(lively music) >> Good afternoon and welcome back to beautiful Las Vegas, Nevada, where we're here live from the show floor, all four days of AWS re:Invent. I'm Savannah Peterson, joined with my co-host Dave Vellante. Dave, how you doing? >> Good. Beautiful and chilly Las Vegas. Can't wait to get back to New England where it's warm. >> Balmy, New England this time of year in December. Wow, Dave, that's a bold statement. I am super excited about the conversation that we're going to be having next. And, you know, I'm not even going to tee it up. I just want to bring Dilip on. Dilip, thank you so much for being here. How you doing? >> Savannah, Dave, thank you so much. >> Hey, Dilip. >> Excited to be here. >> It's joy to have you. So, you have been working at Amazon for about 20 years. >> Almost. Almost. >> Yes. >> Feels like 20, 19 1/2. >> Which is very exciting. You've had a lot of roles. I'm going to touch on some of them, but you just came over to AWS from the physical retail side. Talk to me about that. >> Yup, so I've been to Amazon for 19 1/2 years. Done pricing, supply chain. I was Jeff Bezos technical advisor for a couple years. >> Casual name drop. >> Casual name drop. >> Savannah: But a couple people here for that name before. >> Humble brag, hashtag. And then I, for the last several years, I was leading our physical retail initiatives. We just walk out Amazon One, bringing convenience to physical spaces. And then in August, with like as those things were getting a lot of traction and we were selling to third parties, we felt that it would be better suited in AWS. And, but along with that, there was also another trend that's been brewing, which is, you know, companies have loved building on AWS. They love the infrastructure services, but increasingly, they're also asking us to build applications that are higher up in the stack. Solving key, turnkey business problems. Just walk out Amazon One or examples of that, Amazon Connect. We just recently announced supply chain, so now there's a bevy interesting services all coming together, higher up in the stack for customers. So it's an exciting time. >> It was interesting that you're able to, you know, transfer from that retail. I mean, normally, in historically, if you're within an industry, retail, manufacturing, automotive whatever. You were kind as locked in a little bit. >> Dilip: Siloed a little bit. Yeah, yeah, yeah. >> Because they had their own, your own value chain. And I guess, data has changed that maybe, that you can traverse now. >> Yeah, if you think about the things that we did, even when we were in retail, the tenants was less about the industries and more about how can we bring convenience to physical spaces? The fact that you don't like to wait in line is no more like likely, you know, five years from now than it is today. So, it's a very durable tenant, but it's equally applicable whether you're in a grocery store, a convenience store, a stadium, an airport. So it actually transcends any, and like supply chain, think of supply chain. Supply chain isn't, you know, targeted to any one particular industry. It has broad applicability. So these things are very, you know, horizontally applicable. >> Anything that makes my life easier, I'm down. >> Savannah: We're all here for the easy button. We've been talking about it a bit this week. I'm in. And the retail store, I mean, I'm in San Francisco. I've had the experience of going through. Very interesting and seamless journey, honestly. It's very exciting. So tell us a little bit more about the applications group at AWS. >> Yup. So as I said, you know, we are, the applications group is a combination of several services. You know, we have communication developer services, which is the ability to add simple email service or video and embed video, voice chat using a chime SDK. In a higher up in the stack, we are taking care of things that IT administrators have to deal with where you can provision an entire desktop with the workspaces or provide a femoral access to it. And then as you go up even higher up in the stack, you have productivity applications like AWS Wicker, which we just did GA, you know, last week in AWS Clean Rooms which we announced as a service in preview. And then you have, you know, Connect, which is our cloud contact center, AWS supply chain. Just walk out Amazon One, it just feels like we're getting started. >> Just a couple things going on. >> So, clean rooms. Part of the governance play, part of data sharing. Can you explain, you know, we were talking offline, but I remember back in the disk drive days. We were in a clean room, they'd show you the clean room, you couldn't go near it unless you had a hazmat suit on. So now you're applying that to data. Explain that concept. >> Yeah, so the companies across, you know, financial services or healthcare, advertising, they all want to be able to combine and pull together data`sets with their partners in order to get these collaborative insights. The problem is either the data's fragmented, it's siloed or you have, you know, data governance issues that's preventing them from sharing. And the key requirement is that they want to be able to share this data without exposing any of the underlying data. Clean rooms are always emerged as a solution to that, but the problem with that is that they're hard to maintain. They're expensive. You have to write complex privacy queries. And if you make a mistake, you risk exposing the same data that you've been, you know, studiously trying to protect. >> Trying to protect. >> You know, take advertising as an industry, as an example. You know, advertisers care about, is my ad effective? But it turns out that if you're an advertiser and let's say you're a Nike or some other advertiser and your pop, you know, you place an ad on the website. Well, you want to stop showing the ad to people who have already purchased the product. However, people who purchased the product,- >> Savannah: It happens all the time. >> that purchasing data is not accessible to them easily. But if you could combine those insights, you know, the publishers benefit, advertisers benefits. So AWS Clean Rooms is that service that allows you very easily to be able to collaborate with a group of folks and then be able to gain these collaborative insights. >> And the consumers benefit. I mean, how many times you bought, you search it. >> It happens all the time. >> They know. And like, I just bought that guys, you know? >> Yeah, no, exactly. >> Four weeks. >> And I'm like, you don't need to serve me that, you know? And we understand the marketing backend. And it's just a waste of money and energy and resources. I mean, we're talking about sustainability as well. I don't think supply chain has ever had a hotter moment than it's had the last two and a half years. Tell me more about the announcement. >> Yup, so super excited about this. As you know, as you said, supply chains have always been very critical and very core for companies. The pandemic exacerbated it. So, ours way of sort of thinking about supply chains is to say that, you know, companies have taken, over the years many, like dozens, like millions and millions of dollars of investment in building their own supply chains. But the problem with supply chains is that the reason that they're not as functional as they could be is because of the lack of visibility. Because they're strung together very many disparate systems, that lack of visibility affects agility. And so, our approach in it was to say that, well, if we could have folks use their existing supply chain what can we do to improve the investment on the ROI of what they're getting? By creating a layer on top of it, that provides them that insights, connects all of these disparate data and then provides them insights to say, well, you know, here's where you overstock, here's where you under stock. You know, this is the, you know, the carbon emission impact of being able to transfer something. So like rather without requiring people to re-platform, what's the way that we can add value in it? And then also build upon Amazon's, you know, years of supply chain experience, to be able to build these predictive analytics for customers. >> So, that's a good, I like that you started with the why. >> Yes. >> Right now, what is it? It's an abstraction layer and then you're connecting into different data points. >> Yes, that's correct. >> Injecting ML. >> Feel like you can pick in, like if you think about supply chain, you can have warehouse management systems, order management systems. It could be in disparate things. We use ML to be able to bring all of this disparate data in and create our unified data lake. Once you have that unified data lake, you can then run an insights layer on top of it to be able to say, so that as the data changes, supply chain is not a static thing. Data's constantly changing. As the data's changing, the data lake now reflects the most up-to-date information. You can have alerts and insights set up on it to say that, what are the kinds of things that you're interested in? And then more importantly, supply chain and agility is about communication. In order to be able to make certain things happen, you need to be able to communicate, you need to make sure that everyone's on the same page. And we allow for a lot of the communication and collaboration tools to be built within this platform so that you're not necessarily leaving to go and toggle from one place to the other to solve your problems. >> And in the pie chart of how people spend their time, they're spending a lot less time communicating and being proactive. >> That's correct. >> And getting ahead of the curve. They're spending more time trying to figure out actually what's going on. >> Yes. >> And that's the problem that you're going to solve. >> Well, and it ensures that the customer at the other end of that supply chain experience is going to have their expectations managed in terms of when their good might get there or whatever's going to happen. >> Exactly. >> I feel like that expectation management has been such a big part of it. Okay, I just have to ask because I'm very curious. What was it like advising Jeff? >> Quite possibly the best job that I've ever had. You know, he's a fascinating individual. >> Did he pay you to say that? >> Nope. But I would've, like, I would've done it for like, it's remarkable seeing how he thinks and his approach to problem solving. It is, you know, you could be really tactical and go very deep. You could be extremely strategic. And to be able to sort of move effortlessly between those two is a unique skill. I learned a lot. >> Yeah, absolutely. So what made you want to evolve your career at Amazon after that? 'Cause I see on your LinkedIn, you say, it was the best job you ever had. With curiosity? >> Yeah, so one of the things, so the role is designed for you to be able to transition to something new. >> Savannah: Oh, cool. >> So after I finished that role, we were just getting into our foray with physical stores. And the idea between physical stores is that, you and I as consumers, we all have a lot of choices for physical stores. You know, there's a lot of options, there's a lot of formats. And so the last thing we wanted to do is come up with another me too offering. So, our approach was that what can we do to improve convenience in physical stores? That's what resulted in just walk out to Amazon Go. That's what resulted in Amazon One, which is another in a fast, convenient, contactless way to pay using the power of your palm. And now, what started in Amazon retail is now expanded to several third parties in, you know, stadiums, convention centers, airports. >> Airport, I just had, was in the Houston airport and got to do a humanless checkout. >> Dilip: Exactly. >> And actually in Honolulu a couple weeks ago as well too. Yeah, so we're going to see more and more of this. >> Yes. >> So what Amazon, I think has over a million employees. A lot of those are warehouse employees. But what advice would you give to somebody who's somewhere inside of Amazon, maybe they're on AWS, maybe they're Amazon. What advice would you give somebody inside that's maybe, you know, hey, I've been at this job for five, six years, three, four years, whatever it is. I want to do something else. And there's so much opportunity inside Amazon, right? What would you advise them? >> My single advice, which is actually transferable and I use it for myself is choose something that makes you a little uncomfortable. >> Dave: Get out of your comfort zone. >> It's like, you got to do that. It's like, it's not the easiest thing to hear, but it's also the most satisfying. Because almost every single time that I've done it for myself, it's resulted in like, you don't really know what the answer is. You don't really know exactly where you're going to end up, but the process and the journey through it, if you experience a little bit of discomfort constantly, it makes you non complacent. It makes you sort of not take the job, sort of in a stride. You have to be on it to do it. So that's the advice that I would give anyone. >> Yeah, that's good. So something that's maybe adjacent and maybe not completely foreign to you, but also something that, you know, you got to go dig a little bit and learn. >> You're planning a career change over here, Dave? >> No, I know a lot of people in Amazon are like, hey, I'm trying to figure out what I want to do next. I mean, I love it here. I live by the LPS, you know, but, and there's so much to choose from. >> It is, you know, when I joined in 2003, there were so many things that we were sort of doing today. None of those existed. It's a fascinating company. And the evolution, you could be in 20 different places and the breadth of the kinds of things that, you know, the Amazon experience provides is timeless. It's fascinating. >> And, you know, you look at a company like Amazon, and, you know, it's so amazing. You look at this ecosystem. I've been around- >> Even a show floor. >> I've been around a lot of time. And the show floor says it all. But I've seen a lot of, you know, waves. And each subsequent wave, you know, we always talk about how many companies were in the Fortune 1000 and aren't anymore. And, but the leaders, you know, survive and they thrive. And I think it's fascinating to try to better understand the culture that enables that. You know, you look at a company like Microsoft that was irrelevant and then came back. You know, even IBM was on death store for a while and they come back and so they. And so, but Amazon just feels, you know, at the moment you feel like, "Oh wow, nothing can stop this machine." 'Cause everybody's trying to disrupt Amazon and then, you know, only the paranoid survive, all that stuff. But it's not like, past is not prologue, all right? So that's why I asked these questions. And you just said that a lot of the services today that although the ideas didn't even exist, I mean, walkout. I mean, that's just amazing. >> I think one of the things that Amazon does really well culturally is that they create the single threaded leadership. They give people focus. If you have to get something done, you have to give people focus. You can't distract them with like seven different things and then say that, oh, by the way, your eighth job is to innovate. It just doesn't work that way. It's like it's hard. Like it can be- >> And where were the energy come from that? >> Exactly. And so giving people that single threaded focus is super important. >> Frank Slootman, the CEO of Snowflake, has a great quote. He wrote on his book. He said, "If you got 14 priorities, you got none." And he asks,- >> Well said. >> he challenges people. If you had to give up everything and do only one thing for the next 365 days, what would that be? It's a really hard question to answer. >> I feel like as we're around New Year's resolution times. I mean when we thinking about that, maybe we can all share our one thing. So, Dilip, you've been with the the applications team for five months. What's coming up next? >> Well, as I said, you know, it feels like it's still day one for applications. If you think about the things, the news that we introduced and the several services that we introduced, it has applicability across a variety of horizontal industries. But then we're also feeling that there's considerable vertical applications that can be built for specific things. Like, it could be in advertising, it could be in financial services, it could be in manufacturing. The opportunities are endless. I think the notion of people wanting applications higher up in the stack and a little more turnkey solutions is also, it's not new for us, but it's also new and creative too. You know, AWS has traditionally been doing. >> So again, this relates to what we were sort of talking about before. And maybe, this came from Jazzy or maybe it came from Bezos. But you hear a lot, it's okay to be misunderstood or if we were misunderstood for a long time. So when people hear up the stack, they think, when you think about apps, you know, in the last 10 years it was taking on-prem and bringing it into the cloud. Okay, you saw that with CREM, email, CRM, service management, you know, data warehouses, et cetera. Amazon is thinking about this in a different way. It's like you're looking at the world saying, okay, how can we improve whatever? Workflows, people's lives, doing something that's not been done before? And that seems to be the kind of applications that you guys are thinking about building. >> Yeah. >> And that's unique. It's not just, okay, we're going to take something on-prem put it in the cloud. Been there, done that. That S-curve is sort of flattening now. But there's a new S-curve which is completely new workflows and innovations and processes that we really haven't thought about yet. Or you're thinking about, I presume. >> Yeah. Having said that, I'd also like to sort of remind folks that when you consider the, you know, the entire spend, the portion of workloads that are running in the cloud is a teeny tiny fraction. It's like less than 5%, like 4% or something like that. So it's a very, there's still plenty of things that can sort of move to the cloud. But you're right that there is another trend of where in the stack and the types of applications that you can provide as well. >> Yeah, new innovation that haven't well thought of yet. >> So, Dilip, we have a new tradition here on theCUBE at re:Invent. Where we're looking for your 30 minute Instagram reel, your hot take, biggest key theme, either for you, your team, or just general vibe from the show. >> General vibe from the show. Well, 19 1/2 years at Amazon, this is actually my first re:Invent, believe it or not. This is my, as a AWS employee now, as re:Invent with like launching services. So that's the first. I've been to re:Invent before, but as an attendee rather than as a person who's, you know, a contributing number of the workforce. >> Working actually? >> If you will. >> Actually doing your job. >> And so I'm just amazed at the energy and the breadth. And the, you know, from the partners to the customers to the diversity of people who are coming here from everywhere. I had meetings from people in New Zealand. Like, you know, the UK, like customers are coming at us from like very many different places. And it's fascinating for me to see. It's new for me as well given, you know, some of my past experience. But this is a, it's been a blast. >> People are pumped. >> People are pumped. >> They can't believe the booth traffic. Not only that quality. >> Right. All of our guests have talked about that. >> Like, yeah, you know, we're going to throw half of these leads away, but they're saying no, I'm having like really substantive conversations with business people. This is, I think, my 10th re:Invent. And the first one was mostly developers. And I'm like, what are you talking about? And, you know, so. Now it's a lot more business people, a lot of developers too. >> Yeah. >> It's just. >> The community really makes it. Dilip, thank you so much for joining us today on theCube. >> Thank you for having me. >> You're fantastic. I could ask you a million questions. Be sure and tell Jeff that we said hi. >> Will do. >> Savannah: Next time you guys are hanging out. And thank all of you. >> You want to go into space? >> Yeah. Yes, yes, absolutely. I'm perhaps the most space obsessed on the show. And with that, we will continue our out of this world coverage shortly from fabulous Las Vegas where we are at AWS re:Invent. It is day four with Dave Vellante. I'm Savannah Peterson and you're watching theCUBE, the leader in high tech coverage. (lively music)

>>Hello and welcome back to the Cube's coverage of AWS Reinvent 2022. I'm John Furrier, host of the Cube. We got a great conversation with Patrick Kauflin, vice president of Go to Market Strategy and specialization at Splunk. We're talking about the open cybersecurity scheme of framework, also known as the O C sf, a joint strategic collaboration between Splunk and aws. It's got a lot of traction momentum. Patrick, thanks for coming on the cube for reinvent coverage. >>John, great to be here. I'm excited for this. >>You know, I love this open source movement and open source and continues to add value, almost sets the standards. You know, we were talking at the CNCF Linux Foundation this past fall about how standards are coming outta open source. Not so much the the classic standards groups, but you start to see the developers voting with their code groups deciding what to adopt de facto standards and security is a real key part of that where data becomes key for resilience. And this has been the top conversation at reinvent and all around the industry, is how to make data a key part of building into cyber resilience. So I wanna get your thoughts about the problem that you see that's emerging that you guys are solving with this group kind of collaboration around the ocs f >>Yeah, well look, John, I I think, I think you, you've already, you've already hit the high notes there. Data is proliferating across the enterprise. The attack surface area is rapidly expanding. The threat landscape is ever changing. You know, we, we just had a, a lot of scares around open SSL before that we had vulnerabilities and, and Confluence and Atlassian, and you go back to log four J and SolarWinds before that and, and challenges with the supply chain. In this year in particular, we've had a, a huge acceleration in, in concerns and threat vectors around operational technology. In our customer base alone, we saw a huge uptake, you know, and double digit percentage of customers that we're concerned about the traditional vectors like, like ransomware, like business email compromise, phishing, but also from insider threat and others. So you've got this, this highly complex environment where data continues to proliferate and flow through new applications, new infrastructure, new services, driving different types of outcomes in the digitally transformed enterprise of today. >>And, and what happens there is, is our customers, particularly in security, are, are left with having to stitch all of this together. And they're trying to get visibility across multiple different services, infrastructure applications across a number of different point solutions that they've bought to help them protect, defend, detect, and respond better. And it's a massive challenge. And you know, when our, when our customers come to us, they are often looking for ways to drive more consolidation across a variety of different solutions. They're looking to drive better outcomes in terms of speed to detection. How do I detect faster? How do I bind the thing that when bang in the night faster? How do I then fix it quickly? And then how do I layer in some automation so hopefully I don't have to do it again? Now, the challenge there that really OCF Ocsf helps to, to solve is to do that effectively, to detect and to respond at the speed at which attackers are demanding. >>Today we have to have normalization of data across this entire landscape of tools, infrastructure, services. We have to have integration to have visibility, and these tools have to work together. But the biggest barrier to that is often data is stored in different structures and in different formats across different solution providers, across different tools that are, that are, that our customers are using. And that that lack of data, normalization, chokes the integration problem. And so, you know, several years ago, a number of very smart people, and this was, this was a initiative s started by Splunk and AWS came together and said, look, we as an industry have to solve this for our customers. We have to start to shoulder this burden for our customers. We can't, we can't make our customers have to be systems integrators. That's not their job. Our job is to help make this easier for them. And so OCS was born and over the last couple of years we've built out this, this collaboration to not just be AWS and Splunk, but over 50 different organizations, cloud service providers, solution providers in the cybersecurity space have come together and said, let's decide on a single unified schema for how we're gonna represent event data in this industry. And I'm very proud to be here today to say that we've launched it and, and I can't wait to see where we go next. >>Yeah, I mean, this is really compelling. I mean, it's so much packed in that, in that statement, I mean, data normalization, you mentioned chokes, this the, the solution and integration as you call it. But really also it's like data's not just stored in silos. It may not even be available, right? So if you don't have availability of data, that's an important point. Number two, you mentioned supply chain, there's physical supply chain that's coming up big time at reinvent this time as well as in open source, the software supply chain. So you now have the perimeter's been dead for multiple years. We've been talking with that for years, everybody knows that. But now combined with the supply chain problem, both physical and software, there's so much more to go on. And so, you know, the leaders in the industry, they're not sitting on their hands. They know this, but they're just overloaded. So, so how do leaders deal with this right now before we get into the ocs f I wanna just get your thoughts on what's the psychology of the, of the business leader who's facing this landscape? >>Yeah, well, I mean unfortunately too many leaders feel like they have to face these trade offs between, you know, how and where they are really focusing cyber resilience investments in the business. And, and often there is a siloed approach across security, IT developer operations or engineering rather than the ability to kind of drive visibility integration and, and connection of outcomes across those different functions. I mean, the truth is the telemetry that, that you get from an application for application performance monitoring or infrastructure monitoring is often incredibly valuable when there's a security incident and vice versa. Some of the security data that, that you may see in a security operation center can be incredibly valuable in trying to investigate a, a performance degradation in an application and understanding where that may come from. And so what we're seeing is this data layer is collapsing faster than the org charts are or the budget line items are in the enterprise. And so at Splunk here, you know, we believe security resilience is, is fundamentally a data problem. And one of the things that we do often is, is actually help connect the dots for our customers and bring our customers together across the silos they may have internally so that they can start to see a holistic picture of what resilience means for their enterprise and how they can drive faster detection outcomes and more automation coverage. >>You know, we recently had an event called Super Cloud, we're going into the next gen kind of a cloud, how data and security are all kind of part of this NextGen application. It's not just us. And we had a panel that was titled The Innovators Dilemma, kind of talk about you some of the challenges. And one of the panelists said, it's not the innovator's dilemma, it's the integrator's dilemma. And you mentioned that earlier, and I think this a key point right now into integration is so critical, not having the data and putting pieces together now open source is becoming a composability market. And I think having things snap together and work well, it's a platform system conversation, not a tool conversation. So I really wanna get into where the OCS f kind of intersects with this area people are working on. It's not just solution architects or cloud cloud native SREs, especially where DevSecOps is. So this that's right, this intersection is critical. How does Ocsf integrate into that integration of the data making that available to make machine learning and automation smarter and more relevant? >>Right, right. Well look, I mean, I I think that's a fantastic question because, you know, we talk about, we use Bud buzzwords like machine learning and, and AI all the time. And you know, I know they're all over the place here at Reinvent and, and the, there's so much promise and hope out there around these technologies and these innovations. However, machine learning AI is only as effective as the data is clean and normalized. And, and we will not realize the promise of these technologies for outcomes in resilience unless we have better ways to normalize data upstream and better ways to integrate that data to the downstream tools where detection and response is happening. And so Ocsf was really about the industry coming together and saying, this is no longer the job of our customers. We are going to create a unified schema that represents the, an event that we will all bite down on. >>Even some of us are competitors, you know, this is, this is that, that no longer matters because at the point, the point is how do we take this burden off of our customers and how do we make the industry safer together? And so 15 initial members came together along with AWS and Splunk to, to start to create that, that initial schema and standardize it. And if you've ever, you know, if you've ever worked with a bunch of technical grumpy security people, it's kind of hard to drive consensus about around just about anything. But, but I, I'm really happy to see how quickly this, this organization has come together, has open sourced the schema, and, and, and just as you said, like I think this, this unlocks the potential for real innovation that's gonna be required to keep up with the bad guys. But right now is getting stymied and held back by the lack of normalization and the lack of integration. >>I've always said Splunk was a, it eats data for breakfast, lunch, and dinner and turns it into insights. And I think you bring up the silo thing. What's interesting is the cross company sharing, I think this hits point on, so I see this as a valuable opportunity for the industry. What's the traction on that? Because, you know, to succeed it does take a village, it takes a community of security practitioners and, and, and architects and developers to kind of coalesce around this defacto movement has been, has been the uptake been good? How's traction? Can you share your thoughts on how this is translating across companies? >>Yeah, absolutely. I mean, look, I, I think cybersecurity has a, has a long track record of, of, of standards development. There's been some fantastic standards recently. Things like sticks and taxi for threat intelligence. There's been things like the, you know, the Mir attack framework coming outta mi mir and, and, and the adoption, the traction that we've seen with Attack in particular has been amazing to, to watch how that has kind of roared onto the scene in the last couple of years and has become table stakes for how you do security operations and incident response. And, you know, I think with ocs f we're gonna see something similar here, but, you know, we are in literally the first innings of, of this. So right now, you know, we're architecting this into our, into every part of our sort of backend systems here at Polan. I know our our collaborators at AWS and elsewhere are doing it too. >>And so I think it starts with bringing this standard now that the standard exists on a, you know, in schema format and there, there's, you know, confluence and Jira tickets around it, how do we then sort of build this into the code of, of the, the collaborators that have been leading the way on this? And you know, it's not gonna happen overnight, but I think in the coming quarters you'll start to see this schema be the standard across the leaders in this space. Companies like Splunk and AWS and others who are leading the way. And often that's what helps drive adoption of a standard is if you can get the, the big dogs, so to speak, to, to, to embrace it. And, and, you know, there's no bigger one than aws and I think there's no, no more important one than Splunk in the cybersecurity space. And so as we adopt this, we hope others will follow. And, and like I said, we've got over 50 organizations contributing to it today. And so I think we're off to a running >>Start. You know, it's interesting, choking innovation or having things kind of get, get slowed down has really been a problem. We've seen successes recently over the past few years. Like Kubernetes has really unlocked and accelerated the cloud native worlds of runtime with containers to, to kind of have the consensus of the community to say, Hey, if we just do this, it gets better. I think this is really compelling with the o the ocs F because if people can come together around this and get unified as well as all the other official standards, things can go highly accelerated. So I think, I think it looks really good and I think it's great initiative and I really appreciate your insight on that, on, on your relationship with Amazon. Okay. It's not just a partnership, it's a strategic collaboration. Could you share that relationship dynamic, how to start, how's it going, what's strategic about it? Share to the audience kind of the relationship between Splunk and a on this important OCS ocsf initiative. >>Look, I, I mean I think this, this year marks the, the 10th year anniversary that, that Splunk and AWS have been collaborating in a variety of different ways. I, I think our, our companies have a fantastic and, and long standing relationship and we've, we've partnered on a number of really important projects together that bring value obviously to our individual companies, but also to our shared customers. When I think about some of the most important customers at Splunk that I spend a significant amount of time with, I I I know how many of those are, are AWS customers as well, and I know how important AWS is to them. So I think it's, it's a, it's a collaboration that is rooted in, in a respect for each other's technologies and innovation, but also in a recognition that, that our shared customers want to see us work better together over time. And it's not, it's not two companies that have kind of decided in a back room that they should work together. It's actually our customers that are, that are pushing us. And I think we're, we're both very customer centric organizations and I think that has helped us actually be better collaborators and better partners together because we're, we're working back backwards from our customers >>As security becomes a physical and software approach. We've seen the trend where even Steven Schmidt at Amazon Web Services is, is the cso, he is not the CSO anymore. So, and I asked him why, he says, well, security's also physical stuff too. So, so he's that's right. Whole lens is now expanded. You mentioned supply chain, physical, digital, this is an important inflection point. Can you summarize in your mind why open cybersecurity schema for is important? I know the unification, but beyond that, what, why is this so important? Why should people pay attention to this? >>You know, I, if, if you'll let me be just a little abstract in meta for a second. I think what's, what's really meaningful at the highest level about the O C S F initiative, and that goes beyond, I think, the tactical value it will provide to, to organizations and to customers in terms of making them safer over the coming years and, and decades. I think what's more important than that is it's really the, one of the first times that you've seen the industry come together and say, we got a problem. We need to solve. That, you know, doesn't really have anything to do with, with our own economics. Our customers are, are hurt. And yeah, some of us may be competitors, you know, we got different cloud service providers that are participating in this along with aws. We got different cybersecurity solution providers participating in this along with Splunk. >>But, but folks who've come together and say, we can actually solve this problem if, if we're able to kind of put aside our competitive differences in the markets and approach this from the perspective of what's best for information security as a whole. And, and I think that's what I'm most proud of and, and what I hope we can do more of in other places in this industry, because I think that kind of collaboration from real market leaders can actually change markets. It can change the, the, the trend lines in terms of how we are keeping up with the bad guys. And, and I'd like to see a lot more of >>That. And we're seeing a lot more new kind of things emerging in the cloud next kind of this next generation architecture and outcomes are happening. I think it's interesting, you know, we always talk about sustainability, supply chain sustainability about making the earth a better place. But you're hitting on this, this meta point about businesses are under threat of going under. I mean, we want to keep businesses to businesses to be sustainable, not just, you know, the, the environment. So if a business goes outta business business, which they, their threats here are, can be catastrophic for companies. I mean, there is, there is a community responsibility to protect businesses so they can sustain and and stay Yeah. Stay producing. This is a real key point. >>Yeah. Yeah. I mean, look, I think, I think one of the things that, you know, we, we, we complain a lot of in, in cyber security about the lack of, of talent, the talent shortage in cyber security. And every year we kinda, we kind of whack ourselves over the head about how hard it is to bring people into this industry. And it's true. But one of the things that I think we forget, John, is, is how important mission is to so many people in what they do for a living and how they work. And I think one of the things that cybersecurity is strongest in information Security General and has been for decades is this sense of mission and people work in this industry be not because it's, it's, it's always the, the, the most lucrative, but because it, it really drives a sense of safety and security in the enterprises and the fabric of the economy that we use every day to go through our lives. And when I think about the spun customers and AWS customers, I think about the, the different products and tools that power my life and, and we need to secure them. And, and sometimes that means coming to work every day at that company and, and doing your job. And sometimes that means working with others better, faster, and stronger to help drive that level of, of, of maturity and security that this industry >>Needs. It's a human, is a human opportunity, human problem and, and challenge. That's a whole nother segment. The role of the talent and the human machines and with scale. Patrick, thanks so much for sharing the information and the insight on the Open cybersecurity schema frame and what it means and why it's important. Thanks for sharing on the Cube, really appreciate it. >>Thanks for having me, John. >>Okay, this is AWS Reinvent 2022 coverage here on the Cube. I'm John Furry, you're the host. Thanks for watching.

(corporate electronic xylophone jingle intro) >> Good afternoon and welcome back to our very last segment of Tuesday's live broadcast here on theCUBE from AWS re:Invent in fabulous Las Vegas, Nevada. My name is Savannah Peterson and I am joined here by the brilliant Paul Gillin. Paul, end of our first day. You holding up, are you still feeling overwhelmed with fire hose... >> Savannah, yet my feet are killing me. (savannah laughs) >> Yeah, we've done so much walking in these chairs. >> 14,000 steps already today. It's not even dinner time. >> Hey, well, at least you've earned your dinner, Paul. I love that. I love that. I'm very excited about our next guests. We have Krishna and Sowmya joining us from Tata Consultancy Services. Now, I was impressed when I was doing my background research on you all. The Tata Group has locations in 150 different spots, 46 different countries. You have over 600,000 employees on the team. We are talking about absolutely massive scale here but, today we're going to be focused specifically on the Tata Consultancy Services. Sowmya, can you tell me what you all do? What is that team specifically in charge of? >> Yeah, TCS, first of all, thank you very much for inviting us. >> Savannah: Our pleasure. >> Maybe the last session but, we'll make it very lively. >> Savannah: It's going to be the best session. That's the best part of the day. >> Yes, that's the attitude. From a company standpoint, we are a 50 plus year old company. Part of the Tata group. We focus on IT services. We are categorized as industry verticals and we have horizontal services where AWS is one of the horizontal services that we have. And, when I talk about TCS, we focus a lot more on growth and transformation of our customers. That is one of the key objectives of the current company's growth, I would say. So, that is TCS in a nutshell. >> Extraordinarily important topic to be focused on right now. Growth, transformation, pretty much the core topics of the show. I know you're on the hospitality and transportation side of the business, which is very exciting. And, we're going to dig into that a little bit more. Krishna, you're overseeing the world. Tell us a little bit more about your role within the whole ecosystem. >> Yeah, thank you for the opportunity. Great meeting all of you. It's been awesome experience here. re:Invent is coming back, catching up, right? 50,000 people compared to 25,000 last year. So, great to see and meet all of you. Coming to my role, I am responsible for AWS Business Unit within TCS. That means I am responsible for anything that happens on cloud, on AWS. It's a Full Stack unit. I have the global responsibility. That's whether it's a applications, data, infrastructure, transformation that happens, as well as OT at the edge. So, that's my responsibility. >> Savannah: Well, I love talking about the edge. One of my favorite. >> Transformation is a theme of what you do. We heard that the pandemic accelerated digital transformation initiatives at many companies. How did you see the pandemic affecting your business, affecting the customers you were working with? >> Pandemic definitely kind of accelerated a lot of cloud adoption, right? A lot of companies initially focused on resiliency, coming back to handling the pandemic, the situation. But, it also drove a lot of innovation in the business models. They had to think on their feet, re-look at their business models, change the channels and that continued. Pandemic is thankfully gone by but, the transformation actually continued. The way that we actually see on cloud, especially transformation, it has evolved. What we call as Cloud 2.0. Now, cloud is actually more focused on future-proofing the businesses. And, the initial days it was more about future-proofing the technology and technology architecture. But, it has evolved to future-proofing businesses. That means implementing new business models, bringing in agility, measuring the business value. And, that's where we see a significant traction. >> So, it's not about technology then. It's not about infrastructure. >> It is about technology but, really delivering business value. It's about, how can I improve the customer experience? >> Well, can you give us a couple of examples of companies you work with that embody this idea? >> I can imagine in the travel and hospitality zone. Probably few communities more sensitive than when someone's having a disruption or frustration within that process. And, perhaps few time periods less chaotic than the last few years. Tell us about your experience and what you've seen. >> Absolutely. To answer your question, first of all, coming out of pandemic, right? Many customers in the travel and hospitality industry where legacy, did not modernize for the last decade or so because, there have been many ups and downs in the industry. So, during pandemic, post-pandemic, one of the the way they wanted to rebound was, can we do the transformation? First of all, cloud as a technology adoption, but, beyond that, how do customers derive value, business value? That is one of the key aspects of the old transformation. And, if you take, I can give a couple of examples. Avis Car Rental, they had monolith mainframe applications and, that was there for almost couple of decades, right? But, over a period of time, they were not able to have the availability of those applications. There were many outages. As a result, businesses could not do the bookings. Like OTAs, customers could not do the bookings, the application was not available most of the time. And, it's all legacy, right? So, that is where we all came in, TCS. How do we first of all, simplify the complexity of the landscape? That is one. Then, second is, modernize the legacy application. That's the second thing. Third is, how do you scale it? Because, everyone wants to go faster, right? How do you scale it? That is where we partnered with AWS as well, to bring in some specific solutions. One example for Avis', their Rent Shop. Because, of the lack of availability, because, it's monolith application and legacy application. It was not available. So, as a result, we partnered and we brought in our contextual knowledge of the car rental industry to kind of transform, move it to cloud. And, today, as a result of it, Avis was able to save millions of dollars from a MIB standpoint. Second, in terms of availability, that was 99.9% availability. As a result, they had a pick in their business revenue as well. So, this is one of the ways that its helped. The second example I want to quote is, United Airlines. Here again, we've been present for a long time. We have a deep industry knowledge of the airline industry. So, we brought in our airline contextual knowledge and the United landscape to bring in a TCS's solution that we developed. It's called the Aviana. It's an intelligent operations solution for the airline industry, which we have developed. It's on AWS as well, that is being implemented in United. As a result, the ground staff, they have to take decisions on the moment when there is a irregular operation. That could be flight delays, as a result, customers connections will be lost. >> Savannah: Baggage. >> Baggage, right? Baggage delays. >> So many variables. The complexity... >> exactly >> in this matrix is wild. >> So, leveraging the Aviana solution, the ground staff were able to take decisions based on exceptions. They were able to take decisions quickly so that, they improved the customer experience. I think that was one of the key successes for United in the recent times. So, those two are the examples that I would call where customers have the right business value. So, cloud was not just for technology. They all are deriving a lot of business value as well. I would say. >> How important do you think it is for companies facing these unique challenges and scaling to work with partners like TCS? And, I'm sure you would say very important, but, tell me a little bit more why it's so important and those core benefits that they're going to get. Krishna, let's start off with you. Yeah, let me take again the AWS cloud transformation, right? TCS has formed AWS Business Unit two years back. So, we are a covid baby in a way. We have been working with the AWS for more than a decade but, we formed a dedicated Full-Stack Unit to drive cloud transformation on AWS. In these last two years, we've grown three X and customers we have added 400 new customers we have added. >> Nicely done. Just want to see you there. That's huge. Especially during these times. Congratulations. >> So, it's basically about the scale that we bring in. What we have done as a differentiation is, if you look at the entire cloud journey, right from taking a decision which cloud is, right, all the way to the cloud migration modernization and running operations. So, we have built complete platform. AML based platforms, where we have taken our delivery wisdom and codified it onto these platforms. So, we support around thousand plus customers on AWS in varying capacity. All of that knowledge is codified and, that is what we bring to the table, to the customers. And, so, customers obviously appreciate that value that best practices that are coming. And, coupled with that, the industry knowledge that we have on banking, life sciences, healthcare, automotive. So, it's partly the IT, it is the industry transformation as well. Because, we are working on connected cars, for example, in automotive. We are working on accelerated drug development platforms. We're working on complete banks as a platform that we have. TCS has built on AWS. So, 400 customers are there. It's the complete banking and insurance platform. So, this is the combination of the technical expertize that is digitized using platforms, as well as the industry knowledge, is the reason why customers work with us on the cloud transformation. >> So, we're seeing you talk about the vertical industry knowledge. AWS also has its own vertical industry plays. How do you, I guess, coordinate with them or, do you compete with them or, do you stay out of each other's way? >> No, we actually collaborate aggressively. >> Savannah: I like that (laughs) >> Right, so, it's not.. >> Savannah: With vigor. >> With vigor. TCS supports approximately 14 verticals. With AWS, we went with the focused industry play. We said we look at financial services, travel, transportation, hospitality, healthcare, life sciences and automotive, to start with. And, we have Go Big plans with AWS. very focused. The collaboration is actually at the industry solutions because, AWS is a great platform, ever evolving, keeps you on on your toes to really adapt it. But, that is always going on, the collaboration. But, the industry, I'm actually glad AWS last year took a pivot on focusing on industries. Now, we talk the same language when we go in front of a board or a CEO or COO. Present it. We are talking about the future of the industry not just the future of the technology. So, it's a win-win. >> You are also developing products on top of AWS that are not industry verticals, that build on the platform. What kinds of products are those? >> For cloud transformation, for example, consulting. We have a product called Cloud Counsell. We have a decision engine on the data side. We have something called Cloud Foundation, Mason. CloudMason. It's just the foundation, right? And, entire migration and modernization factory. And, the last one on cloud operations is actually Cloud Exponence. So, these are time tested. You have Fortune 500 customers using this regularly actively leveraging that. And, these are all AWS in a well architecture framework certified. So, they work well and they're designed to work on cloud, not only in the native environment, but, also legacy environment. Because, enterprises is not just only native, cloud-native. There is a lot of legacy. Sowmya spoke about the mainframe model... >> So much legacy, we were talking about it. >> So, you have to have a combination of solutions. So, the platforms that we're building, the products we're building, work in both the environments. >> Yeah, and that agility and ability to help customers navigate that prioritization. I mean, there's so many options. We talk about how many new companies there are every year. New solutions. Our adoption of technology is accelerating. As, McKinsey said, we went through 10 years of technological evolution and workplace evolution over the first six months of the pandemic. So, really everything's moving at unprecedented velocity unlike ever before. We have a new game here on theCUBE specifically for this show. And, we are challenging our guests, prompting our guests, to give us a 30 second sizzly sound bite with your hot take on the most important themes of this year's show. Think of it as a thought leadership moment. Opportunity to plug if you really want it. Krishna, you've just given me the nod. I'm going to start with you first and then we'll then we'll pass it along, yeah >> Sure. I think on thought leadership, the way that on cloud, business value is the focus, not the technology. Technology is important, but business value is the focus. And, the way that I see it evolving is with quantum computing coming out more and more, becoming relevant, and Edge is actually becoming quite active as well. All this while on cloud, we focused on business value at the centralized place at the corporate. But, I think the real value of cloud is when you deliver the results, business results, where the customers consume it, that is at the edge. I think that's basically the combination of centralized and the edge is where the real value of cloud is, right. And, I also loud, I know you said 30 seconds but, give me 30 more seconds. >> I like your answer right now. So, I'm going to give you a little more time. Yeah, thank you. >> You've earned more time. (laughs) >> So, I like the way Adam said in the keynote, if you look at it broadly, I categorizes two things. There are a lot of offerings that are becoming comprehensive, like AWS Connect, bringing in workforce management into it, making it a complete end to end product. Similarly, Security Lake, all bringing in the entire security and compliance under one, similarly data. So, there are lot of things that he announced where it is an end to end comprehensiveness of the thing. But, what I love about is, what Amazon is known for, supply chain. So, they rolled out AWS Supply Chain offering. Walk Out technology. So, the Amazon proposition is actually being brought to AWS as a core proposition. I think that's very futuristic and I think we can see more and more customers, enterprise customers, adopting AWS more to drive transformation >> Badly needed right now. Supply chain resiliency. >> Supply chain really having its moment the last two years. File under two words. No one knew, many of us did who worked in it before this. And, here we are, soon as we lost our toilet paper, everyone's freaked out. I love that you talked about business value and also that the end customer is on the edge and, everyone kind of forgets we are essentially the edge device. This is the edge device, it's all around us. And, all the technology that we're all using that you're even talking about is built right inside here from my airlines app to my car rentals to all of it. All right Sowmya, give us your 30 second hot take, roughly. >> Taking the cue from Krishna, right? Today, things are available on AWS Marketplace. So, tomorrow, somebody wants to start an airline, they just have to come and plug and play the apps that are available in the marketplace. Especially your supply chain. The Amazon is known for that. And, a small and medium business they want to start something, right, a .com. It's very easy. So, that's something that we are all looking for. The future is going to be very, very bright and great for the businesses, is what I would say because, most of it could be plug and play with all the solutions. >> Paul: It's already been built. >> On the cloud, so, we are looking forward to it. The second thing I would talk about is, we have to take it to scale. How more and more people can leverage AWS, right? The talent is very important and, that is where partners like us focus on re-scaling our talent. We have 600,000 people, right? We are not just... >> 600,000 people! That's basically as many people live in the San Francisco Bay area for contexts for our listeners. It's how many people work for Walmart? >> It's 1.2 million in Walmart? >> Is it really? >> It is, yes, yes. That's work for Walmart, sidebar. >> So from that standpoint, as the company, we are focusing on re-skilling, up-skilling our talent in order to work AWS cloud and so on, so, that they can go and support our customers. That is something that is very important and that's going to be the future as well. Bring it to scale, go faster. >> I love that you just touched on the fact that you essentially have to practice what you preach because, you've got to think about those 600,000 people in a 100 locations across 40 plus different countries. I love it. Sowmya, I'm going to close on that note. The future is bright, just like your fabulous blazer. >> Thank you so much. Krishna, Sowmya, thank you so much for being here with us. We can't wait to see what happens next, who you help next, and how Tata continues to transform. Thank all of you for tuning in today. A full jam packed day of coverage live here from Las Vegas, Nevada. We are at AWS re:Invent with Paul Gillin. I'm Savannah Peterson. We're theCUBE, the leader in High-Tech Coverage. (corporate electronic xylophone jingle outro)

>>This past May, The Cube in collaboration with Influx data shared with you the latest innovations in Time series databases. We talked at length about why a purpose built time series database for many use cases, was a superior alternative to general purpose databases trying to do the same thing. Now, you may, you may remember the time series data is any data that's stamped in time, and if it's stamped, it can be analyzed historically. And when we introduced the concept to the community, we talked about how in theory, those time slices could be taken, you know, every hour, every minute, every second, you know, down to the millisecond and how the world was moving toward realtime or near realtime data analysis to support physical infrastructure like sensors and other devices and IOT equipment. A time series databases have had to evolve to efficiently support realtime data in emerging use cases in iot T and other use cases. >>And to do that, new architectural innovations have to be brought to bear. As is often the case, open source software is the linchpin to those innovations. Hello and welcome to Evolving Influx DB into the smart Data platform, made possible by influx data and produced by the Cube. My name is Dave Valante and I'll be your host today. Now, in this program, we're going to dig pretty deep into what's happening with Time series data generally, and specifically how Influx DB is evolving to support new workloads and demands and data, and specifically around data analytics use cases in real time. Now, first we're gonna hear from Brian Gilmore, who is the director of IOT and emerging technologies at Influx Data. And we're gonna talk about the continued evolution of Influx DB and the new capabilities enabled by open source generally and specific tools. And in this program, you're gonna hear a lot about things like Rust, implementation of Apache Arrow, the use of par k and tooling such as data fusion, which powering a new engine for Influx db. >>Now, these innovations, they evolve the idea of time series analysis by dramatically increasing the granularity of time series data by compressing the historical time slices, if you will, from, for example, minutes down to milliseconds. And at the same time, enabling real time analytics with an architecture that can process data much faster and much more efficiently. Now, after Brian, we're gonna hear from Anna East Dos Georgio, who is a developer advocate at In Flux Data. And we're gonna get into the why of these open source capabilities and how they contribute to the evolution of the Influx DB platform. And then we're gonna close the program with Tim Yokum, he's the director of engineering at Influx Data, and he's gonna explain how the Influx DB community actually evolved the data engine in mid-flight and which decisions went into the innovations that are coming to the market. Thank you for being here. We hope you enjoy the program. Let's get started. Okay, we're kicking things off with Brian Gilmore. He's the director of i t and emerging Technology at Influx State of Bryan. Welcome to the program. Thanks for coming on. >>Thanks Dave. Great to be here. I appreciate the time. >>Hey, explain why Influx db, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >>No, no, not at all. I mean, I think it's, for us, it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like sql, you know, query support, things like that, we have to figure out a way to, to execute those for them in a way that will scale long term. And then we also, we wanna make sure we're innovating, we're sort of staying ahead of the market as well and sort of anticipating those future needs. So, you know, this is really a, a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine, but you know, initially the customers who are using us are gonna see just great improvements in performance, you know, especially those that are working at the top end of the, of the workload scale, you know, the massive data volumes and things like that. >>Yeah, and we're gonna get into that today and the architecture and the like, but what was the catalyst for the enhancements? I mean, when and how did this all come about? >>Well, I mean, like three years ago we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product, you know, and, and sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was, that was, that was a long journey I guess, you know, phase one was, you know, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to, to optimize for like multi-tenant, multi-cloud, be able to, to host it in a truly like sass manner where we could use, you know, some type of customer activity or consumption as the, the pricing vector, you know, And, and that was sort of the birth of the, of the real first influx DB cloud, you know, which has been really successful. >>We've seen, I think, like 60,000 people sign up and we've got tons and tons of, of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a, on a daily basis, you know, and having that sort of big pool of, of very diverse and very customers to chat with as they're using the product, as they're giving us feedback, et cetera, has has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that and then also making these big leaps as we're doing with this, with this new engine. >>Right. So you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really wanna understand how much of a pivot this is and what, what does it take to make that shift from, you know, time series, you know, specialist to real time analytics and being able to support both? >>Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. You know, time series data is always gonna be fundamental and sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. You know, the time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics, if we're being honest though, I think our, our user base is well aware that the way we were architected was much more towards those sort of like backwards looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a, and a, you know, a time to response on the queries, and can we get that to the point where the results sets are coming back so quickly from the time of query that we can like limit that window down to minutes and then seconds. >>And now with this new engine, we're really starting to talk about a query window that could be like returning results in, in, you know, milliseconds of time since it hit the, the, the ingest queue. And that's, that's really getting to the point where as your data is available, you can use it and you can query it, you can visualize it, and you can do all those sort of magical things with it, you know? And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the, the real time queries, the, the multiple language query support, but, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a a limited number of customers, strategic customers and strategic availability zones to start. But you know, everybody over time. >>So you're basically going from what happened to in, you can still do that obviously, but to what's happening now in the moment? >>Yeah, yeah. I mean, if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the, by the underlying data collection, the architecture, the infrastructure, the, you know, the, the devices and you know, the sort of highly distributed nature of all of this. So yeah, I mean, getting, getting a customer or a user to be able to use the data as soon as it is available is what we're after here. >>I always thought, you know, real, I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >>Yeah, it's, it's, I mean it is operationally or operational real time is different, you know, and that's one of the things that really triggered us to know that we were, we were heading in the right direction, is just how many sort of operational customers we have. You know, everything from like aerospace and defense. We've got companies monitoring satellites, we've got tons of industrial users, users using us as a processes storing on the plant floor, you know, and, and if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're gonna do here is we're gonna start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems. Certainly not their, their historians and databases. >>I, is this available, these innovations to influx DB cloud customers only who can access this capability? >>Yeah. I mean, commercially and today, yes. You know, I think we want to emphasize that's a, for now our goal is to get our latest and greatest and our best to everybody over time. Of course. You know, one of the things we had to do here was like we double down on sort of our, our commitment to open source and availability. So like anybody today can take a look at the, the libraries in on our GitHub and, you know, can ex inspect it and even can try to, you know, implement or execute some of it themselves in their own infrastructure. You know, we are, we're committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. >>And so just, you know, being careful, maybe a little cautious in terms of, of, of how big we go with this right away. Just sort of both limits, you know, the risk of, of, you know, any issues that can come with new software rollouts. We haven't seen anything so far, but also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products, but once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's gonna be exciting time for the whole ecosystem. >>Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are gonna help deliver on this vision. What, what should we know there? >>Well, I mean, I think foundationally we built the, the new core on Rust. You know, this is a new very sort of popular systems language, you know, it's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well. And if it does find error conditions, I mean, we, we've loved working with Go and, you know, a lot of our libraries will continue to, to be sort of implemented in Go, but you know, when it came to this particular new engine, you know, that power performance and stability rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parque for persistence. I think for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our, our time series merged Trees, this is a big break from that, you know, arrow on the sort of in MI side and then Par K in the on disk side. >>It, it allows us to, to present, you know, a unified set of APIs for those really fast real time inquiries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that PARQUE format, which is also cool because there's an entire ecosystem sort of popping up around Parque in terms of the machine learning community, you know, and getting that all to work, we had to glue it together with aero flight. That's sort of what we're using as our, our RPC component. You know, it handles the orchestration and the, the transportation of the Coer data. Now we're moving to like a true Coer database model for this, this version of the engine, you know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like blurring that line between real time and historical data. It's, you know, it's, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >>Yeah. Again, I mean, it's funny you mentioned Rust. It is, it's been around for a long time, but it's popularity is, is, you know, really starting to hit that steep part of the S-curve. And, and we're gonna dig into to more of that, but give us any, is there anything else that we should know about Bryan? Give us the last word? >>Well, I mean, I think first I'd like everybody sort of watching just to like, take a look at what we're offering in terms of early access in beta programs. I mean, if, if, if you wanna participate or if you wanna work sort of in terms of early access with the, with the new engine, please reach out to the team. I'm sure you know, there's a lot of communications going out and, you know, it'll be highly featured on our, our website, you know, but reach out to the team, believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're, we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to because we can flip a lot of stuff on, especially in cloud through feature flags. >>But if there's something new that you wanna try out, we'd just love to hear from you. And then, you know, our goal would be that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to, to sort of build the next versions of your business. Because, you know, the whole database, the ecosystem as it expands out into to, you know, this vertically oriented stack of cloud services and enterprise databases and edge databases, you know, it's gonna be what we all make it together, not just, you know, those of us who were employed by Influx db. And then finally, I would just say please, like watch in ice in Tim's sessions, Like these are two of our best and brightest. They're totally brilliant, completely pragmatic, and they are most of all customer obsessed, which is amazing. And there's no better takes, like honestly on the, the sort of technical details of this, then there's, especially when it comes to like the value that these investments will, will bring to our customers and our communities. So encourage you to, to, you know, pay more attention to them than you did to me, for sure. >>Brian Gilmore, great stuff. Really appreciate your time. Thank you. >>Yeah, thanks Dave. It was awesome. Look forward to it. >>Yeah, me too. Looking forward to see how the, the community actually applies these new innovations and goes, goes beyond just the historical into the real time, really hot area. As Brian said in a moment, I'll be right back with Anna East Dos Georgio to dig into the critical aspects of key open source components of the Influx DB engine, including Rust, Arrow, Parque, data fusion. Keep it right there. You don't want to miss this.

>>This past May, The Cube in collaboration with Influx data shared with you the latest innovations in Time series databases. We talked at length about why a purpose built time series database for many use cases, was a superior alternative to general purpose databases trying to do the same thing. Now, you may, you may remember the time series data is any data that's stamped in time, and if it's stamped, it can be analyzed historically. And when we introduced the concept to the community, we talked about how in theory, those time slices could be taken, you know, every hour, every minute, every second, you know, down to the millisecond and how the world was moving toward realtime or near realtime data analysis to support physical infrastructure like sensors and other devices and IOT equipment. A time series databases have had to evolve to efficiently support realtime data in emerging use cases in iot T and other use cases. >>And to do that, new architectural innovations have to be brought to bear. As is often the case, open source software is the linchpin to those innovations. Hello and welcome to Evolving Influx DB into the smart Data platform, made possible by influx data and produced by the Cube. My name is Dave Valante and I'll be your host today. Now in this program we're going to dig pretty deep into what's happening with Time series data generally, and specifically how Influx DB is evolving to support new workloads and demands and data, and specifically around data analytics use cases in real time. Now, first we're gonna hear from Brian Gilmore, who is the director of IOT and emerging technologies at Influx Data. And we're gonna talk about the continued evolution of Influx DB and the new capabilities enabled by open source generally and specific tools. And in this program you're gonna hear a lot about things like Rust, implementation of Apache Arrow, the use of par k and tooling such as data fusion, which powering a new engine for Influx db. >>Now, these innovations, they evolve the idea of time series analysis by dramatically increasing the granularity of time series data by compressing the historical time slices, if you will, from, for example, minutes down to milliseconds. And at the same time, enabling real time analytics with an architecture that can process data much faster and much more efficiently. Now, after Brian, we're gonna hear from Anna East Dos Georgio, who is a developer advocate at In Flux Data. And we're gonna get into the why of these open source capabilities and how they contribute to the evolution of the Influx DB platform. And then we're gonna close the program with Tim Yokum, he's the director of engineering at Influx Data, and he's gonna explain how the Influx DB community actually evolved the data engine in mid-flight and which decisions went into the innovations that are coming to the market. Thank you for being here. We hope you enjoy the program. Let's get started. Okay, we're kicking things off with Brian Gilmore. He's the director of i t and emerging Technology at Influx State of Bryan. Welcome to the program. Thanks for coming on. >>Thanks Dave. Great to be here. I appreciate the time. >>Hey, explain why Influx db, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >>No, no, not at all. I mean, I think it's, for us, it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like sql, you know, query support, things like that, we have to figure out a way to, to execute those for them in a way that will scale long term. And then we also, we wanna make sure we're innovating, we're sort of staying ahead of the market as well and sort of anticipating those future needs. So, you know, this is really a, a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine, but you know, initially the customers who are using us are gonna see just great improvements in performance, you know, especially those that are working at the top end of the, of the workload scale, you know, the massive data volumes and things like that. >>Yeah, and we're gonna get into that today and the architecture and the like, but what was the catalyst for the enhancements? I mean, when and how did this all come about? >>Well, I mean, like three years ago we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product, you know, and, and sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was, that was, that was a long journey I guess, you know, phase one was, you know, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to, to optimize for like multi-tenant, multi-cloud, be able to, to host it in a truly like sass manner where we could use, you know, some type of customer activity or consumption as the, the pricing vector, you know, And, and that was sort of the birth of the, of the real first influx DB cloud, you know, which has been really successful. >>We've seen, I think like 60,000 people sign up and we've got tons and tons of, of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a, on a daily basis, you know, and having that sort of big pool of, of very diverse and very customers to chat with as they're using the product, as they're giving us feedback, et cetera, has has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that and then also making these big leaps as we're doing with this, with this new engine. >>Right. So you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really wanna understand how much of a pivot this is and what, what does it take to make that shift from, you know, time series, you know, specialist to real time analytics and being able to support both? >>Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. You know, time series data is always gonna be fundamental and sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. You know, the time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics, if we're being honest though, I think our, our user base is well aware that the way we were architected was much more towards those sort of like backwards looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a, and a, you know, a time to response on the queries, and can we get that to the point where the results sets are coming back so quickly from the time of query that we can like limit that window down to minutes and then seconds. >>And now with this new engine, we're really starting to talk about a query window that could be like returning results in, in, you know, milliseconds of time since it hit the, the, the ingest queue. And that's, that's really getting to the point where as your data is available, you can use it and you can query it, you can visualize it, and you can do all those sort of magical things with it, you know? And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the, the real time queries, the, the multiple language query support, but, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a a limited number of customers, strategic customers and strategic availability zones to start. But you know, everybody over time. >>So you're basically going from what happened to in, you can still do that obviously, but to what's happening now in the moment? >>Yeah, yeah. I mean if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the, by the underlying data collection, the architecture, the infrastructure, the, you know, the, the devices and you know, the sort of highly distributed nature of all of this. So yeah, I mean, getting, getting a customer or a user to be able to use the data as soon as it is available is what we're after here. >>I always thought, you know, real, I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >>Yeah, it's, it's, I mean it is operationally or operational real time is different, you know, and that's one of the things that really triggered us to know that we were, we were heading in the right direction, is just how many sort of operational customers we have. You know, everything from like aerospace and defense. We've got companies monitoring satellites, we've got tons of industrial users, users using us as a processes storing on the plant floor, you know, and, and if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're gonna do here is we're gonna start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems, certainly not their, their historians and databases. >>I, is this available, these innovations to influx DB cloud customers only who can access this capability? >>Yeah. I mean commercially and today, yes. You know, I think we want to emphasize that's a, for now our goal is to get our latest and greatest and our best to everybody over time. Of course. You know, one of the things we had to do here was like we double down on sort of our, our commitment to open source and availability. So like anybody today can take a look at the, the libraries in on our GitHub and, you know, can ex inspect it and even can try to, you know, implement or execute some of it themselves in their own infrastructure. You know, we are, we're committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. >>And so just, you know, being careful, maybe a little cautious in terms of, of, of how big we go with this right away, just sort of both limits, you know, the risk of, of, you know, any issues that can come with new software rollouts. We haven't seen anything so far, but also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products, but once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's gonna be exciting time for the whole ecosystem. >>Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are gonna help deliver on this vision. What, what should we know there? >>Well, I mean, I think foundationally we built the, the new core on Rust. You know, this is a new very sort of popular systems language, you know, it's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well. And if it does find error conditions, I mean we, we've loved working with Go and, you know, a lot of our libraries will continue to, to be sort of implemented in Go, but you know, when it came to this particular new engine, you know, that power performance and stability rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parque for persistence. I think for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our, our time series merged Trees, this is a big break from that, you know, arrow on the sort of in MI side and then Par K in the on disk side. >>It, it allows us to, to present, you know, a unified set of APIs for those really fast real time inquiries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that PARQUE format, which is also cool because there's an entire ecosystem sort of popping up around Parque in terms of the machine learning community, you know, and getting that all to work, we had to glue it together with aero flight. That's sort of what we're using as our, our RPC component. You know, it handles the orchestration and the, the transportation of the Coer data. Now we're moving to like a true Coer database model for this, this version of the engine, you know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like blurring that line between real time and historical data. It's, you know, it's, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >>Yeah. Again, I mean, it's funny you mentioned Rust. It is, it's been around for a long time, but it's popularity is, is you know, really starting to hit that steep part of the S-curve. And, and we're gonna dig into to more of that, but give us any, is there anything else that we should know about Bryan? Give us the last word? >>Well, I mean, I think first I'd like everybody sort of watching just to like take a look at what we're offering in terms of early access in beta programs. I mean, if, if, if you wanna participate or if you wanna work sort of in terms of early access with the, with the new engine, please reach out to the team. I'm sure you know, there's a lot of communications going out and you know, it'll be highly featured on our, our website, you know, but reach out to the team, believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're, we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to because we can flip a lot of stuff on, especially in cloud through feature flags. >>But if there's something new that you wanna try out, we'd just love to hear from you. And then, you know, our goal would be that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to, to sort of build the next versions of your business. Because you know, the whole database, the ecosystem as it expands out into to, you know, this vertically oriented stack of cloud services and enterprise databases and edge databases, you know, it's gonna be what we all make it together, not just, you know, those of us who were employed by Influx db. And then finally I would just say please, like watch in ICE in Tim's sessions, like these are two of our best and brightest, They're totally brilliant, completely pragmatic, and they are most of all customer obsessed, which is amazing. And there's no better takes, like honestly on the, the sort of technical details of this, then there's, especially when it comes to like the value that these investments will, will bring to our customers and our communities. So encourage you to, to, you know, pay more attention to them than you did to me, for sure. >>Brian Gilmore, great stuff. Really appreciate your time. Thank you. >>Yeah, thanks Dave. It was awesome. Look forward to it. >>Yeah, me too. Looking forward to see how the, the community actually applies these new innovations and goes, goes beyond just the historical into the real time really hot area. As Brian said in a moment, I'll be right back with Anna East dos Georgio to dig into the critical aspects of key open source components of the Influx DB engine, including Rust, Arrow, Parque, data fusion. Keep it right there. You don't wanna miss this >>Time series Data is everywhere. The number of sensors, systems and applications generating time series data increases every day. All these data sources producing so much data can cause analysis paralysis. Influx DB is an entire platform designed with everything you need to quickly build applications that generate value from time series data influx. DB Cloud is a serverless solution, which means you don't need to buy or manage your own servers. There's no need to worry about provisioning because you only pay for what you use. Influx DB Cloud is fully managed so you get the newest features and enhancements as they're added to the platform's code base. It also means you can spend time building solutions and delivering value to your users instead of wasting time and effort managing something else. Influx TVB Cloud offers a range of security features to protect your data, multiple layers of redundancy ensure you don't lose any data access controls ensure that only the people who should see your data can see it. >>And encryption protects your data at rest and in transit between any of our regions or cloud providers. InfluxDB uses a single API across the entire platform suite so you can build on open source, deploy to the cloud and then then easily query data in the cloud at the edge or on prem using the same scripts. And InfluxDB is schemaless automatically adjusting to changes in the shape of your data without requiring changes in your application. Logic. InfluxDB Cloud is production ready from day one. All it needs is your data and your imagination. Get started today@influxdata.com slash cloud. >>Okay, we're back. I'm Dave Valante with a Cube and you're watching evolving Influx DB into the smart data platform made possible by influx data. Anna ETOs Georgio is here, she's a developer advocate for influx data and we're gonna dig into the rationale and value contribution behind several open source technologies that Influx DB is leveraging to increase the granularity of time series analysis analysis and bring the world of data into real-time analytics and is welcome to the program. Thanks for coming on. >>Hi, thank you so much. It's a pleasure to be here. >>Oh, you're very welcome. Okay, so IX is being touted as this next gen open source core for Influx db. And my understanding is that it leverages in memory of course for speed. It's a kilo store, so it gives you a compression efficiency, it's gonna give you faster query speeds, you store files and object storage, so you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features, but what are the high level value points that people should understand? >>Sure, that's a great question. So some of the main requirements that IOx is trying to achieve and some of the most impressive ones to me, the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want, whether that's live tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metrics queries, we also wanna have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import super useful. Also broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like sql, Python, and maybe even pandas in the future. >>Okay, so lot there. Now we talked to Brian about how you're using Rust and which is not a new programming language and of course we had some drama around Rust during the pandemic with the Mozilla layoffs, but the formation of the Rust Foundation really addressed any of those concerns. You got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really, the adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with rust, but why rust as an alternative to say c plus plus for example? >>Sure, that's a great question. So Russ was chosen because of his exceptional performance and reliability. So while Russ is synt tactically similar to c plus plus and it has similar performance, it also compiles to a native code like c plus plus. But unlike c plus plus, it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers. And dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like c plus plus. So Russ like helps meet that requirement of having no limits on ality, for example, because it's, we're also using the Russ implementation of Apache Arrow and this control over memory and also Russ Russ's packaging system called crates IO offers everything that you need out of the box to have features like AY and a weight to fix race conditions, to protection against buffering overflows and to ensure thread safe async cashing structures as well. So essentially it's just like has all the control, all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high ity use cases. >>Yeah, and the more I learn about the, the new engine and, and the platform IOCs et cetera, you know, you, you see things like, you know, the old days not even to even today you do a lot of garbage collection in these, in these systems and there's an inverse, you know, impact relative to performance. So it looks like you really, you know, the community is modernizing the platform, but I wanna talk about Apache Arrow for a moment. It it's designed to address the constraints that are associated with analyzing large data sets. We, we know that, but please explain why, what, what is Arrow and and what does it bring to Influx db? >>Sure, yeah. So Arrow is a, a framework for defining in memory calmer data. And so much of the efficiency and performance of IOx comes from taking advantage of calmer data structures. And I will, if you don't mind, take a moment to kind of of illustrate why column or data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our stove. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value, maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the stove. Well usually our room temperature is regulated so those values don't change very often. >>So when you have calm oriented st calm oriented storage, essentially you take each row, each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same, then you'll, you might be able to imagine how equal values will then enable each other and when they neighbor each other in the storage format, this provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you wanna define like the men and max value of the temperature in the room across a thousand different points, you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of calmer oriented storage. >>So if you had a row oriented storage, you'd first have to look at every field like the temperature in, in the room and the temperature of the stove. You'd have to go across every tag value that maybe describes where the room is located or what model the stove is. And every timestamp you'd then have to pluck out that one temperature value that you want at that one time stamp and do that for every single row. So you're scanning across a ton more data and that's why Rowe Oriented doesn't provide the same efficiency as calmer and Apache Arrow is in memory calmer data, commoner data fit framework. So that's where a lot of the advantages come >>From. Okay. So you basically described like a traditional database, a row approach, but I've seen like a lot of traditional database say, okay, now we've got, we can handle colo format versus what you're talking about is really, you know, kind of native i, is it not as effective? Is the, is the foreman not as effective because it's largely a, a bolt on? Can you, can you like elucidate on that front? >>Yeah, it's, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why, why RO row oriented storage isn't as efficient as calm, calmer oriented storage. Yeah. >>Got it. So let's talk about Arrow Data Fusion. What is data fusion? I know it's written in Rust, but what does it bring to the table here? >>Sure. So it's an extensible query execution framework and it uses Arrow as it's in memory format. So the way that it helps in influx DB IOCs is that okay, it's great if you can write unlimited amount of cardinality into influx Cbis, but if you don't have a query engine that can successfully query that data, then I don't know how much value it is for you. So Data fusion helps enable the, the query process and transformation of that data. It also has a PANDAS API so that you could take advantage of PANDAS data frames as well and all of the machine learning tools associated with Pandas. >>Okay. You're also leveraging Par K in the platform cause we heard a lot about Par K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Parque and why is it important? >>Sure. So parque is the column oriented durable file format. So it's important because it'll enable bulk import, bulk export, it has compatibility with Python and Pandas, so it supports a broader ecosystem. Par K files also take very little disc disc space and they're faster to scan because again, they're column oriented in particular, I think PAR K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the, the benefits of par k. >>Got it. Very popular. So and he's, what exactly is influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >>Sure. So Influx DB first has contributed a lot of different, different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing with flux. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up, then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >>Yeah. Got it. You got that virtuous cycle going, the people call the flywheel. Give us your last thoughts and kind of summarize, you know, where what, what the big takeaways are from your perspective. >>So I think the big takeaway is that influx data is doing a lot of really exciting things with Influx DB IOx and I really encourage, if you are interested in learning more about the technologies that Influx is leveraging to produce IOCs, the challenges associated with it and all of the hard work questions and you just wanna learn more, then I would encourage you to go to the monthly Tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel look for the influx DDB unders IAC channel specifically to learn more about how to join those office hours and those monthly tech tech talks as well as ask any questions they have about iacs, what to expect and what you'd like to learn more about. I as a developer advocate, I wanna answer your questions. So if there's a particular technology or stack that you wanna dive deeper into and want more explanation about how INFLUX DB leverages it to build IOCs, I will be really excited to produce content on that topic for you. >>Yeah, that's awesome. You guys have a really rich community, collaborate with your peers, solve problems, and, and you guys super responsive, so really appreciate that. All right, thank you so much Anise for explaining all this open source stuff to the audience and why it's important to the future of data. >>Thank you. I really appreciate it. >>All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yoakum, he's the director of engineering for Influx Data and we're gonna talk about how you update a SAS engine while the plane is flying at 30,000 feet. You don't wanna miss this. >>I'm really glad that we went with InfluxDB Cloud for our hosting because it has saved us a ton of time. It's helped us move faster, it's saved us money. And also InfluxDB has good support. My name's Alex Nada. I am CTO at Noble nine. Noble Nine is a platform to measure and manage service level objectives, which is a great way of measuring the reliability of your systems. You can essentially think of an slo, the product we're providing to our customers as a bunch of time series. So we need a way to store that data and the corresponding time series that are related to those. The main reason that we settled on InfluxDB as we were shopping around is that InfluxDB has a very flexible query language and as a general purpose time series database, it basically had the set of features we were looking for. >>As our platform has grown, we found InfluxDB Cloud to be a really scalable solution. We can quickly iterate on new features and functionality because Influx Cloud is entirely managed, it probably saved us at least a full additional person on our team. We also have the option of running InfluxDB Enterprise, which gives us the ability to even host off the cloud or in a private cloud if that's preferred by a customer. Influx data has been really flexible in adapting to the hosting requirements that we have. They listened to the challenges we were facing and they helped us solve it. As we've continued to grow, I'm really happy we have influx data by our side. >>Okay, we're back with Tim Yokum, who is the director of engineering at Influx Data. Tim, welcome. Good to see you. >>Good to see you. Thanks for having me. >>You're really welcome. Listen, we've been covering open source software in the cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem. The cloud has been being built out on open source, mobile, social platforms, key databases, and of course influx DB and influx data has been a big consumer and contributor of open source software. So my question to you is, where have you seen the biggest bang for the buck from open source software? >>So yeah, you know, influx really, we thrive at the intersection of commercial services and open, so open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services temping engines. Our, our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants and like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product influx db. >>You know, but I gotta ask you, Tim, because one of the challenge that that we've seen in particular, you saw this in the heyday of Hadoop, the, the innovations come so fast and furious and as a software company you gotta place bets, you gotta, you know, commit people and sometimes those bets can be risky and not pay off well, how have you managed this challenge? >>Oh, it moves fast. Yeah, that, that's a benefit though because it, the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we, what we tend to do is, is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example, that ecosystem is driven by thousands of intelligent developers, engineers, builders, they're adding value every day. So we have to really keep up with that. And as the stack changes, we, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's, it's something that we just do every day. >>So we have a survey partner down in New York City called Enterprise Technology Research etr, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity particularly, you know, along with cloud. But, but really Kubernetes is just, you know, still up until the right consistently even with, you know, the macro headwinds and all, all of the stuff that we're sick of talking about. But, so what are you doing with Kubernetes in the platform? >>Yeah, it, it's really central to our ability to run the product. When we first started out, we were just on AWS and, and the way we were running was, was a little bit like containers junior. Now we're running Kubernetes everywhere at aws, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code so our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google and figure out how to deliver services on those three clouds with all of their differences. >>Just to follow up on that, is it, no. So I presume it's sounds like there's a PAs layer there to allow you guys to have a consistent experience across clouds and out to the edge, you know, wherever is that, is that correct? >>Yeah, so we've basically built more or less platform engineering, This is the new hot phrase, you know, it, it's, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that, that just gets all of the underlying infrastructure out of the way and, and lets them focus on delivering influx cloud. >>Yeah, and I know I'm taking a little bit of a tangent, but is that, that, I'll call it a PAs layer if I can use that term. Is that, are there specific attributes to Influx db or is it kind of just generally off the shelf paths? You know, are there, is, is there any purpose built capability there that, that is, is value add or is it pretty much generic? >>So we really build, we, we look at things through, with a build versus buy through a, a build versus by lens. Some things we want to leverage cloud provider services, for instance, Postgres databases for metadata, perhaps we'll get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can, can deliver on that has consistency that is, is all generated from code that we can as a, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions and in no time. >>So how, so sometimes you build, sometimes you buy it. How do you make those decisions and and what does that mean for the, for the platform and for customers? >>Yeah, so what we're doing is, it's like everybody else will do, we're we're looking for trade offs that make sense. You know, we really want to protect our customers data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers you don't even see that, but we don't want to try to reinvent the wheel, like I had mentioned with SQL data stores for metadata, perhaps let's build on top of what of these three large cloud providers have already perfected. And we can then focus on our platform engineering and we can have our developers then focus on the influx data, software, influx, cloud software. >>So take it to the customer level, what does it mean for them? What's the value that they're gonna get out of all these innovations that we've been been talking about today and what can they expect in the future? >>So first of all, people who use the OSS product are really gonna be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across, over 4 billion series keys that people have stored. So there's a proven ability to scale now in terms of the open source, open source software and how we've developed the platform. You're getting highly available high cardinality time series platform. We manage it and, and really as, as I mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in real time. We deploy to our platform every day repeatedly all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change new features, better ways of doing deployments, safer ways of doing deployments. >>All of that happens behind the scenes. And like we had mentioned earlier, Kubernetes, I mean that, that allows us to get that done. We couldn't do it without having that platform as a, as a base layer for us to then put our software on. So we, we iterate quickly. When you're on the, the Influx cloud platform, you really are able to, to take advantage of new features immediately. We roll things out every day and as those things go into production, you have, you have the ability to, to use them. And so in the end we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let, let us do that for you. So, >>And that makes sense, but so is the, is the, are the innovations that we're talking about in the evolution of Influx db, do, do you see that as sort of a natural evolution for existing customers? I, is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >>Yeah, it really is it, it's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are, are really the hot thing. Iot, industrial iot especially, people want to just shove tons of data out there and be able to do queries immediately and they don't wanna manage infrastructure. What we've started to see are people that use the cloud service as their, their data store backbone and then they use edge computing with R OSS product to ingest data from say, multiple production lines and downsample that data, send the rest of that data off influx cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that and being in all sorts of different regions allows for people to really get out of the, the business of man trying to manage that big data, have us take care of that. And of course as we change the platform end users benefit from that immediately. And, >>And so obviously taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IOT and the Edge? How should we be thinking about the value that you bring from a security perspective? >>Yeah, we take, we take security super seriously. It, it's built into our dna. We do a lot of work to ensure that our platform is secure, that the data we store is, is kept private. It's of course always a concern. You see in the news all the time, companies being compromised, you know, that's something that you can have an entire team working on, which we do to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You know, you look at things like software, bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that, that's just part of our jobs to make sure that the platform that we're running it has, has fully vetted software and, and with open source especially, that's a lot of work. And so it's, it's definitely new territory. Supply chain attacks are, are definitely happening at a higher clip than they used to, but that is, that is really just part of a day in the, the life for folks like us that are, are building platforms. >>Yeah, and that's key. I mean especially when you start getting into the, the, you know, we talk about IOT and the operations technologies, the engineers running the, that infrastructure, you know, historically, as you know, Tim, they, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >>That >>Connected now, right? And so you've gotta have a partner that is again, take away that heavy lifting to r and d so you can focus on some of the other activities. Right. Give us the, the last word and the, the key takeaways from your perspective. >>Well, you know, from my perspective I see it as, as a a two lane approach with, with influx, with Anytime series data, you know, you've got a lot of stuff that you're gonna run on-prem, what you had mentioned, air gaping. Sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want torus their data to, to a company that's, that's got a full platform set up for them that they can build on, send that data over to the cloud, the cloud is not going away. I think more hybrid approach is, is where the future lives and that's what we're prepared for. >>Tim, really appreciate you coming to the program. Great stuff. Good to see you. >>Thanks very much. Appreciate it. >>Okay, in a moment I'll be back to wrap up. Today's session, you're watching The Cube. >>Are you looking for some help getting started with InfluxDB Telegraph or Flux Check >>Out Influx DB University >>Where you can find our entire catalog of free training that will help you make the most of your time series data >>Get >>Started for free@influxdbu.com. >>We'll see you in class. >>Okay, so we heard today from three experts on time series and data, how the Influx DB platform is evolving to support new ways of analyzing large data sets very efficiently and effectively in real time. And we learned that key open source components like Apache Arrow and the Rust Programming environment Data fusion par K are being leveraged to support realtime data analytics at scale. We also learned about the contributions in importance of open source software and how the Influx DB community is evolving the platform with minimal disruption to support new workloads, new use cases, and the future of realtime data analytics. Now remember these sessions, they're all available on demand. You can go to the cube.net to find those. Don't forget to check out silicon angle.com for all the news related to things enterprise and emerging tech. And you should also check out influx data.com. There you can learn about the company's products. You'll find developer resources like free courses. You could join the developer community and work with your peers to learn and solve problems. And there are plenty of other resources around use cases and customer stories on the website. This is Dave Valante. Thank you for watching Evolving Influx DB into the smart data platform, made possible by influx data and brought to you by the Cube, your leader in enterprise and emerging tech coverage.

>>This past May, The Cube in collaboration with Influx data shared with you the latest innovations in Time series databases. We talked at length about why a purpose built time series database for many use cases, was a superior alternative to general purpose databases trying to do the same thing. Now, you may, you may remember the time series data is any data that's stamped in time, and if it's stamped, it can be analyzed historically. And when we introduced the concept to the community, we talked about how in theory, those time slices could be taken, you know, every hour, every minute, every second, you know, down to the millisecond and how the world was moving toward realtime or near realtime data analysis to support physical infrastructure like sensors and other devices and IOT equipment. A time series databases have had to evolve to efficiently support realtime data in emerging use cases in iot T and other use cases. >>And to do that, new architectural innovations have to be brought to bear. As is often the case, open source software is the linchpin to those innovations. Hello and welcome to Evolving Influx DB into the smart Data platform, made possible by influx data and produced by the Cube. My name is Dave Valante and I'll be your host today. Now in this program we're going to dig pretty deep into what's happening with Time series data generally, and specifically how Influx DB is evolving to support new workloads and demands and data, and specifically around data analytics use cases in real time. Now, first we're gonna hear from Brian Gilmore, who is the director of IOT and emerging technologies at Influx Data. And we're gonna talk about the continued evolution of Influx DB and the new capabilities enabled by open source generally and specific tools. And in this program you're gonna hear a lot about things like Rust, implementation of Apache Arrow, the use of par k and tooling such as data fusion, which powering a new engine for Influx db. >>Now, these innovations, they evolve the idea of time series analysis by dramatically increasing the granularity of time series data by compressing the historical time slices, if you will, from, for example, minutes down to milliseconds. And at the same time, enabling real time analytics with an architecture that can process data much faster and much more efficiently. Now, after Brian, we're gonna hear from Anna East Dos Georgio, who is a developer advocate at In Flux Data. And we're gonna get into the why of these open source capabilities and how they contribute to the evolution of the Influx DB platform. And then we're gonna close the program with Tim Yokum, he's the director of engineering at Influx Data, and he's gonna explain how the Influx DB community actually evolved the data engine in mid-flight and which decisions went into the innovations that are coming to the market. Thank you for being here. We hope you enjoy the program. Let's get started. Okay, we're kicking things off with Brian Gilmore. He's the director of i t and emerging Technology at Influx State of Bryan. Welcome to the program. Thanks for coming on. >>Thanks Dave. Great to be here. I appreciate the time. >>Hey, explain why Influx db, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >>No, no, not at all. I mean, I think it's, for us, it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like sql, you know, query support, things like that, we have to figure out a way to, to execute those for them in a way that will scale long term. And then we also, we wanna make sure we're innovating, we're sort of staying ahead of the market as well and sort of anticipating those future needs. So, you know, this is really a, a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine, but you know, initially the customers who are using us are gonna see just great improvements in performance, you know, especially those that are working at the top end of the, of the workload scale, you know, the massive data volumes and things like that. >>Yeah, and we're gonna get into that today and the architecture and the like, but what was the catalyst for the enhancements? I mean, when and how did this all come about? >>Well, I mean, like three years ago we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product, you know, and, and sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was, that was, that was a long journey I guess, you know, phase one was, you know, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to, to optimize for like multi-tenant, multi-cloud, be able to, to host it in a truly like sass manner where we could use, you know, some type of customer activity or consumption as the, the pricing vector, you know, And, and that was sort of the birth of the, of the real first influx DB cloud, you know, which has been really successful. >>We've seen, I think like 60,000 people sign up and we've got tons and tons of, of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a, on a daily basis, you know, and having that sort of big pool of, of very diverse and very customers to chat with as they're using the product, as they're giving us feedback, et cetera, has has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that and then also making these big leaps as we're doing with this, with this new engine. >>Right. So you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really wanna understand how much of a pivot this is and what, what does it take to make that shift from, you know, time series, you know, specialist to real time analytics and being able to support both? >>Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. You know, time series data is always gonna be fundamental and sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. You know, the time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics, if we're being honest though, I think our, our user base is well aware that the way we were architected was much more towards those sort of like backwards looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a, and a, you know, a time to response on the queries, and can we get that to the point where the results sets are coming back so quickly from the time of query that we can like limit that window down to minutes and then seconds. >>And now with this new engine, we're really starting to talk about a query window that could be like returning results in, in, you know, milliseconds of time since it hit the, the, the ingest queue. And that's, that's really getting to the point where as your data is available, you can use it and you can query it, you can visualize it, and you can do all those sort of magical things with it, you know? And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the, the real time queries, the, the multiple language query support, but, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a a limited number of customers, strategic customers and strategic availability zones to start. But you know, everybody over time. >>So you're basically going from what happened to in, you can still do that obviously, but to what's happening now in the moment? >>Yeah, yeah. I mean if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the, by the underlying data collection, the architecture, the infrastructure, the, you know, the, the devices and you know, the sort of highly distributed nature of all of this. So yeah, I mean, getting, getting a customer or a user to be able to use the data as soon as it is available is what we're after here. >>I always thought, you know, real, I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >>Yeah, it's, it's, I mean it is operationally or operational real time is different, you know, and that's one of the things that really triggered us to know that we were, we were heading in the right direction, is just how many sort of operational customers we have. You know, everything from like aerospace and defense. We've got companies monitoring satellites, we've got tons of industrial users, users using us as a processes storing on the plant floor, you know, and, and if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're gonna do here is we're gonna start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems, certainly not their, their historians and databases. >>I, is this available, these innovations to influx DB cloud customers only who can access this capability? >>Yeah. I mean commercially and today, yes. You know, I think we want to emphasize that's a, for now our goal is to get our latest and greatest and our best to everybody over time. Of course. You know, one of the things we had to do here was like we double down on sort of our, our commitment to open source and availability. So like anybody today can take a look at the, the libraries in on our GitHub and, you know, can ex inspect it and even can try to, you know, implement or execute some of it themselves in their own infrastructure. You know, we are, we're committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. >>And so just, you know, being careful, maybe a little cautious in terms of, of, of how big we go with this right away, just sort of both limits, you know, the risk of, of, you know, any issues that can come with new software rollouts. We haven't seen anything so far, but also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products, but once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's gonna be exciting time for the whole ecosystem. >>Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are gonna help deliver on this vision. What, what should we know there? >>Well, I mean, I think foundationally we built the, the new core on Rust. You know, this is a new very sort of popular systems language, you know, it's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well. And if it does find error conditions, I mean we, we've loved working with Go and, you know, a lot of our libraries will continue to, to be sort of implemented in Go, but you know, when it came to this particular new engine, you know, that power performance and stability rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parque for persistence. I think for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our, our time series merged Trees, this is a big break from that, you know, arrow on the sort of in MI side and then Par K in the on disk side. >>It, it allows us to, to present, you know, a unified set of APIs for those really fast real time inquiries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that PARQUE format, which is also cool because there's an entire ecosystem sort of popping up around Parque in terms of the machine learning community, you know, and getting that all to work, we had to glue it together with aero flight. That's sort of what we're using as our, our RPC component. You know, it handles the orchestration and the, the transportation of the Coer data. Now we're moving to like a true Coer database model for this, this version of the engine, you know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like blurring that line between real time and historical data. It's, you know, it's, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >>Yeah. Again, I mean, it's funny you mentioned Rust. It is, it's been around for a long time, but it's popularity is, is you know, really starting to hit that steep part of the S-curve. And, and we're gonna dig into to more of that, but give us any, is there anything else that we should know about Bryan? Give us the last word? >>Well, I mean, I think first I'd like everybody sort of watching just to like take a look at what we're offering in terms of early access in beta programs. I mean, if, if, if you wanna participate or if you wanna work sort of in terms of early access with the, with the new engine, please reach out to the team. I'm sure you know, there's a lot of communications going out and you know, it'll be highly featured on our, our website, you know, but reach out to the team, believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're, we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to because we can flip a lot of stuff on, especially in cloud through feature flags. >>But if there's something new that you wanna try out, we'd just love to hear from you. And then, you know, our goal would be that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to, to sort of build the next versions of your business. Because you know, the whole database, the ecosystem as it expands out into to, you know, this vertically oriented stack of cloud services and enterprise databases and edge databases, you know, it's gonna be what we all make it together, not just, you know, those of us who were employed by Influx db. And then finally I would just say please, like watch in ICE in Tim's sessions, like these are two of our best and brightest, They're totally brilliant, completely pragmatic, and they are most of all customer obsessed, which is amazing. And there's no better takes, like honestly on the, the sort of technical details of this, then there's, especially when it comes to like the value that these investments will, will bring to our customers and our communities. So encourage you to, to, you know, pay more attention to them than you did to me, for sure. >>Brian Gilmore, great stuff. Really appreciate your time. Thank you. >>Yeah, thanks Dave. It was awesome. Look forward to it. >>Yeah, me too. Looking forward to see how the, the community actually applies these new innovations and goes, goes beyond just the historical into the real time really hot area. As Brian said in a moment, I'll be right back with Anna East dos Georgio to dig into the critical aspects of key open source components of the Influx DB engine, including Rust, Arrow, Parque, data fusion. Keep it right there. You don't wanna miss this >>Time series Data is everywhere. The number of sensors, systems and applications generating time series data increases every day. All these data sources producing so much data can cause analysis paralysis. Influx DB is an entire platform designed with everything you need to quickly build applications that generate value from time series data influx. DB Cloud is a serverless solution, which means you don't need to buy or manage your own servers. There's no need to worry about provisioning because you only pay for what you use. Influx DB Cloud is fully managed so you get the newest features and enhancements as they're added to the platform's code base. It also means you can spend time building solutions and delivering value to your users instead of wasting time and effort managing something else. Influx TVB Cloud offers a range of security features to protect your data, multiple layers of redundancy ensure you don't lose any data access controls ensure that only the people who should see your data can see it. >>And encryption protects your data at rest and in transit between any of our regions or cloud providers. InfluxDB uses a single API across the entire platform suite so you can build on open source, deploy to the cloud and then then easily query data in the cloud at the edge or on prem using the same scripts. And InfluxDB is schemaless automatically adjusting to changes in the shape of your data without requiring changes in your application. Logic. InfluxDB Cloud is production ready from day one. All it needs is your data and your imagination. Get started today@influxdata.com slash cloud. >>Okay, we're back. I'm Dave Valante with a Cube and you're watching evolving Influx DB into the smart data platform made possible by influx data. Anna ETOs Georgio is here, she's a developer advocate for influx data and we're gonna dig into the rationale and value contribution behind several open source technologies that Influx DB is leveraging to increase the granularity of time series analysis analysis and bring the world of data into real-time analytics and is welcome to the program. Thanks for coming on. >>Hi, thank you so much. It's a pleasure to be here. >>Oh, you're very welcome. Okay, so IX is being touted as this next gen open source core for Influx db. And my understanding is that it leverages in memory of course for speed. It's a kilo store, so it gives you a compression efficiency, it's gonna give you faster query speeds, you store files and object storage, so you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features, but what are the high level value points that people should understand? >>Sure, that's a great question. So some of the main requirements that IOx is trying to achieve and some of the most impressive ones to me, the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want, whether that's live tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metrics queries, we also wanna have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import super useful. Also broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like sql, Python, and maybe even pandas in the future. >>Okay, so lot there. Now we talked to Brian about how you're using Rust and which is not a new programming language and of course we had some drama around Rust during the pandemic with the Mozilla layoffs, but the formation of the Rust Foundation really addressed any of those concerns. You got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really, the adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with rust, but why rust as an alternative to say c plus plus for example? >>Sure, that's a great question. So Russ was chosen because of his exceptional performance and reliability. So while Russ is synt tactically similar to c plus plus and it has similar performance, it also compiles to a native code like c plus plus. But unlike c plus plus, it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers. And dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like c plus plus. So Russ like helps meet that requirement of having no limits on ality, for example, because it's, we're also using the Russ implementation of Apache Arrow and this control over memory and also Russ Russ's packaging system called crates IO offers everything that you need out of the box to have features like AY and a weight to fix race conditions, to protection against buffering overflows and to ensure thread safe async cashing structures as well. So essentially it's just like has all the control, all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high ity use cases. >>Yeah, and the more I learn about the, the new engine and, and the platform IOCs et cetera, you know, you, you see things like, you know, the old days not even to even today you do a lot of garbage collection in these, in these systems and there's an inverse, you know, impact relative to performance. So it looks like you really, you know, the community is modernizing the platform, but I wanna talk about Apache Arrow for a moment. It it's designed to address the constraints that are associated with analyzing large data sets. We, we know that, but please explain why, what, what is Arrow and and what does it bring to Influx db? >>Sure, yeah. So Arrow is a, a framework for defining in memory calmer data. And so much of the efficiency and performance of IOx comes from taking advantage of calmer data structures. And I will, if you don't mind, take a moment to kind of of illustrate why column or data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our stove. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value, maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the stove. Well usually our room temperature is regulated so those values don't change very often. >>So when you have calm oriented st calm oriented storage, essentially you take each row, each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same, then you'll, you might be able to imagine how equal values will then enable each other and when they neighbor each other in the storage format, this provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you wanna define like the men and max value of the temperature in the room across a thousand different points, you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of calmer oriented storage. >>So if you had a row oriented storage, you'd first have to look at every field like the temperature in, in the room and the temperature of the stove. You'd have to go across every tag value that maybe describes where the room is located or what model the stove is. And every timestamp you'd then have to pluck out that one temperature value that you want at that one time stamp and do that for every single row. So you're scanning across a ton more data and that's why Rowe Oriented doesn't provide the same efficiency as calmer and Apache Arrow is in memory calmer data, commoner data fit framework. So that's where a lot of the advantages come >>From. Okay. So you basically described like a traditional database, a row approach, but I've seen like a lot of traditional database say, okay, now we've got, we can handle colo format versus what you're talking about is really, you know, kind of native i, is it not as effective? Is the, is the foreman not as effective because it's largely a, a bolt on? Can you, can you like elucidate on that front? >>Yeah, it's, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why, why RO row oriented storage isn't as efficient as calm, calmer oriented storage. Yeah. >>Got it. So let's talk about Arrow Data Fusion. What is data fusion? I know it's written in Rust, but what does it bring to the table here? >>Sure. So it's an extensible query execution framework and it uses Arrow as it's in memory format. So the way that it helps in influx DB IOCs is that okay, it's great if you can write unlimited amount of cardinality into influx Cbis, but if you don't have a query engine that can successfully query that data, then I don't know how much value it is for you. So Data fusion helps enable the, the query process and transformation of that data. It also has a PANDAS API so that you could take advantage of PANDAS data frames as well and all of the machine learning tools associated with Pandas. >>Okay. You're also leveraging Par K in the platform cause we heard a lot about Par K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Parque and why is it important? >>Sure. So parque is the column oriented durable file format. So it's important because it'll enable bulk import, bulk export, it has compatibility with Python and Pandas, so it supports a broader ecosystem. Par K files also take very little disc disc space and they're faster to scan because again, they're column oriented in particular, I think PAR K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the, the benefits of par k. >>Got it. Very popular. So and he's, what exactly is influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >>Sure. So Influx DB first has contributed a lot of different, different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing with flux. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up, then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >>Yeah. Got it. You got that virtuous cycle going, the people call the flywheel. Give us your last thoughts and kind of summarize, you know, where what, what the big takeaways are from your perspective. >>So I think the big takeaway is that influx data is doing a lot of really exciting things with Influx DB IOx and I really encourage, if you are interested in learning more about the technologies that Influx is leveraging to produce IOCs, the challenges associated with it and all of the hard work questions and you just wanna learn more, then I would encourage you to go to the monthly Tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel look for the influx DDB unders IAC channel specifically to learn more about how to join those office hours and those monthly tech tech talks as well as ask any questions they have about iacs, what to expect and what you'd like to learn more about. I as a developer advocate, I wanna answer your questions. So if there's a particular technology or stack that you wanna dive deeper into and want more explanation about how INFLUX DB leverages it to build IOCs, I will be really excited to produce content on that topic for you. >>Yeah, that's awesome. You guys have a really rich community, collaborate with your peers, solve problems, and, and you guys super responsive, so really appreciate that. All right, thank you so much Anise for explaining all this open source stuff to the audience and why it's important to the future of data. >>Thank you. I really appreciate it. >>All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yoakum, he's the director of engineering for Influx Data and we're gonna talk about how you update a SAS engine while the plane is flying at 30,000 feet. You don't wanna miss this. >>I'm really glad that we went with InfluxDB Cloud for our hosting because it has saved us a ton of time. It's helped us move faster, it's saved us money. And also InfluxDB has good support. My name's Alex Nada. I am CTO at Noble nine. Noble Nine is a platform to measure and manage service level objectives, which is a great way of measuring the reliability of your systems. You can essentially think of an slo, the product we're providing to our customers as a bunch of time series. So we need a way to store that data and the corresponding time series that are related to those. The main reason that we settled on InfluxDB as we were shopping around is that InfluxDB has a very flexible query language and as a general purpose time series database, it basically had the set of features we were looking for. >>As our platform has grown, we found InfluxDB Cloud to be a really scalable solution. We can quickly iterate on new features and functionality because Influx Cloud is entirely managed, it probably saved us at least a full additional person on our team. We also have the option of running InfluxDB Enterprise, which gives us the ability to even host off the cloud or in a private cloud if that's preferred by a customer. Influx data has been really flexible in adapting to the hosting requirements that we have. They listened to the challenges we were facing and they helped us solve it. As we've continued to grow, I'm really happy we have influx data by our side. >>Okay, we're back with Tim Yokum, who is the director of engineering at Influx Data. Tim, welcome. Good to see you. >>Good to see you. Thanks for having me. >>You're really welcome. Listen, we've been covering open source software in the cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem. The cloud has been being built out on open source, mobile, social platforms, key databases, and of course influx DB and influx data has been a big consumer and contributor of open source software. So my question to you is, where have you seen the biggest bang for the buck from open source software? >>So yeah, you know, influx really, we thrive at the intersection of commercial services and open, so open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services temping engines. Our, our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants and like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product influx db. >>You know, but I gotta ask you, Tim, because one of the challenge that that we've seen in particular, you saw this in the heyday of Hadoop, the, the innovations come so fast and furious and as a software company you gotta place bets, you gotta, you know, commit people and sometimes those bets can be risky and not pay off well, how have you managed this challenge? >>Oh, it moves fast. Yeah, that, that's a benefit though because it, the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we, what we tend to do is, is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example, that ecosystem is driven by thousands of intelligent developers, engineers, builders, they're adding value every day. So we have to really keep up with that. And as the stack changes, we, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's, it's something that we just do every day. >>So we have a survey partner down in New York City called Enterprise Technology Research etr, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity particularly, you know, along with cloud. But, but really Kubernetes is just, you know, still up until the right consistently even with, you know, the macro headwinds and all, all of the stuff that we're sick of talking about. But, so what are you doing with Kubernetes in the platform? >>Yeah, it, it's really central to our ability to run the product. When we first started out, we were just on AWS and, and the way we were running was, was a little bit like containers junior. Now we're running Kubernetes everywhere at aws, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code so our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google and figure out how to deliver services on those three clouds with all of their differences. >>Just to follow up on that, is it, no. So I presume it's sounds like there's a PAs layer there to allow you guys to have a consistent experience across clouds and out to the edge, you know, wherever is that, is that correct? >>Yeah, so we've basically built more or less platform engineering, This is the new hot phrase, you know, it, it's, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that, that just gets all of the underlying infrastructure out of the way and, and lets them focus on delivering influx cloud. >>Yeah, and I know I'm taking a little bit of a tangent, but is that, that, I'll call it a PAs layer if I can use that term. Is that, are there specific attributes to Influx db or is it kind of just generally off the shelf paths? You know, are there, is, is there any purpose built capability there that, that is, is value add or is it pretty much generic? >>So we really build, we, we look at things through, with a build versus buy through a, a build versus by lens. Some things we want to leverage cloud provider services, for instance, Postgres databases for metadata, perhaps we'll get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can, can deliver on that has consistency that is, is all generated from code that we can as a, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions and in no time. >>So how, so sometimes you build, sometimes you buy it. How do you make those decisions and and what does that mean for the, for the platform and for customers? >>Yeah, so what we're doing is, it's like everybody else will do, we're we're looking for trade offs that make sense. You know, we really want to protect our customers data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers you don't even see that, but we don't want to try to reinvent the wheel, like I had mentioned with SQL data stores for metadata, perhaps let's build on top of what of these three large cloud providers have already perfected. And we can then focus on our platform engineering and we can have our developers then focus on the influx data, software, influx, cloud software. >>So take it to the customer level, what does it mean for them? What's the value that they're gonna get out of all these innovations that we've been been talking about today and what can they expect in the future? >>So first of all, people who use the OSS product are really gonna be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across, over 4 billion series keys that people have stored. So there's a proven ability to scale now in terms of the open source, open source software and how we've developed the platform. You're getting highly available high cardinality time series platform. We manage it and, and really as, as I mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in real time. We deploy to our platform every day repeatedly all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change new features, better ways of doing deployments, safer ways of doing deployments. >>All of that happens behind the scenes. And like we had mentioned earlier, Kubernetes, I mean that, that allows us to get that done. We couldn't do it without having that platform as a, as a base layer for us to then put our software on. So we, we iterate quickly. When you're on the, the Influx cloud platform, you really are able to, to take advantage of new features immediately. We roll things out every day and as those things go into production, you have, you have the ability to, to use them. And so in the end we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let, let us do that for you. So, >>And that makes sense, but so is the, is the, are the innovations that we're talking about in the evolution of Influx db, do, do you see that as sort of a natural evolution for existing customers? I, is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >>Yeah, it really is it, it's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are, are really the hot thing. Iot, industrial iot especially, people want to just shove tons of data out there and be able to do queries immediately and they don't wanna manage infrastructure. What we've started to see are people that use the cloud service as their, their data store backbone and then they use edge computing with R OSS product to ingest data from say, multiple production lines and downsample that data, send the rest of that data off influx cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that and being in all sorts of different regions allows for people to really get out of the, the business of man trying to manage that big data, have us take care of that. And of course as we change the platform end users benefit from that immediately. And, >>And so obviously taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IOT and the Edge? How should we be thinking about the value that you bring from a security perspective? >>Yeah, we take, we take security super seriously. It, it's built into our dna. We do a lot of work to ensure that our platform is secure, that the data we store is, is kept private. It's of course always a concern. You see in the news all the time, companies being compromised, you know, that's something that you can have an entire team working on, which we do to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You know, you look at things like software, bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that, that's just part of our jobs to make sure that the platform that we're running it has, has fully vetted software and, and with open source especially, that's a lot of work. And so it's, it's definitely new territory. Supply chain attacks are, are definitely happening at a higher clip than they used to, but that is, that is really just part of a day in the, the life for folks like us that are, are building platforms. >>Yeah, and that's key. I mean especially when you start getting into the, the, you know, we talk about IOT and the operations technologies, the engineers running the, that infrastructure, you know, historically, as you know, Tim, they, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >>That >>Connected now, right? And so you've gotta have a partner that is again, take away that heavy lifting to r and d so you can focus on some of the other activities. Right. Give us the, the last word and the, the key takeaways from your perspective. >>Well, you know, from my perspective I see it as, as a a two lane approach with, with influx, with Anytime series data, you know, you've got a lot of stuff that you're gonna run on-prem, what you had mentioned, air gaping. Sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want torus their data to, to a company that's, that's got a full platform set up for them that they can build on, send that data over to the cloud, the cloud is not going away. I think more hybrid approach is, is where the future lives and that's what we're prepared for. >>Tim, really appreciate you coming to the program. Great stuff. Good to see you. >>Thanks very much. Appreciate it. >>Okay, in a moment I'll be back to wrap up. Today's session, you're watching The Cube. >>Are you looking for some help getting started with InfluxDB Telegraph or Flux Check >>Out Influx DB University >>Where you can find our entire catalog of free training that will help you make the most of your time series data >>Get >>Started for free@influxdbu.com. >>We'll see you in class. >>Okay, so we heard today from three experts on time series and data, how the Influx DB platform is evolving to support new ways of analyzing large data sets very efficiently and effectively in real time. And we learned that key open source components like Apache Arrow and the Rust Programming environment Data fusion par K are being leveraged to support realtime data analytics at scale. We also learned about the contributions in importance of open source software and how the Influx DB community is evolving the platform with minimal disruption to support new workloads, new use cases, and the future of realtime data analytics. Now remember these sessions, they're all available on demand. You can go to the cube.net to find those. Don't forget to check out silicon angle.com for all the news related to things enterprise and emerging tech. And you should also check out influx data.com. There you can learn about the company's products. You'll find developer resources like free courses. You could join the developer community and work with your peers to learn and solve problems. And there are plenty of other resources around use cases and customer stories on the website. This is Dave Valante. Thank you for watching Evolving Influx DB into the smart data platform, made possible by influx data and brought to you by the Cube, your leader in enterprise and emerging tech coverage.

>>Good evening, brilliant humans. My name is Savannah Peterson and very delighted to be streaming to you. Live from the Cube Studios here in Motor City, Michigan. I've got John Furrier on my left. John, this is our last interview of the day. Energy just seems to keep oozing. How >>You doing? Take two, Three days of coverage, the queue love segments. This one's great cuz we have a practitioner who's implementing all the hard core talks to be awesome. Can't wait to get into it. >>Yeah, I'm very excited for this one. If it's not very clear, we are a community focused community is a huge theme here at the show at Cape Con. And our next guests are actually a provider and a customer. Turning it over to you. Lisa and Jake, welcome to the show. >>Thank you so much for having us. >>It's great to be here. It is our pleasure. Lisa, you're with Cockroach. Just in case the audience isn't familiar, give us a quick little sound bite. >>We're a distributed sequel database. Highly scalable, reliable. The database you can't kill, right? We will survive the apocalypse. So very resilient. Our customers, mostly retail, FinTech game meet online gambling. They, they, they need that resiliency, they need that scalability. So the indestructible database is the elevator pitch >>And the success has been very well documented. Valuation obviously is a scorp guard, but huge customers. We were at the Escape 19. Just for the record, the first ever multi-cloud conference hasn't come back baby. Love it. It'll come back soon. >>Yeah, well we did a similar version of it just a month ago and I was, that was before Cockroach. I was a different company there talking a lot about multi-cloud. So, but I'm, I've been a car a couple of years now and I run community, I run developer relations. I'm still also a CNCF ambassador, so I lead community as well. I still run a really large user group in the San Francisco Bay area. So we've just >>Been in >>Community, take through the use case. Jake's story set us up. >>Well I would like Jake to take him through the use case and Cockroach is a part of it, but what they've built is amazing. And also Jake's history is amazing. So you can start Jake, >>Wherever you take >>Your Yeah, sure. I'm Jake, I'm CEO and co-founder of Offset. Oted is the commercial entity behind Spice Dvy and Spice Dvy is a permission service. Cool. So a permission service is something that lets developers and let's platform teams really unlock the full potential of their applications. So a lot of people get stuck on My R back isn't flexible enough. How do I do these fine grain things? How do I do these complex sharing workflows that my product manager thinks is so important? And so our service enables those platform teams and developers to do those kinds of things. >>What's your, what's your infrastructure? What's your setup look like? What, how are you guys looking like on the back end? >>Sure. Yeah. So we're obviously built on top of Kubernetes as well. One of the reasons that we're here. So we use Kubernetes, we use Kubernetes operators to orchestrate everything. And then we use, use Cockroach TV as our production data store, our production backend data store. >>So I'm curious, cause I love when these little matchmakers come together. You said you've now been presenting on a little bit of a road show, which is very exciting. Lisa, how are you and the team surfacing stories like Jakes, >>Well, I mean any, any place we can obviously all the social medias, all the blogs, How >>Are you finding it though? >>How, how did you Oh, like from our customers? Yeah, we have an open source version so people start to use us a long time before we even sometimes know about them. And then they'll come to us and they'll be like, I love Cockroach, and like, tell me about it. Like, tell me what you build and if it's interesting, you know, we'll we'll try to give it some light. And it's always interesting to me what people do with it because it's an interesting technology. I like what they've done with it. I mean the, the fact that it's globally distributed, right? That was like a really important thing to you. Totally. >>Yeah. We're also long term fans of Cockroach, so we actually all work together out of Workbench, which was a co-working space and investor in New York City. So yeah, we go way back. We knew the founders. I, I'm constantly saying like if I could have invested early in cockroach, that would've been the easiest check I could have ever signed. >>Yeah, that's awesome. And then we've been following that too and you guys are now using them, but folks that are out there looking to have the, the same challenges, what are the big challenges on selecting the database? I mean, as you know, the history of Cockroach and you're originating the story, folks out there might not know and they're also gonna choose a database. What's the, what's the big challenge that they can solve that that kind of comes together? What, what would you describe that? >>Sure. So we're, as I said, we're a permission service and per the data that you store in a permission service is incredibly sensitive. You need it to be around, right? You need it to be available. If the permission service goes down, almost everything else goes down because it's all calling into the permission service. Is this user allowed to do this? Are they allowed to do that? And if we can't answer those questions, then our customer is down, right? So when we're looking at a database, we're looking for reliability, we're looking for durability, disaster recovery, and then permission services are one of the only services that you usually don't shard geographically. So if you look at like AWS's iam, that's a global service, even though the individual things that they run are actually sharded by region. So we also needed a globally distributed database with all of those other properties. So that's what led us >>To, this is a huge topic. So man, we've been talking about all week the cloud is essentially distributed database at this point and it's distributed system. So distributed database is a hot topic, totally not really well reported. A lot of people talking about it, but how would you describe this distributed trend that's going on? What are the key reasons that they're driving it? What's making this more important than ever in your mind, in your opinion? >>I mean, for our use case, it was just a hard requirement, right? We had to be able to have this global service. But I think just for general use cases, a distributed database, distributed database has that like shared nothing architecture that allows you to kind of keep it running and horizontally scale it. And as your requirements and as your applications needs change, you can just keep adding on capacity and keep adding on reliability and availability. >>I'd love to get both of your opinion. You've been talking about the, the, the, the phases of customers, the advanced got Kubernetes going crazy distributed, super alpha geek. Then you got the, the people who are building now, then you got the lagers who are coming online. Where do you guys see the market now in terms of, I know the Alphas are all building all the great stuff and you guys had great success with all the top logos and they're all doing hardcore stuff. As the mainstream enterprise comes in, where's their psychology, what's on their mind? What's, you share any insight into your perspective on that? Because we're seeing a lot more of it folks becoming like real cloud players. >>Yeah, I feel like in mainstream enterprise hasn't been lagging as much as people think. You know, certainly there's been pockets in big enterprises that have been looking at this and as distributed sequel, it gives you that scalability that it's absolutely essential for big enterprises. But also it gives you the, the multi-region, you know, the, you have to be globally distributed. And for us, for enterprises, you know, you need your data near where the users are. I know this is hugely important to you as well. So you have to be able to have a multi-region functionality and that's one thing that distributed SQL lets you build and that what we built into our product. And I know that's one of the things you like too. >>Yeah, well we're a brand new product. I mean we only founded the company two years ago, but we're actually getting inbound interest from big enterprises because we solve the kinds of challenges that they have and whether, I mean, most of them already do have a cockroach footprint, but whether they did or didn't, once they need to bring in our product, they're going to be adopting cockroach transitively anyway. >>So, So you're built on top of Cockroach, right? And Spice dv, is that open source or? >>It >>Is, yep. Okay. And explain the role of open source and your business model. Can you take a minute to talk about the relevance of that? >>Yeah, open source is key. My background is, before this I was at Red Hat. Before that we were at CoreOS, so CoreOS acquisition and before that, >>One of the best acquisitions that ever happened for the value. That was a great, great team. Yeah, >>We, we, we had fun and before that we built Qua. So my co-founders and I, we built Quay, which is a, a first private docker registry. So CoreOS and, and all of those things are all open source or deeply open source. So it's just in our dna. We also see it as part of our go-to market motion. So if you are a database, a lot of people won't even consider what you're doing without being open source. Cuz they say, I don't want to take a, I don't want to, I don't want to end up in an Oracle situation >>Again. Yeah, Oracle meaning they go, you get you locked in, get you in a headlock, Increase prices. >>Yeah. Oh yeah, >>Can, can >>I got triggered. >>You need to talk about your PTSD there >>Or what. >>I mean we have 20,000 stars on GitHub because we've been open and transparent from the beginning. >>Yeah. And it >>Well, and both of your projects were started based on Google Papers, >>Right? >>That is true. Yep. And that's actually, so we're based off of the Google Zans of our paper. And as you know, Cockroach is based off of the Google Span paper and in the the Zanzibar paper, they have this globally distributed database that they're built on top of. And so when I said we're gonna go and we're gonna make a company around the Zabar paper, people would go, Well, what are you gonna do for Span? And I was like, Easy cockroach, they've got us covered. >>Yeah, I know the guys and my friends. Yeah. So the question is why didn't you get into the first round of Cockroach? She said don't answer that. >>The question he did answer though was one of those age old arguments in our community about pronunciation. We used to argue about Quay, I always called it Key of course. And the co-founder obviously knows how it's pronounced, you know, it's the et cd argument, it's the co cuddl versus the control versus coo, CTL Quay from the co-founder. That is end of argument. You heard it here first >>And we're keeping it going with Osted. So awesome. A lot of people will say Zeed or, you know, so we, we just like to have a little ambiguity >>In the, you gotta have some semantic arguments, arm wrestling here. I mean, it keeps, it keeps everyone entertained, especially on the over the weekend. What's, what's next? You got obviously Kubernetes in there. Can you explain the relationship between Kubernetes, how you're handling Spice dv? What, what does the Kubernetes piece fit in and where, where is that going to be going? >>Yeah, great question. Our flagship product right now is a dedicated, and in a dedicated, what we're doing is we're spinning up a single tenant Kubernetes cluster. We're installing all of our operator suite, and then we're installing the application and running it in a single tenant fashion for our customers in the same region, in the same data center where they're running their applications to minimize latency. Because of this, as an authorization service, latency gets passed on directly to the end user. So everybody's trying to squeeze the latency down as far as they can. And our strategy is to just run these single tenant stacks for people with the minimal latency that we can and give them a VPC dedicated link very similar to what Cockroach does in their dedicated >>Product. And the distributed architecture makes that possible because it's lighter way, it's not as heavy. Is that one of the reasons? >>Yep. And Kubernetes really gives us sort of like a, a level playing field where we can say, we're going going to take the provider, the cloud providers Kubernetes offering, normalize it, lay down our operators, and then use that as the base for delivering >>Our application. You know, Jake, you made me think of something I wanted to bring up with other guests, but now since you're here, you're an expert, I wanna bring that up, but talk about Super Cloud. We, we coined that term, but it's kind of multi-cloud, is that having workloads on multiple clouds is hard. I mean there are, they are, there are workloads on, on clouds, but the complexity of one clouds, let's take aws, they got availability zones, they got regions, you got now data issues in each one being global, not that easy on one cloud, nevermind all clouds. Can you share your thoughts on how you see that progression? Because when you start getting, as its distributed database, a lot of good things might come up that could fit into solving the complexity of global workloads. Could you share your thoughts on or scoping that problem space of, of geography? Yeah, because you mentioned latency, like that's huge. What are some of the other challenges that other people have with mobile? >>Yeah, absolutely. When you have a service like ours where the data is small, but very critical, you can get a vendor like Cockroach to step in and to fill that gap and to give you that globally distributed database that you can call into and retrieve the data. I think the trickier issues come up when you have larger data, you have huge binary blobs. So back when we were doing Quay, we wanted to be a global service as well, but we had, you know, terabytes, petabytes of data that we were like, how do we get this replicated everywhere and not go broke? Yeah. So I think those are kind of the interesting issues moving forward is what do you do with like those huge data lakes, the huge amount of data, but for the, the smaller bits, like the things that we can keep in a relational database. Yeah, we're, we're happy that that's quickly becoming a solved >>Problem. And by the way, that that data problem also is compounded when the architecture goes to the edge. >>Totally. >>I mean this is a big issue. >>Exactly. Yeah. Edge is something that we're thinking a lot about too. Yeah, we're lucky that right now the applications that are consuming us are in a data center already. But as they start to move to the edge, we're going to have to move to the edge with them. And it's a story that we're gonna have to figure out. >>All right, so you're a customer cockroach, what's the testimonial if I put you on the spot, say, hey, what's it like working with these guys? You know, what, what's the, what's the, you know, the founders, so you know, you give a good description, little biased, but we'll, we'll we'll hold you on it. >>Yeah. Working with Cockroach has been great. We've had a couple things that we've run into along the way and we've gotten great support from our account managers. They've brought in the right technical expertise when we need it. Cuz what we're doing with Cockroach is not you, you couldn't do it on Postgres, right? So it's not just a simple rip and replace for us, we're using all of the features of Cockroach, right? We're doing as of system time queries, we're doing global replication. We're, you know, we're, we're consuming it all. And so we do need help from them sometimes and they've been great. Yeah. >>And that's natural as they grow their service. I mean the world's changing. >>Well I think one of the important points that you mentioned with multi-cloud, we want you to have the choice. You know, you can run it in in clouds, you can run it hybrid, you can run it OnPrem, you can do whatever you want and it's just, it's one application that you can run in these different data centers. And so really it's up to you how do you want to build your infrastructure? >>And one of the things we've been talking about, the super cloud concept that we've been issue getting a lot of contrary, but, but people are leaning into it is that it's the refactoring and taking advantage of the services. Like what you mentioned about cockroach. People are doing that now on cloud going the lift and shift market kind of had it time now it's like hey, I can start taking advantage of these higher level services or capability of someone else's stack and refactoring it. So I think that's a dynamic that I'm seeing a lot more of. And it sounds like it's working out great in this situation. >>I just came from a talk and I asked them, you know, what don't you wanna put in the cloud and what don't you wanna run in Kubernetes or on containers and good Yeah. And the customers that I was on stage with, one of the guys made a joke and he said I would put my dog in a container room. I could, he was like in the category, which is his right, which he is in the category of like, I'll put everything in containers and these are, you know, including like mis critical apps, heritage apps, since they don't wanna see legacy anymore. Heritage apps, these are huge enterprises and they wanna put everything in the cloud. Everything >>You so want your dog that gets stuck on the airplane when it's on the tarmac. >>Oh >>God, that's, she was the, don't take that analogy. Literally don't think about that. Well that's, >>That's let's not containerize. >>There's always supply chain concern. >>It. So I mean going macro and especially given where we are cncf, it's all about open source. Do y'all think that open source builds a better future? >>Yeah and a better past. I mean this is, so much of this software is founded on open source. I, we wouldn't be here really. I've been in open source community for many, many years so I wouldn't say I'm biased. I would say this is how we build software. I came from like in a high school we're all like, oh let's build a really cool application. Oh you know what? I built this cuz I needed it, but maybe somebody else needs it too. And you put it out there and that is the ethos of Silicon Valley, right? That's where we grew up. So I've always had that mindset, you know, and social coding and why I have three people, right? Working on the same thing when one person you could share it's so inefficient. All of that. Yeah. So I think it's great that people work on what they're really good at. You know, we all, now you need some standardization, you need some kind of control around this whole thing. Sometimes some foundations to, you know, herd the cats. Yeah. But it's, it's great. Which is why I'm a c CF ambassador and I spend a lot of time, you know, in my free time talking about open source. Yeah, yeah. >>It's clear how passionate you are about it. Jake, >>This is my second company that we founded now and I don't think either of them could have existed without the base of open source, right? Like when you look at I have this cool idea for an app or a company and I want to go try it out, the last thing I want to do is go and negotiate with a vendor to get like the core data component. Yeah. To even be able to get to the >>Prototypes. NK too, by the way. Yeah. >>Hey >>Nk >>Or hire, you know, a bunch of PhDs to go and build that core component for me. So yeah, I mean nobody can argue that >>It truly is, I gotta say a best time if you're a developer right now, it's awesome to be a developer right now. It's only gonna get better. As we were riff from the last session about productivity, we believe that if you follow the digital transformation to its conclusion, developers and it aren't a department serving the business, they are the business. And that means they're running the show, which means that now their entire workflow is gonna change. It's gonna be have to be leveraging services partnering. So yeah, open source just fills that. So the more code coming up, it's just no doubt in our mind that that's go, that's happening and will accelerate. So yeah, >>You know, no one company is gonna be able to compete with a community. 50,000 users contributing versus you riding it yourself in your garage with >>Your dogs. Well it's people driven too. It's humans not container. It's humans working together. And here you'll see, I won't say horse training, that's a bad term, but like as projects start to get traction, hey, why don't we come together as, as the world starts to settle and the projects have traction, you start to see visibility into use cases, functionality. Some projects might not be, they have to kind of see more kind >>Of, not every feature is gonna be development. Oh. So I mean, you know, this is why you connect with truly brilliant people who can architect and distribute sequel database. Like who thought of that? It's amazing. It's as, as our friend >>You say, Well let me ask you a question before we wrap up, both by time, what is the secret of Kubernetes success? What made Kubernetes specifically successful? Was it timing? Was it the, the unambitious nature of it, the unification of it? Was it, what was the reason why is Kubernetes successful, right? And why nothing else? >>Well, you know what I'm gonna say? So I'm gonna let Dave >>First don't Jake, you go first. >>Oh boy. If we look at what was happening when Kubernetes first came out, it was, Mesosphere was kind of like the, the big player in the space. I think Kubernetes really, it had the backing from the right companies. It had the, you know, it had the credibility, it was sort of loosely based on Borg, but with the story of like, we've fixed everything that was broken in Borg. Yeah. And it's better now. Yeah. So I think it was just kind and, and obviously people were looking for a solution to this problem as they were going through their containerization journey. And I, yeah, I think it was just right >>Place, the timing consensus of hey, if we just let this happen, something good might come together for everybody. That's the way I felt. I >>Think it was right place, right time, right solution. And then it just kind of exploded when we were at Cores. Alex Povi, our ceo, he heard about Kubernetes and he was like, you know, we, we had a thing called Fleet D or we had a tool called Fleet. And he's like, Nope, we're all in on Kubernetes now. And that was an amazing Yeah, >>I remember that interview. >>I, amazing decision. >>Yeah, >>It's clear we can feel the shift. It's something that's come up a lot this week is is the commitment. Everybody's all in. People are ready for their transformation and Kubernetes is definitely gonna be the orchestrator that we're >>Leveraging. Yeah. And it's an amazing community. But it was, we got lucky that the, the foundational technology, I mean, you know, coming out of Google based on Go conferences, based on Go, it's no to coincidence that this sort of nature of, you know, pods horizontally, scalable, it's all fits together. I does make sense. Yeah. I mean, no offense to Python and some of the other technologies that were built in other languages, but Go is an awesome language. It's so, so innovative. Innovative things you could do with it. >>Awesome. Oh definitely. Jake, I'm very curious since we learned on the way and you are a Detroit native? >>I am. Yep. I grew up in the in Warren, which is just a suburb right outside of Detroit. >>So what does it mean to you as a Michigan born bloke to be here, see your entire community invade? >>It is, I grew up coming to the Detroit Auto Show in this very room >>That brought me to Detroit the first time. Love n a I a s. Been there with our friends at Ford just behind us. >>And it's just so interesting to me to see the accumulation, the accumulation of tech coming to Detroit cuz it's really not something that historically has been a huge presence. And I just love it. I love to see the activity out on the streets. I love to see all the restaurants and coffee shops full of people. Just, I might tear up. >>Well, I was wondering if it would give you a little bit of that hometown pride and also the joy of bringing your community together. I mean, this is merging your two probably most core communities. Yeah, >>Yeah. Your >>Youth and your, and your career. It doesn't get more personal than that really. Right. >>It's just been, it's been really exciting to see the energy. >>Well thanks for going on the queue. Thanks for sharing. Appreciate it. Thanks >>For having us. Yeah, thank you both so much. Lisa, you were a joy of ball of energy right when you walked up. Jake, what a compelling story. Really appreciate you sharing it with us. John, thanks for the banter and the fabulous questions. I'm >>Glad I could help out. >>Yeah, you do. A lot more than help out sweetheart. And to all of you watching the Cube today, thank you so much for joining us live from Detroit, the Cube Studios. My name is Savannah Peterson and we'll see you for our event wrap up next.

>>Hey, welcome back everyone to Super Cloud 22. I'm John Fur, host of the Cuba here all day talking about the future of cloud. Where's all going? Making it super multi-Cloud is around the corner and public cloud is winning at the private cloud on premise and edge. Got a great guest here, Vascar go, D CEO of Platform nine. Just on the panel on Kubernetes. An enabler blocker. Welcome back. Great to have you on. >>Good to see you again. >>So Kubernetes is a blocker enabler by, with a question mark. I put on on that panel was really to discuss the role of Kubernetes. Now great conversation operations is impacted. What's thing about what you guys are doing a platform nine Is your role there as CEO and the company's position, kind of like the world spun into the direction of Platform nine while you're at the helm, >>Right? Absolutely. In fact, things are moving very well and since they came to us it was an insight to call ourselves the platform company eight years ago, right? So absolutely whether you are doing it in public clouds or private clouds, you know the application world is moving very fast in trying to become digital and cloud native. There are many options for you to run the infrastructure. The biggest blocking factor now is having a unified platform. And that's what where we come into >>Patrick, we were talking before we came on stage here about your background and we were kind of talking about the glory days in 2000, 2001 when the first ASPs application service providers came out. Kind of a SaaS vibe, but that was kind of all kind of cloud-like >>It wasn't, >>And and web services started then too. So you saw that whole growth. Now fast forward 20 years later, 22 years later, where we are now, when you look back then to here and all the different cycles, >>In fact, you know, as we were talking offline, I was in one of those asbs in the year 2000 where it was a novel concept of saying we are providing a software and a capability as a service, right? You sign up and start using it. I think a lot has changed since then. The tooling, the tools, the technology has really skyrocketed. The app development environment has really taken off exceptionally well. There are many, many choices of infrastructure now, right? So I think things are in a way the same but also extremely different. But more importantly now for any company, regardless of size, to be a digital native, to become a digital company is extremely mission critical. It's no longer a nice to have everybody's in the journey somewhere. >>Everyone is going digital transformation here. Even on a so-called downturn recession that's upcoming inflation's here. It's interesting. This is the first downturn in the history of the world where the hyperscale clouds have, have been pumping on all cylinders as an economic input. And if you look at the tech trends, GDPs down, but not tech. Nope. Because pandemic showed everyone digital transformation is here and more spend and more growth is coming even in, in tech. So this is a unique factor which proves that that digital transformation's happening and company, every company will need a super cloud >>E Everyone, every company, regardless of size, regardless of location, has to become modernize their infrastructure. And modernizing infrastructure is not just some, you know, new servers and new application tools. It's your approach, how you're serving your customers, how you're bringing agility in your organization. I think that is becoming a necessity for every enterprise to >>Survive. I wanna get your thoughts on Super Cloud because one of the things Dave, Alan and I want to do with Super Cloud and calling at that was we, I I personally, and I know Dave as well, he can, I'll speak from, he can speak for himself. We didn't like multi-cloud. I mean not because Amazon said don't call things multi-cloud, it just didn't feel right. I mean everyone has multiple clouds by default. If you're running productivity software, you have Azure and Office 365. But it wasn't truly distributed. It wasn't truly decentralized, it wasn't truly cloud enabled. It didn't, it felt like the not ready for a market yet. Yet public clouds booming on premise. Private cloud and Edge is much more on, you know, more, more dynamic, more real. >>I, yeah, I think the reason why we think super cloud is a better term than multi-cloud. Multi-cloud are more than one cloud, but they're disconnected. Okay, you have a productivity cloud, you have a Salesforce cloud, you may have, everyone has an internal cloud, right? But they're not connected. So you can say okay, it's more than one cloud. So it's you know, multi-cloud. But Supercloud is where you are actually trying to look at this holistically. Whether it is on-prem, whether it is public, whether it's at the edge, it's a store at the branch, you are looking at this as one unit. And that's where we see the, the term super cloud is more applicable because what are the qualities that you require if you're in a super cloud, right? You need choice of infrastructure, you need, but at the same time you need a single pane, a single platform for you to build your innovations on regardless of which cloud you're doing it on, right? So I think Super Cloud is actually a more tightly integrated orchestrated management philosophy we think. >>So let's get into some of the super cloud type trends that we've been reporting on. Again, the purpose of this event is to, as a pilots, to get the conversations flowing with with the influencers like yourselves who are running companies and building products and the builders, Amazon and Azure are doing extremely well. Google's coming up in third cloudworks in public cloud. We see the use cases on-premises use cases. Kubernetes has been an interesting phenomenon because it's become from the developer side a little bit, but a lot of ops people love Kubernetes. It's really more of an ops thing. You mentioned OpenStack earlier. Kubernetes kind of came out of that open stack. We need an orchestration and then containers had a good shot with, with Docker, they re pivoted the company. Now they're all in an open source. So you got containers booming and Kubernetes as a new layer there. What's, what's the take on that? What does that really mean? Is that a new defacto enabler? It >>Is here. It's for here for sure. Every enterprise somewhere in the journey is going on and you know, most companies are, 70 plus percent of them have 1, 2, 3 container based, Kubernetes based applications now being rolled out. So it's very much here, it is in production at scale by many customers and it, the beauty of it is yes, open source, but the biggest gating factor is the skillset. And that's where we have a phenomenal engineering team, right? So it's, it's one thing to buy a tool and >>Just be clear, you're a managed service for Kubernetes. >>We provide, provide a software platform for cloud acceleration as a service and it can run anywhere. It can run in public private. We have customers who do it in truly multi-cloud environments. It runs on the edge, it runs at this in stores. There are thousands of stores in a retailer. So we provide that and also for specific segments where data sovereignty and data residency are key regulatory reasons. We also on-prem as an air gap version. >>Can you give an example on how you guys are deploying your platform to enable a super cloud experience for your customer? >>Right. So I'll give you two different examples. One is a very large networking company, public networking company. They have hundreds of products, hundreds of r and d teams that are building different different products. And if you look at few years back, each one was doing it on a different platforms but they really needed to bring the agility and they worked with us now over three years where we are their build test dev pro platform where all their products are built on, right? And it has dramatically increased their agility to release new products. Number two, it actually is a light out operation. In fact the customer says like, like the Maytag service person cuz we provide it as a service and it barely takes one or two people to maintain it for them. So >>It's kinda like an SRE vibe. One person managing a >>Large 4,000 engineers building infrastructure >>On their tools, whatever >>They want on their tools. They're using whatever app development tools they use, but they use our platform. >>And what benefits are they seeing? Are they seeing speed? >>Speed, definitely. Okay. Definitely their speeding speed uniformity because now they're building able to build, so their customers who are using product A and product B are seeing a similar set of tools that are being used. >>So a big problem that's coming outta this super cloud event that we're, we're seeing and we heard it all here, ops and security teams. Cause they're kind of two part of one thing, but ops and great specifically need to catch up. Speedwise, are you delivering that value to ops and security? >>Right? So we, we work with ops and security teams and infrastructure teams and we layer on top of that. We have like a platform team. If you think about it, depending on where you have data centers, where you have infrastructure, you have multiple teams, okay, but you need a unified platform. Who's your buyer? Our buyer is usually, you know, the product divisions of companies that are looking at or the CTO would be a buyer for us functionally cio definitely. So it it's, it's somewhere in the DevOps to infrastructure. But the ideal one we are beginning to see now many large corporations are really looking at it as a platform and saying we have a platform group on which any app can be developed and it is run on any infrastructure. So the platform engineering teams, >>So you were just two sides to that coin. You've got the dev side and then >>And the infrastructure >>Side. Okay, >>Another customer, I give you an example which I would say is kind of the edge of the store. So they have thousands of stores. Retail, retail, you know food retailer, right? They have thousands of stores are on the globe, 50,000, 60,000. And they really want to enhance the customer experience that happens when you either order the product or go into the store and pick up your product or buy or browse or sit there. They have applications that were written in the nineties and then they have very modern AIML applications today. They want something that will not have to send an IT person to install rack in the store or they can't move everything to the cloud because the store operations have to be local. The menu changes based on it's classic edge. >>It's >>Classic edge, yeah. Right? They can't send it people to go install rack of servers then they can't sell software people to go install the software and any change you wanna put through that, you know, truck roll. So they've been working with us where all they do is they ship, depending on the size of the store, one or two or three little servers with instructions that >>You say little service, like how big one like a box, like a small little >>Box, right? And all the person in the store has to do like what you and I do at home and we get a, you know, a router is connect the power, connect the internet and turn the switch on. And from there we pick it up. Yeah, we provide the operating system, everything and then the applications are put on it. And so that dramatically brings the velocity for them. They manage thousands >>Of them. True plugin >>Play two plugin play thousands of stores. They manage it centrally. We do it for them, right? So, so that's another example where on the edge then we have some customers who have both a large private presence and one of the public clouds. Okay. But they want to have the same platform layer of orchestration and management that they can use regardless of the >>Location. So you guys got some success. Congratulations. Got some traction there. It's awesome. The question I want to ask you is that's come up is what is truly cloud native? Cuz there's lift and shift of the cloud >>That's not cloud >>Native. Then there's cloud native. Cloud native seems to be the driver for the super cloud. How do you talk to customers? How do you explain when someone says what's cloud native, what isn't cloud native? >>Right. Look, I think first of all, the best place to look at what is the definition and what are the attributes and characteristics of what is truly a cloud native, is CNC foundation. And I think it's very well documented where >>Youcar, of course Detroit's >>Coming in, so, so it's already there, right? So we follow that very closely, right? I think just lifting and shifting your 20 year old application onto a data center somewhere is not cloud native. Okay? You can't put to cloud, not you have to rewrite and redevelop your application and business logic using modern tools. Hopefully more open source and, and I think that's what Cloudnative is and we are seeing lot of our customers in that journey. Now everybody wants to be cloud native, but it's not that easy, okay? Because it's, I think it's first of all, skill set is very important. Uniformity of tools that there's so many tools there. Thousands and thousands of tools you could spend your time figuring out which tool to you use. Okay? So, so I think the complexities there, but the business benefits of agility and uniformity and customer experience are truly being done. >>And I'll give you an example, I don't know how clear native they are, right? And they're not a customer of ours, but you order pizzas, you do, right? If you just watch the pizza industry, how Domino's actually increase their share and mind share and wallet share was not because they were making better pizzas or not, I don't know anything about that, but the whole experience of how you order, how you watch what's happening, how it's delivered, they were the pioneer in it. To me, those are the kinds of customer experiences that cloud native can provide. >>Being agility and having that flow through the application changes what the expectations >>Are >>For the customer. >>Customer, the customer's expectations change, right? Once you get used to a better customer experience, you will not, >>Thats got to wrap it up. I wanna just get your perspective again. One of the benefits of chatting with you here and having you part of the Super Cloud 22 is you've seen many cycles, you have in a lot of insights. I want to ask you, given your career where you've been and what you've done and now the CEO of Platform nine, how would you compare what's happening now with other inflection points in the industry? And you've been, again, you've been an entrepreneur, you sold your company to Oracle, you've been seeing the, the big companies, you've seen the different waves. What's going on right now put into context this moment in time around Super Cloud. >>Sure. I think as you said, a lot of battles. Cars being, being at an asb, being in a realtime software company, being in large enterprise software houses and a transformation. I've been on the app side, I did the infrastructure right and then tried to build our own platforms. I've gone through all of this myself with lot of lessons learned in there. I think this is an event which is happening now for companies to go through to become cloud native and digitalize. If I were to look back and look at some parallels of the tsunami that's going on is, couple of parallels come to me. One is, think of it, which was forced to on us, like y2k, everybody around the world had to have a plan, a strategy, and an execution for y2k. I would say the next big thing was e-commerce. I think e-commerce has been pervasive right across all industries. >>And disruptive. And >>Disruptive, extremely disruptive. If you did not adapt and adapt and accelerate your e-commerce initiative, you were, it was an existence question. Yeah. I think we are at that pivotal moment now in companies trying to become digital and cloud native. You know, that is what I see >>Happening there. I think that that e-commerce is interesting and I think just to riff with you on that is that it's disrupting and refactoring the business models. I think that is something that's coming out of this is that it's not just completely changing the game, it's just changing how you operate, >>How you think, and how you operate. See, if you think about the early days of eCommerce, just putting up a shopping cart then made you an e-commerce or e retailer or e e customer, right? Or so. I think it's the same thing now is I think this is a fundamental shift on how you're thinking about your business. How are you gonna operate? How are you gonna service your customers? I think it requires that just lift and shift is not gonna work. >>Nascar, thank you for coming on. Spend the time to come in and share with our community and being part of Super Cloud 22. We really appreciate, We're gonna keep this open. We're gonna keep this conversation going even after the event, to open up and look at the structural changes happening now and continue to look at it in the open in the community. And we're gonna keep this going for, for a long, long time as we get answers to the problems that customers are looking for with cloud cloud computing. I'm Sean Feer with Super Cloud 22 in the Cube. Thanks for >>Watching. Thank you. Thank you, John. >>Hello. Welcome back. This is the end of our program, our special presentation with Platform nine on cloud native at scale, enabling the super cloud. We're continuing the theme here. You heard the interviews Super cloud and its challenges, new opportunities around the solutions around like Platform nine and others with Arlon. This is really about the edge situations on the internet and managing the edge multiple regions, avoiding vendor lock in. This is what this new super cloud is all about. The business consequences we heard and and the wide ranging conversations around what it means for open source and the complexity problem all being solved. I hope you enjoyed this program. There's a lot of moving pieces and things to configure with cloud native install, all making it easier for you here with Super Cloud and of course Platform nine contributing to that. Thank you for watching.

(soft upbeat music) >> Okay, we're kicking things off with Brian Gilmore. He's the director of IoT, an emerging technology at InfluxData. Brian, welcome to the program. Thanks for coming on. >> Thanks, Dave, great to be here. I appreciate the time. >> Hey, explain why InfluxDB, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >> No, no, not at all. I mean, I think, for us it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like SQL query support, things like that, we have to figure out a way to execute those for them in a way that will scale long term. And then we also want to make sure we're innovating, we're sort of staying ahead of the market as well, and sort of anticipating those future needs. So, you know, this is really a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine. But, you know, initially, the customers who are using us are going to see just great improvements in performance, you know, especially those that are working at the top end of the workload scale, you know, the massive data volumes and things like that. >> Yeah, and we're going to get into that today and the architecture and the like. But what was the catalyst for the enhancements? I mean, when and how did this all come about? >> Well, I mean, like three years ago, we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product. And sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was a long journey. (chuckles) I guess, you know, phase one was, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to optimize for like multi-tenant, multi-cloud, be able to host it in a truly like SAS manner where we could use, you know, some type of customer activity or consumption as the pricing vector. And that was sort of the birth of the real first InfluxDB cloud, you know, which has been really successful. We've seen, I think, like 60,000 people sign up. And we've got tons and tons of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a daily basis. And having that sort of big pool of very diverse and varied customers to chat with as they're using the product, as they're giving us feedback, et cetera, has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that, and then also making these big leaps as we're doing with this new engine. >> All right, so you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really want to understand how much of a pivot this is, and what does it take to make that shift from, you know, time series specialist to real time analytics and being able to support both? >> Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. Time series data is always going to be fundamental in sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. The time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics. If we're being honest though, I think our user base is well aware that the way we were architected was much more towards those sort of like backwards-looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a time to response on the queries, and can we get that to the point where the result sets are coming back so quickly from the time of query that we can like, limit that window down to minutes and then seconds? And now with this new engine, we're really starting to talk about a query window that could be like returning results in, you know, milliseconds of time since it hit the ingest queue. And that's really getting to the point where, as your data is available, you can use it and you can query it, you can visualize it, you can do all those sort of magical things with it. And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the real time queries, the multiple language query support. But, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a limited number of customers, strategic customers and strategic availabilities zones to start, but, you know, everybody over time. >> So you're basically going from what happened to, and you can still do that, obviously, but to what's happening now in the moment? >> Yeah. Yeah. I mean, if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the underlying data collection, the architecture, the infrastructure, the devices, and you know, the sort of highly distributed nature of all of this. So, yeah, I mean, getting a customer or a user to be able to use the data as soon as it is available, is what we're after here. I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >> Yeah, I mean, it is operationally, or operational real time is different. And that's one of the things that really triggered us to know that we were heading in the right direction is just how many sort of operational customers we have, you know, everything from like aerospace and defense. We've got companies monitoring satellites. We've got tons of industrial users using us as a process historian on the plant floor. And if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're going to do here is we're going to start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems, certainly not their historians and databases. >> Is this available, these innovations to InfluxDB cloud customers, only who can access this capability? >> Yeah, I mean, commercially and today, yes. I think we want to emphasize that for now our goal is to get our latest and greatest and our best to everybody over time of course. You know, one of the things we had to do here was like we doubled down on sort of our commitment to open source and availability. So, like, anybody today can take a look at the libraries on our GitHub and can inspect it and even can try to implement or execute some of it themselves in their own infrastructure. We are committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. And so just, you know, being careful, maybe a little cautious in terms of how big we go with this right away. Just sort of both limits, you know, the risk of any issues that can come with new software roll outs, we haven't seen anything so far. But also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products. But once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's going to be exciting time for the whole ecosystem. >> Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are going to help deliver on this vision. What should we know there? >> Well, I mean, I think, foundationally, we built the new core on Rust. This is a new very sort of popular systems language. It's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well, and if it does find error conditions. I mean, we've loved working with Go, and a lot of our libraries will continue to be sort of implemented in Go, but when it came to this particular new engine, that power performance and stability of Rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parquet for persistence. I think, for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our time series merge trees, this is a big break from that. You know, Arrow on the sort of in mem side and then Parquet in the on disk side. It allows us to present, you know, a unified set of APIs for those really fast real time queries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that Parquet format, which is also cool because there's an entire ecosystem sort of popping up around Parquet in terms of the machine learning community. And getting that all to work, we had to glue it together with Arrow Flight. That's sort of what we're using as our RPC component. It handles the orchestration and the transportation of the columnar data now, we're moving to like a true columnar database model for this version of the engine. You know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like, blurring that line between real time and historical data, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >> Yeah, again, I mean, it's funny. You mentioned Rust. It's been around for a long time but it's popularity is, you know, really starting to hit that steep part of the S-curve. And we're going to dig into more of that, but give us, is there anything else that we should know about, Brian? Give us the last word. >> Well, I mean, I think first, I'd like everybody sort of watching, just to like, take a look at what we're offering in terms of early access in beta programs. I mean, if you want to participate or if you want to work sort of in terms of early access with the new engine, please reach out to the team. I'm sure, you know, there's a lot of communications going out and it'll be highly featured on our website. But reach out to the team. Believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to, because we can flip a lot of stuff on, especially in cloud through feature flags. But if there's something new that you want to try out, we'd just love to hear from you. And then, you know, our goal would be, that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to sort of build the next versions of your business. Because, you know, the whole database, the ecosystem as it expands out into this vertically-oriented stack of cloud services, and enterprise databases, and edge databases, you know, it's going to be what we all make it together, not just those of us who are employed by InfluxDB. And then finally, I would just say, please, like, watch and Anais' and Tim's sessions. Like, these are two of our best and brightest. They're totally brilliant, completely pragmatic, and they are most of all customer-obsessed, which is amazing. And there's no better takes, like honestly, on the sort of technical details of this than theirs, especially when it comes to the value that these investments will bring to our customers and our communities. So, encourage you to, you know, pay more attention to them than you did to me, for sure. >> Brian Gilmore, great stuff. Really appreciate your time. Thank you. >> Yeah, thanks David, it was awesome. Looking forward to it. >> Yeah, me too. I'm looking forward to see how the community actually applies these new innovations and goes beyond just the historical into the real time. Really hot area. As Brian said, in a moment, I'll be right back with Anais Dotis-Georgiou to dig into the critical aspects of key open source components of the InfluxDB engine, including Rust, Arrow, Parquet, Data Fusion. Keep it right there. You don't want to miss this. (soft upbeat music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> This past week we saw two of the Big 3 cloud providers present the latest update on their respective cloud visions, their business progress, their announcements and innovations. The content at these events had many overlapping themes, including modern cloud infrastructure at global scale, applying advanced machine intelligence, AKA AI, end-to-end data platforms, collaboration software. They talked a lot about the future of work automation. And they gave us a little taste, each company of the Metaverse Web 3.0 and much more. Despite these striking similarities, the differences between these two cloud platforms and that of AWS remains significant. With Microsoft leveraging its massive application software footprint to dominate virtually all markets and Google doing everything in its power to keep up with the frenetic pace of today's cloud innovation, which was set into motion a decade and a half ago by AWS. Hello and welcome to this week's Wikibon CUBE Insights, powered by ETR. In this Breaking Analysis, we unpack the immense amount of content presented by the CEOs of Microsoft and Google Cloud at Microsoft Ignite and Google Cloud Next. We'll also quantify with ETR survey data the relative position of these two cloud giants in four key sectors: cloud IaaS, BI analytics, data platforms and collaboration software. Now one thing was clear this past week, hybrid events are the thing. Google Cloud Next took place live over a 24-hour period in six cities around the world, with the main gathering in New York City. Microsoft Ignite, which normally is attended by 30,000 people, had a smaller event in Seattle, in person with a virtual audience around the world. AWS re:Invent, of course, is much different. Yes, there's a virtual component at re:Invent, but it's all about a big live audience gathering the week after Thanksgiving, in the first week of December in Las Vegas. Regardless, Satya Nadella keynote address was prerecorded. It was highly produced and substantive. It was visionary, energetic with a strong message that Azure was a platform to allow customers to build their digital businesses. Doing more with less, which was a key theme of his. Nadella covered a lot of ground, starting with infrastructure from the compute, highlighting a collaboration with Arm-based, Ampere processors. New block storage, 60 regions, 175,000 miles of fiber cables around the world. He presented a meaningful multi-cloud message with Azure Arc to support on-prem and edge workloads, as well as of course the public cloud. And talked about confidential computing at the infrastructure level, a theme we hear from all cloud vendors. He then went deeper into the end-to-end data platform that Microsoft is building from the core data stores to analytics, to governance and the myriad tooling Microsoft offers. AI was next with a big focus on automation, AI, training models. He showed demos of machines coding and fixing code and machines automatically creating designs for creative workers and how Power Automate, Microsoft's RPA tooling, would combine with Microsoft Syntex to understand documents and provide standard ways for organizations to communicate with those documents. There was of course a big focus on Azure as developer cloud platform with GitHub Copilot as a linchpin using AI to assist coders in low-code and no-code innovations that are coming down the pipe. And another giant theme was a workforce transformation and how Microsoft is using its heritage and collaboration and productivity software to move beyond what Nadella called productivity paranoia, i.e., are remote workers doing their jobs? In a world where collaboration is built into intelligent workflows, and he even showed a glimpse of the future with AI-powered avatars and partnerships with Meta and Cisco with Teams of all firms. And finally, security with a bevy of tools from identity, endpoint, governance, et cetera, stressing a suite of tools from a single provider, i.e., Microsoft. So a couple points here. One, Microsoft is following in the footsteps of AWS with silicon advancements and didn't really emphasize that trend much except for the Ampere announcement. But it's building out cloud infrastructure at a massive scale, there is no debate about that. Its plan on data is to try and provide a somewhat more abstracted and simplified solutions, which differs a little bit from AWS's approach of the right database tool, for example, for the right job. Microsoft's automation play appears to provide simple individual productivity tools, kind of a ground up approach and make it really easy for users to drive these bottoms up initiatives. We heard from UiPath that forward five last month, a little bit of a different approach of horizontal automation, end-to-end across platforms. So quite a different play there. Microsoft's angle on workforce transformation is visionary and will continue to solidify in our view its dominant position with Teams and Microsoft 365, and it will drive cloud infrastructure consumption by default. On security as well as a cloud player, it has to have world-class security, and Azure does. There's not a lot of debate about that, but the knock on Microsoft is Patch Tuesday becomes Hack Wednesday because Microsoft releases so many patches, it's got so much Swiss cheese in its legacy estate and patching frequently, it becomes a roadmap and a trigger for hackers. Hey, patch Tuesday, these are all the exploits that you can go after so you can act before the patches are implemented. And so it's really become a problem for users. As well Microsoft is competing with many of the best-of-breed platforms like CrowdStrike and Okta, which have market momentum and appear to be more attractive horizontal plays for customers outside of just the Microsoft cloud. But again, it's Microsoft. They make it easy and very inexpensive to adopt. Now, despite the outstanding presentation by Satya Nadella, there are a couple of statements that should raise eyebrows. Here are two of them. First, as he said, Azure is the only cloud that supports all organizations and all workloads from enterprises to startups, to highly regulated industries. I had a conversation with Sarbjeet Johal about this, to make sure I wasn't just missing something and we were both surprised, somewhat, by this claim. I mean most certainly AWS supports more certifications for example, and we would think it has a reasonable case to dispute that claim. And the other statement, Nadella made, Azure is the only cloud provider enabling highly regulated industries to bring their most sensitive applications to the cloud. Now, reasonable people can debate whether AWS is there yet, but very clearly Oracle and IBM would have something to say about that statement. Now maybe it's not just, would say, "Oh, they're not real clouds, you know, they're just going to hosting in the cloud if you will." But still, when it comes to mission-critical applications, you would think Oracle is really the the leader there. Oh, and Satya also mentioned the claim that the Edge browser, the Microsoft Edge browser, no questions asked, he said, is the best browser for business. And we could see some people having some questions about that. Like isn't Edge based on Chrome? Anyway, so we just had to question these statements and challenge Microsoft to defend them because to us it's a little bit of BS and makes one wonder what else in such as awesome keynote and it was awesome, it was hyperbole. Okay, moving on to Google Cloud Next. The keynote started with Sundar Pichai doing a virtual session, he was remote, stressing the importance of Google Cloud. He mentioned that Google Cloud from its Q2 earnings was on a $25-billion annual run rate. What he didn't mention is that it's also on a 3.6 billion annual operating loss run rate based on its first half performance. Just saying. And we'll dig into that issue a little bit more later in this episode. He also stressed that the investments that Google has made to support its core business and search, like its global network of 22 subsea cables to support things like, YouTube video, great performance obviously that we all rely on, those innovations there. Innovations in BigQuery to support its search business and its threat analysis that it's always had and its AI, it's always been an AI-first company, he's stressed, that they're all leveraged by the Google Cloud Platform, GCP. This is all true by the way. Google has absolutely awesome tech and the talk, as well as his talk, Pichai, but also Kurian's was forward thinking and laid out a vision of the future. But it didn't address in our view, and I talked to Sarbjeet Johal about this as well, today's challenges to the degree that Microsoft did and we expect AWS will at re:Invent this year, it was more out there, more forward thinking, what's possible in the future, somewhat less about today's problem, so I think it's resonates less with today's enterprise players. Thomas Kurian then took over from Sundar Pichai and did a really good job of highlighting customers, and I think he has to, right? He has to say, "Look, we are in this game. We have customers, 9 out of the top 10 media firms use Google Cloud. 8 out of the top 10 manufacturers. 9 out of the top 10 retailers. Same for telecom, same for healthcare. 8 out of the top 10 retail banks." He and Sundar specifically referenced a number of companies, customers, including Avery Dennison, Groupe Renault, H&M, John Hopkins, Prudential, Minna Bank out of Japan, ANZ bank and many, many others during the session. So you know, they had some proof points and you got to give 'em props for that. Now like Microsoft, Google talked about infrastructure, they referenced training processors and regions and compute optionality and storage and how new workloads were emerging, particularly data-driven workloads in AI that required new infrastructure. He explicitly highlighted partnerships within Nvidia and Intel. I didn't see anything on Arm, which somewhat surprised me 'cause I believe Google's working on that or at least has come following in AWS's suit if you will, but maybe that's why they're not mentioning it or maybe I got to do more research there, but let's park that for a minute. But again, as we've extensively discussed in Breaking Analysis in our view when it comes to compute, AWS via its Annapurna acquisition is well ahead of the pack in this area. Arm is making its way into the enterprise, but all three companies are heavily investing in infrastructure, which is great news for customers and the ecosystem. We'll come back to that. Data and AI go hand in hand, and there was no shortage of data talk. Google didn't mention Snowflake or Databricks specifically, but it did mention, by the way, it mentioned Mongo a couple of times, but it did mention Google's, quote, Open Data cloud. Now maybe Google has used that term before, but Snowflake has been marketing the data cloud concept for a couple of years now. So that struck as a shot across the bow to one of its partners and obviously competitor, Snowflake. At BigQuery is a main centerpiece of Google's data strategy. Kurian talked about how they can take any data from any source in any format from any cloud provider with BigQuery Omni and aggregate and understand it. And with the support of Apache Iceberg and Delta and Hudi coming in the future and its open Data Cloud Alliance, they talked a lot about that. So without specifically mentioning Snowflake or Databricks, Kurian co-opted a lot of messaging from these two players, such as life and tech. Kurian also talked about Google Workspace and how it's now at 8 million users up from 6 million just two years ago. There's a lot of discussion on developer optionality and several details on tools supported and the open mantra of Google. And finally on security, Google brought out Kevin Mandian, he's a CUBE alum, extremely impressive individual who's CEO of Mandiant, a leading security service provider and consultancy that Google recently acquired for around 5.3 billion. They talked about moving from a shared responsibility model to a shared fate model, which is again, it's kind of a shot across AWS's bow, kind of shared responsibility model. It's unclear that Google will pay the same penalty if a customer doesn't live up to its portion of the shared responsibility, but we can probably assume that the customer is still going to bear the brunt of the pain, nonetheless. Mandiant is really interesting because it's a services play and Google has stated that it is not a services company, it's going to give partners in the channel plenty of room to play. So we'll see what it does with Mandiant. But Mandiant is a very strong enterprise capability and in the single most important area security. So interesting acquisition by Google. Now as well, unlike Microsoft, Google is not competing with security leaders like Okta and CrowdStrike. Rather, it's partnering aggressively with those firms and prominently putting them forth. All right. Let's get into the ETR survey data and see how Microsoft and Google are positioned in four key markets that we've mentioned before, IaaS, BI analytics, database data platforms and collaboration software. First, let's look at the IaaS cloud. ETR is just about to release its October survey, so I cannot share the that data yet. I can only show July data, but we're going to give you some directional hints throughout this conversation. This chart shows net score or spending momentum on the vertical axis and overlap or presence in the data, i.e., how pervasive the platform is. That's on the horizontal axis. And we've inserted the Wikibon estimates of IaaS revenue for the companies, the Big 3. Actually the Big 4, we included Alibaba. So a couple of points in this somewhat busy data chart. First, Microsoft and AWS as always are dominant on both axes. The red dotted line there at 40% on the vertical axis. That represents a highly elevated spending velocity and all of the Big 3 are above the line. Now at the same time, GCP is well behind the two leaders on the horizontal axis and you can see that in the table insert as well in our revenue estimates. Now why is Azure bigger in the ETR survey when AWS is larger according to the Wikibon revenue estimates? And the answer is because Microsoft with products like 365 and Teams will often be considered by respondents in the survey as cloud by customers, so they fit into that ETR category. But in the insert data we're stripping out applications and SaaS from Microsoft and Google and we're only isolating on IaaS. The other point is when you take a look at the early October returns, you see downward pressure as signified by those dotted arrows on every name. The only exception was Dell, or Dell and IBM, which showing slightly improved momentum. So the survey data generally confirms what we know that AWS and Azure have a massive lead and strong momentum in the marketplace. But the real story is below the line. Unlike Google Cloud, which is on pace to lose well over 3 billion on an operating basis this year, AWS's operating profit is around $20 billion annually. Microsoft's Intelligent Cloud generated more than $30 billion in operating income last fiscal year. Let that sink in for a moment. Now again, that's not to say Google doesn't have traction, it does and Kurian gave some nice proof points and customer examples in his keynote presentation, but the data underscores the lead that Microsoft and AWS have on Google in cloud. And here's a breakdown of ETR's proprietary net score methodology, that vertical axis that we showed you in the previous chart. It asks customers, are you adopting the platform new? That's that lime green. Are you spending 6% or more? That's the forest green. Is you're spending flat? That's the gray. Is you're spending down 6% or worse? That's the pinkest color. Or are you replacing the platform, defecting? That's the bright red. You subtract the reds from the greens and you get a net score. Now one caveat here, which actually is really favorable from Microsoft, the Microsoft data that we're showing here is across the entire Microsoft portfolio. The other point is, this is July data, we'll have an update for you once ETR releases its October results. But we're talking about meaningful samples here, the ends. 620 for AWS over a thousand from Microsoft in more than 450 respondents in the survey for Google. So the real tell is replacements, that bright red. There is virtually no churn for AWS and Microsoft, but Google's churn is 5x, those two in the survey. Now 5% churn is not high, but you'd like to see three things for Google given it's smaller size. One is less churn, two is much, much higher adoption rates in the lime green. Three is a higher percentage of those spending more, the forest green. And four is a lower percentage of those spending less. And none of these conditions really applies here for Google. GCP is still not growing fast enough in our opinion, and doesn't have nearly the traction of the two leaders and that shows up in the survey data. All right, let's look at the next sector, BI analytics. Here we have that same XY dimension. Again, Microsoft dominating the picture. AWS very strong also in both axes. Tableau, very popular and respectable of course acquired by Salesforce on the vertical axis, still looking pretty good there. And again on the horizontal axis, big presence there for Tableau. And Google with Looker and its other platforms is also respectable, but it again, has some work to do. Now notice Streamlit, that's a recent Snowflake acquisition. It's strong in the vertical axis and because of Snowflake's go-to-market (indistinct), it's likely going to move to the right overtime. Grafana is also prominent in the Y axis, but a glimpse at the most recent survey data shows them slightly declining while Looker actually improves a bit. As does Cloudera, which we'll move up slightly. Again, Microsoft just blows you away, doesn't it? All right, now let's get into database and data platform. Same X Y dimensions, but now database and data warehouse. Snowflake as usual takes the top spot on the vertical axis and it is actually keeps moving to the right as well with again, Microsoft and AWS is dominant in the market, as is Oracle on the X axis, albeit it's got less spending velocity, but of course it's the database king. Google is well behind on the X axis but solidly above the 40% line on the vertical axis. Note that virtually all platforms will see pressure in the next survey due to the macro environment. Microsoft might even dip below the 40% line for the first time in a while. Lastly, let's look at the collaboration and productivity software market. This is such an important area for both Microsoft and Google. And just look at Microsoft with 365 and Teams up into the right. I mean just so impressive in ubiquitous. And we've highlighted Google. It's in the pack. It certainly is a nice base with 174 N, which I can tell you that N will rise in the next survey, which is an indication that more people are adopting. But given the investment and the tech behind it and all the AI and Google's resources, you'd really like to see Google in this space above the 40% line, given the importance of this market, of this collaboration area to Google's success and the degree to which they emphasize it in their pitch. And look, this brings up something that we've talked about before on Breaking Analysis. Google doesn't have a tech problem. This is a go-to-market and marketing challenge that Google faces and it's up against two go-to-market champs and Microsoft and AWS. And Google doesn't have the enterprise sales culture. It's trying, it's making progress, but it's like that racehorse that has all the potential in the world, but it's just missing some kind of key ingredient to put it over at the top. It's always coming in third, (chuckles) but we're watching and Google's obviously, making some investments as we shared with earlier. All right. Some final thoughts on what we learned this week and in this research: customers and partners should be thrilled that both Microsoft and Google along with AWS are spending so much money on innovation and building out global platforms. This is a gift to the industry and we should be thankful frankly because it's good for business, it's good for competitiveness and future innovation as a platform that can be built upon. Now we didn't talk much about multi-cloud, we haven't even mentioned supercloud, but both Microsoft and Google have a story that resonates with customers in cross cloud capabilities, unlike AWS at this time. But we never say never when it comes to AWS. They sometimes and oftentimes surprise you. One of the other things that Sarbjeet Johal and John Furrier and I have discussed is that each of the Big 3 is positioning to their respective strengths. AWS is the best IaaS. Microsoft is building out the kind of, quote, we-make-it-easy-for-you cloud, and Google is trying to be the open data cloud with its open-source chops and excellent tech. And that puts added pressure on Snowflake, doesn't it? You know, Thomas Kurian made some comments according to CRN, something to the effect that, we are the only company that can do the data cloud thing across clouds, which again, if I'm being honest is not really accurate. Now I haven't clarified these statements with Google and often things get misquoted, but there's little question that, as AWS has done in the past with Redshift, Google is taking a page out of Snowflake, Databricks as well. A big difference in the Big 3 is that AWS doesn't have this big emphasis on the up-the-stack collaboration software that both Microsoft and Google have, and that for Microsoft and Google will drive captive IaaS consumption. AWS obviously does some of that in database, a lot of that in database, but ISVs that compete with Microsoft and Google should have a greater affinity, one would think, to AWS for competitive reasons. and the same thing could be said in security, we would think because, as I mentioned before, Microsoft competes very directly with CrowdStrike and Okta and others. One of the big thing that Sarbjeet mentioned that I want to call out here, I'd love to have your opinion. AWS specifically, but also Microsoft with Azure have successfully created what Sarbjeet calls brand distance. AWS from the Amazon Retail, and even though AWS all the time talks about Amazon X and Amazon Y is in their product portfolio, but you don't really consider it part of the retail organization 'cause it's not. Azure, same thing, has created its own identity. And it seems that Google still struggles to do that. It's still very highly linked to the sort of core of Google. Now, maybe that's by design, but for enterprise customers, there's still some potential confusion with Google, what's its intentions? How long will they continue to lose money and invest? Are they going to pull the plug like they do on so many other tools? So you know, maybe some rethinking of the marketing there and the positioning. Now we didn't talk much about ecosystem, but it's vital for any cloud player, and Google again has some work to do relative to the leaders. Which brings us to supercloud. The ecosystem and end customers are now in a position this decade to digitally transform. And we're talking here about building out their own clouds, not by putting in and building data centers and installing racks of servers and storage devices, no. Rather to build value on top of the hyperscaler gift that has been presented. And that is a mega trend that we're watching closely in theCUBE community. While there's debate about the supercloud name and so forth, there little question in our minds that the next decade of cloud will not be like the last. All right, we're going to leave it there today. Many thanks to Sarbjeet Johal, and my business partner, John Furrier, for their input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast and Ken Schiffman as well. Kristen Martin and Cheryl Knight helped get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE, who does some wonderful editing. And check out SiliconANGLE, a lot of coverage on Google Cloud Next and Microsoft Ignite. Remember, all these episodes are available as podcast wherever you listen. Just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. And you can always get in touch with me via email, david.vellante@siliconangle.com or you can DM me at dvellante or comment on my LinkedIn posts. And please do check out etr.ai, the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (gentle music)

(gentle music) (upbeat music) (crowd chattering) >> Welcome back to The City That Never Sleeps. Lisa Martin and John Furrier in New York City for AWS Summit '22 with about 10 to 12,000 of our friends. And we've got two more friends joining us here today. We're going to be talking with Haseeb Budhani, one of our alumni, co-founder and CEO of Rafay Systems, and Kevin Coleman, senior manager for Go-to Market for EKS at AWS. Guys, thank you so much for joining us today. >> Thank you very much for having us. Excited to be here. >> Isn't it great to be back at an in-person event with 10, 12,000 people? >> Yes. There are a lot of people here. This is packed. >> A lot of energy here. So, Haseeb, we've got to start with you. Your T-shirt says it all. Don't hate k8s. (Kevin giggles) Talk to us about some of the trends, from a Kubernetes perspective, that you're seeing, and then Kevin will give your follow-up. >> Yeah. >> Yeah, absolutely. So, I think the biggest trend I'm seeing on the enterprise side is that enterprises are forming platform organizations to make Kubernetes a practice across the enterprise. So it used to be that a BU would say, "I need Kubernetes. I have some DevOps engineers, let me just do this myself." And the next one would do the same, and then next one would do the same. And that's not practical, long term, for an enterprise. And this is now becoming a consolidated effort, which is, I think it's great. It speaks to the power of Kubernetes, because it's becoming so important to the enterprise. But that also puts a pressure because what the platform team has to solve for now is they have to find this fine line between automation and governance, right? I mean, the developers, you know, they don't really care about governance. Just give me stuff, I need to compute, I'm going to go. But then the platform organization has to think about, how is this going to play for the enterprise across the board? So that combination of automation and governance is where we are finding, frankly, a lot of success in making enterprise platform team successful. I think, that's a really new thing to me. It's something that's changed in the last six months, I would say, in the industry. I don't know if, Kevin, if you agree with that or not, but that's what I'm seeing. >> Yeah, definitely agree with that. We see a ton of customers in EKS who are building these new platforms using Kubernetes. The term that we hear a lot of customers use is standardization. So they've got various ways that they're deploying applications, whether it's on-prem or in the cloud and region. And they're really trying to standardize the way they deploy applications. And Kubernetes is really that compute substrate that they're standardizing on. >> Kevin, talk about the relationship with Rafay Systems that you have and why you're here together. And two, second part of that question, why is EKS kicking ass so much? (Haseeb and Kevin laughing) All right, go ahead. First one, your relationship. Second one, EKS is doing pretty well. >> Yep, yep, yep. (Lisa laughing) So yeah, we work closely with Rafay, Rafay, excuse me. A lot of joint customer wins with Haseeb and Co, so they're doing great work with EKS customers and, yeah, love the partnership there. In terms of why EKS is doing so well, a number of reasons, I think. Number one, EKS is vanilla, upstream, open-source Kubernetes. So customers want to use that open-source technology, that open-source Kubernetes, and they come to AWS to get it in a managed offering, right? Kubernetes isn't the easiest thing to self-manage. And so customers, you know, back before EKS launched, they were banging down the door at AWS for us to have a managed Kubernetes offering. And, you know, we launched EKS and there's been a ton of customer adoption since then. >> You know, Lisa, when we, theCUBE 12 years, now everyone knows we started in 2010, we used to cover a show called OpenStack. >> I remember that. >> OpenStack Summit. >> What's that now? >> And at the time, at that time, Kubernetes wasn't there. So theCUBE was present at creation. We've been to every KubeCon ever, CNCF then took it over. So we've been watching it from the beginning. >> Right. And it reminds me of the same trend we saw with MapReduce and Hadoop. Very big promise, everyone loved it, but it was hard, very difficult. And Hadoop's case, big data, it ended up becoming a data lake. Now you got Spark, or Snowflake, and Databricks, and Redshift. Here, Kubernetes has not yet been taken over. But, instead, it's being abstracted away and or managed services are emerging. 'Cause general enterprises can't hire enough Kubernetes people. >> Yep. >> They're not that many out there yet. So there's the training issue. But there's been the rise of managed services. >> Yep. >> Can you guys comment on what your thoughts are relative to that trend of hard to use, abstracting away the complexity, and, specifically, the managed services? >> Yeah, absolutely. You want to go? >> Yeah, absolutely. I think, look, it's important to not kid ourselves. It is hard. (Johns laughs) But that doesn't mean it's not practical, right. When Kubernetes is done well, it's a thing of beauty. I mean, we have enough customer to scale, like, you know, it's like a, forget a hockey stick, it's a straight line up, because they just are moving so fast when they have the right platform in place. I think that the mistake that many of us make, and I've made this mistake when we started this company, was trivializing the platform aspect of Kubernetes, right. And a lot of my customers, you know, when they start, they kind of feel like, well, this is not that hard. I can bring this up and running. I just need two people. It'll be fine. And it's hard to hire, but then, I need two, then I need two more, then I need two, it's a lot, right. I think, the one thing I keep telling, like, when I talk to analysts, I say, "Look, somebody needs to write a book that says, 'Yes, it's hard, but, yes, it can be done, and here's how.'" Let's just be open about what it takes to get there, right. And, I mean, you mentioned OpenStack. I think the beauty of Kubernetes is that because it's such an open system, right, even with the managed offering, companies like Rafay can build really productive businesses on top of this Kubernetes platform because it's an open system. I think that is something that was not true with OpenStack. I've spent time with OpenStack also, I remember how it is. >> Well, Amazon had a lot to do with stalling the momentum of OpenStack, but your point about difficulty. Hadoop was always difficult to maintain and hiring against. There were no managed services and no one yet saw that value of big data yet. Here at Kubernetes, people are living a problem called, I'm scaling up. >> Yep. And so it sounds like it's a foundational challenge. The ongoing stuff sounds easier or manageable. >> Once you have the right tooling. >> Is that true? >> Yeah, no, I mean, once you have the right tooling, it's great. I think, look, I mean, you and I have talked about this before, I mean, the thesis behind Rafay is that, you know, there's like 8, 12 things that need to be done right for Kubernetes to work well, right. And my whole thesis was, I don't want my customer to buy 10, 12, 15 products. I want them to buy one platform, right. And I truly believe that, in our market, similar to what vCenter, like what VMware's vCenter did for VMs, I want to do that for Kubernetes, right. And that the reason why I say that is because, see, vCenter is not about hypervisors, right? vCenter is about hypervisor, access, networking, storage, all of the things, like multitenancy, all the things that you need to run an enterprise-grade VM environment. What is that equivalent for the Kubernetes world, right? So what we are doing at Rafay is truly building a vCenter, but for Kubernetes, like a kCenter. I've tried getting the domain. I couldn't get it. (Kevin laughs) >> Well, after the Broadcom view, you don't know what's going to happen. >> Ehh. (John laughs) >> I won't go there! >> Yeah. Yeah, let's not go there today. >> Kevin, EKS, I've heard people say to me, "Love EKS. Just add serverless, that's a home run." There's been a relationship with EKS and some of the other Amazon tools. Can you comment on what you're seeing as the most popular interactions among the services at AWS? >> Yeah, and was your comment there, add serverless? >> Add serverless with AKS at the edge- >> Yeah. >> and things are kind of interesting. >> I mean, so, one of the serverless offerings we have today is actually Fargate. So you can use Fargate, which is our serverless compute offering, or one of our serverless compute offerings with EKS. And so customers love that. Effectively, they get the beauty of EKS and the Kubernetes API but they don't have to manage nodes. So that's, you know, a good amount of adoption with Fargate as well. But then, we also have other ways that they can manage their nodes. We have managed node groups as well, in addition to self-managed nodes also. So there's a variety of options that customers can use from a compute perspective with EKS. And you'll continue to see us evolve the portfolio as well. >> Can you share, Haseeb, can you share a customer example, a joint customer example that you think really articulates the value of what Rafay and AWS are doing together? >> Yeah, absolutely. In fact, we announced a customer very recently on this very show, which is MoneyGram, which is a joint AWS and Rafay customer. Look, we have enough, you know, the thing about these massive customers is that, you know, not everybody's going to give us their logo to use. >> Right. >> But MoneyGram has been a Rafay plus EKS customer for a very, very long time. You know, at this point, I think we've earned their trust, and they've allowed us to, kind of say this publicly. But there's enough of these financial services companies who have, you know, standardized on EKS. So it's EKS first, Rafay second, right. They standardized on EKS. And then they looked around and said, "Who can help me platform EKS across my enterprise?" And we've been very lucky. We have some very large financial services, some very large healthcare companies now, who, A, EKS, B, Rafay. I'm not just saying that because my friend Kevin's here, (Lisa laughs) it's actually true. Look, EKS is a brilliant platform. It scales so well, right. I mean, people try it out, relative to other platforms, and it's just a no-brainer, it just scales. You want to build a big enterprise on the backs of a Kubernetes platform. And I'm not saying that's because I'm biased. Like EKS is really, really good. There's a reason why so many companies are choosing it over many other options in the market. >> You're doing a great job of articulating why the theme (Kevin laughs) of the New York City Summit is scale anything. >> Oh, yeah. >> There you go. >> Oh, yeah. >> I did not even know that but I'm speaking the language, right? >> You are. (John laughs) >> Yeah, absolutely. >> One of the things that we're seeing, also, I want to get your thoughts on, guys, is the app modernization trend, right? >> Yep. >> Because unlike other standards that were hard, that didn't have any benefit downstream 'cause they were too hard to get to, here, Kubernetes is feeding into real app for app developer pressure. They got to get cloud-native apps out. It's fairly new in the mainstream enterprise and a lot of hyperscalers have experience. So I'm going to ask you guys, what is the key thing that you're enabling with Kubernetes in the cloud-native apps? What is the key value? >> Yeah. >> I think, there's a bifurcation happening in the market. One is the Kubernetes Engine market, which is like EKS, AKS, GKE, right. And then there's the, you know, what, back in the day, we used to call operations and management, right. So the OAM layer for Kubernetes is where there's need, right. People are learning, right. Because, as you said before, the skill isn't there, you know, there's not enough talent available to the market. And that's the opportunity we're seeing. Because to solve for the standardization, the governance, and automation that we talked about earlier, you know, you have to solve for, okay, how do I manage my network? How do I manage my service mesh? How do I do chargebacks? What's my, you know, policy around actual Kubernetes policies? What's my blueprinting strategy? How do I do add-on management? How do I do pipelines for updates of add-ons? How do I upgrade my clusters? And we're not done yet, there's a longer list, right? This is a lot, right? >> Yeah. >> And this is what happens, right. It's just a lot. And really, the companies who understand that plethora of problems that need to be solved and build easy-to-use solutions that enterprises can consume with the right governance automation, I think they're going to be very, very successful here. >> Yeah. >> Because this is a train, right? I mean, this is happening whether, it's not us, it's happening, right? Enterprises are going to keep doing this. >> And open-source is a big driver in all of this. >> Absolutely. >> Absolutely. >> And I'll tag onto that. I mean, you talked about platform engineering earlier. Part of the point of building these platforms on top of Kubernetes is giving developers an easier way to get applications into the cloud. So building unique developer experiences that really make it easy for you, as a software developer, to take the code from your laptop, get it out of production as quickly as possible. The question is- >> So is that what you mean, does that tie your point earlier about that vertical, straight-up value once you've set up it, right? >> Yep. >> Because it's taking the burden off the developers for stopping their productivity. >> Absolutely. >> To go check in, is it configured properly? Is the supply chain software going to be there? Who's managing the services? Who's orchestrating the nodes? >> Yep. >> Is that automated, is that where you guys see the value? >> That's a lot of what we see, yeah. In terms of how these companies are building these platforms, is taking all the component pieces that Haseeb was talking about and really putting it into a cohesive whole. And then, you, as a software developer, you don't have to worry about configuring all of those things. You don't have to worry about security policy, governance, how your app is going to be exposed to the internet. >> It sounds like infrastructure is code. >> (laughs) Yeah. >> Come on, like. >> (laughs) Infrastructure's code is a big piece of it, for sure, for sure. >> Yeah, look, infrastructure's code actually- >> Infrastructure's sec is code too, the security. >> Yeah. >> Huge. >> Well, it all goes together. Like, we talk about developer self-service, right? The way we enable developer self-service is by teaching developers, here's a snippet of code that you write and you check it in and your infrastructure will just magically be created. >> Yep. >> But not automatically. It's going to go through a check, like a check through the platform team. These are the workflows that if you get them right, developers don't care, right. All developers want is I want to compute. But then all these 20 things need to happen in the back. That's what, if you nail it, right, I mean, I keep trying to kind of pitch the company, I don't want to do that today. But if you nail that, >> I'll give you a plug at the end. >> you have a good story. >> But I got to, I just have a tangent question 'cause you reminded me. There's two types of developers that have emerged, right. You have the software developer that wants infrastructures code. I just want to write my code, I don't want to stop. I want to build in shift-left for security, shift-right for data. All that's in there. >> Right. >> I'm coding away, I love coding. Then you've got the under-the-hood person. >> Yes. >> I've been to the engines. >> Certainly. >> So that's more of an SRE, data engineer, I'm wiring services together. >> Yeah. >> A lot of people are like, they don't know who they are yet. They're in college or they're transforming from an IT job. They're trying to figure out who they are. So question is, how do you tell a person that's watching, like, who am I? Like, should I be just coding? But I love the tech. Would you guys have any advice there? >> You know, I don't know if I have any guidance in terms of telling people who they are. (all laughing) I mean, I think about it in terms of a spectrum and this is what we hear from customers, is some customers want to shift as much responsibility onto the software teams to manage their infrastructure as well. And then some want to shift it all the way over to the very centralized model. And, you know, we see everything in between as well with our EKS customer base. But, yeah, I'm not sure if I have any direct guidance for people. >> Let's see, any wisdom? >> Aside from experiment. >> If you're coding more, you're a coder. If you like to play with the hardware, >> Yeah. >> or the gears. >> Look, I think it's really important for managers to understand that developers, yes, they have a job, you have to write code, right. But they also want to learn new things. It's only fair, right. >> Oh, yeah. >> So what we see is, developers want to learn. And we enable for them to understand Kubernetes in small pieces, like small steps, right. And that is really, really important because if we completely abstract things away, like Kubernetes, from them, it's not good for them, right. It's good for their careers also, right. It's good for them to learn these things. This is going to be with us for the next 15, 20 years. Everybody should learn it. But I want to learn it because I want to learn, not because this is part of my job, and that's the distinction, right. I don't want this to become my job because I want, I want to write my code. >> Do what you love. If you're more attracted to understanding how automation works, and robotics, or making things scale, you might be under-the-hood. >> Yeah. >> Yeah, look under the hood all day long. But then, in terms of, like, who keeps the lights on for the cluster, for example. >> All right, see- >> That's the job. >> He makes a lot of value. Now you know who you are. Ask these guys. (Lisa laughing) Congratulations on your success on EKS 2. >> Yeah, thank you. >> Quick, give a plug for the company. I know you guys are growing. I want to give you a minute to share to the audience a plug that's going to be, what are you guys doing? You're hiring? How many employees? Funding? Customer new wins? Take a minute to give a plug. >> Absolutely. And look, I come see, John, I think, every show you guys are doing a summit or a KubeCon, I'm here. (John laughing) And every time we come, we talk about new customers. Look, platform teams at enterprises seem to love Rafay because it helps them build that, well, Kubernetes platform that we've talked about on the show today. I think, many large enterprises on the financial service side, healthcare side, digital native side seem to have recognized that running Kubernetes at scale, or even starting with Kubernetes in the early days, getting it right with the right standards, that takes time, that takes effort. And that's where Rafay is a great partner. We provide a great SaaS offering, which you can have up and running very, very quickly. Of course, we love EKS. We work with our friends at AWS. But also works with Azure, we have enough customers in Azure. It also runs in Google. We have enough customers at Google. And it runs on-premises with OpenShift or with EKS A, right, whichever option you want to take. But in terms of that standardization and governance and automation for your developers to move fast, there's no better product in the market right now when it comes to Kubernetes platforms than Rafay. >> Kevin, while we're here, why don't you plug EKS too, come on. >> Yeah, absolutely, why not? (group laughing) So yes, of course. EKS is AWS's managed Kubernetes offering. It's the largest managed Kubernetes service in the world. We help customers who want to adopt Kubernetes and adopt it wherever they want to run Kubernetes, whether it's in region or whether it's on the edge with EKS A or running Kubernetes on Outposts and the evolving portfolio of EKS services as well. We see customers running extremely high-scale Kubernetes clusters, excuse me, and we're here to support them as well. So yeah, that's the managed Kubernetes offering. >> And I'll give the plug for theCUBE, we'll be at KubeCon in Detroit this year. (Lisa laughing) Lisa, look, we're giving a plug to everybody. Come on. >> We're plugging everybody. Well, as we get to plugs, I think, Haseeb, you have a book to write, I think, on Kubernetes. And I think you're wearing the title. >> Well, I do have a book to write, but I'm one of those people who does everything at the very end, so I will never get it right. (group laughing) So if you want to work on it with me, I have some great ideas. >> Ghostwriter. >> Sure! >> But I'm lazy. (Kevin chuckles) >> Ooh. >> So we got to figure something out. >> Somehow I doubt you're lazy. (group laughs) >> No entrepreneur's lazy, I know that. >> Right? >> You're being humble. >> He is. So Haseeb, Kevin, thank you so much for joining John and me today, >> Thank you. >> talking about what you guys are doing at Rafay with EKS, the power, why you shouldn't hate k8s. We appreciate your insights and your time. >> Thank you as well. >> Yeah, thank you very much for having us. >> Our pleasure. >> Thank you. >> We appreciate it. With John Furrier, I'm Lisa Martin. You're watching theCUBE live from New York City at the AWS NYC Summit. John and I will be right back with our next guest, so stick around. (upbeat music) (gentle music)

>>Hey, everyone, welcome to the Cubes Coverage of the International Women's Showcase for 2022. I'm your host, Lisa Martin. Pleased to be here with an agreement ahead of small medium business SMB for Asia Pacific and Japan at Amazon Web services. Anna. It's great to have you on the programme, >>Lisa. I am delighted to be here and really excited to be talking about what we're gonna be talking about today, which is diversity and women in technology. >>One of the great things about International Women's Day Tuesday, March 8th, is there's always a campaign of theme. This year's theme is breaking the bias. What does that mean to you? And are we on our way to actually accomplish that? >>Look, Breaking the bias really is about all of us being more self aware in our workplaces. Really. What it means to me is understanding that the communities and the employment, the employee population, that all of us working is diverse. Um, and this is a great example of that, right? We are a global organisation and our employees come from across the world. I am representing people from across Asia Pacific and Japan. They look, feel and think differently to people in other parts of the world. So, really, what breaking the biases about is understanding our unconscious biases and thinking differently about how we approach conversations in the workplace to make sure that we're including everyone in the conversation. And honestly, Lisa, when you do that, you get much better. Business outcomes. I've seen that for sure. >>Definitely. There's some stats we can talk about later that I think really articulate that point incredibly well. But I want to talk about your background. You pivoted many times from lawyer to the CEO of ANZ Bank in the Philippines to now a leader at Amazon Web services. Talk to you about your career path with all those different pivots. How did you get to where you are tonight? >>Yeah, I mean, honestly, I recognise that I don't have a traditional Orthodox career plan, but that's my intention. I'm somebody who has always been really interested in the world around me, and I would say that my biggest driver is learning and being curious, which, as you know, is an Amazon leadership principles. So it's probably not a surprise that I ended up here at Ws, but really for me when I thought about my career and I have thought about it intentionally. I've been willing to put my hand up and take risks where I think probably others around me were not feeling as safe, and that's that's a function of who I am. But it's also a function of what I see women wanting to and needing to do more in order to bring their career forward. So as you say, I started my I had a pure technical lens when I started my career, which was being a lawyer, and there's been a lot of time just learning that and holding that skill set, I knew Lisa even then that that was not what I wanted to do forever. I wanted to do more than simply sit in an office and negotiate documents. Um, even though that was an exciting career, there was more that I wanted to do. So off the back of that, I moved into banking and was able to to learn and build some really important skill sets in terms of thinking about being a leader. And those skill sets include things like running a balance sheet, managing people thinking differently about risking compliance, which then allowed me to guess, run a bank and run the business. And then finally, how did I then pivot into technology? Well, it was a long conversation. If I'm honest with you, you know, there were there were conversations back and forth and I thought to myself and doing the right thing here. But what I could see for sure was that the world was moving to a technological context and for me not to take an opportunity to do it. A job like running a technology business across Asia, particularly Japan, just It just wasn't a possibility for me. I had to take the opportunity. So here I am, >>And that's one of the most exciting things I think is that these days every company has to be a tech company. Every company has to be a data company, a digital company with one of the lessons we've learned in the last couple of years. But another thing that we've learned is you mentioned skill sets. But it isn't just about those hard skill sets. What are some of those key soft skill sets that you think are really outstanding and really help to break down the bias. >>Yeah, again, Really interesting. So as I'm talking to women, when they hear about my career journey, a lot of them are surprised. How could you move into technology? And I think the challenge is that a lot of women view technology simply as a coding context. They view it as something that only someone with technical skills can do, and that is simply not the case. So if you look at a recent study by Deloitte Access Economics in Australia, for instance, the soft, skill intensive occupations are going to account for two thirds of all jobs by 2030. So if you think about that having a pure technical skill set, so certainly if you're going to do something like be a solutions architect or be a coda, it's really important that you must have those skills. But technology businesses are building and growing like no other, so we need all of those soft skills, like project management like P and L. Accountability and responsibility, like learning how to manage teams. These are caused fuels that have nothing to do with kind of fundamental technology, understanding that business contacts is important, but there are a lot of women out there who could be working in technology now but are a little bit scared to do so because they're thinking maybe they don't have the skills and I would encourage them to think differently. >>I think your your background with your pivots is a great articulation of you can take so many different backgrounds law banking into tech There's probably a fair amount of overlap there, but you also have you have in and of yourself thought diversity because of your background. I think that's another important thing for women to learn how important that thought diversity can be in any sort of job that they do, whether they are in a technical field. Or maybe they're in finance or operations or sales for a technology company. You guys talk about builders at A. W S. Talk to me about what a builder is, what's that definition and one of some of those key skill sets hard and soft that those builders exemplify. >>Yeah, so we are very build focused at AWS because we're building on behalf of our customers. But what that means is that the trays that make you a builder are exemplified by our leadership principles. So things like being curious. As you just pointed out, Lisa, these are the tenants of being a good builder, um, pursuing continuous learning. So whilst you you may know that you're good at something, you're not scared of trying something else. You're not scared of training and learning about something else. Being able to look around corners, um, and take calculated risks. I mean, whilst it may sound like my career journey has been pivot, pivot, pivot. Actually, if we're honest that these have been very intentional moves that I've made with my career to try to learn, as I said, to try to grow, um, and I've been fortunate and have been intentional also about building that leadership profile, But that's because I'm really fundamentally interested in how business and how people are connecting across the world. And as I said to you in a building context, really, that's about learning about how to build and run digital businesses. And at the end of the day is I guess the key message that I would send to everyone out there getting involved in a career in technology is not a bad move. >>No, it's definitely not a bad movie. I love the curiosity angle. That's one of those things that I'd love to hear. How do you encourage that? One of the biggest challenges. If we look at the stats of girls in stem programmes, from primary school to high school to university, as we see the numbers going down, we see them going up in university. And then, of course, when we're in, we're looking at the raw tech numbers. The number of women in technical positions is quite low to your point. There's many other opportunities besides technical positions. How do you encourage women to not be afraid to raise their hand and ask a question, even if they think maybe this is a dumb question? >>Uh, it's such a I think, you know, honestly, we need to see more women in leadership roles. Um, and, uh, and I think it's incumbent upon the organisations that are are running our businesses, that they make this a priority because you can't see I'm sorry. You can't be what you can't see Lisa, Um, and so it's great for us to talk about it. But once we start seeing women having active business, led conversations. That's where we're really going to see the dial shift. I have a 13 year old daughter, Um, and she's deeply interested in everything on her computer. Um, and what I try to do is encourage her to think differently about the type of roles that she could have if she was interested in, say, for instance, graphic design. She loves drawing, Um, singing. There are so many ways you can do all those YouTube videos. Maybe not, but you know, ways in which you can engage with technology to pursue a career that's interesting to you, regardless of your gender. So maybe the first part is making sure that we are talking about female leaders and what they're doing. I think also what we can do is start building programmes where we're involving women in building skills and certification skills. So here we've got this amazing event which we've built called She builds and I'm an active mentor for that. And what that's all about is kind of connecting women in the tech community and those who are interested with programmes that really speak to the way that women are thinking about their roles. So we have like minded peers. We have senior leaders, We have certification skills, programmes, always part of that, and we also have male allies. It's really important to include our male allies in that conversation, and you will have heard about things like male champions of change. These are very important conversations because again, what we know from statistics is that women are not as likely to build networks and sponsors as men are. And that's not statement of Miss Mala intense. What it means is that they just learn differently and think differently as they're building their careers. So if we're starting to get a man involved in the conversation in a more meaningful way, it's a conversation that's inclusive, and that's really what I want to drive. So I'm not sure I answered your question, but I certainly got to a couple of points that I was interested in highlighting, which is it's a conversation that has to happen at a grassroots level at a leadership level and across the organisation in terms of metrics, data understanding where women are and how to build and grow them >>right. But one of the things that you said that I was about to say was, We can't be what we can't see. We need to be able to elevate those female leaders like yourself so that more younger women and even women who maybe have been in the field for a while, can see the opportunities, the leadership. But you also brought up another great point. And that is, and something I was going to ask you about who are who are some of your mentors. And I imagine it's not just all females. It's got to be men as well. As you point out, it's incredibly important to have the men as allies. >>Yeah, absolutely. And certainly I wouldn't even be having this conversation with you now if I didn't have some amazing allies, both men and women, by my side as I've tracked this leadership journey. Certainly, um, Phil Davis, who is the head of our commercial organisation, Greg Pearson. These are people who have taken time out of their careers to talk with me about how we can help to build and grow women leaders, and to me, that's impactful. And I feel that that's an authentic engagement because there is a recognition in technology that we need to do more around this issue, and I see senior leaders like Matt Garman leading into the conversation. So for me, that's that's very inspiring. But I can't I couldn't have answered that question without telling you that the people who probably inspired me most in the organisation and within my network are those young women out there who are female founders. Now you know, I'm going to have to say a couple of names because I get the opportunity. Lisa, I've got a part of the networking, a women's networking, um, and mentoring organisation. And we have women here in Singapore like Ping Ping Han, who is building out an environmental education and sustainability digital business. We've got Francesco Cuccia, who is building Go get. She's already built it, which is an on demand workforce platform, which has over 250,000 people online that are helping people in Malaysia to work and has helped immensely during Covid. So what we're seeing with these young women is that they're actually building the digital businesses of the future, and it's not about, I mean, what I'm seeing them do is invest their time and energy in building. As I said, kind of programmes and models that are sustainable. So they're building businesses not just for the bottom line, but also to help the communities in which we operate, which to me is deeply inspirational. >>Absolutely. And the female founders need much more visibility than they're getting and obviously much more funding. One last point that I want to bring up because this is really important is that there is some data that I know that you have about performance company performance. When there are females at the helm, talk to me a little bit about that, and how can we help get that word out there more? Some more organisations understand the potential they have when they got that thought. Diversity. >>Yeah, it's such a wonderful point, and it's so well made now across the across media. But I feel like we need to double down on it because this is not a piecemeal conversation about doing the right thing. Um, sometimes we view it that way, and of course it is the right thing to have equity and diversity in our workplace. But in fact, there's so much data around how a diverse workforce creates better outcomes for business So in 2020 we had a McKenzie survey that found that companies with more than 30% of women executives were more likely to outperform companies with this percentage. So there is now a huge amount of data that's starting to show us what a diverse. And this is not just about gender. This is also about diversity across various lenses culture, ethnicity, minority groups, etcetera. So and for me, Lisa, it's just common sense. So if you're building a business that is trying to reach the most number of customers, it really is intuitive that you need to have all of those customers represented around the table. If you only have a single point of view, you're not going to represent all of those customers out there. And increasingly, those customers are expecting to be represented as part of your conversation in your business. So it totally makes sense from a business lens to build and recruit a diverse workforce. >>I couldn't agree more. One. I like to have one more question. Talk to me really quickly, briefly about how how are you building your teams to promote effectiveness through that diversity that, as you just described, can be so leading edge. >>Yeah, So what I'm doing is being intentional in my hiring practises. So this is something that all leaders can do. >>And that is really >>carefully about filling the roles in my organisation, where I'm given a role to fulfil, making sure that I'm looking at that diverse candidates, not just the same candidates who might have applied before. And that means sometimes throwing the net a bit wider than what you might usually have and thinking differently about the candidates that are applying. So, for instance, in my team, we have 50 50 men and women. Um, and we all come from very diverse backgrounds. We've got Indian, we've got Singaporean, we've got Australian talent, which means we've got a gender and cultural mix, which is actually, as I said, bringing a very different lens to the conversation when we're trying to solve customer problems. And what I would say is collaboration and respect is the cornerstone of the way that we should be. Building teams and diverse perspectives mean that our teams and the outcomes that we build are going to reflect the complexity of both the cross cultural and the divers, gender lens within which all of our customers are doing business today. >>Anna, thank you so much for joining me today, talking about the intentional pivots that you've made in your career, how inspiring those are two others and also how we're making progress on breaking the bias. My pleasure. >>Lisa. It's wonderful to join you. And thank you always think you for bringing us so much interesting data >>for Anna Greene. I'm Lisa Martin. You're watching the Cubes. Coverage of International Women's Showcase 2022.

(upbeat music) >> Welcome to this CUBE Conversation. This is part of the second season of the AWS startup showcase, season two, episode one. I'm Dave Nicholson, and I am joined with a very special guest, CEO and co-founder of Tidelift, Mr. Donald Fischer. Donald, welcome to the CUBE. >> Thanks David. Really glad to be here. >> So, first and foremost, tell us about Tidelift. >> Happy to, yeah, so, at Tidelift we're on a mission. Our mission is to make open source software work better for everyone, and when we say that, we mean, make it work better for all the organizations and governments and everybody that depends on open source software to build the applications that we all rely on. But also part of our mission, is making open source work better for the creators of open source. The independent open source maintainers, who are behind so many of those building blocks, technology building blocks that our commerce industry and society is comprised of these days. They've got a hard task to hold up all of that stuff and make sure that it meets, you know, professional grade standards and that we can all rely on it. And so, we want to do our part to help both sides of that equation. >> Fantastic, well, I want to double click on a few of the things that you said, but I think I want to format this by starting out with a little role play between the two of us, if you don't mind. I know you're CEO, but for the sake of this, you're going to be the CIO and I'm going to be the CEO, and we're going to play off some recent events here. So, hey Donald, come on in, sit down. Listen, I want to talk to you about this whole log shell, log for something, or another thing that's going on. So, let me get this straight. Our multinational Fortune 500 company is dependent upon software, that's free, and somehow we've been running this and the people who maintain it, do it for free, we don't pay for it, but somehow this has opened us up to a threat from people who can log into a system we're using to keep track of stuff, and then, what's going on? By the way, you're fired, but I want to know if, I want to know if you can stay on for the next 90 days to train your replacement, but, explain to me what's going on with this whole open-source nonsense? >> Yeah. Don't panic boss. Only about 70 or 80% of the software in our enterprise that is third-party open source software. So, there's definitely, like 20 or 30% that's not, and we're on top of it. Now, yeah, I think it's a, you know, you're right to say, we are completely dependent on this software, that's being created by these, you know, amazing folks on the internet. Boss, you told me that we had to have a global corporation here with modern digital customer experience. We're not going to be able to do it using Microsoft front page from 1997, and there's no other path to take than to build with modern building blocks. And today in, you know, the modern era, that means building on open source packages and technologies across a whole slew of language, ecosystems, like JavaScript and Java PHP, Ruby, Python, .NET, Rust, Go, we use all of it here, boss, and, we don't get to have a business unless we do. >> Okay, so, I didn't understand a word that you just said, but it was enough to convince me to let you keep your job. So, end-scene, we're not getting paid scale wages to do this, Donald, so I think we can go back to our normal personas. So, how does Tidelift play into all of this? I'd really want to hear about this concept of what an open source maintainer is, because these are largely volunteers, aren't they, in terms of the maintenance that they're doing? >> Yeah, so, I mean, open source, there's a lot of different models for open source software development. There certainly are a number of foundational open source projects, certainly at the infrastructure level, like operating systems, databases and things like that, that tend to be, you know, predominantly driven by vendors, software vendors, you know, like you can think of Red Hat, VMware organizations like that. But when you get up to the application development world, teams, building, you know, websites, web applications, mobile applications, most of the building blocks at that tier in these a programming language ecosystems, most of the software there is actually being created, that enterprise organizations use, is being created by individual, independent, open source maintainers, where it's not their day job, it's a side hustle for them. And it's a really interesting question, like, how did we get here? You know, why are these folks doing it? It sort of rhymes with the question I asked myself years ago, like, who's typing all this stuff into Wikipedia, and why? Like, it's amazing resource, I'm so glad it's there, but why are they doing this, right? And it turns out that there's a bunch of motivations there's some cynical motivations for the open source maintainers that people attribute that are practical too, you know, people say your GitHub repository is your resume in as a modern developer, things like that helps you get a reputation, you can use that to get a job. But, when we've talked to the maintainers of the most widely used open source packages, and by that, I mean, thousands of packages that every major organization that builds software relies on, the main reason why they do it is actually impact. We find we've actually done direct surveys of this audience and the reason why they spend their nights and weekends and carve out time, where they could be, you know, getting paid to do something else or going skiing or going to the beach, is it really feels good to have this activity that they put out into the world, and, you know, they know that folks use this stuff and rely on it, and there's a pride in their work and the impact that they're making. But the challenge with this model is that when it's only an impact and pride, and sort of a, you know, a good feeling driven effort, it means that maybe all of the things that organizations might want their standards that organizations might want their software to meet doesn't get done, right? Like it's one thing, if you've got a job as a software engineer, building corporate software, or even as a, you know, a maintainer at a corporate open source company, and you have a checklist of, you know, standard enterprise software development, commercial grade software development tasks that you need to be completing, if you're doing it as a side hustle for good reasons, like impact and, you know, releasing your creative juice, you might not get to some of the more boring aspects of commercial software engineering, like security engineering and some of the documentation and release engineering and, you know, making sure there's structured metadata around all the elements of it. And then that's the gap that we're really trying to fill at Tidelift, by connecting these two audiences. >> Yeah. How? How? You want to fill the gap, you want to connect the audiences, but, how do you do that? >> Yeah, perfect, so, we do it by paying the maintainers, paying the open source maintainers, actual dollars, or the currency of their preference, and what we're paying them for is not just to sort of hack on their projects, or hack on their projects more, we're asking them to help us ensure that the software that the organizations that we work with depend on meets certain specific concrete enterprise standards, and those standards fall into three categories, security, licensing, and maintenance. So, on the security front, you know, a baseline standard, there is making sure that we have known versions of the open source packages that are free of known defects, right? So there's like a catalog of known security defects that the industry uses called the National Vulnerability Database, you may have seen the terminology CVE referred to in passing, that's the identifier for these things. So, we work with the open-source maintainers to make sure that we've figured out, mapped out, which versions of software packages are impacted by known security vulnerabilities. And then we also look forward and make sure that we have a plan in place for what happens in the future when there are security vulnerabilities. So, you know, traditional commercial software, there's a security response team, who's kind of standing by 24/7, ready to respond, and then there's a defined protocol of what's going to happen, in terms of what's called responsible disclosure, telling the right folks in the right sequence, that there is a vulnerability causing there to be a patch version of the software available, communicating that through, you know, traditional commercial software vendors for, you know, years have been doing that internally, that doesn't exist by default for volunteer, you know, part-time open source, independent open source maintainers. So we fill that gap and we pre-wire that with them to make sure that that first track security is can be buttoned up. >> So, you're paying them, are you and your co-founders wealthy philanthropists that are just doing this, or what's the business model here? Now you're pulling these people who were doing it for free, they're happy, but how does that translate into a business model for Tidelift. >> Perfect, so, the work that they're doing, you know, I talked a little bit about security, we also do similar things on those other attributes, like licensing, making sure that the licenses are completely accurate, and we kind of know who wrote the software, et cetera, and then maintenance, is it being proactively cared for going forward? Is somebody still on the case with these projects? Now, the result of all of that work, is we create a vetted catalog of known good open source releases that we've vetted with the experts, often the individuals and teams that wrote the code in the first place, usually, we vet that it meets these enterprise standards. That's a really useful tool for organizations that are building with that. So, the way that we convey that to organizations that are building software in a useful way is we have a SAS service software, that as a service platform, that's what Tidelift is, and basically, the teams that use this stuff, they plug us into their software development process, typically alongside other tools that they might have, like CI/CD tools that are running tests on their application logic, they'll plug in Tidelift into their release process to ensure that those, the 70 or 80% of the software that they ship, that comes from GitHub, comes from the Python package index, or NPM, or the Maven Central Repository for Java, we're vetting that that meets their enterprise standards and ensuring that the ingredients, the building blocks that go into their applications are known good and vetted to these concrete standards. And they are, you know, this is an unsolved problem for almost every serious organization. There's a couple of, you know, over-performing organizations, like Google has done some amazing internal work on this, Amazon has an incredible dedicated team that does this internally for Amazon developers, very few other organizations, even some of the largest multinational companies have a dedicated internal function doing this comprehensively and systematically. Tidelift is that function that these organizations can use. They can work with us and our network, our unique network of hundreds of these independent open source maintainers, to ensure that there is a feed of known good vetted packages to go into their applications. >> So, were maintainers going in and auditing, and editing, and vetting software that was essentially created by others? That's one question, and then the other question that kind of goes along with that is, are you vetting a gold copy of something and saying, this software meets certain criteria, you should feel okay using it, that's one thing. Validating that the actual distribution, you know, the actual code that's being executed in their enterprise is secure and hasn't been tampered with is another thing. So where do you sit in that distribution channel or that supply chain? >> Sure, so, on the distribution front, you can think of us, we're sort of a GPS system that your application developers can use to know which versions of software are going to meet your enterprise standards. We don't create a separate world where we have our own, you know, side copy of the entire development ecosystem. It's not what these organizations want. They don't want to use some weird enterprise world set of open source packages, they want to just, you know, type NPM install have the, you know, software flow into their organization, but they also want it to not have no insecurity vulnerabilities in it, and they don't want to get bitten two weeks or two years later with a license violation, because there was kind of fuzzy, or incomplete data around the open source license. So what we do is, we help them consume the open source software, you know, knowing that it's been vetted to these standards. And then we also work with the open source community to cause the software to be changed to meet those standards, right? So back to the first part of your question, We work with a lot of projects with the prime maintainers, often the authors, as I said, and we've actually been extending our model over the years to work with these open source maintainers to cover not just their own project, but, some of those neighboring projects, right? Like the core projects that their project depends on, other projects that are co-used with them, they have a lot of expertise, and also, you know, relationships with the surrounding open source community there. So, they're working with us as curators, if you will, our ambassadors that help us get on the community and cover as much of the landscape as possible. >> And, so, what's the relationship with AWS? This is, you know, we're talking here as part of the AWS startup showcase season two, episode one, which is, that's actually pretty cool. So we need to, you know, the challenge here is, season one was awesome, much like Ted Lasso, season two, we have big shoes to fill here, Donald. So, what's the-- >> We got to up our game. >> (laughs) What's the relationship with AWS? And, I mean, why would they call you out as someone interesting for us to talk to? >> Yeah, so, we've had a great relationship that we've been investing in, and working on together with AWS. So, every one of AWS's customers faces this challenge around the software workloads that they're deploying on AWS. You know, it's just, you can't argue against the fact that the vast majority of the application software in the modern world is comprised majority of this third-party open source software. And so, it's really important whether it's running on a device, you know, an Edge device, or whether it's running in a Cloud data center, that those applications meet these standards, especially on the security front. So, AWS recognizes this need and opportunity for their customers, and so we've been working really well jointly with them. We're glad to say that we're an ISV, and AWS ISV accelerate partner now, which gives us the ability to co-engage with AWS and work together to solve mutual customers challenges, and we've had a great time working with the AWS team to help scale up our efforts to get the word word out around this important area, and then more importantly, give organizations the tools to address it and make sure that they have a comprehensive strategy for managing their open source in place. >> Fantastic, Donald, we're up against time, but I do have a 10 second answer I'd like from you. Tidelift, is that a reference to a rising tide lifting all boats, or is it an admonishment not to build a house on the beach in Malibu? >> It's the former, you know, think about this network of independent open source maintainers, working together, a rising tide lifts all boats. >> Eight seconds, that was like four seconds. Perfect. Donald Fischer, from Tidelift, thank you so much. For me, Dave Nicholson here at the CUBE. This has been a CUBE Conversation, as part of AWS's startup showcase, season two, episode one. Come to the CUBE for the best in tech coverage. (soft music)

(upbeat music) >> Despite its 70 to $80 billion total available market, computer storage is like a small town, everybody knows everybody else. We say in the storage world, there are a hundred people, and 99 seats. Infinidat is a company that was founded in 2011 by storage legend, Moshe Yanai. The company is known for building products with rock solid availability, simplicity, and a passion for white glove service, and client satisfaction. Company went through a leadership change recently, in early this year, appointed industry vet, Phil Bullinger, as CEO. It's making more moves, bringing on longtime storage sales exec, Richard Bradbury, to run EMEA, and APJ Go-To-Market. And just recently appointed marketing maven, Eric Hertzog to be CMO. Hertzog has worked at numerous companies, ranging from startups that were acquired, two stints at IBM, and is SVP of product marketing and management at Storage Powerhouse, EMC, among others. Hertzog has been named CMO of the year as an OnCon Icon, and top 100 influencer in big data, AI, and also hybrid cloud, along with yours truly, if I may say so. Joining me today, is the newly minted CMO of Infinidat, Mr.Eric Hertzog. Good to see you, Eric, thanks for coming on. >> Dave, thank you very much. You know, we love being on theCUBE, and I am of course sporting my Infinidat logo wear already, even though I've only been on the job for two weeks. >> Dude, no Hawaiian shirt, okay. That's a pretty buttoned up company. >> Well, next time, I'll have a Hawaiian shirt, don't worry. >> Okay, so give us the backstory, how did this all come about? you know Phil, my 99 seat joke, but, how did it come about? Tell us that story. >> So, I have known Phil since the late 90s, when he was a VP at LSA of Engineering, and he had... I was working at a company called Milax, which was acquired by IBM. And we were doing a product for HP, and he was providing the subsystem, and we were providing the fiber to fiber, and fiber to SCSI array controllers back in the day. So I met him then, we kept in touch for years. And then when I was a senior VP at EMC, he started originally as VP of engineering for the EMC Isilon team. And then he became the general manager. So, while I didn't work for him, I worked with him, A, at LSA, and then again at EMC. So I just happened to congratulate him about some award he won, and he said "Hey Herzog, "we should talk, I have a CMO opening". So literally happened over LinkedIn discussion, where I reached out to him, and congratulate him, he said "Hey, I need a CMO, let's talk". So, the whole thing took about three weeks in all honesty. And that included interviewing with other members of his exec staff. >> That's awesome, that's right, he was running the Isilon division for awhile at the EMC. >> Right. >> You guys were there, and of course, you talk about Milax, LSA, there was a period of time where, you guys were making subsystems for everybody. So, you sort of saw the whole landscape. So, you got some serious storage history and chops. So, I want to ask you what attracted you to Infinidat. I mean, obviously they're a leader in the magic quadrant. We know about InfiniBox, and the petabyte scale, and the low latency, what are the... When you look at the market, you obviously you see it, you talk to everybody. What were the trends that were driving your decision to join Infinidat? >> Well, a couple of things. First of all, as you know, and you guys have talked about it on theCUBE, most CIOs don't know anything about storage, other than they know a guy got to spend money on it. So the Infinidat message of optimizing applications, workloads, and use cases with 100% guaranteed availability, unmatched reliability, the set and forget ease of use, which obviously AIOps is driving that, and overall IT operations management was very attractive. And then on top of that, the reality is, when you do that consolidation, which Infinidat can do, because of the performance that it has, you can dramatically free up rack, stack, power, floor, and operational manpower by literally getting rid of, tons and tons of arrays. There's one customer that they have, you actually... I found out when I got here, they took out a hundred arrays from EMC Hitachi. And that company now has 20 InfiniBoxes, and InfiniBox SSAs running the exact same workloads that used to be, well over a hundred subsystems from the other players. So, that's got a performance angle, a CapEx and OPEX angle, and then even a clean energy angle because reducing Watson slots. So, lots of different advantages there. And then I think from just a pure marketing perspective, as someone has said, they're the best kept secret to the storage industry. And so you need to, if you will, amp up the message, get it out. They've expanded the portfolio with the InfiniBox SSA, the InfiniGuard product, which is really optimized, not only as the PBA for backup perspective, and it works with all the backup vendors, but also, has an incredible play on data and cyber resilience with their capability of local logical air gapping, remote logical air gapping, and creating a clean room, if you will, a vault, so that you can then recover their review for malware ransomware before you do a full recovery. So it's got the right solutions, just that most people didn't know who they were. So, between the relationship with Phil, and the real opportunity that this company could skyrocket. In fact, we have 35 job openings right now, right now. >> Wow, okay, so yeah, I think it was Duplessy called them the best kept secret, he's not the only one. And so that brings us to you, and your mission because it's true, it is the best kept secret. You're a leader in the Gartner magic quadrant, but I mean, if you're not a leader in a Gartner magic quadrant, you're kind of nobody in storage. And so, but you got chops and block storage. You talked about the consolidation story, and I've talked to many folks in Infinidat about that. Ken Steinhardt rest his soul, Dr. Rico, good business friend, about, you know... So, that play and how you handle the whole blast radius. And that's always a great discussion, and Infinidat has proven that it can operate at very very high performance, low latency, petabyte scale. So how do you get the word out? What's your mission? >> Well, so we're going to do a couple of things. We're going to be very, very tied to the channel as you know, EMC, Dell EMC, and these are articles that have been in CRN, and other channel publications is pulling back from the channel, letting go of channel managers, and there's been a lot of conflict. So, we're going to embrace the channel. We already do well over 90% of our business within general globally. So, we're doing that. In fact, I am meeting, personally, next week with five different CEOs of channel partners. Of which, only one of them is doing business with Infinidat now. So, we want to expand our channel, and leverage the channel, take advantage of these changes in the channel. We are going to be increasing our presence in the public relations area. The work we do with all the industry analysts, not just in North America, but in Europe as well, and Asia. We're going to amp up, of course, our social media effort, both of us, of course, having been named some of the best social media guys in the world the last couple of years. So, we're going to open that up. And then, obviously, increase our demand generation activities as well. So, we're going to make sure that we leverage what we do, and deliver that message to the world. Deliver it to the partner base, so the partners can take advantage, and make good margin and revenue, but delivering products that really meet the needs of the customers while saving them dramatically on CapEx and OPEX. So, the partner wins, and the end user wins. And that's the best scenario you can do when you're leveraging the channel to help you grow your business. >> So you're not only just the marketing guy, I mean, you know product, you ran product management at very senior levels. So, you could... You're like a walking spec sheet, John Farrier says you could just rattle it off. Already impressed that how much you know about Infinidat, but when you joined EMC, it was almost like, there was too many products, right? When you joined IBM, even though it had a big portfolio, it's like it didn't have enough relevant products. And you had to sort of deal with that. How do you feel about the product portfolio at Infinidat? >> Well, for us, it's right in the perfect niche. Enterprise class, AI based software defined storage technologies that happens run on a hybrid array, an all flash array, has a variant that's really tuned towards modern data protection, including data and cyber resilience. So, with those three elements of the portfolio, which by the way, all have a common architecture. So while there are three different solutions, all common architecture. So if you know how to use the InfiniBox, you can easily use an InfiniGuard. You got an InfiniGuard, you can easily use an InfiniBox SSA. So the capability of doing that, helps reduce operational manpower and hence, of course, OPEX. So the story is strong technically, the story has a strong business tie in. So part of the thing you have to do in marketing these days. Yeah, we both been around. So you could just talk about IOPS, and latency, and bandwidth. And if the people didn't... If the CIO didn't know what that meant, so what? But the world has changed on the expenditure of infrastructure. If you don't have seamless integration with hybrid cloud, virtual environments and containers, which Infinidat can do all that, then you're not relevant from a CIO perspective. And obviously with many workloads moving to the cloud, you've got to have this infrastructure that supports core edge and cloud, the virtualization layer, and of course, the container layer across a hybrid environment. And we can do that with all three of these solutions. Yet, with a common underlying software defined storage architecture. So it makes the technical story very powerful. Then you turn that into business benefit, CapEX, OPEX, the operational manpower, unmatched availability, which is obviously a big deal these days, unmatched performance, everybody wants their SAP workload or their Oracle or Mongo Cassandra to be, instantaneous from the app perspective. Excuse me. And we can do that. And that's the kind of thing that... My job is to translate that from that technical value into the business value, that can be appreciated by the CIO, by the CSO, by the VP of software development, who then says to VP of industry, that Infinidat stuff, we actually need that for our SAP workload, or wow, for our overall corporate cybersecurity strategy, the CSO says, the key element of the storage part of that overall corporate cybersecurity strategy are those Infinidat guys with their great cyber and data resilience. And that's the kind of thing that my job, and my team's job to work on to get the market to understand and appreciate that business value that the underlying technology delivers. >> So the other thing, the interesting thing about Infinidat. This was always a source of spirited discussions over the years with business friends from Infinidat was the company figured out a way, it was formed in 2011, and at the time the strategy perfectly reasonable to say, okay, let's build a better box. And the way they approached that from a cost standpoint was you were able to get the most out of spinning disk. Everybody else was moving to flash, of course, floyers work a big flash, all flash data center, etc, etc. But Infinidat with its memory cache and its architecture, and its algorithms was able to figure out how to magically get equivalent or better performance in an all flash array out of a system that had a lot of spinning disks, which is I think unique. I mean, I know it's unique, very rare anyway. And so that was kind of interesting, but at the time it made sense, to go after a big market with a better mouse trap. Now, if I were starting a company today, I might take a different approach, I might try to build, a storage cloud or something like that. Or if I had a huge install base that I was trying to protect, and maybe go into that. But so what's the strategy? You still got huge share gain potentials for on-prem is that the vector? You mentioned hybrid cloud, what's the cloud strategy? Maybe you could summarize your thoughts on that? >> Sure, so the cloud strategy, is first of all, seamless integration to hybrid cloud environments. For example, we support Outpost as an example. Second thing, you'd be surprised at the number of cloud providers that actually use us as their backend, either for their primary storage, or for their secondary storage. So, we've got some of the largest hyperscalers in the world. For example, one of the Telcos has 150 Infiniboxes, InfiniBox SSAS and InfiniGuards. 150 running one of the largest Telcos on the planet. And a huge percentage of that is their corporate cloud effort where they're going in and saying, don't use Amazon or Azure, why don't you use us the giant Telco? So we've got that angle. We've got a ton of mid-sized cloud providers all over the world that their backup is our servers, or their primary storage that they offer is built on top of Infiniboxes or InfiniBox SSA. So, the cloud strategy is one to arm the hyperscalers, both big, medium, and small with what they need to provide the right end user services with the right outside SLAs. And the second thing is to have that hybrid cloud integration capability. For example, when I talked about InfiniGuard, we can do air gapping locally to give almost instantaneous recovery, but at the same time, if there's an earthquake in California or a tornado in Kansas City, or a tsunami in Singapore, you've got to have that remote air gapping capability, which InfiniGuard can do. Which of course, is essentially that logical air gap remote is basically a cloud strategy. So, we can do all of that. That's why it has a cloud strategy play. And again we have a number of public references in the cloud, US signal and others, where they talk about why they use the InfiniBox, and our technologies to offer their storage cloud services based on our platform. >> Okay, so I got to ask you, so you've mentioned earthquakes, a lot of earthquakes in California, dangerous place to live, US headquarters is in Waltham, we're going to pry you out of the Golden State? >> Let's see, I was born at Stanford hospital where my parents met when they were going there. I've never lived anywhere, but here. And of course, remember when I was working for EMC, I flew out every week, and I sort of lived at that Milford Courtyard Marriott. So I'll be out a lot, but I will not be moving, I'm a Silicon Valley guy, just like that old book, the Silicon Valley Guy from the old days, that's me. >> Yeah, the hotels in Waltham are a little better, but... So, what's your priority? Last question. What's the priority first 100 days? Where's your focus? >> Number one priority is team assessment and integration of the team across the other teams. One of the things I noticed about Infinidat, which is a little unusual, is there sometimes are silos and having done seven other small companies and startups, in a startup or a small company, you usually don't see that silo-ness, So we have to break down those walls. And by the way, we've been incredibly successful, even with the silos, imagine if everybody realized that business is a team sport. And so, we're going to do that, and do heavy levels of integration. We've already started to do an incredible outreach program to the press and to partners. We won a couple awards recently, we're up for two more awards in Europe, the SDC Awards, and one of the channel publications is going to give us an award next week. So yeah, we're amping up that sort of thing that we can leverage and extend. Both in the short term, but also, of course, across a longer term strategy. So, those are the things we're going to do first, and yeah, we're going to be rolling into, of course, 2022. So we've got a lot of work we're doing, as I mentioned, I'm meeting, five partners, CEOs, and only one of them is doing business with us now. So we want to get those partners to kick off January with us presenting at their sales kickoff, going "We are going with Infinidat "as one of our strong storage providers". So, we're doing all that upfront work in the first 100 days, so we can kick off Q1 with a real bang. >> Love the channel story, and you're a good guy to do that. And you mentioned the silos, correct me if I'm wrong, but Infinidat does a lot of business in overseas. A lot of business in Europe, obviously the affinity to the engineering, a lot of the engineering work that's going on in Israel, but that's by its very nature, stovepipe. Most startups start in the US, big market NFL cities, and then sort of go overseas. It's almost like Infinidat sort of simultaneously grew it's overseas business, and it's US business. >> Well, and we've got customers everywhere. We've got them in South Africa, all over Europe, Middle East. We have six very large customers in India, and a number of large customers in Japan. So we have a sales team all over the world. As you mentioned, our white glove service includes not only our field systems engineers, but we have a professional services group. We've actually written custom software for several customers. In fact, I was on the forecast meeting earlier today, and one of the comments that was made for someone who's going to give us a PO. So, the sales guy was saying, part of the reason we're getting the PO is we did some professional services work last quarter, and the CIO called and said, I can't believe it. And what CIO calls up a storage company these days, but the CIO called him and said "I can't believe the work you did. We're going to buy some more stuff this quarter". So that white glove service, our technical account managers to go along with the field sales SEs and this professional service is pretty unusual in a small company to have that level of, as you mentioned yourself, white glove service, when the company is so small. And that's been a real hidden gem for this company, and will continue to be so. >> Well, Eric, congratulations on the appointment, the new role, excited to see what you do, and how you craft the story, the strategy. And we've been following Infinidat since, sort of day zero and I really wish you the best. >> Great, well, thank you very much. Always appreciate theCUBE. And trust me, Dave, next time I will have my famous Hawaiian shirt. >> Ah, I can't wait. All right, thanks to Eric, and thank you for watching everybody. This is Dave Vellante for theCUBE, and we'll see you next time. (bright upbeat music)

>>it's mhm Okay, we're here in the cube unpacking the HPD Green Lake announcements, Daniel neumann series Principal analyst and founder of your um research Damn. You're good to see you again, >>Dave always going to jump jump on with you. It's good to have a minute sit down. So >>what's your favorite announcement from from Green Lake? What do you, what do you make of what they announced today? >>Well, I love the opportunity for the company to position itself up against a growth monster like snowflake. I mean looking at the ability to handle the breath of the data at scale and offer a data service that can compete in that space. That's exactly the kind of narrative that I think the markets, the outside world is going to want to hear from HP is how you're not just competing with your traditional, the doubles, the Ciscos, the IBM, you're going after the, the mega growth cloud players and data services. And for me that's really attractive because I've been really on top of hb saying, hey, you're doing a lot of the right things, but people have to feel and see the growth. >>To me this is a major move toward the tam expansion strategy. It's kind of the job of every Ceo right, is to expand the tam. And I'm interested to see how HP e plays this and communicates this because, you know, traditionally it's a hardware company, uh moving into data management Data services. That's an enormous market. We'll talk about how important data is but the data management is just huge. And to do it in a cloud like fashion, how do you see that as potentially expanding the total available market for HP? >>Well, first, let's just almost walking back a second, Dave HP is a cloud player. Okay. And that's the story that it is trying to get out there. It is not a hardware player that's tinkering in software. Hp has done software, this isn't its first go. But if you want to be a cloud player, you look at the big hyper scale as you look at the AWS, as you look at the google, you look at as the google built, not just on hardware, it's built that big C and I've had this conversation before, all the things that make up the cloud, it's the hardware, it's the software, it's the services, the platform, you got to put all these things together. And if HP wants to be a public cloud experience, taking advantage of where we're moving with hybrid and offering it private, it has to have that same subset of services. Look at the investment, whether it's been a W S or google or Azure in data services, HP has to be in this space. So, seeing this come to fruition, in my opinion, is directionally the right path, getting it to be well received, winning the right customers and showing the growth from these investments is going to be the next important phase. >>Do you see that as a service model as being more margin friendly for HP and and if so why? Well, I think >>universally we found there's two major improvements that moving to the as a service. One is, it does over time create expanded operational margin. It's just economies of scale. You can utilize every resource more efficiently. Of course there are Capex expenses, You've seen the amount that hyper skeletons have had to spend to expand their their footprints globally. So there is some Capex upfront but that also on the back end creates the depreciation and different bottom line profit creators. At the same time though, as a service is huge for the multiples and evaluation, which by the way is one of the things that has been a real in focus point for H. P. E. Is how does it up that that number, You know, you look at the snowflakes, not even profitable but getting huge. You know, um, you know, huge multiples on revenue. And then you see even the other hyper scale is all getting bigger plays on revenue and on E. P. S. Most of it has to do with the fact that recurring revenue is beloved by investors, but it's also really sticky and creates a ton of stability within the company for the culture of the business to say, hey, we have customers, they're going to stay with us. They're not going anywhere. They're subscribed to our services. They're buying into what we're doing and by the way, net revenue expansion as you get them sticky, you layer in new services. We've seen how this has worked across the board with public cloud, with software with SAS, can HP do it as well? And of course it's been something they're doing, but it's something we need to watch really closely and I think it's an opportunity that the company needs to lean into it. And I think they will, >>you mentioned snowflake a couple times, there's a there's a, there's a discussion in the industry, it was sort of prompted by martin casado and sarah wang about repatriation and particularly as it relates to software, saas companies uh that the the the cloud bill is so high at some point, they're giving away margin, so they're going to have to come back on prem, I'm not sure that to date that has applied to the general audience of customer, although there's a lot of debate as well between the expensive cloud, obviously, you know, egress charges. So it's hard sometimes to squint through that when you think about HP E bringing Green Lake to market at scale bringing repeatable processes, driving automation, etcetera. How do you think that that cloud repatriation argument, which frankly, I haven't seen a huge cloud repatriation in in the macro, but how do you think that will play out over time, Do you feel like the on prem play can be as cost effective or more cost effective or maybe you feel like it is already today? >>Well, I also listen to the injuries and Horowitz uh, repatriation narrative as well. I think there are economies of scale with cloud that companies have to look at closely. But I also think that has a lot to do with why hybrid has been sort of the story of the day. That's why hyper sailors are going on prem or, and that's why I'm primes are moving to the cloud is because it's always going to be some, you know, some group of different placements of workloads to ultimately get to that optimized result. And so, you know, when you look at, you know, sort of what you asked in my opinion, you know, ultimately it's all about the efficiency of your organization trying to accomplish what your business is. And will there be some repatriation of workloads possibly. But there will be a very important hybrid mix. And I think we're gonna continue to see that trend and I think that's exactly where everyone's going in. Hp is going as well. >>All right, then we've got to leave it there. Thanks so much for your insights, appreciate it. We're gonna definitely have you back you and I are going to do some cool stuff together. So we'll talk next time. Thanks all right, and thank you for watching, this is Dave Volonte for the keeps coverage of H P E Green Lakes announcement, keep it right there. Mm

>>no real filter and that kind of stuff. But you're also an entrepreneur, right? And you know the business, you've been in software, you detect business. I'm instructing you get a lot of pictures, this entertainment business on our show, we're a bubble. We don't do a lot of tech deals that were talking because it's boring tv tech people love tech consumers love the benefit of text. No consumer opens up their iphone and says, oh my gosh, I love the technology behind my, what's it been like being on the shark tank? You know, filming is fun and hang out just fun and it's fun to be a celebrity at first your head gets really big and you get a really good tables at restaurants and who says texas has got a little possessed more skin in the game today in charge of his destiny. Great robert Herjavec. No, these two stars cube alumni >>welcome back to the cubes coverage of A W. S. Public sector seven. I'm john for your host of the cube got a great segment here on healthcare startup accelerators of course. Sandy carter is co hosting media. This one Vice President Aws. She's awesome on the cuBA and jennifer Blumenthal co founder and C of one record entrepreneur, very successful. Thanks for coming on jennifer. Thank good to see you. Sandy thanks for joining me again. You >>are most welcome, >>jennifer. Before we get into the whole accelerated dynamic, just take a minute to explain what you guys do. One record. >>Sure. So one record is a digital health company that enables users to access aggregate and share their healthcare information. So what that means is we help you as a person get your data and then we also help companies who would like to have workflows were consumers in the loop to get their data. So whether they're sharing it with a provider, researcher payer. >>So, Sandy, we've talked about this amazon web services, healthcare accelerator cohort batches. What do you call cohort batches? Cohorts explain what's going on with the healthcare accelerator? >>Yeah. So, um, we decided that we would launch and partner an accelerator program and accelerator program just provides to a start up a little bit extra technical help. A little bit extra subject matter expertise and introductions to funders. And so we decided we were going to start one for health care. It's one of the biggest disruptive industries in public sector. Um, and so we weren't sure how it's gonna go. We partnered with Kids X. Kids X is part of the Los Angeles system for medical. And so we put out a call for startups and we had 427 startups, we were told on average and accelerating it's 50-100. So we were blown away 31 different countries. So it was really amazing. And then what we've been doing is down selecting and selecting that Top 10 for our first cohort. So we're going from 427 down to 10. And so obviously we looked at the founders themselves to see the quality of the leadership of the company, um the strength of their technology and the fit of the technology into the broader overall healthcare and healthcare ecosystem. And so we were thrilled that jennifer and one record was one of the top 10 start ups in this space that we chose to be in the, in the cohort. And so now we're going to take it to the six weeks intensive where we'll do training, helping them with AWS, provide them A W. S. Credits and then Kid X will also provide some of the health care uh subject matter >>expertise as well. Can I get some of those credits over here to maybe? >>Yes, you can actually, you can talk to me don you can't >>Talk to me, Jennifer, I gotta ask you. So you're an entrepreneur. So doing start doing cos it's like a roller coaster. So now to make the top 10 but also be in the area of his accelerator, it's a partnership, right? You're making a bet. What's your take on all this? >>Well, we've always been partners with a W. S. We started building on AWS in the very beginning. So when I was setting up the company a huge decision early on with infrastructure and when I saw the launch of the accelerator, I had to apply because we're at the point in the company that we're growing and part of growing is growing with the VW. So I was really excited to take advantage of that opportunity and now in the accelerator, it's more of thinking about things that we weren't thinking about the services that we can leverage to fill in the gaps within our platform so we can meet our customers where they are >>using award winning MSP cloud status city, your partners, great relationship with the ecosystem. So congratulations Sandi. What's the disruption for the healthcare? Because right now education and health care, the two top areas we're seeing and we're reporting on where cloud scale developed two point or whatever buzzword digital transformation you want to use is impacting heavily healthcare industry. There's some new realities. What's your, what's your vision, what's your view? >>Hey john before she does that, I have to give a plug to Claudius city because they just made premier partner as well, which is a huge deal. Uh and they're also serving public sector. So I just wanted to make sure that you knew that too. So you can congratulate. Go ahead, jennifer >>Well, so if I zoom in, I think about a P. I. S. Every day, that's what I think about and I think about microservices. So for me and for one record, what we think about is legislation. So 21st century Cures act says that you as a consumer have to be able to access your healthcare data from both your providers and from your players and not just your providers, but also the underlying technology vendors and H. I. E. S. H. I am and it's probably gonna extend to really anyone who plays within the healthcare ecosystem. So you're just going to see this explosion of A. P. I. S. And we're just your one of that. I mean for the payers that we went into effect on july 1st. So I mean when you think about the decentralization of healthcare where healthcare is being delivered plus an api economy, you're just going to have a whole new model developing and then throwing price transparency and you've got a whole new cake. >>I'm smiling because I love the peacocks. In fact, last night I shouldn't have tweeted this but there's a little tweet flames going on around A. P. Is being brittle and all this stuff and I said, hey developer experience about building great software apps are there for you. It's not a glue layer by itself. You got to build software around the so kind of a little preaching to the younger generation. But this health care thing is huge because think about like old school health care, it was anti ap I was also siloed. So what's your take on has the culture is changing health care because the user experience, I want my records, I want my privacy, I want to maintain everything confidential but access. That's hard. >>I think well health care to be used to just be paper was forget about a. P. I. Is it was just paper records. I think uh to me you think about uh patient journey, like a patient journey starts with booking an appointment and then everything after that is essentially an api call. So that's how I think about it is to all these micro transactions that are happening all the time and you want your data to go to your health care provider so they can give you the proper care, you want your data to go to your pair so they can pay for your care and then those two stakeholders want your data so that they can provide the right services at the right time to the right channel. And that is just a series of api calls that literally sits on a platform. >>What's interesting, I'd love to get your take on the where you think the progress bar is in the industry because Fintech has shown the way you got defy now behind a decentralized finance, health care seems to be moving on in a very accelerated rate towards that kind of concept of cloud, scale, decentralization, privacy. >>Yeah, I mean, that's a big question, what's interesting to me around that is how healthcare stakeholders are thinking about where they're providing care. So as they're buying up practices primary care specialty care and they're moving more and more outside of the brick and mortar of the health care system or partnering with your startups. That's really where I think you're going to see a larger ecosystem development, you could just look at CVS and walmart or the dollar store if they're going to be moving into health care, what does that look like? And then if you're seeking care in those settings, but then you're going to Mayo clinic or Kaiser permanente, there's so many new relationships that are part of your hair circle >>delivery is just what does that even mean now, delivery of health >>care. It's wherever you it's like the app economy you want to ride right now, you want a doctor right now, that's where we're heading its ease of use. >>This is this exciting startups, changing the game. Yes, I love it. I mean, this is what it's all about this health >>Care, this is what it's all about. And if you look at the funding right now from VCS, we're seeing so much funding pour into health care, we were just looking at some numbers and in the second quarter alone, the funding went up almost 700%. And the amount of funding that is pouring into companies like jennifer's company to really transform healthcare, 30% of it is going into telehealth. So when you talked about, you know, kind of ai at the edge, getting the right doctor the right expert at the right time, we're seeing that as a big trend in healthcare to >>well jennifer, I think the funding dynamics aside the opportunity for market total addressable market is massive when the application is being decomposed, you got front end, whether it's telemedicine, you got the different building blocks of healthcare being radically reconfigured. It's a re factoring of healthcare. Yeah, >>I think if you just think about where we're sitting today, you had to use an app to prove proof of vaccination. So this is not just national, this is a global thing to have that covid wallet. We at one record have a covid wallet. But just a couple years from now, I need more than just by covid vaccination. I need all my vaccinations. I need all my lab results. I need all my beds. It's opening the door for a new consumer behavior pattern, which is the first step to adoption for any technology. >>So somebody else covid wallet. So I need >>that was California. Did the, did a version of we just have a pen and it's pretty cool. Very handy. I should save it to my drive. But my phone, but I don't jennifer, what's the coolest thing you're working on right now because you're in the middle of all the action. >>I get very excited about the payer app is that we're working on. So I think by the end of the month we will be connected to almost to all the blues in the United States. So I'm very excited when a user comes into the one record and they're able to get their clinical data from the provider organization and then their clinical financial and formulary data from their payers because then you're getting a complete view, You're getting the records for someone who gave you care and you're getting the records from someone who paid for your care. And that's an interesting thing that's really moving towards a complete picture. So from a personal perspective that gets exciting. And then from a professional perspective, it's really working with our partners as they're using our API s to build out workflows and their applications. >>It's an api economy. I'd like to ask you to on the impact side to the patient. I hear a lot of people complaining that hey, I want to bring my records to the doctor and I want to have my own control of my own stuff. A lot of times, some doctors don't even know other historical data points about a patient that could open up a diagnosis and, or care >>or they can't even refer you to a doctor. Most doctors really only refer within a network of people that they know having a provider directory that allows doctors refer, having the data from different doctors outside of their, you know, I didn't really allows people to start thinking beyond just their little box. >>Cool. Well, great to have you on and congratulations on being in the top 10 saying this is a wonderful example of how the ecosystem where you got cloud city, your MSP. You mentioned the shout out to them jerry Miller and his team by working together the cloud gives you advantages. So I have to ask, we look at amazon cloud as an entrepreneur. It's kind of a loaded question, but I'm going to ask it. I love it. >>You always do it >>when you look at amazon, what do you see as opportunities as an entrepreneur? Because I'll see the easy ones. They have computing everything else. But like what's the, what does cloud do for you as an entrepreneur? What does it, what does it make you do? >>Yeah. So for been working with jerry since the beginning for me when I think about it, it's really the growth of our company. So when we start building, we really just thinking about it from a monolithic build and we move to microservices and amazon has been there every step of the way to support us as that. And now, you know, the things that I'm interested in are specifically health lake and anything that's NLP related that we could plug into our solution for when we get data from different sources that are coming in really unstructured formats and making it structured so that it's searchable for people and amazon does that for us with their services that we can add into the applications. >>Yeah, we announced that data health like and july it has a whole set of templates for analytics, focused on health care as well as hip hop compliance out of the box as well. >>The I think I think that's what's important is people used to think application first. Now it's creating essentially a data lake, then analytics and then what applications you build on top of that. And that's how our partners think about it and that's how we try and service them using amazon as our problem. So >>you're honing in on the value of the data and how that conflicts and then work within the whatever application requests might come >>in. Yes, >>it's interesting. You know, we had an event last month and jerry Chen from Greylock partners came on and gave a talk called castles in the cloud. He's gonna be cute before. He's a, he's a veces, they talk about moats and competitive manage so having a moat, The old school perimeter moz how cloud destroyed that. He's like, no, now the castles are in the cloud, he pointed snowflake basically data warehouse in the cloud red shifts there too. But they can be successful. And that's how the cloud, you could actually build value, sustainable value in the cloud. If you think that way of re factoring not just hosting a huge, huge, huge thing. >>I think the only thing he, this was customer service because health care is still very personal. So it's always about how you interact with the end user and how you can help me get to where they need to be going >>and what do you see that going? Because that's, that's a good point. >>I think that is a huge opportunity for any new company that wants to enter healthcare, customer service as a service in health care for all the different places that health care is going to be delivered. Maybe there's a company that I don't know about, but when they come out, I'd like to meet them. >>Yeah, I mean, I can't think of one cover that can think of right now. This is what I would say is great customer service for health care. >>And if there is one out there contacted me because I want to talk to you about AWS. >>Yeah. And you need the app from one record that make it all >>happen. That's where Omni channel customer service across all health care entities. Yeah, that's >>a great billion dollar idea for someone listening to our show right now. >>Right, alright. So saying they had to give you the opportunity to talk more because this is a great example of how the world's very agile. What's the next step for the AWS Healthcare accelerator? Are there more accelerators? Do you do it by vertical? >>What happens next? So, with the healthcare accelerator, this was our first go at the accelerator. So, this is our first set of cohorts, Of course, all 427 companies are going to get some help from a W. S. as well. We also you'll love this john We also did a space accelerator. Make sure you ask Clint about that. So we have startups that are synthesizing oxygen on mars to sending an outpost box to the moon. I mean, it's crazy what these startups are doing. Um, and then the third accelerator we started was around clean energy. So sustainability, we sold that one out to, we had folks from 66 different countries participate in that one. So these have been really successful for us. So it reinvent. When we talk again, we'll be announcing a couple of others. So right now we've got healthcare, space, clean energy and we'll be announcing a couple other accelerators moving forward. >>You know, it's interesting, jennifer the pandemic has changed even our ability to get stories. Just more stories out there now. So you're seeing kind of remote hybrid connections, ap ideas, whether it's software or remote interviews or remote connections. There's more stories being told out there with digital transformation. I mean there wasn't that many before pandemic has changed the landscape because let's face it, people were hiding some really bad projects behind metrics. But when you pull the pandemic back and you go, hey, everyone's kind of emperors got no clothes on. Those are bad projects. Those are good projects that cloud investment worked or I didn't have a cloud investment. They were pretty much screwed at that point. So this is now a new reality of like value, you can't show me value. >>It's crazy to me when I meet people who tell me like we want to move to the cloud of like, why are you not on the cloud? Like this really just blows my life. Like I don't understand why you have on prem or while you did start on the cloud, this is more for larger organizations, but younger organizations, you know, the first thing you have to do, it's set up that environment. >>Yeah. And then now with the migration plans and seeing here, uh whereas education or health care or other verticals, you've got, now you've got containers to give you that compatibility and then you've got kubernetes and you've got microservices, you've got land. Uh I mean, come on, that's the perfect storm innovation. There's no excuses in my opinion. So, you know, if you're out there and you're not leveraging it, then you're probably gonna be out of business. That's my philosophy. Thank you for coming up. Okay. Sandy, thank you. Thank you, john Okay. Any of his coverage here, summit here in D. C. I'm john ferrier. Thanks for watching. Mm >>mm mm mhm. I have been in the software and technology industry for over 12 years now, so I've had >>the opportunity