(chill electronic music) >> Hello everyone, welcome to theCUBE's presentation of the AWS Startups Showcase, AI and machine learning, the top startups building generative AI on AWS. This is the season three, episode one of the ongoing series covering the exciting startups from the AWS ecosystem, talk about AI and machine learning. Can't believe it's three years and season one. I'm your host, John Furrier. Got a great guest today, we're joined by Joseph Nelson, the co-founder and CEO of Roboflow, doing some cutting edge stuff around computer vision and really at the front end of this massive wave coming around, large language models, computer vision. The next gen AI is here, and it's just getting started. We haven't even scratched a service. Thanks for joining us today. >> Thanks for having me. >> So you got to love the large language model, foundation models, really educating the mainstream world. ChatGPT has got everyone in the frenzy. This is educating the world around this next gen AI capabilities, enterprise, image and video data, all a big part of it. I mean the edge of the network, Mobile World Conference is happening right now, this month, and it's just ending up, it's just continue to explode. Video is huge. So take us through the company, do a quick explanation of what you guys are doing, when you were founded. Talk about what the company's mission is, and what's your North Star, why do you exist? >> Yeah, Roboflow exists to really kind of make the world programmable. I like to say make the world be read and write access. And our North Star is enabling developers, predominantly, to build that future. If you look around, anything that you see will have software related to it, and can kind of be turned into software. The limiting reactant though, is how to enable computers and machines to understand things as well as people can. And in a lot of ways, computer vision is that missing element that enables anything that you see to become software. So in the virtue of, if software is eating the world, computer vision kind of makes the aperture infinitely wide. It's something that I kind of like, the way I like to frame it. And the capabilities are there, the open source models are there, the amount of data is there, the computer capabilities are only improving annually, but there's a pretty big dearth of tooling, and an early but promising sign of the explosion of use cases, models, and data sets that companies, developers, hobbyists alike will need to bring these capabilities to bear. So Roboflow is in the game of building the community around that capability, building the use cases that allow developers and enterprises to use computer vision, and providing the tooling for companies and developers to be able to add computer vision, create better data sets, and deploy to production, quickly, easily, safely, invaluably. >> You know, Joseph, the word in production is actually real now. You're seeing a lot more people doing in production activities. That's a real hot one and usually it's slower, but it's gone faster, and I think that's going to be more the same. And I think the parallel between what we're seeing on the large language models coming into computer vision, and as you mentioned, video's data, right? I mean we're doing video right now, we're transcribing it into a transcript, linking up to your linguistics, times and the timestamp, I mean everything's data and that really kind of feeds. So this connection between what we're seeing, the large language and computer vision are coming together kind of cousins, brothers. I mean, how would you compare, how would you explain to someone, because everyone's like on this wave of watching people bang out their homework assignments, and you know, write some hacks on code with some of the open AI technologies, there is a corollary directly related to to the vision side. Can you explain? >> Yeah, the rise of large language models are showing what's possible, especially with text, and I think increasingly will get multimodal as the images and video become ingested. Though there's kind of this still core missing element of basically like understanding. So the rise of large language models kind of create this new area of generative AI, and generative AI in the context of computer vision is a lot of, you know, creating video and image assets and content. There's also this whole surface area to understanding what's already created. Basically digitizing physical, real world things. I mean the Metaverse can't be built if we don't know how to mirror or create or identify the objects that we want to interact with in our everyday lives. And where computer vision comes to play in, especially what we've seen at Roboflow is, you know, a little over a hundred thousand developers now have built with our tools. That's to the tune of a hundred million labeled open source images, over 10,000 pre-trained models. And they've kind of showcased to us all of the ways that computer vision is impacting and bringing the world to life. And these are things that, you know, even before large language models and generative AI, you had pretty impressive capabilities, and when you add the two together, it actually unlocks these kind of new capabilities. So for example, you know, one of our users actually powers the broadcast feeds at Wimbledon. So here we're talking about video, we're streaming, we're doing things live, we've got folks that are cropping and making sure we look good, and audio/visual all plugged in correctly. When you broadcast Wimbledon, you'll notice that the camera controllers need to do things like track the ball, which is moving at extremely high speeds and zoom crop, pan tilt, as well as determine if the ball bounced in or out. The very controversial but critical key to a lot of tennis matches. And a lot of that has been historically done with the trained, but fallible human eye and computer vision is, you know, well suited for this task to say, how do we track, pan, tilt, zoom, and see, track the tennis ball in real time, run at 30 plus frames per second, and do it all on the edge. And those are capabilities that, you know, were kind of like science fiction, maybe even a decade ago, and certainly five years ago. Now the interesting thing, is that with the advent of of generative AI, you can start to do things like create your own training data sets, or kind of create logic around once you have this visual input. And teams at Tesla have actually been speaking about, of course the autopilot team's focused on doing vision tasks, but they've combined large language models to add reasoning and logic. So given that you see, let's say the tennis ball, what do you want to do? And being able to combine the capabilities of what LLM's represent, which is really a lot of basically, core human reasoning and logic, with computer vision for the inputs of what's possible, creates these new capabilities, let alone multimodality, which I'm sure we'll talk more about. >> Yeah, and it's really, I mean it's almost intoxicating. It's amazing that this is so capable because the cloud scales here, you got the edge developing, you can decouple compute power, and let Moore's law and all the new silicone and the processors and the GPUs do their thing, and you got open source booming. You're kind of getting at this next segment I wanted to get into, which is the, how people should be thinking about these advances of the computer vision. So this is now a next wave, it's here. I mean I'd love to have that for baseball because I'm always like, "Oh, it should have been a strike." I'm sure that's going to be coming soon, but what is the computer vision capable of doing today? I guess that's my first question. You hit some of it, unpack that a little bit. What does general AI mean in computer vision? What's the new thing? Because there are old technology's been around, proprietary, bolted onto hardware, but hardware advances at a different pace, but now you got new capabilities, generative AI for vision, what does that mean? >> Yeah, so computer vision, you know, at its core is basically enabling machines, computers, to understand, process, and act on visual data as effective or more effective than people can. Traditionally this has been, you know, task types like classification, which you know, identifying if a given image belongs in a certain category of goods on maybe a retail site, is the shoes or is it clothing? Or object detection, which is, you know, creating bounding boxes, which allows you to do things like count how many things are present, or maybe measure the speed of something, or trigger an alert when something becomes visible in frame that wasn't previously visible in frame, or instant segmentation where you're creating pixel wise segmentations for both instance and semantic segmentation, where you often see these kind of beautiful visuals of the polygon surrounding objects that you see. Then you have key point detection, which is where you see, you know, athletes, and each of their joints are kind of outlined is another more traditional type problem in signal processing and computer vision. With generative AI, you kind of get a whole new class of problem types that are opened up. So in a lot of ways I think about generative AI in computer vision as some of the, you know, problems that you aimed to tackle, might still be better suited for one of the previous task types we were discussing. Some of those problem types may be better suited for using a generative technique, and some are problem types that just previously wouldn't have been possible absent generative AI. And so if you make that kind of Venn diagram in your head, you can think about, okay, you know, visual question answering is a task type where if I give you an image and I say, you know, "How many people are in this image?" We could either build an object detection model that might count all those people, or maybe a visual question answering system would sufficiently answer this type of problem. Let alone generative AI being able to create new training data for old systems. And that's something that we've seen be an increasingly prominent use case for our users, as much as things that we advise our customers and the community writ large to take advantage of. So ultimately those are kind of the traditional task types. I can give you some insight, maybe, into how I think about what's possible today, or five years or ten years as you sort go back. >> Yes, definitely. Let's get into that vision. >> So I kind of think about the types of use cases in terms of what's possible. If you just imagine a very simple bell curve, your normal distribution, for the longest time, the types of things that are in the center of that bell curve are identifying objects that are very common or common objects in context. Microsoft published the COCO Dataset in 2014 of common objects and contexts, of hundreds of thousands of images of chairs, forks, food, person, these sorts of things. And you know, the challenge of the day had always been, how do you identify just those 80 objects? So if we think about the bell curve, that'd be maybe the like dead center of the curve, where there's a lot of those objects present, and it's a very common thing that needs to be identified. But it's a very, very, very small sliver of the distribution. Now if you go out to the way long tail, let's go like deep into the tail of this imagined visual normal distribution, you're going to have a problem like one of our customers, Rivian, in tandem with AWS, is tackling, to do visual quality assurance and manufacturing in production processes. Now only Rivian knows what a Rivian is supposed to look like. Only they know the imagery of what their goods that are going to be produced are. And then between those long tails of proprietary data of highly specific things that need to be understood, in the center of the curve, you have a whole kind of messy middle, type of problems I like to say. The way I think about computer vision advancing, is it's basically you have larger and larger and more capable models that eat from the center out, right? So if you have a model that, you know, understands the 80 classes in COCO, well, pretty soon you have advances like Clip, which was trained on 400 million image text pairs, and has a greater understanding of a wider array of objects than just 80 classes in context. And over time you'll get more and more of these larger models that kind of eat outwards from that center of the distribution. And so the question becomes for companies, when can you rely on maybe a model that just already exists? How do you use your data to get what may be capable off the shelf, so to speak, into something that is usable for you? Or, if you're in those long tails and you have proprietary data, how do you take advantage of the greatest asset you have, which is observed visual information that you want to put to work for your customers, and you're kind of living in the long tails, and you need to adapt state of the art for your capabilities. So my mental model for like how computer vision advances is you have that bell curve, and you have increasingly powerful models that eat outward. And multimodality has a role to play in that, larger models have a role to play in that, more compute, more data generally has a role to play in that. But it will be a messy and I think long condition. >> Well, the thing I want to get, first of all, it's great, great mental model, I appreciate that, 'cause I think that makes a lot of sense. The question is, it seems now more than ever, with the scale and compute that's available, that not only can you eat out to the middle in your example, but there's other models you can integrate with. In the past there was siloed, static, almost bespoke. Now you're looking at larger models eating into the bell curve, as you said, but also integrating in with other stuff. So this seems to be part of that interaction. How does, first of all, is that really happening? Is that true? And then two, what does that mean for companies who want to take advantage of this? Because the old model was operational, you know? I have my cameras, they're watching stuff, whatever, and like now you're in this more of a, distributed computing, computer science mindset, not, you know, put the camera on the wall kind of- I'm oversimplifying, but you know what I'm saying. What's your take on that? >> Well, to the first point of, how are these advances happening? What I was kind of describing was, you know, almost uni-dimensional in that you have like, you're only thinking about vision, but the rise of generative techniques and multi-modality, like Clip is a multi-modal model, it has 400 million image text pairs. That will advance the generalizability at a faster rate than just treating everything as only vision. And that's kind of where LLMs and vision will intersect in a really nice and powerful way. Now in terms of like companies, how should they be thinking about taking advantage of these trends? The biggest thing that, and I think it's different, obviously, on the size of business, if you're an enterprise versus a startup. The biggest thing that I think if you're an enterprise, and you have an established scaled business model that is working for your customers, the question becomes, how do you take advantage of that established data moat, potentially, resource moats, and certainly, of course, establish a way of providing value to an end user. So for example, one of our customers, Walmart, has the advantage of one of the largest inventory and stock of any company in the world. And they also of course have substantial visual data, both from like their online catalogs, or understanding what's in stock or out of stock, or understanding, you know, the quality of things that they're going from the start of their supply chain to making it inside stores, for delivery of fulfillments. All these are are visual challenges. Now they already have a substantial trove of useful imagery to understand and teach and train large models to understand each of the individual SKUs and products that are in their stores. And so if I'm a Walmart, what I'm thinking is, how do I make sure that my petabytes of visual information is utilized in a way where I capture the proprietary benefit of the models that I can train to do tasks like, what item was this? Or maybe I'm going to create AmazonGo-like technology, or maybe I'm going to build like delivery robots, or I want to automatically know what's in and out of stock from visual input fees that I have across my in-store traffic. And that becomes the question and flavor of the day for enterprises. I've got this large amount of data, I've got an established way that I can provide more value to my own customers. How do I ensure I take advantage of the data advantage I'm already sitting on? If you're a startup, I think it's a pretty different question, and I'm happy to talk about. >> Yeah, what's startup angle on this? Because you know, they're going to want to take advantage. It's like cloud startups, cloud native startups, they were born in the cloud, they never had an IT department. So if you're a startup, is there a similar role here? And if I'm a computer vision startup, what's that mean? So can you share your your take on that, because there'll be a lot of people starting up from this. >> So the startup on the opposite advantage and disadvantage, right? Like a startup doesn't have an proven way of delivering repeatable value in the same way that a scaled enterprise does. But it does have the nimbleness to identify and take advantage of techniques that you can start from a blank slate. And I think the thing that startups need to be wary of in the generative AI enlarged language model, in multimodal world, is building what I like to call, kind of like sandcastles. A sandcastle is maybe a business model or a capability that's built on top of an assumption that is going to be pretty quickly wiped away by improving underlying model technology. So almost like if you imagine like the ocean, the waves are coming in, and they're going to wipe away your progress. You don't want to be in the position of building sandcastle business where, you don't want to bet on the fact that models aren't going to get good enough to solve the task type that you might be solving. In other words, don't take a screenshot of what's capable today. Assume that what's capable today is only going to continue to become possible. And so for a startup, what you can do, that like enterprises are quite comparatively less good at, is embedding these capabilities deeply within your products and delivering maybe a vertical based experience, where AI kind of exists in the background. >> Yeah. >> And we might not think of companies as, you know, even AI companies, it's just so embedded in the experience they provide, but that's like the vertical application example of taking AI and making it be immediately usable. Or, of course there's tons of picks and shovels businesses to be built like Roboflow, where you're enabling these enterprises to take advantage of something that they have, whether that's their data sets, their computes, or their intellect. >> Okay, so if I hear that right, by the way, I love, that's horizontally scalable, that's the large language models, go up and build them the apps, hence your developer focus. I'm sure that's probably the reason that the tsunami of developer's action. So you're saying picks and shovels tools, don't try to replicate the platform of what could be the platform. Oh, go to a VC, I'm going to build a platform. No, no, no, no, those are going to get wiped away by the large language models. Is there one large language model that will rule the world, or do you see many coming? >> Yeah, so to be clear, I think there will be useful platforms. I just think a lot of people think that they're building, let's say, you know, if we put this in the cloud context, you're building a specific type of EC2 instance. Well, it turns out that Amazon can offer that type of EC2 instance, and immediately distribute it to all of their customers. So you don't want to be in the position of just providing something that actually ends up looking like a feature, which in the context of AI, might be like a small incremental improvement on the model. If that's all you're doing, you're a sandcastle business. Now there's a lot of platform businesses that need to be built that enable businesses to get to value and do things like, how do I monitor my models? How do I create better models with my given data sets? How do I ensure that my models are doing what I want them to do? How do I find the right models to use? There's all these sorts of platform wide problems that certainly exist for businesses. I just think a lot of startups that I'm seeing right now are making the mistake of assuming the advances we're seeing are not going to accelerate or even get better. >> So if I'm a customer, if I'm a company, say I'm a startup or an enterprise, either one, same question. And I want to stand up, and I have developers working on stuff, I want to start standing up an environment to start doing stuff. Is that a service provider? Is that a managed service? Is that you guys? So how do you guys fit into your customers leaning in? Is it just for developers? Are you targeting with a specific like managed service? What's the product consumption? How do you talk to customers when they come to you? >> The thing that we do is enable, we give developers superpowers to build automated inventory tracking, self-checkout systems, identify if this image is malignant cancer or benign cancer, ensure that these products that I've produced are correct. Make sure that that the defect that might exist on this electric vehicle makes its way back for review. All these sorts of problems are immediately able to be solved and tackled. In terms of the managed services element, we have solutions as integrators that will often build on top of our tools, or we'll have companies that look to us for guidance, but ultimately the company is in control of developing and building and creating these capabilities in house. I really think the distinction is maybe less around managed service and tool, and more around ownership in the era of AI. So for example, if I'm using a managed service, in that managed service, part of their benefit is that they are learning across their customer sets, then it's a very different relationship than using a managed service where I'm developing some amount of proprietary advantages for my data sets. And I think that's a really important thing that companies are becoming attuned to, just the value of the data that they have. And so that's what we do. We tell companies that you have this proprietary, immense treasure trove of data, use that to your advantage, and think about us more like a set of tools that enable you to get value from that capability. You know, the HashiCorp's and GitLab's of the world have proven like what these businesses look like at scale. >> And you're targeting developers. When you go into a company, do you target developers with freemium, is there a paid service? Talk about the business model real quick. >> Sure, yeah. The tools are free to use and get started. When someone signs up for Roboflow, they may elect to make their work open source, in which case we're able to provide even more generous usage limits to basically move the computer vision community forward. If you elect to make your data private, you can use our hosted data set managing, data set training, model deployment, annotation tooling up to some limits. And then usually when someone validates that what they're doing gets them value, they purchase a subscription license to be able to scale up those capabilities. So like most developer centric products, it's free to get started, free to prove, free to poke around, develop what you think is possible. And then once you're getting to value, then we're able to capture the commercial upside in the value that's being provided. >> Love the business model. It's right in line with where the market is. There's kind of no standards bodies these days. The developers are the ones who are deciding kind of what the standards are by their adoption. I think making that easy for developers to get value as the model open sources continuing to grow, you can see more of that. Great perspective Joseph, thanks for sharing that. Put a plug in for the company. What are you guys doing right now? Where are you in your growth? What are you looking for? How should people engage? Give the quick commercial for the company. >> So as I mentioned, Roboflow is I think one of the largest, if not the largest collections of computer vision models and data sets that are open source, available on the web today, and have a private set of tools that over half the Fortune 100 now rely on those tools. So we're at the stage now where we know people want what we're working on, and we're continuing to drive that type of adoption. So companies that are looking to make better models, improve their data sets, train and deploy, often will get a lot of value from our tools, and certainly reach out to talk. I'm sure there's a lot of talented engineers that are tuning in too, we're aggressively hiring. So if you are interested in being a part of making the world programmable, and being at the ground floor of the company that's creating these capabilities to be writ large, we'd love to hear from you. >> Amazing, Joseph, thanks so much for coming on and being part of the AWS Startup Showcase. Man, if I was in my twenties, I'd be knocking on your door, because it's the hottest trend right now, it's super exciting. Generative AI is just the beginning of massive sea change. Congratulations on all your success, and we'll be following you guys. Thanks for spending the time, really appreciate it. >> Thanks for having me. >> Okay, this is season three, episode one of the ongoing series covering the exciting startups from the AWS ecosystem, talking about the hottest things in tech. I'm John Furrier, your host. Thanks for watching. (chill electronic music)

(techno intro music) >> Hey everyone, good afternoon from sin city. This is Lisa Martin with Dave Vellante. We are in full swing of theCUBE's four days of coverage of AWS re:invent 2022. North of 50,000 people are here. We're nearing hundreds of thousands online. Dave, this has been, this is a great event. We've had great conversations. We're going to be having more conversations. One of the things we love talking about on theCUBE is AWS and its ecosystem of partners, and we are going to do just that right now. Brian Henderson joins us, Director of Marketing at Dell Technologies. Marc Trimuschat, Director of Worldwide Storage Specialists at AWS is also here. Guys, it's great to have you. >> Great to be here. >> Great to be here, yeah. Feeling the energy of the show. >> Isn't it great? >> Mark: I know, amazing. >> It's amazing. It started out high and it has not dropped since Monday night. Brian, talk a little bit about Dell, what you're doing with customers on their Cloud journeys. Every customer, every industry is on one at different points in their journey, but what's Dell helping out with there? >> What we're here to talk about is the progression that we've seen, right, Cloud has changed a lot over the years and Dell has really put out a strategy to help people with their Cloud journey, kind of wherever they are. So a lot of people have moved full shift. A lot of people see that as another location, and what we're showing at the booth is the idea of taking these enterprise capabilities that people know and trust from Dell, courting them to the Cloud. In some cases not courting, but just delivering that software in the Cloud, as well as taking some of the Kubernetes integrations, EKS Anywhere, bringing that on-prem. So we've got some storage, data protection, and our Kubernetes integration to talk about at the show. >> Awesome, Mark, talk about the role from Amazon's point of view that third party vendors like Dell Technologies plays in AWS's expanding vision of Cloud. >> Great, well, we're really excited to be partnering with Dell. What we see that historically is, you know, AWS is focused on builders, people, and really the developer community who are building those components themselves, putting together really resilient infrastructure and applications. What we're seeing today is a shift also to the type of customers that we're seeing, more traditional enterprise customers, who are demanding really performance, the scalability, also the resiliency of what they had on-premises, and they want that on the Cloud as well. So with Dell, and we've got some great solutions that we're partnering on, including Dell PowerFlex that provides that linear scalability and some of the high performance capabilities that customers are demanding. And also, another big trend that we're seeing is customers being affected by things like unfortunately malware events, right, and data protection. So Dell provides some great solutions in both those areas that allow enterprise customers to really experience that mission critical capability and resiliency that they have on-premises in the Cloud. >> You know, Brian, we've been at this a long time. >> Brian: Oh yeah, great to see you again. >> And I've been hearing my whole career that storage is going to get commoditized. And I guess if you're talking about spinning discs or flash drives, it's probably true, but as Mark was just saying if you want resilient storage and things that are recoverable, that don't go down all the time, they're not commodities. >> Brian: Yeah. >> It's real engineering. And you built the stack up, so talk about how that connection, what value you bring to the Cloud and your customers. >> Yeah, so what we see is people are always looking out for enterprise grade capabilities. So there's going to be a set of offerings, and AWS has a fantastic foundation for building on top of with the marketplace. So what we're able to do is really bring, in some cases, decades worth of investment in software engineering and put these advanced capabilities, whether it be PowerFlex with its linear scale. We'll have a file offering very soon. These products have been built from the ground up to do a very unique purpose. Giving that to people in the Cloud is just another location for us, AWS being the market leader. We're the market leader in storage. So us working together for the benefit of customers is really where it's at. >> Can you double click on that, Brian, what Dell and AWS? Give us all those juicy details. >> Sure, sure, sure, so what we've done right before this show is we put a product called PowerFlex, if you go back to 2018 scale IO, and you're taking this really linear scaling software defined architecture, and you're putting that in the Cloud. What that allows you to do is get that really advanced linear scale performance. You can even span clusters across AWS regions, as well as zones. So it's a really unique capability that allows us to be able to check in and do that. And in the data protection space, it's a whole separate category. We've been at this actually quite a while. We've got about 14 exo bytes of data that's already being protected on the AWS Cloud. So we've been at that for quite a while. And the two levels are really, do you want to back that up? Do you want to take a traditional back up application, maybe it's a lift and shift, and I want to back it up the way I used to, and you can do that in the Cloud now. Or we're seeing cyber resiliency come up a lot more, and we were just talking right before, it's a question of when, not if, and so we have to give our customers the option to not only detect that failure event early, but also to separate that copy with a logical air gap. >> The cyber resiliency is a topic we are talking more and more about. It's absolutely critical. We've seen the threat landscape change dramatically in the last couple of years. To your point, Brian, it's no longer, when we think of ransomware, it's no longer are we going to get hit? It's when, it's how often. What's the damage going to be? I think I saw a stat recently that there's one ransomware attack every 11 seconds. The average cost of reaches is in the millions, so what you're doing together on cyber resiliency for businesses in any industry is table stakes. >> Yeah, we just saw a survey that, it was done earlier this year survey, 66% unfortunately of corporations have experienced a malware attack. And that's an 80% increase from last year. >> Lisa: Wow. >> So again, I think that's an opportunity. It's a threat, but an opportunity, and so the partnership with Dell really helps bridge that and helps our customers, our mutual customers, recover from those incidents. >> A lot of people might say, this is interesting. A storage guy from Amazon, a storage guy from Dell, two leaders. And one might think, why didn't they just throw in a dash three, right, but you guys are both customer driven, customer obsessed. In the field, what are customers saying to you in terms of how they want you to work together? >> Well I think there's a place for everything. When you say throw in to S3, so S3 today, one of the big trends when you're looking here is just the amount of data, you know, we hear that rhetoric, you know, we've been in storage for many years, and the data has all increased up and to the right. But, you know, AWSI, S3 today, we have over 280 trillion objects in our, driving a hundred million transactions per second right now, so that's scale. So there's always a place for those really, we have hundreds of thousands of customers running their data links, so that's always going to be that really, you know, highly reliable, highly durable, high available solution for data links. But customers, there's a lot of different applications out there. So where customers are asking are those enterpise. So we have EBS, for example, which is our great, you know, scalable block search, elastic block store. We introduced some new volume types, like GP2, GP2, and IO2VX, which will have that performance. But there's still single availability zone. So what customers have done historically is they maybe the application layer, they put an application layer replication or resiliency across, but customers on-prem, they've relied on storage layers to do that work for them. So, with PowerFlex, that'll stand either using instant storage or EBS, building on that really strong foundation, but provide that additional layer to make it easy for customers to get that resiliency and that scalability that Brian talked about. >> Yep, yep. >> Anything you can add to that? >> Yeah, I mean to your question, how do we work together is really, it's all customer driven. So we see customers that are shifting workloads in the Cloud for the first time. And it might make sense to take an object, like PowerFlex or another storage technology, maybe you want to compress it a little bit before you send it to the Cloud. Maybe you don't want to lift and shift everything. So we have a team of people that works very closely with AWS to be able to determine how are you going to shift that workload out there? Does this make the right sense for you? So it's a very collaborative relationship. And it's all very customer driven because our customers are saying, I've got assets in the public Cloud, and I want them to be managed in a similar fashion to how I'm doing that on-prem. >> So customer obsession is clearly on both sides there. We know that. >> It's where it starts. >> Exactly, exactly. Going back to PowerFlex for a second, Brian, and I'd love to get an example of a joint customer that really is showing the value of what Dell and AWS are doing together. The question for you on PowerFlex, talk about the value that it offers to the public Cloud. And why should customers start there if they are early in this journey? >> All right, yeah, so the two angles are basically, are you coming from PowerFlex or you're coming from Cloud. If you're Cloud native, the advantage would be things like a really, really advanced block file system that has been built from the ground up to be software defined and pretty much Cloud native. What you're getting is that really linear scale up to about 1,000 nodes. You can span that across regions, across availability zones, so it's highly resilient. So if there's a node failure in one site, you're going to rebuild really fast, depending on the size of that cluster. So it's a very advanced architecture that's been built to run, you know, we didn't have to change a single line of code to run this product in the Cloud because it was Cloud native by default, so. >> Well that's the thing. We also see, and you've seen that with some of the other solutions, but customers really want that. Enterprise customers are, they want us to make sure those mission critical applications are working and stay up. So they also want to use the same environment. So we were talking before, we also see use cases where maybe they're using PowerFlex on-premises today and they want to be able to replicate that to PowerFlex that's in the Cloud. So we're seeing those, and the familiarity with that infrastructure really is that easy path, if you will, for those more conservative mission critical customers. >> We've learned a lot over the years from AWS's entry into the marketplace. Two recent teams working backwards. We talk about customer obsession. And also the Cloud experience. It brings me to APEX. >> Oh yeah. >> Dave: How does APEX fit in here? >> Yeah, so APEX is the categorization for all the things that we're doing around a modern Cloud experience for Dell customers. So we're taking them also on a journey, kind of as a service model. There's a do-it-yourself model. And anything that we do that touches Cloud is now being kind of put under that APEX moniker. So everything that we're doing around Project Alpine, enterprise software capabilities in the Cloud. Do you want someone else to manage it for you? Do you want it in a polo? That might be the right fit for you. It's all under that APEX umbrella and journey. So we're kind of still just getting started there, but we're seeing a lot of great traction. People want to pay as they go, you know, it's a very popular model that AWS has pretty much set the foundation for. So pay as you go, utility based pricing, this is all things our customers have been asking for. >> Yeah, so APEX, you basically set a baseline. You can dial it up, dial it down, very much pay by the drink. >> Absolutely. >> And, you know, like you said, it's early days. >> Brian: Yeah. >> But that's, again, AWS has influenced the business in a lot of different ways. >> Again, with the Dell, you know, the trust customers that Dell has built over the years and having those customers come in. We obviously are getting, again, it's an accelerated option for financial services to healthcare and all these customers that have relied on Dell for years, moving to the Cloud, having that trusted name and also that infrastructure that's similar and familiar to them. And then the resilience of the foundation that we have at AWS, I think it works really well together for those customers. >> I think it underscores to the majority of both AWS and in a lot of ways Dell, right. In the early days of Cloud, it was like uh oh, and now it's like oh, actually big market. Customers are demanding this. There's new value that we can create working together. Let's do it. >> Yeah, I mean, it didn't take us that long to get to it, but I'd say we had little fits and starts over the years, and now we've recognized like, this is where the future is. It's going to be Cloud, it's going to be on-prem, it's going to be Edge, it's going to be everything. It's going to be an and world. And so just doing the right thing for customers I think is exactly where we landed. It's a great partnership. >> Do you have a favorite customer story that you think really shines the light on the value of the Dell AWS partnership in terms of the business impact they're making? >> We have several large customers that I can't always like drop the names, but one of them is a very large video game production company. And we do a lot of work together where they're rendering maybe in house, they're sending to a shared location. They're copying data over to S3. They're able to let all their editors access that. They bring it back when it's compressed down a little bit and deliver that. We're also doing a lot of work with, I think I can say this, Amazon Thursday night football games. So what they've done there, it's a partner of ours working with AWS. All the details inside of that roaming truck that they drive around, there's a lot of Dell gear within there, and then everything connects back to AWS for that exact same kind of model. We need to get to the editors on a nightly basis. They're also streaming directly form that truck while they're enabling the editors to access a shared copy of it, so it's really powerful stuff. >> Thursday night prime is pretty cool. You know, some people are complaining cause I can't just switch channels during the commercials. It's like, first of all, you can. Second of all, the stats are unbelievable, right. You can just do your own replay when you want to. There's some cool innovations there. >> Oh yeah, absolutely. >> Very cool innovations. I've got one more question for each of you before we wrap. Marc, a question for you, we're making a fun Instagram reel. So think about a sizzle reel of if you were to summarize the show so far, what is AWS's message to its massive audience this year? >> Well, that's a big question. Because we have such a wide, as we mentioned, such a wide ranging audience. I really see a couple key trends that we're trying to address. One is, again don't forget, I'm a storage guy, so it's going to come from an angle from data, right. So, I think it's just this volume of data and that customers are bringing into the Cloud, either moving in from enterprises today or organically, just growing. You know, a couple years ago, megabytes were a lot, and now, you know, we're talking about petabytes every day. Soon it's going to be exo bytes are going to become the norm. So the big, I'd say, point one is the trend that I see is just the volume of data. And so what we're doing to address that is obviously we talked a little bit about S3 and being able to manage volumes of data, but also things like DataZone that we introduced because customers are looking to make sure that the right governance and controls to be able to access that data. So I think that's one big thing that I see the theme for the show today. The second thing is around, as I said, really these enterprise customers really wanted to move in these mission critical applications into the Cloud, and having that infrastructure to be able to support that easily from what they're doing today and move in quickly. The third area is around data protection, making sure the data protection and malware recovery, that's the theme that we see is really unfortunately that's today. But being able to recover quickly, both having native services and native offerings just built in resiliency into the core platforms, like S3 with object application, et cetera. And also partnering with Dell with cyber recovery and some of the solutions with Dell. >> Excellent, and Brian, last question for you. A bumper sticker that succinctly and powerfully describes why Dell and AWS are such awesome partners for customer issues. >> Best of both worlds, right? >> Lisa: Mic drop. >> Mic drop, done. >> That's awesome. You said that a lot more succinctly. (people laughing) >> Enterprise in Cloud, Cloud comin' to enterprise. >> Yeah, leader meets leader, right? >> Yeah, right. >> Love it, leader meets leader. Guys, it's been a pleasure having you on theCUBE. We appreciate hearing the latest from AWS and Dell from a storage perspective and from a Cloud perspective and how you're helping customers manage the explosion of data that's not going to slow down. We really appreciate you coming by the set. >> Thank you. >> Great, thanks so much, appreciate it. >> My pleasure. For our guests and Dave Vellante, I'm Lisa Martin, you're watching theCUBE, the leader in live enterprise and emerging tech coverage. (techno music)

(upbeat music) >> Welcome back friends. It's theCUBE LIVE in Las Vegas at the Venetian Expo, covering the first full day of AWS re:Invent 2022. I'm Lisa Martin, and I have the privilege of working much of this week with Dave Vellante. >> Hey. Yeah, it's good to be with you Lisa. >> It's always good to be with you. Dave, this show is, I can't say enough about the energy. It just keeps multiplying as I've been out on the show floor for a few minutes here and there. We've been having great conversations about cloud migration, digital transformation, business transformation. You name it, we're talking about it. >> Yeah, and I got to say the soccer Christians are really happy. (Lisa laughing) >> Right? Because the USA made it through. So that's a lot of additional excitement. >> That's true. >> People were crowded around the TVs at lunchtime. >> They were, they were. >> So yeah, but back to data. >> Back to data. We have a couple of guests here. We're going to be talking a lot with customer challenges, how they're helping to overcome them. Please welcome Kevin Zawodzinski, VP of Sales Engineering at COMMVAULT. >> Thank you. >> And Paul Meighan, Director of Product Management at AWS. Guys, it's great to have you on the program. Thank you for joining us. >> Thanks for having us. >> Thanks for having us. >> Isn't it great to be back in person? >> Paul: It really is. >> Kevin: Hell, yeah. >> You cannot replicate this on virtual, you just can't. It's nice to see how excited people are to be back. There's been a ton of buzz on our program today about Adam's keynote this morning. Amazing. A lot of synergies with the direction, Paul, that AWS is going in and where we're seeing its ecosystem as well. Paul, first question for you. Talk about, you know, in the customer environment, we know AWS is very customer obsessed. Some of the main challenges customers are facing today is they really continue this business transformation, this digital transformation, and they move to cloud native apps. What are some of those challenges and how do you help them eradicate those? >> Well, I can tell you that the biggest contribution that we make is really by focusing on the fundamentals when it comes to running storage at scale, right? So Amazon S3 is unique, distributed architecture, you know, it really does deliver on those fundamentals of durability, availability, performance, security and it does it at virtually unlimited scale, right? I mean, you guys have talked to a lot of storage folks in the industry and anyone who's run an estate at scale knows that doing that and executing on those fundamentals day after day is just super hard, right? And so we come to work every day, we focus on the fundamentals, and that focus allows customers to spend their time thinking about innovation instead of on how to keep their data durably stored. >> Well, and you guys both came out of the storage world. >> Right. >> Yeah, yeah. >> It was a box world, (Kevin laughs) and it ain't no more. >> Kevin: That's right, absolutely. >> It's a service and a service of scale. >> Kevin: Yeah. So architecture matters, right? >> Yeah. >> Yeah. >> Paul, talk a little bit about, speaking of innovation, talk about the evolution of S3. It's been around for a while now. Everyone knows it, loves it, but how has AWS architected it to really help meet customers where they are? >> Paul: Right. >> Because we know, again, there's that customer first focus. You write the press release down the road, you then follow that. How is it evolving? >> Well, I can tell you that architecture matters a lot and the architecture of Amazon S3 is pretty unique, right? I think, you know, the most important thing to understand about the architecture of S3 is that it is truly a regional service. So we're laid out across a minimum of 3 Availability Zones, or AZs, which are physically separated and isolated and have a distance of miles between them to protect against local events like floods and fires and power interruption, stuff like that. And so when you give us an object, we distribute that data across that minimum of 3 Availability Zones and then within multiple devices within each AZ, right? And so what that means is that when you store data with us, your data is on storage that's able to tolerate the failure of multiple devices with no impact to the integrity of your data, which is super powerful. And then again, super hard to do when you're trying to roll your own. So that's sort of a, like an overview of the architecture. In terms of how we think about our roadmap, you know, 90% of our roadmap comes directly from what customers tell us matters, and that's a tenant of how we think about customer obsession at AWS and it really is how we drive a roadmap. >> Right, so speaking of customers Kevin, what are customers asking you guys- >> Yeah. >> for, how does it relate to what you're doing with S3? >> Yeah, it's a wonderful question and one that is actually really appropriate for us being at re:Invent, right? So we got, last three years we've had customers here with us on stage talking about it. First of all, 3 years ago we did a virtual session, unfortunately, but glad to be back as you mentioned, with Coca-Cola and theirs was about scale and scope and really about how can we protect hundreds of thousands of objects, petabyte to data, in a simple and secure way, right. Then last year we actually met with a ACT, Inc. as well and co-presented with them and really talked about how we could protect modern workloads and their modern workloads around whether it was Aurora or as well as EKS and how they continue to evolve as well. And, last but not least it's going to be, this year we're talking with Illinois State University as well about how they're going to continue to grow, adapt and really leverage AWS and ourselves to further their support of their teachers and their staff. So that is really helping us quite a bit to continue to move forward. And the things we're doing, again, with our customer base it's really around, focused on what's important to them, right? Customer obsession, how are we working with that? How are we making sure that we're listening to them? Again, working with AWS to understand how can we evolve together and really ultimately their journeys. As you heard, even with those 3 examples they're all very different, right? And that's the point, is that everybody's at a different point in the journey. They're at a different place from a modernization perspective. So we're helping them evolve, as they're helping us evolve as well, and transform with AWS. >> So very mature COMMVAULT stack, the S3 bucket and all the other capabilities. Paul, you just talked about coming together- >> Right. >> Dave: for your customers. >> Yeah, yeah, absolutely. And just, you know, we were talking the other day, Paul and I were talking the other day, it's been, you know, we've worked with AWS, with integration since 2009, right? So a long time, right? I mean, for some that may not seem like a long time ago, but it is, right? It's, you know, over a decade of time and we've really advanced that integration considerably as well. >> What are some of the things that, I don't know if you had a chance to see the keynote this morning? >> Yeah, a little bit. >> What are some of the things that there was, and in fact this is funny, funny data point for you on data. One of my previous guests told me that Adam Selipsky spent exactly 52 minutes talking about data this morning. 52 minutes. >> Okay. >> That there's a data point. But talk about some of the things that he talked about, the direction AWS is going in, obviously new era in the last year. Talk about what you heard and how you think that will evolve the COMMVAULT-AWS relationship. >> Yeah, I think part of that is about flexibility, as Paul mentioned too, architecture matters, right? So as we evolve and some of the things that we pride ourselves on is that we developed our systems and our software and everything else to not worry about what do I have to build to today but how do I continue to evolve with my customer base? And that's what AWS does, right? And continues to do. So that's really how we would see the data environment. It's really about that integration. As they grow, as they add more features we're going to add more features as well. And we're right there with them, right? So there's a lot of things that we also talk about, Paul and I talk about, around, you know, how do we, like Graviton3 was brought up today around some of the innovations around that. We're supporting that with Auto Scale right now, right? So we're right there releasing, right when AWS releasing, co-developing things when necessary as well. >> So let's talk about security a little bit. First of all, what is COMMVAULT, right? You're not a security company but you're an adjacency to security. It's sort of, we're rethinking security. >> Kevin: Yep. >> including data protection, not a bolt-on anymore. You guys both have a background in that world and I'm sure that resonates. >> Yeah. >> So what is the security play here? What role does COMMVAULT play? I think we know pretty well what role AWS plays, but love to hear, Paul, your thoughts as well on security. >> Yeah, I'll start I guess. >> Go on Paul. >> Okay. Yeah, so on the security side of things, there's a quite a few things. So again, on the development side of things, we do things like file anomaly detection, so seeing patterns in data. We talked a lot about analytics as well in the keynote this morning. We look at what is happening in the customer environment, if there's something odd or out of place that's happening, we can detect that and we'll notify people. And we've seen that, we have case studies about that. Other things we do are simple, simple but elegant. Is with our security dashboard. So we'll use our security dashboard to show best practices. Are they using Multi-Factor Authentication? Are you viewing password complexity? You know, things like that. And allows people to understand from a security landscape perspective, how do we layer in protection with their other systems around security. We don't profess to be the security company, or a security company, but we help, you know, obviously add in those additional layers. >> And obviously you're securing, you know, the S3 piece of it. >> Mmmhmm. >> You know, from your standpoint because building it in. >> That's right. And we can tell you that for us, security is job zero. And anyone at AWS will tell you that, and not only that but it will always be our top priority. Right from the infrastructure on down. We're very focused on our shared responsibility model where we handle security from the hypervisor, or host operating system level, down to the physical security of the facilities in which our services run and then it's our customer's responsibility to build secure applications, right. >> Yeah. And you talk about Graviton earlier, Nitro comes into play and how you're, sort of, fencing off, you know, the various components of the system from the operating system, the VMs, and then that is designed in and that's a new evolution that it comes as part of the package. >> Yeah, absolutely. >> Absolutely. >> Paul, talk a little bit about, you know, security, talking about that we had so many conversations this year alone about the threat landscape and how it's dramatically changing, it's top of mind for everybody. Huge rise in ransomware attacks. Ransomware is now, when are we going to get hit? How often? What's the damage going to be? Rather than, are we going to get hit? It's, unfortunately it's progressed in that direction. How does ensuring data security impact how you're planning the roadmap at AWS and how are partners involved in shaping that? >> Right, so like I said, you know, 90% of our roadmap comes from what customers tell us matters, right? And clearly this is an issue that matters very much to customers right now, right? And so, you know, we're certainly hearing that from customers, and COMMVAULT, and partners like COMMVAULT have a big role to play in helping customers to secure and protect their applications, right? And that's why it's so critical that we come together here at re:Invent and we have a bunch of time here at the show with the COMMVAULT technical folks to talk through what they're hearing from customers and what we're hearing. And we have a number of regular touch points throughout the year as well, right? And so what COMMVAULT gets from the relationship is, sort of, early access and feedback into our features and roadmap. And what we get out of it really is that feedback from that large number of customers who interface with Amazon S3 through COMMVAULT. Who are using S3 as a backup target behind COMMVAULT, right? And so, you know, that partnership really allows us to get close to those customers and understand what really matters to them. >> Are you doing joint engineering, or is it more just, hey here you go COMMVAULT, here's the tools available, go, go build. Can you address that? >> Yeah, no, absolutely. There's definitely joint engineering like even things around, you know, data migration and movement of data, we integrate really well and we talk a lot about, hey, what are you, like as Paul mentioned, what are you seeing out there? We actually, I just left a conversation about an hour ago where we're talking about, you know, where are we seeing placement of data and how does that matter to, do you put it on, you know, instant access, or do you put it on Glacier, you know, what should be the best practices? And we tell them, again, some of the telemetry data that we have around what do we see customers doing, what's the patterns of data? And then we feed that back in and we use that to create joint solutions as well. >> You know, I wonder if we could talk about cloud, you know, optimization of cloud costs for a minute. That's obviously a big discussion point in the hallways with customers. And on your earnings call you guys talked about specifically some customers and they specifically mentioned, for example, pushing storage to lower cost tiers. So you brought up Glacier just then. What are you seeing in the field in that regard? How are customers taking advantage of that? And where does COMMVAULT play in, sort of, helping make that decision? >> You want to take part one or you want me to take it? >> I can take part one. I can tell you that, you know, we're very focused on helping customers optimize costs, however necessary, right? And, you know, we introduced intelligent hearing here at the show in 2019 and since launch it's helped customers to reduce costs by over $750 million, right? So that's a real commitment to optimizing costs on behalf of customers. We also launched, you know, later in 2020, Glacier Deep Archive, which is the lowest cost storage in the cloud. So it's an important piece of the puzzle, is to provide those storage options that can allow customers to match the workloads that are, that need to be on folder storage to the appropriate store. >> Yeah, and so, you know, S3 is not this, you know, backup and recovery system, not an archiving system and, you know, in terms of, but you have that intelligence in your platform. 'Cause when I heard that from the earnings call I was like, okay, how do customers then go about deciding what they can, you know, when it's all good times, like yeah, who cares? You know, just go, go, go. But when you got to tighten the belt, how do you guys? >> Yeah, and that goes back to understanding the data pattern. So some of that is we have intelligence and artificial intelligence and everything else and machine learning within our, so we can detect those patterns, right? We understand the patterns, we learn from that and we help customers right size, right. So ultimately we do see a blend, right? As Paul mentioned, we see, you know, hey I'm not going to put everything on Glacier necessarily upfront. Maybe they are, it all depends on their workloads and patterns. So we use the data that we collect from the different customers that we have to share those best practices out and create, you know, the right templates, so to speak, in ways for people to apply it. >> Guys, great joint, you talked about the joint engineering, joint go to market, obviously a very strong synergistic partnership between the two. A lot of excitement. This is only day one, I can only imagine what's going to be coming the next couple of days. But I have one final question for you, but I have same question for both of you. You had the chance to create your own bumper sticker, so you get a shiny new car and for some reason you want to put a bumper sticker on it. About COMMVAULT, what would it say? >> Yeah, so for me I would say comprehensive, yet simple, right? So ultimately about giving you all the bells and whistles but if you want to be very simple we can help you in every shape and form. >> Paul, what's your bumper sticker say about AWS? >> I would say that AWS starts with the customer and works backwards from there. >> Great one. >> Excellent. Guys- >> Kevin: Well done. >> it's been a pleasure to have you on the program. Thank you- >> Kevin: Thank you. >> for sharing what's going on, the updates on the AWS-COMMVAULT partnership and what's in it for customers. We appreciate it. >> Dave: Thanks you guys. >> Thanks a lot. >> Thank you. >> All right. For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

>>Good afternoon and welcome back to the Classiest Show in Technology. This is the Cube we are at AWS Reinvent 2022 in Fabulous Sin City. That's why I've got my sequence on. We love a little Vegas, don't we? I'm joined by John Farer, another, another Vegas >>Fan. I don't have my sequence, I left it in my room. We're >>Gonna have to figure out how to get us 20 as soon as possible. What's been your biggest shock for you at the show so far? >>Well, I think the data story and security is so awesome. I love how that's front and center. If you look at the minutes of the keynote of Adamski, the CEO on day one, it's all bulked into data and security. All worked hand in hand. That's on top of already the innovation of their infrastructure. So I think you're gonna see a lot of interplay going on in this next segment. It's gonna tell a lot of that innovation story that's coming next. It's pretty awesome. >>It is pretty awesome, and I'm super excited. It's not only what we do here on the Cube, it's also in my show notes. We are gonna be geeking out for the next segment. Please welcome Paul and Puja. Wonderful to have you both here. Paul from Amazon, s3, glacier, and Pujan, CEO of kuo. I wanna turn to you Pujan, to start us off, just in case the audience isn't familiar, give us the Kuo pitch. >>Yeah, so basically Kuo is a, a backup as a service offering, right? Built in AWS four aws, right? And effectively going after, you know, any service that a customer uses on top of aws, right? And so a lot of the data sitting on s3, right? So that's been like our, our big use case going and basically building backup and air gap protection for, for s3. But we basically go to every other service, e c two, ebs, dynamo, you know, you name it, right? So basically do the whole thing >>And the relationship with aws. Can you guys share, I mean, you got you here together. You guys are a great partnership. Born in the cloud, operation in the cloud. Absolutely. I think talk about the partnership with aws. >>Absolutely. I think the last five years of building on AWS has been phenomenal, right? And I love the platform. It's, it's a very pure platform for us. You know, the APIs and, and the access you get and access you get to the service teams like Paul sitting here and the other teams you have gotten access to, I think has been phenomenal. But we also have, I would say, pushed the envelope in terms of how innovative we have been and how aggressive we have been in utilizing all the innovation that AWS has built in over the last few years. But it would not have happened without the fantastic partnership with the service teams. >>Paul, talk about the, AM the S3 part of this. What's the story there? >>Well, it's been great working with the CUO team over the course of the last few years. We were just upstairs diving deep into the, to the features that they're taking advantage of. They really push us hard on behalf of customers, and it's been a, it's just been a great relationship over the last years. >>That's awesome. And the ecosystem at such a, we're gonna hear tomorrow, the keynote on the, from Aruba who's gonna tend over the ecosystem. You guys are working together. There's a lot of strategic partnerships, so much collaboration between you guys that makes it very, this is the next gen cloud of cloud environment we're seeing. And you heard the, the economies around the corner. It's still gonna be challenging, but still there's more growth in the cloud. This is not stopping. This is impacts the customers. What are the customers saying to you guys when you work backwards from their needs? They want it faster, easier, cheaper. They want it more integrated. What are some of the things, all those you guys hearing from customers? >>So for us, you know, if you think about it, like, you know, as people are moving to the cloud, especially like take a use case like s3, right? So much of critical data sitting on top of S3 today. And so what folks have realized that as they're, you know, putting all of those, you know, what, over two 50 trillion objects, you know, sitting on s3, a lot of them need backup and data protection because there could be accidental deletions, there could be software bugs, there could be a ransomware type event due to which you need a second copy of the data that is outside of your security domain, right? But again, that needs to get be done at the, at the right price point, right? And that's where like a technology like Columbia comes in because since we've been built on the cloud, we've optimized it correctly. So especially for folks who are very cost conscious, given the macroeconomic conditions, we are heading into a technology that's built correctly so that, you know, you get the right architecture and the right solution at the right price point and the scale, right? Talking about trillions of objects, billions of objects within a single customer, within a single bucket sometimes. And that's where Columbia comes in. Cause we basically do that at scale without, again, impacting the, the customer's wallet more than it needs to. >>The porridge has to be the right temperature and the right size bowl. With the right spoon. You've got a lot of complexity when it comes to solving those customer challenges. You have a couple customer story examples you're allowed to share with us. Correct? Paul, do you want to kick one off? Go ahead. Oh, puja. All right. >>No, absolutely. I think there's a ton of them. I, I'll talk about, you know, want to begin with like Cox Automotive, right? A phenomenal customer that we, all of us have worked together with them. And again, looking for a solution to backup S3 to essentially go air gap protection outside of their account, right? They looked at doing it themselves, right? They thought they'll go and basically do it themselves. And then they fortunately bumped into Columbia, they looked at our architecture, looked at what it would really go and take to build it. And guess what, sitting in 2022, getting 23 right now, nobody wants to go and build this themselves. They actually want a turnkey solution that just does it, right? And so, again, we are a phenomenal joint customer of ours doing this at a pretty massive scale, right? And there are many more like that. There's Warner Brothers that are essentially going into the cloud from on premises, right? And they're going really fast accelerating the usage on aws again, looking at, you know, backup and data protection and using clum because of our extreme simplicity that we provide. >>Yeah, I think it's, you've got a, a lot of different people solving different problems that you're working with all the time. Millions of customers. Well, how do you prioritize? >>Well, for us, it really all comes down to fundamentals, right? So Amazon, s3 s unique distributed architecture delivers industry leading durability, availability, performance and security at virtually unlimited scale, right? And it's really been delivering on the fundamentals that has earned the trust of so many customers of all sizes and industries over the course of over 16 years. Now, in terms of how we prioritize on behalf of those customers, we always say that 90% of our roadmap comes directly from what customers are telling us is important. And a large number of our customers now are using S3 through lumino, which is why the relationship is so important. We're here talking about customer use cases here at the show, and we do that regularly throughout the year as well. And that's, that's how we land on a road. >>And what are the, what are the top stories from customers? What, what are they telling you? What's the number one top three things you're hearing? >>I tell you, like, again, it just comes down to the fundamentals, right? Of security, availability, durability and performance at virtually unlimited scale. Like that is the first customer first discussions that we have with customers talking about durable storage, for >>Sure. What I find interesting in, you mentioned scale, right? That comes up a lot scale with data. Yeah. That we heard data. The big theme here, security, what's in my S3 bucket? Can you find out what's in there? Is it backed up properly? How do I get it back? Where's the ransomware? Why not just target the ransomware? So how do you navigate the, the security challenges, the, the need to store all that scale data? What's the secret sauce? >>Yeah, so I think the, the big thing is we'll start with the, you know, how we have architected the product, right? If you think about it, this, you're dealing with a lot of scale, right? You get to a hundred million, a billion and billions very fast on S3 few, especially on a cloud native application. So it starts with the visibility, right? It's basically about, like we have things where you do, where you create a subset of your buckets called protection groups that you can essentially, you know, do it based on prefixes. So now you can essentially figure out what prefix you want to back up and what you don't want to back up. Maybe there's log data that you don't care about, so you don't back that up, right? And it all starts with that visibility that you give. And the prefix level data protection then comes the scale, which is where I was telling you, right? We have basically built an orchestration engine, right? It's like we call the ES for Lambdas, right? So we have a internal orchestration engine and essentially what what we have done is we have our own language internally that spawns off these lambdas, right? And they go after these S3 partitions do the right things and then you basically reel them back. So things like that that we do that are not possible if you're not built on the >>Clock. Well also, I mean, just mind blowing and go back 10 years. Yeah. I mean you got Lambda. What you're talking about here is the gift of the cloud innovation. Yeah. So the benefit of S3 is now accelerated. This is the story this year. Yeah. I mean they're highlighting it at scale, not just in the data, but like what we knew when Lambda came out and what S3 could do. But now mainstream solutions are coming in. Does that change your backup plans? Because we're gonna see a lot more end to end, lot more solutions. We heard that on the keynote. Some are saying it's more complexity. Of course it might, but you can abstract another way with the cloud that's the best part of the cloud. So these abstraction leads. So what's your view on that? But I wanna get your thoughts because you guys are perfectly positioned for this scale, but there's more coming. Yes. Yes. Exactly. What, how are you looking at that? >>So again, I think the, you know, obviously the, the S3 teams and every team in AWS is basically pushing the envelope in terms of innovation. But the key for a partner like us is to go and take that innovation. A lot of complex architectures behind the scene. But what you deliver to the customer is simple. I'll give you one more example. One of the things we launched that, you know, Paul and others are very excited about, is this ability to do instant access on the backup, right? So you could have billions of objects that you backed up. Maybe you need just 10,000 of them for a DR test. And we can basically create like an instant virtual bucket on top of that backup that you can instantly restore >>Spinning up a sandbox of temporary data to go check it >>Out. Exactly. Offer an inte application. >>Think we're geeking out right now. >>Yeah, I know. Brought that part of the segment, John. Don't worry, we're safely there. But, >>But that's the thing, right? That all that is possible because of all the, the scale and innovation and all the APIs and everything that, you know, Paul and the team gives us that we go and build on top of >>Paul, geek out on with us on this. We >>Are super excited for instant restore >>For store. I mean, automation programmability. >>It is, I mean it's the logical next step for backup in the cloud. Exactly. Yeah. But it's a super hard engineering problem to go solve for customers. I mean, the RTO benefits alone are super compelling, but then there's a cost element as well of not having to bring back all that stuff for a test restore, for example. And so it's, it's been really great to, to work with the team on that. We have some ideas on how we may help solve it from our side, and we're looking forward to collaborating on it. >>This is a great illustration of what I was writing about this week around the classic cloud, which is great. And as Adam said, and used like to use the word and, and you got this new functionality we're seeing emerge from the growth. Yes. From the companies that are built on Amazon web services that are growing. You're a partner, they have a lot of other partners and people are taking over restaurant here off action. I mean, there's real growth and new functionality on top of aws. You guys are no different. What's, are you prepared for that? Are you ready to go? >>Yeah, no, absolutely. And I think if you think about, if you think about it, right, I think it's also about doing this without impacting the primary application. Like if the customer is running a primary application at scale on s3, a backup application like ours can't come in and really mess with that. So I think being able to do things where, and this is where you solve really hard computer science problems, right? Where you're bottling yourself. If you are essentially seeing any kind of, you know, interfering with the primary, you're going to cut yourself down. You're gonna go after a different partition. So there are a lot of things you need to do behind the scenes, which is again, all the complexity, all of that, but deliver the, to the customer a very, very simple thing. >>You know, Paul, I wanna get your thoughts and I want you to chime in. Yeah. In 2014, I interviewed Steven Schmidt, my first interview with the, he was the CISO then, and now he's a CSO and, and former ciso, he's back at that time, the word was the cloud's not secure. Now we're talking about security. Just in the complexity of how you're partitioning and managing your sub portions, how you explained it, it's harder for the attackers. The cloud in its in its architecture has become a more secure environment. Yeah. Well, and getting more secure as you have laying out this, this is a new dynamic. This is good. Can you explain the, >>I mean, I, I can just tell you that at AWS security is job zero and that it will always be our number one priority, right? We have a, an infrastructure with under AWS that is vetted and approved to run even top secret workloads, which benefits all customers in all regions. >>And your, your security posture is embedded on top of that. And you got your own stuff. >>Yeah. And if you think of it as a shared responsibility model, so security of the cloud is the responsibility of the cloud provider, but then security of the data on top of it. Like you, you go and delete stuff, your software goes and does something that resiliency, the integrity of the data is your responsibility as a customer. And that's where, you know, we come in. Who >>Shared responsibility has been such a hot topic all week. Yeah. >>I gotta ask him one more question. Cause this is fascinating. And we are talking about on the cube all day today after we saw the announcement and Adam's comment on the cube, Adams LE's comment on the keynote. I mean, he said, if you're gonna tighten your belt, meaning economic cost recovery, re right sizing. If you want to tighten your belt, come to the cloud. So I have to ask you guys, Puja, if you can comment, that'd be great. There's a lot of other competitors out there that aren't born on aws. What is the customer gonna do when they tighten the build? What does that mean? They're gonna go to, to the individual contracts. They're gonna work in the marketplace. I mean this, there's a new dynamic in town. It's called AWS 2022. They weren't really around much in the recession of 2008. They were just starting to grow. Now they're an economic force. People like yourselves have embedded in there. There's a lot of competition. What's gonna happen? >>I think people are gonna just go to a place like, you know, AWS marketplace. You're going to essentially look for solutions and essentially like, and, and the right solutions built in are going to be self-service like aws. It's a very self-service thing. A hundred percent. So you go and do self-service, you figure out what's working, what's not working. Also, the model has to be consumption oriented. No longer can you expect the customer to go and pay a bunch of money for shelfware, right? It's like, like how we charge how AWS charges, which is you pay for what you consume. That and all has to be front and center, >>Right? I think that's a really, I think that's a really important >>Point. It's time >>And I think it's time. So we have a new challenge on the cube. We give you 30 seconds roughly to give us your extraordinarily hot take your shining thought leadership moment and, and highlight what you think is the most important takeaway from the show. The biggest soundbite, the juiciest announcement. Paul, I'll >>Start with an Instagram. Real basically. Yeah. Okay. >>Yeah. Hi. Go. I would just say from an S3 perspective, over the course of the last several years, we've really seen workloads shift from just backup and recovery and static images on websites to data lake analytics applications. And you continue to see that here. And I can tell you that some of these scaled applications are running at enormous mind blowing scale, right? And so, so every year we come here, we talk to customers, and it's just every year it sort of blows me away. And I've been in the storage industry for a long time and it's just is, it blows me away. Just the scale at customers are running in >>And >>Blowing scale. And when it comes to backup, let me just say that it's easy to back up and recover a single object, but doing an easy thing, a billion or 10 billion times over, that's actually quite hard. >>And just to, just to bold that a little bit, just pull out my highlighter. S3 now has over 280 trillion objects. That's a lot. >>That's a lot of objects. >>Yeah. You are not, you are not kidding. When you talk about scale, I mean, this is the most scalable. >>That's not solution's not there. Yeah. That, that's right. And we wake up every, we have a culture of durability and we wake up every single day to raise the bar on the fundamentals and make sure that every single one of those objects is protected and safe. >>Okay. You, I, >>I can't imagine worrying about two, two 80 trillion different things. >>Let's go. You're Instagram real >>For me again, you know, between S3 and us, we are two players out there that are really, you know, processing the data at the end of the day, right? And so I'm very excited about, you know, what we are going to do more and more with the instant restore capability where we can integrate third party services on top of it that can do more things with the data that is not, not passively sitting, but now becomes active data that you can analyze and do things with. So that's something where we take this to the next level is something that I'm super excited about. >>There's a lot to be excited about and, and we're excited to have you. We're excited to hear what happens next. Excited to see more collaboration like this. Paul Pon, thank you so much for joining us here on the show. Thank all of you from for tuning into our continuous wall to wall super thrilling live coverage of AWS reinvent here in fabulous Las Vegas, Nevada, with John Furrier. I'm Savannah Peterson. We're the cube, the leading source for high tech coverage.

>>Good morning fellow nerds and welcome back to AWS Reinvent. We are live from the show floor here in Las Vegas, Nevada. My name is Savannah Peterson, joined with my fabulous co-host John Furrier. Day two keynotes are rolling. >>Yeah. What do you thinking this? This is the day where everything comes, so the core gets popped off the bottle, all the announcements start flowing out tomorrow. You hear machine learning from swee lot more in depth around AI probably. And then developers with Verner Vos, the CTO who wrote the seminal paper in in early two thousands around web service that becames. So again, just another great year of next level cloud. Big discussion of data in the keynote bulk of the time was talking about data and business intelligence, business transformation easier. Is that what people want? They want the easy button and we're gonna talk a lot about that in this segment. I'm really looking forward to this interview. >>Easy button. We all want the >>Easy, we want the easy button. >>I love that you brought up champagne. It really feels like a champagne moment for the AWS community as a whole. Being here on the floor feels a bit like the before times. I don't want to jinx it. Our next guest, Scott Castle, from Si Sense. Thank you so much for joining us. How are you feeling? How's the show for you going so far? Oh, >>This is exciting. It's really great to see the changes that are coming in aws. It's great to see the, the excitement and the activity around how we can do so much more with data, with compute, with visualization, with reporting. It's fun. >>It is very fun. I just got a note. I think you have the coolest last name of anyone we've had on the show so far, castle. Oh, thank you. I'm here for it. I'm sure no one's ever said that before, but I'm so just in case our audience isn't familiar, tell us about >>Soy Sense is an embedded analytics platform. So we're used to take the queries and the analysis that you can power off of Aurora and Redshift and everything else and bring it to the end user in the applications they already know how to use. So it's all about embedding insights into tools. >>Embedded has been a, a real theme. Nobody wants to, it's I, I keep using the analogy of multiple tabs. Nobody wants to have to leave where they are. They want it all to come in there. Yep. Now this space is older than I think everyone at this table bis been around since 1958. Yep. How do you see Siente playing a role in the evolution there of we're in a different generation of analytics? >>Yeah, I mean, BI started, as you said, 58 with Peter Lu's paper that he wrote for IBM kind of get became popular in the late eighties and early nineties. And that was Gen one bi, that was Cognos and Business Objects and Lotus 1 23 think like green and black screen days. And the way things worked back then is if you ran a business and you wanted to get insights about that business, you went to it with a big check in your hand and said, Hey, can I have a report? And they'd come back and here's a report. And it wasn't quite right. You'd go back and cycle, cycle, cycle and eventually you'd get something. And it wasn't great. It wasn't all that accurate, but it's what we had. And then that whole thing changed in about two, 2004 when self-service BI became a thing. And the whole idea was instead of going to it with a big check in your hand, how about you make your own charts? >>And that was totally transformative. Everybody started doing this and it was great. And it was all built on semantic modeling and having very fast databases and data warehouses. Here's the problem, the tools to get to those insights needed to serve both business users like you and me and also power users who could do a lot more complex analysis and transformation. And as the tools got more complicated, the barrier to entry for everyday users got higher and higher and higher to the point where now you look, look at Gartner and Forester and IDC this year. They're all reporting in the same statistic. Between 10 and 20% of knowledge workers have learned business intelligence and everybody else is just waiting in line for a data analyst or a BI analyst to get a report for them. And that's why the focus on embedded is suddenly showing up so strong because little startups have been putting analytics into their products. People are seeing, oh my, this doesn't have to be hard. It can be easy, it can be intuitive, it can be native. Well why don't I have that for my whole business? So suddenly there's a lot of focus on how do we embed analytics seamlessly? How do we embed the investments people make in machine learning in data science? How do we bring those back to the users who can actually operationalize that? Yeah. And that's what Tysons does. Yeah. >>Yeah. It's interesting. Savannah, you know, data processing used to be what the IT department used to be called back in the day data processing. Now data processing is what everyone wants to do. There's a ton of data we got, we saw the keynote this morning at Adam Lesky. There was almost a standing of vision, big applause for his announcement around ML powered forecasting with Quick Site Cube. My point is people want automation. They want to have this embedded semantic layer in where they are not having all the process of ETL or all the muck that goes on with aligning the data. All this like a lot of stuff that goes on. How do you make it easier? >>Well, to be honest, I, I would argue that they don't want that. I think they, they think they want that, cuz that feels easier. But what users actually want is they want the insight, right? When they are about to make a decision. If you have a, you have an ML powered forecast, Andy Sense has had that built in for years, now you have an ML powered forecast. You don't need it two weeks before or a week after in a report somewhere. You need it when you're about to decide do I hire more salespeople or do I put a hundred grand into a marketing program? It's putting that insight at the point of decision that's important. And you don't wanna be waiting to dig through a lot of infrastructure to find it. You just want it when you need it. What's >>The alternative from a time standpoint? So real time insight, which is what you're saying. Yep. What's the alternative? If they don't have that, what's >>The alternative? Is what we are currently seeing in the market. You hire a bunch of BI analysts and data analysts to do the work for you and you hire enough that your business users can ask questions and get answers in a timely fashion. And by the way, if you're paying attention, there's not enough data analysts in the whole world to do that. Good luck. I am >>Time to get it. I really empathize with when I, I used to work for a 3D printing startup and I can, I have just, I mean, I would call it PTSD flashbacks of standing behind our BI guy with my list of queries and things that I wanted to learn more about our e-commerce platform in our, in our marketplace and community. And it would take weeks and I mean this was only in 2012. We're not talking 1958 here. We're talking, we're talking, well, a decade in, in startup years is, is a hundred years in the rest of the world life. But I think it's really interesting. So talk to us a little bit about infused and composable analytics. Sure. And how does this relate to embedded? Yeah. >>So embedded analytics for a long time was I want to take a dashboard I built in a BI environment. I wanna lift it and shift it into some other application so it's close to the user and that is the right direction to go. But going back to that statistic about how, hey, 10 to 20% of users know how to do something with that dashboard. Well how do you reach the rest of users? Yeah. When you think about breaking that up and making it more personalized so that instead of getting a dashboard embedded in a tool, you get individual insights, you get data visualizations, you get controls, maybe it's not even actually a visualization at all. Maybe it's just a query result that influences the ordering of a list. So like if you're a csm, you have a list of accounts in your book of business, you wanna rank those by who's priorities the most likely to churn. >>Yeah. You get that. How do you get that most likely to churn? You get it from your BI system. So how, but then the question is, how do I insert that back into the application that CSM is using? So that's what we talk about when we talk about Infusion. And SI started the infusion term about two years ago and now it's being used everywhere. We see it in marketing from Click and Tableau and from Looker just recently did a whole launch on infusion. The idea is you break this up into very small digestible pieces. You put those pieces into user experiences where they're relevant and when you need them. And to do that, you need a set of APIs, SDKs, to program it. But you also need a lot of very solid building blocks so that you're not building this from scratch, you're, you're assembling it from big pieces. >>And so what we do aty sense is we've got machine learning built in. We have an LQ built in. We have a whole bunch of AI powered features, including a knowledge graph that helps users find what else they need to know. And we, we provide those to our customers as building blocks so that they can put those into their own products, make them look and feel native and get that experience. In fact, one of the things that was most interesting this last couple of couple of quarters is that we built a technology demo. We integrated SI sensee with Office 365 with Google apps for business with Slack and MS teams. We literally just threw an Nlq box into Excel and now users can go in and say, Hey, which of my sales people in the northwest region are on track to meet their quota? And they just get the table back in Excel. They can build charts of it and PowerPoint. And then when they go to their q do their QBR next week or week after that, they just hit refresh to get live data. It makes it so much more digestible. And that's the whole point of infusion. It's bigger than just, yeah. The iframe based embedding or the JavaScript embedding we used to talk about four or five years >>Ago. APIs are very key. You brought that up. That's gonna be more of the integration piece. How does embedable and composable work as more people start getting on board? It's kind of like a Yeah. A flywheel. Yes. What, how do you guys see that progression? Cause everyone's copying you. We see that, but this is a, this means it's standard. People want this. Yeah. What's next? What's the, what's that next flywheel benefit that you guys coming out with >>Composability, fundamentally, if you read the Gartner analysis, right, they, when they talk about composable, they're talking about building pre-built analytics pieces in different business units for, for different purposes. And being able to plug those together. Think of like containers and services that can, that can talk to each other. You have a composition platform that can pull it into a presentation layer. Well, the presentation layer is where I focus. And so the, so for us, composable means I'm gonna have formulas and queries and widgets and charts and everything else that my, that my end users are gonna wanna say almost minority report style. If I'm not dating myself with that, I can put this card here, I can put that chart here. I can set these filters here and I get my own personalized view. But based on all the investments my organization's made in data and governance and quality so that all that infrastructure is supporting me without me worrying much about it. >>Well that's productivity on the user side. Talk about the software angle development. Yeah. Is your low code, no code? Is there coding involved? APIs are certainly the connective tissue. What's the impact to Yeah, the >>Developer. Oh. So if you were working on a traditional legacy BI platform, it's virtually impossible because this is an architectural thing that you have to be able to do. Every single tool that can make a chart has an API to embed that chart somewhere. But that's not the point. You need the life cycle automation to create models, to modify models, to create new dashboards and charts and queries on the fly. And be able to manage the whole life cycle of that. So that in your composable application, when you say, well I want chart and I want it to go here and I want it to do this and I want it to be filtered this way you can interact with the underlying platform. And most importantly, when you want to use big pieces like, Hey, I wanna forecast revenue for the next six months. You don't want it popping down into Python and writing that yourself. >>You wanna be able to say, okay, here's my forecasting algorithm. Here are the inputs, here's the dimensions, and then go and just put it somewhere for me. And so that's what you get withy sense. And there aren't any other analytics platforms that were built to do that. We were built that way because of our architecture. We're an API first product. But more importantly, most of the legacy BI tools are legacy. They're coming from that desktop single user, self-service, BI environment. And it's a small use case for them to go embedding. And so composable is kind of out of reach without a complete rebuild. Right? But with SI senses, because our bread and butter has always been embedding, it's all architected to be API first. It's integrated for software developers with gi, but it also has all those low code and no code capabilities for business users to do the minority report style thing. And it's assemble endless components into a workable digital workspace application. >>Talk about the strategy with aws. You're here at the ecosystem, you're in the ecosystem, you're leading product and they have a strategy. We know their strategy, they have some stuff, but then the ecosystem goes faster and ends up making a better product in most of the cases. If you compare, I know they'll take me to school on that, but I, that's pretty much what we report on. Mongo's doing a great job. They have databases. So you kind of see this balance. How are you guys playing in the ecosystem? What's the, what's the feedback? What's it like? What's going on? >>AWS is actually really our best partner. And the reason why is because AWS has been clear for many, many years. They build componentry, they build services, they build infrastructure, they build Redshift, they build all these different things, but they need, they need vendors to pull it all together into something usable. And fundamentally, that's what Cient does. I mean, we didn't invent sequel, right? We didn't invent jackal or dle. These are not, these are underlying analytics technologies, but we're taking the bricks out of the briefcase. We're assembling it into something that users can actually deploy for their use cases. And so for us, AWS is perfect because they focus on the hard bits. The the underlying technologies we assemble those make them usable for customers. And we get the distribution. And of course AWS loves that. Cause it drives more compute and it drives more, more consumption. >>How much do they pay you to say that >>Keynote, >>That was a wonderful pitch. That's >>Absolutely, we always say, hey, they got a lot of, they got a lot of great goodness in the cloud, but they're not always the best at the solutions and that they're trying to bring out, and you guys are making these solutions for customers. Yeah. That resonates with what they got with Amazon. For >>Example, we, last year we did a, a technology demo with Comprehend where we put comprehend inside of a semantic model and we would compile it and then send it back to Redshift. And it takes comprehend, which is a very cool service, but you kind of gotta be a coder to use it. >>I've been hear a lot of hype about the semantic layer. What is, what is going on with that >>Semantec layer is what connects the actual data, the tables in your database with how they're connected and what they mean so that a user like you or me who's saying I wanna bar chart with revenue over time can just work with revenue and time. And the semantic layer translates between what we did and what the database knows >>About. So it speaks English and then they converts it to data language. It's >>Exactly >>Right. >>Yeah. It's facilitating the exchange of information. And, and I love this. So I like that you actually talked about it in the beginning, the knowledge map and helping people figure out what they might not know. Yeah. I, I am not a bi analyst by trade and I, I don't always know what's possible to know. Yeah. And I think it's really great that you're doing that education piece. I'm sure, especially working with AWS companies, depending on their scale, that's gotta be a big part of it. How much is the community play a role in your product development? >>It's huge because I'll tell you, one of the challenges in embedding is someone who sees an amazing experience in outreach or in seismic. And to say, I want that. And I want it to be exactly the way my product is built, but I don't wanna learn a lot. And so you, what you want do is you want to have a community of people who have already built things who can help lead the way. And our community, we launched a new version of the SES community in early 2022 and we've seen a 450% growth in the c in that community. And we've gone from an average of one response, >>450%. I just wanna put a little exclamation point on that. Yeah, yeah. That's awesome. We, >>We've tripled our organic activity. So now if you post this Tysons community, it used to be, you'd get one response maybe from us, maybe from from a customer. Now it's up to three. And it's continuing to trend up. So we're, it's >>Amazing how much people are willing to help each other. If you just get in the platform, >>Do it. It's great. I mean, business is so >>Competitive. I think it's time for the, it's time. I think it's time. Instagram challenge. The reels on John. So we have a new thing. We're gonna run by you. Okay. We just call it the bumper sticker for reinvent. Instead of calling it the Instagram reels. If we're gonna do an Instagram reel for 30 seconds, what would be your take on what's going on this year at Reinvent? What you guys are doing? What's the most important story that you would share with folks on Instagram? >>You know, I think it's really what, what's been interesting to me is the, the story with Redshift composable, sorry. No, composable, Redshift Serverless. Yeah. One of the things I've been >>Seeing, we know you're thinking about composable a lot. Yes. Right? It's, it's just, it's in there, it's in your mouth. Yeah. >>So the fact that Redshift Serverless is now kind becoming the defacto standard, it changes something for, for my customers. Cuz one of the challenges with Redshift that I've seen in, in production is if as people use it more, you gotta get more boxes. You have to manage that. The fact that serverless is now available, it's, it's the default means it now people are just seeing Redshift as a very fast, very responsive repository. And that plays right into the story I'm telling cuz I'm telling them it's not that hard to put some analysis on top of things. So for me it's, it's a, maybe it's a narrow Instagram reel, but it's an >>Important one. Yeah. And that makes it better for you because you get to embed that. Yeah. And you get access to better data. Faster data. Yeah. Higher quality, relevant, updated. >>Yep. Awesome. As it goes into that 80% of knowledge workers, they have a consumer great expectation of experience. They're expecting that five ms response time. They're not waiting 2, 3, 4, 5, 10 seconds. They're not trained on theola expectations. And so it's, it matters a lot. >>Final question for you. Five years out from now, if things progress the way they're going with more innovation around data, this front end being very usable, semantic layer kicks in, you got the Lambda and you got serverless kind of coming in, helping out along the way. What's the experience gonna look like for a user? What's it in your mind's eye? What's that user look like? What's their experience? >>I, I think it shifts almost every role in a business towards being a quantitative one. Talking about, Hey, this is what I saw. This is my hypothesis and this is what came out of it. So here's what we should do next. I, I'm really excited to see that sort of scientific method move into more functions in the business. Cuz for decades it's been the domain of a few people like me doing strategy, but now I'm seeing it in CSMs, in support people and sales engineers and line engineers. That's gonna be a big shift. Awesome. >>Thank >>You Scott. Thank you so much. This has been a fantastic session. We wish you the best at si sense. John, always pleasure to share the, the stage with you. Thank you to everybody who's attuning in, tell us your thoughts. We're always eager to hear what, what features have got you most excited. And as you know, we will be live here from Las Vegas at reinvent from the show floor 10 to six all week except for Friday. We'll give you Friday off with John Furrier. My name's Savannah Peterson. We're the cube, the the, the leader in high tech coverage.

>>Hello, everyone. Welcome to the AWS startup showcase. This is season two, episode four, the ongoing series covering exciting startups from the AWS ecosystem to talk about cybersecurity. I'm your host, John furrier. And today I'm excited for this keynote presentation and I'm joined by John Ramsey, vice president of AWS security, John, welcome to the cubes coverage of the startup community within AWS. And thanks for this keynote presentation, >>Happy to be here. >>So, John, what do you guys, what do you do at AWS? Take, take minutes to explain your role, cuz it's very comprehensive. We saw at AWS reinforce event recently in Boston, a broad coverage of topics from Steven Schmid CJ, a variety of the executives. What's your role in particular at AWS? >>If you look at AWS, there are, there is a shared security responsibility model and CJ, the C the CSO for AWS is responsible for securing the AWS portion of the shared security responsibility model. Our customers are responsible for securing their part of the shared security responsible, responsible model. For me, I provide services to those customers to help them secure their part of that model. And those services come in different different categories. The first category is threat detection with guard. We that does real time detection and alerting and detective is then used to investigate those alerts to determine if there is an incident vulnerability management, which is inspector, which looks for third party vulnerabilities and security hub, which looks for configuration vulnerabilities and then Macy, which does sensitive data discovery. So I have those sets of services underneath me to help provide, to help customers secure their part of their shared security responsibility model. >>Okay, well, thanks for the call out there. I want to get that out there because I think it's important to note that, you know, everyone talks inside out, outside in customer focus. 80 of us has always been customer focused. We've been covering you guys for a long time, but you do have to secure the core cloud that you provide and you got great infrastructure tools technology down to the, down to the chip level. So that's cool. You're on the customer side. And right now we're seeing from these startups that are serving them. We had interviewed here at the showcase. There's a huge security transformation going on within the security market. It's the plane at 35,000 feet. That's engines being pulled out and rechange, as they say, this is huge. And, and what, what's it take for your, at customers with the enterprises out there that are trying to be more cyber resilient from threats, but also at the same time, protect what they also got. They can't just do a wholesale change overnight. They gotta be, you know, reactive, but proactive. How does it, what, what do they need to do to be resilient? That's the >>Question? Yeah. So, so I, I think it's important to focus on spending your resources. Everyone has constrained security resources and you have to focus those resources in the areas and the ways that reduce the greatest amount of risk. So risk really can be summed up is assets that I have that are most valuable that have a vulnerability that a threat is going to attack in that world. Then you wanna mitigate the threat or mitigate the vulnerability to protect the asset. If you have an asset that's vulnerable, but a threat isn't going to attack, that's less risky, but that changes over time. The threat and vulnerability windows are continuously evolving as threats, developing trade craft as vulnerabilities are being discovered as new software is being released. So it's a continuous picture and it's an adaptive picture where you have to continuously monitor what's happening. You, if you like use the N framework cybersecurity framework, you identify what you have to protect. >>That's the asset parts. Then you have to protect it. That's putting controls in place so that you don't have an incident. Then you from a threat perspective, then you ha to de detect an incident or, or a breach or a, a compromise. And then you respond and then you remediate and you have to continuously do that cycle to be in a position to, to de to have cyber resiliency. And one of the powers of the cloud is if you're building your applications in a cloud native form, you, your ability to respond can be very surgical, which is very important because then you don't introduce risk when you're responding. And by design, the cloud was, is, is architected to be more resilient. So being able to stay cyber resilient in a cloud native architecture is, is important characteristic. >>Yeah. And I think that's, I mean, it sounds so easy. Just identify what's to be protected. You monitor it. You're protected. You remediate sounds easy, but there's a lot of change going on and you got the cloud scale. And so you got security, you got cloud, you guys's a lot of things going on there. How do you think about security and how does the cloud help customers? Because again, there's two things going on. There's a shared responsibility model. And at the end of the day, the customer's responsible on their side. That's right, right. So that's right. Cloud has some tools. How, how do you think about going about security and, and where cloud helps specifically? >>Yeah, so really it's about there, there's a model called observe, orient, decide an actor, the ULO and it was created by John Boyd. He was a fighter pilot in the Korean war. And he knew that if I could observe what the opponent is doing, orient myself to my goals and their goals, make a decision on what the next best action is, and then act, and then follow that UTI loop, or, or also said a sense sense, making, deciding, and acting. If I can do that faster than the, than the enemy, then I can, I will win every fight. So in the cyber world, being in a position where you are observing and that's where cloud can really help you, because you can interrogate the infrastructure, you can look at what's happening, you can build baselines from it. And then you can look at deviations from, from the norm. It's just one way to observe this orient yourself around. Does this represent something that increases risk? If it does, then what's the next best action that I need to take, make that decision and then act. And that's also where the cloud is really powerful, cuz there's this huge con control plane that lets you lets you enable or disable resources or reconfigure resources. And if you're in, in the, in the situation where you can continuously do that very, very rapidly, you can, you can outpace and out maneuver the adversary. >>Yeah. You know, I remember I interviewed Steven Schmidt in 2014 and at that time everybody was poo pooing. Oh man, the cloud is so unsecure. He made a statement to me and we wrote about this. The cloud is more secure and will be more secure because it can be complicated to the hacker, but also easy for the, for provisioning. So he kind of brought up this, this discussion around how cloud would be more secure turns out he's right. He was right now. People are saying, oh, the cloud's more secure than, than standalone. What's different John now than not even going back to 2014, just go back a few years. Cloud is helpful, is more interrogation. You mentioned, this is important. What's, what's changed in the cloud per se in AWS that enables customers and say third parties who are trying to comply and manage risk as well. So you have this shared back and forth. What's different in the cloud now than just a few years ago that that's helping security. >>Yeah. So if you look at the, the parts of the shared responsibility model, AWS is the further up the stack you go from just infrastructure to platforms, say containers up to serverless the, the, we are taking more of the responsibility of that, of that stack. And in the process, we are investing resources and capabilities. For example, guard duty takes an S audit feed for containers to be able to monitor what's happening from a container perspective. And then in server list, really the majority of what, what needs to be defended is, is part of our responsibility model. So that that's an important shift because in that world, we have a very large team in our world. We have a very large team who knows the infrastructure who knows the threat and who knows how to protect customers all the way up to the, to the, to the boundary. And so that, that's a really important consideration. When you think about how you design your design, your applications is you want the developers to focus on the business logic, the business value and let, but still, also the security of the code that they're writing, but let us take over the rest of it so that you don't have to worry about it. >>Great, good, good insight there. I want to get your thoughts too. On another trend here at the showcase, one of the things that's emerging besides the normal threat landscape and the compliance and whatnot is API protection. I mean APIs, that's what made the cloud great. Right? So, you know, and it's not going away, it's only gonna get better cuz we live in an interconnected digital world. So, you know, APIs are gonna be lingual Franko what they say here. Companies just can't sit back and expect third parties complying with cyber regulations and best practices. So how do security and organizations be proactive? Not just on API, it's just a, a signal in my mind of, of, of more connections. So you got shared responsibility, AWS, your customers and your customers, partners and customers of connection points. So we live in an interconnected world. How do security teams and organizations be proactive on the cyber risk management piece? >>Yeah. So when it comes to APIs, the, the thing you look for is the trust boundaries. Where are the trust boundaries in the system between the user and the, in the machine, the machine and another machine on the network, the API is a trust boundary. And it, it is a place where you need to facilitate some kind of some form of control because what you're, what could happen on the trust boundaries, it could be used to, to attack. Like I trust that someone's gonna give me something that is legitimate, but you don't know that that a actually is true. You should assume that the, the one side of the trust boundary is, is malicious and you have to validate it. And by default, make sure that you know, that what you're getting is actually trustworthy and, and valid. So think of an API is just a trust boundary and that whatever you're gonna receive at that boundary is not gonna be legitimate in that you need to validate, validate the contents of, of whatever you receive. >>You know, I was noticing online, I saw my land who runs S3 a us commenting about 10 years anniversary, 10, 10 year birthday of S3, Amazon simple storage service. A lot of the customers are using all their applications with S3 means it's file repository for their application, workflow ingesting literally thousands and trillions of objects from S3 today. You guys have about, I mean, trillions of objects on S3, this is big part of the application workflow. Data security has come up as a big discussion item. You got S3. I mean, forget about the misconfiguration about S3 buckets. That's kind of been reported on beyond that as application workflows, tap into S3 and data becomes the conversation around securing data. How do you talk to customers about that? Because that's also now part of the scaling of these modern cloud native applications, managing data on Preem cross in flight at rest in motion. What's your view on data security, John? >>Yeah. Data security is also a trust boundary. The thing that's going to access the data there, you have to validate it. The challenge with data security is, is customers don't really know where all their data is or even where their sensitive data is. And that continues to be a large problem. That's why we have services like Macy, which are whose job is to find in S3 the data that you need to protect the most because it's because it's sensitive. Getting the least privilege has always been the, the goal when it comes, when it comes to data security. The problem is, is least privilege is really, really hard to, to achieve because there's so many different common nations of roles and accounts and org orgs. And, and so there, there's also another technology called access analyzer that we have that helps customers figure out like this is this the right, if are my intended authorizations, the authorizations I have, are they the ones that are intended for that user? And you have to continuously review that as a, as a means to make sure that you're getting as close to least privilege as you possibly can. >>Well, one of the, the luxuries of having you here on the cube keynote for this showcase is that you also have the internal view at AWS, but also you have the external view with customers. So I have to ask you, as you talk to customers, obviously there's a lot of trends. We're seeing more managed services in areas where there's skill gaps, but teams are also overloaded too. We're hearing stories about security teams, overwhelmed by the solutions that they have to deploy quickly and scale up quickly cost effectively the need for in instrumentation. Sometimes it's intrusive. Sometimes it agentless sensors, OT. I mean, it's getting crazy at re Mars. We saw a bunch of stuff there. This is a reality, the teams aspect of it. Can you share your experiences and observations on how companies are organizing, how they're thinking about team formation, how they're thinking about all these new things coming at them, new environments, new scale choices. What, what do you seeing on, on the customer side relative to security team? Yeah. And their role and relationship to the cloud and, and the technologies. >>Yeah, yeah. A absolutely it. And we have to remember at the end of the day on one end of the wire is a black hat on the other end of the wire is a white hat. And so you need people and, and people are a critical component of being able to defend in the context of security operations alert. Fatigue is absolutely a problem. The, the alerts, the number of alerts, the volume of alerts is, is overwhelming. And so you have to have a means to effectively triage them and get the ones into investigation that, that you think will be the most, the, the most significant going back to the risk equation, you found, you find those alerts and events that are, are the ones that, that could harm you. The most. You'll also one common theme is threat hunting. And the concept behind threat hunting is, is I don't actually wait for an alert I lean in and I'm proactive instead of reactive. >>So I find the system that I at least want the hacker in. I go to that system and I look for any anomalies. I look for anything that might make me think that there is a, that there is a hacker there or a compromise or some unattended consequence. And the reason you do that is because it reduces your dwell time, time between you get compromised to the time detect something, which is you, which might be, you know, months, because there wasn't an alert trigger. So that that's also a very important aspect for, for AWS and our security services. We have a strategy across all of the security services that we call end to end, or how do we move from APIs? Because they're all API driven and security buyers generally not most do not ha have like a development team, like their security operators and they want a solution. And so we're moving more from APIs to outcomes. So how do we stitch all the services together in a way so that the time, the time that an analyst, the SOC analyst spends or someone doing investigation or someone doing incident response is the, is the most important time, most valuable time. And in the process of stitching this all together and helping our customers with alert, fatigue, we'll be doing things that will use sort of inference and machine learning to help prioritize the greatest risk for our customers. >>That's a great, that's a great call out. And that brings up the point of you get the frontline, so to speak and back office, front office kind of approach here. The threats are out there. There's a lot of leaning in, which is a great point. I think that's a good, good comment and insight there. The question I have for you is that everyone's kind of always talks about that, but there's the, the, I won't say boring, the important compliance aspect of things, you know, this has become huge, right? So there's a lot of blocking and tackling that's needed behind the scenes on the compliance side, as well as prevention, right? So can you take us through in your mind how customers are looking at the best strategies for compliance and security, because there's a lot of work you gotta get done and you gotta lay out everything as you mentioned, but compliance specifically to report is also a big thing for >>This. Yeah. Yeah. Compliance is interesting. I suggest taking a security approach to compliance instead of a compliance approach to security. If you're compliant, you may not be secure, but if you're secure, you'll be compliant. And the, the really interesting thing about compliance also is that as soon as something like a, a, a category of control is required in, in some form of compliance, compliance regime, the effectiveness of that control is reduced because the threats go well, I'm gonna presume that they have this control. I'm gonna presume cuz they're compliant. And so now I'm gonna change my tactic to evade the control. So if you only are ever following compliance, you're gonna miss a whole set of tactics that threats have developed because they presume you're compliant and you have those controls in place. So you wanna make sure you have something that's outside of the outside of the realm of compliance, because that's the thing that will trip them up. That's the thing that they're not expecting that threats not expecting and that that's what we'll be able to detect them. >>Yeah. And it almost becomes one of those things where it's his fault, right? So, you know, finger pointing with compliance, you get complacent. I can see that. Can you give an example? Cause I think that's probably something that people are really gonna want to know more about because it's common sense. But can you give an example of security driving compliance? Is there >>Yeah, sure. So there's there they're used just as an example, like multifactor authentication was used everywhere that for, for banks in high risk transactions, in real high risk transactions. And then that like that was a security approach to compliance. Like we said, that's a, that's a high net worth individual. We're gonna give them a token and that's how they're gonna authenticate. And there was no, no, the F F I C didn't say at the time that there needed to be multifactor authentication. And then after a period of time, when account takeover was, was on the rise, the F F I C the federally financial Institute examiner's council, something like that said, we, you need to do multifactor authentication. Multifactor authentication was now on every account. And then the threat went down to, okay, well, we're gonna do man in the browser attacks after the user authenticates, which now is a new tactic in that tactic for those high net worth individuals that had multifactor didn't exist before became commonplace. Yeah. And so that, that, that's a, that's an example of sort of the full life cycle and the important lesson there is that security controls. They have a diminishing halflife of effectiveness. They, they need to be continuous and adaptive or else the value of them is gonna decrease over time. >>Yeah. And I think that's a great call up because agility and speed is a big factor when he's merging threats. It's not a stable, mature hacker market. They're evolving too. All right. Great stuff. I know your time's very valuable, John. I really appreciate you coming on the queue. A couple more questions for you. We have 10 amazing startups here in the, a AWS ecosystem, all private looking grade performance wise, they're all got the kind of the same vibe of they're kind of on something new. They're doing something new and clever and different than what was, what was kind of done 10 years ago. And this is where the cloud advantage is coming in cloud scale. You mentioned that some of those things, data, so you start to see new things emerge. How, how would you talk to CSOs or CXOs that are watching about how to evaluate startups like these they're, they're, they're somewhat, still small relative to some of the bigger players, but they've got unique solutions and they're doing things a little bit differently. How should some, how should CSOs and Steve evaluate them? How can startups work with the CSOs? What's your advice to both the buyer and the startup to, to bring their product to the market. And what's the best way to do that? >>Yeah. So the first thing is when you talk to a CSO, be respected, be respectful of their time like that. Like, they'll appreciate that. I remember when I was very, when I just just started, I went to talk to one of the CISOs as one of the five major banks and he sat me down and he said, and I tried to tell him what I had. And he was like son. And he went through his book and he had, he had 10 of every, one thing that I had. And I realized that, and I, I was grateful for him giving me an explanation. And I said to him, I said, look, I'm sorry. I wasted your time. I will not do that again. I apologize. I, if I can't bring any value, I won't come back. But if I think I can bring you something of value now that I know what I know, please, will you take the meeting? >>He was like, of course. And so be respectful of their time. They know what the problem is. They know what the threat is. You be, be specific about how you're different right now. There is so much confusion in the market about what you do. Like if you're really have something that's differentiated, be very, very specific about it. And don't be afraid of it, like lean into it and explain the value to that. And that, that, that would, would save a, a lot of time and a lot and make the meeting more valuable for the CSO >>And the CISOs. Are they evaluate these startups? How should they look at them? What are some kind of markers that you would say would be good, kind of things to look for size of the team reviews technology, or is it doesn't matter? It's more of a everyone's environment's different. What >>Would your, yeah. And, you know, for me, I, I always look first to the security value. Cause if there isn't security value, nothing else matters. So there's gotta be some security value. Then I tend to look at the management team, quite frankly, what are, what are the, what are their experiences and what, what do they know that that has led them to do something different that is driving security value. And then after that, for me, I tend to look to, is this someone that I can have a long term relationship with? Is this someone that I can, you know, if I have a problem and I call them, are they gonna, you know, do this? Or are they gonna say, yes, we're in, we're in this together, we'll figure it out. And then finally, if, if for AWS, you know, scale is important. So we like to look at, at scale in terms of, is this a solution that I can, that I can, that I can get to, to the scale that I needed at >>Awesome. Awesome. John Ramsey, vice president of security here on the cubes. Keynote. John, thank you for your time. I really appreciate, I know how busy you are with that for the next minute, or so share a little bit of what you're up to. What's on your plate. What are you thinking about as you go out to the marketplace, talk to customers what's on your agenda. What's your talk track, put a plug in for what you're up to. >>Yeah. So for, for the services I have, we, we are, we are absolutely moving. As I mentioned earlier, from APIs to outcomes, we're moving up the stack to be able to defend both containers, as well as, as serverless we're, we're moving out in terms of we wanna get visibility and signal, not just from what we see in AWS, but from other places to inform how do we defend AWS? And then also across, across the N cybersecurity framework in terms of we're doing a lot of, we, we have amazing detection capability and we have this infrastructure that we could respond, do like micro responses to be able to, to interdict the threat. And so me moving across the N cybersecurity framework from detection to respond. >>All right, thanks for your insight and your time sharing in this keynote. We've got great 10 great, amazing startups. Congratulations for all your success at AWS. You guys doing a great job, shared responsibility that the threats are out there. The landscape is changing. The scale's increasing more data tsunamis coming every day, more integration, more interconnected, it's getting more complex. So you guys are doing a lot of great work there. Thanks for your time. Really appreciate >>It. Thank you, John. >>Okay. This is the AWS startup showcase. Season two, episode four of the ongoing series covering the exciting startups coming out of the, a AWS ecosystem. This episode's about cyber security and I'm your host, John furrier. Thanks for watching.

>>Hi there. Welcome back to the cubes day. One coverage of VMware Explorer, 2022 from San Francisco, Lisa Martin and Dave Nicholson. Dave, we've been here all day, having some great conversations with the VMware partner ecosystem >>With real live people >>Within in 3d. Yeah. People actually sitting down next to us still >>Appreciated, even though, you know, we've, we've done a few of these events, but yeah, it feels like things are getting back to normal. >>It does. You and I were both in the keynote starting this morning, standing room only. We're hearing somewhere between 7,000 and 10,000 attendees. Yeah. We're in Moscoe west. So we're kind of away from a little bit of the, the main action. But talk to me about some of the things that you heard this morning in the keynote, some of the announcements from VMware, did it meet your expectations? >>Yes. And because I didn't expect, you know, this is very, very different than going to say an AWS event where they're going to launch 300 new shiny objects. This was very much in my mind so far about VMware focusing on its core value proposition and an aspect of its core value proposition that is the cloud stack and how they are shoring up places in that strategy that needed shoring up like addressing issues with licensing. So you don't have to have separate licensing for on premises, VMware things. You're doing separate licenses in hyperscale cloud providers for doing those very same things that looks like something that's going to roll out over time. That's very, very interesting. Something that wasn't really wasn't mentioned directly, but, but, but actually one of our guests mentioned it. It's this idea that if you take the VMware cloud provider partner, community VCP P is the inside term for it. >>There are thousands of VMware partners that deliver VMware cloud software on top of infrastructure, all around the globe. If you take that VCP P community as an entity, you can argue that it is the third or fourth largest cloud on earth. If you look at that as a core value proposition and you look at Broadcom, acquiring VMware, assuming everything goes through it, isn't just vSphere. That is exciting to Broadcom, or it shouldn't be at least because you have the entire cloud stack when you look at it from that perspective. And I think they were trying to get some of that across today. >>So they address the Broadcom acquisition obviously is the elephant in the room. It was right. Impossible. >>Well, well, they have OC 10 stand up in wave. OC >>Tanon stood up. Did, did a wave, just >>Crowd because he can't say anything. And you know, I've got European approval still pending, right. You know, all sorts of stuff. But >>What we are, what we heard today from, I'll say the partner ecosystem, we talked with NetApp, we talked with pure storage. We talked with Phoenix, snap, others. I I'd have to look through my notes. Everyone's actually quite positive. Yeah. On the acquisition and what it can mean for the future of VMware. Did you hear the same? >>Yes, absolutely. And I think partially that's because the partners that we talk to are really close to the core of VMware's value proposition. That's never going to go away. So if you're talking about NetApp and AWS partnering with VMware to deliver NetApp storage services into that environment, that's core VMware proposition, it's nowhere near the bleeding edge of what, of, what, of what VMware has been doing. So they're going to be bullish. The other thing that's interesting from some of the partners that we've talked to, if you had asked us five or 10 years ago, would those partners be successful today? We might have predicted that they'd all be gone, right? NetApp what's gonna happen. Well, all storage is going to cloud. Guess what NetApp's doing? Pretty darn well with its partner, with its cloud partnerships and card and, and cloud strategy, VMware old school virtualization on premises. Ah, what are they gonna do? I'll tell you. I was skeptical when pat Gelsinger first pursued the VMC strategy with AWS. Hey, it's worked out pretty well and now they have the same capabilities everywhere. So I think that it's, it's interesting to see how solidly positioned some traditional good old fashioned blue gene technologies are how well positioned they are in this era of cloud and how VMware is such a, such a core part of that. So of course they're happy. Yeah. >>Yeah. We talked, we had AWS, NetApp and VMware on, on set for a segment and talked about, and you and I were talking about that segment before it went live. Just the power of look what AWS is doing, how you know, how, how many years ago, 10 years ago would they have been, I'm not gonna partner with NetApp and VMware and now look, it's a core to their business unit. >>Yeah, no, they wouldn't have acknowledged it. They, in fact, there was a time when AWS thought that they could maintain their stratospheric rise at the level they needed to while just letting all legacy existing stuff, just sort of fade away, you know, they'll just do it on the backs of everything new. They ran headlong into something. We call stickiness specifically around the area. VMware, they found that application environments for a variety of really good reasons belong in this context. And it's hard to rip them out by the roots. It's, you know, AWS might have told you five or 10 years ago. Well, if people don't move to cloud immediately, it's because of one reason they're stupid. The reality is there are a lot of really good reasons to maintain that VMware context. They embrace that with VMC. And now I think the it's really interesting. The NetApp announcement is another indication that the world of hyperscale cloud sees VMware as something that is part of the future. That is a very, very long tail. That very, very long tail is clearly what Broadcom is interested in. They don't see this as a flash in the pan. Let's make revenue really quickly. This is about a long ti a long time of future long future >>Long future. Well, VMware's coming off solid quarter earnings that just announced speeding estimates growing the top line by up to 6%. So there's, there's momentum that they're bringing with them into this acquisition. >>Yeah, definitely momentum big argument over what the strategy might be moving forward in terms of growth versus efficiency. I think that virtualization that includes the traditional VM with a resident full blown OS is definitely something that is behind us, but that we're carrying forward for good reason. The transition in, from a VMware perspective into the world of Zu critically important, it's critically important that they get that right as they move forward. So that net new cloud native applications could be, can be created in the VMware context that way. So it's, it's really gonna be interesting to watch over the next couple of years, the direction that this goes, but, but it's easy to get immersed in the Kool-Aid when you're at an event like this, I try to be as skeptical as possible. And I'm actually feeling pretty, I'm feeling better about VMware's future than I did before I arrived today. So that's >>Interesting. Yeah. >>Yeah, no question about it. I think, I mean, there, there, there is such a large core that I think it's gonna take it into the future a long way. >>Well, they definitely have a lot of tailwind behind them. The, the one thing that I, that we didn't get to do today was talk to any customers. We will get to do that tomorrow. When I always love hearing from the voice of the customer, we heard voice of the customer stories from the vendors, from VMware, from NetApp, from >>Little skewed, eat a little skewed. Exactly. They're all happy. All the customers are happy >>They're and very >>Successful and very successful. >>But tomorrow we get to actually rack open and talk with some VMware customers, obviously, right. Customers in the ecosystem as well. And I want to hear from them what their thoughts are on the acquisition. Yeah. >>We know they're, they're not bringing their disgruntled customers. Right. You know, this is my, this is my ex-wife's my, my ex-mother-in-law. And she's here to tell you that she didn't have a good experience. Yeah, no, that's not >>Gonna happen. We're gonna hear good stories tomorrow, but it's always nice to, to hear the stories from the customers themselves. Yeah. I always like doing that. >>No, it's always, it is informative. It's all, it's interesting from the perspective that you, you hone in on what they care about, because even if they have sort of an idea of, of, of the message that they want to get across in terms of what they're doing, still build default to that core of what they really care about. And that's interesting because what the customers really care about is part of that core. And as VMware becomes part of Broadcom, potentially, it's gonna be all about those things that are important, that you know, that customers find important. >>And that's exactly what it should be about. You know, of course we, every conversation that we had today, probably every conversation was inclusive of customer outcomes. What outcomes are you helping businesses achieve regardless of industry, especially as we're hopefully coming out of the pandemic, still in a, in a dynamic, remote hybrid work environment, but it's all about enabling businesses to, to achieve their goals. So I always wanna understand from, from VMware's perspective or AWS or NetApp procure, what are the goals that your customers are coming to you with and who are you having those conversations with? We also heard today a number of probably almost everyone that during the pandemic, the conversations are going up the stack. And maybe they've been talking with the director of it. Now it's the VP of engineering. Maybe it's the CFO. Yep. We're seeing much more strategic initiatives and focus here as customers in every industry have to pivot and have gotta get to the cloud. >>Yeah. I think that's why we work together. Well, Lisa, because you have the virtual leash and you can yank me back from diving into the technical stuff because, because I just, I, I get a pit in my stomach when someone says, oh, technology doesn't matter. It's all about outcomes. Yeah, yeah, yeah. Okay. Try doing this on technology that doesn't work. Your outcomes are gonna suck both Arely but no, no, no, they are. I know. And, and, and, and it's important that we focus on those things cuz that's what customers really care about. They do, they really care about the business outcomes >>They do. And, and on the cube, we care about those as well. And we wanna get that message across. >>I wish they would care more about speeds and feeds though. It's super interesting. It's like horsepower and torque and it's all >>He does. He gets really excited about that. But the good thing is tomorrow we have more opportunities. Yes. Got a great guest line up tomorrow. Dave and I are gonna be talking to them from right here on this set. So we encourage you to come check in for day two of our coverage of VMware Explorer live from San Francisco. We hope you have a great rest of your day and we'll see you tomorrow.

(upbeat music) >> Hello, and welcome to "theCUBE" conversation here in Palo Alto, California. I'm John Furrier, host of "theCUBE," got a great security conversation, Ed Casper who's the founder and CEO of Cloud Storage Security, the great Cloud background, Cloud security, Cloud storage. Welcome to the "theCUBE Conversation," Ed. Thanks for coming on. >> Thank you very much for having me. >> I got Lafomo on that background. You got the nice look there. Let's get into the storage blind spot conversation around Cloud Security. Obviously, reinforced has came up a ton, you heard a lot about encryption, automated reasoning but still ransomware was still hot. All these things are continuing to be issues on security but they're all brought on data and storage, right? So this is a big part of it. Tell us a little bit about how you guys came about the origination story. What is the company all about? >> Sure, so, we're a pandemic story. We started in February right before the pandemic really hit and we've survived and thrived because it is such a critical thing. If you look at the growth that's happening in storage right now, we saw this at reinforced. We saw even a recent AWS Storage Day. Their S3, in particular, houses over 200 trillion objects. If you look just 10 years ago, in 2012, Amazon touted how they were housing one trillion objects, so in a 10 year period, it's grown to 200 trillion and really most of that has happened in the last three or four years, so the pandemic and the shift in the ability and the technologies to process data better has really driven the need and driven the Cloud growth. >> I want to get into some of the issues around storage. Obviously, the trend on S3, look at what they've done. I mean, I saw my land at storage today. We've interviewed her. She's amazing. Just the EC2 and S3 the core pistons of AWS, obviously, the silicons getting better, the IaaS layers just getting so much more innovation. You got more performance abstraction layers at the past is emerging Cloud operations on premise now with hybrid is becoming a steady state and if you look at all the action, it's all this hyper-converged kind of conversations but it's not hyper-converged in a box, it's Cloud Storage, so there's a lot of activity around storage in the Cloud. Why is that? >> Well, because it's that companies are defined by their data and, if a company's data is growing, the company itself is growing. If it's not growing, they are stagnant and in trouble, and so, what's been happening now and you see it with the move to Cloud especially over the on-prem storage sources is people are starting to put more data to work and they're figuring out how to get the value out of it. Recent analysts made a statement that if the Fortune 1000 could just share and expose 10% more of their data, they'd have net revenue increases of 65 million. So it's just the ability to put that data to work and it's so much more capable in the Cloud than it has been on-prem to this point. >> It's interesting data portability is being discussed, data access, who gets access, do you move compute to the data? Do you move data around? And all these conversations are kind of around access and security. It's one of the big vulnerabilities around data whether it's an S3 bucket that's an manual configuration error, or if it's a tool that needs credentials. I mean, how do you manage all this stuff? This is really where a rethink kind of comes around so, can you share how you guys are surviving and thriving in that kind of crazy world that we're in? >> Yeah, absolutely. So, data has been the critical piece and moving to the Cloud has really been this notion of how do I protect my access into the Cloud? How do I protect who's got it? How do I think about the networking aspects? My east west traffic after I've blocked them from coming in but no one's thinking about the data itself and ultimately, you want to make that data very safe for the consumers of the data. They have an expectation and almost a demand that the data that they consume is safe and so, companies are starting to have to think about that. They haven't thought about it. It has been a blind spot, you mentioned that before. In regards to, I am protecting my management plane, we use posture management tools. We use automated services. If you're not automating, then you're struggling in the Cloud. But when it comes to the data, everyone thinks, "Oh, I've blocked access. I've used firewalls. I've used policies on the data," but they don't think about the data itself. It is that packet that you talked about that moves around to all the different consumers and the workflows and if you're not ensuring that that data is safe, then, you're in big trouble and we've seen it over and over again. >> I mean, it's definitely a hot category and it's changing a lot, so I love this conversation because it's a primary one, primary and secondary cover data cotton storage. It's kind of good joke there, but all kidding aside, it's a hard, you got data lineage tracing is a big issue right now. We're seeing companies come out there and kind of superability tangent there. The focus on this is huge. I'm curious, what was the origination story? What got you into the business? Was it like, were you having a problem with this? Did you see an opportunity? What was the focus when the company was founded? >> It's definitely to solve the problems that customers are facing. What's been very interesting is that they're out there needing this. They're needing to ensure their data is safe. As the whole story goes, they're putting it to work more, we're seeing this. I thought it was a really interesting series, one of your last series about data as code and you saw all the different technologies that are processing and managing that data and companies are leveraging today but still, once that data is ready and it's consumed by someone, it's causing real havoc if it's not either protected from being exposed or safe to use and consume and so that's been the biggest thing. So we saw a niche. We started with this notion of Cloud Storage being object storage, and there was nothing there protecting that. Amazon has the notion of access and that is how they protect the data today but not the packets themselves, not the underlying data and so, we created the solution to say, "Okay, we're going to ensure that that data is clean. We're also going to ensure that you have awareness of what that data is, the types of files you have out in the Cloud, wherever they may be, especially as they drift outside of the normal platforms that you're used to seeing that data in. >> It's interesting that people were storing data lakes. Oh yeah, just store a womp we might need and then became a data swamp. That's kind of like go back 67 years ago. That was the conversation. Now, the conversation is I need data. It's got to be clean. It's got to feed the machine learning. This is going to be a critical aspect of the business model for the developers who are building the apps, hence, the data has code reference which we've focused on but then you say, "Okay, great. Does this increase our surface area for potential hackers?" So there's all kinds of things that kind of open up, we start doing cool, innovative, things like that so, what are some of the areas that you see that your tech solves around some of the blind spots or with object store, the things that people are overlooking? What are some of the core things that you guys are seeing that you're solving? >> So, it's a couple of things, right now, the still the biggest thing you see in the news is configuration issues where people are losing their data or accidentally opening up to rights. That's the worst case scenario. Reads are a bad thing too but if you open up rights and we saw this with a major API vendor in the last couple of years they accidentally opened rights to their buckets. Hackers found it immediately and put malicious code into their APIs that were then downloaded and consumed by many, many of their customers so, it is happening out there. So the notion of ensuring configuration is good and proper, ensuring that data has not been augmented inappropriately and that it is safe for consumption is where we started and, we created a lightweight, highly scalable solution. At this point, we've scanned billions of files for customers and petabytes of data and we're seeing that it's such a critical piece to that to make sure that that data's safe. The big thing and you brought this up as well is the big thing is they're getting data from so many different sources now. It's not just data that they generate. You see one centralized company taking in from numerous sources, consolidating it, creating new value on top of it, and then releasing that and the question is, do you trust those sources or not? And even if you do, they may not be safe. >> We had an event around super Clouds is a topic we brought up to get bring the attention to the complexity of hybrid which is on premise, which is essentially Cloud operations. And the successful people that are doing things in the software side are essentially abstracting up the benefits of the infrastructures of service from HN AWS, right, which is great. Then they innovate on top so they have to abstract that storage is a key component of where we see the innovations going. How do you see your tech that kind of connecting with that trend that's coming which is everyone wants infrastructures code. I mean, that's not new. I mean, that's the goal and it's getting better every day but DevOps, the developers are driving the operations and security teams to like stay pace, so policy seeing a lot of policy seeing some cool things going on that's abstracting up from say storage and compute but then those are being put to use as well, so you've got this new wave coming around the corner. What's your reaction to that? What's your vision on that? How do you see that evolving? >> I think it's great, actually. I think that the biggest problem that you have to do as someone who is helping them with that process is make sure you don't slow it down. So, just like Cloud at scale, you must automate, you must provide different mechanisms to fit into workflows that allow them to do it just how they want to do it and don't slow them down. Don't hold them back and so, we've come up with different measures to provide and pretty much a fit for any workflow that any customer has come so far with. We do data this way. I want you to plug in right here. Can you do that? And so it's really about being able to plug in where you need to be, and don't slow 'em down. That's what we found so far. >> Oh yeah, I mean that exactly, you don't want to solve complexity with more complexity. That's the killer problem right now so take me through the use case. Can you just walk me through how you guys engage with customers? How they consume your service? How they deploy it? You got some deployment scenarios. Can you talk about how you guys fit in and what's different about what you guys do? >> Sure, so, we're what we're seeing is and I'll go back to this data coming from numerous sources. We see different agencies, different enterprises taking data in and maybe their solution is intelligence on top of data, so they're taking these data sets in whether it's topographical information or whether it's in investing type information. Then they process that and they scan it and they distribute it out to others. So, we see that happening as a big common piece through data ingestion pipelines, that's where these folks are getting most of their data. The other is where is the data itself, the document or the document set, the actual critical piece that gets moved around and we see that in pharmaceutical studies, we see it in mortgage industry and FinTech and healthcare and so, anywhere that, let's just take a very simple example, I have to apply for insurance. I'm going to upload my Social Security information. I'm going to upload a driver's license, whatever it happens to be. I want to one know which of my information is personally identifiable, so I want to be able to classify that data but because you're trusting or because you're taking data from untrusted sources, then you have to consider whether or not it's safe for you to use as your own folks and then also for the downstream users as well. >> It's interesting, in the security world, we hear zero trust and then we hear supply chain, software supply chains. We get to trust everybody, so you got kind of two things going on. You got the hardware kind of like all the infrastructure guys saying, "Don't trust anything 'cause we have a zero trust model," but as you start getting into the software side, it's like trust is critical like containers and Cloud native services, trust is critical. You guys are kind of on that balance where you're saying, "Hey, I want data to come in. We're going to look at it. We're going to make sure it's clean." That's the value here. Is that what I'm hearing you, you're taking it and you're saying, "Okay, we'll ingest it and during the ingestion process, we'll classify it. We'll do some things to it with our tech and put it in a position to be used properly." Is that right? >> That's exactly right. That's a great summary, but ultimately, if you're taking data in, you want to ensure it's safe for everyone else to use and there are a few ways to do it. Safety doesn't just mean whether it's clean or not. Is there malicious content or not? It means that you have complete coverage and control and awareness over all of your data and so, I know where it came from. I know whether it's clean and I know what kind of data is inside of it and we don't see, we see that the interesting aspects are we see that the cleanliness factor is so critical in the workflow, but we see the classification expand outside of that because if your data drifts outside of what your standard workflow was, that's when you have concerns, why is PII information over here? And that's what you have to stay on top of, just like AWS is control plane. You have to manage it all. You have to make sure you know what services have all of a sudden been exposed publicly or not, or maybe something's been taken over or not and you control that. You have to do that with your data as well. >> So how do you guys fit into the security posture? Say it a large company that might want to implement this right away. Sounds like it's right in line with what developers want and what people want. It's easy to implement from what I see. It's about 10, 15, 20 minutes to get up and running. It's not hard. It's not a heavy lift to get in. How do you guys fit in once you get operationalized when you're successful? >> It's a lightweight, highly scalable serverless solution, it's built on Fargate containers and it goes in very easily and then, we offer either native integrations through S3 directly, or we offer APIs and the APIs are what a lot of our customers who want inline realtime scanning leverage and we also are looking at offering the actual proxy aspects. So those folks who use the S3 APIs that our native AWS, puts and gets. We can actually leverage our put and get as an endpoint and when they retrieve the file or place the file in, we'll scan it on access as well, so, it's not just a one time data arrest. It can be a data in motion as you're retrieving the information as well >> We were talking with our friends the other day and we're talking about companies like Datadog. This is the model people want, they want to come in and developers are driving a lot of the usage and operational practice so I have to ask you, this fits kind of right in there but also, you also have the corporate governance policy police that want to make sure that things are covered so, how do you balance that? Because that's an important part of this as well. >> Yeah, we're really flexible for the different ways they want to consume and and interact with it. But then also, that is such a critical piece. So many of our customers, we probably have a 50/50 breakdown of those inside the US versus those outside the US and so, you have those in California with their information protection act. You have GDPR in Europe and you have Asia having their own policies as well and the way we solve for that is we scan close to the data and we scan in the customer's account, so we don't require them to lose chain of custody and send data outside of the accoun. That is so critical to that aspect. And then we don't ask them to transfer it outside of the region, so, that's another critical piece is data residency has to be involved as part of that compliance conversation. >> How much does Cloud enable you to do this that you couldn't really do before? I mean, this really shows the advantage of natively being in the Cloud to kind of take advantage of the IaaS to SAS components to solve these problems. Share your thoughts on how this is possible. What if there was no problem, what would you do? >> It really makes it a piece of cake. As silly as that sounds, when we deploy our solution, we provide a management console for them that runs inside their own accounts. So again, no metadata or anything has to come out of it and it's all push button click and because the Cloud makes it scalable because Cloud offers infrastructure as code, we can take advantage of that and then, when they say go protect data in the Ireland region, they push a button, we stand up a stack right there in the Ireland region and scan and protect their data right there. If they say we need to be in GovCloud and operate in GovCloud East, there you go, push the button and you can behave in GovCloud East as well. >> And with server lists and the region support and all the goodness really makes a really good opportunity to really manage these Cloud native services with the data interaction so, really good prospects. Final question for you. I mean, we love the story. I think it is going to be a really changing market in this area in a big way. I think the data storage relationship relative to higher level services will be huge as Cloud native continues to drive everything. What's the future? I mean, you guys see yourself as a all encompassing, all singing and dancing storage platform or a set of services that you're going to enable developers and drive that value. Where do you see this going? >> I think that it's a mix of both. Ultimately, you saw even on Storage Day the announcement of file cash and file cash creates a new common name space across different storage platforms and so, the notion of being able to use one area to access your data and have it come from different spots is fantastic. That's been in the on-prem world for a couple of years and it's finally making it to the Cloud. I see us following that trend in helping support. We're super laser-focused on Cloud Storage itself so, EBS volumes, we keep having customers come to us and say, "I don't want to run agents in my EC2 instances. I want you to snap and scan and I don't want to, I've got all this EFS and FSX out there that we want to scan," and so, we see that all of the Cloud Storage platforms, Amazon work docs, EFS, FSX, EBS, S3, we'll all come together and we'll provide a solution that's super simple, highly scalable that can meet all the storage needs so, that's our goal right now and where we're working towards. >> Well, Cloud Storage Security, you couldn't get a more a descriptive name of what you guys are working on and again, I've had many contacts with Andy Jassy when he was running AWS and he always loves to quote "The Innovator's Dilemma," one of his teachers at Harvard Business School and we were riffing on that the other day and I want to get your thoughts. It's not so much "The Innovator's Dilemma" anymore relative to Cloud 'cause that's kind of a done deal. It's "The Integrator's Dilemma," and so, it's the integrations are so huge now. If you don't integrate the right way, that's the new dilemma. What's your reaction to that? >> A 100% agreed. It's been super interesting. Our customers have come to us for a security solution and they don't expect us to be 'cause we don't want to be either. Our own engine vendor, we're not the ones creating the engines. We are integrating other engines in and so we can provide a multi engine scan that gives you higher efficacy. So this notion of offering simple integrations without slowing down the process, that's the key factor here is what we've been after so, we are about simplifying the Cloud experience to protecting your storage and it's been so funny because I thought customers might complain that we're not a name brand engine vendor, but they love the fact that we have multiple engines in place and we're bringing that to them this higher efficacy, multi engine scan. >> I mean the developer trends can change on a dime. You make it faster, smarter, higher velocity and more protected, that's a winning formula in the Cloud so Ed, congratulations and thanks for spending the time to riff on and talk about Cloud Storage Security and congratulations on the company's success. Thanks for coming on "theCUBE." >> My pleasure, thanks a lot, John. >> Okay. This conversation here in Palo Alto, California I'm John Furrier, host of "theCUBE." Thanks for watching.

(upbeat music) >> We're here on theCube covering AWS Storage Day 2022. Kevin Miller joins us. He's the vice president and general manager of Amazon S3. Hello, Kevin, good to see you again. >> Hey Dave, it's great to see you as always. >> It seems like just yesterday we were celebrating the 15th anniversary of S3, and of course the launch of the modern public cloud, which started there. You know, when you think back Kevin, over the past year, what are some of the trends that you're seeing and hearing from customers? What do they want to see AWS focus more on? What's the direction that you're setting? >> Yeah, well Dave, really I think there's probably three trends that we're seeing really pop this year. I think one just given the kind of macroeconomic situation right now is cost optimization. That's not a surprise. Everyone's just taking a closer look at what they're using, and where they might be able to pair back. And you know, I think that's a place that obviously S3 has a long history of helping customers save money. Whether it's through our new storage classes, things like our Glacier Instant Retrieval, storage class that we launched to reinvent last year. Or things like our S3 storage lens capability to really dig in and help customers identify where their costs are are being spent. But so certainly every, you know, a lot of customers are focused on that right now, and for obvious reasons. I think the second thing that we're seeing is, just a real focus on simplicity. And it kind of goes hand in hand with cost optimization, because what a lot of customers are looking for is, how do I take the staff that I have, and do more this year. Right, continue to innovate, continue to bring new applications or top line generating revenue applications to the market, but not have to add a lot of extra headcount to do that. And so, what they're looking for is management and simplicity. How do I have all of this IT infrastructure, and not have to have people spending a lot of their time going into kind of routine maintenance and operations. And so that's an area that we're spending a lot of time. We think we have a lot of capability today, but looking at ways that we can continue to simplify, make it easier for customers to manage their infrastructure. Things like our S3 intelligent tiering storage class, which just automatically gives cost savings for data that's not routinely accessed. And so that's a big focus for us this year as well. And then I think the last and probably third thing I would highlight is an emerging theme or it's been a theme, but really continuing to increase in volume, is all around sustainability. And you know, our customers are looking for us to give them the data and the assurances for them, for their own reports and their own understanding of how sustainable is my infrastructure. And so within AWS, of course, you know we're on a path towards operating with 100% renewable energy by 2025. As well as helping the overall Amazon goal of achieving net zero carbon by 2040. So those are some big lofty goals. We've been giving customers greater insights with our carbon footprint tool. And we think that, you know the cloud continues to be just a great place to run and reduce customer's carbon footprint for the similar you know, storage capacity or similar compute capacity. But that's just going to continue to be a trend and a theme that we're looking at ways that we can continue to help customers do more to aggressively drive down their carbon footprint. >> I mean, it makes sense. It's like you're partnering up with the cloud, you know, you did same thing on security, you know, there's that shared responsibility model, same thing now with ESG. And on the macro it's interesting Kevin, this is the first time I can remember where, you know it used to be, if there's a downturn it's cost optimization, you go to simplicity. But at the same time with digital, you know, the rush to digital, people still are thinking about, okay how do I invest in the future? So but let's focus on cost for a moment then we'll come back to sort of the data value. Can you tell us how AWS helps customers save on storage, you know, beyond just the price per terabyte actions that you could take. I mean I love that, you guys should keep doing that. >> Absolutely. >> But what other knobs are you turning? >> Yeah, right and we've had obviously something like 15 cost reductions or price reductions over the years, and we're just going to continue to use that lever where we can, but it's things like the launch of our Glacier Instant Retrieval storage class that we did last year at Reinvent, where that's now you know, 4/10ths of a cent per gigabyte month. For data that customers access pretty infrequently maybe a few times a year, but they can now access that data immediately and just pay a small retrieval fee when they access that data. And so that's an example of a new capability that reduces customer's total cost of ownership, but is not just a straight up price reduction. I mentioned S3 Intelligent-Tiering, that's another case where, you know, when we launch Glacier Instant Retrieval, we integrated that with Intelligent-Tiering as well. So we have the archive instant access tier within Intelligent-Tiering. And so now data that's not accessed for 90 days is just automatically put into AIA and and then results in a reduced storage cost to customers. So again, leaning into this idea that customers are telling us, "Just do, you know what should be done "for my data to help me reduce cost, can you just do it, "and sort of give me the right defaults." And that's what we're trying to do with things like Intelligent-Tiering. We've also, you know, outside of the S3 part of our portfolio, we've been adding similar kinds of capabilities within some of our file services. So things like our, you know elastic file service launched a one zone storage class as well as an intelligent tiering capability to just automatically help customers save money. I think in some cases up to 92% on their their EFS storage costs with this automatic intelligent tiering capability. And then the last thing I would say is that we also are just continuing to help customers in other ways, like I said, our storage lens is a great way for customers to really dig in and figure out. 'Cause you know, often customers will find that they may have, you know, certain data sets that someone's forgotten about or, they're capturing more data than they expected perhaps in a logging application or something that ends up generating a lot more data than they expected. And so storage lens helps them really zoom in very quickly on, you know this is the data, here's how frequently it's being accessed and then they can make decisions about use that data I keep, how long do I keep it? Maybe that's good candidates to move down into one of our very cold storage classes like Glacier Deep Archive, where they they still have the data, but they don't expect to need to actively retrieve it on a regular basis. >> SDL bromide, if you can measure it, you can manage it. So if I can see it, visualize it, that I can take actions. When you think about S3- >> That's right. it's always been great for archival workloads but you made some updates to Glacier that changed the way that we maybe think about archive data. Can you talk about those changes specifically, what it means for how customers should leverage AWS services going forward? >> Yeah, and actually, you know, Glacier's coming up on its 10 year anniversary in August, so we're pretty excited about that. And you know, but there's just been a real increase in the pace of innovation, I think over the last three or four years there. So we launched the Glacier Deep Archive capability in 2019, 2018, I guess it was. And then we launched Glacier Instant Retrieval of course last year. So really what we're seeing is we now have three storage classes that cover are part of the Glacier family. So everything from millisecond retrieval for that data, that needs to be accessed quickly when it is accessed, but isn't being accessed, you know, regularly. So maybe a few times a year. And there's a lot of use cases that we're seeing really quickly emerge for that. Everything from, you know, user generated content like photos and videos, to big broadcaster archives and particularly in media and entertainment segment. Seeing a lot of interest in Glaciers Instant Retrieval because that data is pretty cold on a regular basis. But when they want to access it, they want a huge amount of data, petabytes of data potentially back within seconds, and that's the capability we can provide with Glacier Instant Retrieval. And then on the other end of the spectrum, with Glacier Deep Archive, again we have customers that have huge archives of data that they be looking to have that 3-AZ durability that we provide with Glacier, and make sure that data is protected. But really, you know expect to access it once a year if ever. Now it could be a backup copy of data or secondary or tertiary copy of data, could be data that they just don't have an active use for it. And I think that's one of the things we're starting to see grow a lot, is customers that have shared data sets where they may not need that data right now but they do want to keep it because as they think about, again these like new applications that can drive top line growth, they're finding that they may go back to that data six months or nine months from now and start to really actively use it. So if they want that option value to keep that data so they can use it down the road, Glacier Deep Archive, or Glacier Flexible Retrieval, which is kind of our storage class right in the middle of the road. Those are great options for customers to keep the data, keep it safe and secure, but then have it, you know pretty accessible when they're ready to get it back. >> Got it, thank you for that. So, okay, so customers have choices. I want to get into some of the competitive differentiators. And of course we were talking earlier about cost optimization, which is obviously an important topic given the macro environment you know, but there's more. And so help us understand what's different about AWS in terms of helping customers get value from their data, cost reduction as a component of value, part of the TCO, for sure. But just beyond being a cloud bit bucket, you know just a storage container in the cloud, what are some of the differentiators that you can talk to? >> Yeah, well Dave, I mean, I think that when it comes to value, I think there's tremendous benefits in AWS, well beyond just cost reduction. I think, you know, part of it is S3 now has built, I think, an earned reputation for being resilient, for storing, you know, at massive scale giving customers that confidence that they will be able to scale up. You know, we store more than 200 trillion objects. We regularly peak at over 100 million requests per second. So customers can build on S3 and Glacier with the confidence that we're going to be there to help their applications grow and scale over time. And then I think that in all of the applications both first party and third party, the customers can use, and services that they can use to build modern applications is an incredible benefit. So whether it's all of our serverless offerings, things like Lambda or containers and everything we have to manage that. Or whether it's the deep analytics and machine learning capabilities we have to help really extract, you know value and insight from data in near real time. You know, we're just seeing an incredible number of customers build those kinds of applications where they're processing data and feeding their results right back into their business right away. So I'm just going to briefly mention a couple, like, you know one example is ADP that really helps their customers measure, compare and sort of analyze their workforce. They have a couple petabytes of data, something like 25 billion individual data points and they're just processing that data continuously through their analytics and machine learning applications to then again, give those insights back to their customers. Another good example is AstraZeneca. You know, they are processing petabytes and petabytes of genomic sequencing data. And they have a goal to analyze 2 million genomes over the next four years. And so they're just really scaling up on AWS, both from a pure storage point of view, but more importantly, from all of the compute and analytics capability on top that is really critical to achieving that goal. And then, you know, beyond the first party services we have as I mentioned, it's really our third party, right? The AWS partner network provides customers an incredible range of choice in off the shelf applications that they can quickly provision and make use of the data to drive those business insights. And I think today the APN has something like 100,000 partners over in 150 countries. And we specifically have a storage competency partner where customers can go to get those applications that directly work, you know, on top of their data. And really, like I said, drive some of that insight. So, you know, I think it's that overall benefit of being able to really do a lot more with their data than just have it sit idle. You know, that's where I think we see a lot of customers interested in driving additional value. >> I'm glad you mentioned the ecosystem, and I'm glad you mentioned the storage competency as well. So there are other storage partners that you have, even though you're a head of a big storage division. And then I think there's some other under the cover things too. I've recently wrote, actually have written about this a lot. Things like nitro and rethinking virtualization and how to do, you know offloads. The security that comes, you know fundamentally as part of the platform is, I think architecturally is something that leads the way in the industry for sure. So there's a lot we could unpack, but you've fundamentally changed the storage market over the last 16 years. And again, I've written about this extensively. We used to think about storage in blocks or you got, you know, somebody who's really good in files, there were companies that dominated each space with legacy on-prem storage. You know, when you think about object storage Kevin, it was a niche, right? It was something used for archival, it was known for its simple, get put syntax, great for cheap and deep storage, and S3 changed that. Why do you think that's happened and S3 has evolved, the object has evolved the way it has, and what's the future hold for S3? >> Yeah I mean, you know, Dave, I think that probably the biggest overall trend there is that customers are looking to build cloud native applications. Where as much of that application is managed as they can have. They don't want to have to spend time managing the underlying infrastructure, the compute and storage and everything that goes around it. And so a fully managed service like S3, where there's no provisioning storage capacity, there's, you know we provide the resiliency and the durability that just really resonates with customers. And I think that increasingly, customers are seeing that they want to innovate across the entire range of business. So it's not about a central IT team anymore, it's about engineers that are embedded within lines of business, innovating around what is critical to achieve their business results. So, you know, if they're in a manufacturing segment, how can we pull data from sensors and other instrumentation off of our equipment and then make better decisions about when we need to do predictive maintenance, how quickly we can run our manufacturing line, looking for inefficiencies. And so we've developed around our managed offerings like S3, we've just developed, you know, customers who are investing and executing on plans and you know transformations. That really give them, you know put digital technology directly into the line of business that they're looking for. And I think that trend is just going to continue. People sometimes ask me, well "I mean, 16 years, you know, isn't S3 done?" And I would say, "By no stretcher are we done." We have plenty of feedback from customers on ways that we can continue to simplify, reduce the kinds of things they need to do, when they're looking for example and rolling out new security policies and parameters across their entire organization. So raising the bar there, finding, you know, raising the bar on how they can efficiently manage their storage and reduce costs. So I think we have plenty of innovation ahead of us to continue to help customers provide that fully managed capability. >> Yeah I often say Kevin, the next 10 years ain't going to be like the last in cloud. So I really thank you for coming on theCube and sharing your insights, really appreciate it. >> Absolutely Dave, thanks for having me. >> You're welcome. Okay keep it right there for more coverage of AWS Storage Day 2022 in theCube. (calm bright music)

>>mhm. Joining me now is Drew Schlussel, who is the senior director of product marketing at Wasabi. Hey, Drew. Good to see you again. Thanks for coming back in the Cube. >>They great to be here. Great to see you. >>All right, let's get into it. You know, Drew prior to the pandemic zero trust. Just like, kind of like a digital transformation. It was sort of a buzzword. And now it's become a real thing. Almost a mandate. What's what's Arby's take on zero trust? >>Uh, so absolutely right it was. It's been around a while, and now people are paying attention. Uh, sabes take is zero. Trust is is a good thing. Uh, you know, there are There are too many places right where the bad guys are getting in. And, you know, I think of zero. Trust is as kind of smashing laziness, right? It takes a little work, takes some planning, but, you know, done properly and using the right technology is using the right vendors. The rewards are of course, tremendous. Right? You you you can put to rest the fears of of ransomware and having your systems compromised. >>Well, and we're going to talk about this. But there's a lot of process and thinking involved and, you know, design in your zero trust. And you don't want to be wasting time messing with infrastructure. So we're gonna talk about that. There's a lot of discussion in the industry drew about a mutability and air gaps. I'd like you to share wasabi point of view on these topics. How do you approach it? And what makes wasabi different? >>Uh, so in terms of air gap and mutability, right, the beautiful thing about object storage, which is what we do all the time, is that it makes it that much easier. Right? To have a secure, immutable copy of your data someplace that's easy to access and, uh, doesn't cost you an arm and a leg to get your data back. Um, we're working with some of the best partners in the industry. Um, you know, we're working with folks like VM con vault Arc Marquis MSP 3. 60. Um, all folks who understand that you need to have multiple copies of your data. You need to have a copy stored offsite, and that copy needs to be immutable. And we can We can talk a little bit about what a mutability is and what it really means. >>You know, I want I wonder if you could talk a little bit more about with subi solution, because sometimes people don't understand. You actually are a cloud you're not building on other people's public clouds. And storage is the one use case where it actually makes sense to do that. Tell us a little bit more about those ABS approach and your solution. >>Yeah, I appreciate that. So there's there's definitely some misconception. We are our own cloud storage service. We don't run on top of anybody else, right? It's It's our systems. It's our software deployed globally, and we interoperate because we adhere to the S three standard. We interoperate with practically hundreds of applications, primarily in this case, right? We're talking about backup and recovery applications, and it's such a simple process, right? I mean, uh, just about everybody who's anybody in this business, protecting data has the ability now to, uh, access cloud storage. And so we've made it really simple. Uh, in many cases, you'll see wasabi, as you know, listed in the primary set of available vendors and, uh, you know, put in your private keys. Make sure that your account is locked down properly using, uh, let's say multi factor authentication, and you've got a great place to store copies of your data securely. >>I mean, we just heard from David friend. I did my math, right? He was talking about, you know, 1/6 the cost per terabyte per month, Maybe even a little better than that. How are you able to achieve such attractive economics? >>Yeah, So, you know, I can't remember how to translate my fractions into percentages, but I think we talk a lot about being 80% right, less expensive than the hyper scholars. And, you know, we talked about this at demon, right? There's there's some secret sauce there. Um, and, you know, we take a different approach to how we utilise the raw capacity to the effective capacity. And the fact is, we're also not having to run a few 100 other services, right? We do storage plain and simple all day, all the time, so we don't have to worry about overhead to support, you know, up and coming other services that are perhaps, uh, you know, going to be a loss leader right. Um, customers love it, right? They see the fact that their data is growing 40 80% year over year. They know they need to have some place to keep it secure. And, uh, you know, folks are flocking to us in droves. In fact, we're We're seeing a tremendous amount of migration, actually, right now, multiple petabytes being brought to Assad because folks have figured out that they can't afford to keep going with their current hyper scale or vendor. >>And the mutability is a feature of your product, right? What's the feature called? Can you dig? Double click on that a little bit? >>Yeah, Absolutely. Um So the determined s three is object lock. And what that means is your application will write an object to cloud storage, and it will define a retention period. Let's say a week. And for that period, that object is immutable. Untouchable cannot be altered in any way, shape or form. The application can't change it. The system administration can't change it with subi Can't change it. Okay, it is truly carved in stone, and this is something that it's been around for a while. But you're seeing a huge uptick in adoption and support for that feature by all the major vendors. And I named off a few earlier. Um, and the best part is that with the mutability comes some some sense of Well, it comes with not just a sense of security. It is security, right when you have data that cannot be altered by anybody. Um, even if the bad guys compromise your account, they steal your credentials, right? They can't take away the data. And that's a beautiful thing. A beautiful, beautiful thing. >>And you look like an s three bucket. Is that right? >>Yeah. Yeah. I mean, we're fully compatible with the S three a p I. So if you're using S three a p I based applications today, um, it's a very simple matter of just kind of redirecting where you want to store your data. Beautiful thing about backup and recovery, right? That's probably the simplest application. Simple being a relative term as far as lift and shift right, because that just means for your next full right point that it was subi retain your other falls for whatever 30 60 90 days. And then once you've kind of made that transition from vine divine. You know you're off and running with wasabi. >>I talked to my open about the allure of object storage. Historically, you know the simplicity of the get put syntax. But what about performance? Are you able to deliver performance? That's that's comparable to other storage formats. >>Oh, yeah, Absolutely. And we've got the We've got the performance numbers on the site to back that up. But I forgot to answer something earlier, Right? You said that the mutability is a feature, and I want to make it very clear that it is a feature, but it's an API request. Okay, So when you're talking about gets and puts and so forth, you know the comment you made earlier about being 80% more cost effectively, percent less expensive. Um, you know that API call, right? It's typically something that the other folks charge for, right? And I think we use the metaphor earlier about the refrigerator. Uh, but I'll use a different metaphor today, right? Uh, you can think of cloud storage as as a magical coffee cup, right? It gets as big as you want to store as much copy as you want. And the coffee is always warm right, And when you want to take a sip, there's no charge. You want to pop the lid and see how much coffee is in there. No charge. And that's an important thing. Because when you're talking about millions or billions of objects and you want to get a list of those objects or you want to get the status of the immutable settings for those objects anywhere else, it's going to cost you money to look at your data. We'll also be no additional charge, and that's part of the thing that sets us apart. >>Excellent. Thank you for that. So you mentioned some partners before. How do partners fit into the wasabi story? Where do you stop? Where do they pick up what you know, What do they bring? Can you give us maybe a paint a picture for us? Example or two? >>Sure. So again, we just do storage, right? That is our Our sole purpose in life is to, you know, to safely and securely store our customers' data. And so they're working with, uh, their application vendors. Whether it's, you know, active archive backup in recovery, uh, Iot surveillance, uh, media and entertainment workflows, right? Those systems already know how to manage the day to manage the metadata. They just need someplace to keep the data that is being worked on being stored and so forth. All right, so just like, uh, you know, plugging in a flash drive on your laptop, right? You literally can plug in wasabi as long as your applications support the AP getting started. Incredibly easy, right. We offer a 30 day trial, one terabyte, and most folks find that within, you know, probably a few hours of their P O. C. Right. Um, it's giving them everything they need in terms of performance, in terms of accessibility, in terms of sovereignty. I'm guessing you talked to, uh, you know, Dave friend earlier about data sovereignty, right. We're global company. All right, so there's got to be probably, you know, wherever you are in the world, someplace that will satisfy your sovereignty requirements, um, as well as your compliance requirements. >>We did talk about sovereignty, Drew. This is really what's interesting to me. A bit of an industry historian. When I look back to the early days of cloud, I remember the large storage companies, you know, they CEOs would say, We're going to have an answer for the cloud and they would go out. And for instance, I No. One bought competitor of carbonite and then couldn't figure out what to do with it. They couldn't figure out how to compete with the cloud, in part because they were afraid it was going to cannibalise their existing business. I think another part is because they just didn't have that imagination to develop an architecture that in a business model that could scale to see that you guys have done that is I love it because it brings competition. It brings innovation, and it helps lower clients cost and solve really nagging problems like, you know, uh, Ransomware, mutability and recovery. I'll give you the last word, Drew. >>Yeah, you're absolutely right. You know, the the on prem vendors. They're not going to go away anytime soon, right? There's always going to be a need for, you know, incredibly low latency high band with, you know, But, uh, you know, not all data is taught all the time. And by hot, I mean, you know, extremely hot. Uh, you know, uh, you know, let's take, uh, you know real time, Uh, analytics for maybe facial recognition, right, That requires sub millisecond type of processing. But once you've done that work right, you want to store that data for a long, long time, and, uh, you're gonna want to also tap back into it later. So, you know, other folks are telling you that, you know, you can go to these like cold, glacial type of tiered storage. Don't believe the hype. You're still going to pay way more for that than you would with just a wasabi like hot cloud storage system. And, you know, we don't compete with our partners, right? We complement you know what they're bringing to market in terms of the software vendors in terms of the hardware vendors were beautiful component for that hybrid cloud architecture. And I think folks are gravitating towards that. I think the cloud is kind of hitting a new gear, if you will, in terms of adoption and recognition for the security that they can achieve with it. >>All right, Drew, Thank you for that. We definitely We see the momentum in a moment. Drew and I will be back to get the customer perspective with Kevin Referenda, who's the director of information technology services at the Hodgkiss School. Keep it right there. >>Mhm

>> The rapid rise of ransomware attacks has added yet another challenge that business technology executives have to worry about these days, cloud storage, immutability, and air gaps have become a must have arrows in the quiver of organization's data protection strategies. But the important reality that practitioners have embraced is data protection, it can't be an afterthought or a bolt on it, has to be designed into the operational workflow of technology systems. The problem is, oftentimes, data protection is complicated with a variety of different products, services, software components, and storage formats, this is why object storage is moving to the forefront of data protection use cases because it's simpler and less expensive. The put data get data syntax has always been alluring, but object storage, historically, was seen as this low-cost niche solution that couldn't offer the performance required for demanding workloads, forcing customers to make hard tradeoffs between cost and performance. That has changed, the ascendancy of cloud storage generally in the S3 format specifically has catapulted object storage to become a first class citizen in a mainstream technology. Moreover, innovative companies have invested to bring object storage performance to parity with other storage formats, but cloud costs are often a barrier for many companies as the monthly cloud bill and egress fees in particular steadily climb. Welcome to Secure Storage Hot Takes, my name is Dave Vellante, and I'll be your host of the program today, where we introduce our community to Wasabi, a company that is purpose-built to solve this specific problem with what it claims to be the most cost effective and secure solution on the market. We have three segments today to dig into these issues, first up is David Friend, the well known entrepreneur who co-founded Carbonite and now Wasabi will then dig into the product with Drew Schlussel of Wasabi, and then we'll bring in the customer perspective with Kevin Warenda of the Hotchkiss School, let's get right into it. We're here with David Friend, the President and CEO and Co-founder of Wasabi, the hot storage company, David, welcome to theCUBE. >> Thanks Dave, nice to be here. >> Great to have you, so look, you hit a home run with Carbonite back when building a unicorn was a lot more rare than it has been in the last few years, why did you start Wasabi? >> Well, when I was still CEO of Wasabi, my genius co-founder Jeff Flowers and our chief architect came to me and said, you know, when we started this company, a state of the art disk drive was probably 500 gigabytes and now we're looking at eight terabyte, 16 terabyte, 20 terabyte, even 100 terabyte drives coming down the road and, you know, sooner or later the old architectures that were designed around these much smaller disk drives is going to run out of steam because, even though the capacities are getting bigger and bigger, the speed with which you can get data on and off of a hard drive isn't really changing all that much. And Jeff foresaw a day when the architectures sort of legacy storage like Amazon S3 and so forth was going to become very inefficient and slow. And so he came up with a new, highly parallelized architecture, and he said, I want to go off and see if I can make this work. So I said, you know, good luck go to it and they went off and spent about a year and a half in the lab, designing and testing this new storage architecture and when they got it working, I looked at the economics of this and I said, holy cow, we can sell cloud storage for a fraction of the price of Amazon, still make very good gross margins and it will be faster. So this is a whole new generation of object storage that you guys have invented. So I recruited a new CEO for Carbonite and left to found Wasabi because the market for cloud storage is almost infinite. You know, when you look at all the world's data, you know, IDC has these crazy numbers, 120 zetabytes or something like that and if you look at that as you know, the potential market size during that data, we're talking trillions of dollars, not billions and so I said, look, this is a great opportunity, if you look back 10 years, all the world's data was on-prem, if you look forward 10 years, most people agree that most of the world's data is going to live in the cloud, we're at the beginning of this migration, we've got an opportunity here to build an enormous company. >> That's very exciting. I mean, you've always been a trend spotter, and I want to get your perspectives on data protection and how it's changed. It's obviously on people's minds with all the ransomware attacks and security breaches, but thinking about your experiences and past observations, what's changed in data protection and what's driving the current very high interest in the topic? >> Well, I think, you know, from a data protection standpoint, immutability, the equivalent of the old worm tapes, but applied to cloud storage is, you know, become core to the backup strategies and disaster recovery strategies for most companies. And if you look at our partners who make backup software like Veeam, Convo, Veritas, Arcserve, and so forth, most of them are really taking advantage of mutable cloud storage as a way to protect customer data, customers backups from ransomware. So the ransomware guys are pretty clever and they, you know, they discovered early on that if someone could do a full restore from their backups, they're never going to pay a ransom. So, once they penetrate your system, they get pretty good at sort of watching how you do your backups and before they encrypt your primary data, they figure out some way to destroy or encrypt your backups as well, so that you can't do a full restore from your backups. And that's where immutability comes in. You know, in the old days you, you wrote what was called a worm tape, you know, write once read many, and those could not be overwritten or modified once they were written. And so we said, let's come up with an equivalent of that for the cloud, and it's very tricky software, you know, it involves all kinds of encryption algorithms and blockchain and this kind of stuff but, you know, the net result is if you store your backups in immutable buckets, in a product like Wasabi, you can't alter it or delete it for some period of time, so you could put a timer on it, say a year or six months or something like that, once that data is written, you know, there's no way you can go in and change it, modify it, or anything like that, including even Wasabi's engineers. >> So, David, I want to ask you about data sovereignty. It's obviously a big deal, I mean, especially for companies with the presence overseas, but what's really is any digital business these days, how should companies think about approaching data sovereignty? Is it just large firms that should be worried about this? Or should everybody be concerned? What's your point of view? >> Well, all around the world countries are imposing data sovereignty laws and if you're in the storage business, like we are, if you don't have physical data storage in-country, you're probably not going to get most of the business. You know, since Christmas we've built data centers in Toronto, London, Frankfurt, Paris, Sydney, Singapore, and I've probably forgotten one or two, but the reason we do that is twofold; one is, you know, if you're closer to the customer, you're going to get better response time, lower latency, and that's just a speed of light issue. But the bigger issue is, if you've got financial data, if you have healthcare data, if you have data relating to security, like surveillance videos, and things of that sort, most countries are saying that data has to be stored in-country, so, you can't send it across borders to some other place. And if your business operates in multiple countries, you know, dealing with data sovereignty is going to become an increasingly important problem. >> So in May of 2018, that's when the fines associated with violating GDPR went into effect and GDPR was like this main spring of privacy and data protection laws and we've seen it spawn other public policy things like the CCPA and think it continues to evolve, we see judgments in Europe against big tech and this tech lash that's in the news in the U.S. and the elimination of third party cookies, what does this all mean for data protection in the 2020s? >> Well, you know, every region and every country, you know, has their own idea about privacy, about security, about the use of even the use of metadata surrounding, you know, customer data and things of this sort. So, you know, it's getting to be increasingly complicated because GDPR, for example, imposes different standards from the kind of privacy standards that we have here in the U.S., Canada has a somewhat different set of data sovereignty issues and privacy issues so it's getting to be an increasingly complex, you know, mosaic of rules and regulations around the world and this makes it even more difficult for enterprises to run their own, you know, infrastructure because companies like Wasabi, where we have physical data centers in all kinds of different markets around the world and we've already dealt with the business of how to meet the requirements of GDPR and how to meet the requirements of some of the countries in Asia and so forth, you know, rather than an enterprise doing that just for themselves, if you running your applications or keeping your data in the cloud, you know, now a company like Wasabi with, you know, 34,000 customers, we can go to all the trouble of meeting these local requirements on behalf of our entire customer base and that's a lot more efficient and a lot more cost effective than if each individual country has to go deal with the local regulatory authorities. >> Yeah, it's compliance by design, not by chance. Okay, let's zoom out for the final question, David, thinking about the discussion that we've had around ransomware and data protection and regulations, what does it mean for a business's operational strategy and how do you think organizations will need to adapt in the coming years? >> Well, you know, I think there are a lot of forces driving companies to the cloud and, you know, and I do believe that if you come back five or 10 years from now, you're going to see majority of the world's data is going to be living in the cloud and I think storage, data storage is going to be a commodity much like electricity or bandwidth, and it's going to be done right, it will comply with the local regulations, it'll be fast, it'll be local, and there will be no strategic advantage that I can think of for somebody to stand up and run their own storage, especially considering the cost differential, you know, the most analysts think that the full, all in costs of running your own storage is in the 20 to 40 terabytes per month range, whereas, you know, if you migrate your data to the cloud, like Wasabi, you're talking probably $6 a month and so I think people are learning how to deal with the idea of an architecture that involves storing your data in the cloud, as opposed to, you know, storing your data locally. >> Wow, that's like a six X more expensive in the clouds, more than six X, all right, thank you, David,-- >> In addition to which, you know, just finding the people to babysit this kind of equipment has become nearly impossible today. >> Well, and with a focus on digital business, you don't want to be wasting your time with that kind of heavy lifting. David, thanks so much for coming in theCUBE, a great Boston entrepreneur, we've followed your career for a long time and looking forward to the future. >> Thank you. >> Okay, in a moment, Drew Schlussel will join me and we're going to dig more into product, you're watching theCUBE, the leader in enterprise and emerging tech coverage, keep it right there. ♪ Whoa ♪ ♪ Brenda in sales got an email ♪ ♪ Click here for a trip to Bombay ♪ ♪ It's not even called Bombay anymore ♪ ♪ But you clicked it anyway ♪ ♪ And now our data's been held hostage ♪ ♪ And now we're on sinking ship ♪ ♪ And a hacker's in our system ♪ ♪ Just 'cause Brenda wanted a trip ♪ ♪ She clicked on something stupid ♪ ♪ And our data's out of our control ♪ ♪ Into the hands of a hacker's ♪ ♪ And he's a giant asshole. ♪ ♪ He encrypted it in his basement ♪ ♪ He wants a million bucks for the key ♪ ♪ And I'm pretty sure he's 15 ♪ ♪ And still going through puberty ♪ ♪ I know you didn't mean to do us wrong ♪ ♪ But now I'm dealing with this all week long ♪ ♪ To make you all aware ♪ ♪ Of all this ransomware ♪ ♪ That is why I'm singing you this song ♪ ♪ C'mon ♪ ♪ Take it from me ♪ ♪ The director of IT ♪ ♪ Don't click on that email from a prince Nairobi ♪ ♪ 'Cuz he's not really a prince ♪ ♪ Now our data's locked up on our screen ♪ ♪ Controlled by a kid who's just fifteen ♪ ♪ And he's using our money to buy a Ferrari ♪ (gentle music) >> Joining me now is Drew Schlussel, who is the Senior Director of Product Marketing at Wasabi, hey Drew, good to see you again, thanks for coming back in theCUBE. >> Dave, great to be here, great to see you. >> All right, let's get into it. You know, Drew, prior to the pandemic, Zero Trust, just like kind of like digital transformation was sort of a buzzword and now it's become a real thing, almost a mandate, what's Wasabi's take on Zero Trust. >> So, absolutely right, it's been around a while and now people are paying attention, Wasabi's take is Zero Trust is a good thing. You know, there are too many places, right, where the bad guys are getting in. And, you know, I think of Zero Trust as kind of smashing laziness, right? It takes a little work, it takes some planning, but you know, done properly and using the right technologies, using the right vendors, the rewards are, of course tremendous, right? You can put to rest the fears of ransomware and having your systems compromised. >> Well, and we're going to talk about this, but there's a lot of process and thinking involved and, you know, design and your Zero Trust and you don't want to be wasting time messing with infrastructure, so we're going to talk about that, there's a lot of discussion in the industry, Drew, about immutability and air gaps, I'd like you to share Wasabi's point of view on these topics, how do you approach it and what makes Wasabi different? >> So, in terms of air gap and immutability, right, the beautiful thing about object storage, which is what we do all the time is that it makes it that much easier, right, to have a secure immutable copy of your data someplace that's easy to access and doesn't cost you an arm and a leg to get your data back. You know, we're working with some of the best, you know, partners in the industry, you know, we're working with folks like, you know, Veeam, Commvault, Arc, Marquee, MSP360, all folks who understand that you need to have multiple copies of your data, you need to have a copy stored offsite, and that copy needs to be immutable and we can talk a little bit about what immutability is and what it really means. >> You know, I wonder if you could talk a little bit more about Wasabi's solution because, sometimes people don't understand, you actually are a cloud, you're not building on other people's public clouds and this storage is the one use case where it actually makes sense to do that, tell us a little bit more about Wasabi's approach and your solution. >> Yeah, I appreciate that, so there's definitely some misconception, we are our own cloud storage service, we don't run on top of anybody else, right, it's our systems, it's our software deployed globally and we interoperate because we adhere to the S3 standard, we interoperate with practically hundreds of applications, primarily in this case, right, we're talking about backup and recovery applications and it's such a simple process, right? I mean, just about everybody who's anybody in this business protecting data has the ability now to access cloud storage and so we've made it really simple, in many cases, you'll see Wasabi as you know, listed in the primary set of available vendors and, you know, put in your private keys, make sure that your account is locked down properly using, let's say multifactor authentication, and you've got a great place to store copies of your data securely. >> I mean, we just heard from David Friend, if I did my math right, he was talking about, you know, 1/6 the cost per terabyte per month, maybe even a little better than that, how are you able to achieve such attractive economics? >> Yeah, so, you know, I can't remember how to translate my fractions into percentages, but I think we talk a lot about being 80%, right, less expensive than the hyperscalers. And you know, we talked about this at Vermont, right? There's some secret sauce there and you know, we take a different approach to how we utilize the raw capacity to the effective capacity and the fact is we're also not having to run, you know, a few hundred other services, right? We do storage, plain and simple, all day, all the time, so we don't have to worry about overhead to support, you know, up and coming other services that are perhaps, you know, going to be a loss leader, right? Customers love it, right, they see the fact that their data is growing 40, 80% year over year, they know they need to have some place to keep it secure, and, you know, folks are flocking to us in droves, in fact, we're seeing a tremendous amount of migration actually right now, multiple petabytes being brought to Wasabi because folks have figured out that they can't afford to keep going with their current hyperscaler vendor. >> And immutability is a feature of your product, right? What the feature called? Can you double-click on that a little bit? >> Yeah, absolutely. So, the term in S3 is Object Lock and what that means is your application will write an object to cloud storage, and it will define a retention period, let's say a week. And for that period, that object is immutable, untouchable, cannot be altered in any way, shape, or form, the application can't change it, the system administration can't change it, Wasabi can't change it, okay, it is truly carved in stone. And this is something that it's been around for a while, but you're seeing a huge uptick, right, in adoption and support for that feature by all the major vendors and I named off a few earlier and the best part is that with immutability comes some sense of, well, it comes with not just a sense of security, it is security. Right, when you have data that cannot be altered by anybody, even if the bad guys compromise your account, they steal your credentials, right, they can't take away the data and that's a beautiful thing, a beautiful, beautiful thing. >> And you look like an S3 bucket, is that right? >> Yeah, I mean, we're fully compatible with the S3 API, so if you're using S3 API based applications today, it's a very simple matter of just kind of redirecting where you want to store your data, beautiful thing about backup and recovery, right, that's probably the simplest application, simple being a relative term, as far as lift and shift, right? Because that just means for your next full, right, point that at Wasabi, retain your other fulls, you know, for whatever 30, 60, 90 days, and then once you've kind of made that transition from vine to vine, you know, you're often running with Wasabi. >> I talked to my open about the allure of object storage historically, you know, the simplicity of the get put syntax, but what about performance? Are you able to deliver performance that's comparable to other storage formats? >> Oh yeah, absolutely, and we've got the performance numbers on the site to back that up, but I forgot to answer something earlier, right, you said that immutability is a feature and I want to make it very clear that it is a feature but it's an API request. Okay, so when you're talking about gets and puts and so forth, you know, the comment you made earlier about being 80% more cost effective or 80% less expensive, you know, that API call, right, is typically something that the other folks charge for, right, and I think we used the metaphor earlier about the refrigerator, but I'll use a different metaphor today, right? You can think of cloud storage as a magical coffee cup, right? It gets as big as you want to store as much coffee as you want and the coffee's always warm, right? And when you want to take a sip, there's no charge, you want to, you know, pop the lid and see how much coffee is in there, no charge, and that's an important thing, because when you're talking about millions or billions of objects, and you want to get a list of those objects, or you want to get the status of the immutable settings for those objects, anywhere else it's going to cost you money to look at your data, with Wasabi, no additional charge and that's part of the thing that sets us apart. >> Excellent, so thank you for that. So, you mentioned some partners before, how do partners fit into the Wasabi story? Where do you stop? Where do they pick up? You know, what do they bring? Can you give us maybe, a paint a picture for us example, or two? >> Sure, so, again, we just do storage, right, that is our sole purpose in life is to, you know, to safely and securely store our customer's data. And so they're working with their application vendors, whether it's, you know, active archive, backup and recovery, IOT, surveillance, media and entertainment workflows, right, those systems already know how to manage the data, manage the metadata, they just need some place to keep the data that is being worked on, being stored and so forth. Right, so just like, you know, plugging in a flash drive on your laptop, right, you literally can plug in Wasabi as long as your applications support the API, getting started is incredibly easy, right, we offer a 30-day trial, one terabyte, and most folks find that within, you know, probably a few hours of their POC, right, it's giving them everything they need in terms of performance, in terms of accessibility, in terms of sovereignty, I'm guessing you talked to, you know, Dave Friend earlier about data sovereignty, right? We're global company, right, so there's got to be probably, you know, wherever you are in the world some place that will satisfy your sovereignty requirements, as well as your compliance requirements. >> Yeah, we did talk about sovereignty, Drew, this is really, what's interesting to me, I'm a bit of a industry historian, when I look back to the early days of cloud, I remember the large storage companies, you know, their CEOs would say, we're going to have an answer for the cloud and they would go out, and for instance, I know one bought competitor of Carbonite, and then couldn't figure out what to do with it, they couldn't figure out how to compete with the cloud in part, because they were afraid it was going to cannibalize their existing business, I think another part is because they just didn't have that imagination to develop an architecture that in a business model that could scale to see that you guys have done that is I love it because it brings competition, it brings innovation and it helps lower clients cost and solve really nagging problems. Like, you know, ransomware, of mutability and recovery, I'll give you the last word, Drew. >> Yeah, you're absolutely right. You know, the on-prem vendors, they're not going to go away anytime soon, right, there's always going to be a need for, you know, incredibly low latency, high bandwidth, you know, but, you know, not all data's hot all the time and by hot, I mean, you know, extremely hot, you know, let's take, you know, real time analytics for, maybe facial recognition, right, that requires sub-millisecond type of processing. But once you've done that work, right, you want to store that data for a long, long time, and you're going to want to also tap back into it later, so, you know, other folks are telling you that, you know, you can go to these like, you know, cold glacial type of tiered storage, yeah, don't believe the hype, you're still going to pay way more for that than you would with just a Wasabi-like hot cloud storage system. And, you know, we don't compete with our partners, right? We compliment, you know, what they're bringing to market in terms of the software vendors, in terms of the hardware vendors, right, we're a beautiful component for that hybrid cloud architecture. And I think folks are gravitating towards that, I think the cloud is kind of hitting a new gear if you will, in terms of adoption and recognition for the security that they can achieve with it. >> All right, Drew, thank you for that, definitely we see the momentum, in a moment, Drew and I will be back to get the customer perspective with Kevin Warenda, who's the Director of Information technology services at The Hotchkiss School, keep it right there. >> Hey, I'm Nate, and we wrote this song about ransomware to educate people, people like Brenda. >> Oh, God, I'm so sorry. We know you are, but Brenda, you're not alone, this hasn't just happened to you. >> No! ♪ Colonial Oil Pipeline had a guy ♪ ♪ who didn't change his password ♪ ♪ That sucks ♪ ♪ His password leaked, the data was breached ♪ ♪ And it cost his company 4 million bucks ♪ ♪ A fake update was sent to people ♪ ♪ Working for the meat company JBS ♪ ♪ That's pretty clever ♪ ♪ Instead of getting new features, they got hacked ♪ ♪ And had to pay the largest crypto ransom ever ♪ ♪ And 20 billion dollars, billion with a b ♪ ♪ Have been paid by companies in healthcare ♪ ♪ If you wonder buy your premium keeps going ♪ ♪ Up, up, up, up, up ♪ ♪ Now you're aware ♪ ♪ And now the hackers they are gettin' cocky ♪ ♪ When they lock your data ♪ ♪ You know, it has gotten so bad ♪ ♪ That they demand all of your money and it gets worse ♪ ♪ They go and the trouble with the Facebook ad ♪ ♪ Next time, something seems too good to be true ♪ ♪ Like a free trip to Asia! ♪ ♪ Just check first and I'll help before you ♪ ♪ Think before you click ♪ ♪ Don't get fooled by this ♪ ♪ Who isn't old enough to drive to school ♪ ♪ Take it from me, the director of IT ♪ ♪ Don't click on that email from a prince in Nairobi ♪ ♪ Because he's not really a prince ♪ ♪ Now our data's locked up on our screen ♪ ♪ Controlled by a kid who's just fifteen ♪ ♪ And he's using our money to buy a Ferrari ♪ >> It's a pretty sweet car. ♪ A kid without facial hair, who lives with his mom ♪ ♪ To learn more about this go to wasabi.com ♪ >> Hey, don't do that. ♪ Cause if we had Wasabi's immutability ♪ >> You going to ruin this for me! ♪ This fifteen-year-old wouldn't have on me ♪ (gentle music) >> Drew and I are pleased to welcome Kevin Warenda, who's the Director of Information Technology Services at The Hotchkiss School, a very prestigious and well respected boarding school in the beautiful Northwest corner of Connecticut, hello, Kevin. >> Hello, it's nice to be here, thanks for having me. >> Yeah, you bet. Hey, tell us a little bit more about The Hotchkiss School and your role. >> Sure, The Hotchkiss School is an independent boarding school, grades nine through 12, as you said, very prestigious and in an absolutely beautiful location on the deepest freshwater lake in Connecticut, we have 500 acre main campus and a 200 acre farm down the street. My role as the Director of Information Technology Services, essentially to oversee all of the technology that supports the school operations, academics, sports, everything we do on campus. >> Yeah, and you've had a very strong history in the educational field, you know, from that lens, what's the unique, you know, or if not unique, but the pressing security challenge that's top of mind for you? >> I think that it's clear that educational institutions are a target these days, especially for ransomware. We have a lot of data that can be used by threat actors and schools are often underfunded in the area of IT security, IT in general sometimes, so, I think threat actors often see us as easy targets or at least worthwhile to try to get into. >> Because specifically you are potentially spread thin, underfunded, you got students, you got teachers, so there really are some, are there any specific data privacy concerns as well around student privacy or regulations that you can speak to? >> Certainly, because of the fact that we're an independent boarding school, we operate things like even a health center, so, data privacy regulations across the board in terms of just student data rights and FERPA, some of our students are under 18, so, data privacy laws such as COPPA apply, HIPAA can apply, we have PCI regulations with many of our financial transactions, whether it be fundraising through alumni development, or even just accepting the revenue for tuition so, it's a unique place to be, again, we operate very much like a college would, right, we have all the trappings of a private college in terms of all the operations we do and that's what I love most about working in education is that it's all the industries combined in many ways. >> Very cool. So let's talk about some of the defense strategies from a practitioner point of view, then I want to bring in Drew to the conversation so what are the best practice and the right strategies from your standpoint of defending your data? >> Well, we take a defense in-depth approach, so we layer multiple technologies on top of each other to make sure that no single failure is a key to getting beyond those defenses, we also keep it simple, you know, I think there's some core things that all organizations need to do these days in including, you know, vulnerability scanning, patching , using multifactor authentication, and having really excellent backups in case something does happen. >> Drew, are you seeing any similar patterns across other industries or customers? I mean, I know we're talking about some uniqueness in the education market, but what can we learn from other adjacent industries? >> Yeah, you know, Kevin is spot on and I love hearing what he's doing, going back to our prior conversation about Zero Trust, right, that defense in-depth approach is beautifully aligned, right, with the Zero Trust approach, especially things like multifactor authentication, always shocked at how few folks are applying that very, very simple technology and across the board, right? I mean, Kevin is referring to, you know, financial industry, healthcare industry, even, you know, the security and police, right, they need to make sure that the data that they're keeping, evidence, right, is secure and immutable, right, because that's evidence. >> Well, Kevin, paint a picture for us, if you would. So, you were primarily on-prem looking at potentially, you know, using more cloud, you were a VMware shop, but tell us, paint a picture of your environment, kind of the applications that you support and the kind of, I want to get to the before and the after Wasabi, but start with kind of where you came from. >> Sure, well, I came to The Hotchkiss School about seven years ago and I had come most recently from public K12 and municipal, so again, not a lot of funding for IT in general, security, or infrastructure in general, so Nutanix was actually a hyperconverged solution that I implemented at my previous position. So when I came to Hotchkiss and found mostly on-prem workloads, everything from the student information system to the card access system that students would use, financial systems, they were almost all on premise, but there were some new SaaS solutions coming in play, we had also taken some time to do some business continuity, planning, you know, in the event of some kind of issue, I don't think we were thinking about the pandemic at the time, but certainly it helped prepare us for that, so, as different workloads were moved off to hosted or cloud-based, we didn't really need as much of the on-premise compute and storage as we had, and it was time to retire that cluster. And so I brought the experience I had with Nutanix with me, and we consolidated all that into a hyper-converged platform, running Nutanix AHV, which allowed us to get rid of all the cost of the VMware licensing as well and it is an easier platform to manage, especially for small IT shops like ours. >> Yeah, AHV is the Acropolis hypervisor and so you migrated off of VMware avoiding the VTax avoidance, that's a common theme among Nutanix customers and now, did you consider moving into AWS? You know, what was the catalyst to consider Wasabi as part of your defense strategy? >> We were looking at cloud storage options and they were just all so expensive, especially in egress fees to get data back out, Wasabi became across our desks and it was such a low barrier to entry to sign up for a trial and get, you know, terabyte for a month and then it was, you know, $6 a month for terabyte. After that, I said, we can try this out in a very low stakes way to see how this works for us. And there was a couple things we were trying to solve at the time, it wasn't just a place to put backup, but we also needed a place to have some files that might serve to some degree as a content delivery network, you know, some of our software applications that are deployed through our mobile device management needed a place that was accessible on the internet that they could be stored as well. So we were testing it for a couple different scenarios and it worked great, you know, performance wise, fast, security wise, it has all the features of S3 compliance that works with Nutanix and anyone who's familiar with S3 permissions can apply them very easily and then there was no egress fees, we can pull data down, put data up at will, and it's not costing as any extra, which is excellent because especially in education, we need fixed costs, we need to know what we're going to spend over a year before we spend it and not be hit with, you know, bills for egress or because our workload or our data storage footprint grew tremendously, we need that, we can't have the variability that the cloud providers would give us. >> So Kevin, you explained you're hypersensitive about security and privacy for obvious reasons that we discussed, were you concerned about doing business with a company with a funny name? Was it the trial that got you through that knothole? How did you address those concerns as an IT practitioner? >> Yeah, anytime we adopt anything, we go through a risk review. So we did our homework and we checked the funny name really means nothing, there's lots of companies with funny names, I think we don't go based on the name necessarily, but we did go based on the history, understanding, you know, who started the company, where it came from, and really looking into the technology and understanding that the value proposition, the ability to provide that lower cost is based specifically on the technology in which it lays down data. So, having a legitimate, reasonable, you know, excuse as to why it's cheap, we weren't thinking, well, you know, you get what you pay for, it may be less expensive than alternatives, but it's not cheap, you know, it's reliable, and that was really our concern. So we did our homework for sure before even starting the trial, but then the trial certainly confirmed everything that we had learned. >> Yeah, thank you for that. Drew, explain the whole egress charge, we hear a lot about that, what do people need to know? >> First of all, it's not a funny name, it's a memorable name, Dave, just like theCUBE, let's be very clear about that, second of all, egress charges, so, you know, other storage providers charge you for every API call, right? Every get, every put, every list, everything, okay, it's part of their process, it's part of how they make money, it's part of how they cover the cost of all their other services, we don't do that. And I think, you know, as Kevin has pointed out, right, that's a huge differentiator because you're talking about a significant amount of money above and beyond what is the list price. In fact, I would tell you that most of the other storage providers, hyperscalers, you know, their list price, first of all, is, you know, far exceeding anything else in the industry, especially what we offer and then, right, their additional cost, the egress costs, the API requests can be two, three, 400% more on top of what you're paying per terabyte. >> So, you used a little coffee analogy earlier in our conversation, so here's what I'm imagining, like I have a lot of stuff, right? And I had to clear up my bar and I put some stuff in storage, you know, right down the street and I pay them monthly, I can't imagine having to pay them to go get my stuff, that's kind of the same thing here. >> Oh, that's a great metaphor, right? That storage locker, right? You know, can you imagine every time you want to open the door to that storage locker and look inside having to pay a fee? >> No, that would be annoying. >> Or, every time you pull into the yard and you want to put something in that storage locker, you have to pay an access fee to get to the yard, you have to pay a door opening fee, right, and then if you want to look and get an inventory of everything in there, you have to pay, and it's ridiculous, it's your data, it's your storage, it's your locker, you've already paid the annual fee, probably, 'cause they gave you a discount on that, so why shouldn't you have unfettered access to your data? That's what Wasabi does and I think as Kevin pointed out, right, that's what sets us completely apart from everybody else. >> Okay, good, that's helpful, it helps us understand how Wasabi's different. Kevin, I'm always interested when I talk to practitioners like yourself in learning what you do, you know, outside of the technology, what are you doing in terms of educating your community and making them more cyber aware? Do you have training for students and faculty to learn about security and ransomware protection, for example? >> Yes, cyber security awareness training is definitely one of the required things everyone should be doing in their organizations. And we do have a program that we use and we try to make it fun and engaging too, right, this is often the checking the box kind of activity, insurance companies require it, but we want to make it something that people want to do and want to engage with so, even last year, I think we did one around the holidays and kind of pointed out the kinds of scams they may expect in their personal life about, you know, shipping of orders and time for the holidays and things like that, so it wasn't just about protecting our school data, it's about the fact that, you know, protecting their information is something do in all aspects of your life, especially now that the folks are working hybrid often working from home with equipment from the school, the stakes are much higher and people have a lot of our data at home and so knowing how to protect that is important, so we definitely run those programs in a way that we want to be engaging and fun and memorable so that when they do encounter those things, especially email threats, they know how to handle them. >> So when you say fun, it's like you come up with an example that we can laugh at until, of course, we click on that bad link, but I'm sure you can come up with a lot of interesting and engaging examples, is that what you're talking about, about having fun? >> Yeah, I mean, sometimes they are kind of choose your own adventure type stories, you know, they stop as they run, so they're telling a story and they stop and you have to answer questions along the way to keep going, so, you're not just watching a video, you're engaged with the story of the topic, yeah, and that's what I think is memorable about it, but it's also, that's what makes it fun, you're not just watching some talking head saying, you know, to avoid shortened URLs or to check, to make sure you know the sender of the email, no, you're engaged in a real life scenario story that you're kind of following and making choices along the way and finding out was that the right choice to make or maybe not? So, that's where I think the learning comes in. >> Excellent. Okay, gentlemen, thanks so much, appreciate your time, Kevin, Drew, awesome having you in theCUBE. >> My pleasure, thank you. >> Yeah, great to be here, thanks. >> Okay, in a moment, I'll give you some closing thoughts on the changing world of data protection and the evolution of cloud object storage, you're watching theCUBE, the leader in high tech enterprise coverage. >> Announcer: Some things just don't make sense, like showing up a little too early for the big game. >> How early are we? >> Couple months. Popcorn? >> Announcer: On and off season, the Red Sox cover their bases with affordable, best in class cloud storage. >> These are pretty good seats. >> Hey, have you guys seen the line from the bathroom? >> Announcer: Wasabi Hot Cloud Storage, it just makes sense. >> You don't think they make these in left hand, do you? >> We learned today how a serial entrepreneur, along with his co-founder saw the opportunity to tap into the virtually limitless scale of the cloud and dramatically reduce the cost of storing data while at the same time, protecting against ransomware attacks and other data exposures with simple, fast storage, immutability, air gaps, and solid operational processes, let's not forget about that, okay? People and processes are critical and if you can point your people at more strategic initiatives and tasks rather than wrestling with infrastructure, you can accelerate your process redesign and support of digital transformations. Now, if you want to learn more about immutability and Object Block, click on the Wasabi resource button on this page, or go to wasabi.com/objectblock. Thanks for watching Secure Storage Hot Takes made possible by Wasabi. This is Dave Vellante for theCUBE, the leader in enterprise and emerging tech coverage, well, see you next time. (gentle upbeat music)

(upbeat music) >> Okay, we're now going to go into the customer panel. And we'd like to welcome Angelo Fausti, who's software engineer at the Vera C Rubin Observatory, and Caleb Maclachlan, who's senior spacecraft operations software engineer at Loft Orbital. Guys, thanks for joining us. You don't want to miss folks, this interview. Caleb, let's start with you. You work for an extremely cool company. You're launching satellites into space. Cause doing that is highly complex and not a cheap endeavor. Tell us about Loft Orbital and what you guys do to attack that problem? >> Yeah, absolutely. And thanks for having me here, by the way. So Loft Orbital is a company that's a series B startup now. And our mission basically is to provide rapid access to space for all kinds of customers. Historically, if you want to fly something in space, do something in space, it's extremely expensive. You need to book a launch, build a bus, hire a team to operate it, have big software teams, and then eventually worry about a lot of very specialized engineering. And what we're trying to do is, change that from a super specialized problem that has an extremely high barrier of access to a infrastructure problem. So that it's almost as simple as deploying a VM in AWS or GCP, as getting your programs, your mission deployed on orbit, with access to different sensors, cameras, radios, stuff like that. So that's kind of our mission. And just to give a really brief example of the kind of customer that we can serve. There's a really cool company called Totum labs, who is working on building an IoT constellation, for Internet of Things. Basically being able to get telemetry from all over the world. They're the first company to demonstrate indoor IoT, which means you have this little modem inside a container. A container that you track from anywhere on the world as it's going across the ocean. So it's really little. And they've been able to stay small startup that's focused on their product, which is that super crazy, complicated, cool radio, while we handle the whole space segment for them, which just, before Loft was really impossible. So that's our mission is, providing space infrastructure as a service. We are kind of groundbreaking in this area, and we're serving a huge variety of customers with all kinds of different missions, and obviously, generating a ton of data in space that we've got to handle. >> Yeah, so amazing, Caleb, what you guys do. I know you were lured to the skies very early in your career, but how did you kind of land in this business? >> Yeah, so I guess just a little bit about me. For some people, they don't necessarily know what they want to do, early in their life. For me, I was five years old and I knew, I want to be in the space industry. So I started in the Air Force, but have stayed in the space industry my whole career and been a part of, this is the fifth space startup that I've been a part of, actually. So I've kind of started out in satellites, did spend some time in working in the launch industry on rockets. Now I'm here back in satellites. And honestly, this is the most exciting of the different space startups that I've been a part of. So, always been passionate about space and basically writing software for operating in space for basically extending how we write software into orbit. >> Super interesting. Okay, Angelo. Let's talk about the Rubin Observatory Vera C. Rubin, famous woman scientists, Galaxy guru, Now you guys, the observatory are up, way up high, you're going to get a good look at the southern sky. I know COVID slowed you guys down a bit. But no doubt you continue to code away on the software. I know you're getting close. You got to be super excited. Give us the update on the observatory and your role. >> All right. So yeah, Rubin is state of the art observatory that is in construction on a remote mountain in Chile. And with Rubin we'll conduct the large survey of space and time. We are going to observe the sky with eight meter optical telescope and take 1000 pictures every night with 3.2 gigapixel camera. And we're going to do that for 10 years, which is the duration of the survey. The goal is to produce an unprecedented data set. Which is going to be about .5 exabytes of image data. And from these images will detect and measure the properties of billions of astronomical objects. We are also building a science platform that's hosted on Google Cloud, so that the scientists and the public can explore this data to make discoveries. >> Yeah, amazing project. Now, you aren't a Doctor of Philosophy. So you probably spent some time thinking about what's out there. And then you went on to earn a PhD in astronomy and astrophysics. So this is something that you've been working on for the better part of your career, isn't it? >> Yeah, that's right. About 15 years. I studied physics in college, then I got a PhD in astronomy. And I worked for about five years in another project, the Dark Energy survey before joining Rubin in 2015. >> Yeah, impressive. So it seems like both your organizations are looking at space from two different angles. One thing you guys both have in common, of course, is software. And you both use InfluxDB as part of your data infrastructure. How did you discover InfluxDB, get into it? How do you use the platform? Maybe Caleb, you can start. >> Yeah, absolutely. So the first company that I extensively used InfluxDB in was a launch startup called Astra. And we were in the process of designing our first generation rocket there and testing the engines, pumps. Everything that goes into a rocket. And when I joined the company, our data story was not very mature. We were collecting a bunch of data in LabVIEW. And engineers were taking that over to MATLAB to process it. And at first, that's the way that a lot of engineers and scientists are used to working. And at first that was, like, people weren't entirely sure that, that needed to change. But it's something, the nice thing about InfluxDB is that, it's so easy to deploy. So our software engineering team was able to get it deployed and up and running very quickly and then quickly also backport all of the data that we've collected thus far into Influx. And what was amazing to see and it's kind of the super cool moment with Influx is, when we hooked that up to Grafana, Grafana, is the visualization platform we use with influx, because it works really well with it. There was like this aha moment of our engineers who are used to this post process kind of method for dealing with their data, where they could just almost instantly, easily discover data that they hadn't been able to see before. And take the manual processes that they would run after a test and just throw those all in Influx and have live data as tests were coming. And I saw them implementing crazy rocket equation type stuff in Influx and it just was totally game changing for how we tested. And things that previously it would be like run a test, then wait an hour for the engineers to crunch the data and then we run another test with some changed parameters or a changed startup sequence or something like that, became, by the time the test is over, the engineers know what the next step is, because they have this just like instant game changing access to data. So since that experience, basically everywhere I've gone, every company since then, I've been promoting InfluxDB and using it and spinning it up and quickly showing people how simple and easy it is. >> Yeah, thank you. So Angelo, I was explaining in my open that, you know you could add a column in a traditional RDBMS and do time series. But with the volume of data that you're talking about in the example that Caleb just gave, you have to have a purpose built time series database. Where did you first learn about InfluxDB? >> Yeah, correct. So I worked with the data management team and my first project was the record metrics that measure the performance of our software. The software that we use to process the data. So I started implementing that in our relational database. But then I realized that in fact, I was dealing with time series data. And I should really use a solution built for that. And then I started looking at time series databases and I found InfluxDB, that was back in 2018. Then I got involved in another project. To record telemetry data from the telescope itself. It's very challenging because you have so many subsystems and sensors, producing data. And with that data, the goal is to look at the telescope harder in real time so we can make decisions and make sure that everything's doing the right thing. And another use for InfluxDB that I'm also interested, is the visits database. If you think about the observations, we are moving the telescope all the time and pointing to specific directions in the sky and taking pictures every 30 seconds. So that itself is a time series. And every point in the time series, we call that visit. So we want to record the metadata about those visits in InfluxDB. That time series is going to be 10 years long, with about 1000 points every night. It's actually not too much data compared to the other problems. It's really just the different time scale. So yeah, we have plans on continuing using InfluxDB and finding new applications in the project. >> Yeah and the speed with which you can actually get high quality images. Angelo, my understanding is, you use InfluxDB, as you said, you're monitoring the telescope hardware and the software. And just say, some of the scientific data as well. The telescope at the Rubin Observatory is like, no pun intended, I guess, the star of the show. And I believe, I read that it's going to be the first of the next gen telescopes to come online. It's got this massive field of view, like three orders of magnitude times the Hubble's widest camera view, which is amazing. That's like 40 moons in an image, and amazingly fast as well. What else can you tell us about the telescope? >> Yeah, so it's really a challenging project, from the point of view of engineering. This telescope, it has to move really fast. And it also has to carry the primary mirror, which is an eight meter piece of glass, it's very heavy. And it has to carry a camera, which is about the size of a small car. And this whole structure weighs about 300 pounds. For that to work, the telescope needs to be very compact and stiff. And one thing that's amazing about its design is that the telescope, this 300 tons structure, it sits on a tiny film of oil, which has the diameter of human hair, in that brings an almost zero friction interface. In fact, a few people can move this enormous structure with only their hands. As you said, another aspect that makes this telescope unique is the optical design. It's a wide field telescope. So each image has, in diameter, the size of about seven full moons. And with that we can map the entire sky in only three days. And of course, during operations, everything's controlled by software, and it's automatic. There's a very complex piece of software called the scheduler, which is responsible for moving the telescope and the camera. Which will record the 15 terabytes of data every night. >> And Angelo, all this data lands in InfluxDB, correct? And what are you doing with all that data? >> Yeah, actually not. So we're using InfluxDB to record engineering data and metadata about the observations, like telemetry events and the commands from the telescope. That's a much smaller data set compared to the images. But it is still challenging because you have some high frequency data that the system needs to keep up and we need to store this data and have it around for the lifetime of the project. >> Hm. So at the mountain, we keep the data for 30 days. So the observers, they use Influx and InfluxDB instance, running there to analyze the data. But we also replicate the data to another instance running at the US data facility, where we have more computational resources and so more people can look at the data without interfering with the observations. Yeah, I have to say that InfluxDB has been really instrumental for us, and especially at this phase of the project where we are testing and integrating the different pieces of hardware. And it's not just the database, right. It's the whole platform. So I like to give this example, when we are doing this kind of task, it's hard to know in advance which dashboards and visualizations you're going to need, right. So what you really need is a data exploration tool. And with tools like chronograph, for example, having the ability to query and create dashboards on the fly was really a game changer for us. So astronomers, they typically are not software engineers, but they are the ones that know better than anyone, what needs to be monitored. And so they use chronograph and they can create the dashboards and the visualizations that they need. >> Got it. Thank you. Okay, Caleb, let's bring you back in. Tell us more about, you got these dishwasher size satellites are kind of using a multi tenant model. I think it's genius. But tell us about the satellites themselves. >> Yeah, absolutely. So we have in space, some satellites already. That, as you said, are like dishwasher, mini fridge kind of size. And we're working on a bunch more that are a variety of sizes from shoe box to I guess, a few times larger than what we have today. And it is, we do shoot to have, effectively something like a multi tenant model where we will buy a bus off the shelf, the bus is, what you can kind of think of as the core piece of the satellite, almost like a motherboard or something. Where it's providing the power, it has the solar panels, it has some radios attached to it, it handles the altitude control, basically steers the spacecraft in orbit. And then we build, also in house, what we call our payload hub, which is has all any customer payloads attached, and our own kind of edge processing sort of capabilities built into it. And so we integrate that, we launch it, and those things, because they're in low Earth orbit, they're orbiting the Earth every 90 minutes. That's seven kilometers per second, which is several times faster than a speeding bullet. So we've got, we have one of the unique challenges of operating spacecraft in lower Earth orbit is that generally you can't talk to them all the time. So we're managing these things through very brief windows of time. Where we get to talk to them through our ground sites, either in Antarctica or in the North Pole region. So we'll see them for 10 minutes, and then we won't see them for the next 90 minutes as they zip around the Earth collecting data. So one of the challenges that exists for a company like ours is, that's a lot of, you have to be able to make real time decisions operationally, in those short windows that can sometimes be critical to the health and safety of the spacecraft. And it could be possible that we put ourselves into a low power state in the previous orbit or something potentially dangerous to the satellite can occur. And so as an operator, you need to very quickly process that data coming in. And not just the the live data, but also the massive amounts of data that were collected in, what we call the back orbit, which is the time that we couldn't see the spacecraft. >> We got it. So talk more about how you use InfluxDB to make sense of this data from all those tech that you're launching into space. >> Yeah, so we basically, previously we started off, when I joined the company, storing all of that, as Angelo did, in a regular relational database. And we found that it was so slow, and the size of our data would balloon over the course of a couple of days to the point where we weren't able to even store all of the data that we were getting. So we migrated to InfluxDB to store our time series telemetry from the spacecraft. So that thing's like power level voltage, currents counts, whatever metadata we need to monitor about the spacecraft, we now store that in InfluxDB. And that has, you know, now we can actually easily store the entire volume of data for the mission life so far, without having to worry about the size bloating to an unmanageable amount. And we can also seamlessly query large chunks of data, like if I need to see, for example, as an operator, I might want to see how my battery state of charge is evolving over the course of the year, I can have a plot in an Influx that loads that in a fraction of a second for a year's worth of data, because it does, you know, intelligent. I can intelligently group the data by citing time interval. So it's been extremely powerful for us to access the data. And as time has gone on, we've gradually migrated more and more of our operating data into Influx. So not only do we store the basic telemetry about the bus and our payload hub, but we're also storing data for our customers, that our customers are generating on board about things like you know, one example of a customer that's doing something pretty cool. They have a computer on our satellite, which they can reprogram themselves to do some AI enabled edge compute type capability in space. And so they're sending us some metrics about the status of their workloads, in addition to the basics, like the temperature of their payload, their computer or whatever else. And we're delivering that data to them through Influx in a Grafana dashboard that they can plot where they can see, not only has this pipeline succeeded or failed, but also where was the spacecraft when this occurred? What was the voltage being supplied to their payload? Whatever they need to see, it's all right there for them. Because we're aggregating all that data in InfluxDB. >> That's awesome. You're measuring everything. Let's talk a little bit about, we throw this term around a lot, data driven. A lot of companies say, Oh, yes, we're data driven. But you guys really are. I mean, you got data at the core. Caleb, what does that what does that mean to you? >> Yeah, so you know, I think, the clearest example of when I saw this, be like totally game changing is, what I mentioned before it, at Astra, were our engineers feedback loop went from a lot of, kind of slow researching, digging into the data to like an instant, instantaneous, almost, Seeing the data, making decisions based on it immediately, rather than having to wait for some processing. And that's something that I've also seen echoed in my current role. But to give another practical example, as I said, we have a huge amount of data that comes down every orbit, and we need to be able to ingest all that data almost instantaneously and provide it to the operator in near real time. About a second worth of latency is all that's acceptable for us to react to. To see what is coming down from the spacecraft and building that pipeline is challenging, from a software engineering standpoint. Our primary language is Python, which isn't necessarily that fast. So what we've done is started, in the in the goal being data driven, is publish metrics on individual, how individual pieces of our data processing pipeline, are performing into Influx as well. And we do that in production as well as in dev. So we have kind of a production monitoring flow. And what that has done is, allow us to make intelligent decisions on our software development roadmap. Where it makes the most sense for us to focus our development efforts in terms of improving our software efficiency, just because we have that visibility into where the real problems are. At sometimes we've found ourselves, before we started doing this, kind of chasing rabbits that weren't necessarily the real root cause of issues that we were seeing. But now, that we're being a bit more data driven, there, we are being much more effective in where we're spending our resources and our time, which is especially critical to us as we scaled from supporting a couple of satellites to supporting many, many satellites at once. >> So you reduce those dead ends. Maybe Angela, you could talk about what sort of data driven means to you and your team? >> Yeah, I would say that having real time visibility, to the telemetry data and metrics is crucial for us. We need to make sure that the images that we collect, with the telescope have good quality and that they are within the specifications to meet our science goals. And so if they are not, we want to know that as soon as possible, and then start fixing problems. >> Yeah, so I mean, you think about these big science use cases, Angelo. They are extremely high precision, you have to have a lot of granularity, very tight tolerances. How does that play into your time series data strategy? >> Yeah, so one of the subsystems that produce the high volume and high rates is the structure that supports the telescope's primary mirror. So on that structure, we have hundreds of actuators that compensate the shape of the mirror for the formations. That's part of our active updated system. So that's really real time. And we have to record this high data rates, and we have requirements to handle data that are a few 100 hertz. So we can easily configure our database with milliseconds precision, that's for telemetry data. But for events, sometimes we have events that are very close to each other and then we need to configure database with higher precision. >> um hm For example, micro seconds. >> Yeah, so Caleb, what are your event intervals like? >> So I would say that, as of today on the spacecraft, the event, the level of timing that we deal with probably tops out at about 20 hertz, 20 measurements per second on things like our gyroscopes. But I think the core point here of the ability to have high precision data is extremely important for these kinds of scientific applications. And I'll give you an example, from when I worked on the rockets at Astra. There, our baseline data rate that we would ingest data during a test is 500 hertz, so 500 samples per second. And in some cases, we would actually need to ingest much higher rate data. Even up to like 1.5 kilohertz. So extremely, extremely high precision data there, where timing really matters a lot. And, I can, one of the really powerful things about Influx is the fact that it can handle this, that's one of the reasons we chose it. Because there's times when we're looking at the results of firing, where you're zooming in. I've talked earlier about how on my current job, we often zoom out to look at a year's worth of data. You're zooming in, to where your screen is preoccupied by a tiny fraction of a second. And you need to see, same thing, as Angelo just said, not just the actual telemetry, which is coming in at a high rate, but the events that are coming out of our controllers. So that can be something like, hey, I opened this valve at exactly this time. And that goes, we want to have that at micro or even nanosecond precision, so that we know, okay, we saw a spike in chamber pressure at this exact moment, was that before or after this valve open? That kind of visibility is critical in these kinds of scientific applications and absolutely game changing, to be able to see that in near real time. And with a really easy way for engineers to be able to visualize this data themselves without having to wait for us software engineers to go build it for them. >> Can the scientists do self serve? Or do you have to design and build all the analytics and queries for scientists? >> I think that's absolutely from my perspective, that's absolutely one of the best things about Influx, and what I've seen be game changing is that, generally, I'd say anyone can learn to use Influx. And honestly, most of our users might not even know they're using Influx. Because the interface that we expose to them is Grafana, which is generic graphing, open source graphing library that is very similar to Influx zone chronograph. >> Sure. >> And what it does is, it provides this, almost, it's a very intuitive UI for building your query. So you choose a measurement, and it shows a drop down of available measurements, and then you choose the particular field you want to look at. And again, that's a drop down. So it's really easy for our users to discover it. And there's kind of point and click options for doing math, aggregations. You can even do like, perfect kind of predictions all within Grafana. The Grafana user interface, which is really just a wrapper around the API's and functionality that Influx provides. So yes, absolutely, that's been the most powerful thing about it, is that it gets us out of the way, us software engineers, who may not know quite as much as the scientists and engineers that are closer to the interesting math. And they build these crazy dashboards that I'm just like, wow, I had no idea you could do that. I had no idea that, that is something that you would want to see. And absolutely, that's the most empowering piece. >> Yeah, putting data in the hands of those who have the context, the domain experts is key. Angelo is it the same situation for you? Is it self serve? >> Yeah, correct. As I mentioned before, we have the astronomers making their own dashboards, because they know exactly what they need to visualize. And I have an example just from last week. We had an engineer at the observatory that was building a dashboard to monitor the cooling system of the entire building. And he was familiar with InfluxQL, which was the primarily query language in version one of InfluxDB. And he had, that was really a challenge because he had all the data spread at multiple InfluxDB measurements. And he was like doing one query for each measurement and was not able to produce what he needed. And then, but that's the perfect use case for Flux, which is the new data scripting language that Influx data developed and introduced as the main language in version two. And so with Flux, he was able to combine data from multiple measurements and summarize this data in a nice table. So yeah, having more flexible and powerful language, also allows you to make better a visualization. >> So Angelo, where would you be without time series database, that technology generally, may be specifically InfluxDB, as one of the leading platforms. Would you be able to do this? >> Yeah, it's hard to imagine, doing what we are doing without InfluxDB. And I don't know, perhaps it would be just a matter of time to rediscover InfluxDB. >> Yeah. How about you Caleb? >> Yeah, I mean, it's all about using the right tool for the job. I think for us, when I joined the company, we weren't using InfluxDB and we were dealing with serious issues of the database growing to a an incredible size, extremely quickly. And being unable to, like even querying short periods of data, was taking on the order of seconds, which is just not possible for operations. So time series database is, if you're dealing with large volumes of time series data, Time series database is the right tool for the job and Influx is a great one for it. So, yeah, it's absolutely required to use for this kind of data, there is not really any other option. >> Guys, this has been really informative. It's pretty exciting to see, how the edge is mountain tops, lower Earth orbits. Space is the ultimate edge. Isn't it. I wonder if you could two questions to wrap here. What comes next for you guys? And is there something that you're really excited about? That you're working on. Caleb, may be you could go first and than Angelo you could bring us home. >> Yeah absolutely, So basically, what's next for Loft Orbital is more, more satellites a greater push towards infrastructure and really making, our mission is to make space simple for our customers and for everyone. And we're scaling the company like crazy now, making that happen. It's extremely exciting and extremely exciting time to be in this company and to be in this industry as a whole. Because there are so many interesting applications out there. So many cool ways of leveraging space that people are taking advantage of and with companies like SpaceX, now rapidly lowering cost of launch. It's just a really exciting place to be in. And we're launching more satellites. We're scaling up for some constellations and our ground system has to be improved to match. So there is a lot of improvements that we are working on to really scale up our control systems to be best in class and make it capable of handling such large workloads. So, yeah. What's next for us is just really 10X ing what we are doing. And that's extremely exciting. >> And anything else you are excited about? Maybe something personal? Maybe, you know, the titbit you want to share. Are you guys hiring? >> We're absolutely hiring. So, we've positions all over the company. So we need software engineers. We need people who do more aerospace specific stuff. So absolutely, I'd encourage anyone to check out the Loft Orbital website, if this is at all interesting. Personal wise, I don't have any interesting personal things that are data related. But my current hobby is sea kayaking, so I'm working on becoming a sea kayaking instructor. So if anyone likes to go sea kayaking out in the San Francisco Bay area, hopefully I'll see you out there. >> Love it. All right, Angelo, bring us home. >> Yeah. So what's next for us is, we're getting this telescope working and collecting data and when that's happened, it's going to be just a delish of data coming out of this camera. And handling all that data, is going to be a really challenging. Yeah, I wonder I might not be here for that I'm looking for it, like for next year we have an important milestone, which is our commissioning camera, which is a simplified version of the full camera, is going to be on sky and so most of the system has to be working by then. >> Any cool hobbies that you are working on or any side project? >> Yeah, actually, during the pandemic I started gardening. And I live here in Two Sun, Arizona. It gets really challenging during the summer because of the lack of water, right. And so, we have an automatic irrigation system at the farm and I'm trying to develop a small system to monitor the irrigation and make sure that our plants have enough water to survive. >> Nice. All right guys, with that we're going to end it. Thank you so much. Really fascinating and thanks to InfluxDB for making this possible. Really ground breaking stuff, enabling value at the edge, in the cloud and of course beyond, at the space. Really transformational work, that you guys are doing. So congratulations and I really appreciate the broader community. I can't wait to see what comes next from this entire eco system. Now in the moment, I'll be back to wrap up. This is Dave Vallante. And you are watching The cube, the leader in high tech enterprise coverage. (upbeat music)

>>Hi, buddy. Welcome back to the keeps coverage of AWS 2021. Re-invent you're watching the cube and I'm really excited. We're going to go outside the storage box. I like to say with my lawn Thompson Bukovac, who's the vice-president of block and object storage and Wayne Duso was a VP of storage edge and data governance guys. Great to see you again, we saw you at storage day, the 15 year anniversary of AWS, of course, the first product service ever. So awesome to be here. Isn't it. Wow. >>So much energy in the room. It's so great to see customers learning from each other, learning from AWS, learning from the things that you're observing as well. >>A lot of companies decided not to do physical events. I think you guys are on the right side of history. We're going to show you, you weren't exactly positive. How many people are going to show up. Everybody showed. I mean, it's packed house here, so >>Number 10. Yeah. >>All right. So let's get right into it. Uh, news of the week. >>So much to say, when you want to kick this off, >>We had a, we had a great set of announcements that Milan, uh, talked about yesterday, uh, in her talk and, and a couple of them in the file space, specifically a new, uh, member of the FSX family. And if you remember that the FSA, Amazon FSX is, uh, for customers who want to run fully managed versions of third party and open source file systems on AWS. And so yesterday we announced a new member it's FSX for open ZFS. >>Okay, cool. And there's more, >>Well, there's more, I mean, one of the great things about the new match file service world and CFS is it's powered by gravity. >>It is taught by Gravatar and all of the capabilities that AWS brings in terms of networking, storage, and compute, uh, to our customers. >>So this is really important. I want the audience to understand this. So I I've talked on the cube about how a large proportion let's call it. 30% of the CPU cycles are kind of wasted really on things like offloads, and we could be much more efficient, so graviton much more efficient, lower power and better price performance, lower cost. Amazon is now on a new curve, uh, cycles are faster for processors, and you can take advantage of that in storage it's storage users, compute >>That's right? In fact, you have that big launch as well for luster, with gravity. >>We did in fact, uh, so with, with, uh, Yasmin of open CFS, we also announced the next gen Lustre offering. And both of these offerings, uh, provide a five X improvement in performance. For example, now with luster, uh, customers can drive up to one terabyte per second of throughput, which is simply amazing. And with open CFS, right out of, right out of the box at GA a million IOPS at sub-millisecond latencies taking advantage of gravitas, taking advantage of our storage and networking capabilities. >>Well, I guess it's for HPC workloads, but what's the difference between these days HPC, big data, data intensive, a lot of AI stuff, >>All right. You to just, there's a lot of intersection between all of those different types of workloads they have, as you said, and you know, it all, it all depends on it all matters. And this is the reason why having the suite of capabilities that the, if you would, the members of the family is so important to our guests. >>We've talked a lot about, it's really can't think about traditional storage as a traditional storage anymore. And certainly your world's not a box. It's really a data platform, but maybe you could give us your point of view on that. >>Yeah, I think, you know, if, if we look, if we take a step back and we think about how does AWS do storage? Uh, we think along multiple dimensions, we have the dimension that Wayne's talking about, where you bring together the power of compute and storage for these managed file services that are so popular. You and I talked about, um, NetApp ONTAP. Uh, we went into some detail on that with you as well, and that's been enormously popular. And so that whole dimension of these managed file services is all about where is the customer today and how can we help them get to the cloud? But then you think about the other things that we're also imagining, and we're, re-imagining how customers want to grow those applications and scale them. And so a great example here at reinvent is let's just take the concept of archive. >>So many people, when they think about archive, they think about taking that piece of data and putting it away on tape, putting it away in a closet somewhere, never pulling it out. We don't think about archive like that archive just happens to be data that you just aren't using at the moment, but when you need it, you need it right away. And that's why we built a new storage class that we launched just yesterday, Dave, and it's called glacier instead of retrieval, it has retrieval and milliseconds, just like an Esri storage class has the same pricing of four tenths of a cent as glacier archive. >>So what's interesting at the analyst event today, Adam got a question about, and somebody was poking at him, you know, analysts can be snarky sometimes about, you know, price, declines and so forth. And he said, you know, one of the, one of the things that's not always shown up and we don't always get credit for lowering prices, but we might lower costs. And there's the archive and deep archive is an example of that. Maybe you could explain that point of view. >>Yeah. The way we look at it is that our customers, when they talk to us about the cost of storage, they talked to us about the total cost of the storage, and it's not just storing the data, it's retrieving it and using it. And so we have done an amazing amount across all the portfolio around reducing costs. We have glacier answer retrieval, which is 68% cheaper than standard infrequent access. That's a big cost reduction. We have EBS snapshots archive, which we introduced yesterday, 75% cheaper to archive a snapshot. And these are the types of that just transform the total cost. And in some cases we just eliminate costs. And so the glacier storage class, all bulk retrievals of data from the glacier storage class five to 12 hours, it's now free of charge. If you don't even have to think about, we didn't even reduce it. We just eliminated the cost of that data retrieval >>And additive to what Milan said around, uh, archiving. If you look at what we've done throughout the entire year, you know, a interesting statistic that was brought up yesterday is over the course of 2021, between our respective teams, we've launched over 105 capabilities for our customers throughout this year. And in some of them, for instance, on the file side for EFS, we launched one zone which reduced, uh, customer costs by 47%. Uh, you can now achieve on EFS, uh, cost of roughly 4.30 cents per gigabyte month on, uh, FSX, we've reduced costs up to 92%, uh, on Lustre and FSX for windows and with the introduction of ONTAP and open CFS, we continue those forward, including customers ability to compress and Dedoose against those costs. So they ended up seeing a considerable savings, even over what our standard low prices are. >>100 plus, what can I call them releases? And how can you categorize those? Are they features of eight? Do they fall into, >>Because they range for major services, like what we've launched with open ZFS to major features and really 95 of those were launched before re-invent. And so really what you have between the different teams that work in storage is you have this relentless drive to improve all the storage platforms. And we do it all across the course of the year, all across the course of the year. And in some cases, the benefit shows up at no cost at all to a customer. >>Uh, how, how did this, it seems like you're on an accelerated pace, a S3 EBS, and then like hundreds of services. I guess the question is how come it took so long and how is it accelerating now? Is it just like, there was so much focus on compute before you had to get that in place, or, but now it's just rapidly accessing, >>I I'll tell you, Dave, we took the time to count this year. And so we came to you with this number of 106, uh, that acceleration has been in place for many years. We just didn't take the time to couch. Correct. So this has been happening for years and years. Wayne and I have been with AWS for, for a long time now for 10 plus years. And really that velocity that we're talking about right now that has been happening every single year, which is where you have storage today. And I got to tell you, innovation is in our DNA and we are not going to stop now >>So 10 years. Okay. So it was really, the first five years was kind of slow. And then >>I think that's true at all. I don't think that try, you know, if you, if you look at, uh, the services that we have, we have the most complete portfolio of any cloud provider when it comes to storage and data. And so over the years, we've added to the foundation, which is S3 and the foundation, which is EBS. We've come out with a number of storage services in the, in the file space. Now you have an entire suite of persistent data stores within AWS and the teams behind those that are able to accelerate that pace. Just to give you an example, when I joined 10 years ago, AWS launched within that year, roughly a hundred and twenty, a hundred and twenty eight services or features our teams together this year have launched almost that many, just in those in, just in this space. So AWS continues to accelerate the storage teams continue to accelerate. And as my line said, we just started counting >>The thing. And if you think about those first five years, that was laying the baseline to launch us three, to launch EBS, to get that foundation in place, get lifecycle policies in place. But really, I think you're just going to see an even faster acceleration that number's going up. >>No, I that's what I'm saying. It does appear that way. And you had to build a team and put teams in place. And so that's, you know, part of the equation. But again, I come back to, it's not even, I don't even think of it as storage anymore. It's it's data. People are data lake is here to stay. You might not like the term. We always use the joke about a data ocean, but data lake is here to say 200,000 data lakes. Now we heard Adam talk about, uh, this morning. I think it was Adam. No, it was Swami. Do you want a thousand data lakes in your customer base now? And people are adding value to that data in new ways, injecting machine intelligence, you know, SageMaker is a big piece of that. Tying it in. I know a lot of customers are using glue as catalogs and which I'm like, wow, is glue a catalog or, I mean, it's just so flexible. So what are you seeing customers do with that base of data now and driving new business value? Because I've said last decade plus has been about it transformation. And now we're seeing business transformation. Maybe you could talk about that a little bit. >>Well, the base of every data lake is going to be as three yesterday has over 200 trillion objects. Now, Dave, and if you think about that, if you took every person on the planet, each of those people would have 26,000 S3 objects. It's gotten that big. And you know, if you think about the base of data with 200 trillion plus objects, really the opportunity for innovation is limitless. And you know, a great example for that is it's not just business value. It's really the new customer experiences that our customers are inventing the NFL. Uh, they, you know, they have that application called digital athlete where, you know, they started off with 10,000 labeled images or up to 20,000 labeled images now. And they're all using it to drive machine learning models that help predict and support the players on the field when they start to see things unfold that might cause injury. That is a brand new experience. And it's only possible with vast amounts of data >>Additive to when my line said, we're, we're in you talk about business transformation. We are in the age of data and we represent storage services. But what we really represent is what our customers hold one of their most valuable assets, which is their data. And that set of data is only growing. And the ability to use that data, to leverage that data for value, whether it's ML training, whether it's analytics, that's only accelerated, this is the feedback we get from our customers. This is where these features and new capabilities come from. So that's, what's really accelerating our pace >>Guys. I wish we had more time. I'd have to have you back because we're on a tight clock here, but, um, so great to see you both especially live. I hope we get to do more of this in 2022. I'm an optimist. Okay. And keep it right there, everybody. This is Dave Volante for the cube you're leader in live tech coverage, right back.

(innovative music) >> Welcome back to theCUBE's continuous coverage of AWS re:Invent 2021. My name is Dave Vellante, and we are running one of the industry's most important and largest hybrid tech events of the year. Hybrid as in physical, not a lot of that going on this year. But we're here with the AWS ecosystem, AWS, and special thanks to AMD for supporting this year's editorial coverage of the event. We've got two live sets, two remote studios, more than a hundred guests on the program. We're going really deep, as we enter the next decade of Cloud innovation. We're super excited to be joined by Danny Allan, who's the Chief Technology Officer at Veeam, and James Kirschner who's the Engineering Director for Amazon S3. Guys, great to see you. >> Great to see you as well, Dave. >> Thanks for having me. >> So let's kick things off. Veeam and AWS, you guys have been partnering for a long time. Danny, where's the focus at this point in time? What are customers telling you they want you to solve for? And then maybe James, you can weigh in on the problems that customers are facing, and the opportunities that they see ahead. But Danny, why don't you start us off? >> Sure. So we hear from our customers a lot that they certainly want the solutions that Veeam is bringing to market, in terms of data protection. But one of the things that we're hearing is they want to move to Cloud. And so there's a number of capabilities that they're asking us for help with. Things like S3, things like EC2, and RDS. And so over the last, I'll say four or five years, we've been doing more and more together with AWS in, I'll say, two big categories. One is, how do we help them send their data to the Cloud? And we've done that in a very significant way. We support obviously tiering data into S3, but not just S3. We support S3, and S3 Glacier, and S3 Glacier Deep Archive. And more importantly than ever, we do it with immutability because customers are asking for security. So a big category of what we're working on is making sure that we can store data and we can do it securely. Second big category that we get asked about is "Help us to protect the Cloud-Native Workloads." So they have workloads running in EC2 and RDS, and EFS, and EKS, and all these different services knowing Cloud-Native Data Protection. So we're very focused on solving those problems for our customers. >> You know, James, it's interesting. I was out at the 15th anniversary of S3 in Seattle, in September. I was talking to Mai-Lan. Remember we used to talk about gigabytes and terabytes, but things have changed quite dramatically, haven't they? What's your take on this topic? >> Well, they sure have. We've seen the exponential growth data worldwide and that's made managing backups more difficult than ever before. We're seeing traditional methods like tape libraries and secondary sites fall behind, and many organizations are moving more and more of their workloads to the Cloud. They're extending backup targets to the Cloud as well. AWS offers the most storage services, data transfer methods and networking options with unmatched durability, security and affordability. And customers who are moving their Veeam Backups to AWS, they get all those benefits with a cost-effective offsite storage platform. Providing physical separation from on-premises primary data with pay-as-you-go economics, no upfront fees or capital investments, and near zero overhead to manage. AWS and APM partners like Veeam are helping to build secure, efficient, cost-effective backup, and restore solutions using the products you know and trust with the scale and reliability of the AWS Cloud. >> So thank you for that. Danny, I remember I was way back in the old days, it was a VeeamON physical event. And I remember kicking around and seeing this company called Kasten. And I was really interested in like, "You protect the containers, aren't they ephemeral?" And we started to sort of chit-chat about how that's going to change and what their vision was. Well, back in 2020, you purchased Kasten, you formed the Veeam KBU- the Kubernetes Business Unit. What was the rationale behind that acquisition? And then James, I'm going to get you to talk a little bit about modern apps. But Danny, start with the rationale behind the Kasten acquisition. >> Well, one of the things that we certainly believe is that the next generation of infrastructure is going to be based on containers, and there's a whole number of reasons for that. Things like scalability and portability. And there's a number of significant value-adds. So back in October of last year in 2020, as you mentioned, we acquired Kasten. And since that time we've been working through Kasten and from Veeam to add more capabilities and services around AWS. For example, we supported the Bottlerocket launch they just did and actually EKS anywhere. And so we're very focused on making sure that our customers can protect their data no matter whether it's a Kubernetes cluster, or whether it's on-premises in a data center, or if it's running up in the Cloud in EC2. We give this consistent data management experience and including, of course, the next generation of infrastructure that we believe will be based on containers. >> Yeah. You know, James, I've always noted to our audience that, "Hey AWS, they provide rich set of primitives and API's that ISV's like Veeam can take advantage of it." But I wonder if you could talk about your perspective, maybe what you're seeing in the ecosystem, maybe comment on what Veeam's doing. Specifically containers, app modernization in the Cloud, the evolution of S3 to support all these trends. >> Yeah. Well, it's been great to see Veeam expands for more and more AWS services to help joint customers protect their data. Especially since Veeam stores their data in Amazon S3 storage classes. And over the last 15 years, S3 has helped companies around the world optimize their work, so I'd be happy to share some insights into that with you today. When you think about S3 well, you can find virtually every use case across all industries running on S3. That ranges from backup, to (indistinct) data, to machine learning models, the list goes on and on. And one of the reasons is because S3 provides industry leading scalability, availability, durability, security, and performance. Those are characteristics customers want. To give you some examples, S3 stores exabytes the data across millions of hard drives, trillions of objects around the world and regularly peaks at millions of requests per second. S3 can process in a single region over 60 terabytes a second. So in summary, it's a very powerful storage offering. >> Yeah, indeed. So you guys always talking about, you know, working backwards, the customer centricity. I think frankly that AWS sort of change the culture of the entire industry. So, let's talk about customers. Danny do you have an example of a joint customer? Maybe how you're partnering with AWS to try to address some of the challenges in data protection. What are customers is seeing today? >> Well, we're certainly seeing that migration towards the Cloud as James alluded today. And actually, if we're talking about Kubernetes, actually there's a customer that I know of right now, Leidos. They're a fortune 500 Information Technology Company. They deal in the engineering and technology services space, and focus on highly regulated industry. Things like defense and intelligence in the civil space. And healthcare in these very regulated industries. Anyway, they decided to make a big investment in continuous integration, continuous development. There's a segment of the industry called portable DevSecOps, and they wanted to build infrastructure as code that they could deploy services, not in days or weeks or months, but they literally wanted to deploy their services in hours. And so they came to us, and with Kasten K10 actually around Kubernetes, they created a service that could enable them to do that. So they could be fully compliant, and they could deliver the services in, like I say, hours, not days or months. And they did that all while delivering the same security that they need in a cost-effective way. So it's been a great partnership, and that's just one example. We see these all the time, customers who want to combine the power of Kubernetes with the scale of the Cloud from AWS, with the data protection that comes from Veeam. >> Yes, so James, you know at AWS you don't get dinner if you don't have a customer example. So maybe you could share one with us. >> Yeah. We do love working backwards from customers and Danny, I loved hearing that story. One customer leveraging Veeam and AWS is Maritz. Maritz provides business performance solutions that connect people to results, ensuring brands deliver on their customer promises and drive growth. Recently Maritz moved over a thousand VM's and petabytes of data into AWS, using Veeam. Veeam Backup for AWS enables Maritz to protect their Amazon EC2 instances with the backup of the data in the Amazon S3 for highly available, cost-effective, long-term storage. >> You know, one of the hallmarks of Cloud is strong ecosystem. I see a lot of companies doing sort of their own version of Cloud. I always ask "What's the partner ecosystem look like?" Because that is a fundamental requirement, in my view anyway, and attribute. And so, a big part of that, Danny, is channel partners. And you have a 100 percent channel model. And I wonder if we could talk about your strategy in that regard. Why is it important to be all channel? How to consulting partners fit into the strategy? And then James, I'm going to ask you what's the fit with the AWS ecosystem. But Danny, let's start with you. >> Sure, so one of the things that we've learned, we're 15 years old as well, actually. I think we're about two months older, or younger I should say than AWS. I think their birthday was in August, ours was in October. But over that 15 years, we've learned that our customers enjoy the services, and support, and expertise that comes from the channel. And so we've always been a 100 percent channel company. And so one of the things that we've done with AWS is to make sure that our customers can purchase both how and when they want through the AWS marketplace. They have a program called Consulting Partners Private Agreements, or CPPO, I think is what it's known as. And that allows our customers to consume through the channel, but with the terms and bill that they associate with AWS. And so it's a new route-to-market for us, but we continue to partner with AWS in the channel programs as well. >> Yeah. The marketplace is really impressive. James, I wonder if you could maybe add in a little bit. >> Yeah. I think Danny said it well, AWS marketplace is a sales channel for ISV's and consulting partners. It lets them sell their solutions to AWS customers. And we focus on making it really easy for customers to find, buy, deploy, and manage software solutions, including software as a service in just a matter of minutes. >> Danny, you mentioned you're 15 years old. The first time I mean, the name Veeam. The brilliance of tying it to virtualization and VMware. I was at a VMUG when I first met you guys and saw your ascendancy tied to virtualization. And now you're obviously leaning heavily into the Cloud. You and I have talked a lot about the difference between just wrapping your stack in a container and hosting it in the Cloud versus actually taking advantage of Cloud-Native Services to drive further innovation. So my question to you is, where does Veeam fit on that spectrum, and specifically what Cloud-Native Services are you leveraging on AWS? And maybe what have been some outcomes of those efforts, if in fact that's what you're doing? And then James, I have a follow-up for you. >> Sure. So the, the outcomes clearly are just more success, more scale, more security. All the things that James is alluding to, that's true for Veeam it's true for our customers. And so if you look at the Cloud-Native capabilities that we protect today, certainly it began with EC2. So we run things in the Cloud in EC2, and we wanted to protect that. But we've gone well beyond that today, we protect RDS, we protect EFS- Elastic File Services. We talked about EKS- Elastic Kubernetes Services, ECS. So there's a number of these different services that we protect, and we're going to continue to expand on that. But the interesting thing is in all of these, Dave, when we do data protection, we're sending it to S3, and we're doing all of that management, and tiering, and security that our customers know and love and expect from Veeam. And so you'll continue to see these types of capabilities coming from Veeam as we go forward. >> Thank you for that. So James, as we know S3- very first service offered in 2006 on the AWS' Cloud. As I said, theCUBE was out in Seattle, September. It was a great, you know, a little semi-hybrid event. But so over the decade and a half, you really expanded the offerings quite dramatically. Including a number of, you got on-premise services things, like Outposts. You got other services with "Wintery" names. How have you seen partners take advantage of those services? Is there anything you can highlight maybe that Veeam is doing that's notable? What can you share? >> Yeah, I think you're right to call out that growth. We have a very broad and rich set of features and services, and we keep growing that. Almost every day there's a new release coming out, so it can be hard to keep up with. And Veeam has really been listening and innovating to support our joint customers. Like Danny called out a number of the ways in which they've expanded their support. Within Amazon S3, I want to call out their support for our infrequent access, infrequent access One-Zone, Glacier, and Glacier Deep Archive Storage Classes. And they also support other AWS storage services like AWS Outposts, AWS Storage Gateway, AWS Snowball Edge, and the Cold-themed storage offerings. So absolutely a broad set of support there. >> Yeah. There's those, winter is coming. Okay, great guys, we're going to leave it there. Danny, James, thanks so much for coming to theCUBE. Really good to see you guys. >> Good to see you as well, thank you. >> All right >> Thanks for having us. >> You're very welcome. You're watching theCUBE's coverage of 2021 AWS re:Invent, keep it right there for more action on theCUBE, your leader in hybrid tech event coverage, right back. (uplifting music)

(upbeat music) >> Hello everyone, welcome back to theCUBE's coverage of splunk.com 2021 virtual. We're here live in the Splunk studios. We're all here gettin all the action, all the stories. Garth Fort, senior vice president, Chief Product Officer at Splunk is here with me. CUBE alumni. Great to see you. Last time I saw you, we were at AWS now here at Splunk. Congratulations on the new role. >> Thank you. Great to see you again. >> Great keynote and great team. Congratulations. >> Thank you. Thank you. It's a lot of fun. >> So let's get into the keynote a little bit on the product. You're the Chief Product Officer. We interviewed Shawn Bice, who's also working with you as well. He's your boss. Talk about the, the next level, cause you're seeing some new enhancements. Let's get to the news first. Talk about the new enhancements. >> Yeah, this was actually a really fun keynote for me. So I think there was a lot of great stuff that came out of the rest of it. But I had the honor to actually showcase a lot of the product innovation, you know, since we did .conf last year, we've actually closed four different acquisitions. We shipped 43 major releases and we've done hundreds of small enhancements, like we're shipping code in the cloud every six weeks and we're shipping new versions twice a year for our Splunk Enterprise customers. And so this was kind of like if you've seen that movie Sophie's Choice, you know, where you have to pick one of your children, like this was a really hard, hard thing to pick. Cause we only had about 25 minutes, but we did like four demos that I think landed really well. The first was what we call ingest actions and you know, there's customers that are using, they start small with gigabytes and they go to terabytes and up to petabytes of data per day. And so they wanted tools that allow them to kind of modify filter and then route data to different sort of parts of their infrastructure. So that was the first demo. We did another demo on our, our visual playbook editor for SOAR, which has improved quite a bit. You know, a lot of the analysts that are in the, in the, in the SOC trying to figure out how to automate responses and reduce sort of time to resolution, like they're not Python experts. And so having a visual playbook editor that lets them drag and drop and sort of with a few simple gestures create complex playbooks was pretty cool. We showed some new capabilities in our APM tool. Last year, we announced we acquired a company called Plumbr, which has expertise in basically like code level analysis and, and we're calling it "Always On" profiling. So we, we did that demo and gosh, we did one more, four, but four total demos. I think, you know, people were really happy to see, you know, the thing that we really tried to do was ground all of our sort of like tech talk and stuff that was like real and today, like this is not some futuristic vision. I mean, Shawn did lay out some, some great visions, visionary kind of pillars. But, what we showed in the keynote was I it's all shipping code. >> I mean, there's plenty of head room in this market when it comes to data as value and data in motion, all these things. But we were talking before you came on camera earlier in the morning about actually how good Splunk product and broad and deep the product portfolio as well. >> Garth: Yeah. >> I mean, it's, I mean, it's not a utility and a tooling, it's a platform with tools and utilities. >> Garth: Yeah >> It's a fully blown out platform. >> Yeah. Yeah. It is a platform and, and, you know, it's, it's one that's quite interesting. I've had the pleasure to meet a couple of big customers and it's kind of amazing, like what they do with Splunk. Like I was meeting with a large telco on the east coast and you know, they actually, for their set top boxes, they actually have to figure out in real time, which ads to display and the only tool they could find to process 15 million events in real time, to decide what ad to display, was Splunk. So that was, that was like really cool to hear. Like we never set out to be like an ad tech kind of platform and yet we're the only tool that operates at that level of scale and that kind of data. >> You know, it's funny, Doug Merritt mentioned this in my interview with him earlier today about, you know, and he wasn't shy about it, which was great. He was like, we're an enabling platform. We don't have to be experts in all these vertical industries >> Garth: Yep >> because AI takes care of that. That's where the machine learning >> Garth: Yeah >> and the applications get built. So others are trying to build fully vertically integrated stacks into these verticals when in reality they don't have to, if they don't want it. >> Yeah, and Splunk's kind of, it's quite interesting when you look across our top 100 customers, you know, Doug talks about like the, you know, 92 of the fortune 100 are kind of using Splunk today, but the diversity across industries and, you know, we have government agencies, we have, you know, you name the retail or the vertical, you know, we've got really big customers, they're using Splunk. And the other thing that I kind of, I was excited about, we announced the last demo I forgot was TruSTAR integration with Enterprise Security. That's pretty cool. We're calling that Splunk Threat Intelligence. And so That was really fun and we only acquired, we closed the acquisition to TruSTAR in May, but the good news is they've been a partner with us like for 18 months before we actually bought em. And so they'd already done a lot of the work to integrate. And so they had a running start in that regard, But other, one other one that was kind of a, it was a small thing. I didn't get to demo it, but we talked about the, the content pack for application performance monitoring. And so, you know, in some ways we compete in the APM level, but in many ways there's a ton of great APM vendors out there that customers are using. But what they wanted us to do was like, hey, if I'm using APM for that one app, I still want to get data out of that and into Splunk because Splunk ends up being like the core repository for observability, security, IT ops, Dev Sec Ops, et cetera. It's kind of like where the truth, the operational truth of how your systems works, lives in Splunk. >> It's so funny. The Splunk business model has actually been replicated. They call it data lake, whatever you want to call it. People are bringing up all these different metaphors. But at the end of the day, if you guys can create a value proposition where you can have data just be, you know, stored and dumped and dumped into whatever they call it stored in a way >> Garth: We call it ingest >> Ingested, ingested. >> Garth: Not dumped. >> Data dump. >> Garth: It's ingested. >> Well, I mean, well you given me a plan, but you don't have to do a lot of work to store just, okay, we can only get to it later, >> Garth: Yep. >> But let the machines take over >> Garth: Yep. >> With the machine learning. I totally get that. Now, as a pro, as a product leader, I have to ask you your, your mindset around optimization. What do you optimize for? Because a lot of times these use cases are emerging. They just pop out of nowhere. It's a net new use case that you want to operationalize. So balancing the headroom >> Yep. >> Or not to foreclose those new opportunities for customers. How are customers deciding what's important to them? How do you, because you're trying to read the tea leaves for the future >> Garth: A little bit, yeah. >> and then go, okay, what do our customers need, but you don't want to foreclose anything. How do you think about product strategy around that? >> There's a ton of opportunity to interact with customers. We have this thing called the Customer Advisory Board. We run, I think, four of them and we run a monthly. And so we got an opportunity to kind of get that anecdotal data and the direct contact. We also have a portal called ideas.splunk.com where customers can come tell us what they want us to build next. And we look at that every month, you know, and there's no way that we could ever build everything that they're asking us to, but we look at that monthly and we use it in sort of our sprint planning to decide where we're going to prioritize engineering resources. And it's just, it's kind of like customers say the darndest things, right? Sometimes they ask us for stuff and we never imagined building it in a million years, >> John: Yeah. >> Like that use case around ads on the set top box, but it's, it's kind of a fun place to be like, we, we just, before this event, we kind of laid out internally what, you know, Shawn and I kind of put together this doc, actually Shawn wrote the bulk of it, but it was about sort of what do we think? Where, where can we take Splunk to the next three to five years? And we talked about these, we referred to them as waves of innovation. Cause you know, like when you think about waves, there's multiple waves that are heading towards the beach >> John: Yeah. >> in parallel, right? It's not like a series of phases that are going to be serialized. It's about making a set of investments. that'll kind of land over time. And, and the first wave is really about, you know, what I would say is sort of, you know, really delivering on the promise of Splunk and some of that's around integration, single sign-on things about like making all of the Splunk Splunk products work together more easily. We've talked a lot in the Q and a about like edge and hybrid. And that's really where our customers are. If you watch the Koby Avital's sort of customer keynote, you know, Walmart by necessity, given their geographic breadth and the customers they serve has to have their own infrastructure. They use Google, they use Azure and they have this abstraction layer that Koby's team has built on top. And they use Splunk to manage kind of, operate basically all of their infrastructure across those three clouds. So that's the hybrid edge scenario. We were thinking a lot about, you mentioned data lakes. You know, if you go back to 2002, when Splunk was founded, you know, the thing we were trying to do is help people make sense of log files. But now if you talk to customers that are moving to cloud, everybody's building a data lake and there's like billions of objects flowing into millions of these S3 buckets all over the place. And we're kind of trying to think about, hey, is there an opportunity for us to point our indexing and analytics capability against structured and unstructured data and those data lakes. So that that'll be something we're going to >> Yeah. >> at least start prototyping pretty soon. And then lastly, machine learning, you know, I'd say, you know, to use a baseball metaphor, like in terms of like how we apply machine learning, we're like in the bottom of the second inning, >> Yeah. >> you know, we've been doing it for a number of years, but there's so much more. >> There's so, I mean, machine learning is only as good as the data you put into the machine learning. >> Exactly, exactly. >> And so if you have, if you have gap in the data, the machine learning is going to have gaps in it. >> Yeah. And we have, we announced a feature today called auto detect. And I won't go into the gory details, but effectively what it does is it runs a real-time analytics job over whatever metrics you want to look at and you can do what I would consider more statistics versus machine learning. You can say, hey, if in a 10 minute period, like, you know, we see more errors than we see on average over the last week, throw an alert so I can go investigate and take a look. Imagine if you didn't have to figure out what the right thresholds were, if we could just watch those metrics for you and automatically understand the seasonality, the timing, is it a weekly thing? Is it a monthly thing? And then like tell you like use machine learning to do the anomaly detection, but do it in a way that's more intelligent than just the static threshold. >> Yeah. >> And so I think you'll see things like auto detect, which we announced this week will evolve to take advantage of machine learning kind of under the covers, if you will. >> Yeah. It was interesting with cloud scale and the data velocity, automations become super important. >> Oh yeah. >> You don't have a lot of new disciplines emerge, like explainable AI is hot right now. So you got, the puck is coming. You can see where the puck is going. >> Yeah >> And that is automation at the app edge or the application layer where the data has got to be free-flowing or addressable. >> Garth: Yeah. >> This is something that is being talked about. And we talked about data divide with, with Chris earlier about the policy side of things. And now data is part of everything. It's part of the apps. >> Garth: Yeah. >> It's not just stored stuff. So it's always in flight. It should be addressable. This is what people want. What do you think about all of that? >> No, I think it's great. I actually just can I, I'll quote from Steve Schmidt in, in sort of the keynote, he said, look like security at the end of the day is a human problem, but it kind of manifests itself through data. And so being able to understand what's happening in the data will tell you, like, is there a bad actor, like wreaking havoc inside of my systems? And like, you can use that, the data trail if you will, of the bad actor to chase them down and sort of isolate em. >> The digital footprints, if you will, looking at a trail. >> Yeah. >> All right, what's the coolest thing that you like right now, when you look at the treasure trove of, of a value, as you look at it, and this is a range of value, Splunk, Splunk has had customers come in with, with the early product, but they keep the customers and they always do new things and they operationalize it >> Garth: Yep. >> and another new thing comes, they operationalize it. What's the next new thing that's coming, that's the next big thing. >> Dude that is like asking me which one of my daughters do I love the most, like that is so unfair. (laughing) I'm not going to answer that one. Next question please. >> Okay. All right. Okay. What's your goals for the next year or two? >> Yeah, so I just kind of finished roughly my first 100 days and it's been great to, you know, I had a whole plan, 30, 60, 90, and I had a bunch of stuff I wanted to do. Like I'm really hoping, sort of, we get past this current kind of COVID scare and we get to back to normal. Cause I'm really looking forward to getting back on the road and sort of meeting with customers, you know, you can meet over Zoom and that's great, but what I've learned over time, you know, I used to go, I'd fly to Wichita, Kansas and actually go sit down with the operators like at their desk and watch how they use my tools. And that actually teaches you. Like you, you come up with things when you see, you know, your product in the hands of your customer, that you don't get from like a CAB meeting or from a Zoom call, you know? >> John: Yeah, yeah. >> And so being able to visit customers where they live, where they work and kind of like understand what we can do to make their lives better. Like that's going to, I'm actually really excited to gettin back to travel. >> If you could give advice to CTO, CISO, or CIO or a practitioner out there who are, who is who's sitting at their virtual desk or their physical desk thinking, okay, the pandemic, were coming through the pandemic. I want to come out with a growth strategy, with a plan that's going to be expansive, not restrictive. The pandemic has shown what's what works, what doesn't work. >> Garth: Sure. >> So it's going to be some projects that might not get renewed, but there's doubling down on, certainly with cloud scale. What would advice would you give that person when they start thinking about, okay, I got to get my architecture right. >> Yeah. >> I got to get my playbooks in place. I got to get my people aligned. >> Yeah >> What's what do you see as a best practice for kind of the mindset to actual implementation of data, managing the data? >> Yeah, and again, I'm, I'm, this is not an original Garth thought. It actually came from one of our customers. You know, the, I think we all, like you think back to March and April of 2020 as this thing was really getting real. Everybody moved as fast as they could to either scale up or scale scaled on operations. If you were in travel and hospitality, you know, that was, you know, you had to figure how to scale down quickly and like what you could shut down safely. If you were like in the food delivery business, you had to figure out how you could scale up, like Chipotle hit two, what is it? $2 billion run rate on delivery last year. And so people scrambled as fast as they could to sort of adapt to this new world. And I think we're all coming to the realization that as we sort of exit and get back to some sense of new normal, there's a lot of what we're doing today that's going to persist. Like, I think we're going to have like flexible rules. I don't think everybody's going to want to come back into the office. And so I think, I think the thing to do is you think about returning to whatever this new normal looks like is like, what did we learn that was good. And like the pandemic had a silver lining for folks in many ways. And it sucked for a lot. I'm not saying it was a good thing, but you know, there were things that we did to adapt that I think actually made like the workplace, like stronger and better. And, and sort of. >> It showed that data's important, internet is important. Didn't break, the internet didn't break. >> Garth: Correct. >> Zoom was amazing. And the teleconferencing with other tools. >> But that's kind of, just to sort of like, what did you learn over the last 18 months that you're going to take for it into the next 18 years? You know what I mean? Cause there was a lot of good and I think people were creative and they figured out like how to adapt super quickly and take the best of the pandemic and turn it into like a better place to work. >> Hybrid, hybrid events, hybrid workforce, hybrid workflows. What's what's your vision on Splunk as a tier one enterprise? Because a lot of the news that I'm seeing that's, that's the tell sign to me in terms of this next growth wave is big SI deals, Accenture and others are yours working with and you still got the other Partnerverse going. You have the ecosystems emerging. >> Garth: Yep. >> That's a good, that means your product's enabling people to make money. >> Garth: Yeah. Yeah, yeah, yeah. >> And that's a good thing. >> Yeah, BlueVoyant was a great example in the keynote yesterday and they, you know, they've really, they've kind of figured out how, you know, most of their customers, they serve customers in heavily regulated industries kind of, and you know, those customers actually want their data in a Splunk tenant that they own and control and they want to have that secure boundary around that. But BlueVoyant's figured out how they can come in and say, hey, I'm going to take care of the heavy lifting of the day-to-day operations, the monitoring of that environment with the security. So, so BlueVoyant has done a great job sort of pivoting and figuring out how they can add value to customers and do, you know, because they they're managing not just one Splunk instance, but they're managing 100s of Splunk cloud instances. And so they've got best practices and automation that they can play across their entire client base. And I think you're going to see a lot more of that. And, and Teresa's just, Teresa is just, she loves Partners, absolutely loves Partners. And that was just obvious. You could, you could hear it in her voice. You could see it in her body language, you know, when she talked about Partnerverse. So I think you'll see us start to really get a lot more serious. Cause as big as Splunk is like our pro serve and support teams are not going to scale for the next 10,000, 100,000 Splunk customers. And we really need to like really think about how we use Partners. >> There's a real growth wave. And I, and I love the multiples wave in parallel because I think that's what everyone's consensus on. So I have to ask you as a final question, what's your takeaway? Obviously, there's been a virtual studio here where all the Splunk executives and, and, and customers and partners are here. TheCUBE's here doing all the presentations, live by the way. It was awesome. What would you say the takeaway is for this .conf, for the people watching and consuming all the content online? A lot of asynchronous consumption would be happening. >> Sure. >> What's your takeaway from this year's Splunk .conf? >> You know, I, it's hard cause you know, you get so close to it and we've rehearsed this thing so many times, you know, the feedback that I got and if you look at Twitter and you look at my Slack and everything else, like this felt like a conf that was like kind of like a really genuine, almost like a Splunk two dot O. But it's sort of true to the roots of what Splunk was true to the product reality. I mean, you know, I was really careful with my team and to avoid any whiff of vaporware, like what were, what we wanted to show was like, look, this is Splunk, we're acquiring companies, you know, 43 major releases, you know, 100s of small ones. Like we're continuing to innovate on your behalf as fast as we can. And hopefully this is the last virtual conf. But even when we go back, like there was so much good about the way we did this this week, that, you know, when we, when we broke yesterday on the keynote and we were sitting around with the crew and it kind of looking at that stage and everything, we were like, wow, there is a lot of this that we want to bring to an in-person event as well. Cause so for those that want to travel and come sit in the room with us, we're super excited to do that as soon as we can. But, but then, you know, there may be 25, 50, 100,000 that don't want to travel, but can access us via this virtual event. >> It's like a time. It's a moment in time that becomes a timeless moment. That could be, >> Wow, did you make that up right now? >> that could be an NFT. >> Yeah >> We can make a global cryptocurrency. Garth, great to see you. Of course I made it up right then. So, great to see you. >> Air bump, air bump? Okay, good. >> Okay. Garth Fort, senior vice president, Chief Product Officer. In theCUBE here, we're live on site at Splunk Studio for the .conf virtual event. I'm John Furrier. Thanks for watching. >> All right. Thank you guys. (upbeat music)

>> Welcome back to theCUBE's covering of AWS Public Sector Summit. In-person here in Washington, DC. I'm John Furrier, your host, great to be back face to face. We've got a great, special guest Clint Crosier, who is the Director of AWS' Aerospace & Satellite. Major General of The Air Force/Space Force. Retired. Great to see you in person again. Thanks for coming on theCUBE. >> Thank you for having me. I appreciate that. >> First of all, props to you for doing a great job at Amazon, bringing all your knowledge from Space Force and Air Force into the cloud. >> Thank you. >> So that's great, historical context. >> It's been valuable and it's provided a whole lot of insight into what we're building with the AWS space team, for sure. >> So number one question I get a lot is: We want more space content. What's the coolest thing going on in space? Is there a really a satellite behind the moon there, hidden there somewhere? What's the coolest thing going on in space? >> Well, the coolest thing that's going on in space, I think is you're seeing the rapid growth of the space industry, I mean, to me. I've been in the space industry for 34 years now, and there have been periods where we projected lots of growth and activity and it just didn't really come about, especially in the 80's and the 90's. But what we're seeing today is that growth is taking place. Whether it's the numbers of satellites that are being launched around the globe every year, there's some 3,000 objects on orbit today. Estimates are that there'll be 30,000 objects at the end of the decade, or the number of new companies, or the number of global spinning. It is just happening right now, and it's really exciting. >> So, when people say or hear space, there's a lot of economic changes in terms of the cost structures of how to get things deployed into space. That brings up the question of: Is space an opportunity? Is it a threat vector? What about congestion and security? >> Yeah, well three great things, absolutely an opportunity. We're seeing the rapid growth of the space industry, and we're seeing more commercialization than ever before. In my whole career, The Air Force or, NASA, or the NRO would sort of, hold things and do them themselves Today, you're seeing commercial contracts going out from the National Reconnaissance Office, NASA, from The Air Force, from the Space Force. So lots of opportunity for commercial companies. Security. Absolutely, priority number one should be security is baked into everything we do at AWS. And our customers, our Government classified customers tell us the reason they came to AWS is our security is top notch and certified for all their workloads. And as you well know, we have from unclassified all the way up to top secret capabilities on the AWS cloud. So just powerful opportunities for our customers. >> Yeah. And a lot of competitors will throw foot on that. I know, I've reported on some of that and not a lot of people have that same credential. >> Sure. >> Compared to the competition. >> Sure. >> Now I have to ask you, now that you have the top secret, all these clouds that are very tailorable, flexible with space: How are you helping customers with this Aerospace Division? Is it is a commercial? In the public sector together? What's the... >> All of the above. >> Take us through the value proposition. >> Yeah, happy to do this. So what we recognized over the last two years or so we, at AWS, recognized all this rapid growth that we're talking about within the space industry. Every sector from launch to on-orbit activities, to space exploration, all of it. And so AWS saw that and we looked at ourselves and said: "Do we have the right organization and expertise in place really to help our customers lean into that?" And the answer was: we decided to build a team that had deep experience in space, and that was the team that we grew because our thesis was: If you have a deep experience in space, a deep experience in cloud, you bring those two together and it's a powerful contribution. And so we've assembled a team with more than 500 years of collective hands-on experience, flying satellites, launching rockets. And when we sit down with our customers to innovate on their behalf, we're able to come up with some incredible solutions and I'm happy to talk about those. >> I'd love to, but tell you what, first of all, there's a lot of space nerds out there. I love space. I love space geeking out on the technology, but take us through the year you had, you've had a pretty incredible year with some results. You have that brain trust there. I know you're hiring. I know that people want to work for you. I'm sure the resumes are flying in, a lot of action. >> There is. >> What are the highlights from this year? >> So the highlights I think is, we've built a team that the industry is telling us was needed. Again, there was no organization that really served the space cloud industry. And so we're kind of building this industry within the industry, the space cloud industry. And so number one, just establishing that team and leaning into that industry has been valuable. The other thing that we're real proud of is we built a global team, because space is a global enterprise. We have teams in Europe and in Asia and South America here in the U.S., so we built a global team. One of the things that we did right up front, we weren't even six months old, when we envisioned the idea of doing the AWS Space Accelerator. And some of the folks told me: "Clint, six months under your belt, maybe you ought to get your feet under you." And I said: "No, no. We move fast to support our customers." And so we made a call for any space startup that wanted to come on board with AWS and go through our four week Space Accelerator. We partnered with Sarah from Capital. And the idea was: if you're a small company that wants to grow and build and learn how you can use the cloud to gain competitive advantage, come with us. And so John, I would have been happy if we had 50 companies applied, we had 194 companies across 44 countries that applied to our accelerator. We had to down select a 10, but that was a tremendous accomplishment, two of those are speaking this afternoon, where they met each other at our accelerator and now have formed a partnership: Ursa Space and HawkEye 360 on how they build on the cloud together. Fascinating. >> Well, I love that story. First of all, I love the military mindset. No, we're not going to wait. >> Move it out. >> It's not take that hill, it's take that planet. >> Our customers won't wait, innovation, doesn't wait, the future doesn't wait. We have to move out. >> So, this brings up the entrepreneurship angle. We got there a little early, but I want to talk about it because it's super important. There's an entrepreneurial culture happening right now in the space community >> There is. At large, and it's getting bigger and wider. >> Bigger every day. >> What is that? What if someone says: "Hey, what's going on with entrepreneurship in this space? What are the key dynamics? What's the power dynamics?" It's not money, there's money out there, but like what's the structural thing happening? >> The key dynamic, I think, is we're seeing that we can unlock things that we could never do before. And one of our goals is: the more space data we can make more accessible to more people around the world. It unlocks things we couldn't do. We're working with space companies who are using space data to track endangered whales off the coast of California. We're working with companies that are using space data to measure thermal and greenhouse emissions for climate change and climate management. We're working with one company, Edgybees, who has a small satellite constellation, and they're using it to build satellite based, augmented reality, to provide it to first responders as they go into a disaster response area. And they get a 3D-view of what they're going into. None of those workloads were possible five years ago. And the cloud and cloud-based technologies are really what opens those kinds of workloads up. >> What kind of higher level services do you see emerging from space cloud? Because you know, obviously you have to have some infrastructure. >> Absolutely. Got to put some stuff into space. That's a supply chain, reliability, also threat. I mean, I can have a satellite attack, another satellite, or I'm just making that up, but I'm sure there's other scenarios that the generals are thinking about. >> So space security and cyberspace security is critical. And as I said, it's built into everything we do in all of our platforms, so you're absolutely right about that, but when we think about the entrepreneurship, you know, what we're seeing is, and I'll give you a good example of why the industry is growing so fast and why cloud. So one company we work with, LeoLabs. So Leo identified the growth in the LEO: Low Earth Orbit segment. 3,000 objects on orbit today, 30,000 tomorrow. Who's going to do the space traffic management for 30,000 objects in space that are all in the same orbital regime? And so LeoLabs built a process to do space traffic management, collision avoidance. They were running it on premises. It took them eight hours to do a single run for a single satellite conjunction. We got them to help understand how to use the cloud. They moved all that to AWS. Now that same run they do in 10 seconds. Eight hours to 10 seconds. Those are the kind of workloads as space proliferates in and we grow, that we just can't execute without cloud and cloud-based technologies. >> It's interesting, you know, the cloud has that same kind of line: move your workloads to the cloud and then refactor. >> Yeah. So space workloads are coming to the cloud. >> They are. >> Just changing the culture. So I have to ask you, I know there's a lot of young people out there looking for careers and interests. I mean, Cal poly is going into the high school now offering classes. >> Yeah So high school, there's so much interest in space and technology. What is the cultural mindset to be successful? Andy Jassy last year, reading and talk about the mindset of the builder and the enterprise CXO: "Get off your butt and start building" There's a space ethos going on. What is the mindset? Would you share your view on it? >> The mindset is innovation and moving fast, right? We, we lived, most of my career, in the time where we had an unlimited amount of money and unlimited amount of time. And so we were really slow and deliberate about how we built things. The future won't wait, whether it's commercial application, or military application, we have to move fast. And so the culture is: the faster we can move, The more we'll succeed, and there's no way to move faster than when you're building on the AWS cloud. Ground station is a good example. You know, the proposition of the cloud is: Don't invest your limited resources in your own infrastructure that doesn't differentiate your capability. And so we did that same thing with ground station. And we've said to companies: "Don't spend millions of dollars on developing your own ground station infrastructure, pay by the minute to use AWS's and focus your limited resources back in your product, which differentiate your space mission." and that's just been power. >> How is that going from customer perspective? >> Great. It's going great. We continue to grow. We added another location recently. And just in the last week we announced a licensed accelerator. One of the things our customers told us is it takes too long to work with global governments to get licensed, to operate around the world. And we know that's been the case. So we put together a team that leaned in to solve that problem, and we just announced the licensed accelerator, where we will work with companies to walk them through that process, and we can shave an 18 month process into a three or four month process. And that's been... we've gotten great response on that from our company. >> I've always said: >> I remember when you were hired and the whole space thing was happening. I remember saying to myself: "Man, if democratization can bring, come to space" >> And we're seeing that happening >> You guys started it and you guys, props to your team. >> Making space available to more and more people, and they'll dazzle us with the innovative ways we use space. 10 years ago, we couldn't have envisioned those things I told you about earlier. Now, we're opening up all sorts of workloads and John, real quick, one of the reasons is, in the past, you had to have a specific forte or expertise in working with space data, 'cause it was so unique and formatted and in pipeline systems. We're making that democratized. So it's just like any other data, like apps on your phone. If you can build apps for your phone and manage data, we want to make it that easy to operate with space data, and that's going to change the way the industry operates. >> And that's fundamentally, that's great innovation because you're enabling that. That's why I have to ask you on that note Of the innovation trends that you see or activities: What excites you the most? >> So a lot of things, but I'll give you two examples very quickly: One is high-performance compute. We're seeing more and more companies really lean in to understanding how fast they can go on AWS. I told you about LeoLabs, eight hours to 10 seconds. But that high-performance computes going to be a game changer. The other thing is: oh, and real quick, I want to tell you, Descartes Labs. So Descartes Labs came to us and said: "We want to compete in the Annual Global Top 500 supercomputer challenge" And so we worked with them for a couple of weeks. We built a workload on the AWS standard platform. We came in number 40 in the globe for the Top 500 super computer lists, just by building some workloads on our standard platform. That's powerful, high-performance compute. But the second example I wanted to give you is: digital modeling, digital simulation, digital engineering. Boom Aerospace is a company, Boom, that we work with. Boom decided to build their entire supersonic commercial, supersonic aircraft, digital engineering on the AWS cloud. In the last three years, John, they've executed 6,000 years of high-performance compute in the last three years. How do you do 6,000 years in compute in three years? You spin up thousands of AWS servers simultaneously, let them do your digital management, digital analysis, digital design, bring back a million different perturbations of a wing structure and then pick the one that's best and then come back tomorrow and run it again. That's powerful. >> And that was not even possible, years ago. >> Not at that speed, no, not at that speed. And that's what it's really opening up in terms of innovation. >> So now you've done it so much in your career, okay? Now you're here with Amazon. Looking back on this past year or so, What's the learnings for you? >> The learning is, truly how valuable cloud can be to the space industry, I'll admit to you most people in the space industry and especially in the government space industry. If you ask us a year ago, two years ago: "Hey, what do you think about cloud?" We would have said: "Well, you know, I hear people talk about the cloud. There's probably some value. We should probably look at that" And I was in the same boat, but now that I've dug deeply into the cloud and understand the value of artificial intelligence, machine learning, advanced data analytics, a ground station infrastructure, all those things, I'm more excited than ever before about what the space industry can benefit from cloud computing, and so bringing that, customer by customer is just a really fulfilling way to continue to be part of the space industry. Even though I retired from government service. >> Is there a... I'm just curious because you brought it up. Is there a lot of people coming in from the old, the space industry from public sector? Are they coming into commercial? >> Absolutely. >> Commercial rising up and there's, I mean, I know there's a lot of public/private partnerships, What's the current situation? >> Yeah, lots of partnerships, but we're seeing an interesting trend. You know, it used to be that NASA led the way in science and technology, or the military led the way in science and technology, and they still do in some areas. And then the commercial industry would follow along. We're seeing that's reversed. There's so much growth in the commercial industry. So much money, venture capital being poured in and so many innovative solutions being built, for instance, on the cloud that now the commercial industry is leading technology and building new technology trends that the military and the DOD and their government are trying to take advantage of. And that's why you're seeing all these commercial contracts being led from Air Force, Space Force, NASA, and NRO. To take advantage of that commercialization. >> You like your job. >> I love my job. (laughing) -I can tell, >> I love my job. >> I mean, it is a cool job. I kind of want to work for you. >> So John, space is cool. That's our tagline: space is cool. >> Space is cool. Space equals ratings in the digital TV realm, it is really, super exciting a lot of young people are interested, I mean, robotics clubs in high schools are now varsity sports, eSports, all blend together. >> Space, robotics, artificial intelligence, machine learning, advanced analytics. It's all becoming a singular sector today and it's open to more people than ever before, for the reasons we talked about. >> Big wave and you guys are building the surf boards, everyone a ride it, congratulations. Great to see you in person. >> Thank you. Again, thanks for coming on theCUBE, appreciate that. >> Thanks for having us. >> Clint Crosier is the Director of AWS Aerospace & Satellite. Legend in the industry. Now at AWS. I'm John Furrier with theCUBE. Thanks for watching.