>> Narrator: Live from Las Vegas, it's theCUBE covering AWS re:Invent 2017 presented by AWS, Intel, and our ecosystem of partners. >> Welcome back, I'm Stu Miniman here with my cohost, Justin Warren, and you are watching theCUBE SiliconANGLE Media's live production of AWS re:Invent 2017. Happy to welcome back to the program, Rishi Yadav, who is the CEO of Zettabytes, and Bart Hickenlooper, who is the SAP of client services. Thank you so much for joining us. >> Thank you, Stu. >> So Rishi, yesterday you on the other set with John Furrier and with Justin, and we were really excited to really launch Zettabytes, help you bring the company out. We've known Infoobjects and your company for a while, so of course we want people to go check out the other interview, but in today's hybrid multi-cloud world, we've seen Amazon kind of slowly moderating a little bit the way they discuss it, but why don't you bring us inside a little bit? What are you hearing from customers, and what kind of led to the creation of Zettabytes? >> What we are hearing from customers is that there is a lot of talk about the cloud and AWS. The challenges that what I discussed yesterday also was that how do I take those baby steps toward our option of the cloud? That is where the challenge comes. On one side and they say everything on prem is bad. Everything on cloud is good. Those kind of statements are okay, but somebody who has got billions of dollars of business running, for them it doesn't make any sense. They want to have logical steps, and they also want to have, with every step, what value they are adding. >> We always hear, right, we always take in and it's like all in on any one thing. Oh come on, you are using various SAS providers. You probably have multiple cloud providers. Yes, you've still got something sitting in the backend of your data center, where many things, and that migration takes time. What kind of strategy and tactics do you hear customers doing that gets Zettabyte engaged? >> What was in most enterprises is an effort to really modernize their applications. They want to make those so that they are cloud native leveraging the innovation that's taking place in the cloud. That application modernization is really what's driving an enterprise to do some things and move quickly to the cloud. It's no longer the economics of moving to the cloud, but that innovation engine that can be really egnited with those technologies. Getting there from their legacy platforms is a little tricky. They need a development cycle that works in a hybrid fashion to really go cloud native with those applications. >> When they're starting off on that journey, where do you find customers starting with? What are the applications that they do first, and what are the functions that they use from AWS, like are they going with just EC2 type things? Are they using S3 for storage? What do they start with? >> That's a good point that for the first phase of the cloud out option most of the work was on IES. Whatever you have on prem, you just put that on the cloud then obviously you go through your storage and things like that. That is where there was a lot of talk. If you remember a few years back, everybody was saying, "The cloud is not cheap, "the cloud is costly," and as Bart said, it's not about economics. Has always about convenience. It's always about the value-added, and especially when enterprises started getting into the cloud, started the all opt in cloud a few years back, that's where those things became very important because that is what they wanted. You just cannot save someone 20% in investiture cost and that may not even come and that it's worth the option of the cloud. >> We were talking yesterday about the 100 services, the number of services that you as an orginzation have to wrap your brain around and one of the things that Zettabytes helps with that is to give you some focus so again, what are the things that Zettabytes is focusing on that they find that customers actually really, really want from cloud. Amazon is so huge. Making sense of the whole thing is quite tricky. When you talk about application modernization, if you have a monolithic application, EC2 and S3 are great. If you are going to migrate it, you can do that. What we are seeing is really a switch to DevOps for application development, microservices development that leverage certain platform services from Amazon that are specific to enable an application, and those are things like Lambda, Kinesis, Elasticsearch, and you can write microservices that consume those services in addition to your traditional storage and compute, and really get cloud native. We've selected those services on our platform to help with that application modernization and really enable a customer to make applications with microservices enablement. >> WikiBon has been looking at many years really. What has happened with this transformation of the data center. The research that we put out a few years ago is what we call true private cloud because like you said, what was happening the virtualization plus. I love virtualization. I spent 15 years on that wave, but it wasn't enough, and even when we started simplifying with even some automation on there, that application journey, and how do we get ready for modern applications? I worked a lot on the HCI wave. It was, "Let's modernize our infrastructure, "and then we will worry about that application stuff later, "and maybe it's not a fit." What is different now? What are the toolings available? Why is now, can I put that stuff, I mean, the cloud native, isn't it? That should all live in a public cloud, no? What cannot live in many places? >> I think that's a great point. Three pieces of the puzzle, infrastructure, data, and the applications so there has been a lot of talk about infrastructure and not having infrastructure. Data, every other company in the Bay Area is a backup and restore company. Nobody is talking about applications. Yes, they are SAS players, right? We are like, okay, we will just host an application for you and you don't have to worry about anything else, but what about a lot of these legacy applications which have been built over the last 20 or 30 years? Nobody is talking about that. Everybody talks about greenfield applications. What about we start new? Everything is going to be the cloud. Is going to be cloud native. Everything is awesome, and then the clients say, "Yes "but I already invested $5 million in the applications "in the last 10 years." What's going to happen to them? >> To say that the first 80% of writing software is putting the bugs in, and then the second 80% of writing software is taking them out again, so if you have to completely start with these core business applications that are generating revenue, there's a lot of risk there in going to something brand-new. I know we've had Andy Jassy talking about if I was starting the company again today, I would go completely all serverless. And I think, really? Right now in 2017? Is it really that established and that great? What is your take on that? For an enterprise that have this investment already, should they be going completely all into serverless, or should they be picking off some of these other more mature services do you think? >> I would say it would be really application-specific. If it's traditional transactional, you may or may not want to go serverless because you've got that relational database really kind of structured around it. If it's a modern application and you are a company that has, for example, a brand-new mobile application, then you are going to want to leverage things like Lambda in those application development so you can trigger the correct service to spin up in that application. I think modernization is really specific to the use case. What we are seeing is a digital transformation in most companies where they are really requiring some newer applications to leverage past services like Lambda, Elasticsearch, Kinesis, and other things. >> Rishi, one of the things that we've heard from customers for many years is they so that they'd like to have the same in their data center as in the public cloud. We did a survey years ago and everybody, it was like 80% said that then said, "What do you have?" I've got VMware here and I've got an AWS there. Is it about having the whole stack? Are APIs enough? How much commonality do you need? How does Zettabytes look at this And had to help customers bridge this model? >> Yes absolutely, so number one is that the VMware type of solution is still pretty much, I like VMware but it's pretty much infrastructure as a service base. The second thing is the reason we have come up with our platform is that few core services and for few key workloads, IOT is being one of them, low intensive uploads being another of them, the workloads in which you need special type of security and governance which clients are used to from the last 20 years. Yes, AWS have amazing security and governance, no doubt about that, but still, part of the workload they may want to run locally, and they should at least have that freedom. Only those part of workloads are going to be run on Zettabytes plans, but the API compatibility will provide complete, so whether you want to run it on Zettabytes or on AWS, most of the workloads are going to work on AWS, and that you can run from our platform. >> I want to keep off the word you mentioned there. You mentioned appliances. We have seen lots of solutions over the last decade. You have done quite well as appliances. Talk about the HCI, talk about the backup recovery, lots of things there, but it's a software world now. Hex serverless, Andy Jassy says we will build serverless. Why an appliance? Talk a little bit about the go to market. What do people get today? How do they buy it? Why does that make sense for your customers? >> Yes absolutely, a value added more from the sales perspective but appliance, from the optimization perspective is perfect. In our case, yes, we have figured out a spec which is perfect perfectly optimized for tuning our software platform and we can provide to the clients. If they want to have a similar stack built themselves that is perfectly okay, but the idea is that hardware has an equally important role to play as software has. >> When you think about the platform services that we have like S3, RDS, and others, you definitely need hardware to support a real workload and for us to really standardize on something that someone can do, true development with that depth on the platform is really critical. You can go to GitHub and get open source S3 and work around it, but it's a mock. Really what you need is a platform to develop application, and the other thing is I worked for Cisco for 10 years, and the channel there is extremely powerful with companies like CDW, WWT, the routes to market there is really compelling for combined solution and I think part of the reason you are seeing success with those combined solutions is the customers are used to a service model where it's one throat to choke on those types of platforms, and the channel is a trusted advisor. It's a great way for us to go to market. >> Yeah, to just give my two cents on that, people conflate that we've had some commoditization of what's happening in infrastructure. It doesn't mean just grab stuff off of the shelf. I read an article 4 years ago. AWS infrastructure is hyper optimized. If you went to the Tuesday night's keynote, oh my gosh, they spent way more on hardware than anybody else in this ecosystem, I'm sure, and spent more as much, so it's not that you have IP in hardware. From my understanding it you are making sure you've got, your software is natural to package. If I can do it, somebody else can do it. >> Bart: Yeah, go ahead. >> Absolutely, I think that part is very, very important that one throat to choke, one company which supports everything. In our case, yes, if you want to have your own hardware, then you can do that, but in our case, if you take the whole appliance from us, that we are providing you complete support. Hardware, operating system, as well as the software. >> And in a certain sense, we are really trying to, l like you said, Stu, match the performance of those optimized environments on AWS for our clients so they get a similar experience from our platform that they would get on AWS. If they build something on Zettabytes and then deploy on AWS, they should get the same experience. >> I want to give you the last word. I'm sure you have lots of customers coming by our booth. It's not far from where you're sitting right now. What are some of the key things they are hearing? What is getting them excited, interested in, that they want to follow up with? >> I think most of the customers we've talked to we say, "Okay, are you using AWS?" they say, "Yes," because they are at re:Invent. I say, "Okay, how far you are in the AWS option?" that's where the devil comes in the details. These applications we have been able to migrate, these we have not been able to migrate. We are building our exponents around it and things like that, and then the question comes, "Do you really want to go too deep into figuring out "the problems which the vendors have solved, "or would you rather focus on your business problems?" that's what I would say. They would say one package, one platform when you get to focus on your business problems and we take care of the rest. >> Yeah, and I think in the keynote yesterday, Andy Jassy said it's all about the analytics and what we are hearing is we've given a lot of thought to putting together a platform that supports big data analytics in addition to the AWS abstraction that we've done, so those analytics workloads were really intriguing to people that are talking with us, our support of machine learning, converting what may be a traditional spark job into a Lambda function is really something people are raising their eyebrows about. >> Bart Hickenlooper, Rishi Yadav asking how deep you are into AWS? Well here at theCUBE we are about 60 interviews in which means we have a few more hours left of great interviews here, so for Justin Warren, I'm Stu Miniman. Thank you so much for watching theCUBE.

>> Announcer: Live from Las Vegas, it's The Cube, covering AWS re:Invent 2017 presented by AWS, Intel, and our ecosystem of partners. >> Hey, welcome back everyone. Live here in Las Vegas, the Cube is covering exclusively the AWS re:Invent. We've got two sets. This is set one, set two behind me. We're here with a startup called Zettabytes, Rishi Yadav, Cube Alumni CEO, and Sudhir Janir, CTO. Hot new start-up, Zettabytes. Formerly, you're an entrepreneur, your other company's still going, Info Objects. Welcome back. >> Thanks for having us here. I dont know it's the seventh time, eighth time? I mean, we love Cube guys. Yes, so Info Objects is the mothership and doing really, really great, and today we are launching Zettabytes, which is our hybrid cloud, cloud integration platform. We are starting with AWS, and then it's going to have integration for the clouds. >> So start-ups are impacted, and we were talking yesterday about kind of a demarcation line between a point in time. I say 2012, maybe you can say 2014, if you were born before 2012 or 2014, you probably didn't factor the cloud as large scale as it is. But after that day, you're a new born start-up, you look at the cloud as a resource, an opportunity, so what's your perspective as an entrepreneur, a serial entrepreneur, you start a company, you look at the big beast in Amazon, opportunity, challenge, what's your view? >> So actually 2014 was an inflection point for two things. Number one is that the big data, big data, it started with the hyper scale companies, and at that time, you're talking about Facebook, and Yahoo and other places, but it was not enterprise-ready. And we suddenly saw the option. John, you have been following the big data directly from the, I think the cloud data basement days, right? So in 2014 it got a better option. And the things like security and governance, which were offered not much concern earlier, it became front and center. Another thing which happened was around 2014, 2015, timeframe, the public cloud, which were for eight, nine years, essentially AWS, that was about 70 start-ups about saving money for them. That also started getting an option, and the enterprise, and when you're talking about enterprise, there you cannot tell them that if you deploy 10 servers on AWS, it's going to save you $200,000. They would say you already have $500 million spent. We have these huge data centers, so they needed some more value than that. >> How about your company Zettabytes, so you're launching a new company, what is it, what does it do, why are you starting it? Take a minute to explain what you're doing. >> Yes, absolutely. So the Zettabytes idea came from this convergence of the big data, public cloud and IOT. And market is ripe for it, and the challenge was that we talked to a lot of customers, a lot of them have already started working in the cloud, and some of them were planning to start the journey in the cloud, and the challenge was that at the same time they also wanted to build a big data link, Andy talked about it a lot today, right, assuming the largest big data lake. So now the question was that do you really want to go the old school route in which you are using Hadoup and other services around it, and then you do lift and shift to AWS? And then you transform to PAS. So you spend one and a half, two years in doing Hadoup, and then you spend another one and a half, two years, doing the PAZ, that cloud-native transformation in a better way. And then realize that whether the clients are on AWS today, or they are going to be in one year, they need the same experience, the same cloud experience, the same AWS experience which they have on their AWS, they want on-prem. Now that includes the other cloud-native APIs, but also the agility and everything else. >> So let met ask Sudhir a question. So you're the CTO. I know you're technical too, so I have both of you. So the old days, I'm a developer, I have my local host, I'm banging away code, and then I go, okay I'm done. And I say, ship to the server for QA or whatever. And even the cloud. Businesses want that same kind of functionality on premise. They want to go to the cloud, so all the developers are changing, they want that local host like feel. They don't wanna have to write code, ship it to a server, put it through the cloud, they just want instant integration to Amazon. Is that what you're doing? >> Yeah. >> Did I get it right? 'Cause that seems what I think you're doing. >> Yes, you develop that seamless experience. So you have the same set of APIs, which you normally would do on AWS, so still use the same data, still use the same data blue CLI. Use all data blue APIs, we're accepted those APIs on this platform, build a good base, based on those APIs, now using Kubernetes, you decide where this workload will go. >> So one of the challenges of AWS though is that they release services like constantly. I think we had the announcer at the keynote today, it was like another hundred or so services that they were releasing. So how do you choose which ones? Do you support all of them, or do you focus on specific ones? >> No, first we are focusing on a few specific ones, which are mostly being used. We are starting with Lexi, for example, as three. Lamda, Kenesis, Kafka, and this bargain is DFS are there from day one also. And all of these are Lexi, we are doing Lexi, today official announcement, they have launched Kubernetes Now. Container management service. We have that flexibility from day one only. So we have that in our outlines, and using that, even for example, your workload says, some of the piece should run on that, on Lexi, on permalines. Some of the P should go to the cloud, that is also possible. >> So you're selling an appliance. >> Yeah, yeah. The one million Lexi, or Kubernetes million might run on the AWS, few of the menus might run on your uplines, you can easily Lexi's do the all the container management. >> This is model, they pay for the box, or is it a service? Or they get the box as part of a service? What's the business model? >> So we do both, so it's a (mumbles) format, as well as an appliance, so the beauty of appliances is that everything is already optimized for you, so that makes it very easy. But if a customer has a chosen hardware platform, and we can definitely deploy it on that also. And adding to the hunter services thing, I think that's a great point, that AWS has so many services now that can you really go and figure out which services are most optimized for your needs? So that's where you need a partner on prem-site, and that's what we are going to be, and another thing as Sudhir mentioned, the EKS which they announced today, Kubernetes, so you have Kubernetes on-prem, AWS is supporting Kubernetes, and we are also supporting Kubernetes, so if you want closer to that level, it's completely seamless. >> And you were saying before, your target is enterprise has been good, so the appliance delivery model and the simplicity of being able to manage a lot of different services. Clearly being able to manage things at scale is something that enterprisers are crying out for because otherwise I have to, AWS is great, if you wanna hand build everything yourself, it has all of those components that you can assemble like Lego, but if I'm an enterprise, I want to be able to do that at scale. Humans don't scale very well, so I need some technology to help with that. So it sounds like you are actually providing the leverage to get enterprise humans to be able to manage AWS. Is that a fair characterization? >> Absolutely, that is definitely a very important aspect of it, and another aspect of it is that if you do not want to have some workloads on AWS for one thing or another. IOT workloads by definition cannot be on AWS. Low intensive workloads. They cannot be on AWS. In the same way the workloads in which you need some actual level of security. So within your data center, as much as beat down the data center piece, you have your own security and governance. And you can do that, and that's coming back to your question that are we going to support all hundred services, yes, but the local execution we have only going to provide for some services, which by their very nature make more sense to learn on-prem. >> Yeah, keep the core services. >> Rishi: Core services. >> All right so how do you guys gonna sell this product, take us through the start-up situation, you're here, are you talking to customers? Why are they are buy you? What's the conversations like? When do they need you? Take us through your conversations here at re:Invent. >> Yeah, so before that, the AWS has been super successful for the green field applications. The new applications, the applications which are born in the cloud, but when it comes to transforming the existing application it becomes a big, big challenge. So a lot of customers are coming to us, they are interested in how I can seamlessly transform their-- >> John: What's an example workload? >> So the example workloads for us is going to be the big data workloads. Which we have specialized in for last so many years. So one of them can IOT. Sudhir, probably you can explain what that is. >> So that example could be for example from today's keynote, if you see Expedia case, or Lexi Goldman Sachs case, they spend a lot of time in converting their code to the AWS specific-word, right? Millions of lines, or billions of lines of code. What we are doing today, if you dealing with the application, tomorrow it could be future ready for AWS. It's more convenience, we are actually modeling your experience with AWS. >> So it's making for enterprisers to make that transition from what they're doing today across the cloud, because that's a big deal for them. >> Tomorrow when you are Lexi, then you go to AWS, your data will decide whether you want to earn your workload on our plans, or AWS. >> Okay, so your market is hybrid cloud, basically. People doing hybrid cloud should talk to you guys. >> Yeah, and code would be future proof. What you you are you developing today-- >> John: All right so is the product shipping? >> Yes, so we are in the early beta stage, we already have five beta customers. And the product is going to be ready in a week's time. >> So data now. >> Yeah, yes. >> Yeah, these guys are ready already. >> Open beta, restricted beta? >> It is going to be restricted beta for now. Then it's going to be open beta, so yes, we are going to five more customers in the next two months for the beta. >> Take a minute to explain the type of customer you're looking for. Are they all field spots, any more, you have five more spots, you said? >> Yeah, we have five more spots for the beta. >> John: Who are yo looking for out there? >> Any large enterprise which is planning to move to AWS, but are struggling with all the nitty gritties, looking at the hundred services, and how do you integrate your existing applications there. So how you could take baby steps, like so we are going to not just take that baby steps, but sprint through it, so that's what Zettabytes plans is for. >> Rishi, congratulations on the new start-up, launching here, Zettabytes, open beta, five more spots left. Check 'em out, Zettabytes, if you're doing hybrid cloud or true private cloud, they have five spots available. It's The Cube, bringing all the action, the start-up action here and also the conversations at re:Invent. I'm John Furrier, Justin Warren. We're back with more after this short break. (electronic jingle)

>> And it'll be the fastest 15 minutes of your day from there. >> In three- >> We go Lisa. >> Wait. >> Yes >> Wait, wait, wait. I'm sorry I didn't pin the right speed. >> Yap, no, no rush. >> There we go. >> The beauty of not being live. >> I think, in the background. >> Fantastic, you all ready to go there, Lisa? >> Yeah. >> We are speeding around the horn and we are coming to you in five, four, three, two. >> Hey everyone, welcome to theCUBE's coverage of AWS re:Invent 2022. Lisa Martin here with you with Subbu Iyer one of our alumni who's now the CEO of Aerospike. Subbu, great to have you on the program. Thank you for joining us. >> Great as always to be on theCUBE Lisa, good to meet you. >> So, you know, every company these days has got to be a data company, whether it's a retailer, a manufacturer, a grocer, a automotive company. But for a lot of companies, data is underutilized yet a huge asset that is value added. Why do you think companies are struggling so much to make data a value added asset? >> Well, you know, we see this across the board. When I talk to customers and prospects there is a desire from the business and from IT actually to leverage data to really fuel newer applications, newer services newer business lines if you will, for companies. I think the struggle is one, I think one the, the plethora of data that is created. Surveys say that over the next three years data is going to be you know by 2025 around 175 zettabytes, right? A hundred and zettabytes of data is going to be created. And that's really a growth of north of 30% year over year. But the more important and the interesting thing is the real time component of that data is actually growing at, you know 35% CAGR. And what enterprises desire is decisions that are made in real time or near real time. And a lot of the challenges that do exist today is that either the infrastructure that enterprises have in place was never built to actually manipulate data in real time. The second is really the ability to actually put something in place which can handle spikes yet be cost efficient to fuel. So you can build for really peak loads, but then it's very expensive to operate that particular service at normal loads. So how do you build something which actually works for you for both users, so to speak. And the last point that we see out there is even if you're able to, you know bring all that data you don't have the processing capability to run through that data. So as a result, most enterprises struggle with one capturing the data, making decisions from it in real time and really operating it at the cost point that they need to operate it at. >> You know, you bring up a great point with respect to real time data access. And I think one of the things that we've learned the last couple of years is that access to real time data it's not a nice to have anymore. It's business critical for organizations in any industry. Talk about that as one of the challenges that organizations are facing. >> Yeah, when we started Aerospike, right? When the company started, it started with the premise that data is going to grow, number one exponentially. Two, when applications open up to the internet there's going to be a flood of users and demands on those applications. And that was true primarily when we started the company in the ad tech vertical. So ad tech was the first vertical where there was a lot of data both on the supply set and the demand side from an inventory of ads that were available. And on the other hand, they had like microseconds or milliseconds in which they could make a decision on which ad to put in front of you and I so that we would click or engage with that particular ad. But over the last three to five years what we've seen is as digitization has actually permeated every industry out there the need to harness data in real time is pretty much present in every industry. Whether that's retail, whether that's financial services telecommunications, e-commerce, gaming and entertainment. Every industry has a desire. One, the innovative companies, the small companies rather are innovating at a pace and standing up new businesses to compete with the larger companies in each of these verticals. And the larger companies don't want to be left behind. So they're standing up their own competing services or getting into new lines of business that really harness and are driven by real time data. So this compelling pressures, one, you know customer experience is paramount and we as customers expect answers in you know an instant, in real time. And on the other hand, the way they make decisions is based on a large data set because you know larger data sets actually propel better decisions. So there's competing pressures here which essentially drive the need one from a business perspective, two from a customer perspective to harness all of this data in real time. So that's what's driving an incessant need to actually make decisions in real or near real time. >> You know, I think one of the things that's been in short supply over the last couple of years is patience. We do expect as consumers whether we're in our business lives our personal lives that we're going to be getting be given information and data that's relevant it's personal to help us make those real time decisions. So having access to real time data is really business critical for organizations across any industries. Talk about some of the main capabilities that modern data applications and data platforms need to have. What are some of the key capabilities of a modern data platform that need to be delivered to meet demanding customer expectations? >> So, you know, going back to your initial question Lisa around why is data really a high value but underutilized or under-leveraged asset? One of the reasons we see is a lot of the data platforms that, you know, some of these applications were built on have been then around for a decade plus. And they were never built for the needs of today, which is really driving a lot of data and driving insight in real time from a lot of data. So there are four major capabilities that we see that are essential ingredients of any modern data platform. One is really the ability to, you know, operate at unlimited scale. So what we mean by that is really the ability to scale from gigabytes to even petabytes without any degradation in performance or latency or throughput. The second is really, you know, predictable performance. So can you actually deliver predictable performance as your data size grows or your throughput grows or your concurrent user on that application of service grows? It's really easy to build an application that operates at low scale or low throughput or low concurrency but performance usually starts degrading as you start scaling one of these attributes. The third thing is the ability to operate and always on globally resilient application. And that requires a really robust data platform that can be up on a five nine basis globally, can support global distribution because a lot of these applications have global users. And the last point is, goes back to my first answer which is, can you operate all of this at a cost point which is not prohibitive but it makes sense from a TCO perspective. 'Cause a lot of times what we see is people make choices of data platforms and as ironically their service or applications become more successful and more users join their journey the revenue starts going up, the user base starts going up but the cost basis starts crossing over the revenue and they're losing money on the service, ironically as the service becomes more popular. So really unlimited scale predictable performance always on a globally resilient basis and low TCO. These are the four essential capabilities of any modern data platform. >> So then talk to me with those as the four main core functionalities of a modern data platform, how does Aerospike deliver that? >> So we were built, as I said from day one to operate at unlimited scale and deliver predictable performance. And then over the years as we work with customers we build this incredible high availability capability which helps us deliver the always on, you know, operations. So we have customers who are who have been on the platform 10 years with no downtime for example, right? So we are talking about an amazing continuum of high availability that we provide for customers who operate these, you know globally resilient services. The key to our innovation here is what we call the hybrid memory architecture. So, you know, going a little bit technically deep here essentially what we built out in our architecture is the ability on each node or each server to treat a bank of SSDs or solid-state devices as essentially extended memory. So you're getting memory performance but you're accessing these SSDs. You're not paying memory prices but you're getting memory performance. As a result of that you can attach a lot more data to each node or each server in a distributed cluster. And when you kind of scale that across basically a distributed cluster you can do with Aerospike the same things at 60 to 80% lower server count. And as a result 60 to 80% lower TCO compared to some of the other options that are available in the market. Then basically, as I said that's the key kind of starting point to the innovation. We lay around capabilities like, you know replication, change data notification, you know synchronous and asynchronous replication. The ability to actually stretch a single cluster across multiple regions. So for example, if you're operating a global service you can have a single Aerospike cluster with one node in San Francisco one node in New York, another one in London and this would be basically seamlessly operating. So that, you know, this is strongly consistent, very few no SQL data platforms are strongly consistent or if they are strongly consistent they will actually suffer performance degradation. And what strongly consistent means is, you know all your data is always available it's guaranteed to be available there is no data lost any time. So in this configuration that I talked about if the node in London goes down your application still continues to operate, right? Your users see no kind of downtime and you know, when London comes up it rejoins the cluster and everything is back to kind of the way it was before, you know London left the cluster so to speak. So the ability to do this globally resilient highly available kind of model is really, really powerful. A lot of our customers actually use that kind of a scenario and we offer other deployment scenarios from a higher availability perspective. So everything starts with HMA or Hybrid Memory Architecture and then we start building a lot of these other capabilities around the platform. And then over the years what our customers have guided us to do is as they're putting together a modern kind of data infrastructure, we don't live in the silo. So Aerospike gets deployed with other technologies like streaming technologies or analytics technologies. So we built connectors into Kafka, Pulsar, so that as you're ingesting data from a variety of data sources you can ingest them at very high ingest speeds and store them persistently into Aerospike. Once the data is in Aerospike you can actually run Spark jobs across that data in a multi-threaded parallel fashion to get really insight from that data at really high throughput and high speed. >> High throughput, high speed, incredibly important especially as today's landscape is increasingly distributed. Data centers, multiple public clouds, Edge, IoT devices, the workforce embracing more and more hybrid these days. How are you helping customers to extract more value from data while also lowering costs? Go into some customer examples 'cause I know you have some great ones. >> Yeah, you know, I think, we have built an amazing set of customers and customers actually use us for some really mission critical applications. So, you know, before I get into specific customer examples let me talk to you about some of kind of the use cases which we see out there. We see a lot of Aerospike being used in fraud detection. We see us being used in recommendations engines we get used in customer data profiles, or customer profiles, Customer 360 stores, you know multiplayer gaming and entertainment. These are kind of the repeated use case, digital payments. We power most of the digital payment systems across the globe. Specific example from a specific example perspective the first one I would love to talk about is PayPal. So if you use PayPal today, then you know when you're actually paying somebody your transaction is, you know being sent through Aerospike to really decide whether this is a fraudulent transaction or not. And when you do that, you know, you and I as a customer are not going to wait around for 10 seconds for PayPal to say yay or nay. We expect, you know, the decision to be made in an instant. So we are powering that fraud detection engine at PayPal. For every transaction that goes through PayPal. Before us, you know, PayPal was missing out on about 2% of their SLAs which was essentially millions of dollars which they were losing because, you know, they were letting transactions go through and taking the risk that it's not a fraudulent transaction. With Aerospike they can now actually get a much better SLA and the data set on which they compute the fraud score has gone up by you know, several factors. So by 30X if you will. So not only has the data size that is powering the fraud engine actually gone up 30X with Aerospike but they're actually making decisions in an instant for, you know, 99.95% of their transactions. So that's- >> And that's what we expect as consumers, right? We want to know that there's fraud detection on the swipe regardless of who we're interacting with. >> Yes, and so that's a really powerful use case and you know, it's a great customer success story. The other one I would talk about is really Wayfair, right, from retail and you know from e-commerce. So everybody knows Wayfair global leader in really in online home furnishings and they use us to power their recommendations engine. And you know it's basically if you're purchasing this, people who bought this also bought these five other things, so on and so forth. They have actually seen their cart size at checkout go up by up to 30%, as a result of actually powering their recommendations engine through Aerospike. And they were able to do this by reducing the server count by 9X. So on one ninth of the servers that were there before Aerospike, they're now powering their recommendations engine and seeing cart size checkout go up by 30%. Really, really powerful in terms of the business outcome and what we are able to, you know, drive at Wayfair. >> Hugely powerful as a business outcome. And that's also what the consumer wants. The consumer is expecting these days to have a very personalized relevant experience that's going to show me if I bought this show me something else that's related to that. We have this expectation that needs to be really fueled by technology. >> Exactly, and you know, another great example you asked about you know, customer stories, Adobe. Who doesn't know Adobe, you know. They're on a mission to deliver the best customer experience that they can. And they're talking about, you know great Customer 360 experience at scale and they're modernizing their entire edge compute infrastructure to support this with Aerospike. Going to Aerospike basically what they have seen is their throughput go up by 70%, their cost has been reduced by 3X. So essentially doing it at one third of the cost while their annual data growth continues at, you know about north of 30%. So not only is their data growing they're able to actually reduce their cost to actually deliver this great customer experience by one third to one third and continue to deliver great Customer 360 experience at scale. Really, really powerful example of how you deliver Customer 360 in a world which is dynamic and you know on a data set which is constantly growing at north of 30% in this case. >> Those are three great examples, PayPal, Wayfair, Adobe, talking about, especially with Wayfair when you talk about increasing their cart checkout sizes but also with Adobe increasing throughput by over 70%. I'm looking at my notes here. While data is growing at 32%, that's something that every organization has to contend with data growth is continuing to scale and scale and scale. >> Yap, I'll give you a fun one here. So, you know, you may not have heard about this company it's called Dream11 and it's a company based out of India but it's a very, you know, it's a fun story because it's the world's largest fantasy sports platform. And you know, India is a nation which is cricket crazy. So you know, when they have their premier league going on and there's millions of users logged onto the Dream11 platform building their fantasy league teams and you know, playing on that particular platform, it has a hundred million users a hundred million plus users on the platform, 5.5 million concurrent users and they have been growing at 30%. So they are considered an amazing success story in terms of what they have accomplished and the way they have architected their platform to operate at scale. And all of that is really powered by Aerospike. Think about that they're able to deliver all of this and support a hundred million users 5.5 million concurrent users all with, you know 99 plus percent of their transactions completing in less than one millisecond. Just incredible success story. Not a brand that is, you know, world renowned but at least you know from what we see out there it's an amazing success story of operating at scale. >> Amazing success story, huge business outcomes. Last question for you as we're almost out of time is talk a little bit about Aerospike AWS the partnership Graviton2 better together. What are you guys doing together there? >> Great partnership. AWS has multiple layers in terms of partnerships. So, you know, we engage with AWS at the executive level. They plan out, really roll out of new instances in partnership with us, making sure that, you know those instance types work well for us. And then we just released support for Aerospike on the Graviton platform and we just announced a benchmark of Aerospike running on Graviton on AWS. And what we see out there is with the benchmark a 1.6X improvement in price performance. And you know about 18% increase in throughput while maintaining a 27% reduction in cost, you know, on Graviton. So this is an amazing story from a price performance perspective, performance per watt for greater energy efficiencies, which basically a lot of our customers are starting to kind of talk to us about leveraging this to further meet their sustainability target. So great story from Aerospike and AWS not just from a partnership perspective on a technology and an executive level, but also in terms of what joint outcomes we are able to deliver for our customers. >> And it sounds like a great sustainability story. I wish we had more time so we would talk about this but thank you so much for talking about the main capabilities of a modern data platform, what's needed, why, and how you guys are delivering that. We appreciate your insights and appreciate your time. >> Thank you very much. I mean, if folks are at re:Invent next week or this week come on and see us at our booth and we are in the data analytics pavilion and you can find us pretty easily. Would love to talk to you. >> Perfect, we'll send them there. Subbu Iyer, thank you so much for joining me on the program today. We appreciate your insights. >> Thank you Lisa. >> I'm Lisa Martin, you're watching theCUBE's coverage of AWS re:Invent 2022. Thanks for watching. >> Clear- >> Clear cutting. >> Nice job, very nice job.

[Music] welcome back to aws storage day 2022 i'm dave vellante and we're pleased to have back on thecube edname the gm of aws file storage ed how you doing good to see you i'm good dave good good to see you as well you know we've been tracking aws storage for a lot of years 16 years actually we we've seen the evolution of services of course we started with s3 and object and saw that expand the block and file and and now the pace is actually accelerating and we're seeing aws make more moves again today and block an object but what about file uh it's one format in the world and the day wouldn't really be complete without talking about file storage so what are you seeing from customers in terms of let's start with data growth how are they dealing with the challenges what are those challenges if you could address you know specifically some of the issues that they're having that would be great and then later we're going to get into the role that cloud file storage plays take it away well dave i'm definitely increasingly hearing customers talk about the challenges in managing ever-growing data sets and they're especially challenged in doing that on-premises when we look at the data that's stored on premises zettabytes of data the fastest growing data sets consist of unstructured data that are stored as files and many cups have tens of petabytes or hundreds of petabytes or even exabytes of file data and this data is typically growing 20 30 percent a year and in reality on-premises models really designed to handle this amount of data in this type of growth and i'm not just talking about keeping up with hardware purchases and hardware floor space but a big part of the challenge is labor and talent to keep up with the growth they're seeing companies managing storage on-prem they really need an unprecedented number of skilled resources to manage the storage and these skill sets are in really high demand and they're in short supply and then another big part of the challenge that customers tell me all the time is that that operating at scale dealing with these ever-growing data sets at scale is really hard and it's not just hard in terms of the the people you need and the skill sets that you need but operating at scale presents net new challenges so for example it becomes increasingly hard to know what data you have and what storage media your data stored on when you have a massive amount of data that's spanning hundreds of thousands or uh thousands of applications and users and it's growing super fast each year and at scale you start seeing edge technical issues get triggered more commonly impacting your availability or your resiliency or your security and you start seeing processes that used to work when you were a much smaller scale no longer work it's just scale is hard it's really hard and then finally companies are wanting to do more with their fast growing data sets to get insights from it and they look at the machine learning and the analytics and the processing services and the compute power that they have at their fingertips on the cloud and having that data be in silos on-prem can really limit how they get the most out of their data you know i've been covering glad you brought up the skills gap i've been covering that quite extensively with my colleagues at etr you know our survey partner so that's a really important topic and we're seeing it across the board i mean really acute in cyber security but for sure just generally in i.t and frankly ceos they don't want to invest in training people to manage storage i mean it wasn't that long ago that managing loans was a was a talent and that's of course nobody does that anymore but they'd executives would much rather apply skills to get value from data so my specific question is what can be done what is aws doing to address this problem well with the growth of data that that we're seeing it it's just it's really hard for a lot of it teams to keep up with just the infrastructure management part that's needed so things like deploying capacity and provisioning resources and patching and conducting compliance reviews and that stuff is just table stakes the asks on these teams to your point are growing to be much bigger than than those pieces so we're really seeing fast uptake of our amazon fsx service because it's such an easy path for helping customers with these scaling challenges fsx enables customers to launch and to run and to scale feature rich and highly performant network attached file systems on aws and it provides fully managed file storage which means that we handle all of the infrastructure so all of that provisioning and that patching and ensuring high availability and customers simply make api calls to do things like scale up their storage or change their performance level at any point or change a backup policy and a big part of why fsx has been so feeling able to customers is it really enables them to to choose the file system technology that powers their storage so we provide four of the most popular file system technologies we provide windows file server netapp ontap open zfs and luster so that storage and application admins can use what they're familiar with so they essentially get the full capabilities and even the management clis that they're used to and that they've built workflows and applications around on-premises but they get along with that of course the benefits of fully managed elastic cloud storage that can be spin up and spun spin down and scaled on demand and performance changed on demand etc and what storage and application admins are seeing is that fsx not only helps them keep up with their scale and growth but it gives them the bandwidth to do more of what they want to do supporting strategic decision making helping their end customers figure out how they can get more value from their data identifying opportunities to reduce cost and what we realize is that for for a number of storage and application admins the cloud is is a different environment from what they're used to and we're making it a priority to help educate and train folks on cloud storage earlier today we talked about aws storage digital badges and we announced a dedicated file badge that helps storage admins and professionals to learn and demonstrate their aws skills in our aws storage badges you can think of them as credentials that represent cloud computing learning that customers can add to their repertoire add to their resume as they're embarking on this cloud journey and we'll be talking more in depth on this later today especially around the file badge which i'm very excited about so a couple things there that i wanted to comment on i mean i was there for the netapp you know your announcement we've covered that quite extensively this is just shows that it's not a zero-sum game necessarily right it's a win-win-win for customers you've got your you know specific aws services you've got partner services you know customers want want choice and then the managed service model you know to me is a no-brainer for most customers we learned this in the hadoop years i mean it just got so complicated then you saw what happened with the managed services around you know data lakes and lake houses it's just really simplified things for customers i mean there's still some customers that want to do it yourself but a managed service for the file storage sounds like a really easy decision especially for those it teams that are overburdened as we were talking about before and i also like you know the education component is nice touch too you get the badge thing so that's kind of cool so i'm hearing that if the fully managed file storage service is a catalyst for cloud adoption so the question is which workloads should people choose to move into the cloud where's the low friction low risk sweet spot ed well that's one of the first questions that customers ask when they're about to embark on their cloud journey and i wish i could give a simple or a single answer but the answer is really it varies and it varies per customer and i'll give you an example for some customers the cloud journey begins with what we call extending on-premises workloads into the cloud so an example of that is compute bursting workloads where customers have data on premises and they have some compute on premises but they want to burst their processing of that data to the cloud because they really want to take advantage of the massive amount of compute that they get on aws and that's common with workloads like visual effects ringer chip design simulation genomics analysis and so that's an example of extending to the cloud really leveraging the cloud first for your workloads another example is disaster recovery and that's a really common example customers will use a cloud for their secondary or their failover site rather than maintaining their their second on-prem location and so that's a lot of customers start with some of those workloads by extending to the cloud and then there's there's a lot of other customers where they've made the decision to migrate most or all of their workloads and they're not they're skipping the whole extending step they aren't starting there they're instead focused on going all in as fast as possible because they really want to get to the full benefits of the cloud as fast as possible and for them the migration journey is really it's a matter of sequencing sequencing which specific workloads to move and when and what's interesting is we're increasingly seeing customers prioritizing their most important and their most mission-critical applications ahead of their other workloads in terms of timing and they're they're doing that to get their workloads to benefit from the added resilience they get from running on the cloud so really it really does uh depend dave yeah thank you i mean that's pretty pretty good description of the options there and i i just come something you know bursting obviously i love those examples you gave around genomics chip design visual effects rendering the dr piece is again very common sort of cloud you know historical you know sweet spots for cloud but then the point about mission critical is interesting because i hear a lot of customers especially with the digital transformation push wanting to change their operating model i mean on the one hand not changing things put it in the cloud the lift and shift you have to change things low friction but then once they get there they're like wow we can do a lot more with the cloud so that was really helpful those those examples now last year at storage day you released a new file service and then you followed that up at re-event with another file service introduction sometimes i can admit i get lost in the array of services so help us understand when a customer comes to aws with like an nfs or an smb workload how do you steer them to the right managed service you know the right horse for the right course yeah well i'll start by saying uh you know a big part of our focus has been in providing choice to customers and what customers tell us is that the spectrum of options that we provide to them really helps them in their cloud journey because there really isn't a one-size-fits-all file system for all workloads and so having these options actually really helps them to to be able to move pretty easily to the cloud um and so my answer to your question about uh where do we steer a customer when they have a file workload is um it really depends on what the customer is trying to do and uh in many cases where they're coming from so i'll walk you through a little bit of of of how we think about this with customers so for storage and application admins who are extending existing workloads to the cloud or migrating workloads to aws the easiest path generally is to move to an fsx file system that provides the same or really similar underlying file system engine that they use on premises so for example if you're running a netapp appliance on premises or a windows file server on premises choosing that option within fsx provides the least effort for a customer to lift their application and their data set and they'll get the full safe set of capabilities that they're used to they'll get the performance profiles that they're used to but of course they'll get all the benefits of the cloud that i was talking about earlier like spin up and spin down and fully managed and elastic capacity then we also provide open source file systems within the fsx family so if you're a customer and you're used to those or if you aren't really wedded to a particular file system technology these are really good options and they're built on top of aws's latest infrastructure innovations which really allows them to provide pretty significant price and performance benefits to customers so for example the file system file servers for these offerings are powered by aws's graviton family of processors and under the hood we use storage technology that's built on top of aws's scalable reliable datagram transport protocol which really optimizes for for speed on the cloud and so for those two open source file systems we have open zfs and that provides a really powerful highly performant nfs v3 and v4 and 4.1 and 4.2 file system built on a fast and resilient open source linux file system it has a pretty rich set of capabilities it has things like point-to-time snapshots and in-place data cloning and our customers are really using it because of these capabilities and because of its performance for a pretty broad set of enterprise i.t workloads and vertically focused workloads like within the financial services space and the healthcare life sciences space and then luster is a scale-out file system that's built on the world's most popular high-performance file system which is the luster open source file system and customers are using it for compute intensive workloads where they're throwing tons of compute at massive data sets and they need to drive tens or hundreds of gigabytes per second of throughput it's really popular for things like machine learning training and high performance computing big data analytics video rendering and transcoding so really those scale out compute intensive workloads and then we have a very different type of customer very different persona and this is the individual that we call the aws builder and these are folks who are running cloud native workloads they leverage a broad spectrum of aws's compute and analytic services and they have really no history of on-prem examples are data scientists who require a file share for training sets research scientists who are performing analysis on lab data developers who are building containerized or serverless workloads and cloud practitioners who need a simple solution for storing assets for their cloud workflows and and these these folks are building and running a wide range of data focused workloads and they've grown up using services like lambda and building containerized workloads so most of these individuals generally are not storage experts and they look for storage that just works s3 and consumer file shares uh like dropbox are their reference point for how cloud storage works and they're indifferent to or unaware of bio protocols like smb or nfs and performing typical nas administrative tasks is just not it's not a natural experience for them it's not something they they do and we built amazon efs to meet the needs of that group it's fully elastic it's fully serverless spreads data across multiple availability zones by default it scales infinitely it works very much like s3 so for example you get the same durability and availability profile of s3 you get intelligent tiering of colder data just like you do on s3 so that service just clicks with cloud native practitioners it's it's intuitive and it just works there's mind-boggling the number of use cases you just went through and this is where it's so you know it's you know a lot of times people roll their eyes oh here's amazon talking about you know customer obsession again but if you don't stay close to your customers there's no way you could have predicted when you're building these services how they were going to be put to use the only way you can understand it is watch what customers do with it i loved the conversation about graviton we've written about that a lot i mean nitro we've written about that how it's you've completely rethought virtualization the security components in there the hpc luster piece and and the efs for data scientists so really helpful there thank you i'm going to change uh topics a little bit because there's been this theme that you've been banging on at storage day putting data to work and i tell you it's a bit of a passion of mine ed because frankly customers have been frustrated with the return on data initiatives it's been historically complicated very time consuming and expensive to really get value from data and often the business lines end up frustrated so let's talk more about that concept and i understand you have an announcement that fits with this scene can you tell us more about that absolutely today we're announcing a new service called amazon file cache and it's a service on aws that accelerates and simplifies hybrid workflows and specifically amazon file cache provides a high speed cache on aws that makes it easier to process file data regardless of where the data is stored and amazon file cache serves as a temporary high performance storage location and it's for data that's stored in on-premise file servers or in file systems or object stores in aws and what it does is it enables enterprises to make these dispersed data sets available to file based applications on aws with a unified view and at high speeds so think of sub millisecond latencies and and tens or hundreds of gigabytes per second of throughput and so a really common use case it supports is if you have data stored on premises and you want to burst the processing workload to the cloud you can set up this cache on aws and it allows you to have the working set for your compute workload be cached near your aws compute so what you would do as a customer when you want to use this is you spin up this cache you link it to one or more on-prem nfs file servers and then you mount this cache to your compute instances on aws and when you do this all of your on-prem data will appear up automatically as folders and files on the cache and when your aws compute instances access a file for the first time the cache downloads the data that makes up that file in real time and that data then would reside on the cache as you work with it and when it's in the cache your application has access to that data at those sub millisecond latencies and at up to hundreds of gigabytes per second of throughput and all of this data movement is done automatically and in the background completely transparent to your application that's running on the compute instances and then when you're done with your workload with your data processing job you can export the changes and all the new data back to your on-premises file servers and then tear down the cache another common use case is if you have a compute intensive file-based application and you want to process a data set that's in one or more s3 buckets you can have this cache serve as a really high speed layer that your compute instances mount as a network file system you can also place this cache in front of a mix of on-prem file servers and s3 buckets and even fsx file systems that are on aws all of the data from these locations will appear within a single name space that clients that mount the cache have access to and those clients get all the performance benefits of the cache and also get a unified view of their data sets and and to your point about listening to customers and really paying attention to customers dave we built this service because customers asked us to a lot of customers asked us to actually it's a really helpful enable enabler for a pretty wide variety of cloud bursting workloads and hybrid workflows ranging from media rendering and transcoding to engineering design simulation to big data analytics and it really aligns with that theme of extend that we were talking about earlier you know i often joke that uh aws has the best people working on solving the speed of light problem so okay but so this idea of bursting as i said has been a great cloud use case from the early days and and bringing it to file storage is very sound and approach with file cache looks really practical um when is the service available how can i get started you know bursting to aws give us the details there yeah well stay tuned we we announced it today at storage day and it will be generally available later this year and once it becomes available you can create a cache via the the aws management console or through the sdks or the cli and then within minutes of creating the cache it'll be available to your linux instances and your instances will be able to access it using standard file system mount commands and the pricing model is going to be a pretty familiar one to cloud customers customers will only pay for the cash storage and the performance they need and they can spin a cash up and use it for the duration of their compute burst workload and then tear it down so i'm really excited that amazon file cache will make it easier for customers to leverage the agility and the performance and the cost efficiency of aws for processing data no matter where the data is stored yeah cool really interested to see how that gets adopted ed always great to catch up with you as i said the pace is mind-boggling it's accelerating in the cloud overall but storage specifically so by asking us can we take a little breather here can we just relax for a bit and chill out uh not as long as customers are asking us for more things so there's there's more to come for sure all right ed thanks again great to see you i really appreciate your time thanks dave great catching up okay and thanks for watching our coverage of aws storage day 2022 keep it right there for more in-depth conversations on thecube your leader in enterprise and emerging tech coverage [Music] you

>> The rapid rise of ransomware attacks has added yet another challenge that business technology executives have to worry about these days. Cloud storage, immutability and air gaps have become a must have arrows in the quiver of organization's data protection strategies. But the important reality that practitioners have embraced is data protection, it can't be an afterthought or a bolt on, it has to be designed into the operational workflow of technology systems. The problem is oftentimes data protection is complicated with a variety of different products, services, software components, and storage formats. This is why object storage is moving to the forefront of data protection use cases because it's simpler and less expensive. The put data get data syntax has always been alluring but object storage historically was seen as this low cost niche solution that couldn't offer the performance required for demanding workloads, forcing customers to make hard trade offs between cost and performance. That has changed. The ascendancy of cloud storage generally in the S3 format specifically has catapulted object storage to become a first class citizen in a mainstream technology. Moreover, innovative companies have invested to bring object storage performance to parody with other storage formats. But cloud costs are often a barrier for many companies as the monthly cloud bill and egress fees in particular steadily climb. Welcome to Secure Storage Hot Takes. My name is Dave Vellante and I'll be your host of the program today, where we introduce our community to Wasabi, a company that is purpose built to solve this specific problem with what it claims to be the most cost effective and secure solution on the market. We have three segments today to dig into these issues. First up is David Friend, the well known entrepreneur, who co-founded Carbonite and now Wasabi. We'll then dig into the product with Drew Schlussel of Wasabi. And then we'll bring in the customer perspective with Kevin Warenda of the Hotchkiss, cool. Let's get right into it. We're here with David Friend, the President and CEO, and co-founder of Wasabi, the hot storage company. David, welcome to theCUBE. >> Thanks, Dave. Nice to be here. >> Great to have you. So look, you hit a home run with Carbonite back when building a unicorn was a lot more rare than it has been in the last few years. Why did you start Wasabi? >> Well, when I was still CEO of Wasabi, my genius co-founder, Jeff Flowers, and our chief architect came to me and said, you know, when we started this company, a state of the art disc drive was probably 500 gigabytes. And now we're looking at eight terabyte, 16 terabyte, 20 terabyte, even hundred terabyte drives coming down the road. And, you know, sooner or later the old architectures that were designed around these much smaller disc drives is going to run out of steam, because even though the capacities are getting bigger and bigger, the speed with which you can get data on and off of a hard drive isn't really changing all that much. And Jeff foresaw a day when the architectures of sort of legacy storage like Amazon S3 and so forth, was going to become very inefficient and slow. And so he came up with a new highly parallelized architecture, and he said, I want to go off and see if I can make this work. So I said, you know, good luck go to it. And they went off and spent about a year and a half in the lab designing and testing this new storage architecture. And when they got it working, I looked at the economics of this and I said, holy cow, we could sell cloud storage for a fraction of the price of Amazon, still make very good gross margins and it will be faster. So this is a whole new generation of object storage that you guys have invented. So I recruited a new CEO for Carbonite and left to found Wasabi because the market for cloud storage is almost infinite, you know? When you look at all the world's data, you know, IDC has these crazy numbers, 120 zettabytes or something like that. And if you look at that as, you know, the potential market size during that data we're talking trillions of dollars, not billions. And so I said, look, this is a great opportunity. If you look back 10 years, all the world's data was on prem. If you look forward 10 years, most people agree that most of the world's data is going to live in the cloud. We're at the beginning of this migration, we've got an opportunity here to build an enormous company. >> That's very exciting. I mean, you've always been a trend spotter and I want to get your perspectives on data protection and how it's changed. It's obviously on people's minds with all the ransomware attacks and security breaches but thinking about your experiences and past observations, what's changed in data protection and what's driving the current very high interest in the topic? >> Well, I think, you know, from a data protection standpoint, immutability, the equivalent of the old worm tapes but applied to cloud storage is, you know, become core to the backup strategies and disaster recovery strategies for most companies. And if you look at our partners who make backup software like VEEAM, Commvault, Veritas, Arcserve, and so forth, most of them are really taking advantage of mutable cloud storage as a way to protect customer data, customers backups from ransomware. So the ransomware guys are pretty clever and they, you know, they discovered early on that if someone could do a full restore from their backups they're never going to pay a ransom. So once they penetrate your system, they get pretty good at sort of watching how you do your backups and before they encrypt your primary data, they figure out some way to destroy or encrypt your backups as well so that you can't do a full restore from your backups, and that's where immutability comes in. You know, in the old days you wrote what was called a worm tape, you know? Write once read many. And those could not be overwritten or modified once they were written. And so we said, let's come up with an equivalent of that for the cloud. And it's very tricky software, you know, it involves all kinds of encryption algorithms and blockchain and this kind of stuff. But, you know, the net result is, if you store your backups in immutable buckets in a product like Wasabi, you can't alter it or delete it for some period of time. So you could put a timer on it, say a year or six months or something like that. Once that date is written, you know, there's no way you can go in and change it, modify it or anything like that, including even Wasabi's engineers. >> So, David, I want to ask you about data sovereignty, it's obviously a big deal. I mean, especially for companies with a presence overseas but what's really is any digital business these days? How should companies think about approaching data sovereignty? Is it just large firms that should be worried about this? Or should everybody be concerned? What's your point of view? >> Well, all around the world countries are imposing data sovereignty laws. And if you're in the storage business, like we are, if you don't have physical data storage in country you're probably not going to get most of the business. You know, since Christmas we've built data centers in Toronto, London, Frankfurt, Paris, Sydney, Singapore and I've probably forgotten one or two. But the reason we do that is twofold. One is, you know, if you're closer to the customer, you're going to get better response time, lower latency and that's just a speed of light issue. But the bigger issue is, if you've got financial data, if you have healthcare data, if you have data relating to security, like surveillance videos and things of that sort, most countries are saying that data has to be stored in country, so you can't send it across borders to some other place. And if your business operates in multiple countries, you know, dealing with data sovereignty is going to become an increasingly important problem. >> So in may of 2018, that's when the fines associated with violating GDPR went into effect and GDPR was like this main spring of privacy and data protection laws. And we've seen it spawn other public policy things like the CCPA and it continues to evolve. We see judgements in Europe against big tech and this tech lash that's in the news in the US and the elimination of third party cookies. What does this all mean for data protection in the 2020s? >> Well, you know, every region and every country, you know, has their own idea about privacy, about security, about the use of, even the use of metadata surrounding, you know, customer data and things to this sort. So, you know, it's getting to be increasingly complicated because GDPR, for example, imposes different standards from the kind of privacy standards that we have here in the US. Canada has a somewhat different set of data sovereignty issues and privacy issues. So it's getting to be an increasingly complex, you know, mosaic of rules and regulations around the world. And this makes it even more difficult for enterprises to run their own, you know, infrastructure because companies like Wasabi where we have physical data centers in all kinds of different markets around the world. And we've already dealt with the business of how to meet the requirements of GDPR and how to meet the requirements of some of the countries in Asia, and so forth. You know, rather than an enterprise doing that just for themselves, if you running your applications or keeping your data in the cloud, you know, now a company like Wasabi with, you know, 34,000 customers, we can go to all the trouble of meeting these local requirements on behalf of our entire customer base. And that's a lot more efficient and a lot more cost effective than if each individual country has to go deal with the local regulatory authorities. >> Yeah. It's compliance by design, not by chance. Okay, let's zoom out for the final question, David. Thinking about the discussion that we've had around ransomware and data protection and regulations. What does it mean for a business's operational strategy and how do you think organizations will need to adapt in the coming years? >> Well, you know, I think there are a lot of forces driving companies to the cloud and, you know, and I do believe that if you come back five or 10 years from now, you're going to see majority of the world's data is going to be living in the cloud. And I think, storage, data storage is going to be a commodity much like electricity or bandwidth. And it's going to be done right, it will comply with the local regulations, it'll be fast, it'll be local. And there will be no strategic advantage that I can think of for somebody to stand up and run their own storage, especially considering the cost differential. You know, the most analysts think that the full all in costs of running your own storage is in the 20 to 40 terabytes per month range. Whereas, you know, if you migrate your data to the cloud like Wasabi, you're talking probably $6 a month. And so I think people are learning how to, are learning how to deal with the idea of an architecture that involves storing your data in the cloud, as opposed to, you know, storing your data locally. >> Wow. That's like a six X more expensive and the clouds more than six X. >> Yeah. >> All right, thank you, David. Go ahead, please. >> In addition to which, you know, just finding the people to babysit this kind of equipment has become nearly impossible today. >> Well, and with a focus on digital business you don't want to be wasting your time with that kind of heavy lifting. David, thanks so much for coming on theCUBE. Great Boston entrepreneur, we've followed your career for a long time and looking forward to the future. >> Thank you. >> Okay, in a moment, Drew Schlussel will join me and we're going to dig more into product. You're watching theCUBE, the leader in enterprise and emerging tech coverage. Keep it right there. (upbeat music)

(upbeat music) >> Hello everyone, and welcome to this CUBE conversation where we're going to go deep into system performance. We're here with an expert. Kim Leyenaar is the Principal Performance Architect at Broadcom. Kim. Great to see you. Thanks so much for coming on. >> Thanks so much too. >> So you have a deep background in performance, performance assessment, benchmarking, modeling. Tell us a little bit about your background, your role. >> Thanks. So I've been a storage performance engineer and architect for about 22 years. And I'm specifically been for abroad with Broadcom for I think next month is going to be my 14 year mark. So what I do there is initially I built and I manage their international performance team, but about six years ago I moved back into architecture, and what my roles right now are is I generate performance projections for all of our next generation products. And then I also work on marketing material and I interface with a lot of the customers and debugging customer issues, and looking at how our customers are actually using our storage. >> Great. Now we have a graphic that we want to share. It talks to how storage has evolved over the past decade. So my question is what changes have you seen in storage and how has that impacted the way you approach benchmarking. In this graphic we got sort of big four items that impact performance, memory processor, IO pathways, and the storage media itself, but walk us through this data if you would. >> Sure. So what I put together is a little bit of what we've seen over the past 15 to 20 years. So I've been doing this for about 22 years and kind of going back and focusing a little bit on the storage, we looked back at hard disk, they ruled for. And nearly they had almost 50 years of ruling. And our first hard drive that came out back in the 1950s was only capable of five megabytes in capacity. and one and a half iOS per second. It had almost a full second in terms of seat time. So we've come a long way since then. But when I first came on, we were looking at Ultra 320 SCSI. And one of the biggest memories that I have of that was my office is located close to our tech support. And I could hear the first question was always, what's your termination like? And so we had some challenges with SCSI, and then we moved on into SAS and data protocols. And we continued to move on. But right now, back in the early 2000s when I came on board, the best drives really could do maybe 400 iOS per second. Maybe two 250 megabytes per second, with millisecond response times. And so when I was benchmarking way back when it was always like, well, IOPS are IOPS. We were always faster than what the drives to do. And that was just how it was. The drives were always the bottleneck in the system. And so things started changing though by the early 2000s, mid 2000s. We started seeing different technologies come out. We started seeing that virtualization and multi-tenant infrastructures becoming really popular. And then we had cloud computing that was well on the horizon. And so at this point, we're like, well, wait a minute, we really can't make processors that much faster. And so everybody got excited to include (indistinct) and the home came out but, they had two cores per processor and four cores per processor. And so we saw a little time period where actually the processing capability kind of pulled ahead of everybody else. And memory was falling behind. We had good old DVR, 2, 6, 67. It was new with the time, but we only had maybe one or two memory channels per processor. And then in 2007 we saw disk capacity hit one terabyte. And we started seeing a little bit of an imbalance because we were seeing these drives are getting massive, but their performance per drive was not really kind of keeping up. So now we see a revolution around 2010. And my co-worker and I at the time, we have these little USB discs, if you recall, we would put them in. They were so fast. We were joking at the time. "Hey, you know what, wonder if we could make a raid array out of these little USB disks?" They were just so fast. The idea was actually kind of crazy until we started seeing it actually happen. So in 2010 SSD started revolutionizing storage. And the first SSDs that we really worked with these plaint LS-300 and they were amazing because they were so over-provisioned that they had almost the same reader, right performance. But to go from a drive that could do maybe 400 IOS per second to a drive like 40,000 plus iOS per second, really changed our thought process about how our storage controller could actually try and keep up with the rest of the system. So we started falling behind. That was a big challenge for us. And then in 2014, NVMe came around as well. So now we've got these drives, they're 30 terabytes. They can do one and a half million iOS per second, and over 6,000 megabytes per second. But they were expensive. So people start relegating SSDs more towards tiered storage or cash. And as the prices of these drives kind of came down, they became a lot more mainstream. And then the memory channels started picking up. And they started doubling every few years. And we're looking now at DVR 5 4800. And now we're looking at cores that used to go from two to four cores per processor up to 48 with some of the latest different processes that are out there. So our ability to consume the computing and the storage resources, it's astounding, you know, it's like that whole saying, 'build it and they will come.' Because I'm always amazed, I'm like, how are we going to possibly utilize all this memory bandwidth? How are we going to utilize all these cores? But we do. And the trick to this is having just a balanced infrastructure. It's really critical. Because if you have a performance mismatch between your server and your storage, you really lose a lot of productivity and it does impact your revenue. >> So that's such a key point. Pardon, begin that slide up again with the four points. And that last point that you made Kim about balance. And so here you have these, electronic speeds with memory and IO, and then you've got the spinning disc, this mechanical disc. You mentioned that SSD kind of changed the game, but it used to be, when I looked at benchmarks, it was always the D stage bandwidth of the cash out to the spinning disc was always the bottleneck. And, you go back to the days of you it's symmetrics, right? The huge backend disk bandwidth was how they dealt with that. But, and then you had things the oxymoron of the day was high spin speed disks of a high performance disk. Compared to memories. And, so the next chart that we have is show some really amazing performance increases over the years. And so you see these bars on the left-hand side, it looks at historical performance for 4k random IOPS. And on the right-hand side, it's the storage controller performance for sequential bandwidth from 2008 to 2022. That's 22 is that yellow line. It's astounding the increases. I wonder if you could tell us what we're looking at here, when did SSD come in and how did that affect your thinking? (laughs) >> So I remember back in 2007, we were kind of on the precipice of SSDs. We saw it, the writing was on the wall. We had our first three gig SAS and SATA capable HPAs that had come out. And it was a shock because we were like, wow, we're going to really quickly become the bottleneck once this becomes more mainstream. And you're so right though about people work in, building these massive hard drive based back ends in order to handle kind of that tiered architecture that we were seeing that back in the early 2010s kind of when the pricing was just so sky high. And I remember looking at our SAS controllers, our very first one, and that was when I first came in at 2007. We had just launched our first SAS controller. We're so proud of ourselves. And I started going how many IOPS can this thing, even handled? We couldn't even attach enough drives to figure it out. So what we would do is we'd do these little tricks where we would do a five 12 byte read, and we would do it on a 4k boundary, so that it was actually reading sequentially from the disc, but we were handling these discrete IOPS. So we were like, oh, we can do around 35,000. Well, that's just not going to hit it anymore. Bandwidth wise we were doing great. Really our limitation and our bottleneck on bandwidth was always either the host or the backend. So, our controllers are there basically, there were three bottlenecks for our storage controllers. The first one is the bottleneck from the host to the controller. So that is typically a PCIe connection. And then there's another bottleneck on the controller to the disc. And that's really the number of ports that we have. And then the third one is the discs themselves. So in typical storage, that's what we look at. And we say, well, how do we improve this? So some of these are just kind of evolutionary, such as PCIE generations. And we're going to talk a little bit about that, but some of them are really revolutionary, and those are some of the things that we've been doing over the last five or six years to try and make sure that we are no longer the bottleneck. And we can enable these really, really fast drives. >> So can I ask a question? I'm sorry to interrupted but on these blue bars here. So these all spinning disks, I presume, out years they're not. Like when did flash come in to these blue bars? is that..you said 27 you started looking at it, but on these benchmarks, is it all spinning disc? Is it all flash? How should we interpret that? >> No, no. Initially they were actually all hard drives. And the way that we would identify, the max iOS would be by doing very small sequential reads to these hard drives. We just didn't have SSDs at that point. And then somewhere around 2010 is where we.. it was very early in that chart, we were able to start incorporating SSD technology into our benchmarking. And so what you're looking at here is really the max that our controller is capable of. So we would throw as many drives as we could and do what we needed to do in order to just make sure our controller was the bottleneck and what can we expose. >> So the drive then when SSD came in was no longer the bottleneck. So you guys had to sort of invent and rethink sort of how, what your innovation and your technology, because, I mean, these are astounding increases in performance. I mean, I think in the left-hand side, we've built this out pad, you got 170 X increase for the 4k random IOPS, and you've got a 20 X increase for the sequential bandwidth. How were you able to achieve that level of performance over time? >> Well, in terms of the sequential bandwidth, really those come naturally by increases in the PCIe or the SAS generation. So we just make sure we stay out of the way, and we enable that bandwidth. But the IOPS that's where it got really, really tricky. So we had to start thinking about different things. So, first of all, we started optimizing all of our pathways, all of our IO management, we increased the processing capabilities on our IO controllers. We added more on-chip memory. We started putting in IO accelerators, these hardware accelerators. We put in SAS poor kind of enhancements. We even went and improved our driver to make sure that our driver was as thin as possible. So we can make sure that we can enable all the IOPS on systems. But a big thing happening a few couple of generations ago was we started introducing something called tri capable controllers, which means that you could attach NVMe. You could attach SAS or you could attach SATA. So you could have this really amazing deployment of storage infrastructure based around your customized needs and your cost requirements by using one controller. >> Yeah. So anybody who's ever been to a trade show where they were displaying a glass case with a Winchester disc drive, for example, you see it's spinning and its actuators is moving, wow, that's so fast. Well, no. That's like a tourist slower. It's like a snail compared to the system's speed. So it's, in a way life was easy back in those days, because when you did a right to a disk, you had plenty of time to do stuff, right. And now it's changed. And so I want to talk about Gen3 versus Gen4, and how all this relates to what's new in Gen4 and the impacts of PCIe here, you have a chart here that you've shared with us that talks to that. And I wonder if you could elaborate on that, Kim. >> Sure. But first, you said something that kind of hit my funny bone there. And I remember I made a visit once about 15 or 20 years ago to IBM. And this gentleman actually had one of those old ones in his office and he referred to them as disk files. And he never until the day he retired, he'd never stopped calling them disc files. And it's kind of funny to be a part of that history. >> Yeah. DASD. They used to call it. (both laughing) >> SD, DASD. I used to get all kinds of, you know, you don't know what it was like back then, but yeah. But now nowadays we've got it quite easily enabled because back then, we had, SD DASD and all that. And then, ATA and then SCSI, well now we've got PCIe. And what's fabulous about PCIe is that it just has the generations are already planned out. It's incredible. You know, we're looking at right now, Gen3 moving to Gen4, and that's a lot about what we're going to be talking about. And that's what we're trying to test out. What is Gen4 PCIe when to bias? And it really is. It's fantastic. And PCIe came around about 18 years ago and Broadcom is, and we do participate and contribute to the PCIe SIG, which is, who develops the standards for PCIe, but the host in both our host interface in our NVMe desk and utilize the standards. So this is really, really a big deal, really critical for us. But if you take a look here, you can see that in terms of the capabilities of it, it's really is buying us a lot. So most of our drives right now NVMe drives tend to be by four. And a lot of people will connect them. And what that means is four lanes of NVMe and a lot of people that will connect them either at by one or by two kind of depending on what their storage infrastructure will allow. But the majority of them you could buy, or there are so, as you can see right now, we've gone from eight gig transfers per second to 16 gig of transfers per second. What that means is for a by four, we're going from one drive being able to do 4,000 to do an almost 8,000 megabytes per second. And in terms of those 4k IOPS that really evade us, they were really really tough sometimes to squeeze out of these drives, but now we're got 1 million, all we have to 2 million, it's just, it's insane. You know, just the increase in performance. And there's a lot of other standards that are going to be sitting on top of PCIe. So it's not going away anytime soon. We've got to open standards like CXL and things like that, but we also have graphics cards. You've got all of your hosts connections, they're also sitting on PCIe. So it's fantastic. It's backwards, it's orbits compatible, and it really is going to be our future. >> So this is all well and good. And I think I really believe that a lot of times in our industry, the challenges in the plumbing are underappreciated. But let's make it real for the audience because we have all these new workloads coming out, AI, heavily data oriented. So I want to get your thoughts on what types of workloads are going to benefit from Gen4 performance increases. In other words, what does it mean for application performance? You shared a chart that lists some of the key workloads, and I wonder if we could go through those. >> Yeah, yeah. I could have a large list of different workloads that are able to consume large amounts of data, whether or not it's in small or large kind of bytes of data. But as you know right now, and I said earlier, our ability to consume these compute and storage resources is amazing. So you build it and we'll use it. And the world's data we're expected to grow 61% to 175 zettabytes by the year 2025, according to IDC. So that's just a lot of data to manage. It's a lot of data to have, and it's something that's sitting around, but to be useful, you have to actually be able to access it. And that's kind of where we come in. So who is accessing it? What kind of applications? I spend a lot of time trying to understand that. And recently I attended a virtual conference SDC and what I like to do when I attend these conferences is to try to figure out what the buzz words are. What's everybody talking about? Because every year it's a little bit different, but this year was edge, edge everything. And so I kind of put edge on there first in, even you can ask anybody what's edge computing and it's going to mean a lot of different things, but basically it's all the computing outside of the cloud. That's happening typically at the edge of the network. So it tends to encompass a lot of real time processing on those instant data. So in the data is usually coming from either users or different sensors. It's that last mile. It's where we kind of put a lot of our content caching. And, I uncovered some interesting stuff when I was attending this virtual conference and they say only about 25% of all the usable data actually even reach the data center. The rest is ephemeral and it's localized, locally and in real time. So what it does is in the goal of edge computing is to try and reduce the bandwidth costs for these kinds of IOT devices that go over a long distance. But the reality is the growth of real-time applications that require these kinds of local processing are going to drive this technology forward over the coming years. So Dave, your toaster and your dishwasher they're, IOT edge devices probably in the next year, if they're not already. So edge is a really big one and consumes a lot of the data. >> The buzzword does your now is met the metaverse, it's almost like the movie, the matrix is going to come in real time. But the fact is it's all this data, a lot of videos, some of the ones that I would call out here, you mentioned facial recognition, real-time analytics. A lot of the edge is going to be real-time inferencing, applying AI. And these are just a massive, massive data sets that you again, you and of course your customers are enabling. >> When we first came out with our very first Gen3 product, our marketing team actually asked me, "Hey, how can we show users how they can consume this?" So I actually set up a head to environment. I decided I'm going to learn how to do this. I set up this massive environment with Hadoop, and at the time they called big data, the 3V's, I don't know if you remember these big 3Vs, the volume, velocity and variety. Well Dave, did you know, there are now 10 Vs? So besides those three, we got velocity, we got valued, we got variability, validity, vulnerability, volatility, visualization. So I'm thinking we need just to add another beat of that. >> Yeah. (both laughing) Well, that's interesting. You mentioned that, and that sort of came out of the big data world, a dupe world, which was very centralized. You're seeing the cloud is expanding, the world's getting, you know, data is by its very nature decentralized. And so you've got to have the ability to do an analysis in place. A lot of the edge analytics are going to be done in real time. Yes, sure. Some of it's going to go back in the cloud for detailed modeling, but we are the next decade Kim, ain't going to be like the last I often say. (laughing) I'll give you the last word. I mean, how do you see this sort of evolving, who's going to be adopting this stuff. Give us a sort of a timeframe for this kind of rollout in your world. >> In terms of the timeframe. I mean really nobody knows, but we feel like Gen5, that it's coming out next year. It may not be a full rollout, but we're going to start seeing Gen5 devices and Gen5 infrastructure is being built out over the next year. And then follow very, very, very quickly by Gen6. And so what we're seeing though is, we're starting to see these graphics processors, These GPU's, and I'm coming out as well, that are going to be connecting, using PCIe interfaces as well. So being able to access lots and lots and lots of data locally is going to be a really, really big deal and order because worldwide, all of our companies they're using business analytics. Data is money. And the person that actually can improve their operational efficiency, bolster those sales and increase your customer satisfaction. Those are the companies that are going on to win. And those are the companies that are going to be able to effectively store, retrieve and analyze all the data that they're collecting over the years. And that requires an abundance of data. >> Data is money and it's interesting. It kind of all goes back to when Steve jobs decided to put flash inside of an iPhone and the industry exploded, consumer economics kicked in 5G now edge AI, a lot of the things you talked about, GPU's the neural processing unit. It's all going to be coming together in this decade. Very exciting. Kim, thanks so much for sharing this data and your perspectives. I'd love to have you back when you got some new perspectives, new benchmark data. Let's do that. Okay. >> I look forward to it. Thanks so much. >> You're very welcome. And thank you for watching this CUBE conversation. This is Dave Vellante and we'll see you next time. (upbeat music)

(gentle upbeat music) >> Hello, everyone, and welcome to theCUBE's coverage of Commvault Connections 21. My name is Dave Vellante and I'll be hosting the program today. I want to start with a bit of an assessment on the keynotes that we heard this morning, but before I get into that, I want to set the framework for thinking about Commvault as a company. This company has been around for a long time, since the late 1980s, but really came into prominence in the client server era and it has ridden numerous waves, including network backup and recovery, data management, and now cloud data services. It's a company with more than $700 million in revenue and a market value of nearly $3 billion. Since coming on as CEO, Sanjay Mirchandani has embarked on moving the company towards a subscription model, focusing on optionality for on premises, hybrid and cloud workloads. It's launch of metallic and data management as a service are two components that underpin the strategy. At his keynote earlier today, Mirchandani drew on his experience as both a former CIO and current CEO roles to connect with his audience. His major themes hit on data, the value of data, and the imperative to get control of your data. Of course, data protection has become a fundamental component of digital transformations. For years, data protection was an afterthought or a bolt on, but today, organizations are forced to think about their digital stacks in their entirety, which means they have to build resilience into their platforms from the start. Mirchandani said that if we embrace, manage, and properly protect data, it will become the defining disruptive difference for an organization. But he talked about the gap between what the business wants to do and what the technology teams are actually equipped to do and when it comes to data, I couldn't agree more. He called this the business integrity gap and I'll come back to that. He also put out some fun facts and I'll share those here. According to IDC, 64 zettabytes of data was created and replicated in 2020. That's the equivalent of 2 trillion 4K movies. That's a lot of data. Gardner says by 2025, 85% of business will be delivered through SAS applications. Sophos, the security firm, estimates that the average cost of a ransomware attack is approaching nearly $2 million. The security company Proofpoint did a survey and 64% of surveyed CSOs felt that they were at risk of a material cyber attack in the next 12 months. I'm surprised that number was so, so low. I think the other 36% are busy responding to a cyber attack. Coming back to Sanjay's business integrity gap. Here's how I see it. Data by its very nature is distributed, decentralized, and it's becoming more so with hybrid connections, multicloud installations, and edge use cases. This is only going to accelerate in the future. As such, organizations need to rethink their approaches to getting value from data. Instead of building monolithic data architectures and hyper-specialized technical data teams, organizations are beginning to empower lines of business and domain owners to take end-to-end responsibility for data ownership. The underlying technology platform is becoming an operational detail that serves the data owners, where data protection and governance is computationally automated in a federated model. So the policy is centralized, but the implementation of that policy is done by software. This means that data governance, security, privacy, access, and policy are all adjudicated wherever possible by software and our automated, irrespective of physical location. Data silos are not just a technology problem. They're a symptom of flawed organizational constructs, steeped in the notion that highly technical data specialists and centralized teams should be the stewards of the data and serve multiple lines of business simultaneously, without proper business context. Now, this is changing. Data is being used to create a new class of products and services that can be directly or indirectly monetized, or drive other value, for instance, like saving lives. It's about the organizational mission. Now in this sense, data is undergoing a renaissance, where the responsibility for end-to-end data ownership is being distributed and decentralized, where highly specialized technical teams are becoming enablers for generalists that reside within the lines of business, i.e., those who are building data products and services. This is not shadow IT. It's decentralized management with federated governance. Now, by rethinking the data management paradigm, the responsibility for good data protection policy transcends technical teams and becomes a priority for the entire organization. To that end, Commvault laid out its strategy to deliver a comprehensive set of intelligent data services, spanning data protection, security, compliance, governance, data transformation, and data insights. In my view, a huge part of Commvault's strategy lies in automation. That's a key ingredient of cloud and any cloud strategy. In other words, supporting cloud native and cloud-like data management capabilities that can be programmatically deployed, secured, managed, and governed, and applied across an organization's sprawling data empire. The world of enterprise technology is complex and the winning technology companies are going to be those that can abstract the underlying complexity and assist organizations to implement sound data management practices, irrespective of data location, in the most efficient way. So as you hear the stories and examples here at Commvault Connections, you can decide for yourself if the company is on the right track and if what you hear aligns with your digital business skill goals. So let's now get a practitioner's perspective and hear how the CSO is thinking about data protection. Up next is Dave Martin, Chief Information Security Officer at ADP. You're watching theCUBE. (gentle upbeat music)

(soft electronic music) >> Welcome to this special CUBE Conversation. I'm John Furrier here, in theCUBE's Palo Alto studio. We're here, remotely, with Nick Halsey who's the CEO of OKERA, hot startup doing amazing work in cloud, cloud data, cloud security, policy governance as the intersection of cloud and data comes into real stable operations. That's the number one problem. People are figuring out, right now, is how to make sure that data's addressable and also secure and can be highly governed. So Nick, great to see you. Thanks for coming on theCUBE. >> It's great to be here, John, thank you. >> So you guys have a really hot company going on, here, and you guys are in an intersection, an interesting spot as the market kind of connects together as cloud is going full, kind of, whatever, 3.0, 4.0. You got the edge of the network developing with 5G, you've got space, you've got more connection points, you have more data flowing around. And the enterprises and the customers are trying to figure out, like, okay, how do I architect this thing. And oh, by the way, I got a, like all these compliance issues, too. So this is kind of what you could do. Take a minute to explain what your company's doing. >> Yeah, I'm happy to do that, John. So we're introduced a new category of software that we call universal data authorization or UDA which is really starting to gain some momentum in the market. And there're really two critical reasons why that happening. People are really struggling with how do I enable my digital transformation, my cloud migration while at the same time making sure that my data is secure and that I'm respecting the privacy of my customers, and complying with all of these emerging regulations around data privacy like GDPR, CCPA, and that alphabet soup of regulations that we're all starting to become aware of. >> I want to ask about the market opportunity because, you know, one of the things we see and the cloud covers normal conversations like, "Hey, modern applications are developing." We're starting to see cloud-native. You're starting to see these new use cases so you're starting to see new expectations from users and companies which creates new experiences. And this is throwing off all kinds of new, kinds of data approaches. And a lot of people are scratching their head and they feel like do they slow it down, they speed it up? Do I get a hold of the compliance side first? Do I innovate? So it's like a real kind of conflict between the two. >> Yeah, there's a real tension in most organizations. They're trying to transform, be agile, and use data to drive that transformation. But there's this explosion of the volume, velocity, and variety of data, we've all heard about the three Ds, we'll say there're five Ds. You know, it's really complicated. So you've got the people on the business side of the house and the Chief Data Officer who want to enable many more uses of all of these great data assets. But of course, you've got your security teams and your regulatory and compliance teams that want to make sure they're doing that in the right way. And so you've got to build a zero-trust infrastructure that allows you to be agile and be secure at the same time. And that's why you need universal data authorization because the old manual ways of trying to securely deliver data to people just don't scale in today's demanding environments. >> Well I think that's a really awesome approach, having horizontally scalable data. Like infrastructure would be a great benefit. Take me through what this means. I'd like to get you to define, if you don't mind, what is universal data authorization. What is the definition? What does that mean? >> Exactly and people are like, "I don't understand security. "I do data over here and privacy, "well I do that over here." But the reality is you really need to have the right security platform in order to express your privacy policies, right. And so in the old days, we used to just build it into the database, or we'd build it into the analytic tools. But now, we have too much data in too many platforms in too many locations being accessed by too many, you know, BI applications and A-I-M-L data apps and so you need to centralize the policy definition and policy enforcement so that it can be applied everywhere in the organization. And the example I like to give, John, is we are just like identity access management. Why do I need Okta or Sale Point, or one of those tools? Can't I just log in individually to, you know, SalesForce or to GitHub or? Sure, you can but once you have 30 or 40 systems and thousands of users, it's impossible to manage your employee onboarding and off-boarding policy in a safe and secure way. So you abstract it and then you centralize it and then you can manage and scale it. And that's the same thing you do with OKERA. We do all of the security policy enforcement for all of your data platforms via all of your analytic tools. Anything from Tableau to Databricks to Snowflake, you name it, we support those environments. And then as we're applying the security which says, "Oh, John is allowed access to this data in this format "at this time," we can also make sure that the privacy is governed so that we only show the last four digits of your social security number, or we obfuscate your home address. And we certainly don't show them your bank balance, right? So you need to enable the use of the data without violating the security and privacy rights that you need to enforce. But you can do both, with our customers are doing at incredible scale, then you have sort of digital transformation nirvana resulting from that. >> Yeah, I mean I love what you're saying with the scale piece, that's huge. At AWS's Reinforce Virtual Conference that they had to run because the event was canceled due to the Delta COVID surge, Stephen Schmidt gave a great keynote, I called it a master class, but he mainly focused on cyber security threats. But you're kind of bringing that same architectural thinking to the data privacy, data security piece. 'Cause it's not so much you're vulnerable for hacking, it's still a zero-trust infrastructure for access and management, but-- >> Well you mean you need security for many reasons. You do want to be able to protect external hacks. I mean, every week there's another T-Mobile, you know, you name it, so that's... But 30% of data breaches are by internal trusted users who have rights. So what you needed to make sure is that you're managing those rights and that you're not creating any long tails of data access privilege that can be abused, right? And you also need, one of the great benefits of using a platform like OKERA, is we have a centralized log of what everybody is doing and when, so I could see that you, John, tried to get into the salary database 37 times in the last hour and maybe we don't want to let you do that. So we have really strong stakeholder constituencies in the security and regulatory side of the house because, you know, they can integrate us with Splunk and have a single pane of glass on, weird things are happening in the network and there's, people are trying to hit these secure databases. I can really do event correlation and analysis, I can see who's touching what PII when and whether it's authorized. So people start out by using us to do the enforcement but then they get great value after they've been using us for a while, using that data, usage data, to be able to better manage their environments. >> It's interesting, you know, you bring up the compliance piece as a real added value and I wasn't trying to overlook it but it brings up a good point which is you have, you have multiple benefits when you have a platform like this. So, so take me through like, who's using the product. You must have a lot of customers kicking the tires and adopting it because architecturally, it makes a lot of sense. Take me through a deployment of what it's like in the customer environment. How are they using it? What is some of the first mover types using this approach? And what are some of the benefits they might be realizing? >> Yeah, as you would imagine, our early adopters have been primarily very large organizations that have massive amounts of data. And they tend also to be in more regulated industries like financial services, biomedical research and pharmaceuticals, retail with tons of, you know, consumer information, those are very important. So let me give you an example. We work with one of the very largest global sports retailers in the world, I can't use their name publicly, and we're managing all of their privacy rights management, GDPR, CCPA, worldwide. It's a massive undertaking. Their warehouse is over 65 petabytes in AWS. They have many thousands of users in applications. On a typical day, an average day OKERA is processing and governing six trillion rows of data every single day. On Black Friday, it peaked over 10 trillion rows of data a day, so this is scale that most people really will never get to. But one of the benefits of our architecture is that we are designed to be elastically scalable to sort of, we actually have a capability we call N scale because we can scale to the Nth degree. We really can go as far as you need to in terms of that. And it lets them do extraordinary things in terms of merchandising and profitability and market basket analysis because their teams can work with that data. And even though it's governed and redacted and obfuscated to maintain the individuals' privacy rights, we still let them see the totality of the data and do the kind of analytics that drive the business. >> So large scale, big, big customer base that wants scale, some, I'll say data's huge. What are some of the largest data lakes that you guys have been working with? 'Cause sometimes you hear people saying our data lakes got zettabytes and petabytes of content. What are some of the, give us a taste of the order of magnitude of some of the size of the data lakes and environments that your customers were able to accomplish. >> I want to emphasize that this is really important no matter what size because some of our customers are smaller tech-savvy businesses that aren't necessarily processing huge volumes of data, but it's the way that they are using the data that drives the need for us. But having said that, we're working with one major financial regulator who has a data warehouse with over 200 petabytes of data that we are responsible for providing the governance for. And one thing about that kind of scale that's really important, you know, when you want to have everybody in your organization using data at that scale, which people think of as democratizing your data, you can't just democratize the data, you also have to democratize the governance of the date, right? You can't centralize policy management in IT because then everybody who wants access to the data still has to go back to IT. So you have to make it really easy to write policy and you have to make it very easy to delegate policy management down to the departments. So I need to be able to say this person in HR is going to manage these 50 datasets for those 200 people. And I'm going to delegate the responsibility to them but I'm going to have centralized reporting and auditing so I can trust but verify, right? I can see everything they're doing and I can see how they are applying policy. And I also need to be able to set policy at the macro level at the corporate level that they inherit so I might just say I don't care who you are, nobody gets to see anything but the last four digits of your social security number. And they can do further rules beyond that but they can't change some of the master rules that you're creating. So you need to be able to do this at scale but you need to be able to do it easily with a graphical policy builder that lets you see policy in plain English. >> Okay, so you're saying scale, and then the more smaller use cases are more refined or is it more sensitive data? Regulated data? Or more just levels of granularity? Is that the use case? >> You know, I think there's two things that are really moving the market right now. So the move to remote work with COVID really changed everybody's ideas about how do you do security because you're no longer in a data center, you no longer have a firewall. The Maginot Line of security is gone away and so in a zero-trust world, you know, you have to secure four endpoints: the data, the device, the user, and the application. And so this pretty radical rethinking of security is causing everybody to think about this, big, small, or indifferent. Like, Gartner just came out with a study that said by 2025 75% of all user data in the world is going to be governed by privacy policy. So literally, everybody has to do this. And so we're seeing a lot more tech companies that manage data on behalf of other users, companies that use data as a commodity, they're transacting data. Really, really understand the needs for this and when you're doing data exchange between companies that is really delicate process that have to be highly governed. >> Yeah, I love the security redo. We asked Pat Gelsinger many, many years ago when he was a CEO of VMware what we thought about security and Dave Allante, my co-host at theCUBE said is it a do-over? He said absolutely it's a do-over. I think it was 2013. He mused around that time frame. It's kind of a do-over and you guys are hitting it. This is a key thing. Now he's actually the CEO of Intel and he's still driving forward. Love Pat's vision on this early, but this brings up the question okay, if it's a do-over and these new paradigms are existing and you guys are building a category, okay, it's a new thing. So I have to ask you, I'm sure your customers would say, "Hey, I already got that in another platform." So how do you address that because when you're new you have to convince the customer that this is a new thing. Like, I don't-- >> So, so look, if somebody is still running on Teradata and they have all their security in place and they have a single source of the truth and that's working for them, that's great. We see a lot of our adoption happening as people go on their cloud transformation journey. Because I'm lifting and shifting a lot of data up into the cloud and I'm usually also starting to acquire data from other sources as I'm doing that, and I may be now streaming it in. So when I lift and shift the data, unfortunately, all of the security infrastructure you've built gets left behind. And so a lot of times, that's the forcing function that gets people to realize that they have to make a change here, as well. And we also find other characteristics like, people who are getting proactive in their data transformation initiatives, they'll often hire a CDO, they'll start to use modern data cataloging tools and identity access management tools. And when we see people adopting those things, we understand that they are on a journey that we can help them with. And so we partner very closely with the catalog vendors, with the identity access vendors, you know, with many other parts of the data lake infrastructure because we're just part of the stack, right? But we are the last mile because we're the part of the stack that lets the user connect. >> Well I think you guys are on a wave that's massive and I think it's still, it's going to be bigger coming forward. Again, when you see categories being created it's usually at the beginning of a bigger wave. And I got to ask you because one thing's I've been really kind of harping on on theCUBE and pounding my fist on the table is these siloed approaches. And you're seeing 'em everywhere, I mean, even in the consumer world. LinkedIn's a silo. Facebook's a silo. So you have this siloed mentality. Certainly in the enterprise they're no stranger to silos. So if you want to be horizontally scalable with data you've got to have it free, you've got to break the silos. Are we going to get there? Is this the beginning? Are we breaking down the silos, Nick, or is this the time or what's your reaction to that? >> I'll tell you something, John. I have spent 30 years in the data and analytics business and I've been fortunate enough to help launch many great BI companies like Tableau and Brio Software, and Jaspersoft and Alphablocks we were talking about before the show. Every one of those companies would have been much more successful if they had OKERA because everybody wanted to spread those tools across the organization for better, more agile business analytics, but they were always held back by the security problem. And this was before privacy rights were even a thing. So now with UDA and I think hand-in-hand with identity access management, you truly have the ability to deliver analytic value at scale. And that's key, you need simplicity at scale and that is what lets you let all parts of your organization be agile with data and use it to transform the business. I think we can do that, now. Because if you run in the cloud, it's so easy, I can stand up things like Hadoop in, you know, like Databricks, like Snowflake. I could never do that in my on-prem data center but I can literally press a button and have a very sophisticated data platform, press a button, have OKERA, have enforcement. Really, almost any organization can now take advantage of what only the biggest and most sophisticated organizations use to be able to do it. >> I think Snowflake's an example for all companies that you could essentially build in the shadows of the big clouds and build your own franchise if you nail the security and privacy and that value proposition of scale and good product. So I got, I love this idea of security and privacy managed to a single platform. I'd love to get your final thought while I got you here, on programmability because I'm seeing a lot of regulators and people in the privacy world puttin' down all these rules. You got GDPR and I want to write we forgot and I got all these things... There's a trend towards programmability around extraction of data and managing data where just a simple query could be like okay, I want to know what's goin' on with my privacy and we're a media company and so we record a lot of data too, and we've got to comply with all these like, weird requests, like hey, can you, on June 10th, I want, can you take out my data? And so that's programmatic, that's not a policy thing. It's not like a lawyer with some privacy policy. That's got to be operationalized. So what's your reaction to that as this world starts to be programmable? >> Right, well that's key to our design. So we're an API first approach. We are designed to be a part of a very sophisticated mesh of technology and data so it's extremely simple to just call us to get the information that you need or to express a policy on the fly that might be created because of the current state-based things that are going on. And that's very, very important when you start to do real-time applications that require geo-fencing, you're doing 5G edge computing. It's a very dynamic environment and the policies need to change to reflect the conditions on the ground, so to speak. And so to be callable, programmable, and betable, that is an absolutely critical approach to implementing IUDA in the enterprise. >> Well this is super exciting, I feel you guys are on, again, a bigger wave than it appears. I mean security and privacy operating system, that's what you guys are. >> It is. >> It is what it is. Nick, great to chat with you. >> Couldn't have said it better. >> I love the category creation, love the mojo and I think you guys are on the right track. I love this vision merging data security policy in together into one to get some enablement and get some value creation for your customers and partners. Thanks for coming on to theCUBE. I really appreciate it. >> Now, it's my pleasure and I would just give one piece of advice to our listeners. You can use this everywhere in your organization but don't start with that. Don't boil the ocean, pick one use case like the right to be forgotten and let us help you implement that quickly so you can see the ROI and then we can go from there. >> Well I think you're going to have a customer in theCUBE. We will be calling you. We need this. We've done a lot of digital events now with the pandemic, so locked data that we didn't have to deal with before. But thanks for coming on and sharing, appreciate it. OKERA, hot startup. >> My pleasure, John and thank you so much. >> So OKERA conversation, I'm John Furrier here, in Palo Alto. Thanks for watching. (soft electronic music)

I'd say for me it's called it's really the power of the of the better together you know to me it's nobody's great apart it takes really an ecosystem of players to kind of work together for the customer benefit and the one that we've demonstrated the VMware with NetApp plus VMware has been a powerful one for well well over 17 years and the person they're putting in terms of the joint customers that have a ton of loyalty to both of us and they want us just to work it out so you know whether you're whether your allegiance on one side of the kubernetes community's battle or another or you're on one side of anyone's you know storage choice or another and I think customers want NetApp and VMware to work this out and in como solutions and we've done that and now what we for the second activist to come out will start that tomorrow I mean to me it starts from what the customer would like to do right and what what we're seeing from customers is it's increasingly a multi cloud world right that expands spans private cloud public cloud and Ed you're smiling when I yeah now there's an opportunity yeah but it's a chance for customers right and so if you look at how VMware is trying to help their meso sort of square the circle I think the first piece is this idea of consistent operations right then we have these management tools that you can use to consistently operate those environments whether they're based on a VMware based infrastructure or whether they're based on a native cloud infrastructure right so if you look at our cloud health platform for example it's a great example where that service can help you under get visibility to your cloud spend across different cloud platforms also be store based platforms and can help you reduce that spend over time so that's sort of what we refer to as consistent operations right which can span any any cloud you know my team is responsible for is more in that consistent infrastructure space and that's really all about how do we deliver consistent compute network and storage service that spans on from multiple public clouds an edge so that's really where we're bringing that same VMware cloud foundation stacked all those different environments you know the networking folks and networking was always relegated to being the underlay or the plumbing now what's becoming important is that the application are making their intent aware to the network and the intent is becoming aware as the intern becomes aware we networking people know what to do in the Estevan layer which then shields all the intricacies of what needs to get done in the underlay so to put it in very simple terms the container is what really drives the need and what we're doing is we're building the outcome to satisfy that need now containers are critical because as Pat was saying you know all of the new digital applications are going to be built with containers in mind so the reason we call it client to cloud to containers because the containers can literally be anywhere you know we're talking about them in the private cloud and in the public cloud they could be right next to where the client is because of the edge cloud they could be in the telco network which is the telco cloud so between these four clouds you literally have a network of these containers and the underlying infrastructure that we are doing is to provide that Estevan layer that will get the containers to talk to one another as well as to talk to the clients that are getting access to those application yeah I mean more than McAfee I think you know you you it's sort of you think of the and the the analog analog to cloud Security's data center security where you think of this sort of Amazon Cloud living in an Amazon datacenter and you know how can we protect that you know the data and the egress access into those cloud and you know same technology sort of apply but to your point that you sort of just touched upon its that cloud is not living in isolation right first of all that Amazon Cloud is connected to a whole bunch of you know applications that are still sitting in a data center right so they may not they're potentially not moving the Oracle database today since they're moving some workloads to the cloud right that's what most most companies are hey guess what there's all these endpoints that are connecting they're connecting both the data center and the cloud you're not gonna proxy to the cloud to get to the data center so there is a gateways so to me cloud security can't be an isolated you know sort of technology that companies have to sort of think about now is there is there opportunity to leverage the cloud to manage security better and get visibility in their security environments to do security analytics absolutely so I think to me that's where it's going because security I think has been proven is no longer you know sort of one thing single thing it's just you have to do multiple things every time I go talk to CIA source they tell me they got this technology that I said he made a minute you you have 20 did you cut down any yeah we've cut down a few but you know they just nervous about cutting down too much because if that one piece of software gets Paul so look I mean I think we again we're kind of really evolving our strategic aims you know historically we've looked at how do we really virtual eyes an entire data center right this concept of the software-defined data center really automating all that and driving great speed efficiency increases and now as we've been talking about we're in this world where you kind of STD sees everywhere right on pram and the cloud different public clouds and so how do you really manage across all those and these are the things we've been talking about so the cloud marketplace fits into that whole concept in the sense that now we can get people one place to go to get easy access to both software and solutions from our partners as well as open source solutions and these are things that come from the bitNami acquisition that we recently did so the idea here is that we cannot make it super simple for customers to become aware of the different solutions to draw those consistent operations that exists on top of our platform with our partners and then make it really easy for them to consume those as well I think we've really broaden and expanded our reach over the last ten years it used to be we're known primarily for our sports programming so now we have inclusive education and health programs we're being able to bring together people with and without intellectual disabilities through those mediums so we've divided resources to schools and education and they run Special Olympics programming during the school day so educators wanna have us because we're improving school clamp campuses reducing bullying enhancing social-emotional learning and so the work that we're doing is so so critical with that community then the air if health we have inclusive health so now we've got health and medical professionals that are now providing health screenings for our athletes so some of the the younger volunteers that we get that are there wanting to make a career in in the medical field they're exposed to our population right and so they learn more about their specific health needs so it's really about changing people's attitudes and so this community of supporters volunteers health Vettel's education were really our goal is to change people's attitudes fundamentally worldwide about people with intellectual disabilities and really kind of produce inclusive mindsets we call it really promote understanding and so now that the the road map that was shared in terms of what VMware looks to do to integrate containers into the ESXi platform itself right it's you know managing VMs and containers Nextiva that's perfect in terms of not having customers have to pick or choose between which platform and where you're gonna deploy something allow them to say you can deploy on whichever format you want it runs in the same ecosystem and management and then that trickles down to the again your storage layer so we do a lot of object storage within the container ecosystems today a lot of high-performance objects because you know the the the file sizes of instances or applications is much larger than you know a document file that URI might create online so there's a big need around performance in that space along with again management at scale the whole multi cloud hybrid cloud movement what's going on out at the enterprise your perspective on kind of where we are in that shift if you will or that transformation and and what's what's driving it you know what's what's creating all the bang you get that question a lot right people ask me what inning are we in question you know it's a regular you know I would say a couple years ago you know as people said I don't think that I think the national anthem is still being played kind of thing you know and I think the game has probably started you know but but I still were think for very early innings and you know I think I'd actually bring it up to even a higher level and talk about what's happening in terms of how companies are thinking about digital transformation and it would I what I think is happening is it's becoming a board level priority for companies they can't afford to ignore it you know digital is changing the Commun obey suspended of advantage in most industries around the globe and so they're investing in digital transformation and I think they're going to do that frankly independent of whatever macroeconomic climate we operate in and so and I think you know the big driving force probably you know in digital transformation today the cloud and so and what we're seeing is there's a you know it's a particular architecture of choice that's emerging for customers yep and I think you know you hit the nail on the head networking has changed it's no longer about speeds and feeds it's about availability and simplicity and so you know Dell and VMware I think are uniquely positioned to deliver a level of automation where this stuff just works right I don't need to go and configure these magic boxes individually I want to just write you know a line of code where my infrastructure is built into the CI CD pipeline and then when I deploy a workload it just works I don't need an army of people to go figure that out right and and I think that's the power of what we're working together to unleash so that was pretty dramatic moment of truth when we deployed atrium and we started the imaging process and it was finished and to be honest I thought that is broken but it actually was that fast so gave us a tremendous amount of I mean ability to deploy and manage and do the work during the workday instead of working after hours and what we doing for data protection before date really we use variety of different solutions backups just to tape and variety of services that actually backed up are they still do or know we've given that a lot up the floor of all the legacy stuff it got rid of that did you have to change your processes or what was that like Wow info we have to we have to get rid of a lot of process they were focused on backup focus on a time that it took to manage backup with atrium date reom didn't have the backup from the day one this is something that they designed I think a second year and that was very different to see the company that deals with storage creating such an innovative vision for developing old I mean developing a roadmap that was actually coming true with every iteration of the software deployment so the second tier that we provisioned was the snapshot and the snapshots that were incredibly fast that didn't take a lot of space that was you know give us ability to restore almost instantly gave us a huge amount of you know focus on not focusing and on storage anymore well since we're here at vmworld right you know be immoral has about 70 million work I think it's actually bigger than the public cloud I you correct me if I'm wrong right uh yeah I mean the I look I'm premise way bigger than the public cloud I have no question exactly and and and what's happening of course is faster sorry but the line is blurring between you know what's a public cloud what's a you know hybrid cloud multi-cloud edge and so look our opportunity is to really make all that go away for customers and allow them to choose and express our unique value add in whatever form the customer wants to use it so you've seen us align with all the public clouds you know you're seeing us take steps in the edge we're continuing to improve the on-premise systems you know with project dimension now it's the VMware cloud on Dell EMC that we're managing for you and it's on demand its consumption and it's consumed just like a public cloud I spend about 50 percent of my time talking to these customers so we learn a lot and here are the four big challenges they're facing first is the explosion of data data is just growing so fast Gartner estimates they'll be a hundred and seventy-five zettabytes of data in 2025 if you cram that into iphone so you take two point six trillion iPhones and go to the Sun and back right it's an enormous amount of data second they're worried about ransomware it's not a question of if you'll be attacked it's when you'll be attacked look at what's happening in Texas right now with the 22 municipalities dealing with that what you want in that case is a resilient infrastructure you want to be the ripples to restore from a really good backup copy of data third they want the hybrid multi cloud world just like Pat Gelson juror has been talking about that's what customers want but they want to be able to protect their data wherever it is make it highly available and get insights in their data wherever it's located and then finally they're dealing with this massive growth in government regulations around the world because of this concern about privacy I was in Australia a few weeks ago and one of our customers she was telling me that she deals with 27 different regulatory environments another customer was saying that California Privacy Act will be the death of him and he's based in st. Louis right so our strategy is focused on taking away the complexity and helping the largest companies in the world deal with these challenges and that's why we introduced the enterprise data services platform and that's why we're here at VMworld talking kubernetes the technology enabler I mean tcp/ip was that in the old networking days it enabled a lot of shifts in the industry you were far that way yeah kubernetes that disruptive enabler yeah I really see it as one of those key transition points in the industry and as I sort of joked if my name was Scott and we were 20 years ago I'd be banging the table calling it Java and Java defined enterprise software development for two decades by the way Scott's my neighbor he's down the hill so I looked down on mr. McNeely I always liked but you know the you know it changed how people did enterprise software development for the last two decades and kubernetes has that same kind of transformative effect but maybe even more important it's not just development but also operations and I think that's what we're uniquely bring together with project Pacific really being able to bridge those two worlds together so you know and if we deliver on this you know I think it is you know that X decade or two will be the center of innovation for us how we bridge those two roles together and really give developers what they need and make it operator friendly out-of-the-box across the history to the future this is pretty powerful yes so this conference is is I think a refreshing return to form so VMware is as you say this is an operators conference and VMware is for operators it's not for devs there was a period there where cloud was scary and and it was all this cloud native stuff and VMware tried to appeal to this new market and I guess tried to dress up and as something that it really wasn't and it didn't pull it off and we didn't it didn't feel right and now VMware has decided that well no actually this is what VMware is about and no one can be more VMware than VMware so it's returning to being its best self and I think against software they know software they know software so the the addition of putting project hands are in and having kubernetes in there and and it's it's to operate the software so it's it's going to be in there and apps will run on it and they want to have kubernetes baked into vSphere so that now yeah we'll have new app new apps and yeah there might be sass ups for the people who are consuming them but they've got to run somewhere and now we could run them on vmware whether it's on site at the edge could be in the cloud your vmware on AWS steve emotions [Music] you

>> Announcer: Live from Las Vegas, it's theCUBE, covering AWS re:Invent 2019. Brought to you by Amazon Web Services and Intel along with its ecosystem partners. >> Welcome back to the eighth year of AWS re:Invent. It's 2019. There's over 60,000 in attendance. Seventh year of theCUBE. Wall-to-wall coverage, covering all the angles of this broad and massively-growing ecosystem. I am Stu Miniman. My co-host is Justin Warren, and one of our Cube alumni are back on the program. Ramin Sayar, who is the president and CEO of Sumo Logic. >> Stu: Booth always at the front of the expo hall. I think anybody that's come to this show has one of the Sumo-- >> Squishies. >> Stu: Squish dolls there. I remember a number of years you actually had live sumos-- >> Again this year. >> At the event, so you know, bring us, the sixth year you've been at the show, give us a little bit of the vibe and your experience so far. >> Yeah, I mean, naturally when you've been here so many times, it's interesting to be back, not only as a practitioner who's attended this many years ago, but now as a partner of AWS, and seeing not only our own community growth in terms of Sumo Logic, but also the community in general that we're here to see. You know, it's a good mix of practitioners and business folks from DevOps to security and much, much more, and as we were talking right before the show, the vendors here are so different now then it was three years go, let alone six years ago. So, it's nice to see. >> All right, a lot of news from Amazon. Anything specific jump out from you from their side, or I know Sumo Logic has had some announcements this week. >> Yeah, I mean, like, true to Amazon, there's always a lot of announcements, and, you know, what we see is customers need time to understand and digest that. There's a lot of confusion, but, you know, selfishly speaking from the Sumo side, you know, we continue to be a strong AWS partner. We announced another set of services along with AWS at this event. We've got some new competencies for container, because that's a big aspect of what customers are doing today with microservices, and obviously we announced some new capabilities around our security intelligence capabilities, specifically for CloudTrail, because that's becoming a really important aspect of a lot of customers maturation of cloud and also operating in the cloud in this new world. >> Justin: So walk us through what customers are using CloudTrail to do, and how the Sumo Logic connection to CloudTrail actually helps them with what they're trying to do. >> Well, first and foremost, it's important to understand what Sumo does and then the context of CloudTrail and other services. You know, we started roughly a decade ago with AWS, and we built and intelligence platform on top of AWS that allows us to deal with the vast amount of unstructured data in specific use cases. So one very common use case, very applicable to the users here, is around the DevOps teams. And so, the DevOps teams are having a much more complicated and difficult time today understanding, ascertaining, where trouble, where problems reside, and how to go troubleshoot those. It's not just about a siloed monitoring tool. That's just not enough. It doesn't the analytics or intelligence. It's about understanding all the data, from CloudTrail, from EC2, and non-AWS services, so you can appropriately understand these new modern apps that are dependent on these microservices and architectures, and what's really causing the performance issue, the availability issue, and, God forbid, a security or breach issue, and that's a unique thing that Sumo provides unlike others here. >> Justin: Yeah, now I believe you've actually extended the Sumo support beyond CloudTrail and into some of the Kubernetes services that Amazon offers like AKS, and you also, I believe it's ESC FireLens support? >> Ramin: Yeah, so, and that's just a continuation of a lot of stuff we've done with respect to our analytics platform, and, you know, we introduced some things earlier this year at re:Inforce with AWS as well so, around VPC Flow Logs and the like, and this is a continuation now for CloudTrail. And really what it helps our customers and end users do is better better and more proactively be able to detect potential issues, respond to those security issues, and more importantly, automate the resolution process, and that's what's really key for our users, because they're inundated with false positives all the time whether it's on the ops side let alone the security side. So Sumo Logic is very unique back to our value prop, but providing a horizontal platform across all these different use cases. One being ops, two being cybersecurity and threat, and three being line-of-business users who are trying to understand what their own users on their digital apps are doing with their services and how to better deliver value. >> Justin: Now, automation is so important when you've got this scope and scale of cloud and the pace of innovation that's happening with all the technology that's around us here at the show, so the automation side of things I think is a little bit underappreciated this year. We're talking about transformation and we're talking about AI and ML. I think, with the automation piece, is one thing that's a little bit underestimated from this year's show. What do you think about that? >> Yeah, I mean, our philosophy all along has been, you can't automate without AI and ML, and it's proven fact that, you know, by next year the machine data growth is going to be 16 zettabytes. By 2025, it's going to be 75 zettabytes of data. Okay, while that's really impressive in terms of volume of data, the challenge is, the tsunami of data that's being generated, how to go decipher what's an important aspect and what's not an important aspect, so you first have to understand from the streaming data services, how to be able to dynamically and schema on read, be able to analyze that data, and then be able to put in context to those use cases I talked about, and then to drive automation remediation, so it's a multifaceted problem that we've been solving for nearly a decade. In a given day, we're analyzing several hundred petabytes of data, right? And we're trying to distill it down to the most important aspects for you, for your particular role and your responsibility. >> Stu: Yeah, um, we've talked a lot about transformation at this show, and one of the big challenges for customers is, they're going through that application modernization journey. I wonder if you could bring us inside some of your customers, you know, where are they having success, where are some of the bottlenecks slowing them down from moving along on this transformation journey? >> Yeah, so, it's interesting because, whether you're a cloud-native company like Sumo Logic or you're aspiring to be a cloud-native company or a cloud-first project going through migration, you have similar problems. It's now become a machine-scale problem, not a human-scale problem, back to the data growth, right? And so, some of our customers, regardless of their maturation, are really trying to understand, you know, as they embark on these digital transformations, how do they solve, what we call, the intelligence gap? And that is, because there's so much silos across the enterprise organizations today, across development, operations, IT, security, lines of business, in its context, in its completeness, it's creating more complexity for our customers. So, what Sumo tries to help solve, do, is, solve that intelligence gap in this new intelligence economy by providing an intelligence platform we call "continuous intelligence". So what do customers do? So, some of our customers use Sumo to monitor and troubleshoot their cloud workloads. So whether it's, you know, the Netflix team themselves, right, because they're born and bred in the cloud or it's Hudl, who's trying to provide, you know, analytics and intelligence for players and coaches, right, to insurance companies that are going through the migration journey to the cloud, Hartford Insurance, New York Life, to sports and media companies, Major League Baseball, with the whole cyber SOC, and what they're trying to do there on the backs of Sumo, to even trucking companies like Packard, who's trying to do driverless, autonomous cars. It doesn't matter what industry you're in, everyone is trying to do through the digital transformation or be disrupted. Everyone's trying to gain that intelligence or not just be left behind but be lapped, and so what Sumo really helps them do is provide one single intelligence platform across dev, sec, and ops, bringing these teams together to be able to collaborate much more efficiently and effectively through the true multi-tenant SaaS platform that we've optimized for 10 years on AWS. >> Justin: So we heard from Andy yesterday that one of the important ways to drive that transformational change is to actually have the top-down support for that. So you mentioned that you're able to provide that one layer across multiple different teams who traditionally haven't worked that well together, so what are you seeing with customers around, when they put in Sumo Logic, where does that transformational change come from? Are we seeing the top-down driven change? Is that were customers come from, or is it a little bit more bottom-up, were you have developers and operations and security all trying to work together, and then that bubbles up to the rest of the organization? >> Ramin: Well, it's interesting, it's both for us because a lot of times, it depends on the size of the organization, where the responsibilities reside, so naturally, in a larger enterprise where there's a lot of forces of mass because of the different siloed organizations, you have to, often times, start with the CISO, and we make sure the CISO is a transformation agent, and if they are the transformation agent, then we partner with them to really help get a handle and control on their cybersecurity and threat, and then he or she typically sponsors us into other parts of the line of business, the DevOps teams, like, for example, we've seen with Hartford Insurance, right, or that we saw with F5 Networks and many more. But then, there's a flip side of that where we actually start in, let's use another example, uh, you know, with, for example, Hearst Media, right. They actually started because they were doing a lift-and-shift to the cloud and their DevOps team, in one line of business, started with Sumo, and expanded the usage and growth. They migrated 32 applications over to AWS, and then suddenly the security teams got wind of it and then we went top-down. Great example of starting, you know, bottom-up in the case of Hearst or top-down in the case of other examples. So, the trick here is, as we look at embarking upon these journeys with our customers, we try to figure out which technology partners are they using. It's not only in the cloud provider, but it's also which traditional on-premise tools versus potentially cloud-native services and SaaS applications they're adopting. Second is, which sort of organizational models are they adopting? So, a lot of people talk about DevOps. They don't practice DevOps, and then you can understand that very quickly by asking them, "What tools are you using?" "Are you using GitHub, Jenkins, Artifactory?" "Are you using all these other tools, "and how are you actually getting visibility "into your pipeline, and is that actually speeding "the delivery of services and digital applications, "yes or no?" It's a very binary answer, and if they can't answer that, you know they're aspiring to be. So therefore, it's a consultative sale for us in that mode. If they're already embarking upon that, however, then we use a different approach, where we're trying to understand how they're challenged, what they're challenged with, and show other customers, and then it's really more of a partnership. Does that makes sense? >> Justin: Yeah, makes perfect sense to me. >> So, one of the debates we had coming into this show is, a lot of discussion at multicloud around the industry. Of course, Amazon doesn't talk specifically about multicloud all that well. If you look historically, attempts to manage lots of different environments under a single pane of glass, we always say, "pane is spelled P-I-A-N", when you try to do that. There's been great success. If you look at VMware in the data center, VMware didn't cover the entire environment, but vCenter was the center of your, you know, admin's world, and you would edge cases to manage some of the other environments here. Feels that AWS is extending their footprint with thing like Outposts and the environments, but there are lots of things that won't be on Amazon, whether it be a second cloud provider, my legacy data center pieces, or anything else there. Sounds like you touch many of the pieces, so I'm curious if you, just, weigh in on what you hear from customers, how they get their arms around the heterogeneous mess that IT traditionally is, and what we need to do as an industry to make things better. >> You know, for a long time, many companies have been bi-modal, and now they're tri-modal, right, meaning that, you know, they have their traditional and their new aspects of IT. Now they're tri-modal in the sense of, now they have a third leg of that complexity in stool, which is public cloud, and so, it's a reality regardless of Amazon or GCP or Azure, that customers want flexibility and choice, and if fact, we see that with our own data. Every year, as you guys well know, we put out an intelligence report that actually shows year-over-year, the adoption of not only various technologies, but adoption of technologies used across one cloud provider versus multicloud providers, and earlier this year in September when we put the new release of the report out, we saw that year-over-year, there was more than 2x growth in the user of Kubernetes in production, and it was almost three times growth year-over-year in use of Kubernetes across multiple cloud providers. That tells you something. That tells you that they don't want lock-in. That tells you that they also want choice. That tells you that they're trying to abstract away from the IaaS layer, infrastructure-as-a-service layer, so they have portability, so to speak, across different types of providers for the different types of workload needs as well as the data sovereignty needs they have to constantly manage because of regulatory requirements, compliance requirements and the like. And so, this is actually it benefits someone like Sumo to provide that agnostic platform to customers so they can have the choice, but also most importantly, the value, and this is something that we announced also at this event where we introduced editions to our Cloud Flex licensing model that allows you to not only address multi-tiers of data, but also allows you to have choice of where you run those workloads and have choice for different types of data for different types of use cases at different cost models. So again, delivering on that need for customers to have flexibility and choice, as well as, you know, the promise of options to move workloads from provider to provider without having to worry about the headache of compliance and audit and security requirements, 'cause that's what Sumo uniquely does versus point tools. >> Well, Ramin, I think that's a perfect point to end on. Thank you so much for joining us again. >> Thanks for having me. >> Stu: And looking forward to catching up with Sumo in the future. >> Great to be here. >> All right, we're at the midway point of three days, wall-to-wall coverage here in Las Vegas. AWS re:Invent 2019. He's Justin Warren, I'm Stu Miniman, and you're watching theCUBE. (upbeat music)

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape hello everyone and welcome to this week's episode of the cube insights powered by ETR you know this past week we attended the Dell technologies Industry Analysts event and in this breaking analysis I want to summarize the key takeaways and discuss some of the macro trends in the industry that are affecting Dell I'll also discuss some of the fundamental assumptions that Dell is making in its operating model and I'll talk about some of the challenges that I see for the company going forward and hopefully what is a frank manner now let me start with the event itself it was held in Austin Texas and it's clear that Austin Texas is becoming the epicenter of Dell post-acquisition of EMC it's shifting strongly back to Texas while the legacy of EMC remains what is the most critical part of Dells portfolio thanks to vmware the energy of Dell emanates from its founder Michael Dell the event was attended by about 250 press and analysts over a two-day period it was very well run with strong levels of executive access which is always very important to the analysts and lots of transparency and I thought clarity of message now the number one takeaway on this is Dell in four years the company has gone from irrelevance to a dominant and highly relevant player in the enterprise tech especially the CIOs and it's one of the most amazing transformations of a company that personally I've ever seen and I've seen several there were four other key takeaways for me that I'll show on this first slide of Alex if you bring it up first Michael Dell has put forth a set of moonshot goals for 2030 let me give you some examples by 2030 Dell says that for every product that they sell they're going to recycle an equivalent product by 2030 50 percent of the global workforce of Dell will be women and 40 percent of the managers of people will be women 25 percent of the u.s. workforce will be either Hispanic or African now most tech stories today are negative and this is a great positive message I'm not gonna spend a lot of time on this because in there's much more that Dell laid out but kudos for Dell to make for making these initiatives a priority you know particularly the women in tech and the diversity in the minorities I think it's excellent the second takeaway is Dell for Dell is the Dell is being driven by Jeff Clark and this guy is on a mission to simplify the portfolio Dell claims its reduced its product portfolio from 88 platforms down to 20 of that power platforms that powers a new brand now the reality is Dell really hasn't deprecated 68 products many if not most are still around but the RMD energy is all going into the new stuff now the third takeaway was a big announcement around power one power one is Dells new platform for the next generation of converged infrastructure now a lot of people might look at this and say well this is converged infrastructure without Cisco well it is actually and while that's true power one according to Dell is a much more of a developer friendly API and micro services based platform with a lot of automation software built in it's essentially going to be Dells go forward platform for customers that don't want to roll their own infrastructure the expectation or inference that that we took away was that power one will integrate most if not all future storage networking and server products Adela's positioning this as a complement to HCI or hyper-converged infrastructure which comprises VX rail VX flex which is the scale i/o and of course the OEM Nutanix so you can see Dell still got some work to do in terms of streamlining its portfolio and here's my lock of the day is that they'll be phasing out the Nutanix OEM relationship you could take that one to the bank now the fourth takeaway was the Dells cloud strategy is really coming into focus is it a winning strategy I honestly can't say at this point but in my view it's the only option that Dell has and and because of VMware they have a fighting chance Dell is in a much better position than other suppliers that that rely on you know Prem install bases because of VMware VMware is not only Dells piggy bank it is but it also gives Dell strategic levers with with CIOs and partners like for instance AWS now later on I'm going to share some ETR data that will give you some context but the bottom line is that the cloud is having an impact on everyone's business including Dells and I mean let me add the Dells cloud strategy in addition to relying on VMware is completely dependent on the assumptions that the world is going to be hybrid which is a good assumption and that multi cloud is going to evolve from what today I've said as a symptom of multi-vendor to a fundamental priority for CIOs again not a bad assumption but because of VMware adele has more than a fighting chance to compete for share now finally that that adele is going to be able to capitalize on the edge personally I think this is the biggest wildcard what I do think is that developers are going to be a crucial part of the edge and at this point in time Dell and VMware are not really top of mine in the developer community now the event involved keynotes from Michael Dell and other execs including including the CFO it was Tom sweet and and many other breakout sessions you know the normal one-on-ones as well now I don't have time to go into all this but there are some things that I want to share about Jeff Clark's presentation specifically he's the person that took over from David David Gordon a couple years ago he's been at Dell for more than 30 years and he was there when I think it was called pcs limited so a long time he's a trusted operational executive of Michael Dell's I'm very impressed with this guy he doesn't use a cheap prompter when he talks and in fact he has some notes but he's got these facts and figures at the in his head that he rattles off like a staccato pace he's an OBS exec and so let me summarize the his discussion now to bring up this slide the the big picture is the data sphere is gonna grow to 175 zettabytes and half of that is going to be created at the edge of that 30% is gonna require real-time processing now he talked about the mandate for simplification and he called this staying the easy button now in QA I asked him like why did it take you guys so long to figure out something so obvious which is kind of a snarky analyst question not his credit he didn't throw his predecessors under the bus rather what he did is he focused on the future and sit he said you know they shared the figures that I stated earlier about you know taking 88 platforms down to 20 and he focused on the priorities of the future so he didn't say it but I'm gonna say it for him he inherited a very messy portfolio and he had to clean up the crime scene me tell let me tell you what a buyer said about EMC back in 2018 this is from the ETR Venn survey when they go out and they probe you know specific customers and they talk to them this guy says NetApp has done a really good job of advertising and positioning itself within the cloud and within data centers themselves they've got a broad portfolio and I don't want to make comments about NetApp but so just I'm not sure I agree with all this but okay come back to his statements and and they've they've integrated fairly well here's what's relevant what he said was EMC on the other hand is not as well integrated they've got a broad portfolio but it's not necessarily - easy easy to pick and choose from the different categories okay so I agree with that you know look the mega launch product dujour worked for EMC it allowed them to carry on for another five or six years after the downturn but the lack of integration eventually caught up to that minute and it will always you know caught up catch up to large companies who rely on either lots of M&A or spinning out new products with lots of overlap anyway I digress the third thing that Clarke talked about was the big market size and the share gains pcs are a 200 billion dollar market servers are an 80 billion dollar market an external storage is a 26 billion dollar market Della's gains 600 basis points according to Clarke in pcs over the last six years 400 came in the last three years 375 basis points in storage in the past two years now of course what he didn't mention that was after a dismal performance a few years earlier so they had a pretty easy compare but my point is this when you talk to Michael Dell you talked to Tom sweet you talked to Jeff Clark and all the people folks in the company share gains are critical to Dells strategy especially because the cloud is taking so much share of wallet in the enterprise I'll make some other comments on that now finally there are two fundamental beliefs that dell has that i want to share with you one is that they can be a consolidator of these core markets in a downturn deltax they can hold their breath you know so to speak longer than the competitors and of course in an up market they think they can accelerate their leverage points which leads to the second belief that jeff clark talked about which is how dell will deliver differentiation and value so he decided four items there one is they got 40,000 direct sellers so they got a big go-to market presence they got 35,000 service professionals a 66 billion-dollar supply chain and then Dell financial services arm which you know forces Dell to carry a lot of debt but that debt throws off cash and it's not really part of Dells core debt from EMC acquisition now others have that too but but Dells got you know big presents there all right so I want to pivot to the ETR data and let's see how Dell looks in the spending survey and since market share is so important to Dell why don't we take a look at how they're doing so Alex this slide that I'm showing here what each er refers to as market share market share is defined by you TR as vendor citations in the survey excluding replacements so customers that are adding spending the same or spending more as spending less divided by the total number of respondents in the survey so it's a measure of how pervasive the vendor is in the data set what I'm showing in this slide is Dells market share and its three most important business lines namely VMware Delhi MC and Adele's laptop business and I'm showing this from the January 17 survey to October 19 now notice the survey sample overall is 960 for respondents and the three brands they show 800 and said six hundred and twenty two and three hundred and two shared ends within that 964 so there's two points one else doing pretty well I mean I'd say it's better than holding serve and as you can see it's steadily gaining now the second point is that look at the net scores here you know they're okay especially for vmware intel's laptop but Dell EMC for instance specifically their server and storage and networking business you know not so much so there's there's a mixed story here so let me make some comments on the macro and things that I've discussed with with ETR and and my narrative on demand overall some things that I've said you shared with you before as we've discussed in past breaking analyses spending is reverting back to pre eighteen levels but it's not falling off a cliff we're seeing fewer adoptions of new tech and more replacements of old tech so combine this with lower levels of spending and more citations overall we're seeing net score go down relative to previous surveys so here's what we think is happening there's less experimentation going on with the digital initiatives which started you know back in 2016 so you're seeing fewer adoptions of new tech as customers are start placing their bets and they're retiring leggy legacy systems that they were keeping on as a hedge and they're narrowing their spend on the new stuff and unplugging the stuff they don't need anymore and they're going at the serious production mode with the pocs so that means overall spending is softer it's not a disaster but it's lower than expected then coming into this year storage is on the back burner in a lot of accounts because of cloud and the big flash injection that I've talked about giving him more Headroom servers are really soft for Dell especially because they have a tough compared with previous with last year PC is actually pretty good all things being considered so where is the spending action well it's in the cloud now q how many vendors tell me that there's a big rebate repatriation trend happening ie people have cloud remorse and they're all moving back on pram not all but many M say it doesn't happen but at the macro-level its noise compared to the spending that's happening in the cloud just do the math all you got to do is look at AWS and Microsoft and what they report and compare it to any enterprise company that relies on on-prem selling I mean I don't want to argue about it you believe what you want but I would much prefer to look at the data so let's do that so here's a slide that shows ETR data on customer spending on the cloud so you got a AWS Azure and Google spenders and how their spending patterns have changed over time for dell emc servers so you got six hundred and thirty six cloud accounts 175 to 200 shared dell emc server accounts over the past three periods and yet net scores of 24% down to 16% so look at the gray bar versus the yellow bar gray is October 18 yellow is October 19 okay you get the picture the next slide is the same view for Dell EMC storage the gray bar is last year yellow bar is this year's survey so look at it 22% down to 5% that's not good so storage is getting hit by cloud and that's going to continue all right so let me conclude with some comments in general overall I like to tell strategy you know honestly without VMware I'm probably not gonna fly to Austin this week just being honest but with VMware Dell is far more important to our community so I pay more attention to it I haven't shared many thoughts on Dells financials but I think they have some upside here as they continue to pay down their debt by the way every five billion of dollars that they retire in debt it drops twenty five cents right to earnings per share Dell throws off a lot of cash it's a very well-run company they got an excellent management team we talked about their share gain lever they'll have a public cloud so they got to make on Prem as simple as possible and ideally is cloud like as they can you know the on-premise experience frankly is well behind that of the cloud but but cloud you know getting less simple and it's not cheap so on Prem in my view doesn't have to be exactly cloud it's just got to be good enough now Dell this week also refreshed its on demand pricing but it's good and it's obviously relevant to cloud not have time to go into all the detail but suffice to say that near-term there on-demand stuff it's it's going to be a small factor in their business but longer-term I think it's going to play in it's particularly to the cloud model Dell is also betting on hybrid and multi cloud they have to and but they're up against several competitors Microsoft is the is really strong in this space Microsoft's also a partner of course but you got IBM and Red Hat Cisco Google sort of and some others but VMware it gives Dell an advantage and that is the key the big hole that I see in Dell I'm going to come back to innovation you know Dell spends billions of dollars on R&D I think it's the numbers 20 billion over the last four years so that's good but you know innovation this industry is being delivered delivered by developers no those are the drivers and and it's they're taking advantage of data applying machine intelligence and cloud for scale and Dell is clearly well positioned for the data trend you know could partner for cloud it can certainly play an AI but what it lacks in my opinion is appeal to the developer community and just as Dell has become relevant to CIOs it needs this a similar type of relevance with the devs and that's a different ballgame so it's hopes are leaning on VMware and is of course its acquisition of pivotal but if I were Dell I would not sit back and wait for pivotal and VMware to figure it out here's what I would do if I were Dell I would deploy at least a thousand engineers they got twenty thousand engineers take a thousand or fifteen hundred them and point them toward developing open source tools and build applications and tools around all these hot emerging trends that we hear about multi-cloud multi cloud management edge all the innovations going on at edge autonomous vehicles etc AI workloads machine intelligence machine learning I would open-source that work and make a big commitment to the developer community big contributions and that would build hooks in from my hardware into these tools to make my hardware run better faster cheaper on these systems I want to thank my friend Peter burrows for forgiving me that idea but I think it's a great idea I think it's radical but it makes sense in this world that is really being driven by developers okay this is Dave Volante signing out from this episode of cube insights powered by ETR thanks for watching we'll see you next time

>> From the SiliconANGLE Media office in Boston Massachusetts, it's the theCUBE. Now here's your host, Dave Velllante (electronic music) >> Hi everybody. Welcome to the special CUBE conversation sponsored by Hewlett Packard Enterprise. This is part of our partner series. You know the partner business has changed quite dramatically over the years. It used to be you could make a lot of money pushing hardware and get some pretty good margins there. But increasingly, partners are becoming system integrators. They're becoming much more specialized in helping organizations transform, supporting their digital transformations, their infrastructure modernization, moving to the cloud, hybrid cloud, security. It really runs the gamut. And here to talk to me about that is Tim Ferris, who's a solutions architect at GreenPages. Tim, good to see you. Thanks for coming on. >> Great to be here. Thank you. >> So tell me a little bit about GreenPages. It's kind of a cool name. Where did that come from? And what are you guys all about? >> Oh God, I'm going to be killed for not knowing the history here. But, I think back in the old days, we used to hand out a neon green catalog. So we couldn't, back when we were doing cold calls, you'd probably get a lot of okay, we shipped you a catalog. Did you get that? Oh, I'm not quite sure. It may be buried under there. Neon green catalog, you could not lose. (laughs) I think we do our invoices on neon green paper now. >> That's good, green, the color of money. So tell us about your role as a solutions architect. What does that entail? And what's your background? >> Sure. So I'm a solutions architect. We have a number of different solutions architects at GreenPages who have a number of different specialties. My specialty is storage, disaster recovery and data management and protection and DR automation. And that's where it computes hyperconvergence, infrastructure and hybrid cloud. So specialization, a little bit wide, but we have other architects who are very deep in networking and hybrid cloud networking and that sort of thing as well. >> So let's get into some of that. Looking at your website, you guys are into everything. You've got software defined. You got cloud. You got security. You got DevOps and really runs the gamut. Well sometimes in this industry, we suffer from acronym soup. The reality is that things are changing quite dramatically. I mean it used to be you'd build an infrastructure to support a single application. You'd harden that infrastructure and that was it. It became a silo and people don't want that anymore. They want their data to be shared. They want it out of the silos, but at the same time it has to be protected. So what are some of the big trends that you're seeing in the marketplace and let's get into it. >> Sure. So yeah, many years ago that one app, one server, one application thing went the way of the dodo. You just got back from VM world. I paid my dues during the Wave One virtualization boom. When people were transforming racks and racks of servers into virtual machines. And so it used to be so easy to impress a customer. You show them a vMotion and it was like magic. You move the server from this server to that server without missing a beat. Now people are looking at hybrid cloud. So not just cloud, but hybrid cloud. Everybody we're talking to, we hear some people say that this is the last major hardware purchase that I want to make. Now I don't know the reality is that. That's debatable, right? But I think people want to have a roadmap to move their infrastructure to cloud or cloud services. Not just infrastructure as a service. You know, lift and shift. Software is a service and take advantage of that. So helping our customers manage that hybrid cloud journey is a big part of what GreenPages does. >> And of course, what the customer is really telling you is we don't want to spend a lot of time provisioning LUNs anymore because it doesn't add value to our business. We want to focus on building new apps or our digital transformation, etc. So and I think you're right. It's sort of aspirational that okay, we're not going to buy anymore hardware anymore. To me the key is, can the industry, through R & D, simplify what's on-prem and you know, lets face it, those mission critical apps you don't just want to throw them into the cloud. I mean, they're working. You don't want to have to refactor them and migrate. That's sort of an evil word. So to the extent that the industry can deliver that cloud-like experience on-prem, you can start to see this hybrid cloud vision evolve. What are your thoughts on that? >> Sure. So I think, in H it's fortuitous that we're here with HPE. I think they're doing a couple of things with some of their products and services that help push that. So it used to be that storage was relatively complicated. There were a lot of knobs and dials on storage that you could push and rotate in order to increase performance. You could have a number of different RAID levels. You know the 3PAR chunklets, and this sort of thing. There was a lot of customization you could do, you could use as a customer in order to properly set up your array for your workloads. People appreciate that level of detail that you can put into that but they want it easier. So I'm seeing a trend toward less customization and more ready just set it and forget it arrays. Nimble, the 3PAR array was highly available. Very good, very good array, very fast, but a little bit higher end to operate. Nimble with HPE's acquisition of Nimble, they've taken that operational complexity down significantly. Not only with operating the array, provisioning LUNs but managing it, maintaining it and performing predictive analytics through Infosite and that sort of thing. So at the storage level I think Nimble, in that paradigm is transforming storage. And HPE's GreenLake technologies, that is very much an answer to the private cloud. Having that hyperscale feel, that ability to expand elastically and get out of the hardware maintenance business by using the GreenLake service. >> So actually, a little bit of history here. So 3PAR was actually, the company was formed in the early 2000s before the term cloud computing really came out. They used, I think utility computing in their S-1 registration. But what 3PAR did is, it really simplified that high end. And then 3PAR reached escape velocity by going after the high end EMC base and did very well and of course famously got acquired by Hewlett Packard. At the time HP then became HPE. Nimble now is bringing sort of a new level where you're talking about intelligent automation and AI managing infrastructure, predictive analytics and that drives more automation which I think, Tim has really got to be a theme of hybrid cloud. I mean cloud is all about automation so hybrid cloud, on-prem, and public some kind of interconnection has to be highly automated, doesn't it? >> It absolutely does and people don't have time to turn the dials and to optimize their storage. They need systems that will do that for them. And there's the level one, the level two support that you get through those predictive analytics of Infosite are critical to customers. They don't, you know a lot of customers don't have time for full time storage admins anymore. And these technologies are what's freeing up those resources, those people resources to do other strategic things for the business. >> Especially in small and mid-sized businesses. >> Absolutely. >> Where they're generalist really, not really specialists at one thing. I want to come back to the hybrid cloud. You know thinking about data governance and management and security. Are we at the point where you can start to see sort of a consistent framework across clouds? You're smiling. (laughs) So what's the journey there? How are we going to get there? I mean (mumbling) (laughs) >> Yeah, I would say we're certainly early days there. I think you know customers need to be much more cognizant of the tools that they use and buy. They can't be necessarily proprietary on-prem tools. The best use of your money is to buy tools, that can be used to manage hybrid and secure hybrid infrastructures. So that should be a main qualifier for what people are looking for for security technologies and that sort of thing. It's not quite the wild west, though we still see, you know there's that shared governance model. That shared responsibility in the cloud. I think there are still some who haven't woken up to that basic concept. That just because I moved the workload to the cloud doesn't mean it's no longer my responsibility to secure that data. Though we're still talking with people today who may be under that misimpression. >> You're right, Tim. I mean that is not well understood and people think if I move in the cloud, I'm good. But there is shared responsibility model whether it's for security or governance, etc. And when you talk to chief information security officers they'll tell you, yeah, you know the cloud vendor might secure the storage device, but its' really our responsibility to do everything else. And the list of everything else is still quite long. >> Absolutely, you know rights, roles and responsibilities. Those sorts of things, firewall rules. They provide the firewall. They make sure the firewall is up to date on it's firmware. But you're setting the rules. You're setting the ingress, egress. So, yes it's very much still a shared responsibility. And yeah, it's eye opening still to some. >> Let's talk about your partnership with HPE. We talked about some of the products, but what do you look for in a partner? Obviously as I said before, you know used to be you sell in boxes. You want margin and I'm sure you still want margin. But there's got to be more, right? >> Well yeah, I mean we've known for quite a while. I mean we've seen the writing on the wall that, I remember the glory, I don't know glory days, the old days back when people could make a fortune selling memory, back before the turn of the century, turn of the century. (laughs) I'm dating myself. But it's true you could make quite a bit of money selling memory back then. But today and certainly over the past 20 years, people, our clients are choosing partners that they can't, not just the cheapest price, but people who can talk to them about a solution. Not just a product. Hear their business problems and turn that into technology solutions that help them address those problems. So that's what I would look for as a partner, if I were, we look to HPE for the same thing. Not just pushing product, where to sell product, but to solve business problems. And I think that HPE is listening, they're hearing their clients. They were listening to them with the acquisition of HPE Nimble. They're listening to them, how they're expanding Infosite from just a Nimble platform, the 3PAR and Prolient and other things and expanding some of those things. >> Yeah, the pendulum has swung after the dot.com boom it became cut, cut, cut. Everyone was concerned about budgets. You know IT doesn't matter anymore. We heard all that >> crosstalk >> and that's totally changed. IT's driving revenue. It's driving top line. Of course budgets are still critical and we've talked a lot about simplification which is a lot about attacking the IT labor problem. But right now the sentiment with the booming economy we're in. This tenth, ninth year of a run on a bull market, obviously in the late cycles, but the sentiment is much more toward how do I enable the business with technology? >> Yes. Yeah, yeah. So how does IT add value back to the business? They can do that through AI, through analytics and through digital transformation in general. I think we've seen a, you know there's always been this upward curve to storage growth. But it's dramatically increased I think. It's upward, predicted to be upward of 40 zettabytes, or something like that by the year 2022. And that's because more and more businesses are using this data more creatively. They're saving it more and not only is that growing, the usable data, but they need to retain it for longer. You've got to retain it, you've got to protect it and we've still got data protection problems. Not just storing it and providing the right performance level for it. But it's really difficult. And then you've got to secure all that extra data, as well. >> Well, I think you're right too. The curve is getting non-linear. I mean it used to be, I've said this often on the theCUBE that we for decades, we've marched to the cadence of Moore's law. But now the innovation sandwich, if you will, it's about applying machine intelligence to data and then automating, whether it's public cloud or on-prem cloud-like, it's being able to scale. >> Right. >> And it's those three pieces of the sandwich that are now driving innovation. No longer the doubling of transistors every 18 months. >> Yeah, so do people want to scale on-prem? Do they want to scale to the cloud and the cloud market itself as it's very elastic, very easy to grow and shrink and contrast? Or can you do some of those types of things on-prem? You know with GreenLake and with some other programs that let you have your on-prem security blanket and your on-prem performance with the hands-off operational paradigm and the elastic growth that you have in cloud. I think that's the best of both worlds for some. >> Let's end with a call to action. So what advice would you give to practitioners, clients that are looking to modernize their infrastructure? They're trying to support their digital transformation. They want to get from point A to point B. They don't want to spend a billion dollars doing it. They got to go on a journey. How do they get there? What's your advice? >> My advice is to certainly, I'm jaded here, but I would say engage professionals who have done this many many times. Don't learn on the job here. You can make some expensive mistakes moving workloads to the cloud. And we've seen anecdotal evidence, and in-person evidence of people moving to the cloud, doing it the wrong way and then having to migrate that back. That's a costly mistake. So make sure you do your planning. Migrate in phases. Move your data there in phases. Bite off some smaller chunks first to make sure if you have growing pain, teething pains that that happens with a non-critical application. Build your knowledge base and then make some better decisions. Engage people like GreenPages to help you roadmap your journey, your hybrid cloud journey. And don't go in with a preconceived notion of where you need to end, right? The applications, their performance requirements and that assessment work up front should dictate where the best place is for those workloads. >> Great advice. Tim Ferris from GreenPages. Thanks so much for coming on theCUBE. It's great to have you. >> Thank you. >> And thank you for watching everybody. We'll see you next time. This is Dave Vellante. We're out. (electronic music)

>> From Boston, Massachusetts, it's theCUBE! Covering Actifio 2019 Data Driven. Brought to you by Actifio. >> Here we are in Boston, Massachusetts. I'm Stu Miniman, this is theCUBE at the special, at Data Driven '19, Actifio's user event. Happy to bring on a CUBE alum who's a partner of Actifio, Phil Buckellew, who's General Manager of IBM Cloud Object Storage. Phil, thanks for coming back. >> Great, great to be here Stu. >> All right, so object storage. Why don't you give us first just kind of an encapsulation of kind of the state of your business today. >> Sure, object storage is really an extremely important business for the industry today because really it's a new way accessing data, it's been around obviously for a decade or so but really, it's increasingly important because it's a way to cost-effectively store a lot of data, to really to be able to get access to that data in new and exciting ways, and with the growth in the volume of data, of particularly unstructured data, like 103 zettabytes by 2023 I think I heard from the IDC guys, that really kind of shows how important being able to handle that volume of data really is. >> So Phil, I go back, think about 12 years ago, all the technologists in this space were like, "The future of storage is object," and I was working at one of the big storage companies and I'm like, "Well we've been doing block and file," and there was this big gap out there, and kind of quietly object's taken over the world because underneath a lot of the cloud services there, object's there, so IBM made a big acquisition in this space. Talk about, you know, customers that I talk to it's not like they come out and say, "Oh jeez, I'm buying object storage, "I'm thinking about object storage." They've got use cases and services that they're using that happen to have object underneath. Is that what you hear from your users? >> Yeah, there's a couple of different buying groups that exist in the object storage market today. The historic market is really super large volumes. I mean, we're unique in that IBM acquired the Cleversafe company back in 2015 and that technology is technology we've expanded upon and it really, it's great because it can go to exabyte scale and beyond and that's really important for certain use cases. So some customers that have high volumes of videos and other unstructured data, that is really a super good fit for those clients. Additionally, clients that really have the need for highly resilient, because the other thing that's important the way that we built our object storage is to be able to have a lot of resiliency, to be able to run across multiple data centers, to be able to use erasure coding to ensure the data's protected, that's really a large part of the value, and because you can do that at scale without having downtime when you upgrade, those are really a lot of core benefits of object storage. >> Right, that resiliency is kind of built into the way we do it and that was something that was just kind of a mind shift as opposed to, okay I've got to have this enterprise mindset with an HA configuration and everything with N plus whatever version of it. Object's going to give you some of that built-in. The other thing I always found really interesting is storing data is okay, there's some value there, but how do I gain leverage out of the data? And there's the metadata underneath that helps. You talk about video, you talk about all these kinds there. If I don't understand what I've got and how I'd leverage it, it's not nearly as valuable for me, and that's something, you know really that one of the key topics of this show is, how do I become data driven, is the show, and that I have to believe is something critically important to your customers. >> Absolutely, and really object storage is the foundation for modern cloud-native data lakes, if you will, because it's cost-effective enough you can drop any kind of storage in there and then you can really get value from those assets wherever you are, and wherever you're accessing the data. We've taken the same technology that was the exabyte scale on-premise technology, and we've put it in the IBM public cloud, and so that really allows us to be able to deliver against all kinds of use cases with the data sets that clients want, and there's a lot of great innovation that's happening especially on the cloud side. We've got the ability to query that data, any kind of rectangular data with standard ANSI SQL statements, and that just really allows clients to unlock the potential of those data sets, so really good innovation going on in that space to unlock the value of the data that you put inside of object storage. >> All right, Phil let's make the connection. Actifio's here, IBM OEM's the solution. So, talk about the partnership and what customers are looking for when they're looking at their IPs. Sure, so, quite a ways prior to the partnership our object storage team partnered up with the Actifio team at a large financial services customer that recognized the growth in the volume of the data that they had, that had some unique use cases like cyber resiliency. They get attacked with ransomware attacks, they needed to have a standard way to have those data sets and those databases running in a resilient way against object storage that can still be mounted and used, effectively immediately, in case of ransomware attacks, and so that plus a lot of other traditional backup use cases is what drew the IBM Cloud Object Storage team and the Actifio team together. Successful deployments at large customers are really where we got our traction. And with that we also really began to notice the uptick in clients that wanted to use, they wanted to do test data management, they wanted, they needed to be able to have DevOps team that needed to spin up a replica of this database or that database very fast, and, you know, what we found was the combination of the Actifio product, which we've OEM'd as IBM Virtual Data Pipeline, allows us to run those virtual databases extremely cost-effectively backed by object storage, versus needing to make full replicas on really expensive block storage that takes a long time. >> Well yeah, we'd actually done research on this a number of years ago. Copies are great, but how do I leverage that right? From the developer team it's, I want to have something that mirrors what I have in production, not just some test data, so the more I can replicate that, the better. Phil, please, go ahead. >> There's some really important parts of that whole story, of being able to get that data flow right, to be able to go do point-in-time recoveries of those databases so that the data is accurate, but also being able to mask out that PII or sensitive information, credit card data or others that you really shouldn't be exposing to your testers and DevOps people. Being able to have the kind of-- (Phil laughs) >> Yeah, yeah, shouldn't because, you know, there's laws and lawsuits and security and all these things we have. >> Good, good, absolutely. >> So, Phil, we're talking a lot about data, you've actually got some new data to share with us, a recent survey that was done, should we share some of your data with us? >> Yeah, we did some, we did a, the ESG guys actually worked with us to build out a piece of research that looked at what would it cost to take a 50 terabyte Oracle 12c database and effectively spin up five copies the way you traditionally would so that different test teams can hammer away against that data set. And we compared that to running the VDP offering with our Cloud Object Storage solution. You know, distances apart, we had one where the source database is in Dallas and the destination database is in Washington, D.C. over a 10 gigabyte link, and we were able to show that you could set up five replicas of the database in like 90 minutes, compared with the two weeks that it would take to do full replication, because you were going against object storage, which runs about 2.3 cents per gigabyte per month, versus block storage fully loaded, which runs about 58 cents per gigabyte per month. The economics would blow away. And the fact that you could even do queries, because object storage is interesting. Yes, if you're using, if you have microsecond response times for small queries you got to run some of that content on block storage, but for traditional queries, we look at, like, really big queries that would run against 600 rows, and we were half the time that you would need on traditional block storage. So, for those DevOps use cases where you're doing that test in development you can have mass data, five different copies, and you can actually point back in time because really, the Actifio technology is really super in that it can go do point-in-time, it was able to store the right kind of data so the developers can get the most recent current copies of the data. All in, it was like 80% less than what you would have paid doing it the traditional way. >> Okay, so Phil, you started talking a little bit about some of the cloud pieces, you know, Actifio in the last year launched their first SaaS offering Actifio GO. How much of these solutions are for the cloud versus on-premises these days? >> Absolutely, so one of the benefits of using a virtual data approach is being able to leverage cloud economics 'cause a lot of clients they want to do, you know, they want to be able to do the test in dev which has ups and downs and peaks and valleys when you need to use those resources, the cloud is really an ideal way to do those types of workloads. And so, the integration work that we've done with the Actifio team around VDP allows you to replicate or have virtual copies of those databases in the cloud where you want to do your testing, or we can do it in traditional on-prem object storage environments. Really, whatever makes most sense for the client is where we can stand up those environments. >> The other thing I wonder if you could expand on a little bit more, you talked about, like, cloud-native deployment and what's happening there. How does that tie into this discussion? >> Well, obviously modern architectures and ways of Agile, ways of building things, cloud-native with microservices, those are all extremely important, but you've got to be able to access the data, and it's that core data that no matter how much you do with putting Kubernetes around all of your existing applications you've still got to be able to access that core data, often systems record data, which is sitting on these standard databases of record, and so being able to have the VDP technology, be able to replicate those, stand those up like in our public cloud right next to all of our Kubernetes service and all the other technologies, it gives you the kind of full stack that you need to go do that dev in test, or run production workloads if you prefer from a public cloud environment, without having all of the burdens of running the data centers and maintaining things on your own. >> Okay, so Phil, everybody here for this two day event are going to get a nice, you know, jolt of where Actifio fits. You know, lots of orange here at the show. Give us the final word of what does it mean with orange and blue coming together. >> Well absolutely, we think this is going to be great for our clients. We've got, you know, tons of interested clients in this space because they see the value of being able to take what Actifio's done, to be able to virtualize that data, combine it with some of the technologies we've got for object storage or even block storage, to be able to serve up those environments in a super cost-effective way, all underlined by one of our core values at IBM, which is really trust and being responsible. And so, we often say that there's no AI, which all of this data leads up to, without information architecture and that's really where we specialize, is providing that governance, all the masking, all of the things that you need to feel confident that the data you've got is in the right hands, being used the right way, to be able to give you maximum advantage for your business, so we're super excited about the partnership. >> Phil, definitely a theme we heard at IBM Think, there is no AI without the IA, so, Phil Buckellew, thanks so much for joining us, sharing all the updates on what IBM is doing here with Actifio. >> Great, great to be here. >> All right, and we'll be back with more coverage here in Boston, Massachusetts at Actifio Data Driven 2019. I'm Stu Miniman and thanks for watching theCUBE. (futuristic music)

(funky guitar music) >> From our studios, in the heart of Silicon Valley, Palo Alto, California, This is theCUBE conversation. >> Everyone welcome to this CUBE conversation here in Palo Alto, California CUBE studios, I'm John Furrier, the host of theCUBE. Were with CUBE alumni, special guest Amit Walia, President of Products & Marketing at Informatica. Amit, it's great to see you. It's been a while. It's been a couple of months, how's things? >> Good to be back as always. >> Welcome back. Okay, Informatica worlds is coming up, we have a whole segment on that but we have been covering you guys for a long long time, data is at the center of the value proposition again and again, it's more amplified now, the fog is lifting. >> Sure. >> And the world is now seeing what we were talking about four years ago. (giggles) >> Yeah. >> With data, what's new? What's the big trends that going on that you guys are doubling down on? What's new, what's changed? Give us the update. >> Sure. I think we have been talking the last couple of years, I think your right, data has becoming more and more important. I think, three things we see a lot. One is obviously, you saw this whole world of digital transformation. I think that has de faintly has picked up so much steam now. I mean, every company is going digital and obviously that creates a whole new paradigm shift for companies to carry out almost recreate themselves, rebuild them, so data becomes the new definition. And that's what we call those things you saw at Infomatica even before data3.org, but data is the center of everything, right? And you see the volume of data growth, you know, the utilization of data to make decisions, whether it's, you know, decisions on the shop floor, decisions basically related to cyber security or whatever it is. And the key to what you see different now is the whole AI assisted data management. I mean the scale of complexity, the scale of growth, you know, multi-cloud, multi-platform, all the stuff that is in front of us, it's really difficult to run the old way of doing things, so that's why we see one thing that we see a whole lot is AI is becoming a lot more mainstream, still early days but it's assisting the whole ability for companies, what I call, exploit data to really become a lot more transformative. >> You have been on this for a while, again we can go back to theCUBE archives, we can almost pull out clips from two years ago, be relevant today, you know, the data control, understanding >> Yeah. >> Understanding where the data governance is-- >> Sure. >> That's always a foundational thing but you guys nailed the chat bots, you have been doing AI was previous announcements, this is putting a lot of pressure on you, the president of the products, you got to get this out there. >> What's new? What's happening inside Informatica? pedaling as fast as you can? What is some of the updates? >> No. >> Gives us the-- >> The best example always is like a duck, right? Your really swimming and feel things are calm at the top and then you are really paddling. No, I think it's great for us. I think, I look at AI's, AI is like, there is so much FUD [fear, uncertainty and doubt] around it and machine learning AI. We look at it as two different ways. One is how we leverage machine learning within our products to help our customers. Making it easy for them, like I said, so many different data types, think of IOT data, unstructured data, streaming data, how do you bring all that stuff together and marry it with your existing transactional data to make sense. So, we're leveraging a lot of machine learning to make the internal products a lot more easier to consume, a lot more smarter, a lot more richer. The second thing is that, we're what we call it our AI, CLAIRE, which we unveiled, if you remember, a couple of years ago at the Informatica World. How that then helps our customers make smarter decisions, you know, in data science and all of these data workbenches, you know, the old statistical models is only as good as they can ever be. So, we leveraging helping our customers see the value proposition of our AI, CLAIRE, then to what I make things that, you know, find patterns, you know, statistical models cannot. So, to me I look at both of those really, leveraging ML to shape our products, which is where we do a lot of innovation and then creating our AI, CLAIRE, to help customers to make smarter decisions, easier decisions, complex decisions, which I called the humans or statistical models, really cannot. >> Well this is the balance with machines and humans. >> Right. >> working together, you guys have nailed this before and I'm, I think this was two years ago. I started to hear the words, land, adopt, expand, form you guys, right? Which is, you got to get adoption. >> Right. >> And so, as you're iterating on this product focus, you got to getting working, making secure your products-- >> Big, big maniacal focus on that one. >> So, tell me what you have learned there because that's a hard thing. >> Right. >> You guy are doing well at it. You got to get adoption, which means you got to listen customers, you got to do the course correction. >> Yeah. >> what's the learnings coming out of that piece of that. >> That's actually such a good point. We've made such, we've always been a customer centric company but as you said, like, as whole world shifted towards a new subscription cloud model, we've really focused on helping our customers adopt our products and you know, in this new world, customers are struggling with new architectures and everything, so we doubled down on what we called customer success. Making sure we can help our customers adopt the products and by the way it's to our benefit. Our customers get value really quickly and of course we believe in what we call a customer for life. Our ability to then grow with our customers and help them deliver value becomes a lot better. So, we really focused, so, we have globally across the board customers, success managers, we really invest in our customers, the moment a customer buys a product from us, we directly engage with them to help them understand for this use case, how you implement the product. >> It's not just self service, that's one thing that I appreciate 'cause I know how hard it is to build products these days, especially with the velocity of change but it's also when you have a large scale data. >> Yeah. >> You need automation, you got to have machine learning, you got to have these disciplines. >> Sure. >> And this is both on your end and but also on the customer. >> Yes. >> Any on the updates on the CLAIRE and some customer learnings you're seeing that are turning into use cases or best practices, what are some of them? >> So many of them. So take a simple example, right? I mean, we think of, we take these things for granted, right? I mean, take note, we don't talk about IOB these days right? All these cell cells, we were streaming data, right? Or even robots on the shop floor. So much of that data has no schema, no structure, no definition, it's coming, right? Netflix data and for customers there is a lot of volume in it, a lot of it could be junk, right? So, how do you first take that volume of data? Create some structure to it for you to do analytics. You can only do analytics if you put some structure to it, right? So, first thing is I've leverage CLAIRE, we help our customers to create, what I call, schema and you can create some structure to it. Then what we do allow is basically CLAIRE through CLAIRE, it can naturally bring what we have the data quality on top of it, like how much of it is irrelevant, how much of it is noise, how much of it really makes sense, so, then, as you said it, signal from the noise We are helping our customers get signal from the noise of data. That's where it AI comes very handy because it's very manual, cumbersome, time consuming and sometimes very difficult to do. So, that's a area we have leveraged creating structure and data quality on top and finding rules that didn't naturally probably didn't exist, that you and me wouldn't be able to see. Machines are able to do it and to your point, our belief is, this is my 100% belief, we believe AI assisting the humans. We have given the value of CLAIRE to our users, so it complements you and that's where we are trying to help our users get more productive and deliver more value to you faster. >> Productivity is multifold, it's like, also, efficiency, people wasting time on project that can be automated, so you can focus that valuable resource somewhere else. >> Yeah. >> Okay, let's shift gears onto Informatica World coming up. Let's spend some time on that. What's the focus this year, the show, it's coming up, right around the corner, what's going to be the focus? What's going to be the agenda? What's on the plate? >> Give you a quick sense on how it's shape up, it's probably going to be our Informatica World. So, it's 20th year, again back in Waze, you know, we love Waze of course. We have obviously, a couple of days lined up over there, I know you guys will be there too. A great set of speakers. Obviously, we will have me on stage, speakers like, we'll have some, the CEO of Google Cloud, Thomas Kurian is going to be there, we'll have on the main stage with Anil, we'll have the CEO of Databricks, Ali, with me, we'll also have CMO of AWS, Ariel, there, then we have a couple of customers lined up, Simon from Credit Suisse, Daniel is the CDO of Nissan, we also have the Head of AI, Simon Guggenheimer from Microsoft as well as the Chief Product Officer of Tableau, Francois Ajenstat, so, we have a great line up of speakers, customers and some of our very very strategic partners with us. If you remember last year, We also had Scott Guthrie there main stage. 80 plus sessions, pretty much 90% lead by customers. We have 70 to 80 customers presenting. >> Technical sessions or going to be a Ctrack? >> Technical, business, we have all kinds of tracks, we have hands on labs, we have learnings, customers really want to learn our products, talk with the experts, some want to the product managers, some want to talk to the engineers, literally so many hands on labs, so, it's going to be a full blown couple of days for us. >> What's the pitch for someone watching that never been Informatica World? Why should they come for the show? >> I'll always tell them three things. Number one is that, it's a user conference for our customers to learn all things about data management and of course in that context they learn a lot about. So, they learn a lot about the industry. So, day one we kick it off by market perspectives. We are giving a sense on how the market is going, how everybody is stepping back from the day to and understanding, where are these digital transformation, AI, where is all the world of data going. We've got some great annalists coming, talkings, some customers talking, we are talking about futures over there. Then it is all about hands on learning, right?, learning about the product. Hearing from some of these experts, right?, from the industry experts as well as our customers, teaching what to do and what not to do and networking, it's always go to network, right, it's a great place for people to learn from each other. So, it's a great forum for all those three things but the theme this year is all about AI. I talked about CLAIRE, I'll in fact our tagline this year is, Clarity Unleashed. We really want, basically, AI has been developing over the last couple of years, it's becoming a lot more mainstream, for us in our offerings and this year we're really taking it mainstream, so, it's kind of like, unleashing it for everybody can genuinely use it, truly use it, for the day to day data management activities. >> Clarity is a great theme, I mean, it plays on CLAIRE but this is what we're starting to see some visiblility into some clear >> Yeah. >> Economic benefits, business benefits. >> Yep. >> Technical benefits, >> Yep. >> Kind of all starting to come in. How would you categorize those three areas because you know, generally that's the consensus these days that what was once a couple years ago was, like, foggy when you see, now you're starting to see that lift, you're seeing economic, business and technical benefits. >> To me it's all about economic and business. So, technology plays a role in driving value for the business, right, I'm a full believer in that, right, and if you think about some of the trends today, right, a billion users are coming into play that will be assisted by AI. Data is doubling every year, you know the volume of data, >> Yep. >> The amount of, and I always say business users today, I mean, I run a business, I want, I always say, tomorrow data, yesterday to make a decision today. It's just in time and that's where AI comes into play. So our goal is to help organizations transform themselves, truly be more productive, reduce operation cost, by the way governance and compliance, that's becoming such a mainstream topic. It's not just basically making analytical decisions. How do you make sure your data is safe and secure, you don't want to get basically get hit by all of these cyber attacks, they're all are coming after data. So, governance, compliance of data that's becoming very, so, those-- >> Again you guys are right on the data thing. >> Yeah. >> I want to get your reaction, you mentioned some stats. >> Sure. >> I've got some stats here. Data explosion, 15.3 zettabytes per year >> Yeah, in global traffic. >> Yeah. >> 500 million business data users and growing 20 billion in connected devices, one billion workers will be assisted by machine learning, so, thanks for plugging those stats but I want to get your reaction to some of these other points here. 80% of enterprises are looking at multicloud, their really evaluating where the data sits in that equation >> Sure. And the other thing is the responsibility and role of the Chief Data Officer >> Yes. >> These are new dynamics, I think you guys will be addressing that into the event. >> Absolutely, absolutely. >> Because organizational dynamics, skill gaps are issues but also you have multicloud. So your thoughts on those to. >> That's a big thing, look at, in the old world, John, Hidrantes is always still in large enterprises, right, and it's going to stay here. In fact I think it's not just cloud, think of it this way, on-premise is still here, it's not going a way. It's reducing in scope but then you have this multicloud world, SAS apps, PAS apps, infrastructure, if I'm a customer, I want to do all of it but the biggest problem is that my data is everywhere, how do I make sense of it and then how do I govern it, like my customer data is sitting somewhere in this SAS app, in that platform, on this on-prem application transaction app I'm running, how do I connect the three and how do I make sense it doesn't get, I can have a governance control around it. That's when data management becomes more important but more complex but that's why AI comes in to making it easier. What are the things we've seen a lot, as you touched upon, is the rise of CDO. In fact we have Daniel from Nissan, she is the CDO of Nissan North America, on main stage, talking about her role and how they have leveraged data to transform themselves. That is something we're seeing a lot more because you know, the role of the CDO is making sure that is not only a sense of governance and compliance, a sense of how do we even understand the value of data across an enterprise. Again, I see, one of the things we going to talk about is system thinking around data. We call it System Thinking 3.0, data is becoming a platform. See, there was OSA-D hardware layer whether it is server, or compute, we believe that data is becoming a platform in itself. Whether you think about it in terms of scale, in terms of governance, in terms of AI, in terms of privacy, you have to think of data as a platform. That's the other big thing. >> I think that is a very powerful statement and I like to get your thoughts, we had many conversations on camera, off camera, around product, Silicon Valley, Venture Capital, how can startups create value. On of the old antigens use to be, build a platform, that's your competitive strategy, you were a platform company and that was a strategic competitive advantage. >> Yes. >> That was unique to the company, they created enablement, Facebook is a great example. >> Yeah. >> They monetized all the data from the users, look where they are. >> Sure. >> If you think about platforms today. >> Sure. >> It seems to be table steaks, not as a competitive advantage but more of a foundational. >> Sure. >> Element of all businesses. >> Yeah. >> Not just startups and enterprises. This seems to be a common thread, do you agree with that, that platforms becoming table steaks, 'cause of if we have to think like systems people >> Mm-hmm. >> Whether it's an enterprise. >> Sure. >> Or a supplier, then holistically the platform becomes table steaks on premer or cloud. Your reaction to that. Do you agree? >> No, I think I agree. I'll say it slightly differently, yes. I think platform is a critical component for any enterprise when they think of their end to end technology strategy because you can't do piece meals otherwise you become a system integrator of your own, right? But it's no easy to be a platform player itself, right, because as a platform player, the responsibility of what you have to offer your customer becomes a lot bigger. So, we obviously has this intelligent data platform but the other thing is that the rule of the platform is different too. It has to be very modular and API driven. Nobody wants to buy a monolithic platform. I don't want to, as a enterprise, I don't buy all now, I'm going to implement five years of platform. You want it, it's going to be like a Lego block, okay you, it builds by itself. Not monolithic, very API driven, maybe microservices based and that's our belief that in the new world, yes, platform is very critical for to accelerate your transformational journeys or data driven transformational journeys but the platform better be API driven, microservices based, very nimble that is not a percussor to value creation but creates value as you go along. >> It's all, kind of up to, depends on the customer it could have a thin foundational data platform, from you guys for instance, then what you're saying, compose. >> Of different components. >> On whatever you need. >> For example you have data integration platform, you can do data quality on top, you can do master data management on top, you can provide governance, you can provide privacy, you can do cataloging, it all builds. >> Yeah. >> It's not like, oh my gosh, I have go do all these things over the course of five years, then I get value. You got to create value all along. >> Yeah. >> Today's customers want value like, in two months, three months, you don't want to wait for a year or two. >> This is the excatly the, I think, the operating system, systems mindset. >> Yes. >> You were referring too, this is kind of how enterprises are behaving now. There is the way you see on-premise, >> Yep. >> Thinking around data, cloud, multicloud emerging, it's a systems view distributed computing, with the right Lego blocks. >> That's what our belief is. That's what we heard from customers. See our, I spend most of my time talking to customers and are we trying to understand what customers want today and you know, some of this latent demands that they have, sometimes can't articulate, my job, I always end up on the road most of the time, just hearing customers, that's what they want. They want exactly to your point, a platform that builds, not monolithic, but they do want a platform. They do want to make it easy for them not to do everything piece meal. Every project is a data project. Whether it's a customer experience project, whether it's a governance project, whether it's nothing else but a analytical project, it's a data project. You don't repeat it every time. That's what they want. >> I know you got a hard stop but I want to get your thoughts on this because I have heard the word, workload, mentioned so many more times in the past year, if there was a tag cloud of all theCUBE conversations where the word workload was mentioned, it would be the biggest font. (laughs) >> Yes. >> Workload has been around for a while but now you are seeing more workloads coming on. >> Yeah. >> That's more important for data. >> Yes. >> Workloads being tied into data. >> Absolutely. >> And then sharing data across multiple workloads, that's a big focus, do you see that same thing? >> We absolutely see that and the unique thing we see also is that newer workloads are being created and the old workloads are not going away, which is where the hybrid becomes very important. See, we serve large enterprises and their goal is to have a hybrid. So, you know, I'm running a old transaction workload order here, I want to have a experimental workload, I want to start a new workload, I want all of them to talk to each other, I don't want them to become silos and that's when they look to us to say connect the dots for me, you can be in the cloud, as an example, our cloud platform, you know last time, we talked about a 5 trillion transactions a month, today is double that, eight to ten trillion transactions a month. Growing like crazy but our traditional workload is also still there so we connect the dots for our customers. >> Amit, thank you for coming on sharing your insights, obviously you guys are doing well. You've got 300,000 developers, billions in revenue, thanks for coming on, appreciate the insight and looking forward to your Informatica World. >> Thank you very much. >> Amit Walia here inside theCUBE, with theCUBE conversation, in Palo Alto, thanks for watching.