(light music) >> Welcome to this session at the Amazon EC2 15th birthday event. I'm your host, Lisa Martin. I'm joined by Elaine Harvey, director and technical advisor at AWS. Elaine, welcome to the program. It's great to see you. >> Thank you, Lisa. I'm really glad to be here. >> So here we are celebrating EC2's 15th birthday, probably back in the day, so many customers and many industries couldn't imagine how they would be using the service. Talk to me about how long you've been involved in EC2 and some of the growth and the maturation of the service that you've seen. >> Yeah, I mean, I joined EC2 about eight years ago and it was big then, but much smaller than it is now. And it's grown in so many directions, both in the scale, the instances that we offer, as well as the types of instances, the various types of hardware effectively that we offer for customers to support their workload. It's just grown in so many dimensions. It's really exciting. >> I see here 80 availability zones. 25 regions, local zones in Boston, Dallas, Denver, Houston, Miami, Philadelphia, and nine new locals zones coming just this year. Talk to me a little bit about that. >> So really, what we are trying to do is get compute where customers needed. So we've already had these presences around the world. And with this expansion, we're trying to bring the EC2 offering to customers with much lower latency. And that's why we're doing local zones, regions, availability zones in so many places. So customers can have that compute with low latency to help them interact with their customers. >> I know since its inception, AWS has always been so customer centric, it's always day one there, but prior to joining AWS, as you said, eight years ago, you were involved in a number of startups. One of the things that we consistently hear is how instrumental EC2 has been in reinventing the startup space. What can you tell me about that involvement that it's had? >> Yeah, I mean, the great thing was, I was an EC2 customer before I worked at EC2. So I had been in the startup community for almost 25 years before joining Amazon. And I had been through that life cycle of a startup where you begin, you need some capacity, you need some computers to run your stuff on and eventually you reach a size and you have to go figure out all the hard work. Where am I going to put them? Do I need a data center? What kind of network connectivity do I need? And not only that, you have to invest a lot of money, which startups very rarely have in the early days into buying the equipment you need, just so you could run your business. Do the thing you're really trying to do for your customer. EC2 is a game changer. So I started using EC2 at one of the startups I was at before coming here. Actually I had two prior startups before coming to EC2. And the ability to just get capacity when you needed it, you didn't have to go buy computers. You didn't have to have data center contracts. You just said, I need a hundred of these. And suddenly you had a hundred of the instance you were asking for, completely game changing, especially for a startup where you just don't have that capital to invest. And frankly, you don't want to spend your time dealing with data centers when that's not your business, your business is to serve your customers. >> And I can't imagine the last year and a half, we've seen such acceleration of digital business transformation, how startups and enterprises alike would have fared without having the ability to quickly turn on services like EC2 in this time. >> Yeah, yeah. It was just amazing. During COVID times, we definitely saw that rush of everybody trying to go online companies that had been already starting down that path, going online, scaling more. And suddenly it went from zero to 100 in March and everybody had to go online and it was super exciting to be part of EC2 and be able to enable everybody in the world to do that. >> Incredible amount of acceleration, but also maturation and growth in the whole portfolio of AWS. We've talked about that a number of times on The Cube in the last six or eight months or so, you mentioned nine new availability zones coming in 2021. You've been involved in the regional and the local zone build out. Talk to me about how these regional zones, these availability zones are helping enterprises to run their businesses and applications worldwide with the high availability that their customers are demanding. >> Yeah, yeah. So there's the book the location aspect. So we do need to be worldwide because our customers are worldwide. So we need to be where they need to be. And so that's how we think about the growth of our regions and availability zones and now local zones with lower latency to end customers. There's another aspect to availability zones and regions that is super important for our customers availability, foundationally we treat those as fault zones. So their fault boundaries beyond which customers will not experience faults. So for example, the fundamental way that we think about designing our services isolates faults between regions and between availability zones and customers can use that in their designs such that they'll have a Multi AZ behavior and we contain faults along those boundaries so they can design with that in mind, and their applications can be fault tolerant, relying on those foundational fault domains effectively. >> That's even becoming more and more important as consumers become more and more demanding that services are just available. And you can get anything with the click of a link on your phone. That high availability is really no longer a nice to have what EC2 is delivering, it's table stakes for an organization I can imagine in any industry. >> Absolutely, absolutely. Our customers totally rely on that so that they can serve their customers consistently and reliably. >> It's a tremendous amount of growth Elaine, in the first 15 years, you said you've been with EC2 on this side now working for it for eight years, but had a lot of experience with it before when it was probably in its infancy as a startup customer. What are some of the things that excite you most about the direction in which EC2 is going? >> Yeah, I think we are steadily providing more and more flexibility to our customers. So we are providing them with new instance types to suit their particular workloads. So we're getting more into a variety of offerings that customers can use to achieve the outcomes they want. That's exciting. I think probably the thing that excites me the most though, is the work we're doing around custom silicon. So our Graviton, Inferentia, Trainium chips where we are building custom silicon for a number of reasons. A big factor of that is we are giving our customers the ability to have a much better ROI on compute to cost for their workload. So we're trying to make it more and more cost efficient for our customers to do what they want. The thing that really excites me about it, though, I'll tell you the secret thing that excites me about it is not very well known, but Graviton is not only cost to compute higher efficiency, but it is also power to compute higher efficiency. So it's a greener option. So if a customer for a given workload wanted to reduce their carbon footprint, they can move to Graviton and it consumes substantially less power for the same workload. And that makes me really excited. >> That is exciting and something that I think everybody can wrap their heads around. I was reading something about EC2 and Graviton paving the way for another important initiative, and that's telecommunications, some of the big news, that Dish Network is coming out saying we're going to be building our 5g core network on AWS. A lot of work going on there in telecommunications. >> Yeah. Yeah. That's very exciting. And in line with our overall strategy to get much closer to the end customers, again, to reduce that latency, whether those customers are on a 5g network or on the internet, what we want the ability for our customers to be able to provide compute and their applications wherever their customers are. >> Well Elaine, thank you so much for joining me on the EC2 15th birthday event. A lot of innovation has gone on in the first 15 years. We know what you're excited about and I'm sure, can't even imagine what the next five, 10 or 15 years will hold for EC2, its services and the customers that it delights. We thank you for joining us today. >> Thanks so much, Lisa. >> Elaine Harvey, I Lisa Martin, thanks for watching today's session. (light music)

(soft electronic music) >> Welcome to this session of the Amazon EC2 15th Birthday Event. I'm your host, Lisa Martin. I'm joined by Joshua Burgin, General Manager of AWS Outposts at AWS. Joshua, welcome back to the program. Thank you, it's great to be here again. >> So 15th birthday, a tremendous amount has gone on in the last 15 years, but I want to understand what brought you to AWS? What excited you about cloud and EC2, in particular? >> Yeah, I mean, that's a, it's a great question and it's kind of a fun story. I actually worked at Amazon back in the 90s for three years as a software engineer when I don't think anybody you asked back then would have said that cloud was in our future. And so I'd kind of obviously kept in touch with people over the years and I was working at a customer who, interestingly enough, had moved off of AWS thinking that they could build a better cloud. And then of course, over the years, found out that it's actually quite difficult and was in process of moving back to AWS. And so I reconnected with some of the senior leaders who I was still friendly with and they said, you know, come back in, the water's fine, there's still a lot of opportunity. And it's, it's really been true, right? There's been just a tremendous amount of growth in the last seven years that I've been back and obviously, over the last 15 years for EC2, in general. >> Well, this 15th birthday not only marks a big milestone for AWS, but also for the cloud computing world that it serves globally. Talk to me a little bit about the impact over the last seven years you've been there and 15 years of EC2's life. >> Well, I mean, we've really been transforming every industry that you could possibly imagine as everyone's had to develop a plan to move to the cloud to take advantage of the opportunities for innovation, for cost efficiency, for developer efficiency, for operational improvements. And so EC2 was one of the foundational services inside of AWS and, you know, a lot of things are built on top of it, and so it's been really great to work with all of these different customers in financial services, in Telco, in gaming, you know, healthcare, you name it, all around the world. >> So 15 years ago, EC2 obviously started quite small. Can you talk to us about some of the early trends that are emerging from the hybrid space? >> Yeah, I mean, we're fond of saying here that it's still day one and that's very true for the outposts and the hybrid business, in general, at AWS. The early trends, if I had to kind of bundle them together, would be that first of all, people are operating in more places than they ever thought they would have to. These are big customers, manufacturing, Telco, healthcare, public sector customers, people in gaming, they serve customers around the world. That's a trend that's kind of, irregardless of industry, that's what we're seeing. And so of course, having an outpost available everywhere, we're up to 60 countries now, having local zones in many countries which we hope is our longterm plan, having wavelength zones with lots of partners, you know, that's why we're doing those things 'cause customers are telling us that we need to operate everywhere. It's actually the reason we went from one availability zone or excuse me, three availability zones in one region 15 years ago, to 25 regions in 80 availability zones. And of course, hybrid is building on top of that. The other thing we're seeing, you know, real specifically for hybrid is low latency, local data processing, and data residency. Across every industry, those are the needs that are driving people to adopt hybrid technology and they're the ones pushing us forward here, at AWS to innovate on their behalf. >> Talk to me about some of the innovation in the last few years alone, that customers are helping drive where those regulations are becoming more and more critical. We're seeing more importance on security and ensuring that customer data is secure, protected, but also accessible. >> Yeah, absolutely, I mean, we're fond of saying at AWS that security is job zero. You know, we take it incredibly seriously, even though, of course, it's a shared responsibility model where we secure the underlying infrastructure and then provide tooling and services on top of that for customers to create the level of security that's appropriate for their application. Obviously, a government workload or a banking workload is different than a mobile game, even of course as customer data needs to be secured in all situations. So with outposts and with local zones, what we're giving people the ability to do is ensure that their compute and their storage are in whatever country or municipality or city or state that they need them to be. So you could take something as diverse as a bank or a healthcare company where they might need to have that compute and storage literally in a specific facility because of regulations, or in a specific state, you know, that's kind of happening around the world. You also see something you might not have thought about, but customer is in the iGaming space, so that's mobile betting. Tipico and FanDuel are a couple of early examples of those for outposts where as it becomes legal, at least in more states in the United States and more places in Europe, the regulations are requiring that the cloud computing, if they want to use it, is placed in a specific place. So the only way you can do that is either, of course, if we had a region everywhere, which we don't, or if you have something like outposts, otherwise you'd be forced to revert to like a bare metal solution and kind of take on all that heavy burden yourself. Your developers would be less efficient because they'd be using AWS in one place and bare metal kind of hardware somewhere else. So, you know, it's still really early, but I've been pleased to kind of see that kind of adoption across those diverse industries. >> It is really early, as you said. The philosophy at Amazon AWS is it's day one. Give me some feedback from customers now where, you know, we, we see a lot of different reports that suggest where businesses are, enterprises are in terms of cloud adoption. What are some of the things that you're seeing where you really think hybrid is going to be an absolute game changer? >> Yeah, I mean, one example that comes to mind is Telco which is one of the biggest industries with the smallest amount of cloud adoption to date. And so I think a lot of that was driven by specific requirements in that industry that required on-prem components for that ultra low latency. You can imagine they needed the compute and the storage to be at the cell site or distributed around the United States or other countries. And so that's where you have examples now with Dish Networks where we just announced a strategic partnership with them. They're going to be using this combination of the new small form factor outposts that we're releasing later this year. They're about the size of a pizza box or a couple of pizza boxes. They're also going to be using our network of local zones that we're building out, 15 of them across the United States, and they'll be using our regions for workloads that are, of course, less latency sensitive, and that can kind of be run centrally. So it's really kind of one of the best examples I can think of where people that were held back by the technology, by the offerings are now enabled to move really quickly. And so I think you're going to see a lot in that space and other industries where before they had to kind of not move to the cloud because a portion of their workload needed to remain on-prem, and now we're delivering a continuum of offerings, including, you know, to the very smallest locations. >> Let's look forward into the next decade. As barriers to adoption are being removed daily, you mentioned Dish Network. I saw that they're going to build their 5G, their core 5G network on AWS. That's huge, that's a big signal for the telecommunications industry. But what are some of the things that you think we're going to be able to open this book and there will maybe a crystal ball in the next decade can expect. >> Yeah, I mean, if I had a crystal ball, my roadmap would be perfect. >> Wouldn't it? >> It would be, it would be great. So if anybody's offering one of those I'm, I'm taking. But what I think you'll see is that, that the day one metaphor is going to continue. As big as AWS has become, and I think we're really proud of the accomplishments and innovation we've delivered for customers over the last 15 years, as I mentioned, we started with one instance type and one region, and now we have over 400 instance types in EC2. That's a lot of choice for people and that's just EC2, right? We have another 185 or 200 services these days, I can barely keep up with them which is exciting in its own right. And so the reason is that we're doing all that innovation is that customers are telling us what they want and a lot of that is, although they're driven to move to the cloud and they really want to move there quickly, somewhere between 75 and 90% of technology spending is still in the traditional hardware-software space. So again, I'd like you to think about that. 15 years in, you know, at the run rate that we're at, and obviously with other people in this space, there's still so much more to go that has already moved to the cloud. So I think you'll see more new instance types, more locations, more form factors, you know, from Outpost and us using Outpost to deliver infrastructure like local zones and wavelength which are built on top of Outposts, and so we don't force people to pick and choose between moving to the cloud and running the kinds of workloads they're already running. We want to be driven by the customer not force them into a narrow way of working that we think is best. That's probably the hallmark of AWS is giving people the choice. They can use EC2 and manage their own databases, they can use RDS or one of our, you know, 14 purpose-built databases, depending on what their application needs. And that's true across the board. Storage, compute, machine learning, container services, hybrid offerings, of course, which I manage for the AWS business, we're going to continue to do that. So the choice is going to proliferate, the performance is going to continue to improve, we're going to continue to bring down pricing and increase price for performance, and we're going to hopefully make things easier and more cost-effective for people, whether that's for their developers or their finance people, so that they can innovate on behalf of their customers versus handling all that undifferentiated muck and heavy lifting of managing the infrastructure themselves. >> That customer centricity has always been key to AWS. Just some of what you said, I think we can expect to see a ton more from AWS, announcements, customer-driven choices for customers. Joshua, thank you for joining me today. Happy 15th birthday to Amazon EC2. >> Thank you so much for having me. It's great to be here. >> For Joshua Burgin, I'm Lisa Martin. You're watching theCUBE. (soft electronic music)

(upbeat rhythmic music) >> Everyone, I'm John Furrier with theCUBE here at Palo Alto on a remote interview for a special video interview. The EC2 15th birthday party celebration event. Raj Pai, who's the Vice President of EC2 Product Management AWS is here with me. Congratulations on Amazon Web Services, EC2 with the compute. What a journey. 15 years old. Soon we got the keys to the car at a couple more years. So Raj, great to see you. You guys have been doing great work. Congratulations. >> Thank you. It's great being here. It's super exciting for me too. I can't believe it's 15 years and you know that big, we're still at the very beginning as you know, that we often say. >> The building blocks that have been there from the beginning really set the table, and it's just been fun to watch the innovation on behalf of customers that you guys have done at AWS and more, and for entrepreneurs and for developers, it just continues to be great and the edge is right on the corner. Wavelength, all the great stuff. But let's talk about the specific topic here that I really want to drill into is that as you look at the 15th year and birthday for EC2, okay? You're looking at the future as well. You're looking at the past, present and future. And one of the things that's most compelling about recent re-invent was the Graviton performance numbers are amazing. You guys have been building custom silicon for a while. You also worked with Intel and AMD. What is it about? What's the huge investment for you guys? Where do you started to see some returns? Are you seeing returns? And then why did AWS decide to build its own processors? >> Yeah, now, that's a really good question. And I mean, like with everything else we do in AWS, it's all about innovating on behalf of our customers. And one of the things our customers are telling us, that they continue to tell us is they want to see better performance at lower prices. And we've been able to deliver that with our hardware partners for the last 15 years. But as we've understood the workloads that run on EC2 and AWS, we saw an opportunity. Like, what if we were going to go and design our own processor that was really optimized for the sort of workload that customers run on the Cloud? And make design decisions when designing the CPU and the system and the chip around the CPU that does things like bring a lot more core local cache and speed up the parts of the operations that really benefit real-world workload. So, this isn't about benchmarks. It's about how do real world workloads perform and how do we build systems that optimize that performance? And with Graviton, we were able to hit the nail on the head. We were also very pleasantly surprised when we got our first chips off the line. And we're seeing that a customer, like about 40% performance improvement at significantly lower cost. And that's super exciting. And that's one of the reasons we're getting so much interest from our customers. >> I got to say as a geek and a tech nerd, I love the silicon development. And there's benefits there, also the performance is there. The thing that also is pretty obvious that's happening is and the world seeing it is the shift towards ARM-based computing. What kinds of customers and use cases are you seeing adopt to Graviton? And what kind of workloads were they running on? What are the things that surprise you guys, that didn't surprise me. Did you guys always talk about the upcheck and how everyone's leveraging it? What are some of the examples? Take us through some of the customers, use cases, workloads. What's surprising you and what's going on with Graviton? >> Yes, so I think that the biggest surprise for us is how broadly applicable it's been. So one of the things we did, we launched with reinvent is like we have different form factors of compute. We have memory-optimized instances that are good for databases and in memory caches. We have compute optimized for HPC and workloads that really take advantage of the performance of the chip and then we have general purpose workloads. And we we introduced Graviton variants of all those instance families And we're actually seeing the same sort of performance benefits across workload. So, and it's one of the reasons why companies like Metrol, and Snap and SmugMug, they move one workload over, they see the performance benefit and before you know it, they're starting to move workloads and mass over across kind of that spectrum. So, I think that's one of the biggest surprises is that Graviton seems to do well across a wide range and we're going to keep on introducing it more and more of instance families, because we've seen this uptick well. >> You're seeing a lot of people move to the Graviton. You mentioned a few of those early adopters who were pushing the envelope, and they're always kind of trotted out there as examples at reinvent, which is always fun to see what they're working on next. And now is that people see the Graviton2 instances, okay, the architecture's different, higher performance. How much effort do our customers typically need to move to Graviton2 instances? And what are some of the benefits they're seeing on performance and price performance? Can you talk about that transition? Because that's natural evolution for them. >> Yeah. It's actually a lot less than they originally think. So, some of the hardest effort is just getting them over the line to try it. So, one of the things that we tell our customers who are considering Graviton is it just takes one or two developers take one workload and go off for a couple of weeks and just try reporting it to Graviton. And more often than not, they come back to us in four or five days. They're like, it works. And we just had to do some testing and verification, but we were able to afford it because, you know, the operating system support was there, the ISP support was there and the tools that they use, and they're using most cases, modern programming languages like Python or Go or Java or PhD where, you know, interpret the language and it just run. And so there's very little lift in comparison to what people think it's going to be. And that's one of the reasons that, you know, one of the big announcements we made in the last few weeks is what we're calling the Graviton challenge, right? So it's a set of blueprints for customers to essentially have best practices on how to in four days take, you know, a piece of code and piece of that workload and execute it and run it and migrate it to the Graviton. And we're seeing a lot of interest in that as people in the community realize how easy that actually is. >> What are some of the cool price performance things that are emerging? Obviously it makes sense if you don't really need it, don't pay for it, but you have that option. A lot of people are going there. Is there a wave you see coming that Graviton2 is going to be really set up for that you kind of see some early signals coming in, Raj? Because, I can see the 64 bit. I can see where Graviton fits today. Obviously, performance is key. Is it certain things that are emerging? What's the main problems that it solves? >> Well, I think anything that's a multi-threaded architecture is going to do really well in Graviton because of the, we have really densely packed 64 course. And so you're going to see things like microservices and containers and workloads that are more, that are able to take advantage of that parallel execution do really, really well. And so, we say 40% performance improvement, but like, when our customers have gone and tried this, they've seen upwards of 50% depending on the workload. So yeah, it's going to be more your multi-threaded application. There's some applications that may not be a fit, like it can give a legacy, you know, for example, like, there's some software that hasn't yet been moved over and we're going to continue to invest super heavily in our whole ecosystem of hardware, for the longterm. So I think that because there's a great option and we just encourage them to try it. And then they'll learn from their experience what works and what doesn't. >> Wow. 15th birthday. Still growing up and it's starting to get more mature. You're the VP of Product Management. You have the keys to the kingdom. So, you have wide-ranging responsibilities. Share with us if you can. I know that you really can't say much, but try to give a little bit of teaser. You got Wavelength. I can see the dots connecting at the edge. You got Outposts, so we see all that emerging. I can almost imagine that this is going to get stronger. What should people think about? Where's the headroom for EC2 with Graviton and Graviton2? >> Yeah, I know. I think like, a new architect (mumbles) yourself. But like, our goal is to have AWS kind of everywhere our customers are. And that means the full power of AWS. So, I think you're going to see more and more of us having EC2 in compute capacity, wherever customers need it. That could be in an Outpost. That could be on their 5G network. That could be in a city right next to them, right? And you're going to see us continue to offer the variety, the selection of instances and platforms in all those locations as well. So, I think the key for us is to be ubiquitous and have compute power everywhere our customers need it, in the form factors they need it. >> That's awesome. Congratulations. I love the power. You can't go wrong with sending computers where the data is, where the customers are. AWS, Amazon Web Services. Building their own custom silicon with Graviton2 processors. This is EC2 continuing to grow up. Raj Pai, Vice President of EC2 Product Management. Thank you for coming on and sharing the update and congratulations on the 15th birthday to EC2. >> Yeah, thanks for having me. It's been great. Have a great Friday. >> All right. Great. I'm Jeffrey with theCUBE. You're watching theCUBE coverage of EC2's 15th birthday event. Thanks for watching. (soft rhythmic music)

>>Mhm >>Welcome to the cube where we're celebrating the EC 2/15 birthday anniversary. My name is Dave Volonte and we're joined right now by Sandy carter, Vice President of AWS. Welcome Sandy, it's great to see you again, >>David. So great to see you too. Thanks for having me on the show today. >>Very welcome. We were last physically together. I think it was reinvent 2019. Hopefully I'll see you before 2022. But first happy birthday to EC two. I mean, it's hard to imagine back in 2006, the degree to which EC two would impact our industry. Sandy, >>I totally agree. You know, I joined a W S about 4.5 years ago in EC two and it's, it's even amazing to see what's just happened in the last 4.5 years. So I'm with you. Nobody really expected the momentum, but EC two has really shone brightly in value to our customers. >>You know, we've done the public sector summit, you know, many times. It's a great event. Things are a little different in public sector as you well know. So talk about the public sector momentum with EC two and that journey. What have you seen? >>Yeah, so it's a great question day. So I had to go back in the time vault. You know, public sector was founded in 2010 and we were actually founded by the amazon process writing a paper setting up a two pizza team, which happened to be six people. And that journey really started with a lot of our public sector customers thinking that we don't know about the cloud. So we might want to do a pilot or just look at non mission critical workloads now public sector and I know you know this day but public sector is more than just government, it has education, not for profit healthcare and now space. But everybody at that time was very skeptical. So we had to really work hard to migrate some workloads over. And one of our very first non mission critical workloads was the U. S. Navy. Um and what they did was the Navy Media Services actually moved images over to EC two. Now today that seems like oh that's pretty easy. But back then that was a big monumental reference. Um and we had to spend a lot of time on training and education to win the hearts and souls of our customers. So back then we had half of the floor and Herndon Washington, we just had a few people and that room really became a training room. We trained our reps, we trained our customers um research drive. A lot of our early adopters accounts like Nasa and jpl. And um then when cloud first came out and governments that started with the U. S. A. And we announced Govcloud, you know, things really picked up, we had migration of significant workloads. So if you think back to that S. A. P. And just moving media over um with the Navy, the Navy and S. A. P. Migrated their largest S A P E R P solution to the cloud in that time as well. Um, then we started international. Our journey continued with the UK International was UK and us was us. Then we added a P. J. And latin America and Canada. And then of course the partner team which you know, is very close to my heart. Partners today are about 73% of our overall public sector business. And it started out with some interesting small pro program SVS being very crucial to that, accelerating adoption. And then of course now the journey has continued with Covid. That has really accelerated that movement to the cloud. And we're seeing, you know, use of ec two to really help us drive by the cute power needed for A I N. M. L. And taking all that data in from IOT and computing that data. And are they are. Um, and we're really seeing that journey just continue and we see no end in sight. >>So if we can stay in the infancy and sort of the adolescent years of public sector, I mean, remember, I mean as analysts, we were really excited about, you know, the the the introduction of of of of EC two. But but there was a lot of skepticism in whatever industry, financial services, healthcare concerns about security, I presume it was similar in public sector, but I'm interested in how you you dealt with those challenges, how you you listen to folks, you know, how did you drive that leadership to where it is today? >>Yeah, you're right. The the first questions were what is the cloud? Doesn't amazon sell books? What is this clown thing? Um, what is easy to, what is easy to stand for and then what the heck is an instance? You know, way back when there was one instance, it didn't even have a name. And today of course we have over 400 instant types with different names for each one. Um and the big challenges you asked about challenges, the big challenges that we had to face. Dave were first and foremost, how do we educate? Um we had to educate our employees and then we had to educate our customers. So we created these really innovative hands on training programmes, white boarding um, sessions that we needed. They were wildly popular. So we really have to do that and then also prove security as you know. So you asked how we listen to our customers and of course we followed the amazon way we work backwards from where we were. So at that time, customers needed education. And so we started there um, data was really important. We needed to make customer or data for government more available as well. So for instance, we first started hosting the Census Bureau for instance. Um and that was all on EC two. So we had lots of early adopters and I think the early adopters around EC two really helped us to remember. I said that the UK was our international office for a while. So we had NIH we had a genomes project and the UK Ministry of Justice as well. And we had to prove security out. We had to prove how this drove a structured GovCloud and then we had to also prove it out with our partners with things like helping them get fed ramped or other certifications. I'll for that sort of thing as well. And so we really lead in those early days through that education and training. Um we lead with pilots to show the potential of the possible and we lead with that security setting those security standards and those compliance certifications, always listening to the customer, always listening to the partner, knowing how important the partners we're going to be. So for example, recovery dot gov was the first government wide system that moved to the cloud. Um the recovery transparency board was first overseeing that Recovery act spending, which included stimulus tracking website. I don't know if you remember that, but they hosted the recovery dot gov On amazon.com using EC two. And that site quickly made information available to a million visitors per hour and at that time, that was amazing. And the cost savings were significant. We also launched Govcloud. You'd asked about GovCloud earlier and that federal cloud computing strategy when the U. S. Government came out with cloud first and they had to consider what is really going to compel these federal agencies to consider cloud. They had Public-sector customers had 70 requirements for security and safety of the data that we came out with Govcloud to open up all those great opportunities. And I think Dave we continue to leave because we are customer obsessed uh you know, still supporting more security standards and compliance sort than any other provider. Um You know, now we lead with data not just data for census or images for the US Navy, but we've got now data in space and ground station and data at scale with customers like Finra who's now doing 100 billion financial transactions. Not just that one million from the early days. So it has been a heck of a ride for public sector and I love the way that the public sector team really used and leveraged the leadership principles. Re invent and simplify dive deep. Be obsessed with the customers start where they are. Um and make sure that you're always always always listening to what they need. >>You know, it's interesting just observing public sector. It's not uncommon, especially because of the certifications that some of the services, you know come out after they come out for the commercial sector. And I remember years ago when I was at I. D. C. I was kind of the steward of the public sector business. And that was a time when everybody was trying to focus in public sector on commercial off the shelf software. That was the big thing. And they want to understand, they wanted to look at commercial use cases and how they could apply them to government. And when I dug in a little bit and met with generals and like eight different agencies, I was struck by how many really smart people and the things that they were doing. And I said at the time, you know, a lot of my commercial clients could learn a lot from you. And so the reason I bring that up is because I saw the same thing with Govcloud because there was a lot of skepticism in various industries, particularly regulated industries, financial services, healthcare. And then when Govcloud hit and the CIA deal hit, people said, whoa CIA, they're like the most security conscious industry or organization in the world. And so I feel as though in a way public sector led that that breakthrough. So I'm wondering when you think about EC two today and the momentum that it has in the government, Are there similar things that you see? Where's the momentum today in public sector? >>You are right on target day? I mean that CIA was a monumental moment and that momentum with ever increasing adoption to the cloud has continued in public sector. In fact today, public sector is one of our fastest growing areas. So we've got um, you know, thousands of startups or multiple countries that were helping out today to really ignite that innovation. We have over 4000 government agencies, 9000 education agencies. Um 2000 public sector partners from all over the globe. 24,000 not for profit organizations. And what I see is the way that they're using EC two um is is leading the pack now, especially after Covid, you know, many of these folks accelerated their journey because of Covid. They got to the cloud faster and now they are doing some really things that no one else is doing like sending an outpost postbox into space or leveraging, you know robots and health care for sure. So that momentum continues today and I love that you were the champion of that you know way back when even when you were with I. D. C. >>So I want to ask you, you sort of touched on some interesting use cases, what are some of the more unusual ones and maybe breakthrough use cases that you see? >>Oh so yeah we have a couple. So one is um I mentioned it earlier but there is a robot now that is powered by IOT and EC two and the robot helps to take temperature and and readings for folks that are entering the hospital in latin America really helped during Covid, one of my favorites. It actually blew the socks off of verne or two and you know that's hard to do is a space startup called lunar outpost and they are synthesizing oxygen on mars now that's, that's driven by Ec two. That's crazy. Right? Um, we see state governments like new york, they've got this vision zero traffic and they're leveraging that to prevent accidents all through new york city. I used to live in new york city. So this is really needed. Um, and it continues like with education, we see university of Illinois and Splunk one of our partners, they created a boarding pass for students to get back to school. So I have a daughter in college. Um, and you know, it's really hard for her to prove that she's had the vaccine or that she's tested negative on the covid test. They came out with a past of this little boarding pass, just like you used to get on an airplane to get into different classes and labs and then a couple of my favorites and you guys actually filmed the Cherokee nation. So the Cherokee nation, the chief of the Cherokee nation was on our silicon um show and silicon angles show and the cube featured them And as the chief talked about how he preserves the Cherokee language. And if you remember the Cherokee language has been used to help out the US in many different ways and Presidio. One of our partners helped to create a game, a super cool game that links in with unity To help teach that next generation the language while they're playing a game and then last but not least axle three d out of the UK. Um, they're using easy to, to save lives. They've created a three D imaging process for people getting ready to get kidney transplants and they have just enhanced that taken the time frame down for months. Now today's that they can actually articulate whether the kidney transplant will work. And when I talked to roger their Ceo, they're doing R. O. L return on life's not return on investment. So those are just some of the unusual and breakthrough use cases that we see powered by E. C. To >>Sandy. I'll give you the last word. Your final closing comments. >>Well, my final closing comments are happy birthday to ec two celebrating 15 years. What a game changer and value added. It has been the early days of Ec two. Of course we're about education like what is the cloud? Why is a bookseller doing it. But um, easy to really help to create a new hub of value Now. We've got customers moving so fast with modernization using a I. M and M. L. Containers survivalists. Um, and all of these things are really changing the game and leveling it up as we increased that business connection. So I think the future is really bright. We've only just begun. We've only just begun with EC two and we've only just begun with public sector. You know, our next great moments are still left to come. >>Well, Sandy, thanks so much. Always Great to see you. Really appreciate your time. >>Thank you so much. Dave. I really appreciate it. And happy birthday again to E. C. To keep >>It right there were celebrating Ec 2's 15th birthday right back. >>Mhm.

(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)

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

(light music) >> Announcer: TheCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Welcome back to the Fira in Barcelona. Dave Vellante with Dave Nicholson. Lisa Martin's been here all week. John Furrier is in our Palo Alto studio, banging out all the news. Don't forget to check out siliconangle.com, thecube.net. This is day four, our last segment, winding down. MWC23, super excited to be here. Wayne Duso, friend of theCUBE, VP of engineering from products at AWS is here with Iyad Tarazi, who's the CEO of Federated Wireless. Gents, welcome. >> Good to be here. >> Nice to see you. >> I'm so stoked, Wayne, that we connected before the show. We texted, I'm like, "You're going to be there. I'm going to be there. You got to come on theCUBE." So thank you so much for making time, and thank you for bringing a customer partner, Federated Wireless. Everybody knows AWS. Iyad, tell us about Federated Wireless. >> We're a software and services company out of Arlington, Virginia, right outside of Washington, DC, and we're really focused on this new technology called Shared Spectrum and private wireless for 5G. Think of it as enterprises consuming 5G, the way they used to consume WiFi. >> Is that unrestricted spectrum, or? >> It is managed, organized, interference free, all through cloud platforms. That's how we got to know AWS. We went and got maybe about 300 products from AWS to make it work. Quite sophisticated, highly available, and pristine spectrum worth billions of dollars, but available for people like you and I, that want to build enterprises, that want to make things work. Also carriers, cable companies everybody else that needs it. It's really a new revolution for everyone. >> And that's how you, it got introduced to AWS. Was that through public sector, or just the coincidence that you're in DC >> No, I, well, yes. The center of gravity in the world for spectrum is literally Arlington. You have the DOD spectrum people, you have spectrum people from National Science Foundation, DARPA, and then you have commercial sector, and you have the FCC just an Uber ride away. So we went and found the scientists that are doing all this work, four or five of them, Virginia Tech has an office there too, for spectrum research for the Navy. Come together, let's have a party and make a new model. >> So I asked this, I'm super excited to have you on theCUBE. I sat through the keynotes on Monday. I saw Satya Nadella was in there, Thomas Kurian there was no AWS. I'm like, where's AWS? AWS is everywhere. I mean, you guys are all over the show. I'm like, "Hey, where's the number one cloud?" So you guys have made a bunch of announcements at the show. Everybody's talking about the cloud. What's going on for you guys? >> So we are everywhere, and you know, we've been coming to this show for years. But this is really a year that we can demonstrate that what we've been doing for the IT enterprise, IT people for 17 years, we're now bringing for telcos, you know? For years, we've been, 17 years to be exact, we've been bringing the cloud value proposition, whether it's, you know, cost efficiencies or innovation or scale, reliability, security and so on, to these enterprise IT folks. Now we're doing the same thing for telcos. And so whether they want to build in region, in a local zone, metro area, on-prem with an outpost, at the edge with Snow Family, or with our IoT devices. And no matter where they want to start, if they start in the cloud and they want to move to the edge, or they start in the edge and they want to bring the cloud value proposition, like, we're demonstrating all of that is happening this week. And, and very much so, we're also demonstrating that we're bringing the same type of ecosystem that we've built for enterprise IT. We're bringing that type of ecosystem to the telco companies, with CSPs, with the ISP vendors. We've seen plenty of announcements this week. You know, so on and so forth. >> So what's different, is it, the names are different? Is it really that simple, that you're just basically taking the cloud model into telco, and saying, "Hey, why do all this undifferentiated heavy lifting when we can do it for you? Don't worry about all the plumbing." Is it really that simple? I mean, that straightforward. >> Well, simple is probably not what I'd say, but we can make it straightforward. >> Conceptually. >> Conceptually, yes. Conceptually it is the same. Because if you think about, firstly, we'll just take 5G for a moment, right? The 5G folks, if you look at the architecture for 5G, it was designed to run on a cloud architecture. It was designed to be a set of services that you could partition, and run in different places, whether it's in the region or at the edge. So in many ways it is sort of that simple. And let me give you an example. Two things, the first one is we announced integrated private wireless on AWS, which allows enterprise customers to come to a portal and look at the industry solutions. They're not worried about their network, they're worried about solving a problem, right? And they can come to that portal, they can find a solution, they can find a service provider that will help them with that solution. And what they end up with is a fully validated offering that AWS telco SAS have actually put to its paces to make sure this is a real thing. And whether they get it from a telco, and, and quite frankly in that space, it's SIs such as Federated that actually help our customers deploy those in private environments. So that's an example. And then added to that, we had a second announcement, which was AWS telco network builder, which allows telcos to plan, deploy, and operate at scale telco network capabilities on the cloud, think about it this way- >> As a managed service? >> As a managed service. So think about it this way. And the same way that enterprise IT has been deploying, you know, infrastructure as code for years. Telco network builder allows the telco folks to deploy telco networks and their capabilities as code. So it's not simple, but it is pretty straightforward. We're making it more straightforward as we go. >> Jump in Dave, by the way. He can geek out if you want. >> Yeah, no, no, no, that's good, that's good, that's good. But actually, I'm going to ask an AWS question, but I'm going to ask Iyad the AWS question. So when we, when I hear the word cloud from Wayne, cloud, AWS, typically in people's minds that denotes off-premises. Out there, AWS data center. In the telecom space, yes, of course, in the private 5G space, we're talking about a little bit of a different dynamic than in the public 5G space, in terms of the physical infrastructure. But regardless at the edge, there are things that need to be physically at the edge. Do you feel that AWS is sufficiently, have they removed the H word, hybrid, from the list of bad words you're not allowed to say? 'Cause there was a point in time- >> Yeah, of course. >> Where AWS felt that their growth- >> They'll even say multicloud today, (indistinct). >> No, no, no, no, no. But there was a period of time where, rightfully so, AWS felt that the growth trajectory would be supported solely by net new things off premises. Now though, in this space, it seems like that hybrid model is critical. Do you see AWS being open to the hybrid nature of things? >> Yeah, they're, absolutely. I mean, just to explain from- we're a services company and a solutions company. So we put together solutions at the edge, a smart campus, smart agriculture, a deployment. One of our biggest deployment is a million square feet warehouse automation project with the Marine Corps. >> That's bigger than the Fira. >> Oh yeah, it's bigger, definitely bigger than, you know, a small section of here. It's actually three massive warehouses. So yes, that is the edge. What the cloud is about is that massive amount of efficiency has happened by concentrating applications in data centers. And that is programmability, that is APIs that is solutions, that is applications that can run on it, where people know how to do it. And so all that efficiency now is being ported in a box called the edge. What AWS is doing for us is bringing all the business and technical solutions they had into the edge. Some of the data may send back and forth, but that's actually a smaller piece of the value for us. By being able to bring an AWS package at the edge, we're bringing IoT applications, we're bringing high speed cameras, we're able to integrate with the 5G public network. We're able to bring in identity and devices, we're able to bring in solutions for students, embedded laptops. All of these things that you can do much much faster and cheaper if you are able to tap in the 4,000, 5,000 partners and all the applications and all the development and all the models that AWS team did. By being able to bring that efficiency to the edge why reinvent that? And then along with that, there are partners that you, that help do integration. There are development done to make it hardened, to make the data more secure, more isolated. All of these things will contribute to an edge that truly is a carbon copy of the data center. >> So Wayne, it's AWS, Regardless of where the compute, networking and storage physically live, it's AWS. Do you think that the term cloud will sort of drift away from usage? Because if, look, it's all IT, in this case it's AWS and federated IT working together. How, what's your, it's sort of a obscure question about cloud, because cloud is so integrated. >> You Got this thing about cloud, it's just IT. >> I got thing about cloud too, because- >> You and Larry Ellison. >> Because it's no, no, no, I'm, yeah, well actually there's- >> There's a lot of IT that's not cloud, just say that okay. >> Now, a lot of IT that isn't cloud, but I would say- >> But I'll (indistinct) cloud is an IT tool, and you see AWS obviously with the Snow fill in the blank line of products and outpost type stuff. Fair to say that you're, doesn't matter where it is, it could be AWS if it's on the edge, right? >> Well, you know, everybody wants to define the cloud as what it may have been when it started. But if you look at what it was when it started and what it is today, it is different. But the ability to bring the experience, the AWS experience, the services, the operational experience and all the things that Iyad had been talking about from the region all to all the way to, you know, the IoT device, if you would, that entire continuum. And it doesn't matter where you start. Like if you start in region and you need to bring your value to other places because your customers are asking you to do so, we're enabling that experience where you need to bring it. If you started at the edge, and- but you want to build cloud value, you know, whether it's again, cost efficiency, scalability, AI, ML or analytics into those capabilities, you can start at the edge with the same APIs, with the same service, the same capabilities, and you can build that value in right from the get go. You don't build this bifurcation or many separations and try to figure out how do I glue them together? There is no gluing together. So if you think of cloud as being elastic, scalable flexible, where you can drive innovation, it's the same exact model on the continuum. And you can start at either end, it's up to you as a customer. >> And I think if, the key to me is the ecosystem. I mean, if you can do for this industry what you've done for the technology- enterprise technology business from an ecosystem standpoint, you know everybody talks about flywheel, but that gives you like the massive flywheel. I don't know what the ratio is, but it used to be for every dollar spent on a VMware license, $15 is spent in the ecosystem. I've never heard similar ratios in the AWS ecosystem, but it's, I go to reinvent and I'm like, there's some dollars being- >> That's a massive ecosystem. >> (indistinct). >> And then, and another thing I'll add is Jose Maria Alvarez, who's the chairman of Telefonica, said there's three pillars of the future-ready telco, low latency, programmable networks, and he said cloud and edge. So they recognizing cloud and edge, you know, low latency means you got to put the compute and the data, the programmable infrastructure was invented by Amazon. So what's the strategy around the telco edge? >> So, you know, at the end, so those are all great points. And in fact, the programmability of the network was a big theme in the show. It was a huge theme. And if you think about the cloud, what is the cloud? It's a set of APIs against a set of resources that you use in whatever way is appropriate for what you're trying to accomplish. The network, the telco network becomes a resource. And it could be described as a resource. We, I talked about, you know, network as in code, right? It's same infrastructure in code, it's telco infrastructure as code. And that code, that infrastructure, is programmable. So this is really, really important. And in how you build the ecosystem around that is no different than how we built the ecosystem around traditional IT abstractions. In fact, we feel that really the ecosystem is the killer app for 5G. You know, the killer app for 4G, data of sorts, right? We started using data beyond simple SMS messages. So what's the killer app for 5G? It's building this ecosystem, which includes the CSPs, the ISVs, all of the partners that we bring to the table that can drive greater value. It's not just about cost efficiency. You know, you can't save your way to success, right? At some point you need to generate greater value for your customers, which gives you better business outcomes, 'cause you can monetize them, right? The ecosystem is going to allow everybody to monetize 5G. >> 5G is like the dot connector of all that. And then developers come in on top and create new capabilities >> And how different is that than, you know, the original smartphones? >> Yeah, you're right. So what do you guys think of ChatGPT? (indistinct) to Amazon? Amazon turned the data center into an API. It's like we're visioning this world, and I want to ask that technologist, like, where it's turning resources into human language interfaces. You know, when you see that, you play with ChatGPT at all, or I know you guys got your own. >> So I won't speak directly to ChatGPT. >> No, don't speak from- >> But if you think about- >> Generative AI. >> Yeah generative AI is important. And, and we are, and we have been for years, in this space. Now you've been talking to AWS for a long time, and we often don't talk about things we don't have yet. We don't talk about things that we haven't brought to market yet. And so, you know, you'll often hear us talk about something, you know, a year from now where others may have been talking about it three years earlier, right? We will be talking about this space when we feel it's appropriate for our customers and our partners. >> You have talked about it a little bit, Adam Selipsky went on an interview with myself and John Furrier in October said you watch, you know, large language models are going to be enormous and I know you guys have some stuff that you're working on there. >> It's, I'll say it's exciting. >> Yeah, I mean- >> Well proof point is, Siri is an idiot compared to Alexa. (group laughs) So I trust one entity to come up with something smart. >> I have conversations with Alexa and Siri, and I won't judge either one. >> You don't need, you could be objective on that one. I definitely have a preference. >> Are the problems you guys solving in this space, you know, what's unique about 'em? What are they, can we, sort of, take some examples here (indistinct). >> Sure, the main theme is that the enterprise is taking control. They want to have their own networks. They want to focus on specific applications, and they want to build them with a skeleton crew. The one IT person in a warehouse want to be able to do it all. So what's unique about them is that they're now are a lot of automation on robotics, especially in warehousing environment agriculture. There simply aren't enough people in these industries, and that required precision. And so you need all that integration to make it work. People also want to build these networks as they want to control it. They want to figure out how do we actually pick this team and migrate it. Maybe just do the front of the house first. Maybe it's a security team that monitor the building, maybe later on upgrade things that use to open doors and close doors and collect maintenance data. So that ability to pick what you want to do from a new processors is really important. And then you're also seeing a lot of public-private network interconnection. That's probably the undercurrent of this show that haven't been talked about. When people say private networks, they're also talking about something called neutral host, which means I'm going to build my own network, but I want it to work, my Verizon (indistinct) need to work. There's been so much progress, it's not done yet. So much progress about this bring my own network concept, and then make sure that I'm now interoperating with the public network, but it's my domain. I can create air gaps, I can create whatever security and policy around it. That is probably the power of 5G. Now take all of these tiny networks, big networks, put them all in one ecosystem. Call it the Amazon marketplace, call it the Amazon ecosystem, that's 5G. It's going to be tremendous future. >> What does the future look like? We're going to, we just determined we're going to be orchestrating the network through human language, okay? (group laughs) But seriously, what's your vision for the future here? You know, both connectivity and cloud are on on a continuum. It's, they've been on a continuum forever. They're going to continue to be on a continuum. That being said, those continuums are coming together, right? They're coming together to bring greater value to a greater set of customers, and frankly all of us. So, you know, the future is now like, you know, this conference is the future, and if you look at what's going on, it's about the acceleration of the future, right? What we announced this week is really the acceleration of listening to customers for the last handful of years. And, we're going to continue to do that. We're going to continue to bring greater value in the form of solutions. And that's what I want to pick up on from the prior question. It's not about the network, it's not about the cloud, it's about the solutions that we can provide the customers where they are, right? And if they're on their mobile phone or they're in their factory floor, you know, they're looking to accelerate their business. They're looking to accelerate their value. They're looking to create greater safety for their employees. That's what we can do with these technologies. So in fact, when we came out with, you know, our announcement for integrated private wireless, right? It really was about industry solutions. It really isn't about, you know, the cloud or the network. It's about how you can leverage those technologies, that continuum, to deliver you value. >> You know, it's interesting you say that, 'cause again, when we were interviewing Adam Selipsky, everybody, you know, all journalists analysts want to know, how's Adam Selipsky going to be different from Andy Jassy, what's the, what's he going to do to Amazon to change? And he said, listen, the real answer is Amazon has changed. If Andy Jassy were here, we'd be doing all, you know, pretty much the same things. Your point about 17 years ago, the cloud was S3, right, and EC2. Now it's got to evolve to be solutions. 'Cause if that's all you're selling, is the bespoke services, then you know, the future is not as bright as the past has been. And so I think it's key to look for what are those outcomes or solutions that customers require and how you're going to meet 'em. And there's a lot of challenges. >> You continue to build value on the value that you've brought, and you don't lose sight of why that value is important. You carry that value proposition up the stack, but the- what you're delivering, as you said, becomes maybe a bigger or or different. >> And you are getting more solution oriented. I mean, you're not hardcore solutions yet, but we're seeing more and more of that. And that seems to be a trend. We've even seen in the database world, making things easier, connecting things. Not really an abstraction layer, which is sort of antithetical to your philosophy, but it creates a similar outcome in terms of simplicity. Yeah, you're smiling 'cause you guys always have a different angle, you know? >> Yeah, we've had this conversation. >> It's right, it's, Jassy used to say it's okay to be misunderstood. >> That's Right. For a long time. >> Yeah, right, guys, thanks so much for coming to theCUBE. I'm so glad we could make this happen. >> It's always good. Thank you. >> Thank you so much. >> All right, Dave Nicholson, for Lisa Martin, Dave Vellante, John Furrier in the Palo Alto studio. We're here at the Fira, wrapping out MWC23. Keep it right there, thanks for watching. (upbeat music)

(bright music) >> Hi, everybody, this is Dave Vellante, welcome back to Supercloud 2. Last August, at the first Supercloud event, we invited the broader community to help further define Supercloud, we assessed its viability, and identified the critical elements and deployment models of the concept. The objectives here at Supercloud too are, first of all, to continue to tighten and test the concept, the second is, we want to get real world input from practitioners on the problems that they're facing and the viability of Supercloud in terms of applying it to their business. So on the program, we got companies like Walmart, Sachs, Western Union, Ionis Pharmaceuticals, NASDAQ, and others. And the third thing that we want to do is we want to drill into the intersection of cloud and data to project what the future looks like in the context of Supercloud. So in this segment, we want to explore the concept of data architectures and what's going to be required for Supercloud. And I'm pleased to welcome one of our Supercloud sponsors, ChaosSearch, Ed Walsh is the CEO of the company, with Thomas Hazel, who's the Founder, CTO, and Chief Scientist. Guys, good to see you again, thanks for coming into our Marlborough studio. >> Always great. >> Great to be here. >> Okay, so there's a little debate, I'm going to put you right in the spot. (Ed chuckling) A little debate going on in the community started by Bob Muglia, a former CEO of Snowflake, and he was at Microsoft for a long time, and he looked at the Supercloud definition, said, "I think you need to tighten it up a little bit." So, here's what he came up with. He said, "A Supercloud is a platform that provides a programmatically consistent set of services hosted on heterogeneous cloud providers." So he's calling it a platform, not an architecture, which was kind of interesting. And so presumably the platform owner is going to be responsible for the architecture, but Dr. Nelu Mihai, who's a computer scientist behind the Cloud of Clouds Project, he chimed in and responded with the following. He said, "Cloud is a programming paradigm supporting the entire lifecycle of applications with data and logic natively distributed. Supercloud is an open architecture that integrates heterogeneous clouds in an agnostic manner." So, Ed, words matter. Is this an architecture or is it a platform? >> Put us on the spot. So, I'm sure you have concepts, I would say it's an architectural or design principle. Listen, I look at Supercloud as a mega trend, just like cloud, just like data analytics. And some companies are using the principle, design principles, to literally get dramatically ahead of everyone else. I mean, things you couldn't possibly do if you didn't use cloud principles, right? So I think it's a Supercloud effect, you're able to do things you're not able to. So I think it's more a design principle, but if you do it right, you get dramatic effect as far as customer value. >> So the conversation that we were having with Muglia, and Tristan Handy of dbt Labs, was, I'll set it up as the following, and, Thomas, would love to get your thoughts, if you have a CRM, think about applications today, it's all about forms and codifying business processes, you type a bunch of stuff into Salesforce, and all the salespeople do it, and this machine generates a forecast. What if you have this new type of data app that pulls data from the transaction system, the e-commerce, the supply chain, the partner ecosystem, et cetera, and then, without humans, actually comes up with a plan. That's their vision. And Muglia was saying, in order to do that, you need to rethink data architectures and database architectures specifically, you need to get down to the level of how the data is stored on the disc. What are your thoughts on that? Well, first of all, I'm going to cop out, I think it's actually both. I do think it's a design principle, I think it's not open technology, but open APIs, open access, and you can build a platform on that design principle architecture. Now, I'm a database person, I love solving the database problems. >> I'm waited for you to launch into this. >> Yeah, so I mean, you know, Snowflake is a database, right? It's a distributed database. And we wanted to crack those codes, because, multi-region, multi-cloud, customers wanted access to their data, and their data is in a variety of forms, all these services that you're talked about. And so what I saw as a core principle was cloud object storage, everyone streams their data to cloud object storage. From there we said, well, how about we rethink database architecture, rethink file format, so that we can take each one of these services and bring them together, whether distributively or centrally, such that customers can access and get answers, whether it's operational data, whether it's business data, AKA search, or SQL, complex distributed joins. But we had to rethink the architecture. I like to say we're not a first generation, or a second, we're a third generation distributed database on pure, pure cloud storage, no caching, no SSDs. Why? Because all that availability, the cost of time, is a struggle, and cloud object storage, we think, is the answer. >> So when you're saying no caching, so when I think about how companies are solving some, you know, pretty hairy problems, take MySQL Heatwave, everybody thought Oracle was going to just forget about MySQL, well, they come out with Heatwave. And the way they solve problems, and you see their benchmarks against Amazon, "Oh, we crush everybody," is they put it all in memory. So you said no caching? You're not getting performance through caching? How is that true, and how are you getting performance? >> Well, so five, six years ago, right? When you realize that cloud object storage is going to be everywhere, and it's going to be a core foundational, if you will, fabric, what would you do? Well, a lot of times the second generation say, "We'll take it out of cloud storage, put in SSDs or something, and put into cache." And that adds a lot of time, adds a lot of costs. But I said, what if, what if we could actually make the first read hot, the first read distributed joins and searching? And so what we went out to do was said, we can't cache, because that's adds time, that adds cost. We have to make cloud object storage high performance, like it feels like a caching SSD. That's where our patents are, that's where our technology is, and we've spent many years working towards this. So, to me, if you can crack that code, a lot of these issues we're talking about, multi-region, multicloud, different services, everybody wants to send their data to the data lake, but then they move it out, we said, "Keep it right there." >> You nailed it, the data gravity. So, Bob's right, the data's coming in, and you need to get the data from everywhere, but you need an environment that you can deal with all that different schema, all the different type of technology, but also at scale. Bob's right, you cannot use memory or SSDs to cache that, that doesn't scale, it doesn't scale cost effectively. But if you could, and what you did, is you made object storage, S3 first, but object storage, the only persistence by doing that. And then we get performance, we should talk about it, it's literally, you know, hundreds of terabytes of queries, and it's done in seconds, it's done without memory caching. We have concepts of caching, but the only caching, the only persistence, is actually when we're doing caching, we're just keeping another side-eye track of things on the S3 itself. So we're using, actually, the object storage to be a database, which is kind of where Bob was saying, we agree, but that's what you started at, people thought you were crazy. >> And maybe make it live. Don't think of it as archival or temporary space, make it live, real time streaming, operational data. What we do is make it smart, we see the data coming in, we uniquely index it such that you can get your use cases, that are search, observability, security, or backend operational. But we don't have to have this, I dunno, static, fixed, siloed type of architecture technologies that were traditionally built prior to Supercloud thinking. >> And you don't have to move everything, essentially, you can do it wherever the data lands, whatever cloud across the globe, you're able to bring it together, you get the cost effectiveness, because the only persistence is the cheapest storage persistent layer you can buy. But the key thing is you cracked the code. >> We had to crack the code, right? That was the key thing. >> That's where the plans are. >> And then once you do that, then everything else gets easier to scale, your architecture, across regions, across cloud. >> Now, it's a general purpose database, as Bob was saying, but we use that database to solve a particular issue, which is around operational data, right? So, we agree with Bob's. >> Interesting. So this brings me to this concept of data, Jimata Gan is one of our speakers, you know, we talk about data fabric, which is a NetApp, originally NetApp concept, Gartner's kind of co-opted it. But so, the basic concept is, data lives everywhere, whether it's an S3 bucket, or a SQL database, or a data lake, it's just a node on the data mesh. So in your view, how does this fit in with Supercloud? Ed, you've said that you've built, essentially, an enabler for that, for the data mesh, I think you're an enabler for the Supercloud-like principles. This is a big, chewy opportunity, and it requires, you know, a team approach. There's got to be an ecosystem, there's not going to be one Supercloud to rule them all, so where does the ecosystem fit into the discussion, and where do you fit into the ecosystem? >> Right, so we agree completely, there's not one Supercloud in effect, but we use Supercloud principles to build our platform, and then, you know, the ecosystem's going to be built on leveraging what everyone else's secret powers are, right? So our power, our superpower, based upon what we built is, we deal with, if you're having any scale, or cost effective scale issues, with data, machine generated data, like business observability or security data, we are your force multiplier, we will take that in singularly, just let it, simply put it in your object storage wherever it sits, and we give you uniformity access to that using OpenAPI access, SQL, or you know, Elasticsearch API. So, that's what we do, that's our superpower. So I'll play it into data mesh, that's a perfect, we are a node on a data mesh, but I'll play it in the soup about how, the ecosystem, we see it kind of playing, and we talked about it in just in the last couple days, how we see this kind of possibly. Short term, our superpowers, we deal with this data that's coming at these environments, people, customers, building out observability or security environments, or vendors that are selling their own Supercloud, I do observability, the Datadogs of the world, dot dot dot, the Splunks of the world, dot dot dot, and security. So what we do is we fit in naturally. What we do is a cost effective scale, just land it anywhere in the world, we deal with ingest, and it's a cost effective, an order of magnitude, or two or three order magnitudes more cost effective. Allows them, their customers are asking them to do the impossible, "Give me fast monitoring alerting. I want it snappy, but I want it to keep two years of data, (laughs) and I want it cost effective." It doesn't work. They're good at the fast monitoring alerting, we're good at the long-term retention. And yet there's some gray area between those two, but one to one is actually cheaper, so we would partner. So the first ecosystem plays, who wants to have the ability to, really, all the data's in those same environments, the security observability players, they can literally, just through API, drag our data into their point to grab. We can make it seamless for customers. Right now, we make it helpful to customers. Your Datadog, we make a button, easy go from Datadog to us for logs, save you money. Same thing with Grafana. But you can also look at ecosystem, those same vendors, it used to be a year ago it was, you know, its all about how can you grow, like it's growth at all costs, now it's about cogs. So literally we can go an environment, you supply what your customer wants, but we can help with cogs. And one-on one in a partnership is better than you trying to build on your own. >> Thomas, you were saying you make the first read fast, so you think about Snowflake. Everybody wants to talk about Snowflake and Databricks. So, Snowflake, great, but you got to get the data in there. All right, so that's, can you help with that problem? >> I mean we want simple in, right? And if you have to have structure in, you're not simple. So the idea that you have a simple in, data lake, schema read type philosophy, but schema right type performance. And so what I wanted to do, what we have done, is have that simple lake, and stream that data real time, and those access points of Search or SQL, to go after whatever business case you need, security observability, warehouse integration. But the key thing is, how do I make that click, click, click answer, and do it quickly? And so what we want to do is, that first read has to be fast. Why? 'Cause then you're going to do all this siloing, layers, complexity. If your first read's not fast, you're at a disadvantage, particularly in cost. And nobody says I want less data, but everyone has to, whether they say we're going to shorten the window, we're going to use AI to choose, but in a security moment, when you don't have that answer, you're in trouble. And that's why we are this service, this Supercloud service, if you will, providing access, well-known search, well-known SQL type access, that if you just have one access point, you're at a disadvantage. >> We actually talked about Snowflake and BigQuery, and a different platform, Data Bricks. That's kind of where we see the phase two of ecosystem. One is easy, the low-hanging fruit is observability and security firms. But the next one is, what we do, our super power is dealing with this messy data that schema is changing like night and day. Pipelines are tough, and it's changing all the time, but you want these things fast, and it's big data around the world. That's the next point, just use us alongside, or inside, one of their platforms, and now we get the best of both worlds. Our superpower is keeping this messy data as a streaming, okay, not a batch thing, allow you to do that. So, that's the second one. And then to be honest, the third one, which plays you to Supercloud, it also plays perfectly in the data mesh, is if you really go to the ultimate thing, what we have done is made object storage, S3, GCS, and blob storage, we made it a database. Put, get, complex query with big joins. You know, so back to your original thing, and Muglia teed it up perfectly, we've done that. Now imagine if that's an ecosystem, who would want that? If it's, again, it's uniform available across all the regions, across all the clouds, and it's right next to where you are building a service, or a client's trying, that's where the ecosystem, I think people are going to use Superclouds for their superpowers. We're really good at this, allows that short term. I think the Snowflakes and the Data Bricks are the medium term, you know? And then I think eventually gets to, hey, listen if you can make object storage fast, you can just go after it with simple SQL queries, or elastic. Who would want that? I think that's where people are going to leverage it. It's not going to be one Supercloud, and we leverage the super clouds. >> Our viewpoint is smart object storage can be programmable, and so we agree with Bob, but we're not saying do it here, do it here. This core, fundamental layer across regions, across clouds, that everyone has? Simple in. Right now, it's hard to get data in for access for analysis. So we said, simply, we'll automate the entire process, give you API access across regions, across clouds. And again, how do you do a distributed join that's fast? How do you do a distributed join that doesn't cost you an arm or a leg? And how do you do it at scale? And that's where we've been focused. >> So prior, the cloud object store was a niche. >> Yeah. >> S3 obviously changed that. How standard is, essentially, object store across the different cloud platforms? Is that a problem for you? Is that an easy thing to solve? >> Well, let's talk about it. I mean we've fundamentally, yeah we've extracted it, but fundamentally, cloud object storage, put, get, and list. That's why it's so scalable, 'cause it doesn't have all these other components. That complexity is where we have moved up, and provide direct analytical API access. So because of its simplicity, and costs, and security, and reliability, it can scale naturally. I mean, really, distributed object storage is easy, it's put-get anywhere, now what we've done is we put a layer of intelligence, you know, call it smart object storage, where access is simple. So whether it's multi-region, do a query across, or multicloud, do a query across, or hunting, searching. >> We've had clients doing Amazon and Google, we have some Azure, but we see Amazon and Google more, and it's a consistent service across all of them. Just literally put your data in the bucket of choice, or folder of choice, click a couple buttons, literally click that to say "that's hot," and after that, it's hot, you can see it. But we're not moving data, the data gravity issue, that's the other. That it's already natively flowing to these pools of object storage across different regions and clouds. We don't move it, we index it right there, we're spinning up stateless compute, back to the Supercloud concept. But now that allows us to do all these other things, right? >> And it's no longer just cheap and deep object storage. Right? >> Yeah, we make it the same, like you have an analytic platform regardless of where you're at, you don't have to worry about that. Yeah, we deal with that, we deal with a stateless compute coming up -- >> And make it programmable. Be able to say, "I want this bucket to provide these answers." Right, that's really the hope, the vision. And the complexity to build the entire stack, and then connect them together, we said, the fabric is cloud storage, we just provide the intelligence on top. >> Let's bring it back to the customers, and one of the things we're exploring in Supercloud too is, you know, is Supercloud a solution looking for a problem? Is a multicloud really a problem? I mean, you hear, you know, a lot of the vendor marketing says, "Oh, it's a disaster, because it's all different across the clouds." And I talked to a lot of customers even as part of Supercloud too, they're like, "Well, I solved that problem by just going mono cloud." Well, but then you're not able to take advantage of a lot of the capabilities and the primitives that, you know, like Google's data, or you like Microsoft's simplicity, their RPA, whatever it is. So what are customers telling you, what are their near term problems that they're trying to solve today, and how are they thinking about the future? >> Listen, it's a real problem. I think it started, I think this is a a mega trend, just like cloud. Just, cloud data, and I always add, analytics, are the mega trends. If you're looking at those, if you're not considering using the Supercloud principles, in other words, leveraging what I have, abstracting it out, and getting the most out of that, and then build value on top, I think you're not going to be able to keep up, In fact, no way you're going to keep up with this data volume. It's a geometric challenge, and you're trying to do linear things. So clients aren't necessarily asking, hey, for Supercloud, but they're really saying, I need to have a better mechanism to simplify this and get value across it, and how do you abstract that out to do that? And that's where they're obviously, our conversations are more amazed what we're able to do, and what they're able to do with our platform, because if you think of what we've done, the S3, or GCS, or object storage, is they can't imagine the ingest, they can't imagine how easy, time to glass, one minute, no matter where it lands in the world, querying this in seconds for hundreds of terabytes squared. People are amazed, but that's kind of, so they're not asking for that, but they are amazed. And then when you start talking on it, if you're an enterprise person, you're building a big cloud data platform, or doing data or analytics, if you're not trying to leverage the public clouds, and somehow leverage all of them, and then build on top, then I think you're missing it. So they might not be asking for it, but they're doing it. >> And they're looking for a lens, you mentioned all these different services, how do I bring those together quickly? You know, our viewpoint, our service, is I have all these streams of data, create a lens where they want to go after it via search, go after via SQL, bring them together instantly, no e-tailing out, no define this table, put into this database. We said, let's have a service that creates a lens across all these streams, and then make those connections. I want to take my CRM with my Google AdWords, and maybe my Salesforce, how do I do analysis? Maybe I want to hunt first, maybe I want to join, maybe I want to add another stream to it. And so our viewpoint is, it's so natural to get into these lake platforms and then provide lenses to get that access. >> And they don't want it separate, they don't want something different here, and different there. They want it basically -- >> So this is our industry, right? If something new comes out, remember virtualization came out, "Oh my God, this is so great, it's going to solve all these problems." And all of a sudden it just got to be this big, more complex thing. Same thing with cloud, you know? It started out with S3, and then EC2, and now hundreds and hundreds of different services. So, it's a complex matter for a lot of people, and this creates problems for customers, especially when you got divisions that are using different clouds, and you're saying that the solution, or a solution for the part of the problem, is to really allow the data to stay in place on S3, use that standard, super simple, but then give it what, Ed, you've called superpower a couple of times, to make it fast, make it inexpensive, and allow you to do that across clouds. >> Yeah, yeah. >> I'll give you guys the last word on that. >> No, listen, I think, we think Supercloud allows you to do a lot more. And for us, data, everyone says more data, more problems, more budget issue, everyone knows more data is better, and we show you how to do it cost effectively at scale. And we couldn't have done it without the design principles of we're leveraging the Supercloud to get capabilities, and because we use super, just the object storage, we're able to get these capabilities of ingest, scale, cost effectiveness, and then we built on top of this. In the end, a database is a data platform that allows you to go after everything distributed, and to get one platform for analytics, no matter where it lands, that's where we think the Supercloud concepts are perfect, that's where our clients are seeing it, and we're kind of excited about it. >> Yeah a third generation database, Supercloud database, however we want to phrase it, and make it simple, but provide the value, and make it instant. >> Guys, thanks so much for coming into the studio today, I really thank you for your support of theCUBE, and theCUBE community, it allows us to provide events like this and free content. I really appreciate it. >> Oh, thank you. >> Thank you. >> All right, this is Dave Vellante for John Furrier in theCUBE community, thanks for being with us today. You're watching Supercloud 2, keep it right there for more thought provoking discussions around the future of cloud and data. (bright music)

(light music) >> Hi everybody. Welcome to this Cube Conversation. I'm really pleased to announce a collaboration with Rob Strechay. He's a guest cube analyst, and we'll be working together to extract the signal from the noise. Rob is a long-time product pro, working at a number of firms including AWS, HP, HPE, NetApp, Snowplow. I did a stint as an analyst at Enterprise Strategy Group. Rob, good to see you. Thanks for coming into our Marlboro Studios. >> Well, thank you for having me. It's always great to be here. >> I'm really excited about working with you. We've known each other for a long time. You've been in the Cube a bunch. You know, you're in between gigs, and I think we can have a lot of fun together. Covering events, covering trends. So. let's get into it. What's happening out there? We're sort of exited the isolation economy. Things were booming. Now, everybody's tapping the brakes. From your standpoint, what are you seeing out there? >> Yeah. I'm seeing that people are really looking how to get more out of their data. How they're bringing things together, how they're looking at the costs of Cloud, and understanding how are they building out their SaaS applications. And understanding that when they go in and actually start to use Cloud, it's not only just using the base services anymore. They're looking at, how do I use these platforms as a service? Some are easier than others, and they're trying to understand, how do I get more value out of that relationship with the Cloud? They're also consolidating the number of Clouds that they have, I would say to try to better optimize their spend, and getting better pricing for that matter. >> Are you seeing people unhook Clouds, or just reduce maybe certain Cloud activities and going maybe instead of 60/40 going 90/10? >> Correct. It's more like the 90/10 type of rule where they're starting to say, Hey I'm not going to get rid of Azure or AWS or Google. I'm going to move a portion of this over that I was using on this one service. Maybe I got a great two-year contract to start with on this platform as a service or a database as a service. I'm going to unhook from that and maybe go with an independent. Maybe with something like a Snowflake or a Databricks on top of another Cloud, so that I can consolidate down. But it also gives them more flexibility as well. >> In our last breaking analysis, Rob, we identified six factors that were reducing Cloud consumption. There were factors and customer tactics. And I want to get your take on this. So, some of the factors really, you got fewer mortgage originations. FinTech, obviously big Cloud user. Crypto, not as much activity there. Lower ad spending means less Cloud. And then one of 'em, which you kind of disagreed with was less, less analytics, you know, fewer... Less frequency of calculations. I'll come back to that. But then optimizing compute using Graviton or AMD instances moving to cheaper storage tiers. That of course makes sense. And then optimize pricing plans. Maybe going from On Demand, you know, to, you know, instead of pay by the drink, buy in volume. Okay. So, first of all, do those make sense to you with the exception? We'll come back and talk about the analytics piece. Is that what you're seeing from customers? >> Yeah, I think so. I think that was pretty much dead on with what I'm seeing from customers and the ones that I go out and talk to. A lot of times they're trying to really monetize their, you know, understand how their business utilizes these Clouds. And, where their spend is going in those Clouds. Can they use, you know, lower tiers of storage? Do they really need the best processors? Do they need to be using Intel or can they get away with AMD or Graviton 2 or 3? Or do they need to move in? And, I think when you look at all of these Clouds, they always have pricing curves that are arcs from the newest to the oldest stuff. And you can play games with that. And understanding how you can actually lower your costs by looking at maybe some of the older generation. Maybe your application was written 10 years ago. You don't necessarily have to be on the best, newest processor for that application per se. >> So last, I want to come back to this whole analytics piece. Last June, I think it was June, Dev Ittycheria, who's the-- I call him Dev. Spelled Dev, pronounced Dave. (chuckles softly) Same pronunciation, different spelling. Dev Ittycheria, CEO of Mongo, on the earnings call. He was getting, you know, hit. Things were starting to get a little less visible in terms of, you know, the outlook. And people were pushing him like... Because you're in the Cloud, is it easier to dial down? And he said, because we're the document database, we support transaction applications. We're less discretionary than say, analytics. Well on the Snowflake earnings call, that same month or the month after, they were all over Slootman and Scarpelli. Oh, the Mongo CEO said that they're less discretionary than analytics. And Snowflake was an interesting comment. They basically said, look, we're the Cloud. You can dial it up, you can dial it down, but the area under the curve over a period of time is going to be the same, because they get their customers to commit. What do you say? You disagreed with the notion that people are running their calculations less frequently. Is that because they're trying to do a better job of targeting customers in near real time? What are you seeing out there? >> Yeah, I think they're moving away from using people and more expensive marketing. Or, they're trying to figure out what's my Google ad spend, what's my Meta ad spend? And what they're trying to do is optimize that spend. So, what is the return on advertising, or the ROAS as they would say. And what they're looking to do is understand, okay, I have to collect these analytics that better understand where are these people coming from? How do they get to my site, to my store, to my whatever? And when they're using it, how do they they better move through that? What you're also seeing is that analytics is not only just for kind of the retail or financial services or things like that, but then they're also, you know, using that to make offers in those categories. When you move back to more, you know, take other companies that are building products and SaaS delivered products. They may actually go and use this analytics for making the product better. And one of the big reasons for that is maybe they're dialing back how many product managers they have. And they're looking to be more data driven about how they actually go and build the product out or enhance the product. So maybe they're, you know, an online video service and they want to understand why people are either using or not using the whiteboard inside the product. And they're collecting a lot of that product analytics in a big way so that they can go through that. And they're doing it in a constant manner. This first party type tracking within applications is growing rapidly by customers. >> So, let's talk about who wins in that. So, obviously the Cloud guys, AWS, Google and Azure. I want to come back and unpack that a little bit. Databricks and Snowflake, we reported on our last breaking analysis, it kind of on a collision course. You know, a couple years ago we were thinking, okay, AWS, Snowflake and Databricks, like perfect sandwich. And then of course they started to become more competitive. My sense is they still, you know, compliment each other in the field, right? But, you know, publicly, they've got bigger aspirations, they get big TAMs that they're going after. But it's interesting, the data shows that-- So, Snowflake was off the charts in terms of spending momentum and our EPR surveys. Our partner down in New York, they kind of came into line. They're both growing in terms of market presence. Databricks couldn't get to IPO. So, we don't have as much, you know, visibility on their financials. You know, Snowflake obviously highly transparent cause they're a public company. And then you got AWS, Google and Azure. And it seems like AWS appears to be more partner friendly. Microsoft, you know, depends on what market you're in. And Google wants to sell BigQuery. >> Yeah. >> So, what are you seeing in the public Cloud from a data platform perspective? >> Yeah. I think that was pretty astute in what you were talking about there, because I think of the three, Google is definitely I think a little bit behind in how they go to market with their partners. Azure's done a fantastic job of partnering with these companies to understand and even though they may have Synapse as their go-to and where they want people to go to do AI and ML. What they're looking at is, Hey, we're going to also be friendly with Snowflake. We're also going to be friendly with a Databricks. And I think that, Amazon has always been there because that's where the market has been for these developers. So, many, like Databricks' and the Snowflake's have gone there first because, you know, Databricks' case, they built out on top of S3 first. And going and using somebody's object layer other than AWS, was not as simple as you would think it would be. Moving between those. >> So, one of the financial meetups I said meetup, but the... It was either the CEO or the CFO. It was either Slootman or Scarpelli talking at, I don't know, Merrill Lynch or one of the other financial conferences said, I think it was probably their Q3 call. Snowflake said 80% of our business goes through Amazon. And he said to this audience, the next day we got a call from Microsoft. Hey, we got to do more. And, we know just from reading the financial statements that Snowflake is getting concessions from Amazon, they're buying in volume, they're renegotiating their contracts. Amazon gets it. You know, lower the price, people buy more. Long term, we're all going to make more money. Microsoft obviously wants to get into that game with Snowflake. They understand the momentum. They said Google, not so much. And I've had customers tell me that they wanted to use Google's AI with Snowflake, but they can't, they got to go to to BigQuery. So, honestly, I haven't like vetted that so. But, I think it's true. But nonetheless, it seems like Google's a little less friendly with the data platform providers. What do you think? >> Yeah, I would say so. I think this is a place that Google looks and wants to own. Is that now, are they doing the right things long term? I mean again, you know, you look at Google Analytics being you know, basically outlawed in five countries in the EU because of GDPR concerns, and compliance and governance of data. And I think people are looking at Google and BigQuery in general and saying, is it the best place for me to go? Is it going to be in the right places where I need it? Still, it's still one of the largest used databases out there just because it underpins a number of the Google services. So you almost get, like you were saying, forced into BigQuery sometimes, if you want to use the tech on top. >> You do strategy. >> Yeah. >> Right? You do strategy, you do messaging. Is it the right call by Google? I mean, it's not a-- I criticize Google sometimes. But, I'm not sure it's the wrong call to say, Hey, this is our ace in the hole. >> Yeah. >> We got to get people into BigQuery. Cause, first of all, BigQuery is a solid product. I mean it's Cloud native and it's, you know, by all, it gets high marks. So, why give the competition an advantage? Let's try to force people essentially into what is we think a great product and it is a great product. The flip side of that is, they're giving up some potential partner TAM and not treating the ecosystem as well as one of their major competitors. What do you do if you're in that position? >> Yeah, I think that that's a fantastic question. And the question I pose back to the companies I've worked with and worked for is, are you really looking to have vendor lock-in as your key differentiator to your service? And I think when you start to look at these companies that are moving away from BigQuery, moving to even, Databricks on top of GCS in Google, they're looking to say, okay, I can go there if I have to evacuate from GCP and go to another Cloud, I can stay on Databricks as a platform, for instance. So I think it's, people are looking at what platform as a service, database as a service they go and use. Because from a strategic perspective, they don't want that vendor locking. >> That's where Supercloud becomes interesting, right? Because, if I can run on Snowflake or Databricks, you know, across Clouds. Even Oracle, you know, they're getting into business with Microsoft. Let's talk about some of the Cloud players. So, the big three have reported. >> Right. >> We saw AWSs Cloud growth decelerated down to 20%, which is I think the lowest growth rate since they started to disclose public numbers. And they said they exited, sorry, they said January they grew at 15%. >> Yeah. >> Year on year. Now, they had some pretty tough compares. But nonetheless, 15%, wow. Azure, kind of mid thirties, and then Google, we had kind of low thirties. But, well behind in terms of size. And Google's losing probably almost $3 billion annually. But, that's not necessarily a bad thing by advocating and investing. What's happening with the Cloud? Is AWS just running into the law, large numbers? Do you think we can actually see a re-acceleration like we have in the past with AWS Cloud? Azure, we predicted is going to be 75% of AWS IAS revenues. You know, we try to estimate IAS. >> Yeah. >> Even though they don't share that with us. That's a huge milestone. You'd think-- There's some people who have, I think, Bob Evans predicted a while ago that Microsoft would surpass AWS in terms of size. You know, what do you think? >> Yeah, I think that Azure's going to keep to-- Keep growing at a pretty good clip. I think that for Azure, they still have really great account control, even though people like to hate Microsoft. The Microsoft sellers that are out there making those companies successful day after day have really done a good job of being in those accounts and helping people. I was recently over in the UK. And the UK market between AWS and Azure is pretty amazing, how much Azure there is. And it's growing within Europe in general. In the states, it's, you know, I think it's growing well. I think it's still growing, probably not as fast as it is outside the U.S. But, you go down to someplace like Australia, it's also Azure. You hear about Azure all the time. >> Why? Is that just because of the Microsoft's software state? It's just so convenient. >> I think it has to do with, you know, and you can go with the reasoning they don't break out, you know, Office 365 and all of that out of their numbers is because they have-- They're in all of these accounts because the office suite is so pervasive in there. So, they always have reasons to go back in and, oh by the way, you're on these old SQL licenses. Let us move you up here and we'll be able to-- We'll support you on the old version, you know, with security and all of these things. And be able to move you forward. So, they have a lot of, I guess you could say, levers to stay in those accounts and be interesting. At least as part of the Cloud estate. I think Amazon, you know, is hitting, you know, the large number. Laws of large numbers. But I think that they're also going through, and I think this was seen in the layoffs that they were making, that they're looking to understand and have profitability in more of those services that they have. You know, over 350 odd services that they have. And you know, as somebody who went there and helped to start yet a new one, while I was there. And finally, it went to beta back in September, you start to look at the fact that, that number of services, people, their own sellers don't even know all of their services. It's impossible to comprehend and sell that many things. So, I think what they're going through is really looking to rationalize a lot of what they're doing from a services perspective going forward. They're looking to focus on more profitable services and bringing those in. Because right now it's built like a layer cake where you have, you know, S3 EBS and EC2 on the bottom of the layer cake. And then maybe you have, you're using IAM, the authorization and authentication in there and you have all these different services. And then they call it EMR on top. And so, EMR has to pay for that entire layer cake just to go and compete against somebody like Mongo or something like that. So, you start to unwind the costs of that. Whereas Azure, went and they build basically ground up services for the most part. And Google kind of falls somewhere in between in how they build their-- They're a sort of layer cake type effect, but not as many layers I guess you could say. >> I feel like, you know, Amazon's trying to be a platform for the ecosystem. Yes, they have their own products and they're going to sell. And that's going to drive their profitability cause they don't have to split the pie. But, they're taking a piece of-- They're spinning the meter, as Ziyas Caravalo likes to say on every time Snowflake or Databricks or Mongo or Atlas is, you know, running on their system. They take a piece of the action. Now, Microsoft does that as well. But, you look at Microsoft and security, head-to-head competitors, for example, with a CrowdStrike or an Okta in identity. Whereas, it seems like at least for now, AWS is a more friendly place for the ecosystem. At the same time, you do a lot of business in Microsoft. >> Yeah. And I think that a lot of companies have always feared that Amazon would just throw, you know, bodies at it. And I think that people have come to the realization that a two pizza team, as Amazon would call it, is eight people. I think that's, you know, two slices per person. I'm a little bit fat, so I don't know if that's enough. But, you start to look at it and go, okay, if they're going to start out with eight engineers, if I'm a startup and they're part of my ecosystem, do I really fear them or should I really embrace them and try to partner closer with them? And I think the smart people and the smart companies are partnering with them because they're realizing, Amazon, unless they can see it to, you know, a hundred million, $500 million market, they're not going to throw eight to 16 people at a problem. I think when, you know, you could say, you could look at the elastic with OpenSearch and what they did there. And the licensing terms and the battle they went through. But they knew that Elastic had a huge market. Also, you had a number of ecosystem companies building on top of now OpenSearch, that are now domain on top of Amazon as well. So, I think Amazon's being pretty strategic in how they're doing it. I think some of the-- It'll be interesting. I think this year is a payout year for the cuts that they're making to some of the services internally to kind of, you know, how do we take the fat off some of those services that-- You know, you look at Alexa. I don't know how much revenue Alexa really generates for them. But it's a means to an end for a number of different other services and partners. >> What do you make of this ChatGPT? I mean, Microsoft obviously is playing that card. You want to, you want ChatGPT in the Cloud, come to Azure. Seems like AWS has to respond. And we know Google is, you know, sharpening its knives to come up with its response. >> Yeah, I mean Google just went and talked about Bard for the first time this week and they're in private preview or I guess they call it beta, but. Right at the moment to select, select AI users, which I have no idea what that means. But that's a very interesting way that they're marketing it out there. But, I think that Amazon will have to respond. I think they'll be more measured than say, what Google's doing with Bard and just throwing it out there to, hey, we're going into beta now. I think they'll look at it and see where do we go and how do we actually integrate this in? Because they do have a lot of components of AI and ML underneath the hood that other services use. And I think that, you know, they've learned from that. And I think that they've already done a good job. Especially for media and entertainment when you start to look at some of the ways that they use it for helping do graphics and helping to do drones. I think part of their buy of iRobot was the fact that iRobot was a big user of RoboMaker, which is using different models to train those robots to go around objects and things like that, so. >> Quick touch on Kubernetes, the whole DevOps World we just covered. The Cloud Native Foundation Security, CNCF. The security conference up in Seattle last week. First time they spun that out kind of like reinforced, you know, AWS spins out, reinforced from reinvent. Amsterdam's coming up soon, the CubeCon. What should we expect? What's hot in Cubeland? >> Yeah, I think, you know, Kubes, you're going to be looking at how OpenShift keeps growing and I think to that respect you get to see the momentum with people like Red Hat. You see others coming up and realizing how OpenShift has gone to market as being, like you were saying, partnering with those Clouds and really making it simple. I think the simplicity and the manageability of Kubernetes is going to be at the forefront. I think a lot of the investment is still going into, how do I bring observability and DevOps and AIOps and MLOps all together. And I think that's going to be a big place where people are going to be looking to see what comes out of CubeCon in Amsterdam. I think it's that manageability ease of use. >> Well Rob, I look forward to working with you on behalf of the whole Cube team. We're going to do more of these and go out to some shows extract the signal from the noise. Really appreciate you coming into our studio. >> Well, thank you for having me on. Really appreciate it. >> You're really welcome. All right, keep it right there, or thanks for watching. This is Dave Vellante for the Cube. And we'll see you next time. (light music)

Hello and welcome back to Supercloud 2 where we examine the intersection of cloud and data in the 2020s. My name is Dave Vellante. Our Supercloud panel, our power panel is back. Maribel Lopez is the founder and principal analyst at Lopez Research. Sanjeev Mohan is former Gartner analyst and principal at Sanjeev Mohan. And Keith Townsend is the CTO advisor. Folks, welcome back and thanks for your participation today. Good to see you. >> Okay, great. >> Great to see you. >> Thanks. Let me start, Maribel, with you. Bob Muglia, we had a conversation as part of Supercloud the other day. And he said, "Dave, I like the work, you got to simplify this a little bit." So he said, quote, "A Supercloud is a platform." He said, "Think of it as a platform that provides programmatically consistent services hosted on heterogeneous cloud providers." And then Nelu Mihai said, "Well, wait a minute. This is just going to create more stove pipes. We need more standards in an architecture," which is kind of what Berkeley Sky Computing initiative is all about. So there's a sort of a debate going on. Is supercloud an architecture, a platform? Or maybe it's just another buzzword. Maribel, do you have a thought on this? >> Well, the easy answer would be to say it's just a buzzword. And then we could just kill the conversation and be done with it. But I think the term, it's more than that, right? The term actually isn't new. You can go back to at least 2016 and find references to supercloud in Cornell University or assist in other documents. So, having said this, I think we've been talking about Supercloud for a while, so I assume it's more than just a fancy buzzword. But I think it really speaks to that undeniable trend of moving towards an abstraction layer to deal with the chaos of what we consider managing multiple public and private clouds today, right? So one definition of the technology platform speaks to a set of services that allows companies to build and run that technology smoothly without worrying about the underlying infrastructure, which really gets back to something that Bob said. And some of the question is where that lives. And you could call that an abstraction layer. You could call it cross-cloud services, hybrid cloud management. So I see momentum there, like legitimate momentum with enterprise IT buyers that are trying to deal with the fact that they have multiple clouds now. So where I think we're moving is trying to define what are the specific attributes and frameworks of that that would make it so that it could be consistent across clouds. What is that layer? And maybe that's what the supercloud is. But one of the things I struggle with with supercloud is. What are we really trying to do here? Are we trying to create differentiated services in the supercloud layer? Is a supercloud just another variant of what AWS, GCP, or others do? You spoken to Walmart about its cloud native platform, and that's an example of somebody deciding to do it themselves because they need to deal with this today and not wait for some big standards thing to happen. So whatever it is, I do think it's something. I think we're trying to maybe create an architecture out of it would be a better way of saying it so that it does get to those set of principles, but it also needs to be edge aware. I think whenever we talk about supercloud, we're always talking about like the big centralized cloud. And I think we need to think about all the distributed clouds that we're looking at in edge as well. So that might be one of the ways that supercloud evolves. >> So thank you, Maribel. Keith, Brian Gracely, Gracely's law, things kind of repeat themselves. We've seen it all before. And so what Muglia brought to the forefront is this idea of a platform where the platform provider is really responsible for the architecture. Of course, the drawback is then you get a a bunch of stove pipes architectures. But practically speaking, that's kind of the way the industry has always evolved, right? >> So if we look at this from the practitioner's perspective and we talk about platforms, traditionally vendors have provided the platforms for us, whether it's distribution of lineage managed by or provided by Red Hat, Windows, servers, .NET, databases, Oracle. We think of those as platforms, things that are fundamental we can build on top. Supercloud isn't today that. It is a framework or idea, kind of a visionary goal to get to a point that we can have a platform or a framework. But what we're seeing repeated throughout the industry in customers, whether it's the Walmarts that's kind of supersized the idea of supercloud, or if it's regular end user organizations that are coming out with platform groups, groups who normalize cloud native infrastructure, AWS multi-cloud, VMware resources to look like one thing internally to their developers. We're seeing this trend that there's a desire for a platform that provides the capabilities of a supercloud. >> Thank you for that. Sanjeev, we often use Snowflake as a supercloud example, and now would presumably would be a platform with an architecture that's determined by the vendor. Maybe Databricks is pushing for a more open architecture, maybe more of that nirvana that we were talking about before to solve for supercloud. But regardless, the practitioner discussions show. At least currently, there's not a lot of cross-cloud data sharing. I think it could be a killer use case, egress charges or a barrier. But how do you see it? Will that change? Will we hide that underlying complexity and start sharing data across cloud? Is that something that you think Snowflake or others will be able to achieve? >> So I think we are already starting to see some of that happen. Snowflake is definitely one example that gets cited a lot. But even we don't talk about MongoDB in this like, but you could have a MongoDB cluster, for instance, with nodes sitting in different cloud providers. So there are companies that are starting to do it. The advantage that these companies have, let's take Snowflake as an example, it's a centralized proprietary platform. And they are building the capabilities that are needed for supercloud. So they're building things like you can push down your data transformations. They have the entire security and privacy suite. Data ops, they're adding those capabilities. And if I'm not mistaken, it'll be very soon, we will see them offer data observability. So it's all works great as long as you are in one platform. And if you want resilience, then Snowflake, Supercloud, great example. But if your primary goal is to choose the most cost-effective service irrespective of which cloud it sits in, then things start falling sideways. For example, I may be a very big Snowflake user. And I like Snowflake's resilience. I can move from one cloud to another cloud. Snowflake does it for me. But what if I want to train a very large model? Maybe Databricks is a better platform for that. So how do I do move my workload from one platform to another platform? That tooling does not exist. So we need server hybrid, cross-cloud, data ops platform. Walmart has done a great job, but they built it by themselves. Not every company is Walmart. Like Maribel and Keith said, we need standards, we need reference architectures, we need some sort of a cost control. I was just reading recently, Accenture has been public about their AWS bill. Every time they get the bill is tens of millions of lines, tens of millions 'cause there are over thousand teams using AWS. If we have not been able to corral a usage of a single cloud, now we're talking about supercloud, we've got multiple clouds, and hybrid, on-prem, and edge. So till we've got some cross-platform tooling in place, I think this will still take quite some time for it to take shape. >> It's interesting. Maribel, Walmart would tell you that their on-prem infrastructure is cheaper to run than the stuff in the cloud. but at the same time, they want the flexibility and the resiliency of their three-legged stool model. So the point as Sanjeev was making about hybrid. It's an interesting balance, isn't it, between getting your lowest cost and at the same time having best of breed and scale? >> It's basically what you're trying to optimize for, as you said, right? And by the way, to the earlier point, not everybody is at Walmart's scale, so it's not actually cheaper for everybody to have the purchasing power to make the cloud cheaper to have it on-prem. But I think what you see almost every company, large or small, moving towards is this concept of like, where do I find the agility? And is the agility in building the infrastructure for me? And typically, the thing that gives you outside advantage as an organization is not how you constructed your cloud computing infrastructure. It might be how you structured your data analytics as an example, which cloud is related to that. But how do you marry those two things? And getting back to sort of Sanjeev's point. We're in a real struggle now where one hand we want to have best of breed services and on the other hand we want it to be really easy to manage, secure, do data governance. And those two things are really at odds with each other right now. So if you want all the knobs and switches of a service like geospatial analytics and big query, you're going to have to use Google tools, right? Whereas if you want visibility across all the clouds for your application of state and understand the security and governance of that, you're kind of looking for something that's more cross-cloud tooling at that point. But whenever you talk to somebody about cross-cloud tooling, they look at you like that's not really possible. So it's a very interesting time in the market. Now, we're kind of layering this concept of supercloud on it. And some people think supercloud's about basically multi-cloud tooling, and some people think it's about a whole new architectural stack. So we're just not there yet. But it's not all about cost. I mean, cloud has not been about cost for a very, very long time. Cloud has been about how do you really make the most of your data. And this gets back to cross-cloud services like Snowflake. Why did they even exist? They existed because we had data everywhere, but we need to treat data as a unified object so that we can analyze it and get insight from it. And so that's where some of the benefit of these cross-cloud services are moving today. Still a long way to go, though, Dave. >> Keith, I reached out to my friends at ETR given the macro headwinds, And you're right, Maribel, cloud hasn't really been about just about cost savings. But I reached out to the ETR, guys, what's your data show in terms of how customers are dealing with the economic headwinds? And they said, by far, their number one strategy to cut cost is consolidating redundant vendors. And a distant second, but still notable was optimizing cloud costs. Maybe using reserve instances, or using more volume buying. Nowhere in there. And I asked them to, "Could you go look and see if you can find it?" Do we see repatriation? And you hear this a lot. You hear people whispering as analysts, "You better look into that repatriation trend." It's pretty big. You can't find it. But some of the Walmarts in the world, maybe even not repatriating, but they maybe have better cost structure on-prem. Keith, what are you seeing from the practitioners that you talk to in terms of how they're dealing with these headwinds? >> Yeah, I just got into a conversation about this just this morning with (indistinct) who is an analyst over at GigaHome. He's reading the same headlines. Repatriation is happening at large scale. I think this is kind of, we have these quiet terms now. We have quiet quitting, we have quiet hiring. I think we have quiet repatriation. Most people haven't done away with their data centers. They're still there. Whether they're completely on-premises data centers, and they own assets, or they're partnerships with QTX, Equinix, et cetera, they have these private cloud resources. What I'm seeing practically is a rebalancing of workloads. Do I really need to pay AWS for this instance of SAP that's on 24 hours a day versus just having it on-prem, moving it back to my data center? I've talked to quite a few customers who were early on to moving their static SAP workloads onto the public cloud, and they simply moved them back. Surprising, I was at VMware Explore. And we can talk about this a little bit later on. But our customers, net new, not a lot that were born in the cloud. And they get to this point where their workloads are static. And they look at something like a Kubernetes, or a OpenShift, or VMware Tanzu. And they ask the question, "Do I need the scalability of cloud?" I might consider being a net new VMware customer to deliver this base capability. So are we seeing repatriation as the number one reason? No, I think internal IT operations are just naturally come to this realization. Hey, I have these resources on premises. The private cloud technologies have moved far along enough that I can just simply move this workload back. I'm not calling it repatriation, I'm calling it rightsizing for the operating model that I have. >> Makes sense. Yeah. >> Go ahead. >> If I missed something, Dave, why we are on this topic of repatriation. I'm actually surprised that we are talking about repatriation as a very big thing. I think repatriation is happening, no doubt, but it's such a small percentage of cloud migration that to me it's a rounding error in my opinion. I think there's a bigger problem. The problem is that people don't know where the cost is. If they knew where the cost was being wasted in the cloud, they could do something about it. But if you don't know, then the easy answer is cloud costs a lot and moving it back to on-premises. I mean, take like Capital One as an example. They got rid of all the data centers. Where are they going to repatriate to? They're all in the cloud at this point. So I think my point is that data observability is one of the places that has seen a lot of traction is because of cost. Data observability, when it first came into existence, it was all about data quality. Then it was all about data pipeline reliability. And now, the number one killer use case is FinOps. >> Maribel, you had a comment? >> Yeah, I'm kind of in violent agreement with both Sanjeev and Keith. So what are we seeing here? So the first thing that we see is that many people wildly overspent in the big public cloud. They had stranded cloud credits, so to speak. The second thing is, some of them still had infrastructure that was useful. So why not use it if you find the right workloads to what Keith was talking about, if they were more static workloads, if it was already there? So there is a balancing that's going on. And then I think fundamentally, from a trend standpoint, these things aren't binary. Everybody, for a while, everything was going to go to the public cloud and then people are like, "Oh, it's kind of expensive." Then they're like, "Oh no, they're going to bring it all on-prem 'cause it's really expensive." And it's like, "Well, that doesn't necessarily get me some of the new features and functionalities I might want for some of my new workloads." So I'm going to put the workloads that have a certain set of characteristics that require cloud in the cloud. And if I have enough capability on-prem and enough IT resources to manage certain things on site, then I'm going to do that there 'cause that's a more cost-effective thing for me to do. It's not binary. That's why we went to hybrid. And then we went to multi just to describe the fact that people added multiple public clouds. And now we're talking about super, right? So I don't look at it as a one-size-fits-all for any of this. >> A a number of practitioners leading up to Supercloud2 have told us that they're solving their cloud complexity by going in monocloud. So they're putting on the blinders. Even though across the organization, there's other groups using other clouds. You're like, "In my group, we use AWS, or my group, we use Azure. And those guys over there, they use Google. We just kind of keep it separate." Are you guys hearing this in your view? Is that risky? Are they missing out on some potential to tap best of breed? What do you guys think about that? >> Everybody thinks they're monocloud. Is anybody really monocloud? It's like a group is monocloud, right? >> Right. >> This genie is out of the bottle. We're not putting the genie back in the bottle. You might think your monocloud and you go like three doors down and figure out the guy or gal is on a fundamentally different cloud, running some analytics workload that you didn't know about. So, to Sanjeev's earlier point, they don't even know where their cloud spend is. So I think the concept of monocloud, how that's actually really realized by practitioners is primary and then secondary sources. So they have a primary cloud that they run most of their stuff on, and that they try to optimize. And we still have forked workloads. Somebody decides, "Okay, this SAP runs really well on this, or these analytics workloads run really well on that cloud." And maybe that's how they parse it. But if you really looked at it, there's very few companies, if you really peaked under the hood and did an analysis that you could find an actual monocloud structure. They just want to pull it back in and make it more manageable. And I respect that. You want to do what you can to try to streamline the complexity of that. >> Yeah, we're- >> Sorry, go ahead, Keith. >> Yeah, we're doing this thing where we review AWS service every day. Just in your inbox, learn about a new AWS service cursory. There's 238 AWS products just on the AWS cloud itself. Some of them are redundant, but you get the idea. So the concept of monocloud, I'm in filing agreement with Maribel on this that, yes, a group might say I want a primary cloud. And that primary cloud may be the AWS. But have you tried the licensed Oracle database on AWS? It is really tempting to license Oracle on Oracle Cloud, Microsoft on Microsoft. And I can't get RDS anywhere but Amazon. So while I'm driven to desire the simplicity, the reality is whether be it M&A, licensing, data sovereignty. I am forced into a multi-cloud management style. But I do agree most people kind of do this one, this primary cloud, secondary cloud. And I guarantee you're going to have a third cloud or a fourth cloud whether you want to or not via shadow IT, latency, technical reasons, et cetera. >> Thank you. Sanjeev, you had a comment? >> Yeah, so I just wanted to mention, as an organization, I'm complete agreement, no organization is monocloud, at least if it's a large organization. Large organizations use all kinds of combinations of cloud providers. But when you talk about a single workload, that's where the program arises. As Keith said, the 238 services in AWS. How in the world am I going to be an expert in AWS, but then say let me bring GCP or Azure into a single workload? And that's where I think we probably will still see monocloud as being predominant because the team has developed its expertise on a particular cloud provider, and they just don't have the time of the day to go learn yet another stack. However, there are some interesting things that are happening. For example, if you look at a multi-cloud example where Oracle and Microsoft Azure have that interconnect, so that's a beautiful thing that they've done because now in the newest iteration, it's literally a few clicks. And then behind the scene, your .NET application and your Oracle database in OCI will be configured, the identities in active directory are federated. And you can just start using a database in one cloud, which is OCI, and an application, your .NET in Azure. So till we see this kind of a solution coming out of the providers, I think it's is unrealistic to expect the end users to be able to figure out multiple clouds. >> Well, I have to share with you. I can't remember if he said this on camera or if it was off camera so I'll hold off. I won't tell you who it is, but this individual was sort of complaining a little bit saying, "With AWS, I can take their best AI tools like SageMaker and I can run them on my Snowflake." He said, "I can't do that in Google. Google forces me to go to BigQuery if I want their excellent AI tools." So he was sort of pushing, kind of tweaking a little bit. Some of the vendor talked that, "Oh yeah, we're so customer-focused." Not to pick on Google, but I mean everybody will say that. And then you say, "If you're so customer-focused, why wouldn't you do a ABC?" So it's going to be interesting to see who leads that integration and how broadly it's applied. But I digress. Keith, at our first supercloud event, that was on August 9th. And it was only a few months after Broadcom announced the VMware acquisition. A lot of people, myself included said, "All right, cuts are coming." Generally, Tanzu is probably going to be under the radar, but it's Supercloud 22 and presumably VMware Explore, the company really... Well, certainly the US touted its Tanzu capabilities. I wasn't at VMware Explore Europe, but I bet you heard similar things. Hawk Tan has been blogging and very vocal about cross-cloud services and multi-cloud, which doesn't happen without Tanzu. So what did you hear, Keith, in Europe? What's your latest thinking on VMware's prospects in cross-cloud services/supercloud? >> So I think our friend and Cube, along host still be even more offended at this statement than he was when I sat in the Cube. This was maybe five years ago. There's no company better suited to help industries or companies, cross-cloud chasm than VMware. That's not a compliment. That's a reality of the industry. This is a very difficult, almost intractable problem. What I heard that VMware Europe were customers serious about this problem, even more so than the US data sovereignty is a real problem in the EU. Try being a company in Switzerland and having the Swiss data solvency issues. And there's no local cloud presence there large enough to accommodate your data needs. They had very serious questions about this. I talked to open source project leaders. Open source project leaders were asking me, why should I use the public cloud to host Kubernetes-based workloads, my projects that are building around Kubernetes, and the CNCF infrastructure? Why should I use AWS, Google, or even Azure to host these projects when that's undifferentiated? I know how to run Kubernetes, so why not run it on-premises? I don't want to deal with the hardware problems. So again, really great questions. And then there was always the specter of the problem, I think, we all had with the acquisition of VMware by Broadcom potentially. 4.5 billion in increased profitability in three years is a unbelievable amount of money when you look at the size of the problem. So a lot of the conversation in Europe was about industry at large. How do we do what regulators are asking us to do in a practical way from a true technology sense? Is VMware cross-cloud great? >> Yeah. So, VMware, obviously, to your point. OpenStack is another way of it. Actually, OpenStack, uptake is still alive and well, especially in those regions where there may not be a public cloud, or there's public policy dictating that. Walmart's using OpenStack. As you know in IT, some things never die. Question for Sanjeev. And it relates to this new breed of data apps. And Bob Muglia and Tristan Handy from DBT Labs who are participating in this program really got us thinking about this. You got data that resides in different clouds, it maybe even on-prem. And the machine polls data from different systems. No humans involved, e-commerce, ERP, et cetera. It creates a plan, outcomes. No human involvement. Today, you're on a CRM system, you're inputting, you're doing forms, you're, you're automating processes. We're talking about a new breed of apps. What are your thoughts on this? Is it real? Is it just way off in the distance? How does machine intelligence fit in? And how does supercloud fit? >> So great point. In fact, the data apps that you're talking about, I call them data products. Data products first came into limelight in the last couple of years when Jamal Duggan started talking about data mesh. I am taking data products out of the data mesh concept because data mesh, whether data mesh happens or not is analogous to data products. Data products, basically, are taking a product management view of bringing data from different sources based on what the consumer needs. We were talking earlier today about maybe it's my vacation rentals, or it may be a retail data product, it may be an investment data product. So it's a pre-packaged extraction of data from different sources. But now I have a product that has a whole lifecycle. I can version it. I have new features that get added. And it's a very business data consumer centric. It uses machine learning. For instance, I may be able to tell whether this data product has stale data. Who is using that data? Based on the usage of the data, I may have a new data products that get allocated. I may even have the ability to take existing data products, mash them up into something that I need. So if I'm going to have that kind of power to create a data product, then having a common substrate underneath, it can be very useful. And that could be supercloud where I am making API calls. I don't care where the ERP, the CRM, the survey data, the pricing engine where they sit. For me, there's a logical abstraction. And then I'm building my data product on top of that. So I see a new breed of data products coming out. To answer your question, how early we are or is this even possible? My prediction is that in 2023, we will start seeing more of data products. And then it'll take maybe two to three years for data products to become mainstream. But it's starting this year. >> A subprime mortgages were a data product, definitely were humans involved. All right, let's talk about some of the supercloud, multi-cloud players and what their future looks like. You can kind of pick your favorites. VMware, Snowflake, Databricks, Red Hat, Cisco, Dell, HP, Hashi, IBM, CloudFlare. There's many others. cohesive rubric. Keith, I wanted to start with CloudFlare because they actually use the term supercloud. and just simplifying what they said. They look at it as taking serverless to the max. You write your code and then you can deploy it in seconds worldwide, of course, across the CloudFlare infrastructure. You don't have to spin up containers, you don't go to provision instances. CloudFlare worries about all that infrastructure. What are your thoughts on CloudFlare this approach and their chances to disrupt the current cloud landscape? >> As Larry Ellison said famously once before, the network is the computer, right? I thought that was Scott McNeley. >> It wasn't Scott McNeley. I knew it was on Oracle Align. >> Oracle owns that now, owns that line. >> By purpose or acquisition. >> They should have just called it cloud. >> Yeah, they should have just called it cloud. >> Easier. >> Get ahead. >> But if you think about the CloudFlare capability, CloudFlare in its own right is becoming a decent sized cloud provider. If you have compute out at the edge, when we talk about edge in the sense of CloudFlare and points of presence, literally across the globe, you have all of this excess computer, what do you do with it? First offering, let's disrupt data in the cloud. We can't start the conversation talking about data. When they say we're going to give you object-oriented or object storage in the cloud without egress charges, that's disruptive. That we can start to think about supercloud capability of having compute EC2 run in AWS, pushing and pulling data from CloudFlare. And now, I've disrupted this roach motel data structure, and that I'm freely giving away bandwidth, basically. Well, the next layer is not that much more difficult. And I think part of CloudFlare's serverless approach or supercloud approaches so that they don't have to commit to a certain type of compute. It is advantageous. It is a feature for me to be able to go to EC2 and pick a memory heavy model, or a compute heavy model, or a network heavy model, CloudFlare is taken away those knobs. and I'm just giving code and allowing that to run. CloudFlare has a massive network. If I can put the code closest using the CloudFlare workers, if I can put that code closest to where the data is at or residing, super compelling observation. The question is, does it scale? I don't get the 238 services. While Server List is great, I have to know what I'm going to build. I don't have a Cognito, or RDS, or all these other services that make AWS, GCP, and Azure appealing from a builder's perspective. So it is a very interesting nascent start. It's great because now they can hide compute. If they don't have the capacity, they can outsource that maybe at a cost to one of the other cloud providers, but kind of hiding the compute behind the surplus architecture is a really unique approach. >> Yeah. And they're dipping their toe in the water. And they've announced an object store and a database platform and more to come. We got to wrap. So I wonder, Sanjeev and Maribel, if you could maybe pick some of your favorites from a competitive standpoint. Sanjeev, I felt like just watching Snowflake, I said, okay, in my opinion, they had the right strategy, which was to run on all the clouds, and then try to create that abstraction layer and data sharing across clouds. Even though, let's face it, most of it might be happening across regions if it's happening, but certainly outside of an individual account. But I felt like just observing them that anybody who's traditional on-prem player moving into the clouds or anybody who's a cloud native, it just makes total sense to write to the various clouds. And to the extent that you can simplify that for users, it seems to be a logical strategy. Maybe as I said before, what multi-cloud should have been. But are there companies that you're watching that you think are ahead in the game , or ones that you think are a good model for the future? >> Yes, Snowflake, definitely. In fact, one of the things we have not touched upon very much, and Keith mentioned a little bit, was data sovereignty. Data residency rules can require that certain data should be written into certain region of a certain cloud. And if my cloud provider can abstract that or my database provider, then that's perfect for me. So right now, I see Snowflake is way ahead of this pack. I would not put MongoDB too far behind. They don't really talk about this thing. They are in a different space, but now they have a lakehouse, and they've got all of these other SQL access and new capabilities that they're announcing. So I think they would be quite good with that. Oracle is always a dark forest. Oracle seems to have revived its Cloud Mojo to some extent. And it's doing some interesting stuff. Databricks is the other one. I have not seen Databricks. They've been very focused on lakehouse, unity, data catalog, and some of those pieces. But they would be the obvious challenger. And if they come into this space of supercloud, then they may bring some open source technologies that others can rely on like Delta Lake as a table format. >> Yeah. One of these infrastructure players, Dell, HPE, Cisco, even IBM. I mean, I would be making my infrastructure as programmable and cloud friendly as possible. That seems like table stakes. But Maribel, any companies that stand out to you that we should be paying attention to? >> Well, we already mentioned a bunch of them, so maybe I'll go a slightly different route. I'm watching two companies pretty closely to see what kind of traction they get in their established companies. One we already talked about, which is VMware. And the thing that's interesting about VMware is they're everywhere. And they also have the benefit of having a foot in both camps. If you want to do it the old way, the way you've always done it with VMware, they got all that going on. If you want to try to do a more cross-cloud, multi-cloud native style thing, they're really trying to build tools for that. So I think they have really good access to buyers. And that's one of the reasons why I'm interested in them to see how they progress. The other thing, I think, could be a sleeping horse oddly enough is Google Cloud. They've spent a lot of work and time on Anthos. They really need to create a certain set of differentiators. Well, it's not necessarily in their best interest to be the best multi-cloud player. If they decide that they want to differentiate on a different layer of the stack, let's say they want to be like the person that is really transformative, they talk about transformation cloud with analytics workloads, then maybe they do spend a good deal of time trying to help people abstract all of the other underlying infrastructure and make sure that they get the sexiest, most meaningful workloads into their cloud. So those are two people that you might not have expected me to go with, but I think it's interesting to see not just on the things that might be considered, either startups or more established independent companies, but how some of the traditional providers are trying to reinvent themselves as well. >> I'm glad you brought that up because if you think about what Google's done with Kubernetes. I mean, would Google even be relevant in the cloud without Kubernetes? I could argue both sides of that. But it was quite a gift to the industry. And there's a motivation there to do something unique and different from maybe the other cloud providers. And I'd throw in Red Hat as well. They're obviously a key player and Kubernetes. And Hashi Corp seems to be becoming the standard for application deployment, and terraform, or cross-clouds, and there are many, many others. I know we're leaving lots out, but we're out of time. Folks, I got to thank you so much for your insights and your participation in Supercloud2. Really appreciate it. >> Thank you. >> Thank you. >> Thank you. >> This is Dave Vellante for John Furrier and the entire Cube community. Keep it right there for more content from Supercloud2.

(lively music) >> Good afternoon cloud community and welcome back to beautiful Las Vegas, Nevada. We are here at AWS re:Invent, day four of our wall to wall coverage. It is day four in the afternoon and we are holding strong. I'm Savannah Peterson, joined by my fabulous co-host Paul Gillen. Paul, how you doing? >> I'm doing well, fine Savannah. You? >> You look great. >> We're in the home stretch here. >> Yeah, (laughs) we are. >> You still look fresh as a daisy. I don't know how you do it. >> (laughs) You're too kind. You're too kind, but I'm vain enough to take that compliment. I'm very excited about the conversation that we're going to have up next. We get to get a little DevRel and we got a little swagger on the stage. Welcome, Austin. How you doing? >> Hey, great to be here. Thanks for having me. >> Savannah: Yeah, it's our pleasure. How's the show been for you so far? >> Busy, exciting. Feels a lot like, you know it used to be right? >> Yeah, I know. A little reminiscent of the before times. >> Well, before times. >> Before we dig into the technical stuff, you're the most intriguingly dressed person we've had on the show this week. >> Austin: I feel extremely underdressed. >> Well, and we were talking about developer fancy. Talk to me a little bit about your approach to fashion. Wasn't expecting to lead with this, but I like this but I like this actually. >> No, it's actually good with my PR. You're going to love it. My approach, here's the thing, I give free advice all the time about developer relations, about things that work, have worked, and don't work in community and all that stuff. I love talking about that. Someone came up to me and said, "Where do you get your fashion tips from? What's the secret Discord server that I need to go on?" I'm like, "I will never tell." >> Oh, okay. >> This is an actual trait secret. >> Top secret. Wow! Talk about. >> If someone else starts wearing the hat, then everyone's going to be like, "There's so many white guys." Look, I'm a white guy with a beard that works in technology. >> Savannah: I've never met one of those. >> Exactly, there's none of them at all. So, you have to do something to kind stand out from the crowd a little bit. >> I love it, and it's a talk trigger. We're talking about it now. Production team loved it. It's fantastic. >> It's great. >> So your DevRel for Lightstep, in case the audience isn't familiar tell us about Lightstep. >> So Lightstep is a cloud native observability platform built at planet scale, and it powers observability at some places you've heard of like Spotify, GitHub, right? We're designed to really help developers that are working in the cloud with Kubernetes, with these huge distributed systems, understand application performance and being able to find problems, fix problems. We're also part of the ServiceNow family and as we all know ServiceNow is on a mission to help the world of work work better by powering digital transformation around IT and customer experiences for their many, many, many global 2000 customers. We love them very much. >> You know, it's a big love fest here. A lot of people have talked about the collaboration, so many companies working together. You mentioned unified observability. What is unified observability? >> So if you think about a tradition, or if you've heard about this traditional idea of observability where you have three pillars, right? You have metrics, and you have logs, and you have traces. All those three things are different data sources. They're picked up by different tools. They're analyzed by different people for different purposes. What we believe and what we're working to accomplish right now is to take all that and if you think those pillars, flip 'em on their side and think of them as streams of data. If we can take those streams and integrate them together and let you treat traces and metrics and logs not as these kind of inviolate experiences where you're kind of paging between things and going between tab A to tab B to tab C, and give you a standard way to query this, a standard way to display this, and letting you kind of find the most relevant data, then it really unlocks a lot of power for like developers and SREs to spend less time like managing tools. You know, figuring out where to build their query or what dashboard to check, more just being able to like kind of ask a question, get an answer. When you have an incident or an outage that's the most important thing, right? How quickly can you get those answers that you need so that you can restore system health? >> You don't want to be looking in multiple spots to figure out what's going on. >> Absolutely. I mean, some people hear unified observability and they go to like tool consolidation, right? That's something I hear from a lot of our users and a lot of people in re:Invent. I'll talk to SREs, they're like, "Yeah, we've got like six or seven different metrics products alone, just on services that they cover." It is important to kind of consolidate that but we're really taking it a step lower. We're looking at the data layer and trying to say, "Okay, if the data is all consistent and vendor neutral then that gives you flexibility not only from a tool consolidation perspective but also you know, a consistency, reliability. You could have a single way to deploy your observability out regardless of what cloud you're on, regardless if you're using Kubernetes or Fargate or whatever else. or even just Bare Metal or EC2 Bare Metal, right? There's been so much historically in this space. There's been a lot of silos and we think that unify diversability means that we kind of break down those silos, right? The way that we're doing it primarily is through a project called OpenTelemetry which you might have heard of. You want to talk about that in a minute? . >> Savannah: Yeah, let's talk about it right now. Why don't you tell us about it? Keep going, you're great. You're on a roll. >> I am. >> Savannah: We'll just hang out over here. >> It's day four. I'm going to ask the questions and answer the questions. (Savannah laughs) >> Yes, you're right. >> I do yeah. >> Open Tele- >> OpenTelemetry . >> Explain what OpenTelemetry is first. >> OpenTelemetry is a CNCF project, Cloud Native Computing Foundation. The goal is to make telemetry data, high quality telemetry data, a builtin feature of cloud native software right? So right now if you wanted to get logging data out, depending on your application stack, depending on your application run time, depending on language, depending on your deployment environment. You might have a lot... You have to make a lot of choices, right? About like, what am I going to use? >> Savannah: So many different choices, and the players are changing all the time. >> Exactly, and a lot of times what people will do is they'll go and they'll say like, "We have to use this commercial solution because they have a proprietary agent that can do a lot of this for us." You know? And if you look at all those proprietary agents, what you find very quickly is it's very commodified right? There's no real difference in what they're doing at a code level and what's stopped the industry from really adopting a standard way to create this logs and metrics and traces, is simply just the fact that there was no standard. And so, OpenTelemetry is that standard, right? We've got dozens of companies many of them like very, many of them here right? Competitors all the same, working together to build this open standard and implementation of telemetry data for cloud native software and really any software right? Like we support over 12 languages. We support Kubernetes, Amazon. AWS is a huge contributor actually and we're doing some really exciting stuff with them on their Amazon distribution of OpenTelemetry. So it's been extremely interesting to see it over the past like couple years go from like, "Hey, here's this like new thing that we're doing over here," to really it's a generalized acceptance that this is the way of the future. This is what we should have been doing all along. >> Yeah. >> My opinion is there is a perception out there that observability is kind of a commodity now that all the players have the same set of tools, same set of 15 or 17 or whatever tools, and that there's very little distinction in functionality. Would you agree with that? >> I don't know if I would characterize it that way entirely. I do think that there's a lot of duplicated effort that happens and part of the reason is because of this telemetry data problem, right? Because you have to wind up... You know, there's this idea of table stakes monitoring that we talk about right? Table stakes monitoring is the stuff that you're having to do every single day to kind of make sure your system is healthy to be able to... When there's an alert, gets triggered, to see why it got triggered and to go fix it, right? Because everyone has the kind of work on that table stake stuff and then build all these integrations, there's very little time for innovation on top of that right? Because you're spending all your time just like working on keeping up with technology. >> Savannah: Doing the boring stuff to make sure the wheels don't fall off, basically. >> Austin: Right? What I think the real advantage of OpenTelemetry is that it really, from like a vendor perspective, like it unblocks us from having to kind of do all this repetitive commodified work. It lets us help move that out to the community level so that... Instead of having to kind of build, your Kubernetes integration for example, you can just have like, "Hey, OpenTelemetry is integrated into Kubernetes and you just have this data now." If you are a commercial product, or if you're even someone that's interested in fixing a, scratching a particular itch about observability. It's like, "I have this specific way that I'm doing Kubernetes and I need something to help me really analyze that data. Well, I've got the data now I can just go create a project. I can create an analysis tool." I think that's what you'll see over time as OpenTelemetry promulgates out into the ecosystem is more people building interesting analysis features, people using things like machine learning to analyze this large amount, large and consistent amount of OpenTelemetry data. It's going to be a big shakeup I think, but it has the potential to really unlock a lot of value for our customers. >> Well, so you're, you're a developer relations guy. What are developers asking for right now out of their observability platforms? >> Austin: That's a great question. I think there's two things. The first is that they want it to just work. It's actually the biggest thing, right? There's so many kind of... This goes back to the tool proliferation, right? People have too much data in too many different places, and getting that data out can still be really challenging. And so, the biggest thing they want is just like, "I want something that I can... I want a lot of these questions I have to ask, answered already and OpenTelemetry is going towards it." Keep in mind it's the project's only three years old, so we obviously have room to grow but there are people running it in production and it works really well for them but there's more that we can do. The second thing is, and this isn't what really is interesting to me, is it's less what they're asking for and more what they're not asking for. Because a lot of the stuff that you see people, saying around, "Oh, we need this like very specific sort of lower level telemetry data, or we need this kind of universal thing." People really just want to be able to get questions or get questions answered, right? They want tools that kind of have these workflows where you don't have to be an expert because a lot of times this tooling gets locked behind sort of is gate kept almost in a organization where there are teams that's like, "We're responsible for this and we're going to set it up and manage it for you, and we won't let you do things outside of it because that would mess up- >> Savannah: Here's your sandbox and- >> Right, this is your sandbox you can play in and a lot of times that's really useful and very tuned for the problems that you saw yesterday, but people are looking at like what are the problems I'm going to get tomorrow? We're deploying more rapidly. We have more and more intentional change happening in the system. Like it's not enough to have this reactive sort of approach where our SRE teams are kind of like or this observability team is building a platform for us. Developers want to be able to get in and have these kind of guided workflows really that say like, "Hey, here's where you're starting at. Let's get you to an answer. Let's help you find the needle in the haystack as it were, without you having to become a master of six different or seven different tools." >> Savannah: Right, and it shouldn't be that complicated. >> It shouldn't be. I mean we've certainly... We've been working on this problem for many years now, starting with a lot of our team that started at Google and helped build Google's planet scale monitoring systems. So we have a lot of experience in the field. It's actually one... An interesting story that our founder or now general manager tells BHS, Ben Sigelman, and he told me this story once and it's like... He had built this really cool thing called Dapper that was a tracing system at Google, and people weren't using it. Because they were like, "This is really cool, but I don't know how to... but it's not relevant to me." And he's like, the one thing that we did to get to increase usage 20 times over was we just put a link. So we went to the place that people were already looking for that data and we added a link that says, "Hey, go over here and look at this." It's those simple connections being able to kind of draw people from like point A to point B, take them from familiar workflows into unfamiliar ones. You know, that's how we think about these problems right? How is this becoming a daily part of someone's usage? How is this helping them solve problems faster and really improve their their life? >> Savannah: Yeah, exactly. It comes down to quality of life. >> Warner made the case this morning that computer architecture should be inherently event-driven and that we are moving toward a world where the person matters less than what the software does, right? The software is triggering events. Does this complicate observability or simplify it? >> Austin: I think that at the end of the day, it's about getting the... Observability to me in a lot of ways is about modeling your system, right? It's about you as a developer being able to say this is what I expect the system to do and I don't think the actual application architecture really matters that much, right? Because it's about you. You are building a system, right? It can be event driven, can be support request response, can be whatever it is. You have to be able to say, "This is what I expect to... For these given inputs, this is the expected output." Now maybe there's a lot of stuff that happens in the middle that you don't really care about. And then, I talk to people here and everyone's talking about serverless right? Everyone... You can see there's obviously some amazing statistics about how many people are using Lambda, and it's very exciting. There's a lot of stuff that you shouldn't have to care about as a developer, but you should care about those inputs and outputs. You will need to have that kind of intermediate information and understand like, what was the exact path that I took through this invented system? What was the actual resources that were being used? Because even if you trust that all this magic behind the scenes is just going to work forever, sometimes it's still really useful to have that sort of lower level abstraction, to say like, "Well, this is what actually happened so that I can figure out when I deployed a new change, did I make performance better or worse?" Or being able to kind of segregate your data out and say like... Doing AB testing, right? Doing canary releases, doing all of these things that you hear about as best practices or well architected applications. Observability is at the core of all that. You need observability to kind of do any of, ask any of those higher level interesting questions. >> Savannah: We are here at ReInvent. Tell us a little bit more about the partnership with AWS. >> So I would have to actually probably refer you to someone at Service Now on that. I know that we are a partner. We collaborate with them on various things. But really at Lightstep, we're very focused on kind of the open source part of this. So we work with AWS through the OpenTelemetry project, on things like the AWS distribution for OpenTelemetry which is really... It's OpenTelemetry, again is really designed to be like a neutral standard but we know that there are going to be integrators and implementers that need to package up and bundle it in a certain way to make it easy for their end users to consume it. So that's what Amazon has done with ADOT which is the shortening for it. So it's available in several different ways. You can use it as like an SDK and drop it into your application. There's Lambda layers. If you want to get Lambda observability, you just add this extension in and then suddenly you're getting OpenTelemetry data on the other side. So it's really cool. It's been a really exciting to kind of work with people on the AWS side over the past several years. >> Savannah: It's exciting, >> I've personally seen just a lot of change. I was talking to a PM earlier this week... It's like, "Hey, two years ago I came and talked to you about OpenTelemetry and here we are today. You're still talking about OpenTelemetry." And they're like, "What changes?" Our customers have started coming to us asking for OpenTelemetry and we see the same thing now. >> Savannah: Timing is right. >> Timing is right, but we see the same thing... Even talking to ServiceNow customers who are... These very big enterprises, banks, finance, healthcare, whatever, telcos, it used to be... You'd have to go to them and say like, "Let me tell you about distributed tracing. Let me tell you about OpenTelemetry. Let me tell you about observability." Now they're coming in and saying, "Yeah, so we're standard." If you think about Kubernetes and how Kubernetes, a lot of enterprises have spent the past five-six years standardizing, and Kubernetes is a way to deploy applications or manage containerized applications. They're doing the same journey now with OpenTelemetry where they're saying, "This is what we're betting on and we want partners we want people to help us go along that way." >> I love it, and they work hand in hand in all CNCF projects as well that you're talking about. >> Austin: Right, so we're integrated into Kubernetes. You can find OpenTelemetry and things like kept in which is application standards. And over time, it'll just like promulgate out from there. So it's really exciting times. >> A bunch of CNCF projects in this area right? Prometheus. >> Prometheus, yeah. Yeah, so we inter-operate with Prometheus as well. So if you have Prometheus metrics, then OpenTelemetry can read those. It's a... OpenTelemetry metrics are like a super set of Prometheus. We've been working with the Prometheus community for quite a while to make sure that there's really good compatibility because so many people use Prometheus you know? >> Yeah. All right, so last question. New tradition for us here on theCUBE. We're looking for your 32nd hot take, Instagram reel, biggest theme, biggest buzz for those not here on the show floor. >> Oh gosh. >> Savannah: It could be for you too. It could be whatever for... >> I think the two things that are really striking to me is one serverless. Like I see... I thought people were talking about servers a lot and they were talking about it more than ever. Two, I really think it is observability right? Like we've gone from observability being kind of a niche. >> Savannah: Not that you're biased. >> Huh? >> Savannah: Not that you're biased. >> Not that I'm biased. It used to be a niche. I'd have to go niche thing where I would go and explain what this is to people and nowpeople are coming up. It's like, "Yeah, yeah, we're using OpenTelemetry." It's very cool. I've been involved with OpenTelemetry since the jump, since it was started really. It's been very exciting to see and gratifying to see like how much adoption we've gotten even in a short amount of time. >> Yeah, absolutely. It's a pretty... Yeah, it's been a lot. That was great. Perfect soundbite for us. >> Austin: Thanks, I love soundbites. >> Savannah: Yeah. Awesome. We love your hat and your soundbites equally. Thank you so much for being on the show with us today. >> Thank you for having me. >> Savannah: Hey, anytime, anytime. Will we see you in Amsterdam, speaking of KubeCon? Awesome, we'll be there. >> There's some real exciting OpenTelemetry stuff coming up for KubeCon. >> Well, we'll have to get you back on theCUBE. (talking simultaneously) Love that for us. Thank you all for tuning in two hour wall to wall coverage here, day four at AWS re:Invent in fabulous Las Vegas, Nevada, with Paul Gillin. I'm Savannah Peterson and you're watching theCUBE, the leader in high tech coverage. (lively music)

(upbeat music) >> Welcome back to theCUBE's live coverage of AWS re:Invent. Friends, it's good to see you. Lisa Martin here with Dave Vellante. This is our fourth day of CUBE wall-to-wall coverage, Dave. I can't believe it. And the expo hall is still going incredibly strong. >> Yeah, it is. It feels like the biggest re:Invent ever. I'm told it's almost as big as 2019. I don't know, maybe I was half asleep at 2019. That's very possible. But I'm excited because in 2017 Andy Jassy came on theCUBE and he said if Amazon had to do it all over again, if it knew then what it had now, we would've done the whole thing in containers or using Lambda, using serverless and using containers. Didn't have that opportunity back then. And I'm excited 'cause Rafay Systems is someone we've worked with a lot as an innovator in this space. >> Yep, and we're going to be talking with Rafay again. I think it's your 10th time Haseeb on the show >> Like once or twice. >> And a great customer who's going to talk about their serverless journey. Haseeb Budhani joins us once again, the CEO of Rafay. Great to see you. Rakesh Singh is here as well, the Head of Cloud and DevOps at Regeneron. Guys, it's great to have you on the program. How you feeling on day four of re:Invent? >> Excitement is as high as ever basically. >> Isn't it amazing? >> Rakesh: That's true. >> Haseeb: I just need some sleep. >> I'm with you on that. Caffeine and sleep. >> So many parties. So many meetings, oh my God. >> But the great thing is, Haseeb, that people want to engage with you. They're loving what Rafay is doing. You guys are a great testament to that, which we're going to uncover on the show. What are some of the things that you're hearing in the booth from customers? What's been some of the feedback? >> So firstly, as I said, it feels like the biggest one ever. I've been coming to re:Invent a long time and I mean, I know the numbers say it's not, but oh my God, this is a lot of people. Every time we've spoken over the last year and the point I always make to you, and we've spoken enough time about this is that enterprises are truly adopting this idea of Kubernetes containers, serverless, et cetera. And they're all trying to figure out what is the enterprise strategy for these things? They're thinking beyond technology and thinking operationalization of these technologies. And that's not the same thing. There's a toy and then there's the real thing. And that's not the same thing. And that's the gap that every enterprise customer I talked to and the booth traffic has been just amazing. I mean, but coming here I was thinking, my God, this is really expensive. And I'm thinking, wow, this is a great investment. Because we met such amazing companies who all essentially are saying exactly the same thing, which is as we go and productize and bring our high value applications to the modern infrastructure space, like Kubernetes, Lambda, et cetera, solving for the automation governance is really, really hard because, well, at one point, I guess when the economy was doing crazy well, I could keep hiring people, but I can't do that anymore either. So they're out looking for automation strategies that allow them to do more with the teams they have. And that's exactly what Rafay is here for. >> Yeah. Lisa, Adam Selipsky in his keynote, I love the, he said, "If you want to save money, the cloud is the place to do it." >> Exactly. Yep. Let's talk about Regeneron. Everyone knows it's a household word especially over the last couple of years, but talk about, Rakesh, Regeneron as a technology company that delivers life-saving pharmaceuticals. And where does cloud and Rafay fit into your strategy? >> So cloud has been a backbone of our compute strategy within Regeneron for a very long time now. The evolution from a traditional compute structure to more serverless compute has been growing at a rapid pace. And I would say like we are seeing exponential growth within the adaption of the compute within containers and Kubernetes world. So we've been on this journey for a long time and I think it's not stopping anytime soon. So we have more and more workload, which is running on Kubernetes containers and we are looking forward to our partnership with Rafay to further enhance it, as Haseeb mentioned, the efficiency is the key. We need to do more with less. Resourcing is critical and cloud is evolved from that journey that do more things in a more efficient manner. >> That was the original catalyst as we got to help our development team, be more productive. >> That's correct. >> Eliminate the heavy lifting. And then you started presumably doing some of the less heavy, but still heavy lifting and we talked off camera and then you're increasingly moving toward serverless. >> Rakesh: That's correct. >> Can you describe that journey? What that's like? >> So I think like with the whole adoption that things are taking a much faster pace. Basically we are putting more compute onto containers and the DevOps journey is increasingly getting more, more faster. >> Go ahead. 'Cause I want to understand where Rafay sits in this whole equation. I was talking about, I'm not a developer, but I was talking to developer yesterday trying to really understand the benefits of containers and serverless and I said, take me through what you have to do when you're using containers. He said, I got to build the container image then I got to deploy an EC2 instance where I got to choose and I got to allocate memory of the fence the app in a VM then I got to run the computing instance against the app. And then, oh by the way, I got to pay 'cause all that EC2 that whole time. Depending on how you approach serverless you're going to eliminate a lot of those steps. >> That is correct. So what we do is basically like in a traditional sense, the computer is sitting idle at quite a lot basically. >> But you're paying. >> And you're still paying for that. Serverless technologies allows us to use the compute as needed basis. So whenever you need it, it is available. You run your workload on that and after that it shuts down or goes to minimal state and you don't need to pay as much as your paying. >> And then where do you guys fit in that whole equation? >> Look, serverless has a paradigm. If you step back from the idea of containers versus Lambda or whatever functions. The idea should be that the list you just read out of what developers have to do. Here's what they really should do. They should write their code, they should check it in, and they never have to think about it again. That should be the case. If they want to debug their application, there should be a nice front end where they go and they interact with their application and that's it. What is Kubernetes? I don't care. That's the right answer. And we did not start this journey as an industry there because usually the initial adopters are developers who do the heavy lifting. Developers want to learn, they want to solve these problems. But then eventually the expectation is that the platform organization and an enterprise is going to own this platform for me so I can go back to doing my job, which is writing code. And that's where Rakesh's team comes in. So Rakesh team is building the standard at Regeneron. Whether you're writing a long-lasting app, which is going to run in a container or you're going to write an event-driven application, which is going to be a function, whatever. You write your app, we will give you the necessary tooling and plumbing to take care of all these things. And this is my problem. My being Rakesh. Rakesh is my customer. He has his customers. We as Rafay, A, we have to make Rakesh's system successful because we have to give them right automation to do all these things so that he can service hundred, or in his case, thousands and thousands of different individuals. But then collectively, we have to make sure that the developer experience is optimal so that truly they just write their code and EC2, they don't want to deal with this. In fact, on Monday evening, in the Kubernetes keynote by Barry Cooks, one of the things he said was that in a CIO sort of survey they did, CIO said, 80% of the time of developers is wasted on infrastructure stuff and not on innovation. We need to bring that 80% back so that a hundred percent of the work is on innovation and today it's not. >> And that's what you do. >> That's what we do. >> In your world as a developer, I only have to worry about my writing my code and what functions I'm going to call. >> That is correct. And it is important because the efficiencies of a developer need to be focused on doing the things which business is asking for. The 80% of the work like to make sure the things are secure, they're done the right way, the standards are followed, scanning part of it, that work if we can offload to a platform, for example, Rafay, saves a lot of works, a lot of work cycles from the developers perspective. >> Thank you for that. It was nice little tutorial on the benefits. >> Absolutely. So you transform the developer experience. >> That's correct. >> How does that impact Regeneron overall business? We uplevel that. Give me that view. >> So with that, like what happens, the key thing is the developers productivity increases. We are able to do more with less. And that is the key thing to our strategy that like with the increase in business demand, with the increase in lot of compute things, which we are doing, we need to do and hiring resources is getting more difficult than ever. And we need to make sure that we are leveraging platforms and tools basically to do, enable our developers to focus on key business activity rather than doing redundant things and things which we can leverage some other tooling and platform for that business. >> Is this something in terms of improving the developer experience and their productivity faster time to market? Is this accelerating? >> That's correct. >> Is this even like accelerating drug discovery in some cases? >> So COVID is like a great example for that. Like we were able to fast track our drug discovery and like we were able to turn it into an experience where we were able to discover new drugs and get it to the market in a much faster pace. That whole process was expedited using these tools and processes basically. So we are very proud of that. >> So my understanding is you're running Rafay with EKS. A lot of choices out there. Why? Why did you choose to go in that direction? >> So Regeneron has heavily invested in cloud recently, over the years basically. And then we are focusing on hybrid cloud now that we we are like, again, these multiple cloud providers of platforms which are coming in are strategies to focus on hybrid cloud and Rafay is big leader in that particular space where we felt that we need to engage or partner with Rafay to enable those capabilities, not just on AWS, but across the board. One single tool, one single process, one single knowledge base helps us achieve more efficiencies. >> Less chaos, less complexity. >> That's correct. Let's say when you're in customer conversations, which I know you've had many this week, but you probably do that all the time. Regeneron is a great use case for Rafay. It's so tangible, life sciences. We all get that, especially coming out of the pandemic. What do you say to customers are the top three differentiators of Rafay and why they should go Rafay on top of EKS? >> What's really interesting about these conversations is that, look, we have some pretty cool features in our product. Obviously we must have something interesting otherwise nobody would buy our product. And we have access management and zero trust models and cluster provisioning, all these very nice things. But it always comes down to exactly the same thing, which is every large enterprise that started a journey, independent or Rafay because they didn't know who we were, it's fine. Last year we were a young company, now we are a larger company and they all are basically building towards a roadmap which Rafay truly understands. And in my opinion, and I'm confident when I say this, we understand their life, their journey better than any other company in the market. The reason why we have the flurry of customers we have, the reason why the product has the capacity that it does is because for whatever reason, look, it's scale lock. That's for the history books. But we have complete clarity on what a pharmaceutical company or financial customers company or a high tech company the journey they will take to the cloud and automation for modern infrastructure, we get it. And what I'm selling them is the is the why, not the what. There's a lot of great answers for the what? What do we do? Rakesh doesn't care. I mean, he's trying to solve a bigger problem. He's trying to get his researchers to go faster. So then when they want to run a model, they should be able to do it right now. That's what he cares about. Then he looks for a tool to solve the business problem. And we figured out how to have that conversation and explain why Rafay helps him, essentially multiply the bandwidth that he has in his organization. And of course to that end we have some great technology/ But that's a secondary issue, the first, to me the why is more important than the what. And then we talk about how, which he has to pay us money. That's the how. But yeah, we get there too. But look, this is the important thing. Every enterprise is on exactly the same journey, Lisa. And that if you think about it from just purely economic efficiencies perspective that is not a good investment for our industry. If everybody's solving the same problem that's a waste of resources. Let's find a way to do, what is the point of the cloud? We used to all build data centers. That was not efficient. We all went to the cloud because it's more efficient to have somebody else, AWS, solve this problem for us so we can now focus on the next level problem. And then Rafay solving that problem so that he can focus on his drug discovery, not on Kubernetes. >> That's correct. It's all about efficiencies. Like doing things, learn from each other's experience and build upon it. So the things have been solved. One way you need to leverage that, reuse it. So the principles are the same. >> So then what's next? You had done an amazing job transforming the company. You're facilitating drug discovery faster than ever before. From an infrastructure perspective, what's next on your journey? >> So right now the roadmap what we have is basically talking about making sure that the workload are running more efficient, they're more secure. As we go into these expandable serverless technology, there are more challenging opportunities for us to solve. Those challenges are coming up. We need to make sure that with the new, the world we are living in, we are more securely doing stuff what we were doing previously. More efficiencies is also the key and more distributed. Like if we can leverage the power of cloud in doing more things on demand is on our roadmap. And I think that is where we are all driving. >> And when you said hybrid, you're talking about connecting to your on-prem tools and data? How about cross cloud? >> We are invested in multiple cloud platform itself and we are looking forward to leveraging a technology, which is truly cloud native and we can leverage things together on that. >> And I presume you're helping with that, obviously. >> Last question for both of you. We're making an Instagram reel. Think of this as a sizzle reel, like a 32nd elevator pitch. Question, first one goes to you, Rakesh. If you had a bumper sticker, you put it on, I don't know, say a DeLorean, I hear those are coming back. What would it say about Regeneron as a technology company that's delivering therapeutics? >> It's a tough question, but I would try my best. The bumper sticker would say, discover drug more faster, more efficient. >> Perfect. Haseeb, question about Rafay. What's the bumper sticker? If you had a billboard in on Highway 101 in Redwood City about Rafay and what it's enabling organizations enterprises across the globe to achieve, what would it say? >> I'll tell you what our customers say. So our customers call us the vCenter for Kubernetes and we all know what a vCenter is. We all know why vCenter's so amazingly successful because it takes IT engineers and gives them superpowers. You can run a data center. What is the vCenter for this new world? It us. So vCenter is obviously a trademark with our friends at VMware, so that's why I'm, but our customers truly call us the vCenter for Kubernetes. And I think that's an incredible moniker because that truly codifies our roadmap. It codifies what we are selling today. >> There's nothing more powerful and potent in the voice of the customer. Thank you both for coming on. Thank you for sharing the Regeneron story. Great to have you back on, Haseeb. You need a pin for the number of times you've been on theCUBE. >> At least a gold star. >> We'll work on that. Guys, thank you. We appreciate your time. >> Haseeb: Thank you very much. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

(upbeat music) >> Hello, beautiful cloud community, and welcome back to AWS reInvent. It is day four here in fabulous Las Vegas, Nevada. My voice can feel it, clearly. I'm Savannah Peterson with my co-host Paul Gillin. Paul, how you doing? >> Doing fine, Savannah. >> Are your feet about where my voice is? >> Well, getting little rest here as we have back to back segments. >> Yeah, yeah, we'll keep you off those. Very excited about this next segment. We get to have a chat with one of our very favorite analysts, Keith Townsend. Welcome back to theCUBE. >> Savannah Page. I'm going to use your south names, Savannah Page. Thank you for having me, Paul. Good to see you again. It's been been too long since CubeCon Valencia. >> Valencia. >> Valencia. >> Well at that beautiful lisp, love that. Keith, how's the show been for you so far? >> It has been great. I tweeted it a couple of days ago. Amazon reInvent is back. >> Savannah: Whoo! Love that. >> 50, 60 thousand people, you know? After 40 thousand, I stop countin'. It has been an amazing show. I don't know if it's just the assignment of returning, but easily the best reInvent of the four that I've attended. >> Savannah: Love that. >> Paul: I love that we have you here because, you know, we tend to get anchored to these desks, and we don't really get a sense of what's going on out there. You've been spending the last four days traversing the floor and talking to people. What are you hearing? Are there any mega themes that are emerging? >> Keith: So, a couple of mega themes is... We were in the Allen session with Adam, and Adam bought up the idea of hybrid cloud. At the 2019 show, that would be unheard of. There's only one cloud, and that's the AWS cloud, when you're at the Amazon show. Booths, folks, I was at the VMware booth and there's a hybrid cloud sign session. People are talking about multicloud. Yes, we're at the AWS show, but the reality that most customers' environments are complex. Adam mentioned that it's hybrid today and more than likely to be hybrid in the future in Amazon, and the ecosystem has adjusted to that reality. >> Paul: Now, is that because they want sell more outposts? >> You know, outpost is definitely a part of the story, but it's a tactile realization that outposts alone won't get it. So, you know, from Todd Consulting, to Capgemini, to PWC, to many of the integrations on the show floor... I even saw company that's doing HP-UX in the cloud or on-prem. The reality is these, well, we've deemed these legacy systems aren't going anywhere. AWS announced the mainframe service last year for converting mainframe code into cloud workloads, and it's just not taking on the, I think, the way that the Amazon would like, and that's a reality that is too complex for all of it to run in the cloud. >> Paul: So it sounds like the strategy is to envelop and consume then if you have mainframe conversion services and HP-UX in the cloud, I mean, you're talking about serious legacy stuff there. >> Keith: You're talking about serious legacy stuff. They haven't de-emphasized their relationship with VMware. You know, hybrid is not a place, it is a operating model. So VMware cloud on AWS allows you to do both models concurrently if you have those applications that need layer two. You have these workloads that just don't... SAP just doesn't... Sorry, AWS, SAP in the cloud and EC2 just doesn't make financial sense. It's a reality. It's accepting of that and meeting customers where they're at. >> And all the collaboration, I mean, you've mentioned so many companies in that answer, and I think it's very interesting to see how much we're all going to have to work together to make the cloud its own operating system. Cloud as an OS came up on our last conversation here and I think it's absolutely fascinating. >> Keith: Yeah, cloud is the OS I think is a thing. This idea that I'm going to use the cloud as my base layer of abstraction. I've talked to a really interesting startup... Well actually it's a open source project cross plane of where they're taking that cloud model and now I can put my VMware vsphere, my AWS, GCP, et cetera, behind that and use that operating model to manage my overall infrastructure. So, the maturity of the market has fascinated me over the past year, year and a half. >> It really feels like we're at a new inflection point. I totally agree. I want to talk about something completely different. >> Keith: Okay. >> Because I know that we both did this challenge. So one of the things that's really inspiring quite frankly about being here at AWS reInvent, and I know you all at home don't have an opportunity to walk the floor and get the experience and get as many steps as Paul gets in, but there's a real emphasis on giving back. This community cares about giving back and AWS is doing a variety of different activations to donate to a variety of different charities. And there's a DJ booth. I've been joking. It kind of feels like you're arriving at a rave when you get to reInvent. And right next to that, there is a hydrate and help station with these reusable water bottles. This is actually firm. It's not one of those plastic ones that's going to end up in the recycled bin or the landfill. And every single time that you fill up your water bottle, AWS will donate $3 to help women in Kenya get access to water. One of the things that I found really fascinating about the activation is women in sub-Saharan Africa spend 16 million hours carrying water a day, which is a wild concept to think about, and water is heavy. Keith, my man, I know that you did the activation. They had you carrying two 20 pound jugs of water. >> Keith: For about 15 feet. It's not the... >> (laughs) >> 20 pound jugs of water, 20 gallons, whatever the amount is. It was extremely heavy. I'm a fairly sizeable guy. Six four, six five. >> You're in good shape, yeah. >> Keith: Couple of a hundred pounds. >> Yeah. >> Keith: And I could not imagine spending that many hours simply getting fresh water. We take it for granted. Every time I run the water in the sink, my family gets on me because I get on them when they leave the sink water. It's like my dad's left the light on. If you leave the water on in my house, you are going to hear it from me because, you know, things like this tickle in my mind like, wow, people walk that far. >> Savannah: That's your whole day. >> Just water, and that's probably not even enough water for the day. >> Paul: Yeah. We think of that as being, like, an 18th century phenomenon, but it's very much today in parts of Sub-Saharan Africa. >> I know, and we're so privileged. For me, it was just, we work in technology. Everyone here is pretty blessed, and to do that activation really got my head in the right space to think, wow I'm so lucky. The team here, the fabulous production team, can go refill my water bottle. I mean, so simple. They've also got a fitness activation going on. You can jump on a bike, a treadmill, and if you work out for five minutes, they donate $5 to Fred Hutch up in Seattle. And that was nice. I did a little cross-training in between segments yesterday and I just, I really love seeing that emphasis. None of this matters if we're not taking care of community. >> Yeah, I'm going to go out and google Fred Hutch, and just donate the five bucks. 'Cause I'm not, I'm not. >> (laughs) >> I'll run forever, but I'm not getting on a bike. >> This from a guy who did 100 5Ks in a row last year. >> Yeah. I did 100 5Ks in a row, and I'm not doing five minutes on a bike. That's it. That's crazy, right? >> I mean there is a treadmill And they have the little hands workout thing too if you want. >> About five minutes though. >> Savannah: I know. >> Like five minutes is way longer than what you think it is. >> I mean, it's true. I was up there in a dress in sequence. Hopefully, I didn't scar any anyone on the show floor yesterday. It's still toss up. >> I'm going to take us back to back. >> Take us back Paul. >> Back to what we were talking about. I want to know what you're hearing. So we've had a lot of people on this show, a lot of vendors on the show who have said AWS is our most important cloud partner, which would imply that AWS's lead is solidifying its lead and pulling away from the pack as the number one. Do you hear that as well? Or is that lip service? >> Keith: So I always think about AWS reInvent as the Amazon victory lap. This is where they come and just thumb their noses at all the other cloud providers and just show how far ahead they're are. Werner Vogels, CTO at Amazon's keynotes, so I hadn't watched it yet, but at that keynote, this is where they literally take the victory lap and say that we're going to expose what we did four or five years ago on stage, and what we did four or five years ago is ahead of every cloud provider with maybe the exception of GCP and they're maybe three years behind. So customers are overwhelmingly choosing Amazon for these reasons. Don't get me wrong, Corey Quinn, Gardner folks, really went at Adam yesterday about Amazon had three majors outages in December last year. AWS has way too many services that are disconnected, but from the pure capability, I talked to a born in the cloud data protection company who could repatriate their data protection and storage on-prem private data center, save money. Instead, they double down on Amazon. They're using, they modernize their application and they're reduced their cost by 60 to 70%. >> Massive. >> This is massive. AWS is keeping up with customers no matter where they're at on the spectrum. >> Savannah: I love that you use the term victory lap. We've had a lot of folks from AWS here up on the show this week, and a couple of them have said they live for this. I mean, and it's got to be pretty cool. You've got 70 thousand plus people obsessed with your product and so many different partners doing so many different things from the edge to hospital to the largest companies on earth to the Israeli Ministry of Defense we were just talking about earlier, so everybody needs the cloud. I feel like that's where we're at. >> Keith: Yeah, and the next step, I think the next level opportunity for AWS is to get to that analyst or that citizen developer, being able to enable the end user to use a lambda, use these data services to create new applications, and the meanwhile, there's folks on the show floor filling that gap that enable develop... the piece of owner, the piece of parlor owner, to create a web portal that compares his prices and solutions to other vendors in his area and adjust dynamically. You go into a restaurant now and there is no price menu. There's a QR code that Amazon is powering much of that dynamic relationship between the restaurateur, the customer, and even the menu and availability. It's just a wonderful time. >> I always ask for the print menu. I'm sorry. >> Yeah. You want the printed menu. >> Look down, my phone doesn't work. >> Gimme something I could shine my light on. >> I know you didn't have have a chance to look at Vogel's keynote yet, but I mean you mentioned citizen developer. One of the things they announced this morning was essentially a low code lambda interface. So you can plug, take your lamb dysfunctions and do drag and drop a connection between them. So they are going after that market. >> Keith: So I guess I'll take my victory lap because that was my prediction. That's where Amazon's next... >> Well done, Keith. >> Because Lambda is that thing when you look at what server list was and the name of the concept of being, not having to have to worry about servers in your application development, the logical next step, I won't take too much of a leap. That logical first step is, well, code less code. This is something that Kelsey Hightower has talked about a lot. Low code, no code, the ability to empower people without having these artificial barriers, learning how to code in a different language. This is the time where I can go to Valencia, it's pronounced, where I can go to Valencia and not speak Spanish and just have my phone. Why can't we do, at business value, for people who have amazing ideas and enable those amazing ideas before I have to stick a developer in between them and the system. >> Paul: Low-code market is growing 35% a year. It's not surprising, given the potential that's out there. >> And as a non-technical person, who works in technology, I've been waiting for this moment. So keep predicting this kind of thing, Keith. 'Cause hopefully it'll keep happening. Keith, I'm going to give you the challenge we've been giving all of our guests this week. >> Keith: Okay. >> And I know you're going to absolutely crush this. So we are looking for your 32nd Instagram real, sizzle hot take, biggest takeaway from this year's show. >> So 32nd Instagram, I'll even put it on TikTok. >> Savannah: Heck yeah. >> Hybrid cloud, hybrid infrastructure. This is way bigger than Amazon. Whether we're talking about Amazon, AWS, I mean AWS's solutions, Google Cloud, Azure, OCI, on-prem. Customers want it all. They want a way to manage it all, and they need the skill and tools to enable their not-so-growing work force to do it. That is, that's AWS reInvent 2019 to 2022. >> Absolutely nailed it. Keith Townsend, it is always such a joy to have you here on theCUBE. Thank you for joining us >> Savannah Page. Great to have you. Paul, you too. You're always a great co-host. >> (laughs) We co-hosted for three days. >> We've got a lot of love for each other here. And we have even more love for all of you tuning into our fabulous livestream from AWS reInvent Las Vegas, Nevada, with Paul Gillin. I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (upbeat music)

(digital music) >> Welcome back to "theCUBE's" live coverage of AWS re:Invent 2022. Lisa Martin here in Las Vegas with Dave Vellante. Dave, we've been here.. This is our third day, we started Monday night. We've done well over 70 interviews so far. I've lost count. >> Yeah, I don't count anymore. (Lisa laughing) >> Just go with the flow. >> We've been talking all things Cloud with AWS it's ecosystem of partners and customers. We're excited to welcome a couple of folks from Pluralsight to the program. Talking about the state of Cloud. Faye Ellis joins us, Principle Training Architect at A Cloud Guru, Pluralsight. Mattias Andersson is also here, Principle Developer Advocate at Pluralsight. Guys welcome to the queue. >> Thank you >> Thank you so much for having us. >> Great to have you. >> Mattias: Glad to be here. >> Just in case our audience isn't familiar with A Cloud Guru and Pluralsight, why don't you give us just that high level elevator pitch? >> Yeah, well we basically help organizations transform their people so that they can deliver Cloud transformations within their own organizations. So it's all about upskilling and getting people Cloud fluent and ready to rock Cloud in their own organizations. >> Love that, Cloud fluent. But what are you hearing from the developer community? Your a developer advocate. We've seen so much pivot towards the developers really influencing business decisions, business direction. What's the voice of the developer like these days? >> Well, I think that a lot of developers are recognizing that the Cloud does offer a lot of value for the things that they're wanting to get done. Developers generally want to do things, they want to build things, they want stuff that they can look at and say, "Hey I made that and it's really good and it solves problems." And so I'm hearing a lot of people talking about how they value things like serverless, to be able to build those sorts of systems without a whole lot of other people necessarily needing to support them. They can get so much built on their own even. And then as teams, they can accomplish a lot of, again, the same sorts of projects. They can build those forward much more efficiently as a smaller team than they could have in the past without that technology. So I'm hearing a lot about that. Especially because I'm working with Cloud so much is what I mean, right? >> So it's kind of putting the power back into their hands as developers. Instead of having to wait for the infrastructure people or the support people to create a server so that they can deploy applications, there's a lot more tools to allow them to actually do that for themselves, isn't there? >> Absolutely, absolutely. It opens up so many doors. >> So pre-Ukraine, we were writing about the skills shortage. I call it the slingshot economy. All right. Oh wow it's like this talent war. And then all of a sudden, Twitter layoffs and there's this talent on the street. Now it might not be a perfect match, but what are you seeing in terms of new talent coming on that you can train and coach. How are you seeing the match and the alignment with what the demand for talent? Now I know your philosophy is you should be producers of talent, not consumers of talent. I get that. >> Faye: Yeah. >> But to produce talent you've got to coach, train, assist people. So what are you seeing today? What's the state of that sort of market? >> That's a really good question. I mean our State of Cloud report, it says that 75% of tech leaders are building all their new products and features in the Cloud. But what was the other stat, Mattias? >> Only 8% of the actual individuals that are working with the technology say that they have extensive skills with the Cloud. So that's a huge gap between the people who are wanting to build that forward as the leadership of the organization and the people that they have available, whether it's internal to their organization or external. So they do have a lot of people who are working in technology already in their organizations in general. But they do need to invest in that. Those technologists are learning things all the time. But are they maybe not learning the right things? Are they not learning them effectively? Are they not moving the organization forward? >> Dave: So go ahead, please. >> Yeah, so we think it's all about like nurturing the talent that you have already in your own organization. And those are the people who really know your business. And you know, it takes time to kind of upskill and really, really develop those Cloud skills and develop that experience. But it's not always the right thing to take on new teams. Like bring in new people and then you've got to get them up to speed with your own business. And actually isn't it much more wonderful to be able to nurture the talent within your own organization and and create that long-term relationship with your own employees. >> So where do you start? Like to get to work for Amazon you got to prove that you're reasonably professional. I mean everybody, the whole company has to like spin up an EC2 instance and do something with it. Is that where you start? Is it sort of education and what's available? What's the Cloud? Or is it more advanced than that? You're looking for maybe people with a technical mind that you're.. or do you have.. obviously have different levels, but take us through sort of the anatomy of experience. >> When you say, "Where do you start?" Who are you meaning? Are you meaning an organization, an individual, a team? >> You guys, when you bring on.. begin to expose an individual to the Cloud, >> Mattias: Right. >> Their objective is to become proficient at something. >> Right. >> Right. And so is it something that you have 100, 101, 201, basically? >> Well, you know what, if you want to learn how to swim you got to jump in the water. That's what I always think. And we focus on practical skills, the ability to do something, to get something done. Get something configured within the Cloud. A lot of the time our customers are asking us for skills that kind of go beyond certification. And for a really long time we were.. A Cloud Guru has been famous for getting engineers certified. But that's just one piece of the puzzle, isn't it? Certification is wonderful, but it's that chicken and egg scenario that I think that you were alluding to which is that you need experience to get the experience. So how are you going to get that experience? And we've got loads of different ideas to help people to actually do that. On our platform we've got lots of practical exercises that you can do. Building out serverless websites, configuring a web application firewall, building a VPC. We've got troubleshooting labs, we've got challenge labs, that kind of thing. And we've also got some free resources, haven't we as well, Mattias. >> Yes. >> Things like our Cloud Portfolio Challenges, which are like little projects that you can complete all by yourself. Creating serverless websites, playing around with SageMaker. You get some requirements and you have to design and actually build that. But it's all about getting that hands-on practice and that's kind of what we focus on. And we start off with easy things, and then we kind of layer it up and layer it up. And we kind of build on the easy foundations until, before you know it, you're Cloud fluent. >> Yeah, I think that there is a lot of value.. You were mentioning to, just to circle back on certifications, that is a really valuable way for a lot of people to start to take a look at the certifications that AWS offers, for example, and say, "How can I use those to guide my learning?" Because I know that sometimes people look at certifications as like a replacement for some sort of an assessment or whatever. And it's not really that most of the time. Most of the time the key value is that it guides people to learn a scope of material that is really valuable to them. And in particular it uncovers blind spots for them. So to answer your question of "Where do you start as an individual?".. People often ask me, "Okay, so I know all these things, which certifications should I get?" And I say, the Cloud Practitioner is the place to start. And they're like, "Oh, but maybe that's too easy." And I say, maybe it is, but then it's going to be really quick for you. If it's not really quick for you, then it was really valuable. You learned those key things. And if it was really quick but you didn't spend a lot of time on it and now you're just that much further along on the next certification that sort of guides you to the next larger scope. So it's a really valuable system that I often guide people to. To say that you can jump into that, anyone actually can jump into the Cloud Practitioner and learn that. And we often recommend that across an entire organization, you could potentially have everyone that gets that Cloud Practitioner. Whether you're finance or sales or leadership executive, the individual teams in technology departments of course. But everyone can get that Cloud fluency and then they can communicate far more effectively with each other. So it's not just the technologists that are needing to do that. >> Absolutely. And I think also it's about leading by example. If you're in leadership and you are asking your engineers to upskill themselves so that you can deliver your transformation goals, well actually, it's leadership responsibility to lead by example as well. And I heard a wonderful story from a customer. Just yesterday, a female CFO in her seventies just got her Cloud Practitioner certification. >> Lisa: Right on. >> I mean, that's wonderful. As I said before, a career in Cloud is a commitment to learning. It's lifelong learning. So yeah, that's wonderful. And long may it continue. I'd love to be in my seventies still learning new things and still rocking it. Maybe not the CFO, maybe something different. But yeah, that would be wonderful. >> How do you define Cloud fluency? There's so many opportunities that you both talked about and you walked through really kind of the step-by-step process. But how would someone define themselves as Cloud fluent? And how.. it's almost like what you were talking about, Mattias, is sort of the democratization of Cloud fluency across an organization, but what does it actually look like? >> Wow, good question. For me, I think it means everybody speaking the same language and having a common understanding. And I think that does kind of hark back to what you were saying before, Mattias, about the foundational certifications. The Cloud Practitioner type certification. What do you think? >> Yeah, I think a part of it is a mindset shift that people need to understand a different way of thinking about technology. That Cloud isn't just another tool just like all the others. It's a different way, a higher level of abstraction in technology that makes us more effective and efficient because of that. But because of that, also, we need to think about it in not the same way as we were before. So if you take it to the language analogy, instead of memorizing a few phrases like "Where is the bathroom?" or "How much does that cost?" or whatever, you have an understanding of the flow of the language. You understand that okay, there are verbs and nouns and I can put them together in this way. Oh, adjectives, those are kind of interesting. I can add those to things. And you have this model, mental model for how you can interact with the technology just like you would interact with the language or whatever other things. So the mental model actually, I think, is really the key thing that I keep coming back to a lot when people are learning that the mental model that you have for something is really what.. this sort of helps you understand the mastery of that. It's whether your mental model is mature and it's not changing a lot as you're learning new information, that's a really valuable milestone for someone to get to. Because as you're learning new things.. otherwise you would make assumptions, and then you learn new things that challenge those assumptions and you have to change the mental model to move forward. So the fluency is when that mental model, you have the understanding and you can then communicate. >> Yep. Love that. Last question for you guys is, we have about a minute left. If you had a billboard that you could put anywhere about A Cloud Guru at Pluralsight and what you're enabling with respect to Cloud fluency. I want you to each kind of take about 30 seconds to.. from your perspective, what would it say? >> Oh my goodness. I think it would say something like, Cloud is for everybody. It's no longer this elitist, difficult to understand, abstract thing. And I think it's something that is inclusive to everybody and that we should all be embracing it. And if you don't do it, you are going to be left behind because your competitors are going to be getting the advantages from Cloud. You're going to miss that competitive advantage and you're going to lose out. So yeah, that's probably quite a lot to put on a billboard. >> I love it. And Mattias, what would your billboard say? >> Ah, let me think. Okay. I might say something like, "The future of technology is accessible and important if you're in a technology career." I don't know, now it's getting more wordy. That's not quite right. But the point is that the Cloud really is the future of technology. It's not just some other little tool that's a fad or whatever. It's a different way of approaching technology. I'm realizing you're asking about the billboard as a short thing. The Cloud is the future. You can do it. You should do it. (everyone laughing) >> Drop the mic. Nailed it! Faye, Mattias, thank you so much joining us.. >> Thank you so much, we really appreciate it. >> Lisa: This was a great session. >> Thank you. >> Lisa: Great to have A Cloud Guru by Pluralsight on the program. We appreciate you stopping by. >> Oh, thank you so much. >> Thank you both so very much. >> We appreciate it. >> Lisa: Our pleasure. >> Thank you. For our guests and for Dave Vellante, I'm Lisa Martin. You're watching "theCUBE", the leader in live enterprise and emerging tech coverage. (digital music)

(calming music) >> Hello and welcome back to fabulous Las Vegas, Nevada. We're here at AWS re:Invent day three of our scintillating coverage here on theCUBE. I'm Savannah Peterson, joined by John Furrier. John Day three energy's high. How you feeling? >> I dunno, it's day two, day three, day four. It feels like day four, but again, we're back. >> Who's counting? >> Three pandemic levels in terms of 50,000 plus people? Hallways are packed. I got pictures. People don't believe it. It's actually happening. Then people are back. So, you know, and then the economy is a big question too and it's still, people are here, they're still building on the cloud and cost is a big thing. This next segment's going to be really important. I'm looking forward to this next segment. >> Yeah, me too. Without further ado let's welcome our guests for this segment. We have Brad from AMD and we have Rahul from you are, well you do a variety of different things. We'll start with CloudFix for this segment, but we could we could talk about your multiple hats all day long. Welcome to the show, gentlemen. How you doing? Brad how does it feel? We love seeing your logo above our stage here. >> Oh look, we love this. And talking about re:Invent last year, the energy this year compared to last year is so much bigger. We love it. We're excited to be here. >> Yeah, that's awesome. Rahul, how are you feeling? >> Excellent, I mean, I think this is my eighth or ninth re:Invent at this point and it's been fabulous. I think the, the crowd, the engagement, it's awesome. >> You wouldn't know there's a looming recession if you look at the activity but yet still the reality is here we had an analyst on yesterday, we were talking about spend more in the cloud, save more. So that you can still use the cloud and there's a lot of right sizing, I call you got to turn the lights off before you go to bed. Kind of be more efficient with your infrastructure as a theme. This re:Invent is a lot more about that now. Before it's about the glory days. Oh yeah, keep building, now with a little bit of pressure. This is the conversation. >> Exactly and I think most companies are looking to figure out how to innovate their way out of this uncertainty that's kind of on everyone's head. And the only way to do it is to be able to be more efficient with whatever your existing spend is, take those savings and then apply them to innovating on new stuff. And that's the way to go about it at this point. >> I think it's such a hot topic, for everyone that we're talking about. I mean, total cost optimization figuring out ways to be more efficient. I know that that's a big part of your mission at CloudFix. So just in case the audience isn't versed, give us the pitch. >> Okay, so a little bit of background on this. So the other hat I wear is CTO of ESW Capital. We have over 150 enterprise software companies within the portfolio. And one of my jobs is also to manage and run about 40 to 45,000 AWS accounts of our own. >> Casual number, just a few, just a couple pocket change, no big deal. >> And like everyone else here in the audience, yeah we had a problem with our costs, just going out of control and as we were looking at a lot of the tools to help us kind of get more efficient one of the biggest issues was that while people give you a lot of recommendations recommendations are way too far from realized savings. And we were running through the challenge of how do you take recommendation and turn them into real savings and multiple different hurdles. The short story being, we had to create CloudFix to actually realize those savings. So we took AWS recommendations around cost, filtered them down to the ones that are completely non-disruptive in nature, implemented those as simple automations that everyone could just run and realize those savings right away. We then took those savings and then started applying them to innovating and doing new interesting things with that money. >> Is there a best practice in your mind that you see merging in this time? People start more focused on it. Is there a method or a purpose kind of best practice of how to approach cost optimization? >> I think one of the things that most people don't realize is that cost optimization is not a one and done thing. It is literally nonstop. Which means that, on one hand AWS is constantly creating new services. There are over a hundred thousand API at this point of time How to use them right, how to use them efficiently You also have a problem of choice. Developers are constantly discovering new services discovering new ways to utilize them. And they are behaving in ways that you had not anticipated before. So you have to stay on top of things all the time. And really the only way to kind of stay on top is to have automation that helps you stay on top of all of these things. So yeah, finding efficiencies, standardizing your practices about how you leverage these AWS services and then automating the governance and hygiene around how you utilize them is really the key >> Brad tell me what this means for AMD and what working with CloudFix and Rahul does for your customers. >> Well, the idea of efficiency and cost optimization is near and dear to our heart. We have the leading. >> It's near and dear to everyone's heart, right now. (group laughs) >> But we are the leaders in x86 price performance and density and power efficiency. So this is something that's actually part of our core culture. We've been doing this a long time and what's interesting is most companies don't understand how much more efficiency they can get out of their applications aside from just the choices they make in cloud. but that's the one thing, the message we're giving to everybody is choice matters very much when it comes to your cloud solutions and just deciding what type of instance types you choose can have a massive impact on your bottom line. And so we are excited to partner with CloudFix, they've got a great model for this and they make it very easier for our customers to help identify those areas. And then AMD can come in as well and then help provide additional insight into those applications what else they can squeeze out of it. So it's a great relationship. >> If I hear you correctly, then there's more choice for the customers, faster selection, so no bad choices means bad performance if they have a workload or an app that needs to run, is that where you you kind of get into the, is that where it is or more? >> Well, I mean from the AMD side right now, one of the things they do very quickly is they identify where the low hanging fruit is. So it's the thing about x86 compatibility, you can shift instance types instantly in most cases without any change to your environment at all. And CloudFix has an automated tool to do that. And that's one thing you can immediately have an impact on your cost without having to do any work at all. And customers love that. >> What's the alternative if this doesn't exist they have to go manually figure it out or it gets them in the face or they see the numbers don't work or what's the, if you don't have the tool to automate what's the customer's experience >> The alternative is that you actually have people look at every single instance of usage of resources and try and figure out how to do this. At cloud scale, that just doesn't make sense. You just can't. >> It's too many different options. >> Correct The reality is that your resources your human resources are literally your most expensive part of your budget. You want to leverage all the amazing people you have to do the amazing work. This is not amazing work. This is mundane. >> So you free up all the people time. >> Correct, you free up wasting their time and resources on doing something that's mundane, simple and should be automated, because that's the only way you scale. >> I think of you is like a little helper in the background helping me save money while I'm not thinking about it. It's like a good financial planner making you money since we're talking about the economy >> Pretty much, the other analogy that I give to all the technologists is this is like garbage collection. Like for most languages when you are coding, you have these new languages that do garbage collection for you. You don't do memory management and stuff where developers back in the day used to do that. Why do that when you can have technology do that in an automated manner for you in an optimal way. So just kind of freeing up your developer's time from doing this stuff that's mundane and it's a standard best practice. One of the things that we leverage AMD for, is they've helped us define the process of seamlessly migrating folks over to AMD based instances without any major disruptions or trying to minimize every aspect of disruption. So all the best practices are kind of borrowed from them, borrowed from AWS in most other cases. And we basically put them in the automation so that you don't ever have to worry about that stuff. >> Well you're getting so much data you have the opportunity to really streamline, I mean I love this, because you can look across industry, across verticals and behavior of what other folks are doing. Learn from that and apply that in the background to all your different customers. >> So how big is the company? How big is the team? >> So we have people in about 130 different countries. So we've completely been remote and global and actually the cloud has been one of the big enablers of that. >> That's awesome, 130 countries. >> And that's the best part of it. I was just telling Brad a short while ago that's allowed us to hire the best talent from across the world and they spend their time building new amazing products and new solutions instead of doing all this other mundane stuff. So we are big believers in automation not only for our world. And once our customers started asking us about or telling us about the same problem that they were having that's when we actually took what we had internally for our own purpose. We packaged it up as CloudFix and launched it last year at re:Invent. >> If the customers aren't thinking about automation then they're going to probably have struggle. They're going to probably struggle. I mean with more data coming in you see the data story here more data's coming in, more automation. And this year Brad price performance, I've heard the word price performance more this year at re:Invent than any other year I've heard it before, but this year, price performance not performance, price performance. So you're starting to hear that dialogue of squeeze, understand the use cases use the right specialized processor instance starting to see that evolve. >> Yeah and and there's so much to it. I mean, AMD right out of the box is any instance is 10% less expensive than the equivalent in the market right now on AWS. They do a great job of maximizing those products. We've got our Zen four core general processor family just released in November and it's going to be a beast. Yeah, we're very excited about it and AWS announced support for it so we're excited to see what they deliver there too. But price performance is so critical and again it's going back to the complexity of these environments. Giving some of these enterprises some help, to help them understand where they can get additional value. It goes well beyond the retail price. There's a lot more money to be shaved off the top just by spending time thinking about those applications. >> Yeah, absolutely. I love that you talked about collaboration we've been talking about community. I want to acknowledge the AWS super fans here, standing behind the stage. Rahul, I know that you are an AWS super fan. Can you tell us about that community and the program? >> Yeah, so I have been involved with AWS and building products with AWS since 2007. So it's kind of 15 years back when literally there were just a handful of API for launching EC2 instances and S3. >> Not the a hundred thousand that you mentioned earlier, my goodness, the scale. >> So I think I feel very privileged and honored that I have been part of that journey and have had to learn or have had the opportunity to learn both from successes and failures. And it's just my way of contributing back to that community. So we are part of the FinOps foundation as well, contributing through that. I run a podcast called AWS Insiders and a livestream called AWS Made Easy. So we are trying to make sure that people out there are able to understand how to leverage AWS in the best possible way. And yeah, we are there to help and hold their hand through it. >> Talk about the community, take a minute to explain to the audience watching the community around this cost optimization area. It's evolving, you mentioned FinOps. There's a whole large community developing, of practitioners and technologists coming together to look at this. What does this all mean? Talk about this community. >> So cost management within organizations is has evolved so drastically that organizations haven't really coped with it. Historically, you've had finance teams basically buy a lot of infrastructure, which is CapEx and the engineering teams had kind of an upper bound on what they would spend and where they would spend. Suddenly with cloud, that's kind of enabled so much innovation all of a sudden, everyone's realized it, five years was spent figuring out whether people should be on the cloud or not. That's no longer a question, right. Everyone needs to be in the cloud and I think that's a no-brainer. The problem there is that suddenly your operating model has moved from CapEx to OpEx. And organizations haven't really figured out how to deal with it. Finance now no longer has the controls to control and manage and forecast costs. Engineering has never had to deal with it in the past and suddenly now they have to figure out how to do all this finance stuff. And procurement finds itself in a very awkward way position because they are no longer doing these negotiations like they were doing in the past where it was okay right up front before you engage, you do these negotiations. Now it's kind of an ongoing thing and it's constantly changing. Like every day is different. >> And you got marketplace >> And you got marketplace. So it's a very complex situation and I think what we are trying to do with the FinOps foundation is try and take a lot of the best practices across organizations that have been doing this at least for the last 10, 15 years. Take all the learnings and failures and turn them into hopefully opinionated approaches that people can take organizations can take to navigate through this faster rather than kind of falter and then decide that oh, this is not for us. >> Yeah. It's a great model, it's a great model. >> I know it's time John, go ahead. >> All right so, we got a little bumper sticker exercise we used to say what's the bumper sticker for the show? We used to say that, now we're modernizing, we're saying if you had to do an Instagram reel right now, short hot take of what's going on at re:Invent this year with AMD or CloudFix or just in general what would be the sizzle reel, that would be on Instagram or TikTok, go. >> Look, I think when you're at re:Invent right now and number one the energy is fantastic. 23 is going to be a building year. We've got a lot of difficult times ahead financially but it's the time, the ones that come out of 23 stronger and more efficient, and cost optimize are going to survive the long run. So now's the time to build. >> Well done, Rahul let's go for it. >> Yeah, so like Brad said, cost and efficiencies at the top of everyone's mind. Stuff that's the low hanging fruit, easy, use automation. Apply your sources to do most of the innovation. Take the easiest part to realizing savings and operate as efficiently as you possibly can. I think that's got to be key. >> I think they nailed it. They both nailed it. Wow, well it was really good. >> I put you on our talent list of >> And alright, so we repeat them. Are you part of our host team? I love this, I absolutely love this Rahul we wish you the best at CloudFix and your 17 other jobs. And I am genuinely impressed. Do you sleep actually? Last question. >> I do, I do. I have an amazing team that really helps me with all of this. So yeah, thanks to them and thank you for having us here. >> It's been fantastic. >> It's our pleasure. And Brad, I'm delighted we get you both now and again on our next segment. Thank you for being here with us. >> Thank you very much. >> And thank you all for tuning in to our live coverage here at AWS re:Invent, in fabulous Sin City with John Furrier, my name's Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (calm music)

(upbeat music) (background crowd chatter) >> Hello, fantastic cloud community and welcome back to Las Vegas where we are live from the show floor at AWS re:Invent. My name is Savannah Peterson. Joined for the first time. >> Yeah, Doobie. >> VIP, I know. >> All right, let's do this. >> Thanks for having me Dave, I really appreciate it. >> I appreciate you doing all the hard work. >> Yeah. (laughs) >> You, know. >> I don't know about that. We wouldn't be here without you and all these wonderful stories that all the businesses have. >> Well, when I host with John it's hard for me to get a word in edgewise. I'm just kidding, John. (Savannah laughing) >> Shocking, I've never want that experience. >> We're like knocking each other, trying to, we're elbowing. No, it's my turn to speak, (Savannah laughing) so I'm sure we're going to work great together. I'm really looking forward to it. >> Me too Dave, I feel very lucky to be here and I feel very lucky to introduce our guest this afternoon, Clint Sharp, welcome to the show. You are with Cribl. Yeah, how does it feel to be on the show floor today? >> It's amazing to be back at any conference in person and this one is just electric, I mean, there's like a ton of people here love the booth. We're having like a lot of activity. It's been really, really exciting to be here. >> So you're a re:Ieinvent alumni? Have you been here before? You're a Cube alumni. We're going to have an OG conversation about observability, I'm looking forward to it. Just in case folks haven't been watching theCUBE for the last nine years that you've been on it. I know you've been with a few different companies during that time period. Love that you've been with us since 2013. Give us the elevator pitch for Cribl. >> Yeah, so Cribl is an observability company which we're going to talk about today. Our flagship product is a telemetry router. So it just really helps you get data into the right places. We're very specifically in the observability and security markets, so we sell to those buyers and we help them work with logs and metrics and open telemetry, lots of different types of data to get it into the right systems. >> Why did observability all of a sudden become such a hot thing? >> Savannah: Such a hot topic. >> Right, I mean it just came on the scene so quickly and now it's obviously a very crowded space. So why now, and how do you guys differentiate from the crowd? >> Yeah, sure, so I think it's really a post-digital transformation thing Dave, when I think about how I interact with organizations you know, 20 years ago when I started this business I called up American Airlines when things weren't working and now everything's all done digitally, right? I rarely ever interact with a human being and yet if I go on one of these apps and I get a bad experience, switching is just as easy as booking another airline or changing banks or changing telecommunications providers. So companies really need an ability to dive into this data at very high fidelity to understand what Dave's experience with their service or their applications are. And for the same reasons on the security side, we need very, very high fidelity data in order to understand whether malicious actors are working their way around inside of the enterprise. And so that's really changed the tooling that we had, which, in prior years, it was really hard to ask arbitrary questions of that data. You really had to deal with whatever the vendor gave you or you know, whatever the tool came with. And observability is really an evolution, allowing people to ask and answer questions of their data that they really weren't planning in advance. >> Dave: Like what kind of questions are people asking? >> Yeah sure so what is Dave's performance with this application? I see that a malicious actor has made their way on the inside of my network. Where did they go? What did they do? What files did they access? What network connections did they open? And the scale of machine data of this machine to machine communication is so much larger than what you tend to see with like human generated data, transactional data, that we really need different systems to deal with that type of data. >> And what would you say is your secret sauce? Like some people come at it, some search, some come at it from security. What's your sort of superpower as Lisa likes to say? >> Yeah, so we're a customer's first company. And so one of the things I think that we've done incredibly well is go look at the market and look for problems that are not being solved by other vendors. And so when we created this category of an observability pipeline, nobody was really marketing an observability pipeline at that time. And really the problem that customers had is they have data from a lot of different sources and they need to get it to a lot of different destinations. And a lot of that data is not particularly valuable. And in fact, one of the things that we like to say about this class of data is that it's really not valuable until it is, right? And so if I have a security breach, if I have an outage and I need to start pouring through this data suddenly the data is very, very valuable. And so customers need a lot of different places to store this data. I might want that data in a logging system. I might want that data in a metric system. I might want that data in a distributed tracing system. I might want that data in a data lake. In fact AWS just announced their security data lake product today. >> Big topic all day. >> Yeah, I mean like you can see that the industry is going in this way. People want to be able to store massively greater quantities of data than they can cost effectively do today. >> Let's talk about that just a little bit. The tension between data growth, like you said it's not valuable until it is or until it's providing context, whether that be good or bad. Let's talk about the tension between data growth and budget growth. How are you seeing that translate in your customers? >> Yeah, well so data's growing in a 25% CAGR per IDC which means we're going to have two and a half times the data in five years. And when you talk to CISOs and CIOs and you ask them, is your budget growing at a 25% CAGR, absolutely not, under no circumstances am I going to have, you know, that much more money. So what got us to 2022 is not going to get us to 2032. And so we really need different approaches for managing this data at scale. And that's where you're starting to see things like the AWS security data lake, Snowflake is moving into this space. You're seeing a lot of different people kind of moving into the database for security and observability type of data. You also have lots of other companies that are competing in broad spectrum observability, companies like Splunk or companies like Datadog. And these guys are all doing it from a data-first approach. I'm going to bring a lot of data into these platforms and give users the ability to work with that data to understand the performance and security of their applications. >> Okay, so carry that through, and you guys are different how? >> Yeah, so we are this pipeline that's sitting in the middle of all these solutions. We don't care whether your data was originally intended for some other tool. We're going to help you in a vendor-neutral way get that data wherever you need to get it. And that gives them the ability to control cost because they can put the right data in the right place. If it's data that's not going to be frequently accessed let's put it in a data lake, the cheapest place we can possibly put that data to rest. Or if I want to put it into my security tool maybe not all of the data that's coming from my vendor, my vendor has to put all the data in their records because who knows what it's going to be used for. But I only use half or a quarter of that information for security. And so what if I just put the paired down results in my more expensive storage but I kept full fidelity data somewhere else. >> Okay so you're observing the observability platforms basically, okay. >> Clint: We're routing that data. >> And then creating- >> It's meta observability. >> Right, observability pipeline. When I think a data pipeline, I think of highly specialized individuals, there's a data analyst, there's a data scientist, there's a quality engineer, you know, etc, et cetera. Do you have specific roles in your customer base that look at different parts of that pipeline and can you describe that? >> Yeah, absolutely, so one of the things I think that we do different is we sell very specifically to the security tooling vendors. And so in that case we are, or not to the vendors, but to the customers themselves. So generally they have a team inside of that organization which is managing their security tooling and their operational tooling. And so we're building tooling very specifically for them, for the types of data they work with for the volumes and scale of data that they work with. And that is giving, and no other vendor is really focusing on them. There's a lot of general purpose data people in the world and we're really the only ones that are focusing very specifically on observability and security data. >> So the announcement today, the security data lake that you were talking about, it's based on the Open Cybersecurity Framework, which I think AWS put forth, right? And said, okay, everybody come on. [Savannah] Yeah, yeah they did. >> So, right, all right. So what are your thoughts on that? You know, how does it fit with your strategy, you know. >> Yeah, so we are again a customer's first neutral company. So if OCSF gains traction, which we hope it does then we'll absolutely help customers get data into that format. But we're kind of this universal adapter so we can take data from other vendors, proprietary schemas, maybe you're coming from one of the other send vendors and you want to translate that to OCSF to use it with the security data lake. We can provide customers the ability to change and reshape that data to fit into any schema from any vendor so that we're really giving security data lake customers the ability to adapt the legacy, the stuff that they have that they can't get rid of 'cause they've had it for 10 years, 20 years and nothing inside of an enterprise ever goes away. That stuff stays forever. >> Legacy. >> Well legacy is working right? I mean somebody's actually, you know, making money on top of this thing. >> We never get rid of stuff. >> No, (laughing) we just added the toolkit. It's like all the old cell phones we have, it's everything. I mean we even do it as individual users and consumers. It's all a part of our little personal library. >> So what's happened in the field company momentum? >> Yeah let's talk trends too. >> Yeah so the company's growing crazily fast. We're north of 400 employees and we're only a hundred and something, you know, a year ago. So you can kind of see we're tripling you know, year over year. >> Savannah: Casual, especially right now in a lot of companies are feeling that scale back. >> Yeah so obviously we're keeping our eye closely on the macro conditions, but we see such a huge opportunity because we're a value player in this space that there's a real flight to value in enterprises right now. They're looking for projects that are going to pay themselves back and we've always had this value prop, we're going to come give you a lot of capabilities but we're probably going to save you money at the same time. And so that's just really resonating incredibly well with enterprises today and giving us an opportunity to continue to grow in the face of some challenging headwinds from a macro perspective. >> Well, so, okay, so people think okay, security is immune from the macro. It's not, I mean- >> Nothing, really. >> No segment is immune. CrowdStrike announced today the CrowdStrike rocket ship's still growing AR 50%, but you know, stocks down, I don't know, 20% right now after our- >> Logically doesn't make- >> Okay stuff happens, but still, you know, it's interesting, the macro, because it was like, to me it's like a slingshot, right? Everybody was like, wow, pandemic, shut down. All of a sudden, oh wow, need tech, boom. >> Savannah: Yeah, digitally transformed today. >> It's like, okay, tap the brakes. You know, when you're driving down the highway and you get that slingshotting effect and I feel like that's what's going on now. So, the premise is that the real leaders, those guys with the best tech that really understand the customers are going to, you know, get through this. What are your customers telling you in terms of, you know they're spending patterns, how they're trying to maybe consolidate vendors and how does that affect you guys? >> Yeah, for sure, I mean, I think, obviously, back to that flight to value, they're looking for vendors who are aligned with their interests. So, you know, as their budgets are getting pressure, what vendors are helping them provide the same capabilities they had to provide to the business before especially from a security perspective 'cause they're going to get cut along with everybody else. If a larger organization is trimming budgets across, security's going to get cut along with everybody else. So is IT operations. And so since they're being asked to do more with less that's you know, really where we're coming in and trying to provide them value. But certainly we're seeing a lot of pressure from IT departments, security departments all over in terms of being able to live and do more with less. >> Yeah, I mean, Celip's got a great quote today. "If you're looking to tighten your belt the cloud is the place to do it." I mean, it's probably true. >> Absolutely, elastic scalability in this, you know, our new search product is based off of AWS Lambda and it gives you truly elastic scalability. These changes in architectures are what's going to allow, it's not that cloud is cheaper, it's that cloud gives you on-demand scalability that allows you to truly control the compute that you're spending. And so as a customer of AWS, like this is giving us capabilities to offer products that are scalable and cost effective in ways that we just have not been able to do in the cloud. >> So what does that mean for the customer that you're using serverless using Lambda? What does that mean for them in terms of what they don't have to do that they maybe had to previously? >> It offers us the ability to try to charge them like a truly cloud native vendor. So in our cloud product we sell a credit model whereby which you deduct credits for usage. So if you're streaming data, you pay for gigabytes. If you're searching data then you're paying for CPU consumption, and so it allows us to charge them only for what they're consuming which means we don't have to manage a whole fleet of servers, and eventually, well we go to managing our own compute quite possibly as we start to get to scale at certain customers. But Lambda allowed us to not have to launch that way, not have to run a bunch of infrastructure. And we've been able to align our charging model with something that we think is the most customer friendly which is true consumption, pay for what you consume. >> So for example, you're saying you don't have to configure the EC2 Instance or figure out the memory sizing, you don't have to worry about any of that. You just basically say go, it figures that out and you can focus on upstream, is that right? >> Yep, and we're able to not only from a cost perspective also from a people perspective, it's allowed us velocity that we did not have before, which is we can go and prototype and build significantly faster because we're not having to worry, you know, in our mature products we use EC2 like everybody else does, right? And so as we're launching new products it's allowed us to iterate much faster and will we eventually go back to running our own compute, who knows, maybe, but it's allowed us a lot faster velocity than we were able to get before. >> I like what I've heard you discuss a lot is the agility and adaptability. We're going to be moving and evolving, choosing different providers. You're very outspoken about being vendor agnostic and I think that's actually a really unique and interesting play because we don't know what the future holds. So we're doing a new game on that note here on theCUBE, new game, new challenge, I suppose I would call it to think of this as your 30 second thought leadership highlight reel, a sizzle of the most important topic or conversation that's happening theme here at the show this year. >> Yeah, I mean, for me, as I think, as we're looking, especially like security data lake, et cetera, it's giving customers ownership of their data. And I think that once you, and I'm a big fan of this concept of open observability, and security should be the same way which is, I should not be locking you in as a vendor into my platform. Data should be stored in open formats that can be analyzed by multiple places. And you've seen this with AWS's announcement, data stored in open formats the same way other vendors store that. And so if you want to plug out AWS and you want to bring somebody else in to analyze your security lake, then great. And as we move into our analysis product, our search product, we'll be able to search data in the security data lake or data that's raw in S3. And we're really just trying to give customers back control over their future so that they don't have to maintain a relationship with a particular vendor. They're always getting the best. And that competition fuels really great product. And I'm really excited for the next 10 years of our industry as we're able to start competing on experiences and giving customers the best products, the customer wins. And I'm really excited about the customer winning. >> Yeah, so customer focused, I love it. What a great note to end on. That was very exciting, very customer focused. So, yo Clint, I have really enjoyed talking to you. Thanks. >> Thanks Clint. >> Thanks so much, it's been a pleasure being on. >> Thanks for enhancing our observability over here, I feel like I'll be looking at things a little bit differently after this conversation. And thank all of you for tuning in to our wonderful afternoon of continuous live coverage here at AWS re:Ieinvent in fabulous Las Vegas, Nevada with Dave Vellante. I'm Savannah Peterson. We're theCUBE, the leading source for high tech coverage. (bright music)