the next year or so? >>Well, for, for HOMEDALE data, it's all about improving database performance and scale. And those workloads change. We have O ltp, we have OLA with artificial intelligence ml. There's different type of traffic profiles and we're focused on improving those data profiles. It could be unstructured structured. Right now we're focused on structured data, which is relational databases, but there's a lot of opportunity to improve the performance of data. >>Well, you're driving the car, you got a good navigator. I think the GPS is working. So keep up the good work and thank you for sharing the time today. Thank you. Thank you, joy. Do appreciate it. All right, you are watching the cube. We continue our coverage here from AWS Reinvent 22, the Cube, of course, the leader in high tech coverage.

>>And welcome back to the Cube everyone. I'm John Walls to continue our coverage here of AWS Reinvent 22. We're part of the AWS Startup Showcase is the global startup program that AWS so proudly sponsors and with us to talk about what they're doing now in the AWS space. Shaun Knapps, the CEO of AS Send IO and Sean, good to have here with us. We appreciate >>It. Thanks for having me, >>John. Yeah, thanks for the time. First off, gotta show the t-shirt. You caught my attention. Big data is a cluster. I don't think you get a lot of argument from some folks, right? But it's your job to make some sense of it, is it not? Yeah. Tell us about a Send io. >>Sure. As Send IO is a data automation platform. What we do is connect a lot of the, the disparate parts of what data teams do when they create ETL and E o T data pipelines. And we use advanced levels of automation to make it easier and faster for them to build these complex systems and have their world be a little bit less of a, a cluster. >>All right. So let's get into automation a little bit then again, I, your definition of automation and how you're applying it to your business case. >>Absolutely. You know, what we see oftentimes is as spaces mature and evolve, the number of repetitive and repeatable tasks that actually become far less differentiating, but far more taxable if you will, right to the business, start to accumulate as those common patterns emerge. And, and, you know, as we see standardization around tech stacks, like on Amazon and on Snowflake and on data bricks, and as you see those patterns really start to, to formalize and standardize, it opens up the door to basically not have your team have to do all those things anymore and write code or perform the same actions that they used to always have to, and you can lean more on technology to properly automate and remove the, the monotony of those tasks and give your teams greater leverage. >>All right. So, so let's talk about at least maybe your, the journey, say in the past 18 months in terms of automation and, and what have you seen from a trend perspective and how are you trying to address that in order to, to meet that need? >>Yeah, I think the last 18 months have become, you know, really exciting as we've seen both that, you know, a very exciting boom and bust cycle that are driving a lot of other macro behaviors. You know, what we've seen over the last 18 months is far greater adoption of the, the standard, what we call the data planes, the, the architectures around snowflake and data bricks and, and Amazon. And what that's created as a result is the emergence of what I would call is the next problem. You know, as you start to solve that category of how >>You, that's it always works too, isn't >>It? Yeah, exactly. Always >>Works that >>This is the wonderful thing about technology is the job security. There's always the next problem to go solve. And that's what we see is, you know, as we we go into cloud, we get that infinite scale, infinite capacity, capacity, infinite flexibility. And you know, with these modern now data platforms, we get that infinite ability to store and process data incredibly quickly with incredible ease. And so what, what do most organizations do? You take a ton of new bodies, like all the people who wanted to do those like really cool things with data you're like, okay, now you can. And so you start throwing a lot more use cases, you start creating a lot more data products, you start doing a lot more things with data. And this is really where that third category starts to emerge, which is you get this data mess, not mesh, but the data mess. >>You get a cluster cluster, you get a cluster exactly where the complexity skyrockets. And as a result that that rapid innovation that, that you are all looking for and, and promised just comes to a screeching halt as you're just, just like trying to swim through molasses. And as a result, this is where that, that new awareness around automation starts really heightened. You know, we, we did a really interesting survey at the start of this year, did it as a blind survey, independent third party surveyed, 500 chief data officers, data scientists, data architects, and asked them a plethora of questions. But one of the questions we asked them was, do you currently or do you intend on investing in data automation to increase your team's productivity? And what was shocking, and I was very surprised by this, okay, what was shocking was only three and a half percent said they do today. Which is really interesting because it really hones in on this notion of automation is beyond what a lot of a think of, you know, tooling and enhancements today, only three and a half percent today had it, but 88.5% said they intend on making data automation investments in the next 12 months. And that stark contrast of how many people have a thing and how many people want that benefit of automation, right? I think it is incredibly critical as we look to 2023 and beyond. >>I mean, this seems like a no-brainer, does it not? I mean, know it is your business, of course you agree with me, but, but of course, of course what brilliant statement. But it is, it seems like, you know, the more you're, you're able to automate certain processes and then free up your resources and your dollars to be spent elsewhere and your, and your human capital, you know, to be invested elsewhere. That just seems to be a layup. I'm really, I'm very surprised by that three and a half percent figure >>I was too. I actually was expecting it to be higher. I was expecting five to 10%. Yeah. As there's other tools in the, the marketplace around ETL tools or orchestration tools that, that some would argue fit in the automation category. And I think the, what, what the market is telling us based on, on that research is that those themselves are, don't qualify as automation. That, that the market has a, a larger vision for automation. Something that is more metadata driven, more AI back, that takes us a greater leap and of leverage for the teams than than what the, the existing capabilities in the industry today can >>Afford. Okay. So if you got this big leap that you can make, but, but, but maybe, you know, should sites be set a little lower, are you, are you in danger of creating too much of an expectation or too much of a false hope? Because you know, I mean sometimes incremental increases are okay. I >>Agree. I I I think the, you know, I think you wanna do a little bit of both. I think you, you want to have a plan for, for reaching for the stars and you gotta be really pragmatic as well. Even inside of a a suni, we actually have a core value, which is build for 10 x plan for a hundred x and so know where you're going, right? But, but solve the problems that are right in front of you today as, as you get to that next scale. And I think the, the really important part for a lot of companies is how do you think about what that trajectory is and be really smart around where you choose to invest as you, one of the, the scenes that we have is last year's innovation is next year's anchor around your neck. And that's because we, we were in this very fortunately, so this really exciting, rapidly moving innovative space, but the thing that was your advantage not too long ago is everybody can move so quickly now becomes commonplace and a year or two later, if you don't jump on whatever that next innovation is that the industry start to standardize on, you're now on hook paying massive debt and, and paying, you know, you thought you had, you know, home mortgage debt and now you're paying the worst of credit card debt trying to pay that down and maintain your velocity. >>It's >>A whole different kind of fomo, right? I'm fair, miss, I'm gonna miss out. What am I missing out on? What the next big thing exactly been missing out >>On that? And so we encourage a lot of folks, you know, as you think about this as it pertains to automation too, is you solve for some of the problems right in front of you, but really make sure that you're, you're designing the right approach that as you stack on, you know, five times, 10 times as many people building data products and, and you, you're, you're your volume and library of, of data weaving throughout your, your business, make sure you're making those right investments. And that's one of the reasons why we do think automation is so important and, and really this, this next generation of automation, which is a, a metadata and AI back to level of automation that can just achieve and accomplish so much more than, than sort of traditional norms. >>Yeah. On that, like, as far as Dex Gen goes, what do you think is gonna be possible that cloud sets the stage for that maybe, you know, not too long ago seem really outta reach, like, like what's gonna give somebody to work on that 88% in there that's gonna make their spin come your way? >>Ah, good question. So I, I think there's a couple fold. I, you know, I think the, right now we see two things happening. You know, we see large movements going to the, the, the dominant data platforms today. And, and you know, frankly, one of the, the biggest challenges we see people having today is just how do you get data in which is insanity to me because that's not even the value extraction, that is the cost center piece of it. Just get data in so you can start to do something with it. And so I think that becomes a, a huge hurdle, but the access to new technologies, the ability to start to unify more of your data and, and in rapid fashion, I think is, is really important. I think as we start to, to invest more in this metadata backed layer that can connect that those notions of how do you ingest your data, how do you transform it, how do you orchestrate it, how do you observe it? One of the really compelling parts of this is metadata does become the new big data itself. And so to do these really advanced things to give these data teams greater levels of automation and leverage, we actually need cloud capabilities to process large volumes of not the data, but the metadata around the data itself to deliver on these really powerful capabilities. And so I think that's why the, this new world that we see of the, the developer platforms for modern data cloud applications actually benefit from being a cloud native application themselves. >>So before you take off, talk about the AWS relationship part of the startup showcase part of the growth program. And we've talked a lot about the cloud, what it's doing for your business, but let's just talk about again, how integral they have been to your success and, and likewise what you're thinking maybe you bring to their table too. Yeah, >>Well we bring a lot to the table. >>Absolutely. I had no doubt about that. >>I mean, honestly, it, working with with AWS has been truly fantastic. Yep. You know, I think, you know, as a, a startup that's really growing and expanding your footprint, having access to the resources in AWS to drive adoption, drive best practices, drive awareness is incredibly impactful. I think, you know, conversely too, the, the value that Ascend provides to the, the AWS ecosystem is tremendous leverage on onboarding and driving faster use cases, faster adoption of all the really great cool, exciting technologies that we get to hear about by bringing more advanced layers of automation to the existing product stack, we can make it easier for more people to build more powerful things faster and safely. Which I think is what most businesses at reinvent really are looking for. >>It's win-win, win-win. Yeah. That's for sure. Sean, thanks for the time. Thank you John. Good job on the t-shirt and keep up the good work. Thank you very much. I appreciate that. Sean Na, joining us here on the AWS startup program, part of their of the Startup Showcase. We are of course on the Cube, I'm John Walls. We're at the Venetian in Las Vegas, and the cube, as you well know, is the leader in high tech coverage.

>>And good afternoon. Welcome back here on the Cub as to continue our coverage at aws Reinvent 22, win the Venetian here in Las Vegas, day two, it's Wednesday. Thanks. Still rolling. Quite a along. We have another segment for you as part of the Global Startup program, which is under the AWS Startup Showcase. I'm joined now by Vink at Viera, who is the CEO and co-founder of R Set. And good to see you, >>Sir. Thanks for having me here. Yeah, >>No, a real pleasure. Looking forward to it. So first off, for some of, for yours who might not be familiar with Roxette, I know you've been on the cube a little bit, so you're, you're an alum, but, but why don't you set the stage a little bit for Rock set and you know, where you're engaged with in terms of, with aws? >>Definitely. Rock Set is a realtime analytics database that is built for the cloud. You know, we make realtime applications possible in the cloud. You know, realtime applications need high concurrency, low latency query processing data needs to be fresh, your analytic needs to be fast. And, you know, we built on aws and that's why we are here. We are very, very proud partners of aws. We are in the AWS Accelerate program, and also we are in the startup program of aws. We are strategic ISV partner. And so yeah, we make real time analytics possible without all the cost and complexity barriers that are usually associated with it. And very, very happy to be part of this movement from batch to real time that is happening in the world. >>Right. Which is certainly an exciting trend. Right. I know great news for you, you made news yesterday, had an announcement involved with the intel with aws, who wants to share some of that >>With us too? Definitely. So, you know, one, one question that I always ask people is like, you know, if you go perspective that I share is like, if you go ask a hundred people, do you want fast analytics on fresh data or slow analytics on stale data? You know, a hundred out of a hundred would say fast and fresh, right? Sure. So then the question is, why hasn't this happened already? Why is this still a new trend that is emerging as opposed to something that everybody's taking for granted? It really comes down to compute efficiency, right? I think, you know, at the end of the day, real time analytics was always in using, you know, technologies that are, let's say 10 years ago using let's say processors that were available 10 years ago to, you know, three cloud, you know, days. There was a lot of complexity barriers associated with realtime analytics and also a lot of cost and, and performance barriers associated with it. >>And so Rox said from the, you know, from the very beginning, has been obsessing about building the most compute efficient realtime database in the world. And, you know, AWS on one hand, you know, allows us to make a consumption based pricing model. So you only pay for what you use. Sure. And that shatters all the cost barriers. But in terms of computer efficiency, what we announced yesterday is the Intel's third generation Zon scalable processors, it's code named Intel Ice Lake. When we port it over Rock said to that architecture, taking advantage of some of the instructions sets that Intel has, we got an 84% performance boost, 84, 84, 84. >>It's, it's incredible, right? >>It's, it's an incredible charts, it's an incredible milestone. It reduces the barrier even more in terms of cost and, you know, and, and pushes the efficiency and sets a, a really new record for how efficient realtime, you know, data processing can be in the cloud. And, and it's very, very exciting news. And so we used to benchmark ourselves against some of our other, you know, realtime, you know, did up providers and we were already faster and now we've set a, a much, much higher bar for other people to follow. >>Yep. And, and so what is, or what was it about real time that, that, you know, was such a barrier because, and now you've got the speed of, of course, obviously, and maybe that's what it was, but I think cost is probably part of that too, right? That's all part of that equation. I mean, real time, so elusive. >>Yeah. So real time has this inherent pattern that your data never stops coming. And when your data never stops coming, and you can now actually do analytics on that. Now, initially people start with saying, oh, I just want a real time dashboard. And then very quickly they realize, well, the dashboard is actually in real time. I'm not gonna be staring at the 24 7. Can you tap on my shoulder when something is off, something needs to be looked at. So in which case you're constantly also asking the question, is everything okay? Is everything all right? Do I need to, is is that something that I need to be, you know, double clicking on and, and following up on? So essentially very quickly in real time analytics, what happens is your queries never stop. The questions that you're asking on your data never stops. And it's often a program asking the question to detect anomalies and things like that. >>And your data never stops coming. And so compute is running 24 7. If you look at traditional data warehouses and data lakes, they're not really optimized for these kinds of workloads. They're optimized to store massive volumes of data and in a storage efficient format. And when an analyst comes and asks a question to generate a report, you can spin up a whole bunch of compute, generate the report and tear it all down when you're done. Well, that is not compute running 24 7 to continuously, you know, you know, keep ingesting the data or continuously keep answering questions. So the compute efficiency that is needed is, is much, much, much higher. Right? And that is why, you know, Rox was born. So from the very beginning, we're only built, you know, for these use cases, we have a, an extremely powerful SQL engine that can give you full feature SQL analytics in a very, very compute efficient way in the cloud. >>Right. So, so let's talk about the leap that you've made, say in the last two years and, and, and what's been the spur of that? What has been allowed you to, to create this, you know, obviously a, a different kind of an array for your customers from which to choose, but, but what's been the spark you think >>We touched upon this a little earlier, right? This spark is really, you know, the world going from batch to real time. So if you look at mainstream adoption of technologies like Apache, Kafka and Confluent doing a really good job at that. In, in, in growing that community and, and use cases, now businesses are now acquiring business data, really important business data in real time. Now they want to operationalize it, right? So, you know, extract based static reports and bi you know, business intelligence is getting replaced in all modern enterprises with what we call operational intelligence, right? Don't tell me what happened last quarter and how to plan this quarter better. Tell me what's happening today, what's happening right now. And it's, it's your business operations using data to make day to day decisions better that either grows your top line, compresses your bottom line, eliminates risk that are inherently creeping up in your business. >>Sure. You know, eliminate potential churn from a customer or fraud, you know, deduction and, and getting on top of, you know, that, you know, a minute into this, into, into an outage as opposed to an hour into the outage. Right? And so essentially I think businesses are now realizing that operational intelligence and operational analytics really, you know, allows them to leverage data and especially real time data to make their, you know, to grow their businesses faster and more efficiently. And especially in this kind of macro environment that is, you know, more important to have better unit economics in your business than ever before. Sure. And so that is really, I think that is the real market movement happening. And, and we are here to just serve that market. We are making it much, much easier for companies that have already adopted, you know, streaming technologies like Kafka and, and, and knows Canis MSK and all these technologies. Now businesses are acquiring these data in real time now. They can also get realtime analytics on the other end of it. Sure. >>You know, you just touched on this and, and I'd like to hear your thoughts about this, about, about the economic environment because it does drive decisions, right? And it does motivate people to look for efficiencies and maybe costs, you know, right. Cutting costs. What are you seeing right now in terms of that, that kind of looming influence, right? That the economy can have in terms of driving decisions about where investments are being made and what expectations are in terms of delivering value, more value for the buck? >>Exactly. I think we see across the board, all of our customers come back and tell us, we don't want to manage data infrastructure and we don't want to do kind of DIY open source clusters. We don't wanna manage and scale and build giant data ops and DevOps teams to manage that, because that is not really, you know, in their business. You know, we have car rental companies want to be better at car rentals, we want airlines to be a better airline, and they don't, don't want their, you know, a massive investment in DevOps and data ops, which is not really their core business. And they really want to leverage, you know, you know, fully managed and, you know, cloud offerings like Rock said, you know, built on aws, massively scalable in the cloud with zero operational overhead, very, very easy to get started and scale. >>And so that completely removes all the operational overhead. And so they can invest the resources they have, the manpower, they have, the calories that they have on actually growing their businesses because that is what really gonna allow them to have better unit economics, right? So everybody that is on my payroll is helping me grow my top line or shrink my bottom line, eliminate risk in my business and, and, and, and churn and, and fraud and other, and eliminate all those risks that are inherent in my business. So, so that is where I think a lot of the investments going. So gone are the days where, you know, you're gonna have these in like five to 10% team managing a very hard to operate, you know, open source data management clusters on EC two nodes in, in AWS and, and kind of DIYing it their way because those 10 people, you know, if all they do is just operational maintenance of infrastructure, which is a means to an end, you're way better off, you know, using a cloud, you know, a bond in the cloud built for the cloud solution like rock and eliminate all that cost and, and replace that with an operationally much, much simpler, you know, system to op, you know, to to work with such as, such as rock. >>So that is really the big trend that we are seeing why, you know, not only real time is going more and more mainstream cloud native solutions or the real future even when it comes to real time because the complexity barrier needs to be shattered and only cloud native solutions can actually, >>You get the two Cs cost and complexity, right. That you, you need to address. Exactly. Yeah, for sure. You know, what is it about building trust with your, with your clients, with your partners? Because you, you're talking about this cloud environment that, that everyone is talking about, right? Not everyone's made that commitment. There are still some foot draggers out there. How are you going about establishing confidence and establishing trust and, and, and providing them with really concrete examples of the values and the benefits that you can provide, you know, with, with these opportunities? >>So, you know, I grew up, so there's a few ways to to, to answer this question. I'll, I'll, I'll come, I'll cover all the angles. So in, in order to establish trust, you have to create value. They, you know, your customer has to see that with you. They were able to solve the problem faster, better, cheaper, and they're able to, you know, have a, the business impact they were looking for, which is why they started the project in the first place. And so establishing that and proving that, I think there's no equivalence to that. And, you know, I grew up at, at, you know, at Facebook back in the day, you know, I was managing online data infrastructure, okay. For Facebook from 2007 and 2015. And internally we always had this kind of culture of all the product teams building on top of the infrastructure that my team was responsible for. >>And so they were not ever, there was never a, a customer vendor relationship internally within Facebook that we're all like, we're all part of the same team. We're partnering here to have you, you know, to help you have a successful product launch. There's a very similar DNA that, that exists in Rock said, when our customers work with us and they come to us and we are there to make them successful, our consumption based pricing model also forces us to say they're not gonna really use Rock said and consume more. I mean, we don't make money until they consume, right? And so their success is very much integral part of our, our success. And so that I think is one really important angle on, you know, give us a shot, come and do an evaluation, and we will work with you to build the most efficient way to solve your problem. >>And then when you succeed, we succeed. So that I think is a very important aspect. The second one is AWS partnership. You know, we are an ISV partner, you know, AWS a lot of the time. That really helps us establish trust. And a lot of the time, one of the, the, the people that they look up to, when a customer comes in saying, Hey, what is, who is Rock? Said? You know, who are your friends? Yeah. Who are your friends? And then, you know, and then the AWS will go like, oh, you know, we'll tell you, you know, all these other successful case studies that R has, you know, you know, built up on, you know, the world's largest insurance provider, Europe's largest insurance provider. We have customers like, you know, JetBlue Airlines to Klarna, which is a big bator company. And so, so all these case studies help and, and, and, and platform and partners like AWS helps us, helps you amplify that, that, you know, and, and, and, and, and give more credibility. And last but not least, compliance matters. You know, being Soto type two compliant is, is a really important part of establishing trust. We are hip hop compliant now so that, you know, we can, you know, pi I phi data handling that. And so I think that will continue to be a part, a big part of our focus in improving the security, you know, functionality and, and capabilities that R set has in the cloud, and also compliance and, and the set of com, you know, you know, standards that we are gonna be compliant against. >>Well, I'm glad you hit on the AWS too, cause I did wanna bring that up. I, I appreciate that and I know they appreciate the relationship as well. Thanks for the time here. It's been a pleasure. Awesome. Learning about Rockette and what you're up to. Thank you. >>You bet. >>It's a pleasure. Thank you. Vi ka. All right. You are watching the cube coverage here at AWS Reinvent 22. And on the cube, of course, the leader, the leader in high tech coverage.

(upbeat music) >> Hi everybody. Welcome back to theCUBE as to continue our coverage here at AWS re:Invent '22. We're in the Venetian. Out in Las Vegas, it is Wednesday. And the PaaS is still happening. I can guarantee you that. We continue our series of discussions as part of the "AWS Startup Showcase". This is the "Global Startup Program", a part of that showcase. And I'm joined by two gentlemen today who are going to talk about what CoreStack is up to. One of them is Ez Natarajan, who is the Founder and CEO. Good to have you- (simultaneous chatter) with us today. We appreciate it. Thanks, EZ. >> Nice to meet you, John. >> And Brad Winney who is the area Sales Leader for startups at AWS. Brad, good to see you. >> Good to see you, John. >> Thanks for joining us here on The Showcase. So Ez, first off, let's just talk about CoreStack a little bit for people at home who might not be familiar with what you do. It's all about obviously data, governance, giving people peace of mind, but much deeper than that. I'll let you take it from there. >> So CoreStack is a governance platform that helps customers maximize their cloud usage and get governance at scale. When we talk about governance, we instill confidence through three layers: solving the problems of the CIO, solving the problems of the CTO, solving the problems of the CFO, together with a single pin of class,- >> John: Mm-hmm. >> which helps them achieve continuous holistic automated outcomes at any given time. >> John: Mm-hmm. So, Brad, follow up on that a little bit- >> Yeah. because Ez touched on it there that he's got a lot of stakeholders- >> Right. >> with a lot of different needs and a lot of different demands- >> Mm-hmm. >> but the same overriding emotion, right? >> Yeah. >> They all want confidence. >> They all want confidence. And one of the trickiest parts of confidence is the governance issue, which is policy. It's how do we determine who has access to what, how we do that scale. And across not only start been a process. This is a huge concern, especially as we talked a lot about cutting costs as the overriding driver for 2023. >> John: Mm-hmm. >> The economic compression being what it is, you still have to do this in a secure way and as a riskless way as possible. And so companies like CoreStack really offer core, no pun intended, (Ez laughs) function there where you abstract out a lot of the complexity of governance and you make governance a much more simple process. And that's why we're big fans of what they do. >> So we think governance from a three dimensional standpoint, right? (speaks faintly) How do we help customers be more compliant, secure, achieve the best performance and operations with increased availability? >> Jaohn: Mm-hmm. >> At the same time do the right spend from a cost standpoint. >> Interviewer: Mm-hmm. So when all three dimensions are connected, the business velocity increases and the customer's ability to cater to their customers increase. So our governance tenants come from these three pillars of finance operations, security operations and air operations at cloud operations. >> Yeah. And... Yeah. Please, go ahead. >> Can I (indistinct)? >> Oh, I'm sorry. Just- >> No, that's fine. >> So part of what's going on here, which is critical for AWS, is if you notice a lot of (indistinct) language is at the business value with key stakeholders of the CTO, the CSO and so on. And we're doing a much better job of speaking business value on top of AWS services. But the AWS partners, again, like CoreStack have such great expertise- >> John: Mm-hmm. >> in that level of dialogue. That's why it's such a key part for us, why we're really interested partnering with them. >> How do you wrestle with this, wrestle may not be the right word, but because you do have, as we just went through these litany, these business parts of your business or a business that need access- >> Ez: Mm-hmm. >> and that you need to have policies in place, but they change, right? I mean, and somebody maybe from the financial side should have a window into data and other slices of their business. There's a lot of internal auditing. >> Man: Mm-hmm. >> Obviously, it's got to be done, right? And so just talk about that process a little bit. How you identify the appropriate avenues or the appropriate gateways for people to- >> Sure. >> access data so that you can have that confidence as a CTO or CSO, that it's all right. And we're not going to let too much- >> out to the wrong people. >> Sure. >> Yeah. So there are two dimensions that drive the businesses to look for that kind of confidence building exercise, right? One, there are regulatory external requirements that say that I know if I'm in the financial industry, I maybe need to following NIST, PCI, and sort of compliances. Or if I'm in the healthcare industry, maybe HIPAA and related compliance, I need to follow. >> John: Mm-hmm. >> That's an external pressure. Internally, the organizations based on their geographical presence and the kind of partners and customers they cater to, they may have their own standards. And when they start adopting cloud; A, for each service, how do I make sure the service is secure and it operates at the best level so that we don't violate any of the internal or external requirements. At the same time, we get the outcome that is needed. And that is driven into policies, that is driven into standards which are consumable easily, like AWS offers well-architected framework that helps customers make sure that I know I'm architecting my application workloads in a way that meets the business demands. >> John: Mm-hmm. >> And what CoreStack has done is taken that and automated it in such a way it helps the customers simplify that process to get that outcome measured easily so they get that confidence to consume more of the higher order services. >> John: Okay. And I'm wondering about your relationship as far with AWS goes, because, to me, it's like going deep sea fishing and all of a sudden you get this big 4, 500 pound fish. Like, now what? >> Mm-hmm. >> Now what do we do because we got what we wanted? So, talk about the "Now what?" with AWS in terms of that relationship, what they're helping you with, and the kind of services that you're seeking from them as well. >> Oh, thanks to Brad and the entire Global Startup Ecosystem team at AWS. And we have been part of AWS Ecosystem at various levels, starting from Marketplace to ISV Accelerate to APN Partners, Cloud Management Tools Competency Partner, Co-Sell programs. The team provides different leverages to connect to the entire ecosystem of how AWS gets consumed by the customers. Customers may come through channels and partners. And these channels and partners maybe from WAs to MSPs to SIs to how they really want to use each. >> John: Mm-hmm. >> And the ecosystem that AWS provides helps us feed into all these players and provide this higher order capability which instills confidence to the customers end of the day. >> Man: Absolutely. Right. >> And this can be taken through an MSP. This can be taken through a GSI. This can be taken to the customer through a WA. And that's how our play of expansion into larger AWS customer base. >> Brad: Yeah. >> Brad, from your side of the fence. >> Brad: No, its... This is where the commons of scale come to benefit our partners. And AWS has easily the largest ecosystem. >> John: Mm-hmm. >> Whether or not it's partners, customers, and the like. And so... And then, all the respective teams and programs bring all those resources to bear for startups. Your analogy of of catching a big fish off coast, I actually have a house in Florida. I spend a lot of time there. >> Interviewer: Okay. >> I've yet to catch a big 500 pound fish. But... (interviewer laughs) >> But they're out there. >> But they're definitely out there. >> Yeah. >> And so, in addition to the formalized programs like the Global Partner Network Program, the APN and Marketplace, we really break our activities down with the CoreStacks of the world into two major kind of processes: "Sell to" and "Sell with". And when we say "Sell to", what we're really doing is helping them architect for the future. And so, that plays dividends for their customers. So what do we mean by that? We mean helping them take advantage of all the latest serverless technologies: the latest chip sets like Graviton, thing like that. So that has the added benefit of just lowering the overall cost of deployment and expend. And that's... And we focus on that really extensively. So don't ever want to lose that part of the picture of what we do. >> Mm-hmm. >> And the "Sell with" is what he just mentioned, which is, our teams out in the field compliment these programs like APN and Marketplace with person-to-person in relationship development for core key opportunities in things like FinTech and Retail and so on. >> Interviewer: Mm-hmm. >> We have significant industry groups and business units- >> Interviewer: Mm-hmm. >> in the enterprise level that our teams work with day in and day out to help foster those relationships. And to help CoreStack continue to develop and grow that business. >> Yeah. We've talked a lot about cost, right? >> Yeah. >> But there's a difference between reducing costs or optimizing your spend, right? I mean there- >> Brad: Right. >> Right. There's a... They're very different prism. So in terms of optimizing and what you're doing in the data governance world, what kind of conversations discussions are you having with your clients? And how is that relationship with AWS allowing you to go with confidence into those discussions and be able to sell optimization of how they're going to spend maybe more money than they had planned on originally? >> So today, because of the extra external micro-market conditions, every single customer that we talk to wanting to take a foster status of, "Hey, where are we today? How are we using the cloud? Are we in an optimized state?" >> Interviewer: Mm-hmm. >> And when it comes to optimization, again, the larger customers that we talk to are really bothered about the business outcome and how their services and ability to cater to their customers, right? >> Interviewer: Mm-hmm. >> They don't want to compromise on that just because they want to optimize on the spend. That conversation trickled down to taking a poster assessment first, and then are you using the right set of services within AWS? Are the right set of services being optimized for various requirements? >> Interviewer: Mm-hmm. >> And AWS help in terms of catering to the segment of customers who need that kind of a play through the patent ecosystem. >> John: Mm-hmm. Yeah. We've talked a lot about confidence too, cloud with confidence. >> Brad: Yeah. Yeah. >> What does that mean to different people, you think? I mean, (Brad laughing) because don't you have to feel them out and say "Okay. What's kind of your tolerance level for certain, not risks, but certain measures that you might need to change"? >> I actually think it's flipped the other way around now. I think the risk factor- >> Okay. >> is more on your on-prem environment. And all that goes with that. 'Cause you... Because the development of the cloud in the last 15 years has been profound. It's gone from... That's been the risky proposition now. With all of the infrastructure, all the security and compliance guardrails we have built into the cloud, it's really more about transition and risk of transition. And that's what we see a lot of. And that's why, again, where governance comes into play here, which is how do I move my business from on-prem in a fairly insecure environment relatively speaking to the secure cloud? >> Interviewer: Sure. >> How do I do that without disrupting business? How do I do that without putting my business at risk? And that's a key piece. I want to come back, if I may, something on cost-cutting. >> Interviewer: Sure. >> We were talking about this on the way up here. Cost-cutting, it's the bonfire of the vanities in that in that everybody is talking about cost-cutting. And so we're in doing that perpetuating the very problem that we kind of want to avoid, which is our big cost-cutting. (laughs) So... And I say that because in the venture capital community, what's happening is two things: One is, everybody's being asked to extend their runways as much as possible, but they are not letting them off the hook on growth. And so what we're seeing a lot of is a more nuanced conversation of where you trim your costs, it's not essential, spend, but reinvest. Especially if you've got good strong product market fit, reinvest that for growth. And so that's... So if I think about our playbook for 2023, it's to help good strong startups. Either tune their market fit or now that they good have have good market fit, really run and develop their business. So growth is not off the hook for 2023. >> And then let me just hit on something- >> Yeah. >> before we say goodbye here that you just touched on too, Brad, about. How we see startups, right? AWS, I mean, obviously there's a company focus on nurturing this environment of innovation and of growth. And for people looking at maybe through different prisms and coming. >> Brad: Yeah. >> So if you would maybe from your side of the fence, Ez from CoreStack, about working as a startup with AWS, I mean, how would you characterize that relationship about the kind of partnership that you have? And I want to hear from Brad too about how he sees AWS in general in the startup world. But go ahead. >> It's kind of a mutually enriching relationship, right? The support that comes from AWS because our combined goal is help the customers maximize the potential of cloud. >> Interviewer: Mm-hmm. >> And we talked about confidence. And we talked about all the enablement that we provide. But the partnership helps us get to the reach, right? >> Interviewer: Mm-hmm. >> Reach at scale. >> Interviewer: Mm-hmm. We are talking about customers from different industry verticals having different set of problems. And how do we solve it together so that like the reimbursement that happens, in fact healthcare customers that we repeatedly talk to, even in the current market conditions, they don't want to save. They want to optimize and re-spend their savings using more cloud. >> Interviewer: Mm-hmm. >> So that's the partnership that is mutually enriching. >> Absolutely. >> Yeah. To me, this is easy. I think the reason why a lot of us are here at AWS, especially the startup world, is that our business interests are completely aligned. So I run a pretty significant business unit in a startup neighbor. But a good part of my job and my team's job is to go help cut costs. >> Interviewer: Mm-hmm. >> So tell me... Show me a revenue responsibility position where part of your job is to go cut cost. >> Interviewer: Right. >> It's so unique and we're not a non-profit. We just have a very good long-term view, right? Which is, if we help companies reduce costs and conserve capital and really make sure that that capital is being used the right way, then their long-term viability comes into play. And that's where we have a chance to win more of that business over time. >> Interviewer: Mm-hmm. >> And so because those business interests are very congruent and we come in, we earn so much trust in the process. But I think that... That's why I think we being AWS, are uniquely successful startups. Our business interests are completely aligned and there's a lot of trust for that. >> It's a great success story. It really is. And thank you for sharing your little slice of that and growing slice of that too- >> Yeah. Absolutely. >> from all appearances. Thank you both. >> Thank you, John. >> Thank you very much, John. >> Appreciate your time. >> This is part of the AWS Startup Showcase. And I'm John Walls. You're watching theCUBE here at AWS re:Invent '22. And theCUBE, of course, the leader in high tech coverage.

>>Well, hello everybody at John Wallace here on the Cube, and glad to have you along here for day two of our coverage here at AWS Reinvent 22. We're up in the global startup program, which is part of AWS's Startup Showcase, and I've got Kevin Farley with me. He is the director of Strategic Alliances with Maria Day db. And Kevin, good to see you this morning. Good to see you, John. Thanks for joining us. Thank >>You. >>Appreciate it. Yeah. First off, tell us about Maria db. Sure. Obviously data's your thing. Yep. But to share that with some folks at home who might not be familiar with your offering. >>Yeah. So Maria DB's been around as a corporate entity for 10 plus years, and we have a massive customer base. You know, there's a billion downloads from Docker Hub, 75% of the Fortune 500. We have an enormous sea of really happy users. But what we realize is that all of these users are really thinking about what do we, what does it mean to transform it? What does cloud modernization mean? And how do we build a strategy on something we really love to drive it into the cloud and take it to the future. So what we launched about two years ago, two and a half years ago, is Skye. It's our database as a service. It leverages all the best elements, what we provide on the enterprise platform. It marries to the AWS cloud, and it really provides the best of both worlds for our >>Customers. So in your thought then, what, what problem is that solving? >>I think what you see in the overall database market is that many people have been using what we would call legacy technology. There's been lots of sort of stratification and mixes of different database solutions. All of them come with some promise, and all of 'em come with a lot of compromise. So I think what the market is really looking for is something that can take what they know and love, can bring it to the cloud and can survive the port drive the performance and scale. That completely changes the landscape, especially as you think about what modern data needs look like, right? What people did 10 years ago with the exponential scale of data no longer works. And what they need is something that not only can really deliver against their core business values and their core business deliverables, but gets 'em to the future. How do we drive something new? How do we innovate? How do we change the game? And I think what we built with AWS really delivers what we call cloud scale. It's taking something that is the best technology, and I as a V can build, marrying it to, you know, Kubernetes layer, marrying it to global availability, thinking about having true global high availability across all of your environments and really delivering that to customers through an integrated partnership. >>Could we see this coming? I mean, because you know data, right? I mean, yeah, we, we, everybody talked about the tsunami of growth, you know, >>Back 10 >>Sure. 11 years ago. But, but maybe the headlights didn't go far enough or, or, but, but you could see that there was going to be crunch time. >>There's no doubt. And I think that this has been a, there's, there's been these sort of pocket solutions, right? So if you think at the entire no sequel world, right? People said, oh, I need scale, I can get it, but what do I have to give up asset compliance? So I have to change the way I think about what data is and how I, I can govern it. So there's been these things that deliver on half the promise, but there's never been something that comes together and really drives what we deliver through CIQ is something called expand. So distributed SQL really tied to the SQL Query language, having that asset data. So having everything you need without the compromise built on the cloud allows you to scale out and allows you to think about, I can actually do exponential layers of, of data, data modeling, data querying, complete read, write, driving that forward. And I think it gives us a whole nother dynamic that we can deliver on in a way that hasn't been before. And I think that's kind of the holy grail of what people are looking for is how am I building modern applications and how do I have a database in the cloud that's really gonna support >>It? You know, you talk about distributed, you know, sequel and, and I mean, there's a little mystery behind it, isn't there? Or at least maybe not mystery. There's a little, I guess, confusion or, or just misunderstanding. I mean, I, how, nail that down a little bit. I >>Would say the best way to say it, honestly, this is the great thing, is it people believe it's too good to be true. And I think what we see over and over >>Again, you know, what they say about that. >>But this is the great part is, you know, you know, we've just had two taste studies recently with aws, with HIT labs and Certified power, both on expand, both proof in the pudding. They did the POCs, they're like, oh my God, this works. If you watch the keynote yesterday, you know, Adam had a slide that was, you know, as big as the entire room and it highlighted Samsung and they said, you know, we're doing 80,000 requests per second. So the, you know, the story there is that AWS is able as, as an entity with their scale and their breadth to handle that kind of workload. But guess what that is? That's MariaDB expand underneath there driving all of that utilization. So it's already there, it's already married, it's already in the cloud, and now we're taking it to a completely different level with a fully managed database solution. Right? >>How impressive is that? Right? I mean, you would think that somebody out there who, I mean that that volume, that kind of capacity is, is mind blowing. >>I mean, to your kind of previous point, it's like one of those things, do I see what's coming and it's here, right? You know, it's, is it actually ever gonna be possible? And now we're showing that it really is on a daily basis for some of the biggest brands in the world. We're also seeing companies moving off not only transitioning from, you know, MariaDB or myse, but all of the big licensed, you know, conversions as well. So you think about Oracle DBS Bank is one of our biggest customers, one of the largest Oracle conversions in the world onto MariaDB. And now thinking about what is the promise of connecting that to the cloud? How do you take things that you're currently doing, OnPrem delivering a hybrid model that also then starts to say, Hey, here's my path to cloud modernization. Skye gives me that bridge. And then you take it one layer farther and you think about multi-cloud, right? That's one of the things that's critical that ISVs can really only deliver in a meaningful way, is how can we have a solution for a customer that we can take to any availability zone. We can have performance, proximity, cost, proximity. We're always able to have that total data dexterity across any environment we need and we can build on that for the future. >>So if, if we're talking about cloud database and there's so many good things going forward here. You're talking about easy use and scalability and all that. But as with ever have you talked about this, there's some push and there's some pull. Yeah. So, so what's the, what's the other side that's still, you know, you that you think has to be >>Addressed? And I think that's a great question. So there's, we see that there's poll, right? We've seen these deals, this pipeline growth, this, there's great adoption. But what I think we're still not at the point of massive hockey stick adoption is that customers still don't fully understand the capabilities distributed SQL and the power they can actually deliver. So the more we drive case studies, the more we drive POCs, the more we prove the model, I think you're gonna see just a massive adoption scale. And I also think customers are tired of doing lots of different things in lots of different pockets. So neither one of the key elements of Sky SQL is we can do both transactional and analytical data out of the same database driven by the same proxy. So what, instead of having DBAs and developers try to figure out, okay, I'm gonna pull from this database here. >>Yeah. That there, it's, it's this big spaghetti wire concept that is super expensive and super time intensive. So the ability to write modern applications and pull data from both pockets and really be able to have that as a seamless entity and deliver that to customers is massive. I mean, another part of the keynote yesterday was a new deliverable, like kind of no etl. Adam talked about Aurora and Redshift and the massive complexity of what used to exist for getting data back and forth. You also have to pay for two different databases. It's super expensive. So I think the idea that you can take the real focus of AWS and US is customer value. How do you deliver that next thing that changes the game? Always utilizes AWS delivers on that promise, but then takes a net new technology that really starts to think about how do we bring things together? How do we make it more simple? How do we make it more powerful? And how do we deliver more customer value as we go forward? >>But you know, if, if I'm, I'm still an on-prim guy, just pretend I'm not saying I am. Just pretend I just for the sake of the discussion here, it's like I just can't let it go. Yeah. Right. I, I still, you know, there's control, there's the known versus the unknown. The uncertain. Yeah. So twist my arm just a little bit more and get me over the hum. >>Well, first of all, you don't have to, right? And there's gonna be some industries and some verticals that will always have elements of their business that will be OnPrem. Guess what? We make the best based in the world. It can be MariaDB, but there's those that then say, these, these elements of our business are gonna be far more effective moving to the cloud. So we give you Skye, there's a natural symbiotic bridge between everything we do and how we deliver it. Where you can be hybrid and it's great. You can adopt the cloud as your business needs grow. And you can have multi-cloud. This is that, that idea that you can, can have your cake and eat it too, right? You can literally have all these elements of your business met without these big pressure to say, you gotta throw that away. You gotta move to this. It's really, how do you kind of gracefully adopt the cloud in a way that makes sense for your business? Where are you trying to drive your business? Is it time to value, right? Is it governance? Is it is there's different elements of what matters the most to individual businesses. You know, we wanna address those and we can address >>Those. So you're saying you don't have to dive >>In, you don't have to dive >>In. You, you can, you can go ankle deep, knee deep, whatever you wanna >>Do. Absolutely. And you know, some of the largest MariaDB users still have massive, massive on-prem implementations. And that's okay. But there's elements that are starting to fall behind. There's cost savings, there's things that they need to do in the cloud that they can't do. OnPrem. And that's where expand Skye really says, okay, here is your platform. Grow as you want to, migrate as you want to. And we're there every step along the way. We, we also provide a whole Sky DBA team. Some guys just say, I wanna get outta the database world at all. This is, this is expensive, it's costly and it's difficult to be an expert. So you can bring in our DBA team and they'll man and run, they'll, they'll run your entire environment. They'll optimize it, you know, they'll troubleshoot it, they'll bug fix, they'll do everything for you. So you can just say, I just wanna focus on building phenomenal applications for my customers. And the database game as we knew it is not something that I know I want to invest in anymore. Right. I wanna make that transition >>That makes that really, yeah. You know, I mean really attractive to a lot of people because you are, you talk about a lot of headache there. Yeah. So let's talk about AWS before Sure. I let you go just about that relationship. Okay. You've talked about the platform that it provides you and, and obviously the benefits, but just talk about how you've worked with AWS over the years Yep. And, and how you see that relationship allowing you to expand your services, no pun intended. >>For sure. So, I mean, I would start with the way we even contemplated architecture. You know, we worked with the satisfactory team. We made sure that the things that we built were optimized in their environment. You know, I think it was a lot of collaboration on how does this combined entity really make the most value for our customers? How does it make the most sense for our developers as we build it out? Then we work in the, in the global startup team. So the strategic element of who we are, not all startups are created equal, right? We have, right, we have 75% of the Fortune 100, we've got over a billion downloads. So, you know, we come in with promise. And the reason this partnership is so valuable and the reason there's so much investment going forward is cuz what really, what do the cloud guys care about? >>The very, very most, they want all of these mission critical, big workloads that are on prem to land in their cloud. What do we have a massive, massive TAM sitting out there, these customers that could go to aws. So we both see, like if we can deliver incredible value to that customer base, these big workloads will end up in aws. They'll use other AWS services. And as we scale and grow, you know, we have that platform that's already built for it. So I think that when you go back to like the tenants, the core principles of aws, the one that always stands out, the one that we always kind of lean back on is, are we delivering customer value? Is this the best thing for the customer? Because we do have some competition just like many other, other partners do, right? So there is Aurora and there is rds and there is times when that's a great service for a customer. But when people are really thinking about where do I need my database to go? Where do I really need to be set for the future growth? Where am I gonna get the kind of ROI I need going forward? That's where you can go, Hey, sky sql, expand distributed sql. This is the best game in town. It's built on aws and collectively, you know, we're gonna present that to a customer. I'm >>Sold. Done. >>I love it. Right? >>Maria db, check 'em out, they're on the show floor. Great traffic. I know at at the, at the booth. They're here at AWS Reinvent. So check 'em out. Maria db. Thanks >>Kevin. Hey, thanks John. Appreciate your >>Time. Appreciate Great. That was great. Right back with more, you're watching the cube, the leader in high tech coverage.

>>Hey everyone. Welcome to the cubes presentation of the AWS startup showcase. This is season two, episode four of our ongoing series. That's featuring exciting startups within the AWS ecosystem. This theme, cybersecurity protect and detect against threats. I'm your host. Lisa Martin. I've got two guests here with me. Please. Welcome back to the program. Sam Kam, a COO and co-founder of security scorecard and bar Roth. Charri team lead solutions marketing at confluent guys. It's great to have you on the program talking about cybersecurity. >>Thanks for having us, Lisa, >>Sam, let's go ahead and kick off with you. You've been on the queue before, but give the audience just a little bit of context about security scorecard or SSC as they're gonna hear it referred to. >>Yeah. AB absolutely. Thank you for that. Well, the easiest way to, to put it is when people wanna know about their credit risk, they consult one of the major credit scoring companies. And when companies wanna know about their cybersecurity risk, they turn to security scorecard to get that holistic view of, of, of the security posture. And the way it works is SSC is continuously 24 7 collecting signals from across the entire internet. I entire IPV four space and they're doing it to identify vulnerable and misconfigured digital assets. And we were just looking back over like a three year period. We looked from 2019 to 2022. We, we, we assessed through our techniques over a million and a half organizations and found that over half of them had at least one open critical vulnerability exposed to the internet. What was even more shocking was 20% of those organizations had amassed over a thousand vulnerabilities each. >>So SSC we're in the business of really building solutions for customers. We mine the data from dozens of digital sources and help discover the risks and the flaws that are inherent to their business. And that becomes increasingly important as companies grow and find new sources of risk and new threat vectors that emerge on the internet for themselves and for their vendor and business partner ecosystem. The last thing I'll mention is the platform that we provide. It relies on data collection and processing to be done in an extremely accurate and real time way. That's a key for that's allowed us to scale. And in order to comp, in order for us to accomplish this security scorecard engineering teams, they used a really novel combination of confluent cloud and confluent platform to build a really, really robust data for streaming pipelines and the data streaming pipelines enabled by confluent allow us at security scorecard to collect the data from a lot of various sources for risk analysis. Then they get feer further analyzed and provided to customers as a easy to understand summary of analytics. >>Rob, let's bring you into the conversation, talk about confluent, give the audience that overview and then talk about what you're doing together with SSC. >>Yeah, and I wanted to say Sam did a great job of setting up the context about what confluent is. So, so appreciate that, but a really simple way to think about it. Lisa is confident as a data streaming platform that is pioneering a fundamentally new category of data infrastructure that is at the core of what SSE does. Like Sam said, the key is really collect data accurately at scale and in real time. And that's where our cloud native offering really empowers organizations like SSE to build great customer experiences for their customers. And the other thing we do is we also help organizations build a sophisticated real time backend operations. And so at a high level, that's the best way to think about comfort. >>Got it. But I'll talk about data streaming, how it's being used in cyber security and what the data streaming pipelines enable enabled by confluent allow SSE to do for its customers. >>Yeah, I think Sam can definitely share his thoughts on this, but one of the things I know we are all sort of experiencing is the, is the rise of cyber threats, whether it's online from a business B2B perspective or as consumers just be our data and, and the data that they're generating and the companies that have access to it. So as the, the need to protect the data really grows companies and organizations really need to effectively detect, respond and protect their environments. And the best way to do this is through three ways, scale, speed, and cost. And so going back to the points I brought up earlier with conference, you can really gain real time data ingestion and enable those analytics that Sam talked about previously while optimizing for cost scale. So those are so doing all of this at the same time, as you can imagine, is, is not easy and that's where we Excel. >>And so the entire premise of data streaming is built on the concepts. That data is not static, but constantly moving across your organization. And that's why we call it data streams. And so at its core, we we've sort of built or leveraged that open source foundation of APA sheet Kafka, but we have rearchitected it for the cloud with a totally new cloud native experience. And ultimately for customers like SSE, we have taken a away the need to manage a lot of those operational tasks when it comes to Apache Kafka. The other thing we've done is we've added a ton of proprietary IP, including security features like role based access control. I mean, some prognosis talking about, and that really allows you to securely connect to any data no matter where it resides at scale at speed. And it, >>Can you talk about bar sticking with you, but some of the improvements, and maybe this is a actually question for Sam, some of the improvements that have been achieved on the SSC side as a result of the confluent partnership, things are much faster and you're able to do much more understand, >>Can I, can Sam take it away? I can maybe kick us off and then breath feel, feel free to chime in Lisa. The, the, the, the problem that we're talking about has been for us, it was a longstanding challenge. We're about a nine year old company. We're a high growth startup and data collection has always been in, in our DNA. It's at it's at the core of what we do and getting, getting the insights, the, and analytics that we synthesize from that data into customer's hands as quickly as possible is the, is the name of the game because they're trying to make decisions and we're empowering them to make those decisions faster. We always had challenges in, in the arena because we, well partners like confluent didn't didn't exist when we started scorecard when, when we we're a customer. But we, we, we think of it as a partnership when we found confluent technology and you can hear it from Barth's description. >>Like we, we shared a common vision and they understood some of the pain points that we were experiencing on a very like visceral and intimate level. And for us, that was really exciting, right? Just to have partners that are there saying, we understand your problem. This is exactly the problem that we're solving. We're, we're here to help what the technology has done for us since then is it's not only allowed us to process the data faster and get the analytics to the customer, but it's also allowed us to create more value for customers, which, which I'll talk about in a bit, including new products and new modules that we didn't have the capabilities to deliver before. >>And we'll talk about those new products in a second exciting stuff coming out there from SSC, bro. Talk about the partnership from, from confluence perspective, how has it enabled confluence to actually probably enhance its technology as a result of seeing and learning what SSC is able to do with the technology? >>Yeah, first of all, I, I completely agree with Sam it's, it's more of a partnership because like Sam said, we sort of shared the same vision and that is to really make sure that organizations have access to the data. Like I said earlier, no matter where it resides so that you can scan and identify the, the potential security security threads. I think from, from our perspective, what's really helped us from the perspective of partnering with SSE is just looking at the data volumes that they're working with. So I know a stat that we talked about recently was around scanning billions of records, thousands of ports on a daily basis. And so that's where, like I, like I mentioned earlier, our technology really excels because you can really ingest and amplify the volumes of data that you're processing so that you can scan and, and detect those threats in real time. >>Because I mean, especially the amount of volume, the data volume that's increasing on a year by basis, that aspect in order to be able to respond quickly, that is paramount. And so what's really helped us is just seeing what SSE is doing in terms of scanning the, the web ports or the data systems that are at are at potential risk. Being able to support their use cases, whether it's data sharing between their different teams internally are being able to empower customers, to be able to detect and scan their data systems. And so the learning for us is really seeing how those millions and billions of records get processed. >>Got it sounds like a really synergistic partnership that you guys have had there for the last year or so, Sam, let's go back over to you. You mentioned some new products. I see SSC just released a tax surface intelligence product. That's detecting thousands of vulnerabilities per minute. Talk to us about that, the importance of that, and another release that you're making. >>There are some really exciting products that we have released recently and are releasing at security scorecard. When we think about, when we think about ratings and risk, we think about it not just for our companies or our third parties, but we think about it in a, in a broader sense of an, of an ecosystem, because it's important to have data on third parties, but we also want to have the data on their third parties as well. No, nobody's operating in a vacuum. Everybody's operating in this hyper connected ecosystem and the risk can live not just in the third parties, but they might be storing processing data in a myriad of other technological solutions, which we want to understand, but it's really hard to get that visibility because today the way it's done is companies ask their third parties. Hey, send me a list of your third parties, where my data is stored. >>It's very manual, it's very labor intensive, and it's a trust based exercise that makes it really difficult to validate. What we've done is we've developed a technology called a V D automatic vendor detection. And what a V D does is it goes out and for any company, your own company or another business partner that you work with, it will go detect all of the third party connections that we see that have a live network connection or data connection to an organization. So that's like an awareness and discovery tool because now we can see and pull the veil back and see what the bigger ecosystem and connectivity looks like. Thus allowing the customers to go hold accountable, not just the third parties, but their fourth parties, fifth parties really end parties. And they, and they can only do that by using scorecard. The attack surface intelligence tool is really exciting for us because well, be before security scorecard people thought what we were doing was fairly, I impossible. >>It was really hard to get instant visibility on any company and any business partner. And at the same time, it was of critical importance to have that instant visibility into the risk because companies are trying to make faster decisions and they need the risk data to steer those decisions. So when I think about, when I think about that problem in, in managing sort of this evolving landscape, what it requires is it requires insightful and actionable, real time security data. And that relies on a couple things, talent and tech on the talent side, it starts with people. We have an amazing R and D team. We invest heavily. It's the heartbeat of what we do. That team really excels in areas of data collection analysis and scaling large data sets. And then we know on the tech side, well, we figured out some breakthrough techniques and it also requires partners like confluent to help with the real time streaming. >>What we realized was those capabilities are very desired in the market. And we created a new product from it called the tech surface intelligence. A tech surface intelligence focuses less on the rating. There's, there's a persona on users that really value the rating. It's easy to understand. It's a bridge language between technical and non-technical stakeholders. That's on one end of the spectrum on the other end of the spectrum. There's customers and users, very technical customers and users that may not have as much interest in a layman's rating, but really want a deep dive into the strong threat Intel data and capabilities and insights that we're producing. So we produced ASI, which stands for attack surface intelligence that allows customers to look at the surface area of attack all of the digital assets for any organization and see all of the threats, vulnerabilities, bad actors, including sometimes discoveries of zero day vulnerabilities that are, that are out in the wild and being exploited by bad guys. So we have a really strong pulse on what's happening on the internet, good and bad. And we created that product to help service a market that was interested in, in going deep into the data. >>So it's >>So critical. Go >>Ahead to jump in there real quick, because I think the points that Sam brought up, we had a great, great discussion recently while we were building on the case study that I think brings this to life, going back to the AVD product that Sam talked about and, and Sam can probably do a better job of walking through the story, but the way I understand it, one of security scorecards customers approached them and told them that they had an issue to resolve and what they ended up. So this customer was using an AVD product at the time. And so they said that, Hey, the car SSE, they said, Hey, your product shows that we used, you were using HubSpot, but we stopped using that age server. And so I think when SSE investigated, they did find a very recent HubSpot ping being used by the marketing team in this instance. And as someone who comes from that marketing background, I can raise my hand and said, I've been there, done that. So, so yeah, I mean, Sam can probably share his thoughts on this, but that's, I think the great story that sort of brings this all to life in terms of how actually customers go about using SSCs products. >>And Sam, go ahead on that. It sounds like, and one of the things I'm hearing that is a benefit is reduction in shadow. It, I'm sure that happens so frequently with your customers about Mar like a great example that you gave of, of the, the it folks saying we don't use HubSpot, have it in years marketing initiates an instance. Talk about that as some of the benefits in it for customers reducing shadow it, there's gotta be many more benefits from a security perspective. >>Yeah, the, there's a, there's a big challenge today because the market moved to the cloud and that makes it really easy for anybody in an organization to go sign, sign up, put in a credit card, or get a free trial to, to any product. And that product can very easily connect into the corporate system and access the data. And because of the nature of how cloud products work and how easy they are to sign up a byproduct of that is they sort of circumvent a traditional risk assessment process that, that organizations go through and organizations invest a, a lot of money, right? So there's a lot of time and money and energy that are invested in having good procurement risk management life cycles, and making sure that contracts are buttoned up. So on one side you have companies investing loads of energy. And then on the other side, any employee can circumvent that process by just going and with a few clicks, signing up and purchasing a product. >>And that's, and, and, and then that causes a, a disparity and Delta between what the technology and security team's understanding is of the landscape and, and what reality is. And we're trying to close that gap, right? We wanna close and reduce any windows of time or opportunity where a hacker can go discover some misconfigured cloud asset that somebody signed up for and maybe forgot to turn off. I mean, it's a lot of it is just human error and it, and it happens the example that Barra gave, and this is why understanding the third parties are so important. A customer contacted us and said, Hey, you're a V D detection product has an error. It's showing we're using a product. I think it was HubSpot, but we stopped using that. Right. And we don't understand why you're still showing it. It has to be a false positive. >>So we investigated and found that there was a very recent live HubSpot connection, ping being made. Sure enough. When we went back to the customer said, we're very confident the data's accurate. They looked into it. They found that the marketing team had started experimenting with another instance of HubSpot on the side. They were putting in real customer data in that instance. And it, it, you know, it triggered a security assessment. So we, we see all sorts of permutations of it, large multinational companies spin up a satellite office and a contractor setting up the network equipment. They misconfigure it. And inadvertently leave an administrator portal to the Cisco router exposed on the public internet. And they forget to turn off the administrative default credentials. So if a hacker stumbles on that, they can ha they have direct access to the network. We're trying to catch those things and surface them to the client before the hackers find it. >>So we're giving 'em this, this hacker's eye view. And without the continuous data analysis, without the stream processing, the customer wouldn't have known about those risks. But if you can automatically know about the risks as they happen, what that does is that prevents a million shoulder taps because the customer doesn't have to go tap on the marketing team's shoulder and go tap on employees and manually interview them. They have the data already, and that can be for their company. That can be for any company they're doing business with where they're storing and processing data. That's a huge time savings and a huge risk reduction, >>Huge risk reduction. Like you're taking blinders off that they didn't even know were there. And I can imagine Sam tune in the last couple of years, as SAS skyrocketed the use of collaboration tools, just to keep the lights on for organizations to be able to communicate. There's probably a lot of opportunity in your customer base and perspective customer base to engage with you and get that really full 360 degree view of their entire organization. Third parties, fourth parties, et cetera. >>Absolutely. Absolutely. CU customers are more engaged than they've ever been because that challenge of the market moving to the cloud, it hasn't stopped. We've been talking about it for a long time, but there's still a lot of big organizations that are starting to dip their toe in the pool and starting to cut over from what was traditionally an in-house data center in the basement of the headquarters. They're, they're moving over to the cloud. And then on, on top of that cloud providers like Azure, AWS, especially make it so easy for any company to go sign up, get access, build a product, and launch that product to the market. We see more and more organizations sitting on AWS, launching products and software. The, the barrier to entry is very, very low. And the value in those products is very, very high. So that's drawing the attention of organizations to go sign up and engage. >>The challenge then becomes, we don't know who has control over this data, right? We don't have know who has control and visibility of our data. We're, we're bringing that to surface and for vendors themselves like, especially companies that sit in AWS, what we see them doing. And I think Lisa, this is what you're alluding to. When companies engage in their own scorecard, there's a bit of a social aspect to it. When they look good in our platform, other companies are following them, right? So now all of the sudden they can make one motion to go look good, make their scorecard buttoned up. And everybody who's looking at them now sees that they're doing the right things. We actually have a lot of vendors who are customers, they're winning more competitive bakeoffs and deals because they're proving to their clients faster that they can trust them to store the data. >>So it's a bit of, you know, we're in a, two-sided kind of market. You have folks that are assessing other folks. That's fun to look at others and see how they're doing and hold them accountable. But if you're on the receiving end, that can be stressful. So what we've done is we've taken the, that situation and we've turned it into a really positive and productive environment where companies, whether they're looking at someone else or they're looking at themselves to prove to their clients, to prove to the board, it turns into a very productive experience for them >>One. Oh >>Yeah. That validation. Go ahead, bro. >>Really. I was gonna ask Sam his thoughts on one particular aspect. So in terms of the industry, Sam, that you're seeing sort of really moving to the cloud and like this need for secure data, making sure that the data can be trusted. Are there specific like verticals that are doing that better than the others? Or do you see that across the board? >>I think some industries have it easier and some industries have it harder, definitely in industries that are, I think, health, healthcare, financial services, a absolutely. We see heavier activity there on, on both sides, right? They they're, they're certainly becoming more and more proactive in their investments, but the attacks are not stopping against those, especially healthcare because the data is so valuable and historically healthcare was under, was an underinvested space, right. Hospitals. And we're always strapped for it folks. Now, now they're starting to wake up and pay very close attention and make heavier investments. >>That's pretty interesting. >>Tremendous opportunity there guys. I'm sorry. We are out of time, but this is such an interesting conversation. You see, we keep going, wanna ask you both where can, can prospective interested customers go to learn more on the SSC side, on the confluence side, through the AWS marketplace? >>I let some go first. >>Sure. Oh, thank thank, thank you. Thank you for on the security scorecard side. Well look, security scorecard is with the help of Colu is, has made it possible to instantly rate the security posture of any company in the world. We have 12 million organizations rated today and, and that, and that's going up every day. We invite any company in the world to try security scorecard for free and experience how, how easy it is to get your rating and see the security rating of, of any company and any, any company can claim their score. There's no, there's no charge. They can go to security, scorecard.com and we have a special, actually a special URL security scorecard.com/free-account/aws marketplace. And even better if someone's already on AWS, you know, you can view our security posture with the AWS marketplace, vendor insights, plugin to quickly and securely procure your products. >>Awesome. Guys, this has been fantastic information. I'm sorry, bro. Did you wanna add one more thing? Yeah. >>I just wanted to give quick call out leads. So anyone who wants to learn more about data streaming can go to www confluent IO. There's also an upcoming event, which has a separate URL. That's coming up in October where you can learn all about data streaming and that URL is current event.io. So those are the two URLs I just wanted to quickly call out. >>Awesome guys. Thanks again so much for partnering with the cube on season two, episode four of our AWS startup showcase. We appreciate your insights and your time. And for those of you watching, thank you so much. Keep it right here for more action on the, for my guests. I am Lisa Martin. We'll see you next time.

>>Hey everyone. Welcome to the cubes presentation of the AWS startup showcase. This is season two, episode four of our ongoing series that features exciting startups within the AWS ecosystem. This episode's theme, cybersecurity protect and detect against threats. I'm your host, Lisa Martin, and I'm pleased to welcome back. One of our alumni chase joins me the principal strategist at jump cloud chase. It's great to have you back on the >>Perfect Michael, thank you so much for having me again, >>Tell the audience just a little quick refresher on jump cloud, open directory platform. We just give them that little bit of context. >>You bet. So jump cloud provides an open directory platform and what we mean by that is we help manage all of your employees, identities, the devices that they operate on, and then all the access that they need in order to get their work done in a modern it environment. >>So from a target, a market segment perspective, this is really targeted at small medium enterprise SMEs managed security providers. MSPs, talk to me a little bit about that and some of the what's in it for me, for those folks. >>Yeah, absolutely. And when we are thinking about specifically within that market, so small, medium enterprises and the it, or the managed service providers that help support those organizations, there's a lot of different technologies that you use in order to make sure that you have a secure organization. And within that group specifically, there's a lot less of a luxury right of an enterprise budget or kind of all these different personnel that you might have available to you. And it's really kind of down to maybe one team or just a couple folks or just one person wearing a lot of different hats. And so we've designed the open directory platform to help accommodate for a lot of those different pieces where we're bringing in multiple different types of technologies from identity access management, device management and MDM, MFA access through single sign on all of those different pieces and more that help kind of come into one platform. >>So not only do you have all the technology there at your disposable, but also all the visibility and analytics of folks that are getting in and just trying to get their job done. But now all of those pieces are, are consolidated into one platform and it really helps support a lot of those organizations, right? And keep in mind, you know, small, medium businesses are the most common businesses, not everyone's coming in from an enterprise. And so here we're able to layer on levels of security and making sure that you have best practices, no matter what size you're operating in. >>So consolidating it management, securing employees, access to a variety of it. Resources is really kind of in a nutshell. >>Absolutely. And just making sure that you're combining that combination of securely accessing all the things that you need, but also making sure that from an end user perspective, it's really easy and you have all those things kind of built in from the get go. >>So how are SSEs and MSPs leveraging jump cloud right now? What are some of the outcomes that you are helping them to achieve? Anything stand out to you? >>I think there's a couple different areas that we help support organizations. One is you can think about just the whole employee life cycle. So when, when someone joins an organization from onboarding, you know, where does that identity come from? How can we make sure that they're productive, you know, effective human beings as they come into it, but then the whole life cycle, as they're accessing or changing resources within their role, all the way to the end, where they might be leaving the organization and we can securely off board that person. And so that whole flow that you might have from an organization standpoint is one aspect. Another area is as companies continue to grow, they might be going after, you know, maybe audits, level compliance, other pieces that might help them grow. And there's a lot of layers that you need to think about or different types of technologies and processes to have those certifications and credentials. >>And so we help support those organizations again, by consolidating all those different technologies into one spot. It makes it a lot easier for people to get up to par in how they think that their security standards should be set within an organization. And finally too, I'd say just ease of mind. There's a lot of pieces when you're thinking about, you know, where people might be coming in from how do I get visibility into all those different aspects? And when you have all that under one roof, it adds a lot of, I'd say, you know, less mental stress in terms of one, how all those technologies should be working together effectively, also securely, but then also making sure that you have time in the day to tackle big projects and let some of the, let's say, run rate security out of the way. >>Yeah. That's really important to be able to assign resources that are able to make the biggest impact across the organization, moving things off the plate that are not necessary or more mundane twice a year. I understand jump cloud does a survey with SMEs where you really are aimed at understanding kind of where they are in the market today, their concerns, trends, challenges, budgets. Then I saw you just published results from a survey in June of 2022. Talk to me a little bit about the demographics of the survey, who, who are you talking to within SMEs? And then we can kind of crack open some of those really interesting findings that came out this year. >>Yeah. So we love to get a pulse check of what's happening within the industry, but specifically within that small, medium size, if you will. And so for that survey that we ran, we talked to 400 different roles, kind of that touch it from security. So from vice president of the CCSO all the way down to it, admins and anyone else in between, and we're really looking at organizations that had about 500 employees or less, cuz there's a lot of information out there, especially from the enterprise of, you know, Hey, here's best practices. Here's all the things that you can do. But for smaller organizations, it's not as clear cut or you have less of an understanding of what your peers might be going through or kind of what their concerns are. And so when we're running that survey, that's one thing that we like to keep in mind is it's really meant for organizations at that size because there's, there's some commonalities that you start to see in suss out. >>And it's not to say that those aren't the same concerns that the enterprise folks have as well, because a lot of the things that will come out, you know, they are security based say, Hey, what's top of mind, or what's kind of keeping you up at night. There were some clear indicators and especially well from kind of, as we do this survey, you know, every six months or kind of even year over year, you start to see some trends that are emerging. And so a, a lot of the big ones are, you know, ransomware software, vulnerability and network security. Those are kind of the top three aspects when we're looking at, Hey, what are specifics that are keeping you up? And those are easy to say because ransomware is obviously in the news. Even this week, there are three different organizations just kind of pick out. >>So brussel who does dental manufacturing, they had ransomware in trust, which is another cybersecurity organization. They were breached. But then also Fremont county here in Colorado as a government organization, all three of those were hit by ransomware. And you might not say, Hey, there's, you know, they're all kind of random and they're not put together, but under the hood really it's a lot of the same different technologies that are powering, how people get access into things. Do they have the right levels of credentials? Are there conditions set within that type of access, especially if it's privilege. And so you start to consolidate and bubble down all those different things that can lead up to those concerns. And then even on the software vulnerability side, Mac release, two different vulnerabilities this week. And so now it quickly becomes, okay, great. How can I make sure that my employees are using not only a secure device, but a secure device, that's up to date because it's a dynamic field as all of these things coming through. >>And these are a lot of the gotchas that can keep, you know, small, medium enterprises up at night because if something happens a security event like that, it could be a, you know, a career ending event, but also a company ending event. When you think about that. And so that becomes a really high level of importance because no one wants to see their name in the news, but it also takes a lot of different steps in order to create the layers that are necessary in order to achieve, you know, really solid round stand on for organization to do that. And so that's where we like to come in and help and making sure that a lot of those layers are actually easier to implement than you thought. And it's not this huge project, but you're doing it in a way that's conscious and also not really getting the way of kind of battling users or making sure that their experience is a nightmare as well in order to achieve these goals that you have as an organization, >>You bring up ransomware, it's become a household term that I think probably every generation alive right now in some form or fashion understands what it is to a, to some degree it's now security threats in general. Now no longer if we get hit, it's a matter of one. You gave three great examples of SMEs that were hit recently and organizations. We wouldn't think really them everybody's vulnerable. You talked about the different, you know, some of the, the concerns, software, vulnerable vulnerability, exploits, the use of unsecured networks, people, and this is so common using the same password across applications that SSEs and enterprises too are dealing with. They have to be able to lean on MSPs, for example, in the SME space to say, help us with these obvious vulnerabilities, we need to make sure that our employees are productive. They're working together. We can onboard and offboard people in a secure way. How did this survey uncover how SMEs are leaning more on MSPs to help solve some of those risks that you've talked about? >>I think one of the more interesting trends that we've seen is just the ability and the ramp for organizations to lean on managed service providers. You saw a lot of this during kind of the, the beginning of the pandemic or kind of this really shift to remote work where people kind of have this mentality of, okay, it might be a cost center and, and will have, but it it's always felt this importance to making sure that people are on site. They understand their culture. They understand the, the ways that the organization works. However, now, a lot more organizations are stepping back and saying, well, if I can't see anyone in the office or if there's only half or maybe 10% that are showing up, you know, are there other economies of scale almost that I can get from leveraging a managed service provider bringing in other expertise, right? >>And so it might be valuable to say, Hey, it's not only just managing my organization, but five others. And so now you can start to see and kind of lean on best practices that they've evolved over time. And I think one of the more interesting stats is we see that, you know, almost nine out of 10 organizations that we surveyed are either leveraging an MSP or have considered it. And one of those things that's actually pulling them back or some organizations say, Hey, I've looked at it, but I'm not quite ready to commit to outsourcing this section of my organization that, or kind of bringing in someone to manage it fully alongside with me almost in a co-managed type of environment is a third of 'em say, Hey, I, I don't know how secure the MSPs are themselves. How do they think about their own internal practices? >>And what does that look like? Because again, you, you're thinking about handing over the crown jewels over to someone and say, Hey, here's some of our, our most vulnerable or critical assets that we need to have secured and, and making sure that that's part of the organization. And so it's a, it's an honest conversation that a lot of owners have with MSPs and say, look, are, are you up to snuff, right? Because if something happens, sure, I might have one person to go after, or you might have SLAs that I can, I can go. But it still means me as an organization has been targeted. What does that look like in our types of relationship? And so a lot of the partners that we have on the jump outside, it's a very common conversation that they have with our clients and saying, walking them through and say, Hey, here's our, our security plan. >>Here's how we approach that. Here's all the different tools that we have at, at our disposal that are working alongside jump cloud in order to make sure that not only do you have good posture, I'd say good areas where the organization is set up for success, where you're thinking about not sharing passwords or there's password complexity, or there's other technologies like single sign on that, help reduce that. But in addition to what type of network scanning do you have available? What type of antivirus do you leverage? What are all the other pieces that create that holistic security structure? And so sometimes it's a lot easier for MSPs to deliver that and package it up instead of having, you know, an overburdened it, admin said, great, this is another project that I have to go through and think about and look at pricing and kind of other those components, because it helps speed up. I'd say your time to being more secure. And that's a really real conversation for organizations as they think about planning, as they think about budgets and what impact that might have on organization, making sure that employees can get work done. But we're also thinking about in a very secure mindset within the organization. >>That's so critical as we talked about every or every organization of every size in every industry is vulnerable. There's just no weight getting around it. These days. You talked about an interesting stat, about 90% of the SME surveyed some written we're yes, we're relying on MSV, but we still worry about security. Talk to me from the jump cloud, AWS perspective. How do you help though? That's cause that's a big number, the 90% of SMEs that are still concerned about security, how do you help them dial that down? >>I think it's really understanding, you know, you mentioned AWS, so what are the critical access and what are those points that look like that we need to get a handle on? And how can we make that easier? Cause I think one of the pieces that will often come at and say, Hey, we really wanna make this approach work. We really wanna make sure that when you, when you wake up and you need to get into Q and a environments or, or production or whatever, that might be, that it's a seamless experience, but we as an organization have visibility into what's going on and Hey, if you're getting promoted or your role is changing, we wanna make sure that those attributes or kind of those pieces that are associated to you and your identity are changing with it. And so making sure that there's this dynamic motion available to folks, as they start thinking about, you know, where a majority of their IP lives, it's no longer in some server closet and yes, it might still be on a, on a manufacturing floor, but it's those components that become the most critical for organizations you've heard, I'd say, you know, certainly within the last five years and probably even goes further back where a lot of traditional organizations say, Hey, we're a software company now we're, you know, kind of insert for innovation, making sure we can do that. >>And I think a lot of organizations are still going through that transition, but right behind it and what's coming next. And certainly a lot of organizations start to say, not only are we a software company, but we're a security company. And with that, that comes the mindset. Not only of here's how we tactically get into the things that we need to do our job, but the why behind it. And I think that's one of the elements that might be missing or is certainly one of, I know that we have a lie attainment kind of take that approach of, yes, we're gonna be implementing, we need to have your device passion updated because there's vulnerabilities. But for everyone else kind of on the end user side, it's like, well, okay, well why, why do we need to do that? And so by having that security first type of mentality, that allows everyone to be on the same page, play on the same team and making sure that when, you know, those requests are coming in both back and forth between end users and its security team, anyone else that might be involved within that process, you all understand that say, Hey, it's not, you know, it, it's not my job. >>It's everyone's job, right? We're all in this together because that's some of the parts where it can start to fall down too. You might have a team that has the best practices and in, you know, in intentions, but if the implementation and the follow through isn't bought in from everyone, then you're also playing against the speed of the organization to adopt it. And that's really the timeline that you're battling, especially when you're thinking about ransomware or someone who already might be in it is how can we help mitigate a lot of those different pieces. So by combining all those different elements into a thought process, into a mentality of being a security first organization, that's really kind of helps within the ripple effect all the way down into, you know, the critical resources like AWS. >>It has to be a holistic view. There's really no other choice these days. And it also has to be done in a timely fashion. What did, as we wrap up kind of talking about the survey here, what were some of the trends, the future trends it uncovered as we are still in a remote and distributed work environment. It probably always will be. We've seen challenges and everyone's mental health in terms of, of strapped resources. What did the survey uncover as to what these folks saw as future trends? >>So I'd say there's a, there's a couple, there there's a lot, but we'll break it down and say, I'd say three core trends that you saw across every organization that we talked to, including our own base of over 180,000 organizations that rely on gem cloud is, Hey, security is number one, right? And we we've talked to that about at length device management is another extension of that. I'm sorry, making sure that, Hey, this is the only piece of hardware I have from the company in front of me. I wanna make sure that I can manage secure it, make sure it's patched as well as we kind of operate in this dynamic and environment, making sure that we're resilient as an organization. And then I'd say finally, as those pieces start to evolve, there's still some organizations that are how trying to understand kind of truly manage what does hybrid and remote and kind of what does that look like for me as an organization? >>Cause I think we're now out of this panic mode and now organizations are now setting up. Okay, what are some of the long term structures as I think about that, and you hear a lot about too, from other organizations that are mandating folks to come back or okay. Maybe it's just a couple days a week or all of those decisions have impacts on the it organization. So that is very alive and well, I'd say one of the other pieces you mentioned mental health is that we are starting to understand a little bit more, you know, kind of who's behind the computer. Who's, who's behind the keyboard. What does the impact have for them? Because in this type of work environment as well, you know, it's still challenging to find really good talent. And so you might be strapped for resources. You might be the only person that's trying to implement these processes or the security protocol, or trying to help get us up into a good compliance posture, all of those different pieces kind of on it. >>And so you can start to think about man, how do I, how do I make progress? And I think that's one of the other pieces that is really important for folks kind of from that perspective is, you know, always understand that you're making progress, even though the, the tickets might be coming at you and you, there's never ending in sight. All those steps that you take for an organization are critically important. And so, and it's not always just a people answer cuz you might, might not be in the position to say, Hey, we need an extra five hands on this in order to make it done. It might have to be more of a conversation of, Hey, here are the pieces that we need to automate. Here are the business processes that we really need to think about in order to have a fundamental impact on what we can do. >>And then you can come back and say, great. And if we have this, it might actually look like one and a half people. You can't really hire a half person, but you come into those types of mentality with a really solid argument of here's what we need to have in order to make this happen. And I think too, getting that type of buy-in again, making sure, Hey, we are a security company after all, we're all in this together that allows everyone to kind of help pitch in because if you don't have that piece, then you know, everything can feel much more burdensome, right? And the level of burnout increases the, the level of mental health in general, across the teams that are acting as supporting functions for an organization, start to get burnout. And it might not always be as Hey, as important as, as revenue or Hey, we're getting this marketing campaign out, but it's this underwriting thing in terms of really, truly important infrastructure that the company needs to think about. >>And when you can involve all of those different pieces, then people feel like they can make a positive impact. They feel more empowered. They have, you know, emojis attached to tickets and say, Hey, it was so great to help you out today. And a lot of those I'd say interpersonal connections that you might be missing in a remote only type of world in organization. And so bringing all those little tidbits back into, you know, how to, how to be a good person, how to be a good human and how to make sure that there's some personality involved with it. And it's not just this ongoing process. I think there's a little bit of give and take, but that's one other thing that we've surfaced is really just understanding a better picture of who's implementing all these amazing things around the world. >>That's so important. There's so many different levers to the pull here where becoming a security company is concerned. Where can folks go to one chase, get the surveying two, some final thoughts. What, where can folks go to actually test out jump drive? >>Yeah, absolutely >>Jump out. Excuse me. >>So within everything that we talked about, some from various different technologies from identity management, device management, SSO, MFA, and many, many more. So you can go to jumpcloud.com, create a free organization. It's free up to 10 users, 10 devices. So even for really small organizations, even if you're a startup, we can help leverage enterprise grade security technology for you to implement as well as more detailed on the reports. And so if you wanna get a better sense of kind of how we look at the world types of information that we can bring back and making sure that you're learning from your peers and how to implement and put your best foot forward within the organization, we always have a ton of amazing resources and content that really looks at, you know, who's doing the work. Why are they doing the work? And how is that work impactful within multiple different organizations and not only just the organizations themselves, but those that are supporting it like managed service providers of the world. >>Got it. Awesome. Chase. Thank you so much for joining me on this episode of the AWS startup showcase, talking to us about what jump cloud is uncovered with respect to the concerns that SMEs have, how MSPs are helping, how jump cloud is also a facilitator of really helping to organizations to become security organizations. We appreciate your time. >>Absolutely. Thank you so much for having me again. >>Our pleasure. We wanna you for watching. Keep it right here on the, for more action. The, is your leader in live coverage?