>> Commentator: Live from Austin, Texas, it's the Cube. Covering KubeCon and CloudNativeCon 2017. Brought to you by Red Hat, the Linux foundation, and the Cube's ecosystem partners. >> Hey welcome back everyone. Live here in Austin, Texas the Cube's exclusive coverage of KubeCon and CloudNativeCon, its third year, not even third year I think it's second year and not even three years old as a community, growing like crazy. Over 4500 people here. Combined the bulk of the shows it's double than it was before. I'm John Ferrier, co-founder of SiliconANGLE. Stu Miniman, analysts here. Next is Gabe Monroy who was lead p.m. product manager for containers for Microsoft Azure, Gabe welcome to the Cube. >> Thanks, glad to be here. Big fan of the show. >> Great to have you on. I mean obviously container madness we've gotten past that now it's Kubernetes madness which really means that the evolution of the industry is really starting to get some clear lines of sight as a straight and narrow if you will people starting to see a path towards scale, developer acceleration, more developers coming in than ever before, this cloud native world. Microsoft's doing pretty well with the cloud right now. Numbers are great, hiring a bunch of people, give us a quick update big news what's going on? >> Yeah so you know a lot of things going on. I'm just excited to be here, I think for me, I'm new to Microsoft right. I came here about seven months ago by way of a Dais acquisition and I like to think of myself as kind of representing part of this new Microsoft trend. My career was built on open source. I started a company called Dais and we were focused on really Kubernetes based solutions and here at Microsoft I'm really doing a lot of the same thing but with Microsoft's Cloud as sort of the vehicle that we're trying to attract developers to. >> What news do you guys have here, some services? >> Yeah so we got a bunch of things, we're talking about so the first is something I'm especially excited about. So this is the virtual kubelet. Now, tell a little bit of story here, I think it's actually kind of fascinating, so back in July we launched this thing called Azure Container Instances and what ACI was first of its kind service containers in the cloud. Just run a container, runs in the cloud. It's micro build and it is invisible infrastructure, so part of the definition of serverless there. As part of that we want to make it clear that if you were going to do complex things with these containers you really need an orchestrator so we released this thing called the ACI Connector for Kubernetes along with it. And we were excited to see people just were so drawn its idea of serverless Kubernetes, Kubernetes that you know didn't have any VMs associated with it and folks at hyper.sh, who have a similar service container offering, they took our code base and forked it and did a version of theirs and you know Brent and I were thinking together when we were like "oh man there's something here, we should explore this" and so we got some engineers together, we put a lot of work together and we announced now, this in conjunction with hyper and others, this virtual kubelet that bridges the world of Kubernetes with the world of these new serverless container runtimes like ACI. >> Okay, can you explain that a little bit. >> Sure. >> People have been coming in saying wait does serverless replace, how does it work, is Kubernetes underneath still? >> Yeah so I think the best place to start is the definition of serverless and I think serverless is really the conflation of three things: it's invisible infrastructure, it is micro billing, and it is an event based programming model. It's sort of the classical definition right. Now what we did with ACI and serverless containers is we took that last one, the event based programming model, and we said look you don't need to do that. If you want to write a container, anything that runs in that container can work, not just functions and so that is I think a really important distinction that I believe it's really the best of serverless is you know that micro billing and invisible infrastructure. >> Well that's built in isn't it? >> Correct yeah. >> What are the biggest challenges of serverless because first of all its [Inaudible 00:03:58] in the mind of a developer who doesn't want to deal with plumbing. >> Yes. >> Meaning networking plumbing, storage, and a lot of the details around configurating, just program away, be creative, spend their time building. >> Yes. >> What is the big differences between that? What are the issues and challenges that service has for people adopting it or is it frictionless at this point? >> Well you know as far I mean it depends on what you're talking about right. So I think you know for functions you know it's very simple to you know get a function service and add your functions and deploy functions and start chaining those together and people are seeing rapid adoption and that's progressing nicely but there's also a contingent of folks who are represented here at the show who are really interested in containers as the primitive and not functions right. Containers are inclusive of lots of things, functions being one of them, betting on containers as like the compute artifact is actually a lot more flexible and solves a lot more use cases. So we're making sure that we can streamline ease of use for that while also bringing the benefits of serverless, really the way I think of this is marrying our AKS, our Managed Kubernetes Service with ACI, our you know serverless containers so you can get to a place where you can have a Kubernetes environment that has no VMs associated with it like literally zero VMs, you'd scale the thing down to zero and when you want to run a pod or container you just pay for a few seconds of time and then you kill it and you stop paying for it right. >> Alright so talk about customers. >> Yep. >> What's the customer experience you guys are going after, did you have any beta customers, who's adopting your approach, and can highlight some examples of some really cool and you don't have to name names or you can, anecdotal data will be good. >> Yeah well you know I think on the blog post announcement blog post page we have a really great video of Siemens Health and Years, I believe is the name, but basically a health care company that is looking, that is using Kubernetes on Azure, AKS specifically, to disrupt the health care market and to benefit real people and you know to me I think it's important that we remember that we're deep in this technology right but at the end of the day this is about helping developers who are in turn helping real world people and I think that video is a good example of that. >> An what was there impact, speed? Speed of developers? >> Yeah, I mean I think it's really the main thing is agility right, people want to move faster right and so that's the main benefit that we hear. I think cost is obviously a concern for folks but I think in practice the people cost of operating some of these systems is tends to be a lot higher than the infrastructure costs when you stack them up, so people are willing to pay a little bit of a premium to make it easier on people and we see that over and over again. >> Yeah Gabe, want you to speak to kind of the speed of company the size of Microsoft. So you know the Dais acquisition of course was already focused on Kubernetes before inside of Microsoft, see I mean big cloud companies moving really fast on Kubernetes. I've heard complaints from customers like "I can't get a good roadmap because it's moving so fast". >> You know I would say that was one of the biggest surprises for me joining Microsoft, is just how fast things move inside of Azure in particular. And I think it's terrific you know. I think that there's a really good focus of making sure that we're meeting customers where they are and building solutions that meet the market but also just executing and delivering and doing that with speed. One of the things that is most interesting to me is like the geographic spread. Microsoft is in so many different regions more than any other cloud. Compliance certification, we take to all that stuff really seriously and being able to do all those things, be the enterprise friendly cloud while also moving at this breakneck pace in terms of innovation, it's really spectacular to watch from the inside. >> A lot of people don't know that. When they think about Azure they think "oh they're copying Amazon" but Microsoft has tons of data centers. They've had browsers, they're all over the world, so it's not like they're foreign to region areas I mean they're everywhere. >> Microsoft is ever and not only is it not foreign but I mean you got to remember Microsoft is an enterprise software company at its core. We know developers, that is what we do and going into cloud in this way is just it's extremely natural for us. And I think that the same can't really be said for everyone who's trying to move into cloud. Like we've got history of working with developers, building platforms, we've entire division devoted to developer tooling right. >> I want to ask you about two things that comes up a lot, one is very trendy, one is kind of not so trendy but super important, one is AI. >> Yes. >> AI with software units impact disrupt storage and with virtual kubelets this is going to be changing storage game buts going to enhance the machine learning and AI capability. The other one is data warehousing or data analytics. Two very important trends, one is certainly a driver for growth and has a lot of sex appeal as the AI machine learning but all the analytics being done on cloud whether it's an IOT device, this is like a nice use case for containers and orchestration. Your comment and reaction for those two trends. >> Yeah and you know I think that AI and deep learning generally is something that we see driving a ton of demand for container orchestration. I've worked lots of customers including folks like OpenAI on there Kubernetes infrastructure running on a Azure today. Something that Elon Musk actually proudly mention, that was a good moment for the containers (chuckling) >> Get a free Tesla. Brokerage some Teslas and get that new one, goes from 0 to 100 and 4.5 seconds. >> Right yeah. >> So you got a good customer, OpenAI, what was the impact of them? What was the big? >> Well you know this is ultimately about empowering people, in this case they happen to be data scientists, to get their job done in a way where I mean I look at it has we're doing our jobs in the infrastructure space if the infrastructure disappears. The more conceptual overhead we're bringing to developers that means we're not doing our job. >> So question then specifically is deep learning in AI, is it enhanced by containers and Kubernetes? >> Absolutely. >> What order of magnitude? >> I don't know but in order of magnitude in enhancement I would argue. >> Just underlying that the really important piece is we're talking about data here >> Yes. >> and one of the things we've been kind of trying to tackle the last couple years of containers is you know storage and that's carried over to Kubernetes, how's Microsoft involved? What's you're you know prognosis as to where we go with cloud native storage? >> Yeah that's a fascinating question and I actually, so back in the early days when I was still contributing to Docker, I was one of the largest external contributors to the Docker Project earlier in my career. I actually wrote some of the storage stuff and so I've been going around Dockers inception 2013 saying don't run databases in containers. It's not cause you can't, right, you can, but just because you can doesn't mean you should (chuckling) >> Exactly. >> and I think that you know as somebody who has worked in my career as on the operation side things like an SLA mean a lot and so this leads me to another one of our announcements at the show which is the Open Service Broker for Azure. Now what we've done, thanks to the Cloud Foundry Foundation who basically took the service broker concept and spun it out, we now are able to take the world of Kubernetes and bridge it to the world of Azure services, data services being sort of some of the most interesting. Now the demo that I like to show this is WordPress which by the way sounds silly but WordPress powers tons of the web today still. WordPress is a PHP application and a MySQL database. Well if you're going to run WordPress at scale you're going to want to run that MySQL in a container? Probably not, you're probably going to want to use something like Azure database for MySQL which comes with an SLA, backup/restore, DR, ops team by Microsoft to manage the whole thing right. So but then the question is well I want to use Kubernetes right so how do I do that right, well with the Open Service Broker for Azure we actually shipped a helm chart. We can helm install Azure WordPress and it will install in Kubernetes the same way you would a container based system and behind the scenes it uses the broker to go spin up a Postgres, sorry a MySQL and dynamically attach it. Now the coolest thing to me about this yeah is the agility but I think that one of the underrated features is the security. The developer who does that doesn't ever touch credentials, the passwords are automatically generated and automatically injected into the application so you get to do things with rotations without ever touching the app. >> So we're at publisher we use WordPress, we'd love, will this help us with scale if we did Azure? >> Absolutely. After this is over we'll go set it up. (laughing) >> I love WordPress but when it breaks down well this is the whole point of where auto scaling shows a little bit of its capabilities in the world is that, PHP does you'd like to have more instances >> Yeah. >> that would be a use case. Okay Redshift in Amazon wasn't talking about much at re:Invent last week. We don't hear a lot of talk around the data warehouse which is a super important way to think about collecting data in cloud and is that going to be an enhanced feature because people want to do analytics. There's a huge analytics audience out there, they're moving off of tera-data. They're doing you guys have a lot of analytics at Microsoft. They might have moved from Hadoop or Hive or somewhere else so there's a lot of analytics workloads that would be prime or at least potentially prime for Kubernetes. >> Yeah I think >> Or is that not fully integrated. >> No I think it's interesting, I mean for us we look at, I personally think using something like the service broker, Open Service Broker API to bridge to something like a data lake or some of these other Azure hosted services is probably the better way of doing that because if you're going to run it on containers, these massive data warehouses, yes you can do it, but the operational burden is high, >> So your point about the >> its really high. >> database earlier. >> Yeah. Same general point there. Now can you do it? Do we see people doing it? Absolutely right. >> Yeah, they do you things sometimes that they shouldn't be doing. >> Yeah and of course back to the deep learning example those are typically big large training models that have similar characteristics. >> Alright as a newbie inside Azure, not new to the industry and the community, >> Yep. >> share some color. What's it like in there? Obviously a number two to Amazon, you guys have great geography presence, you're adding more and more services every day at Azure, what's the vibe, what's the mojo like over there, and share some inside baseball. >> Yeah I got to say so really I'm just saying it's a really exciting place to work. Things are moving so fast, we're growing so fast, customers really want what we're building. Honestly day to day I'm not spending a lot of time looking out I'm spending a lot of time dealing with enterprises who want to use our cloud products. >> And one of the top things that you have on your p.m. list that are the top stack ranked features people want? >> I think a lot of this comes down, in general I think this whole space is approaching a level of enterprise friendliness and enterprise hardening where we want to start adding governance, and adding security, and adding role based access controls across the board and really making this palatable to high trust environment. So I think a lot that's a lot of our focus. >> Stability, ease of use. >> Stability, ease of use are always there. I think the enterprise hardening and things like v-net support for all of our services, v-net service endpoints, those are some things that are high on the list. >> Gabe Monroy, lead product manager for containers at Microsoft Azure Cloud. Great to have you on and love to talk more about geographies and moving apps around the network and multi-cloud but another time, thanks for the time. >> Another time. >> It's the Cube live coverage I'm John Ferrier co-founder of [Inaudible 00:15:21]. Stu Miniman with Wikibon, back with more live coverage after this short break.

>> Announcer: Live from Austin, Texas, It's theCUBE, covering DockerCon 2017. Brought to you by Docker and support from its ecosystem partners. >> Welcome back to theCUBE here in Austin, Texas at DockerCon 2017. I'm Stu Miniman with my cohost for the two days of live broadcast, Jim Kobielus. Happy to welcome back to the program, John Gossman, who is the lead architect with Microsoft Azure. Also part of the keynote this morning. John, had the pleasure of interviewing you two years ago. We went though the obligatory wait, Microsoft Open Source, Linux, and Windows and everything living together. It's like cats and dogs. But thanks so much for joining us again. >> Yeah well as I was saying, that's 14 years in cloud years. So it's been a lot of change in that time, but thanks for having me again. >> Yeah. Absolutely. You said it was three years that you've been working Microsoft and Docker together. 21 years in it, dog or cloud years, if you will. I think Docker is more whales and turtles, as opposed to the dogs. But enough about the cartoons and the animals. Why don't you give our audience just a synopsis of kind of the key messages you were trying to get across in the keynote this morning. >> Okay well the very simple message is that what we enabled this new technology, Hyper-V isolation for Linux containers, is the ability to run Linux containers just seamlessly on Windows using the normal Docker experience. It's just Docker run, BusyBox or Docker run, MySQL, or whatever it is, and it just works. And of course if you know a little more technical detail about containers, you realize that one of the reasons that the containers are the way there are is that all the containers on a box normally share a kernel. And so you can run a Canonical, Ubuntu on user space, on a Red Hat kernel or vice versa. But Windows and Linux kernels are too different. So if you want to run Windows container, it's not going to run easily on Linux and vice versa. And you can still get this effect, if you want it, by also using a virtual machine. But then you've got the management overhead of managing the virtual machine, managing the containers, all the complexity that that involves. You have to get a VHD or AMI or something like that, as well a container image and you lose a lot of that sort of experience. >> John, first of all, I have to say congratulations to Microsoft. When the announcement was made that Windows containers were going to be developed, I have to say that I and most of my peers were a little bit skeptical as to how fast that would work; the development cycle. Probably because we have lots of experience and it's always okay, we understand how many man years this usually takes, but you guys hit and were delivering, got through the Betas, so can you speak to us about where we are with Windows containers? And one of the things people want to kind of understand is, compared to like Linux containers, how do you expect the adoption of that now that it's generally available to roll out? Do I have to wait for the next server refresh, OS refresh, how do you expect your customers to adopt and embrace? >> Well we were able to get this to work so quickly because if you remember, Docker didn't actually invent containers. They took a bunch of kernel primitives that were in Linux and put a really great user experience on it. And I'm not taking anything away from Docker by doing that, because oftentimes in the technology industry, it's easy to make something that was complicated, powerful, but not easy to use. And Windows already had a lot of those kernel primitives, same sort of similar kind of kernel primitives built-in. They had to take out Java javax, I think when Windows 2000. And so it was kind of the same experience. We took the Docker engine, so we got the API, we were using the open source project, so we have complete compatibility. And then we just had to write a basically a new back-end, and that's why it was able to come up rather quickly. And now we're in a mode you know, Windows server updates things more incrementally, than we did in the past. So this will just keep on improving as time goes on. >> Okay, one of the other big announcements in the keynote this morning was LinuxKit. And it was open source project, we actually saw Solomon move it to open source during the keynote, when they laid out the ecosystems for it like IBM, HPE, INTEL and Microsoft. So what does that mean for Microsoft? You are now a provider of Linux? How are we supposed to look at this? >> Yeah. So we're working with all the Linux vendors. So if you saw our blog about the work we did today. We also have announcements from SUSE and Red Hat and Canonical, and the usual people. And one of the things I said in this box, I said look there's the new model is that you could choose both the Linux container that you want and the kernel that you want to run it on. And we're open to all sorts of things. But we have been working with Docker for a long time. On making sure that there was a great experience for running Docker for Linux on Windows. This thing called Docker for Windows. Which they developed. And we have been helping out. And that's basically an earlier generation of this same Linux technology. So it's just the next step on that journey. >> Microsoft's pretty well recognized to have a robust solution for a hybrid cloud. Cause of course you go your Azure stack, that you're putting on premises. There's Azure itself, it's really the cloud first methodology that you've been rolling through and you offer as a service. Containers really anywhere in your environment, baked in anywhere? How should we be thinking about this going forward? >> Yeah absolutely. I mean one of the points of containers in general, one of the attractive parts of containers is that they run everywhere. Including from your laptop, to the various clouds to bare metal, to virtualized environments. And so we have both things. We want Windows containers, where we're the vendor of the container. We want those to work everywhere. And we also, as the vendors of Azure and Azure Stack, and just server system center, and other older enterprise technologies. We want containers to work on all those things. So both directions. I mean, that's kind of the world we're in now, where everything works everywhere. >> Can you square you container strategy as reflected in your partnership with Docker, With your serverless computer strategy for Azure Functions? I'm trying to get a sense for Microsoft's overall approach to running containers as it relates to the Azure strategy. >> In some ways, you can think of this as a serverless functions mode as a step even further. You just deploy a hardware machine and install everything on it. Next thing, you'd have a virtual machine and you install everything. And then you put your code and all its affinities to the container. And with serverless with Azure Functions, it's like, well why do any of that? Just write a function. Now at the same time, we think there's lots of reasons. Under the covers, all of these past systems, going all the way back, that's how Docker started. Run a container underneath the covers. in the same place, it's not literally a Docker container, but the same place down in functions has that sort of a capability. And we're certainly thinking about how Docker can handle for work in that serverless model in the future. >> See one of my core focus areas for Wikibon as an analyst, is looking at developers going more deeply into deep learning and machine learning. To what extent is Microsoft already taking its core tools in that area and containerizing them and enabling access to that functionality through serverless APIs and functions and so forth in Azure? On the serverless stuff, I'm not on the serverless team. I'm not really qualified to explain everything on their end. I do know that the CNT team has a Docker container that they put the bits in. There's the Azure Machine Learning team who's been working a lot of these sort of technologies. I'm just not the right guy to answer that question. >> As you talk to your customers, where does this fit in to the whole discussion? Do containers just happen in the background? Is it helping them with some of their application modernization? Does it help Microsoft change the way we architect things? What's kind of the practitioner, your ultimate end user viewpoint on this? Well cloud adoption is at all points on the curve simultaneously. Even the inside of individual companies. So everybody's in it, in a kind of different place. The two models that I think people have really concentrated on, is on one end, the path at least is infrastructure where you just bring your existing applications and another one would be PADS, where you rewrite the application for a more modern architecture, more cloud centric architecture. And containers fit kind of squarely in the middle of that in some respects. Because in many ways and primarily, I see Docker containers as a better form of infrastructure. It is an easier, more portable way to get all your dependency together and run them everywhere. So a lot of lift-and-shift works is in there, but once you're in containers, it is also easier to break the components apart and put them back together into a more microservice oriented cloud-native model. >> I think that's a great point because we've been having this discussion about okay, there's applications that I'm rewriting, but then I've got this huge amount of applications that I need some way to have the bridge to the future, if you will. Because I don't know, there's one analyst firm that calls it bimodal, but to customers we talked to in general, we don't segment everything we do. I have application type infrastructure and I need to be able to live across multiple environments. Wrapping versus refactoring. >> And they do both. But I always prefer to, you know some people come in and they talk about legacy and they're developers. I'm a developer, right? Developers we always want to rewrite everything. And there's a time and place to doing that. But the legacy applications are required for those applications to work. And if you don't need to refactor that thing, if you can get it into a container or virtual machine or however, and get it into that more environment, and then work around it, re-architect it, it's a whole different set of approaches. It's a good conversation to have with a customer to understand. I've seen people go both too slow, and I see people refactor their whole thing and then try to figure out how to get it to work again. >> So Microsoft has a gigantic user base, What kind of things are you doing to help educate and help the people that had certification or jobs were running exchange to move towards this new kind of world and cloud in general. And containers specifically maybe. >> Well we have a ton of stuff. I'm not familiar with the certification programs myself, but we certainly have our Developer Evangelism team, out going out training people. We've been trying to improve our documentation. And we have a bunch of guidance on cloud migration and things like that. There is a real challenge and it's the same problem for our customers and anybody looking at cloud. Is to re-educate people who have been working in some of their previous moment. Which is another reason again, where the lift and shift stuff is, you can make it more like it is on Premise, or more like it is on your laptop. It makes that journey a little easier. But we're indefinitely in one of those points where the industry is changing so fast, I personally have to spend a lot of time, What's going on? What happened this day? What's new today coming to the conference, I learn new things. >> You bring up a huge challenge that we see. I kind of like Docker has their two delivery models. They've got the Community Edition, CE, and the Enterprise Edition, EE. An EE feels more like traditional software. It's packaged, it's on the regular release cycle. CE is, Solomon talked this morning about the edge pieces. Can I keep up with every six months, or can I have stuff flying at me? People inside of Docker can't keep up with the pace of change that much. What do you see, I mean, I think back to the major Windows operating system releases that we used to, like the Intel tick-tock on releases. It's the pace of change is tough for everyone, how are you helping, you know with you product development and customers, you know, take advantage of things and try to keep up with this rapidly changing ecosystem? >> This is a constant challenge with physically software now. We can't afford to only ever ship things every three years. And at the same time there's stability. So with the major products like Windows, we have these stable branches, where things are pretty much the same going along. And then there's an inactive branch Where things are coming down and the changes and the updates are coming. I'd say the one biggest difference I'd say, but you know I've been in this industry for a long time. So say between the '90s and now, is that we have so much of it is actually off servers. Where when something crashes, we get a crash dump and we can debug the thing and so going out in the field we have much more capability in finding what's going on in the customer base than we did 20 years ago. But other than that, it's just a really hard challenge to both satisfy people that can't have anything to change, and everything changing. >> John you've been watching this for a number of years, what do we still have left to do? We come back to DockerCon next year, you know, we'll have more people, it'll be a bigger event, but you know, what's the progression, what kind of things are you looking forward to the ecosystem and yourself and Docker, knocking down and moving customers forward with? >> The first year was kind of like, what is this thing? Second year was now, the individual Docker container is there now how do you orchestrate them and next step is how do we network these things. And there's an initiative now to standardize on storage, for storage systems and docker containers. Monitoring. There's a lot of things that are still to do. We have a long ways to go. On the other side, I think this other track, which we talked about today, which is that virtualization and containers are going to blur and mend, and I don't think that seven years from now we're going to be talking about containers or virtual machines, we're just going to be saying it's some unit of compute and then there's so much in knobs and tweaks that you want it a little more isolated, you want it a little less isolated, you trade off some performance for something else. >> Business capability, in other words the enterprise architecture framework of business capabilities, will be paramount in terms of composing applications or microservices. From what I understand you saying. >> Yeah, I think where we're really going to get to is a model where people we get past this basics of storage of networking and start working up the next level So things like Helm or DCS Universe, or Storm Stacks, where you can describe more of an application, it just keeps moving up. And so I think in seven years, we won't be talking so much about this, it'll some other disruption, right? But there won't be talking about this virtualization layer as much as building apps again. >> On a visual composition of microservices, what is Microsoft doing, you say that you long ago entered Microsoft during the Vizio acquisition, what's Microsoft doing to enable more visual composition across these functions, across orchestrated team-like environments going forward? >> I think there is some work going on. It's not my area again, on visual composition, despite the fact that I came from Vizio. I kind of got away from that space >> Well I'm betraying my age. I remember that period. >> All right. Well John, always a pleasure catching up with you and thank you so much for joining us for this segment. Look forward to watching Microsoft going forward. >> Thanks. Thank you for having me. We'll be back with lots more coverage here from DockerCon 2017. You're watching theCUBE.

>> Narrator: Live from Las Vegas, Nevada, it's theCUBE covering Accelerate 2017 brought to you by Fortinett. Now, here are your hosts, Lisa Martin and Peter Burris. >> Hi, welcome back to theCUBE. We are SiliconANGLE's flagship program where we go out to the events and extract the signal from the noise. Today, we are with Fortinet at their 2017 Accelerate event in Las Vegas. I'm your host, Lisa Martin, and I'm joined by my cohost, Peter Burris. We are fortunate right now to be joined by George Moore. George is the technology, excuse me, the CSO for Microsoft Azure who is a big technology alliance partner for Fortinet. George, welcome to theCUBE. >> Nice to have you, thank you. >> We are excited to have you on. You are, as you mentioned, the CSO at Azure, but you are the CSO for all of the Azure computer services. You are one of the founders of the Azure engineering team from back in 2006, and we were talking off-line. You hold over 40 patents in things like security deployment, interactive design, et cetera. You are a busy guy. >> I am, yes. (laughing) >> One of the things we have been talking about with our guests on the show today, and a great topic that was in the general session was about the value of data, and how do businesses transform to digital businesses. The value in that data has to be critical. I'd love to get your take on as businesses have to leverage that data to become more successful or to become successful as digital businesses, we know the security of the perimeter is not the only thing. It needs to be with the data. What is Azure doing to secure the cloud for your customers, and how do you help them mitigate or deal with the proliferation of mobile devices and IOT devices that they have that are connecting to their networks? >> Digital disruption is affecting everybody, and it is a huge thing that many companies are struggling to understand and to adopt to their business models, and to really leverage what digital can do for them, and certainly we are doing in the public cloud with Azure helps that significantly. As you mentioned, there is just a proliferation of devices, a proliferation of data, so how do you have defense in depth so you don't have perimeter-based security, but you actually have defense in depth at every level, and at its heart, it really falls down to how do you do encryption at rest, how do you secure the data encrypted? Who holds the keys for the data? What is the proliferation of the keys? How did the controls manage for that? Of course, of the data is encrypted, you really want to be able to do things upon it. You want to be able computer over it. You want to be able to queries, analytics, everything, so there's the question of how to securely exchange the keys? How do you make sure that the right virtual machines are running, the right computers running at the time to do the queries? That's the set of controls and security models and services that we provide in Azure that makes it super easy for customers to actually use that. >> Azure represent what's called the second big transformation for Microsoft where the first one might have been associated with Explorer, those amazing things that Microsoft did to transform itself in the 1990s and it seems to be going pretty well. How is security facilitating this transformation from a customer value proposition? >> Security is absolutely the number one question that every customer has whenever they start talking about the cloud, and so we take that very, very seriously. Microsoft spends over billion dollars a year on all of our security products all up. We have literally armies of people who do nothing every day but wake up and make sure that the product is secure, and that really boils down to two big pieces. One is how do we keep the platform secure from the security control that we have ourselves in the compliance ADA stations and everything to make sure that when customers bring their workloads to us, they are in fact kept secure. Second is a set of security controls that we provide the customers so they can actually secure their workloads, integrate their security models with whatever they're running on premise, and have the right security models, ADA stations, multifactor authentication, identity controls, et cetera for their own workloads. >> Security is very context specific. I'm not necessarily getting into a conversation about industry or whatnot, but in terms of the classifications of services that need to be provided, we were talking a little bit about how some of the services that you provide end being part of the architecture for other services within the Azure cloud. Talk a little bit about how you envision security over time evolving as a way of thinking about how different elements of the cloud are going to be integrated and come together in the role that security is going to play in making that possible and easy. >> You are absolutely right. Azure is composed of, right now, 80 some-odd different services and there's definitely a layering where for example, my components around the compute pieces are used by the higher order of services around HD insight and some of the analytic services and such, and so the security models we have in place internally for compute in turn are used by those higher order services, and the real value we can provide is having a common customer-facing security model for customers, so there is a common way by which they can access the control plane, do management operations upon these services, how they can access the endpoints of the services using a common identity model, a common security model, role-based access control, again, from a common perspective, logging, auditing, reporting, so all this has to be cohesive, correct, and unified so that customers aren't facing this tumultuous array of different services that speak different languages, so to speak. >> We are here at Fortinet Accelerate 2017. Tell us how long Microsoft Azure and Fortinet have been working together, and what are you most excited about with some of the announcements from Fortinet today? >> Microsoft and Fortinet partnership has been going on for quite some time. Specifically in Azure space we've been doing two different, two major thrusts around integration with the Azure Security Center which is a set of services that we have within Azure that provides turnkey access to many, many different vendors including Fortinet as one of our primary partners, and Fortinet also has all their products in Azure marketplace so that customers can readily in a turnkey manner use Fortinet next generation firewalls and such as virtual machines, incorporate those directly within their workloads, and have a very seamless billing model, a very seamless partnership model, a very seamless go-to-market strategy for how we jointly promote, jointly provide the services. >> One of the things that one of our guests was talking with us about today was really about it's an easy sell, if you will, at the C-level to sell the value of investing in the right infrastructure to secure environments. Looking at that in correlation to the fact that there's always historically been a challenge or concerned with security when it comes to enterprises moving workloads to the cloud, I'm curious about this easy-sell position that cyber security and the rise of attacks brings to seeing the adoption of more enterprise workloads. We are seeing numbers that are going to show, or predicting that north of 85% of enterprise workloads will be in the cloud by 2020. How much is Microsoft Azure seeing the fact that cyber security attacks are becoming more and more common, hitting some pretty big targets, affecting a lot of big names. How much are using that as an impetus to and maybe drive that adoption higher and higher from an enterprise perspective? >> Absolutely, I see that everyday. I give many, many talks to the C-level, to CSOs, CEOs, et cetera, and I can say in many industries like the banking industry, financial sector, 18 months ago banks did not have any interest in public cloud. Is just like, "Thank you, we have no interest in cloud," but recently there has been the dawning realization that Azure and the public cloud products are in fact, in many cases, more secure than what the banks and other financial industry sectors can actually provide themselves because we are providing huge amounts of investments from an ongoing basis that we can actually provide better security, better integrated security than what they can afford on premise, so as a result, we are seeing this now, literally, stampede of customers coming to us and saying, "Okay, I get it. "You can actually have a very, very "highly secure environment. "You can provide security controls "that can go well above and beyond "whatever I could do on premise, "and it's better integrated "than what I could ever pull together on premise." >> One of the reasons for that is because of the challenge of finding talent, and you guys can find a really talented person, bring them in, and that person can build security architectures for your cloud that then can be served, can be used by a lot of different customers, so what will be the role of or how will this need for talent in the future, what would be the role for how people engage your people, client's people engage your people to ensure that that people side and moves forward, and how do you keep scaling that is you scale the cloud? >> Certainly people are always the bottleneck in virtually every industry, and specifically within the computing space. The value that we are seeing from customers is that the people that they had previously on premise who were working to secure the base level common infrastructure are now freed because they don't have to do that work. They can do other interesting things at the application level and move their value added further up the stack which means I can innovate more rapidly, they can add more features more quickly, because they are not having to worry about the lower-level infrastructure pieces that are secured by Azure, so we are seeing the dawning realization that we are moving to this new golden age where there is higher degree of agility with respect to innovation happening at the application level, because remember, applications have to be, if you are having a compliant workload, if you are having PCI compliance within the credit card industry for example, you have to have the entire application and its infrastructure part of the compliance boundary, so that means when you are building that app, you have to give your auditors the complete stack for them to pass that. If you are only having to worry about this much as opposed to that much, then the amount of work that you can do, the amount of integration, the amount agility, the amount of innovation you can do at that level is many orders of magnitude higher, so you really see that the value that a lot of customers are having here is that their talented people can be put to use on more important higher order business-related problems as opposed to lower-level infrastructure level issues. >> Let's talk about that for second because one of the things that we see within our research is that the era of cloud as renting virtual machines is starting to transition as people start renting applications, or applications as services that they themselves can start putting together. Partly the reason why that's exciting is because it will liberate more developers. It brings more developers into the process of creating value in the cloud, but as they do that, they now have visibility, or they are going to be doing things that touch an enormous set of resources, so how do you make security easier to developers in Azure? >> The key is that we can do high degrees of integration at the low level between these very services. >> Peter: It goes back to that issue of a cascading of your stuff up into the other Azure services. >> Absolutely, I mean think about it, we sat on top a mountain of information. We have analytics and log files that know about virtually everything that's happening in the cloud, and we can have machine learning, we can have intelligence, we can have machine intelligence and such, that can extract signals from noise that would otherwise be impossible to discover from a single customer's perspective. If you have a low and slow attack by some sort of persistent individual, the fact that they are trying the slow and low attack means that we are able to pull that signal out and extract that information that would not be really physically possible, or economically possible for most companies to do on premise. >> Does this get embedded to some of the toolkits that we are going to use to build these next-generation cloud-based apps? >> It gets embedded into the toolkits, but it also gets embedded at the set of services like the Azure Security Center. A single pane of glass that's integrated with the products from Fortinet and others where the customer can go and have a single view across all their work was running within Azure and get comprehensive alerts and understanding about the analytics that we are able to pull out and provide to those customers. >> What's next? >> Security is an ever evolving field, and the bad guys are always trying new things, so the work that is really happening, a lot of the innovation that's happening is within the analytics, machine learning space around being able to pull more log files out, being able to refine the algorithms and basically being able to provide more AI to the logs themselves so that we can provide integrated alerts, like for example, if you have a kill chain of an individual coming in attacking one of your product, and then using that to the lateral mobility to other products, or other services within your product, we can pull this together in a common log. We can show to customers here's the sequence of this one individual that across three, or four, or five different services. You have top level disability, and we can give you then guidance to say if you insert separation of duties between these two individuals, then you could've broken that kill chain. We can do proactive guidance to customers to help them secure their own workloads even if they necessarily initially were not deployed in a necessarily most secure manner. >> George, we just have a couple of minutes left, but I'd like to get your perspective. You showed a tremendous amount of the accomplishments that Azure has made in public cloud and in security. What are the opportunities for partners to sell and resell Azure services? >> Absolutely. Microsoft has historically always worked incredibly well with partners. We have a very large partner ecosystem. >> Peter: It's the biggest. >> Is the biggest, exactly. Okay, I don't want to brag too much, yes. (laughing) >> That's what I'm here for, George. >> We see specifically in the security space that partners are increasingly, around 40% of their revenue increasingly is coming from cloud-based assets, cloud-based sales. We are setting up the necessary partner channels and partner models where we can make sure that the reseller channels and our partners are an integral part of our environment, and they can get the necessary revenue shares, and we can give them the leads on how the whole system evolves. Absolutely we believe that partners are first and foremost to our success, and we are making deep, deep, deep investments in the partner programs to make that possible. >> Well George, we wish you and Microsoft Azure continued success as well as your partnership with Fortinet. We thank you so much for taking the time to join us on theCUBE today. >> Thank you. >> And for my cohost, Peter Burris, I'm Lisa Martin. Stick around, we will be right back on theCUBE.

>>Okay, we're back with the hybrid Cloud power panel. I'm Dave Ante, and with me our Eric Lockard, who's the corporate vice president of Microsoft Azure Specialized Thomas Corn's, the senior vice president of products at Nutanix. And Indu Carey, who's the Senior Vice President of engineering, NCI and nnc two at Nutanix. Gentlemen, welcome to the cube. Thanks for coming on. >>It's to be >>Here. Have us, >>Eric, let's, let's start with you. We hear so much about cloud first. What's driving the need for hybrid cloud for organizations today? I mean, I not just ev put everything in the public cloud. >>Yeah, well, I mean the public cloud has a bunch of inherent advantages, right? I mean it's, it has effectively infinite capacity, the ability to, you know, innovate without a lot of upfront costs, you know, regions all over the world. So there is a, a trend towards public cloud, but you know, not everything can go to the cloud, especially right away. There's lots of reasons. Customers want to have assets on premise, you know, data gravity, sovereignty and so on. And so really hybrid is the way to achieve the best of both worlds, really to kind of leverage the assets and investments that customers have on premise, but also take advantage of, of the cloud for bursting or regionality or expansion, especially coming outta the pandemic. We saw a lot of this from work from home and, and video conferencing and so on, driving a lot of cloud adoption. So hybrid is really the way that we see customers achieving the best of both worlds. >>Yeah, it makes sense. I wanna, Thomas, if you could talk a little bit, I don't wanna inundate people with the acronyms, but, but the Nutanix cloud clusters on Azure, what is that? What problems does it solve? Give us some color there please. >>Yeah, there, so, you know, cloud clusters on Azure, which we actually call NC two to make it simple and SONC two on Azure is really our solutions for hybrid cloud, right? And you about hybrid cloud, highly desirable customers want it. They, they know this is the right way to do it for them, given that they wanna have workloads on premises at the edge, any public clouds, but it's complicated. It's hard to do, right? And the first thing that you did with just silos, right? You have different infrastructure that you have to go and deal with. You have different teams, different technologies, different areas of expertise and dealing with different portals, networkings get complicated, security gets complicated. And so you heard me say this already, you know, hybrid can be complex. And so what we've done, we then c to Azure is we make that simple, right? We allow teams to go and basically have a solution that allows you to go and take any application running on premises and move it as is to any Azure region where Ncq is available. Once it's running there, you keep the same operating model, right? And that's, so that's actually super valuable to actually go and do this in a simple fashion, do it faster, and basically do hybrid in a more cost effective fashion, know for all your applications. And that's really what's really special about NC two Azure today. >>So Thomas, just a quick follow up on that. So you're, you're, if I understand you correctly, it's an identical experience. Did I get that right? >>This is, this is the key for us, right? Is when you think you're sending on premises, you are used to way of doing things of how you run your applications, how you operate, how you protect them. And what we do here is we extend the Nutanix operating model two workloads running in Azure using the same core stack that you're running on premises, right? So once you have a cluster deploying C to an Azure, it's gonna look like the same cluster that you might be running at the edge or in your own data center using the same tools you, using the same admin constructs to go protect the workloads, make them highly available, do disaster recovery or secure them. All of that becomes the same. But now you are in Azure, and this is what we've spent a lot of time working with Americanist teams on, is you actually have access now to all of those suites of Azure services in from those workloads. So now you get the best of both world, you know, and we bridge them together and you get seamless access of those services between what you get from Nutanix, what you get from Azure. >>Yeah. And as you alluded to, this is traditionally been non-trivial and people have been looking forward to this for, for quite some time. So Indu, I want to understand from an engineering perspective, your team had to work with the Microsoft team, and I'm sure there was this, this is not just a press releases or a PowerPoint, you had to do some some engineering work. So what specific engineering work did you guys do and what's unique about this relative to other solutions in the marketplace? >>So let me start with what's unique about this, and I think Thomas and Eric both did a really good job of describing that the best way to think about what we are delivering jointly with Microsoft is that it speeds of the journey to the public cloud. You know, one way to think about this is moving to the public cloud is sort of like remodeling your house. And when you start remodeling your house, you know, you find that you start with something and before you know it, you're trying to remodel the entire house. And that's a little bit like what journey to the public cloud sort of starts to look like when you start to refactor applications. Because it wasn't, most of the applications out there today weren't designed for the public cloud to begin with. NC two allows you to flip that on its head and say that take your application as is and then lift and shift it to the public cloud, at which point you start the refactor journey. >>And one of the things that you have done really well with the NC two on Azure is that NC two is not something that sits by Azure side. It's fully integrated into the Azure fabric, especially the software defined network and SDN piece. What that means is that, you know, you don't have to worry about connecting your NC two cluster to Azure to some sort of an net worth pipe. You have direct access to the Azure services from the same application that's now running on an NC two cluster. And that makes your refactoring journey so much easier. Your management plan looks the same, your high performance notes let the NVMe notes, they look the same. And really, I mean, other than the facts that you're doing something in the public cloud, all the nutanix's goodness that you're used to continue to receive that, there is a lot of secret sauce that we have had to develop as part of this journey. >>But if we had to pick one that really stands out, it is how do we take the complexity, the network complexity of a public cloud, in this case Azure, and make it as familiar to Nutanix's customers as the VPC construc, the virtual private cloud construc that allows them to really think of that on-prem networking and the public cloud networking in very similar terms. There's a lot more that's gone on behind the scenes. And by the way, I'll tell you a funny sort of anecdote. My dad used to say when I drew up that, you know, if you really want to grow up, you have to do two things. You have to like build a house and you have to marry your kid off to someone. And I would say our dad a third do a flow development with the public cloud provider of the partner. This has been just an absolute amazing journey with Eric and the Microsoft team, and you're very grateful for their >>Support. I, I need NC two for my house. I live in a house that was built in, it's 1687 and we connect all to new and it's, it is a bolt on, but, but, but, and so, but the secret sauce, I mean there's, there's a lot there, but is it a PAs layer? You didn't just wrap it in a container and shove it into the public cloud, You've done more than that. I'm inferring, >>You know, the, it's actually an infrastructure layer offering on top of fid. You can obviously run various types of platform services. So for example, down the road, if you have a containerized application, you'll actually be able to TA it from OnPrem and run it on C two. But the NC two offer itself, the NCAA offer itself is an infrastructure level offering. And the trick is that the storage that you're used to the high performance storage that you know, define tenants to begin with, the hypervisor that you're used to, the network constructs that you're used to light MI segmentation for security purposes, all of them are available to you on NC two in Azure, the same way that we're used to do on-prem. And furthermore, managing all of that through Prism, which is our management interface and management console also remains the same. That makes your security model easier, that makes your management challenge easier, that makes it much easier for an application person or the IT office to be able to report back to the board that they have started to execute on the cloud mandate and they've done that much faster than they'll be able to otherwise. >>Great. Thank you for helping us understand the plumbing. So now Thomas, maybe we can get to like the customers. What, what are you seeing, what are the use cases that are, that are gonna emerge for the solution? >>Yeah, I mean we've, you know, we've had a solution for a while, you know, this is now new on Azure's gonna extend the reach of the solution and get us closer to the type of use cases that are unique to Azure in terms of those solutions for analytics and so forth. But the kind of key use cases for us, the first one you know, talks about it is a migration. You know, we see customers on that cloud journey. They're looking to go and move applications wholesale from on premises to public cloud. You know, we make this very easy because in the end they take the same concept that are around the application and make them, we make them available Now in the Azure region, you can do this for any applications. There's no change to the application, no networking change. The same IP will work the same whether you're running on premises or in Azure. >>The app stays exactly the same, manage the same way, protected the same way. So that's a big one. And you know, the type of drivers point politically or maybe I wanna go do something different or I wanna go and shut down location on premises, I need to do that with a given timeline. I can now move first and then take care of optimizing the application to take advantage of all that Azure has to offer. So migration and doing that in a simple fashion, in a very fast manner is, is a key use case. Another one, and this is classic for leveraging public cloud force, which are doing on premises, is disaster recovery. And something that we refer to as elastic disaster recovery, being able to go and actually configure a secondary site to protect your on premises workloads. But I think that site sitting in Azure as a small site, just enough to hold the data that you're replicating and then use the fact that you cannot get access to resources on demand in Azure to scale out the environment, feed over workloads, run them with performance, potentially fill them back to on premises and then shrink back the environment in Azure to again, optimize cost and take advantage of elasticity that you get from public cloud models. >>And then the last one, building on top of that is just the fact that you cannot get bursting use cases and maybe running a large environment, typically desktop, you know, VDI environments that we see running on premises and I have, you know, a seasonal requirement to go and actually enable more workers to go get access the same solution. You could do this by sizing for the large burst capacity on premises wasting resources during the rest of the year. What we see customers do is optimize what they're running on premises and get access to resources on demand in Azure and basically move the workload and now basically get combined desktop running on premises desktops running on NC two on Azure, same desktop images, same management, same services, and do that as a burst use case during, say you're a retailer that has to go and take care of your holiday season. You know, great use case that we see over and over again for our customers, right? And pretty much complimenting the notion of, look, I wanna go to desktop as a service, but right now, now I don't want to refactor the entire application stack. I just won't be able to get access to resources on demand in the right place at the right time. >>Makes sense. I mean this is really all about supporting customers', digital transformations. We all talk about how that was accelerated during the pandemic and, but the cloud is a fundamental component of the digital transformations. And Eric, you, you guys have obviously made a commitment between Microsoft and and Nutanix to simplify hybrid cloud and that journey to the cloud. How should customers, you know, measure that? What does success look like? What's the ultimate vision here? >>Well, the ultimate vision is really twofold. I think the one is to, you know, first is really to ease a customer's journey to the cloud to allow them to take advantage of all the benefits to the cloud, but to do so without having to rewrite their applications or retrain their, their administrators and or, or to obviate their investment that they already have in platforms like, like Nutanix. And so the, the work that companies have done together here, you know, first and foremost is really to allow folks to come to the cloud in the way that they want to come to the cloud and take really the best of both worlds, right? Leverage, leverage their investment in the capabilities of the Nutanix platform, but do so in conjunction with the advantages and and capabilities of of Azure, you know. Second, it is really to extend some of the cloud capabilities down onto the on-premise infrastructure. And so with investments that we've done together with Azure arc for example, we're really extending the Azure control plane down onto on-premise Nutanix clusters and bringing the capabilities that that provides to the Nutanix customer as well as various Azure services like our data services and Azure SQL server. So it's really kind of coming at the problem from, from two directions. One is from kind of traditional on-prem up into the cloud, and then the second is kind of from the cloud leveraging the investment customers have in in on-premise hci. >>Got it. Thank you. Okay, last question. Maybe each of you could just give us one key takeaway for our audience today. Maybe we start with with with with Thomas and then Indu and then Eric you can bring us home. >>Sure. So the key takeaway is, you know, you takes cloud clusters on Azure is ngi, you know, this is something that we've had tremendous demand from our customers, both from the Microsoft side and the Nutanix side going, going back years literally, right? People have been wanting to go and see this, this is now live GA open for business and you know, we're ready to go and engage and ready to scale, right? This is our first step in a long journey in a very key partnership for us at Nutanix. >>Great Indu >>In our Dave. In a prior life about seven or eight, eight years ago, I was a part of a team that took a popular patch preparation software and moved it to the public cloud. And that was a journey that took us four years and probably several hundred million dollars. And if we had had NC two then it would've saved us half the money, but more importantly would've gotten there in one third the time. And that's really the value of this. >>Okay. Eric, bring us home please. >>Yeah, I'll just point out like this is not something that's just both on or something. We, we, we started yesterday. This is something the teams, both companies have been working on together for, for years really. And it's, it's a way of, of deeply integrating Nutanix into the Azure Cloud and with the ultimate goal of, of again, providing cloud capabilities to the Nutanix customer in a way that they can, you know, take advantage of the cloud and then compliment those applications over time with additional Azure services like storage, for example. So it really is a great on-ramp to the cloud for, for customers who have significant investments in, in Nutanix clusters on premise, >>Love the co-engineering and the ability to take advantage of those cloud native tools and capabilities, real customer value. Thanks gentlemen. Really appreciate your time. >>Thank >>You. Thank you. Thank you. >>Okay, keep it right there. You're watching. Accelerate hybrid cloud, that journey with Nutanix and Microsoft technology on the cube. You're leader in enterprise and emerging tech coverage >>Organizations are increasingly moving towards a hybrid cloud model that contains a mix of on premises public and private clouds. A recent study confirms 83% of businesses agree that hybrid multi-cloud is the ideal operating model. Despite its many benefits, deploying a hybrid cloud can be challenging, complex, slow and expensive require different skills and tool sets and separate siloed management interfaces. In fact, 87% of surveyed enterprises believe that multi-cloud success will require simplified management of mixed infrastructures >>With Nutanix and Microsoft. Your hybrid cloud gets the best of both worlds. The predictable costs, performance control and data sovereignty of a private cloud and the scalability, cloud services, ease of use and fractional economics of the public cloud. Whatever your use case, Nutanix cloud clusters simplifies IT. Operations is faster and lowers risk for migration projects, lowers cloud TCO and provides investment optimization and offers effortless, limitless scale and flexibility. Choose NC two to accelerate your business in the cloud and achieve true hybrid cloud success. Take a free self-guided 30 minute test drive of the solutions provisioning steps and use cases at nutanix.com/azure td. >>Okay, so we're just wrapping up accelerate hybrid cloud with Nutanix and Microsoft made possible by Nutanix where we just heard how Nutanix is partnering with cloud and software leader Microsoft to enable customers to execute on a true hybrid cloud vision with actionable solutions. We pushed and got the answer that with NC two on Azure, you get the same stack, the same performance, the same networking, the same automation, the same workflows across on-prem and Azure Estates. Realizing the goal of simplifying and extending on-prem workloads to any Azure region to move apps without complicated refactoring and to be able to tap the full complement of native services that are available on Azure. Remember, all these videos are available on demand@thecube.net and you can check out silicon angle.com for all the news related to this announcement and all things enterprise tech. Please go to nutanix.com as of course information about this announcement and the partnership, but there's also a ton of resources to better understand the Nutanix product portfolio. There are white papers, videos, and other valuable content, so check that out. This is Dave Ante for Lisa Martin with the Cube, your leader in enterprise and emerging tech coverage. Thanks for watching the program and we'll see you next time.

>>Okay, we're back with the hybrid Cloud power panel. I'm Dave Ante and with me our Eric Lockhart, who's the corporate vice president of Microsoft Azure, Specialized Thomas Corny, the senior vice president of products at Nutanix, and Indu Care, who's the Senior Vice President of engineering, NCI and nnc two at Nutanix. Gentlemen, welcome to the cube. Thanks for coming on. >>It's to >>Be here. Have us, >>Eric, let's, let's start with you. We hear so much about cloud first. What's driving the need for hybrid cloud for organizations today? I mean, I wanna just ev put everything in the public cloud. >>Yeah, well, I mean, the public cloud has a bunch of inherent advantages, right? I mean, it's, it has effectively infinite capacity, the ability to, you know, innovate without a lot of upfront costs, you know, regions all over the world. So there is a, a trend towards public cloud, but you know, not everything can go to the cloud, especially right away. There's lots of reasons. Customers want to have assets on premise, you know, data gravity, sovereignty and so on. And so really hybrid is the way to achieve the best of both worlds, really to kind of leverage the assets and investments that customers have on premise, but also take advantage of, of the cloud for bursting or regionality or expansion, especially coming outta the pandemic. We saw a lot of this from work from home and, and video conferencing and so on, driving a lot of cloud adoption. So hybrid is really the way that we see customers achieving the best of both worlds. >>Yeah, makes sense. I wanna, Thomas, if you could talk a little bit, I don't wanna inundate people with the acronyms, but, but the Nutanix Cloud clusters on Azure, what is that? What problems does it solve? Give us some color there, please. >>That is, so, you know, cloud clusters on Azure, which we actually call NC two to make it simple. And so NC two on Azure is really our solutions for hybrid cloud, right? And you think about the hybrid cloud, highly desirable customers want it. They, they know this is the right way to do for them, given that they wanna have workloads on premises at the edge, any public clouds. But it's complicated. It's hard to do, right? And the first thing that you deal with is just silos, right? You have different infrastructure that you have to go and deal with. You have different teams, different technologies, different areas of expertise and dealing with different portals. Networkings get complicated, security gets complicated. And so you heard me say this already, you know, hybrid can be complex. And so what we've done, we then c to Azure is we make that simple, right? We allow teams to go and basically have a solution that allows you to go and take any application running on premises and move it as is to any Azure region where ncq is available. Once it's running there, you keep the same operating model, right? And that's something actually super valuable to actually go and do this in a simple fashion, do it faster, and basically do, do hybrid in a more cost effective fashion, know for all your applications. And that's really what's really special about NC Azure today. >>So Thomas, just a quick follow up on that. So you're, you're, if I understand you correctly, it's an identical experience. Did I get that right? >>This is, this is the key for us, right? Is when you think you're sending on premises, you are used to way of doing things of how you run your applications, how you operate, how you protect them. And what we do here is we extend the Nutanix operating model two workloads running in Azure using the same core stack that you're running on premises, right? So once you have a cluster deploying C to an Azure, it's gonna look like the same cluster that you might be running at the edge or in your own data center, using the same tools, using, using the same admin constructs to go protect the workloads, make them highly available with disaster recovery or secure them. All of that becomes the same, but now you are in Azure, and this is what we've spent a lot of time working with Americanist teams on, is you actually have access now to all of those suites of Azure services in from those workloads. So now you get the best of both world, you know, and we bridge them together and you get seamless access of those services between what you get from Nutanix, what you get from Azure. >>Yeah. And as you alluded to, this is traditionally been non-trivial and people have been looking forward to this for, for quite some time. So Indu, I want to understand from an engineering perspective, your team had to work with the Microsoft team, and I'm sure there was this, this is not just a press releases or a PowerPoint, you had to do some some engineering work. So what specific engineering work did you guys do and what's unique about this relative to other solutions in the marketplace? >>So let me start with what's unique about this, and I think Thomas and Eric both did a really good job of describing that the best way to think about what we are delivering jointly with Microsoft is that it speeds up the journey to the public cloud. You know, one way to think about this is moving to the public cloud is sort of like remodeling your house. And when you start remodeling your house, you know, you find that you start with something and before you know it, you're trying to remodel the entire house. And that's a little bit like what journey to the public cloud sort of starts to look like when you start to refactor applications. Because it wasn't, most of the applications out there today weren't designed for the public cloud to begin with. NC two allows you to flip that on its head and say that take your application as is and then lift and shift it to the public cloud, at which point you start the refactor journey. >>And one of the things that you have done really well with the NC two on Azure is that NC two is not something that sits by Azure side. It's fully integrated into the Azure fabric, especially the software defined network and SDN piece. What that means is that, you know, you don't have to worry about connecting your NC two cluster to Azure to some sort of a net worth pipe. You have direct access to the Azure services from the same application that's now running on an C2 cluster. And that makes your refactoring journey so much easier. Your management claim looks the same, your high performance notes let the NVMe notes, they look the same. And really, I mean, other than the facts that you're doing something in the public cloud, all the Nutanix goodness that you're used to continue to receive that, there is a lot of secret sauce that we have had to develop as part of this journey. >>But if we had to pick one that really stands out, it is how do we take the complexity, the network complexity, offer public cloud, in this case Azure, and make it as familiar to Nutanix's customers as the VPC construc, the virtual private cloud construct that allows them to really think of their on-prem networking and the public cloud networking in very similar terms. There's a lot more that's gone on behind the scenes. And by the way, I'll tell you a funny sort of anecdote. My dad used to say when I drew up that, you know, if you really want to grow up, you have to do two things. You have to like build a house and you have to marry your kid off to someone. And I would say our dad a third do a code development with the public cloud provider of the partner. This has been just an absolute amazing journey with Eric and the Microsoft team, and you're very grateful for their support. >>I need NC two for my house. I live in a house that was built and it's 1687 and we connect old to new and it's, it is a bolt on, but, but, but, and so, but the secret sauce, I mean there's, there's a lot there, but is it a PAs layer? You didn't just wrap it in a container and shove it into the public cloud, You've done more than that. I'm inferring, >>You know, the, it's actually an infrastructure layer offering on top of fid. You can obviously run various types of platform services. So for example, down the road, if you have a containerized application, you'll actually be able to tat it from OnPrem and run it on C two. But the NC two offer itself, the NCAA often itself is an infrastructure level offering. And the trick is that the storage that you're used to the high performance storage that you know, define Nutanix to begin with, the hypervisor that you're used to, the network constructs that you're used to light MI segmentation for security purposes, all of them are available to you on NC two in Azure, the same way that we're used to do on-prem. And furthermore, managing all of that through Prism, which is our management interface and management console also remains the same. That makes your security model easier, that makes your management challenge easier, that makes it much easier for an accusation person or the IT office to be able to report back to the board that they have started to execute on the cloud mandate and they have done that much faster than they'll be able to otherwise. >>Great. Thank you for helping us understand the plumbing. So now Thomas, maybe we can get to like the customers. What, what are you seeing, what are the use cases that are, that are gonna emerge for this solution? >>Yeah, I mean we've, you know, we've had a solution for a while and you know, this is now new on Azure is gonna extend the reach of the solution and get us closer to the type of use cases that are unique to Azure in terms of those solutions for analytics and so forth. But the kind of key use cases for us, the first one you know, talks about it is a migration. You know, we see customers on the cloud journey, they're looking to go and move applications wholesale from on premises to public cloud. You know, we make this very easy because in the end they take the same culture that are around the application and make them, we make them available Now in the Azure region, you can do this for any applications. There's no change to the application, no networking change. The same IP will work the same whether you're running on premises or in Azure. >>The app stays exactly the same, manage the same way, protected the same way. So that's a big one. And you know, the type of drivers point to politically or maybe I wanna go do something different or I wanna go and shut down education on premises, I need to do that with a given timeline. I can now move first and then take care of optimizing the application to take advantage of all that Azure has to offer. So migration and doing that in a simple fashion, in a very fast manner is, is a key use case. Another one, and this is classic for leveraging public cloud force, which are doing on premises IT disaster recovery and something that we refer to as elastic disaster recovery, being able to go and actually configure a secondary site to protect your on premises workloads, but I that site sitting in Azure as a small site, just enough to hold the data that you're replicating and then use the fact that you cannot get access to resources on demand in Azure to scale out the environment, feed over workloads, run them with performance, potentially feed them back to on premises and then shrink back the environment in Azure to again, optimize cost and take advantage of elasticity that you get from public cloud models. >>Then the last one, building on top of that is just the fact that you cannot get boosting use cases and maybe running a large environment, typically desktop, you know, VDI environments that we see running on premises and I have, you know, a seasonal requirement to go and actually enable more workers to go get access the same solution. You could do this by sizing for the large burst capacity on premises wasting resources during the rest of the year. What we see customers do is optimize what they're running on premises and get access to resources on demand in Azure and basically move the workload and now basically get combined desktops running on premises desktops running on NC two on Azure, same desktop images, same management, same services, and do that as a burst use case during, say you're a retailer that has to go and take care of your holiday season. You know, great use case that we see over and over again for our customers, right? And pretty much complimenting the notion of, look, I wanna go to desktop as a service, but right now I don't want to refactor the entire application stack. I just wanna be able to get access to resources on demand in the right place at the right time. >>Makes sense. I mean this is really all about supporting customers', digital transformations. We all talk about how that was accelerated during the pandemic and, but the cloud is a fundamental component of the digital transformation generic. You, you guys have obviously made a commitment between Microsoft and and Nutanix to simplify hybrid cloud and that journey to the cloud. How should customers, you know, measure that? What does success look like? What's the ultimate vision here? >>Well, the ultimate vision is really twofold. I think the one is to, you know, first is really to ease a customer's journey to the cloud to allow them to take advantage of all the benefits to the cloud, but to do so without having to rewrite their applications or retrain their, their administrators and or or to obviate their investment that they already have and platforms like, like Nutanix. And so the, the work that companies have done together here, you know, first and foremost is really to allow folks to come to the cloud in the way that they want to come to the cloud and take really the best of both worlds, right? Leverage, leverage their investment in the capabilities of the Nutanix platform, but do so in conjunction with the advantages and and capabilities of, of Azure. You know, Second is really to extend some of the cloud capabilities down onto the on-premise infrastructure. And so with investments that we've done together with Azure arc for example, we're really extending the Azure control plane down onto on premise Nutanix clusters and bringing the capabilities that that provides to the, the Nutanix customer as well as various Azure services like our data services and Azure SQL server. So it's really kind of coming at the problem from, from two directions. One is from kind of traditional on-premise up into the cloud and then the second is kind of from the cloud leveraging the investment customers have in in on-premise hci. >>Got it. Thank you. Okay, last question. Maybe each of you can just give us one key takeaway for our audience today. Maybe we start with with with with Thomas and then Indu and then Eric you can bring us home. >>Sure. So the key takeaway is, you know, Nutanix Cloud clusters on Azure is now ga you know, this is something that we've had tremendous demand from our customers, both from the Microsoft side and the Nutanix side going, going back years literally, right? People have been wanting to go and see this, this is now live GA open for business and you know, we're ready to go and engage and ready to scale, right? This is our first step in a long journey in a very key partnership for us at Nutanix. >>Great Indu >>In our Dave. In a prior life about seven or eight, eight years ago, I was a part of a team that took a popular cat's preparation software and moved it to the public cloud. And that was a journey that took us four years and probably several hundred million. And if we had had NC two then it would've saved us half the money, but more importantly would've gotten there in one third the time. And that's really the value of this. >>Okay. Eric, bring us home please. >>Yeah, I'll just point out like this is not something that's just both on or something. We, we, we started yesterday. This is something the teams, both companies have been working on together for, for years, really. And it's, it's a way of, of deeply integrating Nutanix into the Azure Cloud and with the ultimate goal of, of again, providing cloud capabilities to the Nutanix customer in a way that they can, you know, take advantage of the cloud and then compliment those applications over time with additional Azure services like storage, for example. So it really is a great on-ramp to the cloud for, for customers who have significant investments in, in Nutanix clusters on premise, >>Love the co-engineering and the ability to take advantage of those cloud native tools and capabilities, real customer value. Thanks gentlemen. Really appreciate your time. >>Thank >>You. Thank you. >>Okay. Keep it right there. You're watching Accelerate Hybrid Cloud, that journey with Nutanix and Microsoft technology on the cube. You're a leader in enterprise and emerging tech coverage.

(gentle music) >> Okay, we're back with the hybrid cloud power panel. I'm Dave Vellante, and with me Eric Lockard who is the Corporate Vice President of Microsoft Azure Specialized. Thomas Cornely is the Senior Vice President of Products at Nutanix and Indu Keri, who's the Senior Vice President of Engineering, NCI and NC2 at Nutanix. Gentlemen, welcome to The Cube. Thanks for coming on. >> It's good to be here. >> Thanks for having us. >> Eric, let's, let's start with you. We hear so much about cloud first. What's driving the need for hybrid cloud for organizations today? I mean, I want to just put everything in the public cloud. >> Yeah, well, I mean the public cloud has a bunch of inherent advantages, right? I mean it's, it has effectively infinite capacity the ability to, you know, innovate without a lot of upfront costs, you know, regions all over the world. So there is a trend towards public cloud, but you know not everything can go to the cloud, especially right away. There's lots of reasons. Customers want to have assets on premise you know, data gravity, sovereignty and so on. And so really hybrid is the way to achieve the best of both worlds, really to kind of leverage the assets and investments that customers have on premise but also take advantage of the cloud for bursting, originality or expansion especially coming out of the pandemic. We saw a lot of this from work from home and and video conferencing and so on driving a lot of cloud adoption. So hybrid is really the way that we see customers achieving the best of both worlds. >> Yeah, makes sense. I want to, Thomas, if you could talk a little bit I don't want to inundate people with the acronyms, but the Nutanix Cloud clusters on Azure, what is that? What problems does it solve? Give us some color there, please. >> Yeah, so, you know, cloud clusters on Azure which we actually call NC2 to make it simple. And so NC2 on Azure is really our solutions for hybrid cloud, right? And you think about hybrid cloud highly desirable, customers want it. They, they know this is the right way to do it for them given that they want to have workloads on premises at the edge, any public clouds, but it's complicated. It's hard to do, right? And the first thing that you deal with is just silos, right? You have different infrastructure that you have to go and deal with. You have different teams, different technologies, different areas of expertise. And dealing with different portals, networking get complicated, security gets complicated. And so you heard me say this already, you know hybrid can be complex. And so what we've done we then NC2 Azure is we make that simple, right? We allow teams to go and basically have a solution that allows you to go and take any application running on premises and move it as-is to any Azure region where NC2 is available. Once it's running there you keep the same operating model, right? And that's, so that actually super valuable to actually go and do this in a simple fashion. Do it faster, and basically do hybrid in a more (indistinct) fashion know for all your applications. And that's what's really special about NC2 today. >> So Thomas, just a quick follow up on that. So you're, you're, if I understand you correctly it's an identical experience. Did I get that right? >> This is the key for us, right? When you think you're sitting on premises you are used to way of doing things of how you run your applications, how you operate, how you protect them. And what we do here is we extend the Nutanix operating model to workloads running in Azure using the same core stack that you're running on premises, right? So once you have a cluster, deploy in NC2 Azure, it's going to look like the same cluster that you might be running at the edge or in your own data center, using the same tools, using the same admin constructs to go protect the workloads make them highly available do disaster recovery or secure them. All of that becomes the same. But now you are in Azure, and this is what we've spent a lot of time working with Eric and his teams on is you actually have access now to all of those suites of Azure services (indistinct) from those workloads. So now you get the best of both world, you know and we bridge them together and you to get seamless access of those services between what you get from Nutanix, what you get from Azure. >> Yeah. And as you alluded to this is traditionally been non-trivial and people have been looking forward to this for quite some time. So Indu, I want to understand from an engineering perspective, your team had to work with the Microsoft team, and I'm sure there was this is not just a press release, this is, or a PowerPoint you had to do some some engineering work. So what specific engineering work did you guys do and what's unique about this relative to other solutions in the marketplace? >> So let me start with what's unique about this. And I think Thomas and Eric both did a really good job of describing that. The best way to think about what we are delivering jointly with Microsoft is that it speeds up the journey to the public cloud. You know, one way to think about this is moving to the public cloud is sort of like remodeling your house. And when you start remodeling your house, you know, you find that you start with something and before you know it, you're trying to remodel the entire house. And that's a little bit like what journey to the public cloud sort of starts to look like when you start to refactor applications. Because it wasn't, most of the applications out there today weren't designed for the public cloud to begin with. NC2 allows you to flip that on its head and say that take your application as-is and then lift and shift it to the public cloud at which point you start the refactor journey. And one of the things that you have done really well with the NC2 on Azure is that NC2 is not something that sits by Azure side. It's fully integrated into the Azure fabric especially the software-defined networking, SDN piece. What that means is that, you know you don't have to worry about connecting your NC2 cluster to Azure to some sort of a network pipe. You have direct access to the Azure services from the same application that's now running on an NC2 cluster. And that makes your refactor journey so much easier. Your management claim looks the same, your high performance notes let the NVMe notes they look the same. And really, I mean, other than the fact that you're doing something in the public cloud all the Nutanix goodness that you're used to continue to receive that. There is a lot of secret sauce that we have had to develop as part of this journey. But if we had to pick one that really stands out it is how do we take the complexity, the network complexity offer public cloud, in this case Azure and make it as familiar to Nutanix's customers as the VPC, the virtual private cloud (indistinct) that allows them to really think of their on-prem networking and the public cloud networking in very similar terms. There's a lot more that's done on behind the scenes. And by the way, I'll tell you a funny sort of anecdote. My dad used to say when I grew up that, you know if you really want to grow up, you have to do two things. You have to like build a house and you have to marry your kid off to someone. And I would say our dad a third, do a cloud development with the public cloud provider of the partner. This has been just an absolute amazing journey with Eric and the Microsoft team and we're very grateful for their support. >> I need NC2 for my house. I live in a house that was built and it's 1687 and we connect all the new and it is a bolt on, but the secret sauce, I mean there's, there's a lot there but is it a (indistinct) layer. You didn't just wrap it in a container and shove it into the public cloud. You've done more than that, I'm inferring. >> You know, the, it's actually an infrastructure layer offering on top of (indistinct). You can obviously run various types of platform services. So for example, down the road if you have a containerized application you'll actually be able to take it from on prem and run it on NC2. But the NC2 offer itself, the NC2 offering itself is an infrastructure level offering. And the trick is that the storage that you're used to the high performance storage that you know define Nutanix to begin with the hypervisor that you're used to the network constructs that you're used to light micro segmentation for security purposes, all of them are available to you on NC2 in Azure the same way that we're used to do on-prem. And furthermore, managing all of that through Prism, which is our management interface and management console also remains the same. That makes your security model easier that makes your management challenge easier that makes it much easier for an application person or the IT office to be able to report back to the board that they have started to execute on the cloud mandate and they've done that much faster than they would be able to otherwise. >> Great. Thank you for helping us understand the plumbing. So now Thomas, maybe we can get to like the customers. What, what are you seeing, what are the use cases that are that are going to emerge for this solution? >> Yeah, I mean we've, you know we've had a solution for a while and you know this is now new on Azure is going to extend the reach of the solution and get us closer to the type of use cases that are unique to Azure in terms of those solutions for analytics and so forth. But the kind of key use cases for us the first one you know, talks about it is a migration. You know, we see customers on that cloud journey. They're looking to go and move applications wholesale from on premises to public cloud. You know, we make this very easy because in the end they take the same culture that were around the application and we make them available now in the Azure region. You can do this for any applications. There's no change to the application, no networking change the same IP constraint will work the same whether you're running on premises or in Azure. The app stays exactly the same manage the same way, protected the same way. So that's a big one. And you know, the type of drivers for (indistinct) maybe I want to go do something different or I want to go and shut down the location on premises I need to do that with a given timeline. I can now move first and then take care of optimizing the application to take advantage of all that Azure has to offer. So migration and doing that in a simple fashion in a very fast manner is, is a key use case. Another one, and this is classic for leveraging public cloud force, which we're doing on premises IT disaster recovery and something that we refer to as Elastic disaster recovery, being able to go and actually configure a secondary site to protect your on premises workloads. But I think that site sitting in Azure as a small site just enough to hold the data that you're replicating and then use the fact that you cannot get access to resources on demand in Azure to scale out the environment feed over workloads, run them with performance potentially fill them back to on premises, and then shrink back the environment in Azure to again optimize cost and take advantage of the elasticity that you get from public cloud models. Then the last one, building on top of that is just the fact that you cannot get bursting use cases and maybe running a large environment, typically desktop, you know, VDI environments that we see running on premises and I have, you know, a seasonal requirement to go and actually enable more workers to go get access the same solution. You could do this by sizing for the large burst capacity on premises wasting resources during the rest of the year. What we see customers do is optimize what they're running on premises and get access to resources on demand in Azure and basically move the workloads and now basically get combined desktops running on premises desktops running on NC2 on Azure same desktop images, same management, same services and do that as a burst use case during say you're a retailer that has to go and take care of your holiday season. You know, great use case that we see over and over again for our customers, right? And pretty much complimenting the notion of, look I want to go to desktop as a service, but right now I don't want to refactor the entire application stack. I just want to be able to get access to resources on demand in the right place at the right time. >> Makes sense. I mean this is really all about supporting customer's, digital transformations. We all talk about how that was accelerated during the pandemic and but the cloud is a fundamental component of the digital transformations generic. You, you guys have obviously made a commitment between Microsoft and Nutanix to simplify hybrid cloud and that journey to the cloud. How should customers, you know, measure that? What does success look like? What's the ultimate vision here? >> Well, the ultimate vision is really twofold, I think. The one is to, you know first is really to ease a customer's journey to the cloud to allow them to take advantage of all the benefits to the cloud, but to do so without having to rewrite their applications or retrain their administrators and or to obviate their investment that they already have and platforms like Nutanix. And so the work that companies have done together here, you know, first and foremost is really to allow folks to come to the cloud in the way that they want to come to the cloud and take really the best of both worlds, right? Leverage their investment in the capabilities of the Nutanix platform, but do so in conjunction with the advantages and capabilities of Azure. You know, second is really to extend some of the cloud capabilities down onto the on-premise infrastructure. And so with investments that we've done together with Azure arc for example, we're really extending the Azure control plane down onto on-premise Nutanix clusters and bringing the capabilities that provides to the Nutanix customer as well as various Azure services like our data services and Azure SQL server. So it's really kind of coming at the problem from two directions. One is from kind of traditional on-premise up into the cloud, and then the second is kind of from the cloud leveraging the investment customers have in on-premise HCI. >> Got it. Thank you. Okay, last question. Maybe each of you could just give us one key takeaway for our audience today. Maybe we start with Thomas and then Indu and then Eric you can bring us home. >> Sure. So the key takeaway is, you know, cloud customers on Azure is now GA you know, this is something that we've had tremendous demand from our customers both from the Microsoft side and the Nutanix side going back years literally, right? People have been wanting to go and see this this is now live GA open for business and you know we're ready to go and engage and ready to scale, right? This is our first step in a long journey in a very key partnership for us at Nutanix. >> Great, Indu. >> In our day, in a prior life about seven or eight years ago, I was a part of a team that took a popular text preparation software and moved it to the public cloud. And that was a journey that took us four years and probably several hundred million dollars. And if we had NC2 then it would've saved us half the money, but more importantly would've gotten there in one third the time. And that's really the value of this. >> Okay. Eric, bring us home please. >> Yeah, I'll just point out that, this is not something that's just bought on or something we started yesterday. This is something the teams both companies have been working on together for years really. And it's a way of deeply integrating Nutanix into the Azure Cloud. And with the ultimate goal of again providing cloud capabilities to the Nutanix customer in a way that they can, you know take advantage of the cloud and then compliment those applications over time with additional Azure services like storage, for example. So it really is a great on-ramp to the cloud for customers who have significant investments in Nutanix clusters on premise. >> Love the co-engineering and the ability to take advantage of those cloud native tools and capabilities, real customer value. Thanks gentlemen. Really appreciate your time. >> Thank you. >> Thank you. >> Okay. Keep it right there. You're watching accelerate hybrid cloud, that journey with Nutanix and Microsoft technology on The Cube, your leader in enterprise and emerging tech coverage. (gentle music)

>>Time series data is any data that's stamped in time in some way that could be every second, every minute, every five minutes, every hour, every nanosecond, whatever it might be. And typically that data comes from sources in the physical world like devices or sensors, temperature, gauges, batteries, any device really, or things in the virtual world could be software, maybe it's software in the cloud or data and containers or microservices or virtual machines. So all of these items, whether in the physical or virtual world, they're generating a lot of time series data. Now time series data has been around for a long time, and there are many examples in our everyday lives. All you gotta do is punch up any stock, ticker and look at its price over time and graphical form. And that's a simple use case that anyone can relate to and you can build timestamps into a traditional relational database. >>You just add a column to capture time and as well, there are examples of log data being dumped into a data store that can be searched and captured and ingested and visualized. Now, the problem with the latter example that I just gave you is that you gotta hunt and Peck and search and extract what you're looking for. And the problem with the former is that traditional general purpose databases they're designed as sort of a Swiss army knife for any workload. And there are a lot of functions that get in the way and make them inefficient for time series analysis, especially at scale. Like when you think about O T and edge scale, where things are happening super fast, ingestion is coming from many different sources and analysis often needs to be done in real time or near real time. And that's where time series databases come in. >>They're purpose built and can much more efficiently support ingesting metrics at scale, and then comparing data points over time, time series databases can write and read at significantly higher speeds and deal with far more data than traditional database methods. And they're more cost effective instead of throwing processing power at the problem. For example, the underlying architecture and algorithms of time series databases can optimize queries and they can reclaim wasted storage space and reuse it. At scale time, series databases are simply a better fit for the job. Welcome to moving the world with influx DB made possible by influx data. My name is Dave Valante and I'll be your host today. Influx data is the company behind InfluxDB. The open source time series database InfluxDB is designed specifically to handle time series data. As I just explained, we have an exciting program for you today, and we're gonna showcase some really interesting use cases. >>First, we'll kick it off in our Palo Alto studios where my colleague, John furrier will interview Evan Kaplan. Who's the CEO of influx data after John and Evan set the table. John's gonna sit down with Brian Gilmore. He's the director of IOT and emerging tech at influx data. And they're gonna dig into where influx data is gaining traction and why adoption is occurring and, and why it's so robust. And they're gonna have tons of examples and double click into the technology. And then we bring it back here to our east coast studios, where I get to talk to two practitioners, doing amazing things in space with satellites and modern telescopes. These use cases will blow your mind. You don't want to miss it. So thanks for being here today. And with that, let's get started. Take it away. Palo Alto. >>Okay. Today we welcome Evan Kaplan, CEO of influx data, the company behind influx DB. Welcome Evan. Thanks for coming on. >>Hey John, thanks for having me >>Great segment here on the influx DB story. What is the story? Take us through the history. Why time series? What's the story >><laugh> so the history history is actually actually pretty interesting. Um, Paul dicks, my partner in this and our founder, um, super passionate about developers and developer experience. And, um, he had worked on wall street building a number of time series kind of platform trading platforms for trading stocks. And from his point of view, it was always what he would call a yak shave, which means you had to do a ton of work just to start doing work, which means you had to write a bunch of extrinsic routines. You had to write a bunch of application handling on existing relational databases in order to come up with something that was optimized for a trading platform or a time series platform. And he sort of, he just developed this real clear point of view is this is not how developers should work. And so in 2013, he went through why Combinator and he built something for, he made his first commit to open source in flu DB at the end of 2013. And, and he basically, you know, from my point of view, he invented modern time series, which is you start with a purpose-built time series platform to do these kind of workloads. And you get all the benefits of having something right outta the box. So a developer can be totally productive right away. >>And how many people in the company what's the history of employees and stuff? >>Yeah, I think we're, I, you know, I always forget the number, but it's something like 230 or 240 people now. Um, the company, I joined the company in 2016 and I love Paul's vision. And I just had a strong conviction about the relationship between time series and IOT. Cuz if you think about it, what sensors do is they speak time, series, pressure, temperature, volume, humidity, light, they're measuring they're instrumenting something over time. And so I thought that would be super relevant over long term and I've not regretted it. >>Oh no. And it's interesting at that time, go back in the history, you know, the role of databases, well, relational database is the one database to rule the world. And then as clouds started coming in, you starting to see more databases, proliferate types of databases and time series in particular is interesting. Cuz real time has become super valuable from an application standpoint, O T which speaks time series means something it's like time matters >>Time. >>Yeah. And sometimes data's not worth it after the time, sometimes it worth it. And then you get the data lake. So you have this whole new evolution. Is this the momentum? What's the momentum, I guess the question is what's the momentum behind >>You mean what's causing us to grow. So >>Yeah, the time series, why is time series >>And the >>Category momentum? What's the bottom line? >>Well, think about it. You think about it from a broad, broad sort of frame, which is where, what everybody's trying to do is build increasingly intelligent systems, whether it's a self-driving car or a robotic system that does what you want to do or a self-healing software system, everybody wants to build increasing intelligent systems. And so in order to build these increasing intelligent systems, you have to instrument the system well, and you have to instrument it over time, better and better. And so you need a tool, a fundamental tool to drive that instrumentation. And that's become clear to everybody that that instrumentation is all based on time. And so what happened, what happened, what happened what's gonna happen? And so you get to these applications like predictive maintenance or smarter systems. And increasingly you want to do that stuff, not just intelligently, but fast in real time. So millisecond response so that when you're driving a self-driving car and the system realizes that you're about to do something, essentially you wanna be able to act in something that looks like real time, all systems want to do that, want to be more intelligent and they want to be more real time. And so we just happen to, you know, we happen to show up at the right time in the evolution of a >>Market. It's interesting near real time. Isn't good enough when you need real time. >><laugh> yeah, it's not, it's not. And it's like, and it's like, everybody wants, even when you don't need it, ironically, you want it. It's like having the feature for, you know, you buy a new television, you want that one feature, even though you're not gonna use it, you decide that your buying criteria real time is a buying criteria >>For, so you, I mean, what you're saying then is near real time is getting closer to real time as possible, as fast as possible. Right. Okay. So talk about the aspect of data, cuz we're hearing a lot of conversations on the cube in particular around how people are implementing and actually getting better. So iterating on data, but you have to know when it happened to get, know how to fix it. So this is a big part of how we're seeing with people saying, Hey, you know, I wanna make my machine learning algorithms better after the fact I wanna learn from the data. Um, how does that, how do you see that evolving? Is that one of the use cases of sensors as people bring data in off the network, getting better with the data knowing when it happened? >>Well, for sure. So, so for sure, what you're saying is, is, is none of this is non-linear, it's all incremental. And so if you take something, you know, just as an easy example, if you take a self-driving car, what you're doing is you're instrumenting that car to understand where it can perform in the real world in real time. And if you do that, if you run the loop, which is I instrumented, I watch what happens, oh, that's wrong? Oh, I have to correct for that. I correct for that in the software. If you do that for a billion times, you get a self-driving car, but every system moves along that evolution. And so you get the dynamic of, you know, of constantly instrumenting watching the system behave and do it. And this and sets up driving car is one thing. But even in the human genome, if you look at some of our customers, you know, people like, you know, people doing solar arrays, people doing power walls, like all of these systems are getting smarter. >>Well, let's get into that. What are the top applications? What are you seeing for your, with in, with influx DB, the time series, what's the sweet spot for the application use case and some customers give some >>Examples. Yeah. So it's, it's pretty easy to understand on one side of the equation that's the physical side is sensors are sensors are getting cheap. Obviously we know that and they're getting the whole physical world is getting instrumented, your home, your car, the factory floor, your wrist, watch your healthcare, you name it. It's getting instrumented in the physical world. We're watching the physical world in real time. And so there are three or four sweet spots for us, but, but they're all on that side. They're all about IOT. So they're think about consumer IOT projects like Google's nest todo, um, particle sensors, um, even delivery engines like rapid who deliver the Instacart of south America, like anywhere there's a physical location do and that's on the consumer side. And then another exciting space is the industrial side factories are changing dramatically over time. Increasingly moving away from proprietary equipment to develop or driven systems that run operational because what, what has to get smarter when you're building, when you're building a factory is systems all have to get smarter. And then, um, lastly, a lot in the renewables sustainability. So a lot, you know, Tesla, lucid, motors, Cola, motors, um, you know, lots to do with electric cars, solar arrays, windmills, arrays, just anything that's gonna get instrumented that where that instrumentation becomes part of what the purpose >>Is. It's interesting. The convergence of physical and digital is happening with the data IOT. You mentioned, you know, you think of IOT, look at the use cases there, it was proprietary OT systems. Now becoming more IP enabled internet protocol and now edge compute, getting smaller, faster, cheaper AI going to the edge. Now you have all kinds of new capabilities that bring that real time and time series opportunity. Are you seeing IOT going to a new level? What was the, what's the IOT where's the IOT dots connecting to because you know, as these two cultures merge yeah. Operations, basically industrial factory car, they gotta get smarter, intelligent edge is a buzzword, but I mean, it has to be more intelligent. Where's the, where's the action in all this. So the >>Action, really, it really at the core, it's at the developer, right? Because you're looking at these things, it's very hard to get an off the shelf system to do the kinds of physical and software interaction. So the actions really happen at the developer. And so what you're seeing is a movement in the world that, that maybe you and I grew up in with it or OT moving increasingly that developer driven capability. And so all of these IOT systems they're bespoke, they don't come out of the box. And so the developer, the architect, the CTO, they define what's my business. What am I trying to do? Am I trying to sequence a human genome and figure out when these genes express theself or am I trying to figure out when the next heart rate monitor's gonna show up on my apple watch, right? What am I trying to do? What's the system I need to build. And so starting with the developers where all of the good stuff happens here, which is different than it used to be, right. Used to be you'd buy an application or a service or a SA thing for, but with this dynamic, with this integration of systems, it's all about bespoke. It's all about building >>Something. So let's get to the developer real quick, real highlight point here is the data. I mean, I could see a developer saying, okay, I need to have an application for the edge IOT edge or car. I mean, we're gonna have, I mean, Tesla's got applications of the car it's right there. I mean, yes, there's the modern application life cycle now. So take us through how this impacts the developer. Does it impact their C I C D pipeline? Is it cloud native? I mean, where does this all, where does this go to? >>Well, so first of all, you're talking about, there was an internal journey that we had to go through as a company, which, which I think is fascinating for anybody who's interested is we went from primarily a monolithic software that was open sourced to building a cloud native platform, which means we had to move from an agile development environment to a C I C D environment. So to a degree that you are moving your service, whether it's, you know, Tesla monitoring your car and updating your power walls, right. Or whether it's a solar company updating the arrays, right. To degree that that service is cloud. Then increasingly remove from an agile development to a C I C D environment, which you're shipping code to production every day. And so it's not just the developers, all the infrastructure to support the developers to run that service and that sort of stuff. I think that's also gonna happen in a big way >>When your customer base that you have now, and as you see, evolving with infl DB, is it that they're gonna be writing more of the application or relying more on others? I mean, obviously there's an open source component here. So when you bring in kind of old way, new way old way was I got a proprietary, a platform running all this O T stuff and I gotta write, here's an application. That's general purpose. Yeah. I have some flexibility, somewhat brittle, maybe not a lot of robustness to it, but it does its job >>A good way to think about this is versus a new way >>Is >>What so yeah, good way to think about this is what, what's the role of the developer slash architect CTO that chain within a large, within an enterprise or a company. And so, um, the way to think about it is I started my career in the aerospace industry <laugh> and so when you look at what Boeing does to assemble a plane, they build very, very few of the parts. Instead, what they do is they assemble, they buy the wings, they buy the engines, they assemble, actually, they don't buy the wings. It's the one thing they buy the, the material for the w they build the wings, cuz there's a lot of tech in the wings and they end up being assemblers smart assemblers of what ends up being a flying airplane, which is pretty big deal even now. And so what, what happens with software people is they have the ability to pull from, you know, the best of the open source world. So they would pull a time series capability from us. Then they would assemble that with, with potentially some ETL logic from somebody else, or they'd assemble it with, um, a Kafka interface to be able to stream the data in. And so they become very good integrators and assemblers, but they become masters of that bespoke application. And I think that's where it goes, cuz you're not writing native code for everything. >>So they're more flexible. They have faster time to market cuz they're assembling way faster and they get to still maintain their core competency. Okay. Their wings in this case, >>They become increasingly not just coders, but designers and developers. They become broadly builders is what we like to think of it. People who start and build stuff by the way, this is not different than the people just up the road Google have been doing for years or the tier one, Amazon building all their own. >>Well, I think one of the things that's interesting is is that this idea of a systems developing a system architecture, I mean systems, uh, uh, systems have consequences when you make changes. So when you have now cloud data center on premise and edge working together, how does that work across the system? You can't have a wing that doesn't work with the other wing kind of thing. >>That's exactly. But that's where the that's where the, you know, that that Boeing or that airplane building analogy comes in for us. We've really been thoughtful about that because IOT it's critical. So our open source edge has the same API as our cloud native stuff that has enterprise on pre edge. So our multiple products have the same API and they have a relationship with each other. They can talk with each other. So the builder builds it once. And so this is where, when you start thinking about the components that people have to use to build these services is that you wanna make sure, at least that base layer, that database layer, that those components talk to each other. >>So I'll have to ask you if I'm the customer. I put my customer hat on. Okay. Hey, I'm dealing with a lot. >>That mean you have a PO for <laugh> >>A big check. I blank check. If you can answer this question only if the tech, if, if you get the question right, I got all this important operation stuff. I got my factory, I got my self-driving cars. This isn't like trivial stuff. This is my business. How should I be thinking about time series? Because now I have to make these architectural decisions, as you mentioned, and it's gonna impact my application development. So huge decision point for your customers. What should I care about the most? So what's in it for me. Why is time series >>Important? Yeah, that's a great question. So chances are, if you've got a business that was, you know, 20 years old or 25 years old, you were already thinking about time series. You probably didn't call it that you built something on a Oracle or you built something on IBM's DB two, right. And you made it work within your system. Right? And so that's what you started building. So it's already out there. There are, you know, there are probably hundreds of millions of time series applications out there today. But as you start to think about this increasing need for real time, and you start to think about increasing intelligence, you think about optimizing those systems over time. I hate the word, but digital transformation. Then you start with time series. It's a foundational base layer for any system that you're gonna build. There's no system I can think of where time series, shouldn't be the foundational base layer. If you just wanna store your data and just leave it there and then maybe look it up every five years. That's fine. That's not time. Series time series is when you're building a smarter, more intelligent, more real time system. And the developers now know that. And so the more they play a role in building these systems, the more obvious it becomes. >>And since I have a PO for you and a big check, yeah. What is, what's the value to me as I, when I implement this, what's the end state, what's it look like when it's up and running? What's the value proposition for me. What's an >>So, so when it's up and running, you're able to handle the queries, the writing of the data, the down sampling of the data, they're transforming it in near real time. So that the other dependencies that a system that gets for adjusting a solar array or trading energy off of a power wall or some sort of human genome, those systems work better. So time series is foundational. It's not like it's, you know, it's not like it's doing every action that's above, but it's foundational to build a really compelling, intelligent system. I think that's what developers and archs are seeing now. >>Bottom line, final word. What's in it for the customer. What's what, what's your, um, what's your statement to the customer? What would you say to someone looking to do something in time series on edge? >>Yeah. So, so it's pretty clear to clear to us that if you're building, if you view yourself as being in the build business of building systems that you want 'em to be increasingly intelligent, self-healing autonomous. You want 'em to operate in real time that you start from time series. But I also wanna say what's in it for us influx what's in it for us is people are doing some amazing stuff. You know, I highlighted some of the energy stuff, some of the human genome, some of the healthcare it's hard not to be proud or feel like, wow. Yeah. Somehow I've been lucky. I've arrived at the right time, in the right place with the right people to be able to deliver on that. That's that's also exciting on our side of the equation. >>Yeah. It's critical infrastructure, critical, critical operations. >>Yeah. >>Yeah. Great stuff, Evan. Thanks for coming on. Appreciate this segment. All right. In a moment, Brian Gilmore director of IOT and emerging technology that influx day will join me. You're watching the cube leader in tech coverage. Thanks for watching >>Time series data from sensors systems and applications is a key source in driving automation and prediction in technologies around the world. But managing the massive amount of timestamp data generated these days is overwhelming, especially at scale. That's why influx data developed influx DB, a time series data platform that collects stores and analyzes data influx DB empowers developers to extract valuable insights and turn them into action by building transformative IOT analytics and cloud native applications, purpose built and optimized to handle the scale and velocity of timestamped data. InfluxDB puts the power in your hands with developer tools that make it easy to get started quickly with less code InfluxDB is more than a database. It's a robust developer platform with integrated tooling. That's written in the languages you love. So you can innovate faster, run in flex DB anywhere you want by choosing the provider and region that best fits your needs across AWS, Microsoft Azure and Google cloud flex DB is fast and automatically scalable. So you can spend time delivering value to customers, not managing clusters, take control of your time series data. So you can focus on the features and functionalities that give your applications a competitive edge. Get started for free with influx DB, visit influx data.com/cloud to learn more. >>Okay. Now we're joined by Brian Gilmore director of IOT and emerging technologies at influx data. Welcome to the show. >>Thank you, John. Great to be here. >>We just spent some time with Evan going through the company and the value proposition, um, with influx DV, what's the momentum, where do you see this coming from? What's the value coming out of this? >>Well, I think it, we're sort of hitting a point where the technology is, is like the adoption of it is becoming mainstream. We're seeing it in all sorts of organizations, everybody from like the most well funded sort of advanced big technology companies to the smaller academics, the startups and the managing of that sort of data that emits from that technology is time series and us being able to give them a, a platform, a tool that's super easy to use, easy to start. And then of course will grow with them is, is been key to us. Sort of, you know, riding along with them is they're successful. >>Evan was mentioning that time series has been on everyone's radar and that's in the OT business for years. Now, you go back since 20 13, 14, even like five years ago that convergence of physical and digital coming together, IP enabled edge. Yeah. Edge has always been kind of hyped up, but why now? Why, why is the edge so hot right now from an adoption standpoint? Is it because it's just evolution, the tech getting better? >>I think it's, it's, it's twofold. I think that, you know, there was, I would think for some people, everybody was so focused on cloud over the last probably 10 years. Mm-hmm <affirmative> that they forgot about the compute that was available at the edge. And I think, you know, those, especially in the OT and on the factory floor who weren't able to take Avan full advantage of cloud through their applications, you know, still needed to be able to leverage that compute at the edge. I think the big thing that we're seeing now, which is interesting is, is that there's like a hybrid nature to all of these applications where there's definitely some data that's generated on the edge. There's definitely done some data that's generated in the cloud. And it's the ability for a developer to sort of like tie those two systems together and work with that data in a very unified uniform way. Um, that's giving them the opportunity to build solutions that, you know, really deliver value to whatever it is they're trying to do, whether it's, you know, the, the out reaches of outer space or whether it's optimizing the factory floor. >>Yeah. I think, I think one of the things you also mentions genome too, dig big data is coming to the real world. And I think I, OT has been kind of like this thing for OT and, and in some use case, but now with the, with the cloud, all companies have an edge strategy now. So yeah, what's the secret sauce because now this is hot, hot product for the whole world and not just industrial, but all businesses. What's the secret sauce. >>Well, I mean, I think part of it is just that the technology is becoming more capable and that's especially on the hardware side, right? I mean, like technology compute is getting smaller and smaller and smaller. And we find that by supporting all the way down to the edge, even to the micro controller layer with our, um, you know, our client libraries and then working hard to make our applications, especially the database as small as possible so that it can be located as close to sort of the point of origin of that data in the edge as possible is, is, is fantastic. Now you can take that. You can run that locally. You can do your local decision making. You can use influx DB as sort of an input to automation control the autonomy that people are trying to drive at the edge. But when you link it up with everything that's in the cloud, that's when you get all of the sort of cloud scale capabilities of parallelized, AI and machine learning and all of that. >>So what's interesting is the open source success has been something that we've talked about a lot in the cube about how people are leveraging that you guys have users in the enterprise users that IOT market mm-hmm <affirmative>, but you got developers now. Yeah. Kind of together brought that up. How do you see that emerging? How do developers engage? What are some of the things you're seeing that developers are really getting into with InfluxDB >>What's? Yeah. Well, I mean, I think there are the developers who are building companies, right? And these are the startups and the folks that we love to work with who are building new, you know, new services, new products, things like that. And, you know, especially on the consumer side of IOT, there's a lot of that, just those developers. But I think we, you gotta pay attention to those enterprise developers as well, right? There are tons of people with the, the title of engineer in, in your regular enterprise organizations. And they're there for systems integration. They're there for, you know, looking at what they would build versus what they would buy. And a lot of them come from, you know, a strong, open source background and they, they know the communities, they know the top platforms in those spaces and, and, you know, they're excited to be able to adopt and use, you know, to optimize inside the business as compared to just building a brand new one. >>You know, it's interesting too, when Evan and I were talking about open source versus closed OT systems, mm-hmm <affirmative> so how do you support the backwards compatibility of older systems while maintaining open dozens of data formats out there? Bunch of standards, protocols, new things are emerging. Everyone wants to have a control plane. Everyone wants to leverage the value of data. How do you guys keep track of it all? What do you guys support? >>Yeah, well, I mean, I think either through direct connection, like we have a product called Telegraph, it's unbelievable. It's open source, it's an edge agent. You can run it as close to the edge as you'd like, it speaks dozens of different protocols in its own, right? A couple of which MQTT B, C U a are very, very, um, applicable to these T use cases. But then we also, because we are sort of not only open source, but open in terms of our ability to collect data, we have a lot of partners who have built really great integrations from their own middleware, into influx DB. These are companies like ke wear and high bite who are really experts in those downstream industrial protocols. I mean, that's a business, not everybody wants to be in. It requires some very specialized, very hard work and a lot of support, um, you know, and so by making those connections and building those ecosystems, we get the best of both worlds. The customers can use the platforms they need up to the point where they would be putting into our database. >>What's some of customer testimonies that they, that share with you. Can you share some anecdotal kind of like, wow, that's the best thing I've ever used. This really changed my business, or this is a great tech that's helped me in these other areas. What are some of the, um, soundbites you hear from customers when they're successful? >>Yeah. I mean, I think it ranges. You've got customers who are, you know, just finally being able to do the monitoring of assets, you know, sort of at the edge in the field, we have a customer who's who's has these tunnel boring machines that go deep into the earth to like drill tunnels for, for, you know, cars and, and, you know, trains and things like that. You know, they are just excited to be able to stick a database onto those tunnel, boring machines, send them into the depths of the earth and know that when they come out, all of that telemetry at a very high frequency has been like safely stored. And then it can just very quickly and instantly connect up to their, you know, centralized database. So like just having that visibility is brand new to them. And that's super important. On the other hand, we have customers who are way far beyond the monitoring use case, where they're actually using the historical records in the time series database to, um, like I think Evan mentioned like forecast things. So for predictive maintenance, being able to pull in the telemetry from the machines, but then also all of that external enrichment data, the metadata, the temperatures, the pressure is who is operating the machine, those types of things, and being able to easily integrate with platforms like Jupyter notebooks or, you know, all of those scientific computing and machine learning libraries to be able to build the models, train the models, and then they can send that information back down to InfluxDB to apply it and detect those anomalies, which >>Are, I think that's gonna be an, an area. I personally think that's a hot area because I think if you look at AI right now, yeah. It's all about training the machine learning albums after the fact. So time series becomes hugely important. Yeah. Cause now you're thinking, okay, the data matters post time. Yeah. First time. And then it gets updated the new time. Yeah. So it's like constant data cleansing data iteration, data programming. We're starting to see this new use case emerge in the data field. >>Yep. Yeah. I mean, I think you agree. Yeah, of course. Yeah. The, the ability to sort of handle those pipelines of data smartly, um, intelligently, and then to be able to do all of the things you need to do with that data in stream, um, before it hits your sort of central repository. And, and we make that really easy for customers like Telegraph, not only does it have sort of the inputs to connect up to all of those protocols and the ability to capture and connect up to the, to the partner data. But also it has a whole bunch of capabilities around being able to process that data, enrich it, reform at it, route it, do whatever you need. So at that point you're basically able to, you're playing your data in exactly the way you would wanna do it. You're routing it to different, you know, destinations and, and it's, it's, it's not something that really has been in the realm of possibility until this point. Yeah. Yeah. >>And when Evan was on it's great. He was a CEO. So he sees the big picture with customers. He was, he kinda put the package together that said, Hey, we got a system. We got customers, people are wanting to leverage our product. What's your PO they're sell. He's selling too as well. So you have that whole CEO perspective, but he brought up this notion that there's multiple personas involved in kind of the influx DB system architect. You got developers and users. Can you talk about that? Reality as customers start to commercialize and operationalize this from a commercial standpoint, you got a relationship to the cloud. Yep. The edge is there. Yep. The edge is getting super important, but cloud brings a lot of scale to the table. So what is the relationship to the cloud? Can you share your thoughts on edge and its relationship to the cloud? >>Yeah. I mean, I think edge, you know, edges, you can think of it really as like the local information, right? So it's, it's generally like compartmentalized to a point of like, you know, a single asset or a single factory align, whatever. Um, but what people do who wanna pro they wanna be able to make the decisions there at the edge locally, um, quickly minus the latency of sort of taking that large volume of data, shipping it to the cloud and doing something with it there. So we allow them to do exactly that. Then what they can do is they can actually downsample that data or they can, you know, detect like the really important metrics or the anomalies. And then they can ship that to a central database in the cloud where they can do all sorts of really interesting things with it. Like you can get that centralized view of all of your global assets. You can start to compare asset to asset, and then you can do those things like we talked about, whereas you can do predictive types of analytics or, you know, larger scale anomaly detections. >>So in this model you have a lot of commercial operations, industrial equipment. Yep. The physical plant, physical business with virtual data cloud all coming together. What's the future for InfluxDB from a tech standpoint. Cause you got open. Yep. There's an ecosystem there. Yep. You have customers who want operational reliability for sure. I mean, so you got organic <laugh> >>Yeah. Yeah. I mean, I think, you know, again, we got iPhones when everybody's waiting for flying cars. Right. So I don't know. We can like absolutely perfectly predict what's coming, but I think there are some givens and I think those givens are gonna be that the world is only gonna become more hybrid. Right. And then, you know, so we are going to have much more widely distributed, you know, situations where you have data being generated in the cloud, you have data gen being generated at the edge and then there's gonna be data generated sort sort of at all points in between like physical locations as well as things that are, that are very virtual. And I think, you know, we are, we're building some technology right now. That's going to allow, um, the concept of a database to be much more fluid and flexible, sort of more aligned with what a file would be like. >>And so being able to move data to the compute for analysis or move the compute to the data for analysis, those are the types of, of solutions that we'll be bringing to the customers sort of over the next little bit. Um, but I also think we have to start thinking about like what happens when the edge is actually off the planet. Right. I mean, we've got customers, you're gonna talk to two of them, uh, in the panel who are actually working with data that comes from like outside the earth, like, you know, either in low earth orbit or you know, all the way sort of on the other side of the universe. Yeah. And, and to be able to process data like that and to do so in a way it's it's we gotta, we gotta build the fundamentals for that right now on the factory floor and in the mines and in the tunnels. Um, so that we'll be ready for that one. >>I think you bring up a good point there because one of the things that's common in the industry right now, people are talking about, this is kind of new thinking is hyper scale's always been built up full stack developers, even the old OT world, Evan was pointing out that they built everything right. And the world's going to more assembly with core competency and IP and also property being the core of their apple. So faster assembly and building, but also integration. You got all this new stuff happening. Yeah. And that's to separate out the data complexity from the app. Yes. So space genome. Yep. Driving cars throws off massive data. >>It >>Does. So is Tesla, uh, is the car the same as the data layer? >>I mean the, yeah, it's, it's certainly a point of origin. I think the thing that we wanna do is we wanna let the developers work on the world, changing problems, the things that they're trying to solve, whether it's, you know, energy or, you know, any of the other health or, you know, other challenges that these teams are, are building against. And we'll worry about that time series data and the underlying data platform so that they don't have to. Right. I mean, I think you talked about it, uh, you know, for them just to be able to adopt the platform quickly, integrate it with their data sources and the other pieces of their applications. It's going to allow them to bring much faster time to market on these products. It's gonna allow them to be more iterative. They're gonna be able to do more sort of testing and things like that. And ultimately it will, it'll accelerate the adoption and the creation of >>Technology. You mentioned earlier in, in our talk about unification of data. Yeah. How about APIs? Cuz developers love APIs in the cloud unifying APIs. How do you view view that? >>Yeah, I mean, we are APIs, that's the product itself. Like everything, people like to think of it as sort of having this nice front end, but the front end is B built on our public APIs. Um, you know, and it, it allows the developer to build all of those hooks for not only data creation, but then data processing, data analytics, and then, you know, sort of data extraction to bring it to other platforms or other applications, microservices, whatever it might be. So, I mean, it is a world of APIs right now and you know, we, we bring a very sort of useful set of them for managing the time series data. These guys are all challenged with. It's >>Interesting. You and I were talking before we came on camera about how, um, data is, feels gonna have this kind of SRE role that DevOps had site reliability engineers, which manages a bunch of servers. There's so much data out there now. Yeah. >>Yeah. It's like reigning data for sure. And I think like that ability to be like one of the best jobs on the planet is gonna be to be able to like, sort of be that data Wrangler to be able to understand like what the data sources are, what the data formats are, how to be able to efficiently move that data from point a to point B and you know, to process it correctly so that the end users of that data aren't doing any of that sort of hard upfront preparation collection storage's >>Work. Yeah. That's data as code. I mean, data engineering is it is becoming a new discipline for sure. And, and the democratization is the benefit. Yeah. To everyone, data science get easier. I mean data science, but they wanna make it easy. Right. <laugh> yeah. They wanna do the analysis, >>Right? Yeah. I mean, I think, you know, it, it's a really good point. I think like we try to give our users as many ways as there could be possible to get data in and get data out. We sort of think about it as meeting them where they are. Right. So like we build, we have the sort of client libraries that allow them to just port to us, you know, directly from the applications and the languages that they're writing, but then they can also pull it out. And at that point nobody's gonna know the users, the end consumers of that data, better than those people who are building those applications. And so they're building these user interfaces, which are making all of that data accessible for, you know, their end users inside their organization. >>Well, Brian, great segment, great insight. Thanks for sharing all, all the complexities and, and IOT that you guys helped take away with the APIs and, and assembly and, and all the system architectures that are changing edge is real cloud is real. Yeah, absolutely. Mainstream enterprises. And you got developer attraction too, so congratulations. >>Yeah. It's >>Great. Well, thank any, any last word you wanna share >>Deal with? No, just, I mean, please, you know, if you're, if you're gonna, if you're gonna check out influx TV, download it, try out the open source contribute if you can. That's a, that's a huge thing. It's part of being the open source community. Um, you know, but definitely just, just use it. I think when once people use it, they try it out. They'll understand very, >>Very quickly. So open source with developers, enterprise and edge coming together all together. You're gonna hear more about that in the next segment, too. Right. Thanks for coming on. Okay. Thanks. When we return, Dave LAN will lead a panel on edge and data influx DB. You're watching the cube, the leader in high tech enterprise coverage. >>Why the startup, we move really fast. We find that in flex DB can move as fast as us. It's just a great group, very collaborative, very interested in manufacturing. And we see a bright future in working with influence. My name is Aaron Seley. I'm the CTO at HBI. Highlight's one of the first companies to focus on manufacturing data and apply the concepts of data ops, treat that as an asset to deliver to the it system, to enable applications like overall equipment effectiveness that can help the factory produce better, smarter, faster time series data. And manufacturing's really important. If you take a piece of equipment, you have the temperature pressure at the moment that you can look at to kind of see the state of what's going on. So without that context and understanding you can't do what manufacturers ultimately want to do, which is predict the future. >>Influx DB represents kind of a new way to storm time series data with some more advanced technology and more importantly, more open technologies. The other thing that influx does really well is once the data's influx, it's very easy to get out, right? They have a modern rest API and other ways to access the data. That would be much more difficult to do integrations with classic historians highlight can serve to model data, aggregate data on the shop floor from a multitude of sources, whether that be P C U a servers, manufacturing execution systems, E R P et cetera, and then push that seamlessly into influx to then be able to run calculations. Manufacturing is changing this industrial 4.0, and what we're seeing is influx being part of that equation. Being used to store data off the unified name space, we recommend InfluxDB all the time to customers that are exploring a new way to share data manufacturing called the unified name space who have open questions around how do I share this new data that's coming through my UNS or my QTT broker? How do I store this and be able to query it over time? And we often point to influx as a solution for that is a great brand. It's a great group of people and it's a great technology. >>Okay. We're now going to go into the customer panel and we'd like to welcome Angelo Fasi. Who's a software engineer at the Vera C Ruben observatory in Caleb McLaughlin whose senior spacecraft operations software engineer at loft orbital guys. Thanks for joining us. You don't wanna miss folks this interview, Caleb, let's start with you. You work for an extremely cool company. You're launching satellites into space. I mean, there, of course doing that is, is highly complex and not a cheap endeavor. Tell us about loft Orbi and what you guys do to attack that problem. >>Yeah, absolutely. And, uh, thanks for having me here by the way. Uh, so loft orbital is a, uh, company. That's a series B startup now, uh, who and our mission basically is to provide, uh, rapid access to space for all kinds of customers. Uh, historically if you want to fly something in space, do something in space, it's extremely expensive. You need to book a launch, build a bus, hire a team to operate it, you know, have a big software teams, uh, and then eventually worry about, you know, a bunch like just a lot of very specialized engineering. And what we're trying to do is change that from a super specialized problem that has an extremely high barrier of access to a infrastructure problem. So that it's almost as simple as, you know, deploying a VM in, uh, AWS or GCP is getting your, uh, programs, your mission deployed on orbit, uh, with access to, you know, different sensors, uh, cameras, radios, stuff like that. >>So that's, that's kind of our mission. And just to give a really brief example of the kind of customer that we can serve. Uh, there's a really cool company called, uh, totem labs who is working on building, uh, IOT cons, an IOT constellation for in of things, basically being able to get telemetry from all over the world. They're the first company to demonstrate indoor T, which means you have this little modem inside a container container that you, that you track from anywhere in the world as it's going across the ocean. Um, so they're, it's really little and they've been able to stay a small startup that's focused on their product, which is the, uh, that super crazy complicated, cool radio while we handle the whole space segment for them, which just, you know, before loft was really impossible. So that's, our mission is, uh, providing space infrastructure as a service. We are kind of groundbreaking in this area and we're serving, you know, a huge variety of customers with all kinds of different missions, um, and obviously generating a ton of data in space, uh, that we've gotta handle. Yeah. >>So amazing Caleb, what you guys do, I, now I know you were lured to the skies very early in your career, but how did you kinda land on this business? >>Yeah, so, you know, I've, I guess just a little bit about me for some people, you know, they don't necessarily know what they wanna do like early in their life. For me, I was five years old and I knew, you know, I want to be in the space industry. So, you know, I started in the air force, but have, uh, stayed in the space industry, my whole career and been a part of, uh, this is the fifth space startup that I've been a part of actually. So, you know, I've, I've, uh, kind of started out in satellites, did spent some time in working in, uh, the launch industry on rockets. Then, uh, now I'm here back in satellites and you know, honestly, this is the most exciting of the difference based startups. That I've been a part of >>Super interesting. Okay. Angelo, let's, let's talk about the Ruben observatory, ver C Ruben, famous woman scientist, you know, galaxy guru. Now you guys the observatory, you're up way up high. You're gonna get a good look at the Southern sky. Now I know COVID slowed you guys down a bit, but no doubt. You continued to code away on the software. I know you're getting close. You gotta be super excited. Give us the update on, on the observatory and your role. >>All right. So yeah, Rubin is a state of the art observatory that, uh, is in construction on a remote mountain in Chile. And, um, with Rubin, we conduct the, uh, large survey of space and time we are going to observe the sky with, uh, eight meter optical telescope and take, uh, a thousand pictures every night with a 3.2 gig up peaks of camera. And we are going to do that for 10 years, which is the duration of the survey. >>Yeah. Amazing project. Now you, you were a doctor of philosophy, so you probably spent some time thinking about what's out there and then you went out to earn a PhD in astronomy, in astrophysics. So this is something that you've been working on for the better part of your career, isn't it? >>Yeah, that's that's right. Uh, about 15 years, um, I studied physics in college, then I, um, got a PhD in astronomy and, uh, I worked for about five years in another project. Um, the dark energy survey before joining rubing in 2015. >>Yeah. Impressive. So it seems like you both, you know, your organizations are looking at space from two different angles. One thing you guys both have in common of course is, is, is software. And you both use InfluxDB as part of your, your data infrastructure. How did you discover influx DB get into it? How do you use the platform? Maybe Caleb, you could start. >>Uh, yeah, absolutely. So the first company that I extensively used, uh, influx DBN was a launch startup called, uh, Astra. And we were in the process of, uh, designing our, you know, our first generation rocket there and testing the engines, pumps, everything that goes into a rocket. Uh, and when I joined the company, our data story was not, uh, very mature. We were collecting a bunch of data in LabVIEW and engineers were taking that over to MATLAB to process it. Um, and at first there, you know, that's the way that a lot of engineers and scientists are used to working. Um, and at first that was, uh, like people weren't entirely sure that that was a, um, that that needed to change, but it's something the nice thing about InfluxDB is that, you know, it's so easy to deploy. So as the, our software engineering team was able to get it deployed and, you know, up and running very quickly and then quickly also backport all of the data that we collected thus far into influx and what, uh, was amazing to see. >>And as kind of the, the super cool moment with influx is, um, when we hooked that up to Grafana Grafana as the visualization platform we used with influx, cuz it works really well with it. Uh, there was like this aha moment of our engineers who are used to this post process kind of method for dealing with their data where they could just almost instantly easily discover data that they hadn't been able to see before and take the manual processes that they would run after a test and just throw those all in influx and have live data as tests were coming. And, you know, I saw them implementing like crazy rocket equation type stuff in influx, and it just was totally game changing for how we tested. >>So Angelo, I was explaining in my open, you know, you could, you could add a column in a traditional RDBMS and do time series, but with the volume of data that you're talking about, and the example of the Caleb just gave you, I mean, you have to have a purpose built time series database, where did you first learn about influx DB? >>Yeah, correct. So I work with the data management team, uh, and my first project was the record metrics that measured the performance of our software, uh, the software that we used to process the data. So I started implementing that in a relational database. Um, but then I realized that in fact, I was dealing with time series data and I should really use a solution built for that. And then I started looking at time series databases and I found influx B. And that was, uh, back in 2018. The another use for influx DB that I'm also interested is the visits database. Um, if you think about the observations we are moving the telescope all the time in pointing to specific directions, uh, in the Skype and taking pictures every 30 seconds. So that itself is a time series. And every point in that time series, uh, we call a visit. So we want to record the metadata about those visits and flex to, uh, that time here is going to be 10 years long, um, with about, uh, 1000 points every night. It's actually not too much data compared to other, other problems. It's, uh, really just a different, uh, time scale. >>The telescope at the Ruben observatory is like pun intended, I guess the star of the show. And I, I believe I read that it's gonna be the first of the next gen telescopes to come online. It's got this massive field of view, like three orders of magnitude times the Hub's widest camera view, which is amazing, right? That's like 40 moons in, in an image amazingly fast as well. What else can you tell us about the telescope? >>Um, this telescope, it has to move really fast and it also has to carry, uh, the primary mirror, which is an eight meter piece of glass. It's very heavy and it has to carry a camera, which has about the size of a small car. And this whole structure weighs about 300 tons for that to work. Uh, the telescope needs to be, uh, very compact and stiff. Uh, and one thing that's amazing about it's design is that the telescope, um, is 300 tons structure. It sits on a tiny film of oil, which has the diameter of, uh, human hair. And that makes an almost zero friction interface. In fact, a few people can move these enormous structure with only their hands. Uh, as you said, uh, another aspect that makes this telescope unique is the optical design. It's a wide field telescope. So each image has, uh, in diameter the size of about seven full moons. And, uh, with that, we can map the entire sky in only, uh, three days. And of course doing operations everything's, uh, controlled by software and it is automatic. Um there's a very complex piece of software, uh, called the scheduler, which is responsible for moving the telescope, um, and the camera, which is, uh, recording 15 terabytes of data every night. >>Hmm. And, and, and Angela, all this data lands in influx DB. Correct. And what are you doing with, with all that data? >>Yeah, actually not. Um, so we are using flex DB to record engineering data and metadata about the observations like telemetry events and commands from the telescope. That's a much smaller data set compared to the images, but it is still challenging because, uh, you, you have some high frequency data, uh, that the system needs to keep up and we need to, to start this data and have it around for the lifetime of the price. Mm, >>Got it. Thank you. Okay, Caleb, let's bring you back in and can tell us more about the, you got these dishwasher size satellites. You're kind of using a multi-tenant model. I think it's genius, but, but tell us about the satellites themselves. >>Yeah, absolutely. So, uh, we have in space, some satellites already that as you said, are like dishwasher, mini fridge kind of size. Um, and we're working on a bunch more that are, you know, a variety of sizes from shoebox to, I guess, a few times larger than what we have today. Uh, and it is, we do shoot to have effectively something like a multi-tenant model where, uh, we will buy a bus off the shelf. The bus is, uh, what you can kind of think of as the core piece of the satellite, almost like a motherboard or something where it's providing the power. It has the solar panels, it has some radios attached to it. Uh, it handles the attitude control, basically steers the spacecraft in orbit. And then we build also in house, what we call our payload hub, which is, has all, any customer payloads attached and our own kind of edge processing sort of capabilities built into it. >>And, uh, so we integrate that. We launch it, uh, and those things, because they're in lower orbit, they're orbiting the earth every 90 minutes. That's, you know, seven kilometers per second, which is several times faster than a speeding bullet. So we've got, we have, uh, one of the unique challenges of operating spacecraft and lower orbit is that generally you can't talk to them all the time. So we're managing these things through very brief windows of time, uh, where we get to talk to them through our ground sites, either in Antarctica or, you know, in the north pole region. >>Talk more about how you use influx DB to make sense of this data through all this tech that you're launching into space. >>We basically previously we started off when I joined the company, storing all of that as Angelo did in a regular relational database. And we found that it was, uh, so slow in the size of our data would balloon over the course of a couple days to the point where we weren't able to even store all of the data that we were getting. Uh, so we migrated to influx DB to store our time series telemetry from the spacecraft. So, you know, that's things like, uh, power level voltage, um, currents counts, whatever, whatever metadata we need to monitor about the spacecraft. We now store that in, uh, in influx DB. Uh, and that has, you know, now we can actually easily store the entire volume of data for the mission life so far without having to worry about, you know, the size bloating to an unmanageable amount. >>And we can also seamlessly query, uh, large chunks of data. Like if I need to see, you know, for example, as an operator, I might wanna see how my, uh, battery state of charge is evolving over the course of the year. I can have a plot and an influx that loads that in a fraction of a second for a year's worth of data, because it does, you know, intelligent, um, I can intelligently group the data by, uh, sliding time interval. Uh, so, you know, it's been extremely powerful for us to access the data and, you know, as time has gone on, we've gradually migrated more and more of our operating data into influx. >>You know, let's, let's talk a little bit, uh, uh, but we throw this term around a lot of, you know, data driven, a lot of companies say, oh, yes, we're data driven, but you guys really are. I mean, you' got data at the core, Caleb, what does that, what does that mean to you? >>Yeah, so, you know, I think the, and the clearest example of when I saw this be like totally game changing is what I mentioned before at Astro where our engineer's feedback loop went from, you know, a lot of kind of slow researching, digging into the data to like an instant instantaneous, almost seeing the data, making decisions based on it immediately, rather than having to wait for some processing. And that's something that I've also seen echoed in my current role. Um, but to give another practical example, uh, as I said, we have a huge amount of data that comes down every orbit, and we need to be able to ingest all of that data almost instantaneously and provide it to the operator. And near real time, you know, about a second worth of latency is all that's acceptable for us to react to, to see what is coming down from the spacecraft and building that pipeline is challenging from a software engineering standpoint. >>Um, our primary language is Python, which isn't necessarily that fast. So what we've done is started, you know, in the, in the goal of being data driven is publish metrics on individual, uh, how individual pieces of our data processing pipeline are performing into influx as well. And we do that in production as well as in dev. Uh, so we have kind of a production monitoring, uh, flow. And what that has done is allow us to make intelligent decisions on our software development roadmap, where it makes the most sense for us to, uh, focus our development efforts in terms of improving our software efficiency. Uh, just because we have that visibility into where the real problems are. Um, it's sometimes we've found ourselves before we started doing this kind of chasing rabbits that weren't necessarily the real root cause of issues that we were seeing. Uh, but now, now that we're being a bit more data driven, there we are being much more effective in where we're spending our resources and our time, which is especially critical to us as we scale to, from supporting a couple satellites, to supporting many, many satellites at >>Once. Yeah. Coach. So you reduced those dead ends, maybe Angela, you could talk about what, what sort of data driven means to, to you and your teams? >>I would say that, um, having, uh, real time visibility, uh, to the telemetry data and, and metrics is, is, is crucial for us. We, we need, we need to make sure that the image that we collect with the telescope, uh, have good quality and, um, that they are within the specifications, uh, to meet our science goals. And so if they are not, uh, we want to know that as soon as possible and then, uh, start fixing problems. >>Caleb, what are your sort of event, you know, intervals like? >>So I would say that, you know, as of today on the spacecraft, the event, the, the level of timing that we deal with probably tops out at about, uh, 20 Hertz, 20 measurements per second on, uh, things like our, uh, gyroscopes, but the, you know, I think the, the core point here of the ability to have high precision data is extremely important for these kinds of scientific applications. And I'll give an example, uh, from when I worked at, on the rocket at Astra there, our baseline data rate that we would ingest data during a test is, uh, 500 Hertz. So 500 samples per second. And in some cases we would actually, uh, need to ingest much higher rate data, even up to like 1.5 kilohertz. So, uh, extremely, extremely high precision, uh, data there where timing really matters a lot. And, uh, you know, I can, one of the really powerful things about influx is the fact that it can handle this. >>That's one of the reasons we chose it, uh, because there's times when we're looking at the results of a firing where you're zooming in, you know, I talked earlier about how on my current job, we often zoom out to look, look at a year's worth of data. You're zooming in to where your screen is preoccupied by a tiny fraction of a second. And you need to see same thing as Angela just said, not just the actual telemetry, which is coming in at a high rate, but the events that are coming out of our controllers. So that can be something like, Hey, I opened this valve at exactly this time and that goes, we wanna have that at, you know, micro or even nanosecond precision so that we know, okay, we saw a spike in chamber pressure at, you know, at this exact moment, was that before or after this valve open, those kind of, uh, that kind of visibility is critical in these kind of scientific, uh, applications and absolutely game changing to be able to see that in, uh, near real time and, uh, with a really easy way for engineers to be able to visualize this data themselves without having to wait for, uh, software engineers to go build it for them. >>Can the scientists do self-serve or are you, do you have to design and build all the analytics and, and queries for your >>Scientists? Well, I think that's, that's absolutely from, from my perspective, that's absolutely one of the best things about influx and what I've seen be game changing is that, uh, generally I'd say anyone can learn to use influx. Um, and honestly, most of our users might not even know they're using influx, um, because what this, the interface that we expose to them is Grafana, which is, um, a generic graphing, uh, open source graphing library that is very similar to influx own chronograph. Sure. And what it does is, uh, let it provides this, uh, almost it's a very intuitive UI for building your queries. So you choose a measurement and it shows a dropdown of available measurements. And then you choose a particular, the particular field you wanna look at. And again, that's a dropdown, so it's really easy for our users to discover. And there's kind of point and click options for doing math aggregations. You can even do like perfect kind of predictions all within Grafana, the Grafana user interface, which is really just a wrapper around the APIs and functionality of the influx provides putting >>Data in the hands of those, you know, who have the context of domain experts is, is key. Angela, is it the same situation for you? Is it self serve? >>Yeah, correct. Uh, as I mentioned before, um, we have the astronomers making their own dashboards because they know what exactly what they, they need to, to visualize. Yeah. I mean, it's all about using the right tool for the job. I think, uh, for us, when I joined the company, we weren't using influx DB and we, we were dealing with serious issues of the database growing to an incredible size extremely quickly, and being unable to like even querying short periods of data was taking on the order of seconds, which is just not possible for operations >>Guys. This has been really formative it's, it's pretty exciting to see how the edge is mountaintops, lower orbits to be space is the ultimate edge. Isn't it. I wonder if you could answer two questions to, to wrap here, you know, what comes next for you guys? Uh, and is there something that you're really excited about that, that you're working on Caleb, maybe you could go first and an Angela, you can bring us home. >>Uh, basically what's next for loft. Orbital is more, more satellites, a greater push towards infrastructure and really making, you know, our mission is to make space simple for our customers and for everyone. And we're scaling the company like crazy now, uh, making that happen, it's extremely exciting and extremely exciting time to be in this company and to be in this industry as a whole, because there are so many interesting applications out there. So many cool ways of leveraging space that, uh, people are taking advantage of. And with, uh, companies like SpaceX and the now rapidly lowering cost, cost of launch, it's just a really exciting place to be. And we're launching more satellites. We are scaling up for some constellations and our ground system has to be improved to match. So there's a lot of, uh, improvements that we're working on to really scale up our control software, to be best in class and, uh, make it capable of handling such a large workload. So >>You guys hiring >><laugh>, we are absolutely hiring. So, uh, I would in we're we need, we have PE positions all over the company. So, uh, we need software engineers. We need people who do more aerospace, specific stuff. So, uh, absolutely. I'd encourage anyone to check out the loft orbital website, if there's, if this is at all interesting. >>All right. Angela, bring us home. >>Yeah. So what's next for us is really, uh, getting this, um, telescope working and collecting data. And when that's happen is going to be just, um, the Lu of data coming out of this camera and handling all, uh, that data is going to be really challenging. Uh, yeah. I wanna wanna be here for that. <laugh> I'm looking forward, uh, like for next year we have like an important milestone, which is our, um, commissioning camera, which is a simplified version of the, of the full camera it's going to be on sky. And so yeah, most of the system has to be working by them. >>Nice. All right, guys, you know, with that, we're gonna end it. Thank you so much, really fascinating, and thanks to influx DB for making this possible, really groundbreaking stuff, enabling value creation at the edge, you know, in the cloud and of course, beyond at the space. So really transformational work that you guys are doing. So congratulations and really appreciate the broader community. I can't wait to see what comes next from having this entire ecosystem. Now, in a moment, I'll be back to wrap up. This is Dave ante, and you're watching the cube, the leader in high tech enterprise coverage. >>Welcome Telegraph is a popular open source data collection. Agent Telegraph collects data from hundreds of systems like IOT sensors, cloud deployments, and enterprise applications. It's used by everyone from individual developers and hobbyists to large corporate teams. The Telegraph project has a very welcoming and active open source community. Learn how to get involved by visiting the Telegraph GitHub page, whether you want to contribute code, improve documentation, participate in testing, or just show what you're doing with Telegraph. We'd love to hear what you're building. >>Thanks for watching. Moving the world with influx DB made possible by influx data. I hope you learn some things and are inspired to look deeper into where time series databases might fit into your environment. If you're dealing with large and or fast data volumes, and you wanna scale cost effectively with the highest performance and you're analyzing metrics and data over time times, series databases just might be a great fit for you. Try InfluxDB out. You can start with a free cloud account by clicking on the link and the resources below. Remember all these recordings are gonna be available on demand of the cube.net and influx data.com. So check those out and poke around influx data. They are the folks behind InfluxDB and one of the leaders in the space, we hope you enjoyed the program. This is Dave Valante for the cube. We'll see you soon.

>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE in ETR. This is "Breaking Analysis" with Dave Vellante. >> Despite all the talk about repatriation, hybrid and multi-Cloud opportunities, and Cloud is an increasingly expensive option for customers, the data continues to show the importance of public Cloud to the digital economy. Moreover, the two leaders, AWS and Azure, are showing signs of accelerated momentum that point to those two giants pulling away from the pack in the years ahead, with each firm's showing broad based momentum across their respective product lines. It's unclear if anything, other than government intervention or self-inflicted wounds will slow these two companies down this decade. Despite their commanding lead, a winning strategy for companies that don't run their own Cloud continues to be innovating on top of their massive CapEx investments. The most notable example here being Snowflake. Hello, everyone. Welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis, we provide our quarterly market share update for the big four hyperscale Cloud providers. And we'll share some new ETR data from their most recent survey. And we'll drill into some of the reasons for the momentum of these two companies and drill further into the database and data warehouse sector to see what, if anything, has changed in that space. First, let's look at some of the noteworthy comments from AWS and Microsoft in their recent earnings updates. We heard from Amazon, the following, "AWS has seen a reacceleration of revenue growth as customers have expanded their commitment to the Cloud and selected AWS as their Cloud partner." Notably, AWS revenues increased 39% in Q3 2021. That's a thousand basis point increase in growth relative to Q3 2020. That's an astounding milestone for a company that we expect to surpass $60 billion in revenue this year. Further, AWS touted the adoption of its custom silicon, and specifically its Graviton2 processors. AWS is fond of emphasizing Graviton's 40% price performance improvements relative to x86 processors, something we've reported on quite extensively. AWS is investing in custom silicon, encouraging ISVs to port their code to the platform so that customers will experience little or no code changes when they migrate. Again, we believe this is a secret weapon for AWS as its cost structure will continue to improve at a rate faster than competitors that don't have the resources or the skills or the stomach to develop such capabilities. Microsoft, for its part, also saw astoundingly good growth of 48% this past quarter for Azure. This is a company that we forecast will approach $40 billion in IaaS and PaaS public Cloud revenue this year. Microsoft's CEO, Satya Nadella, on its earnings call, emphasized the changing nature of Cloud expanding in a distributed fashion to the edge. He referenced Azure as the world's computer. Building on his statements last year that Microsoft is building out a powerful, ubiquitous, intelligent, sensing and predictive Cloud. Yes, folks, it does feel like we're entering the so-called Metaverse, doesn't it? Okay, to underscore the momentum of these two companies, let's take a look at the ETR breakdown of Net score, which measures spending momentum. This chart will be familiar to our listeners. It shows the breakdown of net score for AWS, with the lime green showing new adoptions. That's 11%. The forest green is spending more than 6% relative to the first half of this year. That's a very robust 53%. The gray is flat spending. That's 30% on a very, very large base. And the pink is spending declines of minus 6% or worse. That's 4%. And the bright red is defections i.e those leaving AWS. That's 1%. That's virtually non-existent. You subtract the reds from the greens and you get a net score of 59. Remember, anything over 40, we can still consider to be elevated. Let's look at that same data for Microsoft again. You have some new ads that lime green, that's 7%. The forest green is at 46% of customers spending more, which is an incredible figure for a company with revenues that will in the near term surpass $200 billion. And the red is in the low single digits. Buffered by its enormous PC software profits over the years, Microsoft is powered through its Window's Dogma and transitioned into a Cloud powerhouse. Let's now share some of our latest numbers for the big four hyperscale players, AWS, Azure, Alibaba and Google. Here, we show data for these companies from 2018 and our estimates for 2021. This data includes our final figures for AWS, Azure and GCP for Q3 with Alibaba yet to report. Remember, only AWS and Alibaba report IaaS revenue cleanly with Microsoft and Google, they give us a little breadcrumb nuggets that allow us to triangulate with our survey data and other intelligence. But it's our attempt to do an apples to apples comparison for those four companies using AWS and it's reporting as a baseline. In Q3, AWS reported more than $16 billion in revenue. We estimate Azure at 10 billion, Alibaba, we expect to come in at just under 3 billion, and GCP at 2.5 billion for the quarter. With three quarters of data in, with the exception of Alibaba, we're forecasting AWS to capture 51% of the big four revenue, the hyperscale revenue. And really we believe these are the only four hyperscalers. AWS will surpass 60 billion with Azure just under 40 billion, Alibaba approaching 11 billion, and Google coming in just under 10 billion for the year is our expectation. We forecast these four will account for $120 billion this year. That's a 41% increase over 2020 and the same collective growth rate as 2020 relative to 2019. We expect Azure to be 63% of the size of AWS revenue. So it is gaining share. Both of those companies, however, saw accelerated growth this past quarter with Alibaba and GCP's growth rates decelerating relative to last year. Now, let's take a closer look at those growth rates. This chart shows the quarterly growth rates for each of the four going back to the beginning of 2019. Both GCP and Alibaba are showing dramatic declines in growth rates, whereas, this past quarter Azure saw accelerated growth and AWS has now seen an increased rate of growth for the past two quarters. In fact, AWS' growth is about where it was in 2019 when it was around half of its current revenue size. And in 2019 growth was decelerating through the quarters as you can see where today that trend has reversed. It's quite amazing. All right, let's take a look at the broader Cloud landscape and bring back some ETR data. This chart that we're showing here, it shows net score or spending momentum on the vertical axis and market share or presence in the dataset on the horizontal axis. Note that red dotted line, anything above that we can still consider elevated and impressive. As when we've previously shared this data, AWS and Microsoft Azure are up and to the right. Now remember, this chart is not just counting IaaS and PaaS as we showed you earlier, it's however the customers views whatever they think Cloud is. And so they're likely including Microsoft SaaS in this picture. Which is why Microsoft shows larger than AWS despite what we showed you earlier. Nonetheless, these two are well ahead of the pack and the growth rates indicate that they're pulling away. But we've added some of the other players, most notably VMware Cloud on AWS. It's showing momentum as is VMware Cloud, which is VMware Cloud foundation and other on-prem Cloud offerings, even though it's below the red line for the on-prem piece, it's very respectable. The VMware Cloud on AWS has been consistently up above that red line. Has popped beneath it in some quarters, but it's very, very strong. As is, you know, Red Hat OpenShift, it's a little bit below the line, but it is respectable. We've superimposed this by the way. Red Hat OpenShift in the ETR platform is under the container orchestration taxonomy, but we'd like to put it in next to the Cloud players for context. That's how Red Hat sort of thinks about this as well. They think about OpenShift as Cloud. And then you can see the other players. Alibaba has got a small sample in the ETR dataset. Just does not enough presence in China. But Dell and HPE have started to show up in the Cloud taxonomy. So buyers are associating their private Clouds with Cloud. So Dell's Apex, HPE's GreenLake. So that's a positive. And you can see Oracle, which of course is OCI, Oracle Cloud infrastructure. And then IBM with its public Cloud. So, it's a positive that these on-prem players are showing up in this data, but the reality is the hyperscalers are growing collectively at 40% annually and the on-prem players are growing in the low single digits. So, and if you carve out the IaaS business of AWS and Azure, they're larger than most of the on-premises infrastructure players. And all the on-prem players are moving toward an as a service model, as I just alluded to. So, undoubtedly, hybrid multicloud edge are going to present opportunities for the likes of Dell, HPE, Cisco, VMware, IBM, Red Hat, et cetera. But they also present opportunities for the public Cloud players who have vibrant ecosystems and marketplaces much more diverse and deep than the traditional vendors. You know, we have a clearer picture of Microsoft's sort of hybrid and edge strategy because the company has such an enormous legacy business, it really had to think about that much more deeply. It wasn't a blank sheet of paper like AWS. It's going to be interesting at reinvent this year if new CEO, Adam Selipsky, will talk about this. And it will be good to hear how he's thinking about the next decade, how AWS thinks about hybrid and edge, I guarantee that with their developer affinity and custom Silicon capabilities, they're thinking about it differently than traditional enterprise players. And as we've stressed in this segment, they have across the board momentum. Now to quantify that, let's take a look at AWS as portfolio in the spending momentum within its product segments. This chart shows AWS's net scores or spending momentum in the areas where AWS participates in the ETR taxonomy. Again, note that red line. Anything above 40% is considered an elevated watermark. We're showing data from last October, this past July and the latest October 21 survey. That yellow line or a bar. What's notable is the yellow versus the gray bars up across the board for the most part, other than chime... And by the way, other than chime, everything is above the 40% mark as well. Now, we've highlighted database because we feel it's one of the most strategic sectors in a real battleground. So we want to drill into that a bit. Here's our familiar X Y graph showing Net score on the Y axis, remember, that's, again, spending momentum and market share or pervasiveness in the survey on the horizontal axis. This data, by the way, includes on-prem and Cloud database data warehouse. So keep that in mind. Let's start with one of our favorite topics; Snowflake. We've reported again and again and again, that we've never seen anything like this. The company's net score has moderated ever so slightly this quarter, but it's still just below 80%. Very highly elevated. Well, above that 40% mark. It's Snowflake's presence continues to grow as a gain share in the market. Snowflake is growing revenue in the triple digits. It's an insane pace, hence its current $115 billion market cap as of this episode. Now that said, all three US-based Cloud players there are above the 40% line with AWS and Microsoft having significant presence on the horizontal axis. You see Cockroach Labs, Redis, Couchbase, they're all elevated or highly elevated. Couchbase just went public this summer. So that may help with its presence. MongoDB, they're killing it. They have a $37 billion market cap as of this episode. The stock has been on a tear. You see MariaDB was also in the mix. And then of course you have Oracle, the database leader. Look, they continue to invest in making the Oracle database and other software like MySQL, the best solution for mission critical workloads, and they're investing in their Cloud. But you can see overall, they just don't have the momentum from a spending standpoint that the others do because the declines in their legacy business. And they've been around a long time. Those declines are not fully offset by the growth in Cloud database and Cloud migration. But look, Oracle is a financial powerhouse with a $250 billion plus market cap. And the stock has done very well this past year. Up over 60%. Cloudera is going private. So it can hide the pain of the transitions that it's undergoing between the legacy install bases of Cloudera and Hortonworks. It's just a tough situation. When the companies came together, Cloudera essentially had a dead end. Each of those respective platforms and migrate their customers to a more modern stack as part of its Cloud strategy. Ironic that it's name is Cloudera. You know, that's always a difficult thing to do. So as a private company, Cloudera can maybe get off that 90 day shot clock and buy some time to invest without getting hammered by the street. And you know, Teradata consistently has not shown up well in the ETR dataset. It's transitioned to Cloud and cross-Cloud still hasn't shown momentum in the surveys. So, look right now, it's looking like the rich get richer. So just to quantify that a little bit, let's line up some of the database players and look a little bit more closely at net score. This chart shows the spending momentum or lack thereof with the net score or spending velocity granularity that we described before. Remember, green is spending more, red is spending less, bright red is leaving the platform, bright green is adding the platform. You take red, subtract red from the green, and that gives you a net score. Snowflake, as we said, tops the list. You can see the granularity there. You can compare the performance. In a little different view to understand how these scores are derived, look, the ideal profile is a solid lime green, a big forest green, a not too large gray and ideally little or no bright red AKA defections. And you can see the green funnel in the gray increasing prominence as the vendor momentum declines. Interestingly, with the exception of Cloudera and Teradata, defections are all in the single digits or nonexistent. In the case of Snowflake, Redis, red is no red at all, but small sample, Couchbase has no defections and very little defection for the giant Microsoft. Incredibly impressive. This speaks to how hard it is to migrate off of a database no matter how disgruntled you are. The more common scenario is to isolate the database and build new functionality on modern platforms. Okay, so what to watch out for. Well, reinvent this coming up next month. Oh this month. It's the first time someone other than Andy Jassy will be keynoting as CEO. 15 years of Cloud, this is the 10th re-invent, which is always a market for the direction of the industry. I've said many times that the last decade was largely about IT transformation powered by the Cloud. I believe we're entering a new era of business transformation where the Cloud is going to play a significant role. But the Cloud is evolving from a set of remote services out there in the Cloud to an omnipresent platform on top of which many customers and technology companies can innovate. And virtually every industry will be impacted by Cloud. However it evolves in the coming decade. The question will be, how fast can you go? And how will players like AWS and Microsoft and many others that are building on top of these platforms make it easier for you to go fast? That's what I'll be watching for at re-invent and beyond. Okay, that's a wrap for today. Remember, these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis podcasts. Check out ETR's website at etr.plus. We also publish a full report every week on wikibon.com and siliconangle.com. You can get in touch with me, david.vellante@siliconangle.com. You can DM me @dvellante or comment on our LinkedIn posts. This is Dave Vellante for theCUBE insights powered by ETR. Have a great week, everybody. Stay safe, be well. And we'll see you next time. We'll see you at re-invent. (soft upbeat music)

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante despite all the chatter about cloud repatriation and the exorbitant cost of cloud computing customer spending momentum continues to accelerate in the post-isolation economy if the pandemic was good for the cloud it seems that the benefits of cloud migration remain lasting in the late stages of covid and beyond and we believe this stickiness is going to continue for quite some time we expect i asked revenue for the big four hyperscalers to surpass 115 billion dollars in 2021 moreover the strength of aws specifically as well as microsoft azure remain notable such large organizations showing elevated spending momentum as shown in the etr survey results is perhaps unprecedented in the technology sector hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll share some some fresh july survey data that indicates accelerating momentum for the largest cloud computing firms importantly not only is the momentum broad-based but it's also notable in key strategic sectors namely ai and database there seems to be no stopping the cloud momentum there's certainly plenty of buzz about the cloud tax so-called cloud tax but other than wildly assumptive valuation models and some pockets of anecdotal evidence you don't really see the supposed backlash impacting cloud momentum our forecast calls for the big four hyperscalers aws azure alibaba and gcp to surpass 115 billion as we said in is revenue this year the latest etr survey results show that aws lambda has retaken the lead among all major cloud services tracked in the data set as measured in spending momentum this is the service with the most elevated scores azure overall azure functions vmware cloud on aws and aws overall also demonstrate very highly elevated performance all above that of gcp now impressively aws momentum in the all-important fortune 500 where it has always showed strength is also accelerating one concern in the most recent survey data is that the on-prem clouds and so-called hybrid platforms which we had previously reported as showing an upward spending trajectory seem to have cooled off a bit but the data is mixed and it's a little bit too early to draw firm conclusions nonetheless while hyperscalers are holding steady the spending data appears to be somewhat tepid for the on-prem players you know particularly for their cloud we'll study that further after etr drops its full results on july 23rd now turning our attention back to aws the aws cloud is showing strength across its entire portfolio and we're going to show you that shortly in particular we see notable strength relative to others in analytics ai and the all-important database category aurora and redshift are particularly strong but several other aws database services are showing elevated spending velocity which we'll quantify in a moment all that said snowflake continues to lead all database suppliers in spending momentum by a wide margin which again will quantify in this episode but before we dig into the survey let's take a look at our latest projections for the big four hyperscalers in is as you know we track quarterly revenues for the hyperscalers remember aws and alibaba ias data is pretty clean and reported in their respective earnings reports azure and gcp we have to extrapolate and strip out all a lot of the the apps and other certain revenue to make an apples-to-apples comparison with aws and alibaba and as you can see we have the 2021 market exceeding 115 billion dollars worldwide that's a torrid 35 growth rate on top of 41 in 2020 relative to 2019. aggressive yes but the data continues to point us in this direction until we see some clearer headwinds for the cloud players this is the call we're making aws is perhaps losing a sharepoint or so but it's also is so large that its annual incremental revenue is comparable to alibaba's and google's respective cloud business in total is business in total the big three u.s cloud companies all report at the end of july while alibaba is mid mid-august so we'll update these figures at that time okay let's move on and dig into the survey data we don't have the data yet on alibaba and we're limited as to what we can share until etr drops its research update on on the 23rd but here's a look at the net score timeline in the fortune 500 specifically so we filter the fortune 500 for cloud computing you got azure and the yellow aws and the black and gcp in blue so two points here stand out first is that aws and microsoft are converging and remember the customers who respond to the survey they probably include a fair amount of application software spending in their cloud answers so it favors microsoft in that respect and gcp second point is showing notable deceleration relative to the two leaders and the green call out is because this cut is from an aws point of view so in other words gcp declines are a positive for aws so that's how it should be interpreted now let's take a moment to better understand the idea of net score this is one of the fundamental metrics of the etr methodology here's the data for aws so we use that as a as a reference point net score is calculated by asking customers if they're adding a platform new that's the lime green bar that you see here in the current survey they're asking are you spending six percent or more in the second half relative to the first half of the year that's the forest green they're also asking is spending flat that's the gray or are you spending less that's the pink or are you replacing the platform i.e repatriating so not much spending going on in replacements now in fairness one percent of aws is half a billion dollars so i can see where some folks would get excited about that but in the grand scheme of things it's a sliver so again we don't see repatriation in the numbers okay back to net score subtract the reds from the greens and you get net score which in the case of aws is 61 now just for reference my personal subjective elevated net score level is 40 so anything above that is really impressive based on my experience and to have a company of this size be so elevated is meaningful same for microsoft by the way which is consistently well above the 50 mark in net score in the etr surveys so that's you can think about it that's even more impressive perhaps than aws because it's triple the revenue okay let's stay with aws and take a look at the portfolio and the strength across the board this chart shows net score for the past three surveys serverless is on fire by the way not just aws but azure and gcp functions as well but look at the aws portfolio every category is well above the 40 percent elevated red line the only exception is chime and even chime is showing an uptick and chime is meh if you've ever used chime every other category is well above 50 percent next net score very very strong for aws now as we've frequently reported ai is one of the four biggest focus areas from a spending standpoint along with cloud containers and rpa so it stands to reason that the company with the best ai and ml and the greatest momentum in that space has an advantage because ai is being embedded into apps data processes machines everywhere this chart compares the ai players on two dimensions net score on the vertical axis and market share or presence in the data set on the horizontal axis for companies with more than 15 citations in the survey aws has the highest net score and what's notable is the presence on the horizontal axis databricks is a company where high on also shows elevated scores above both google and microsoft who are showing strength in their own right and then you can see data iq data robot anaconda and salesforce with einstein all above that 40 percent mark and then below you can see the position of sap with leonardo ibm watson and oracle which is well below the 40 line all right let's look at at the all-important database category for a moment and we'll first take a look at the aws database portfolio this chart shows the database services in aws's arsenal and breaks down the net score components with the total net score superimposed on top of the bars point one is aurora is highly elevated with a net score above 70 percent that's due to heavy new adoptions redshift is also very strong as are virtually all aws database offerings with the exception of neptune which is the graph database rds dynamodb elastic document db time stream and quantum ledger database all show momentum above that all important 40 line so while a lot of people criticize the fragmentation of the aws data portfolio and their right tool for the right job approach the spending spending metrics tell a story and that that the strategy is working now let's take a look at the microsoft database portfolio there's a story here similar similar to that of aws azure sql and cosmos db microsoft's nosql distributed database are both very highly elevated as are azure database for mysql and mariadb azure cash for redis and azure for cassandra also microsoft is giving look at microsoft's giving customers a lot of options which is kind of interesting you know we've often said that oracle's strategy because we think about oracle they're building the oracle database cloud we've said oracle strategy should be to not just be the cloud for oracle databases but be the cloud for all databases i mean oracle's got a lot of specialty capability there but it looks like microsoft is beating oracle to that punch not that oracle is necessarily going there but we think it should to expand the appeal of its cloud okay last data chart that we'll show and then and then this one looks at database disruption the chart shows how the cloud database companies are doing in ibm oracle teradata in cloudera accounts the bars show the net score granularity as we described earlier and the etr callouts are interesting so first remember this is an aws this is in an aws context so with 47 responses etr rightly indicates that aws is very well positioned in these accounts with the 68 net score but look at snowflake it has an 81 percent net score which is just incredible and you can see google database is also very strong and the high 50 percent range while microsoft even though it's above the 40 percent mark is noticeably lower than the others as is mongodb with presumably atlas which is surprisingly low frankly but back to snowflake so the etr callout stresses that snowflake doesn't have a strong as strong a presence in the legacy database vendor accounts yet now i'm not sure i would put cloudair in the legacy database category but okay whatever cloudera they're positioning cdp is a hybrid platform as are all the on-prem players with their respective products and platforms but it's going to be interesting to see because snowflake has flat out said it's not straddling the cloud and on-prem rather it's all in on cloud but there is a big opportunity to connect on-prem to the cloud and across clouds which snowflake is pursuing that that ladder the cross-cloud the multi-cloud and snowflake is betting on incremental use cases that involve data sharing and federated governance while traditional players they're protecting their turf at the same time trying to compete in cloud native and of course across cloud i think there's room for both but clearly as we've shown cloud has the spending velocity and a tailwind at its back and aws along with microsoft seem to be getting stronger especially in the all-important categories related to machine intelligence ai and database now to be an essential infrastructure technology player in the data era it would seem obvious that you have to have database and or data management intellectual property in your portfolio or you're going to be less valuable to customers and investors okay we're going to leave it there for today remember these episodes they're all available as podcasts wherever you listen all you do is search breaking analysis podcast and please subscribe to the series check out etr's website at etr dot plus plus etr plus we also publish a full report every week on wikibon.com and siliconangle.com you can get in touch with me david.velante at siliconangle.com you can dm me at d vallante or you can hit hit me up on our linkedin post this is dave vellante for the cube insights powered by etr have a great week stay safe be well and we'll see you next time you

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Mobile World Congress is alive, theCUBE will be there and we'll certainly let you know if it's alive and well when we get on the ground. Now, as we approach a delayed mobile world congress, it's really appropriate to reflect in the state of the telecoms industry. Let's face it. Telcos have done of really good job of keeping us all connected during the pandemic, supporting work from home and that whole pivot, accommodating the rapid shift to landline traffic, securing the network and keeping it up and running but it doesn't change the underlying fundamental dilemma that Telco has faced. Telco is a slow growth, no growth industry, with revenue expectations in the low single digits. And at the same time network traffic continues to grow at 20% annually. And last year it grew at 40% to 50%. Despite these challenges, Telcos are still investing in the future. For example, the Telco industry collectively is selling out more than a trillion dollars in the first half of this decade on 5G and fiber infrastructure. And it's estimated that there are now more than 200 5G networks worldwide. But a lot of questions remain, not the least of which is, can and should Telcos go beyond connectivity and fiber. Can the Telcos actually monetize 5G or whatever's next beyond 5G? Or is that going to be left to the ecosystem? Now what about the ecosystem? How is that evolving? And very importantly, what role will the Cloud Hyperscalers play in Telco? Are they infrastructure on which the Telcos can build or are they going to suck the value out of the market as they have done in the enterprise? Hello everyone, and welcome to this week's Wiki Bond Cube Insights powered by ETR. In this breaking analysis, it's my pleasure to welcome a long time telecoms industry analyst and colleague, and the founding director of Lewis Insight, Mr. Chris Lewis. Chris, welcome to the program. Thanks for coming on >> Dave, it's a pleasure to be here. Thank you for having me. >> It is really our pleasure. So, we're going to cover a lot of ground today. And first thing, we're going to talk about Mobile World Congress. I've never been, you're an expert at that and what we can expect. And then we're going to review the current state of telecoms infrastructure, where it should go. We're going to dig into transformation. Is it a mandate? Is it aspirational? Can Telcos enter adjacent markets in ways they haven't been able to in the past? And then how about the ecosystem? We're going to talk about that, and then obviously we're going to talk about Cloud as I said, and we'll riff a little bit on the tech landscape. So Chris, let's get into it, Mobile World Congress, it's back on, what's Mobile World Congress typically like? What's your expectation this year for the vibe compared to previous events? >> Well Dave, the issue of Mobile World Congress is always that we go down there for a week into Barcelona. We stress ourselves building a matrix of meetings in 30 minutes slots and we return at the end of it trying to remember what we'd been told all the way through. The great thing is that with the last time we had a live, with around 110,000 people there, you could see anyone and everyone you needed to within the mobile, and increasingly the adjacent industry and ecosystem. So, he gave you that once a year, big download of everything new, obviously because it's the Mobile World Congress, a lot of it around devices, but increasingly over the last few years, we saw many, many stands with cars on them because the connected car became an issue, a lot more software oriented players there, but always the Telcos, always the people providing the network infrastructure. Increasingly in the last few years people provided the software and IT infrastructure, but all of these people contributing to what the network should be in the future, what needs to be connected. But of course the reach of the network has been growing. You mentioned during lockdown about connecting people in their homes, well, of course we've also been extending that connection to connect things whether it's in the home or the different devices, monitoring of doorbells and lights and all that sort of stuff. And in the industry environment, connecting all of the robots and sensors. So, actually the perimeter, the remit of the industry to connect has been expanding, and so is the sort of remit of Mobile World Congress. So, we set an awful lot of different suppliers coming in, trying to attach to this enormous market of roughly $1.5 trillion globally. >> Chris, what's the buzz in the industry in terms of who's going to show up. I know a lot of people have pulled out, I've got the Mobile World Congress app and I can see who's attending. And it looks like quite a few people are going to go but what's your expectation? >> Well, from an analyst point of view, obviously I'm mainly keeping up with my clients and trying to get new clients. I'm looking at it and going most of my clients are not attending in person. Now, of course, we need the DSMA, we need Mobile World Congress for future for the industry interaction. But of course, like many people having adopted and adapted to be online, then they're putting a lot of the keynotes online, a lot of the activities will be online. But of course many of the vendors have also produced their independent content and content to actually deliver to us as analysts. So, I'm not sure who will be there. I like you, but you'll be on the ground. You'll be able to report back and let us know exactly who turned up. But from my point of view, I've had so many pre-briefs already, the difference between this year and previous years, I used to get loads of pre-briefs and then have to go do the briefs as well. So this year I've got the pre-brief so I can sit back, put my feet up and wait for your report to come back as to what's happening on the ground. >> You got it. Okay, let's get into a little bit and talk about Telco infrastructure and the state, where it is today, where it's going, Chris, how would you describe the current state of Telco infrastructure? Where does it need to go? Like, what is the ideal future state look like for Telcos in your view? >> So there's always a bit of an identity crisis when it comes to Telco. I think going forward, the connectivity piece was seen as being table stakes, and then people thought where can we go beyond connectivity? And we'll come back to that later. But actually to the connectivity under the scenario I just described of people, buildings, things, and society, we've got to do a lot more work to make that connectivity extend, to be more reliable, to be more secure. So, the state of the network is that we have been building out infrastructure, which includes fiber to connect households and businesses. It includes that next move to cellular from 4G to 5G. It obviously includes Wi-Fi, wherever we've got that as well. And actually it's been a pretty good state, as you said in your opening comments they've done a pretty good job keeping us all connected during the pandemic, whether we're a fixed centric market like the UK with a lot of mobile on top and like the US, or in many markets in Africa and Asia, where we're very mobile centric. So, the fact is that every country market is different, so we should never make too many assumptions at a very top level, but building out that network, building out the services, focusing on that connectivity and making sure we get that cost of delivery right, because competition is pushing us towards having and not ever increasing prices, because we don't want to pay a lot extra every time. But the big issue for me is how do we bring together the IT and the network parts of this story to make sure that we build that efficiency in, and that brings in many questions that we going to touch upon now around Cloud and Hyperscalers around who plays in the ecosystem. >> Well, as you know, Telco is not my wheelhouse, but hanging around with you, I've learned, you've talked a lot about the infrastructure being fit for purpose. It's easy from an IT perspective. Oh yeah, it's fossilized, it's hardened, and it's not really flexible, but the flip side of that coin is as you're pointing out, it's super reliable. So, the big talk today is, "Okay, we're going to open up the network, open systems, and Open RAN, and open everything and microservices and containers. And so, the question is this, can you mimic that historical reliability in that open platform? >> Well, for me, this is the big trade-off and in my great Telco debate every year, I always try and put people against each other to try and to literally debate the future. And one of the things we looked at was is a more open network against this desire of the Telcos to actually have a smaller supplier roster. And of course, as a major corporation, these are on a national basis, very large companies, not large compared to the Hyperscalers for example, but they're large organizations, and they're trying to slim down their organization, slim down the supplier ecosystem. So actually in some ways, the more open it becomes, the more someone's got to manage and integrate all those pieces together. And that isn't something we want to do necessarily. So, I see a real tension there between giving more and more to the traditional suppliers. The Nokia's, Ericsson's, Huawei's, Amdocs and so on, the Ciscos. And then the people coming in breaking new ground like Mavenir and come in, and the sort of approach that Rakuten and Curve taken in bringing in more open and more malleable pieces of smaller software. So yeah, it's a real challenge. And I think as an industry which is notorious for being slow moving, actually we've begun to move relatively quickly, but not necessarily all the way through the organization. We've got plenty of stuff sitting on major or mainframes still in the back of the organization. But of course, as mobile has come in, we've started to deal much more closely, uninteractively in real time, God forbid, with the customers. So actually, at that front end, we've had to do things a lot more quickly. And that's where we're seeing the quickest adaptation to what you might see in your IT environment as being much more, continuous development, continuous improvement, and that sort of on demand delivery. >> Yeah, and we're going to get to that sort of in the Cloud space, but I want to now touch on Telco transformation which is sort of the main theme of this episode. And there's a lot of discussion on this topic, can Telcos move beyond connectivity and managing fiber? Is this a mandate? Is it a pipe dream that's just aspirational? Can they attack adjacencies to grow beyond the 1% a year? I mean, they haven't been successful historically. What are those adjacencies that might be, an opportunity and how will that ecosystem develop? >> Sure. >> So Chris, can and should Telcos try to move beyond core connectivity? Let's start there. >> I like what you did there by saying pipe dreams. Normally, pipe is a is a negative comment in the telecom world. But pipe dream gives it a real positive feel. So can they move beyond connectivity? Well, first of all, connectivity is growing in terms of the number of things being connected. So, in that sense, the market is growing. What we pay for that connectivity is not necessarily growing. So, therefore the mandate is absolutely to transform the inner workings and reduce the cost of delivery. So, that's the internal perspective. The external perspective is that we've tried in many Telcos around the world to break into those adjacent markets, being around media, being enterprise, being around IOT, and actually for the most part they've failed. And we've seen some very significant recent announcements from AT&T, Verizon, BT, beginning to move away from, owning content and not delivering content, but owning content. And the same as they've struggled often in the enterprise market to really get into that, because it's a well-established channel of delivery bringing all those ecosystem players in. So, actually rather than the old Telco view of we going to move into adjacent markets and control those markets, actually moving into them and enabling fellow ecosystem players to deliver the service is what I think we're beginning to see a lot more of now. And that's the big change, it's actually learning to play with the other people in the ecosystem. I always use a phrase that there's no room for egos in the ecosystem. And I think Telcos went in initially with an ego thinking we're really important, we are on connectivity. But actually now they're beginning to approach the ecosystem things saying, "How can we support partners? How can we support everyone in this ecosystem to deliver the services to consumers, businesses and whomever in this evolving ecosystem?" So, there are opportunities out there, plenty of them, but of course, like any opportunity, you've got to approach it in the right way. You've got to get the right investment in place. You've got to approach it with the right open API so everyone can integrate with your approach, and approach it, do I say with a little bit of humility to say, "Hey, we can bring this to the table, how do we work together? >> Well, it's an enormous market. I think you've shared with me, it's like 1.4 trillion. And I want to stay on these adjacencies for a minute, because one of the obvious things that Telcos will talk about is managed services. And I know we have to be careful of that term in an IT context, that it's different in a, you're talking about managing connectivity, but there's professional services. That's a logical sort of extension of their business and probably a safe adjacency, maybe not even adjacency, but they're not going to get into devices. I mean, they'll resell devices, but they're not going to be, I would presume not go back to trying to make devices, but there's certainly the edge and that's so, it'll define in opaque, but it's huge. If there's 5G, there's the IT component and that's probably a partnership opportunity. And as you pointed out, there's the ecosystem, but I wonder, how do you think about 5G as an adjacency or indoor opportunity? Is it a revenue opportunity for Telcos or is that just something that is really aspirational? >> Oh, absolutely it's a revenue opportunity, but I prefer to think of 5G as being a sort of a metaphor for the whole future of telecom. So, we usually talk, and MWC would normally talk about 5G just as a mobile solution. Of course, what you can get with, you can use this fixed wireless access approach, where the roots that sits in your house or your building. So, it's a potential replacement for some fixed lines. And of course, it's also, gives you the ability to build out, let's say in a manufacturing or a campus environment, a private 5G network. So, many of the early opportunities we're seeing with 5G are actually in that more private network environment addressing those very low latency, and high bandwidth requirements. So yeah, there are plenty of opportunities. Of course, the question here is, is connectivity enough, or especially with your comment around the edge, at the edge we need to manage connectivity, storage, compute, analytics, and of course the applications. So, that's a blend of players. It's not going to be in the hands of one player. So yes, plenty of opportunities but understanding what comes the other way from the customer base, where that's, you and I in our homes or outward as an about, or from a business point of view, an office or a campus environment, that's what should be driving, and not the technology itself. And I think this is the trap that the industry has fallen into many times, is we've got a great new wave of technology coming, how can we possibly deliver it to everybody rather than listening to what the customers really require and delivering it in a way consumable by all those different markets. >> Yeah now, of course all of these topics blend together. We try to keep them separately, but we're going to talk about Cloud, we're going to talk about competition, But one of the areas that we don't have a specific agenda item on is, is data and AI. And of course there's all this data flowing through the network, so presumably it's an opportunity for the Telcos. At the same time, they're not considered AI experts. They do when you talk about Edge, they would appear to have the latency advantage because of the last mile and their proximity, to various end points. But the Cloud is sort of building out as well. How do you think about data and AI as an opportunity for Telco? >> I think the whole data and AI piece for me sits on top of the cake or pie, whatever you want to call it. What we're doing with all this connectivity, what we're doing with all these moving parts and gathering information around it, and building automation into the delivery of the service, and using the analytics, whether you call it ML or AI, it doesn't really matter. But actually using that information to deliver a better service, a better outcome. Now, of course, Telcos have had much of this data for years and years, for decades, but they've never used it. So, I think what's happening is, the Cloud players are beginning to educate many of the Telcos around how valuable this stuff is. And that then brings in that question of how do we partner with people using open APIs to leverage that data. Now, do the Telcos keep hold of all that data? Do they let the Cloud players do all of it? No, it's going to be a combination depending on particular environments, and of course the people owning their devices also have a vested interest in this as well. So, you've always got to look at it end to end and where the data flows are, and where we can analyze it. But I agree that analysis on the device at the Edge, and perhaps less and less going back to the core, which is of course the original sort of mandate of the Cloud. >> Well, we certainly think that most of the Edge is going to be about AI inferencing, and then most of the data is going to stay at the edge. Some will come back for sure. And that is big opportunity for whether you're selling compute or conductivity, or maybe storage as well, but certainly insights at the Edge. >> Everything. >> Yeah. >> Everything, yeah. >> Let's get into the Cloud discussion and talk about the Hyperscalers, the big Hyperscaler elephant in the room. We're going to try to dig into what role the Cloud will play in the transformation of telecoms on Telecom TV at the great Telco debate. You likened the Hyperscalers, Chris, to Dementors from Harry Potter hovering over the industry. So, the question is, are the Cloud players going to suck the value out of the Telcos? Or are they more like Dobby the elf? They're powerful, there's sometimes friendly but they're unpredictable. >> Thank you for extending that analogy. Yes, it got a lot of reaction when I use that, but I think it indicates some of the direction of power shift where, we've got to remember here that Telcos are fundamentally national, and they're restricted by regulation, and the Cloud players are global, perhaps not as global as they'd like be, but some regional restrictions, but the global players, the Hyperscalers, they will use that power and they they will extend their reach, and they are extending their reach. If you think they now command some fantastic global networks, in some ways they've replaced some of the Telco international networks, all the submarine investments that tend to be done primarily for the Hyperscalers. So, they're building that out. So, as soon as you get onto their network, then you suddenly become part of that environment. And that is reducing some of the spend on the longer distances we might have got in the past approaches from the Telcos. Now, does that mean they're going to go all the way down and take over the Telcos? I don't believe so, because it's a fundamentally different business digging fiber in people's streets and delivering to the buildings, and putting antennas up. So, they will be a coexistence. And in fact, what we've already seen with Cloud and the Hyperscalers is that they're working much more close together than people might imagine. Now, you mentioned about data in the previous question, Google probably the best known of the of the AI and ML delivers from the Cloud side, working with many of the Telcos, even in some cases to actually have all the data outsourced into the Google Cloud for analytics purposes. They've got the power, the heavy lifting to do that. And so, we begin to see that, and obviously with shifting of workloads as appropriate within the Telco networking environment, we're seeing that with AWS, and of course with Azure as well. And Azure of course acquired a couple of companies in affirmed and Metro switch, which actually do some of the formal 5G core and the likes there within the connectivity environment. So, it's not clean cuts. And to go back to the analogy, those Dementors are swooping around and looking for opportunities, and we know that they will pick up opportunities, and they will extend their reach as far as they can down to that edge. But of course, the edge is where, as you rightly say, the Telcos have the control, they don't necessarily own the customer. I don't believe anyone owns the customer in this digital environment, because digital allows you to move your allegiance and your custom elsewhere anyway. So, but they do own that access piece, and that's what's important from a national point of view, from an economic point of view. And that's why we've seen some of the geopolitical activity banning Huawei from certain markets, encouraging more innovation through open ecosystem plays. And so, there is a tension there between the local Telco, the local market and the Hyperscaler market, but fundamentally they've got an absolute brilliant way of working together using the best of both worlds to deliver the services that we need as an economy. >> Well, and we've talked about this you and I in the past where the Telcos, portions of the Telco network could move into the Cloud. And there of course the Telcos all run the big data centers, and portions of that IT infrastructure could move into the Cloud. But it's very clear, they're not going to give up the entire family jewels to the Cloud players. Why would they? But there are portions of their IT that they could move into. Particularly, in the front end, they want to build like everybody. They want to build an abstraction layer. They're not going to move their core systems and their backend Oracle databases, they're going to put a brick wall around those, but they wanted abstraction layer, and they want to take advantage of microservices and use that data from those transaction systems. But the web front end stuff makes sense to put into Cloud. So, how do you think about that? >> I think you've hit the nail on the head. So you can't move those big backend systems straight away, gradually over time, you will, but you've got to go for those easy wins. And certainly in the research I've been doing with many of my clients, they're suggested that front end piece, making sure that you can onboard customers more easily, you can get the right mix of services. You can provide the omnichannel interaction from that customer experience that everybody talks about, for which the industry is not very well known at all by the way. So, any improvement on that is going to be good from an MPS point of view. So yeah, leveraging what we might, what we call BSS OSS in the telecom world, and actually putting that into the Cloud, leveraging both the Hyperscalers, but also by the way, many of the traditional players who people think haven't moved Cloud wards, but they are moving Cloud wards and they're embracing microservices and Cloud native. So, what you would have seen if we'd been in person down in Barcelona next week, would be a lot of the vendors who perhaps traditionally seems a bit slow moving, actually have done a lot of work to move their portfolio into the Cloud and into Cloud native environments. And yes, as you say, we can use that front end, we can use the API openness that's developed by people at the TM forum, to actually make sure we don't have to do the backend straight away, do it over time. Because of course the thing that we're not touching upon here, is the revenue stream is a consistent revenue stream. So, just because you don't need to change the backend to keep your revenue stream going, this is on a new, it keeps delivering every month, we keep paying our 50, 40, whatever bucks a month into the Telco pot. That's why it's such a big market, and people aren't going to stop doing that. So, I think the dynamics of the industry, we often spend a lot of time thinking about the inner workings of it and the potential of adjacent markets, whereas actually, we keep paying for this stuff, we keep pushing revenue into the pockets of all the Telcos. So, it's not a bad industry to be in, even if they were just pushed back to be in the access market, it's a great business. We need it more and more. The elasticity of demand is very inelastic, we need it. >> Yeah, it's the mother of old golden geese. We don't have a separate topic on security, and I want to touch on security here, is such an important topic. And it's top of mind obviously for everybody, Telcos, Hyperscalers, the Hyperscalers have this shared responsibility model, you know it well. A lot of times it's really confusing for customers. They don't realize it until there has been a problem. The Telcos are going to be very much tuned into this. How will all this openness, and we're going to talk about technology in a moment, but how will this transformation in your view, in the Cloud, with the shared responsibility model, how will that affect the whole security posture? >> Security is a great subject, and I do not specialize in it. I don't claim to be an expert by any stretch of the imagination, but I would say security for me is a bit like AI and analytics. It's everywhere. It's part of everything. And therefore you cannot think of it as a separate add on issue. So, every aspect, every element, every service you build into your micro services environment has to think about how do you secure that connection, that transaction, how do you secure the customer's data? Obviously, sovereignty plays a role in that as well in terms of where it sits, but at every level of every connection, every hop that we look through, every route to jump, we've got to see that security is built in. And in some ways, it's seen as being a separate part of the industry, but actually, as we collapse parts of the network down, we're talking about bringing optical and rooting together in many environments, security should be talked about in the same breath. So when I talked about Edge, when I talked about connectivity, storage, compute, analytics, I should've said security as well, because I absolutely believe that is fundamental to every chain in the link and let's face it, we've got a lot of links in the chain. >> Yeah, 100%. Okay, let's hit on technologies and competition, we kind of blend those together. What technology should we be paying attention to that are going to accelerate this transformation. We hear a lot about 5G, Open RAN. There's a lot of new tech coming in. What are you watching? Who are the players that we maybe should be paying attention to, some that you really like, that are well positioned? >> We've touched upon it in various of the questions that have proceeded this. So, the sort of Cloudification of the networking environment is obviously really important. The automation of the process we've got to move away from bureaucratic manual processes within these large organizations, because we've got to be more efficient, we've got to be more reliable. So, anything which is related to automation. And then the Open RAN question is really interesting. Once again, you raised this topic of when you go down an Open RAN routes or any open route, it ultimately requires more integration. You've got more moving parts from more suppliers. So, therefore there are potential security issues there, depending on how it's defined, but everybody is entering the Open RAN market. There are some names that you will see regularly next week, being pushed, I'm not going to push them anymore, because some of them just attract the oxygen of attention. But there are plenty out there. The good news is, the key vendors who come from the more traditional side are also absolutely embracing that and accept the openness. But I think the piece which probably excites me more, apart from the whole shift towards Cloud and microservices, is the coming together, the openness between the IT environment and the networking environment. And you see it, for example, in the Open RAN, this thing called the RIC, the RAN Interconnection Controller. We're actually, we're beginning to find people come from the IT side able to control elements within the wireless controller piece. Now that that starts to say to me, we're getting a real handle on it, anybody can manage it. So, more specialization is required, but understanding how the end to end flow works. What we will see of course is announcements about new devices, the big guys like Apple and Samsung do their own thing during the year, and don't interrupt their beat with it with MWC, but you'll see a lot of devices being pushed by many other providers, and you'll see many players trying to break into the different elements of the market. But I think mostly, you'll see the people approaching it from more and more Cloudified angle where things are much more leveraging, that Cloud capability and not relying on the sort of rigid and stodgy infrastructure that we've seen in the past >> Which is kind of interesting because Cloud, a lot of the Clouds are Walled Gardens, at the same time they host a lot of open technologies, and I think as these two worlds collide, IT and the Telco industry, it's going to be interesting to see how the Telco developer ecosystem evolves. And so, that's something that we definitely want to watch. You've got a comment there? >> Yeah, I think the Telco developer they've not traditionally been very big in that area at all, have they? They've had their traditional, if you go back to when you and I were kids, the plain old telephone service was a, they were a one trick pony, and they've moved onto that. In some ways, I'd like them to move on and to have the one trick of plain old broadband that we just get broadband delivered everywhere. So, there are some issues about delivering service to all parts of every country, and obviously the globe, whether we do that through satellite, we might see some interesting satellite stuff coming out during NWC. There's an awful lot of birds flying up there trying to deliver signal back to the ground. Traditionally, that's not been very well received, with the change in generation of satellite might help do that. But we've known traditionally that a lot of developer activity in there, what it does bring to the four though, Dave, is this issue of players like the Ciscos and Junipers, and all these guys of the world who bring a developer community to the table as well. This is where the ecosystem play comes in, because that's where you get the innovation in the application world, working with channels, working with individual applications. And so it's opening up, it's basically building a massive fabric that anybody can tap into, and that's what becomes so exciting. So, the barriers to entry come down, but I think it will see us settling down, a stabilization of relationship between the Telcos and the Hyperscalers, because they need each other as we talked about previously, then the major providers, the Ciscos, Nokias, Ericssons, Huawei's, the way they interact with the Telcos. And then allowing that level of innovation coming in from the smaller players, whether it's on a national or a global basis. So, it's actually a really exciting environment. >> So I want to continue that theme and just talk about Telco in the enterprise. And Chris, on this topic, I want to just touch on some things and bring in some survey data from ETR, Enterprise Technology Research, our partner. And of course the Telcos, they've got lots of data centers. And as we talked about, they're going to be moving certain portions into the Cloud, lots of the front end pieces in particular, but let's look at the momentum of some of the IT players within the ETR dataset, and look at how they compare to some of the Telcos that ETR captures specifically within the Telco industry. So, we filtered this data on the Telco industry. So, this is our X, Y graph that we show you oftentimes on the vertical axis, is net score which measures spending momentum, and in the horizontal axis is market share, which is a measure of pervasiveness in the dataset. Now, this data is for shared accounts just in the Telco sector. So we filtered on certain sectors, like within the technology sectors, Cloud, networking, and so it's narrow, it's a narrow slice of the 1500. It respondents, it represents about 133 shared accounts. And a couple of things to jump right out. Within the Telco industry, it's no surprise, but Azure and AWS have massive presence on the horizontal axis, but what's notable as they score very highly in the vertical axis, with elevated spending velocity on their platforms within Telco. Google Cloud doesn't have as much of a presence, but it's elevated as well. Chris was talking about their data posture before, Arista and Verizon, along with VMware are also elevated, as is Aruba, which is HPEs networking division, but they don't have the presence on the horizontal axis. And you got Red Hat OpenStack is actually quite prominent in Telco as we've reported in previous segments. Is no surprise You see Akamai there. Now remember, this survey is weighted toward enterprise IT, so you have to take that into consideration, but look at Cisco, very strong presence, nicely elevated as is Equinox, both higher than many of the others including Dell, but you could see Dell actually has pretty respectable spending in Telco. It's an area that they're starting to focus on more. And then you got that cluster below, your Juniper, AT&T, Oracle, the rest of HPE TELUM and Lumen which is formerly, century link via IBM. Now again, I'm going to caution you. This is an enterprise IT heavy survey, but the big takeaway is the Cloud players have a major presence inside of firms that say they're in the telecommunications industry. And certain IT players like Cisco, VMware and Red Hat appear to be well positioned inside these accounts. So Chris, I'm not sure if any of this commentary resonates with you, but it seems that the Telcos would love to partner up with traditional IT vendors and Cloud players, and maybe find ways to grow their respective businesses. >> I think some of the data points you brought out there are very important. So yes, we've seen a Microsoft Azure and AWS very strong working with Telcos. We've seen Google Cloud platform actually really aggressively pushed into the market certainly the last 12, 24 months. So yeah, they're well positioned, and they all come from a slightly different background. As I said, the Google with this, perhaps more data centric approach in its analytics, tools very useful, AWS with this outpost reaching out, connecting out, and as you'll, with its knowledge of the the Microsoft business market certainly pushing into private networks as well, by the way. So yeah, and Cisco, of course in there does have, and it's a mass scale division, a lot of activity there, some of the people collapsing, some of that rooting an obstacle together, their big push on Silicon. So, what you've got here is a sort of cross representation of many of the different sorts of suppliers who are active in this market. Now Telcos is a big spenders, the telecom market, as we said, a $1.4 trillion market, they spend a lot, they probably have to double bubble spend at the moment to get over the hump of 5G investment, to build out fiber where they need to build out. So, any anything that relates to that is of course a major spending opportunity, a major market opportunity for players. And we know when you need the infrastructure behind it, whether it's in data centers or in their own data centers or in the Cloud to deliver against it. So, what I do like about this as an analyst, a lot of people would focus on one particular piece of the market. So you specialize on handsets, people specialize on home markets and home gateways. So, I tend to sit back and try and look at the big picture, the whole picture. And I think we're beginning to see some very good momentum where people are, where companies are building upon, of course their core business within the telecom industry, extending it out. But the lines of demarcation are blurring between enterprise, Telco, and indeed moving down into small business. And you think about the SD-WAN Market, which came from nowhere to build a much more flexible solution for connecting people over the wide area network, which has been brilliant during the pandemic, because it's allowed us to extend that to home, but be of course, build a campus ready for the future as well. So there are plenty of opportunities out there. I think the big question in my mind is always about from going into the Telco, as I said, whether they wannna reduce the number of suppliers on the roster. So that puts a question mark against some of the open approaches, and then from the Telco to the end customer, because it goes to the Telcos, 30% of their revenue comes from the enterprise market, 60% from the consumer market. How do they leverage the channel? Which includes all the channels, we talked about security, all of the IT stuff that you've already touched upon and the Cloud. It's going to be a very interesting mix and balancing act between different channels to get the services that the customers want. And I think increasingly, customers are more aware of the opportunities open to them to reach back into this ecosystem and say, "Yeah, I want a piece of humans to Telco, but I want it to come to me through my local integrated channel, because I need a bit of their expertise on security." So, fascinating market, and I think not telecom's no longer considered in isolation, but very much as part of that broader digital ecosystem. >> Chris, it's very hard to compress an analysis of a $1.4 trillion business into 30 or 35 minutes, but you're just the guy to help me do it. So, I got to really thank you for participating today and bringing your knowledge. Awesome. >> Do you know, it's my pleasure. I love looking at this market. Obviously I love analogies like Harry Potter, which makes it bring things to life. But at the end of the day, we as people, we want to be connected, we as business, we want to be connected, in society we want to be connected. So, the fundamental of this industry are unbelievably strong. Let's hope that governments don't mess with it too much. And let's hope that we get the right technology comes through, and help support that world of connectivity going forward. >> All right, Chris, well, I'll be texting you from Mobile World Congress in Barcelona, and many thanks to my colleague, Chris Lewis, he brought some serious knowledge today and thank you. And remember, I publish each week on wikibond.com and siliconangle.com. And these episodes are all available as podcasts. You just got to search for Breaking Analysis podcasts. You can always connect with me on twitter @dvellante or email me at dave.vellante@siliconangle.com. And you can comment on my LinkedIn post, and don't forget to check out etr.plus for all the survey data. This is Dave Vellante, for theCUBE Insights powered by ETR. Be well, and we'll see you next time. (upbeat music)

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante aws is pointing the way to a revolution in system architecture much in the same way that aws defined the cloud operating model last decade we believe it is once again leading in future systems design the secret sauce underpinning these innovations is specialized designs that break the stranglehold of inefficient and bloated centralized processing and allows aws to accommodate a diversity of workloads that span cloud data center as well as the near and far edge hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll dig into the moves that aws has been making which we believe define the future of computing we'll also project what this means for customers partners and aws many competitors now let's take a look at aws's architectural journey the is revolution it started by giving easy access as we all know to virtual machines that could be deployed and decommissioned on demand amazon at the time used a highly customized version of zen that allowed multiple vms to run on one physical machine the hypervisor functions were controlled by x86 now according to werner vogels as much as 30 of the processing was wasted meaning it was supporting hypervisor functions and managing other parts of the system including the storage and networking these overheads led to aws developing custom asics that help to accelerate workloads now in 2013 aws began shipping custom chips and partnered with amd to announce ec2 c3 instances but as the as the aws cloud started to scale they really weren't satisfied with the performance gains that they were getting and they were hitting architectural barriers that prompted aws to start a partnership with anaperta labs this was back in 2014 and they launched then ec2 c4 instances in 2015. the asic in c4 optimized offload functions for storage and networking but still relied on intel xeon as the control point aws aws shelled out a reported 350 million dollars to acquire annapurna in 2015 which is a meager sum to acquire the secret sauce of its future system design this acquisition led to a modern version of project nitro in 2017 nitro nitro offload cards were first introduced in 2013 at this time aws introduced c5 instances and replaced zen with kvm and more tightly coupled the hypervisor with the asic vogels shared last year that this milestone offloaded the remaining components including the control plane the rest of the i o and enabled nearly a hundred percent of the processing to support customer workloads it also enabled a bare metal version of the compute that spawned the partnership the famous partnership with vmware to launch vmware cloud on aws then in 2018 aws took the next step and introduced graviton its custom designed arm-based chip this broke the dependency on x86 and launched a new era of architecture which now supports a wide variety of configurations to support data intensive workloads now these moves preceded other aws innovations including new chips optimized for machine learning and training and inferencing and all kinds of ai the bottom line is aws has architected an approach that offloaded the work currently done by the central processing unit in most general purpose workloads like in the data center it has set the stage in our view for the future allowing shared memory memory disaggregation and independent resources that can be configured to support workloads from the cloud all the way to the edge and nitro is the key to this architecture and to summarize aws nitro think of it as a set of custom hardware and software that runs on an arm-based platform from annapurna aws has moved the hypervisor the network the storage virtualization to dedicated hardware that frees up the cpu to run more efficiently this in our opinion is where the entire industry is headed so let's take a look at that this chart pulls data from the etr data set and lays out key players competing for the future of cloud data center and the edge now we've superimposed nvidia up top and intel they don't show up directly in the etr survey but they clearly are platform players in the mix we covered nvidia extensively in previous breaking analysis and won't go too deep there today but the data shows net scores on the vertical axis that's a measure of spending velocity and then it shows market share in the horizontal axis which is a measure of pervasiveness within the etr data set we're not going to dwell on the relative positions here rather let's comment on the players and start with aws we've laid out aws how they got here and we believe they are setting the direction for the future of the industry and aws is really pushing migration to its arm-based platforms pat morehead at the 6-5 summit spoke to dave brown who heads ec2 at aws and he talked extensively about migrating from x86 to aws's arm-based graviton 2. and he announced a new developer challenge to accelerate that migration to arm instances graviton instances and the end game for customers is a 40 better price performance so a customer running 100 server instances can do the same work with 60 servers now there's some work involved but for the by the customers to actually get there but the payoff if they can get 40 improvement in price performance is quite large imagine this aws currently offers 400 different ec2 instances last year as we reported sorry last year as we reported earlier this year nearly 50 percent of the new ec2 instances so nearly 50 percent of the new ec2 instances shipped in 2020 were arm based and aws is working hard to accelerate this pace it's very clear now let's talk about intel i'll just say it intel is finally responding in earnest and basically it's taking a page out of arm's playbook we're going to dig into that a bit today in 2015 intel paid 16.7 billion dollars for altera a maker of fpgas now also at the 6.5 summit nevin shenoy of intel presented details of what intel is calling an ipu it's infrastructure processing unit this is a departure from intel norms where everything is controlled by a central processing unit ipu's are essentially smart knicks as our dpus so don't get caught up in all the acronym soup as we've reported it's all about offloading work and disaggregating memory and evolving socs system-on-chip and sops system on package but just let this sink in a bit a bit for a moment intel's moves this past week it seems to us anyway are designed to create a platform that is nitro like and the basis of that platform is a 16.7 billion dollar acquisition just compare that to aws's 350 million dollar tuck-in of annapurna that is incredible now chenoy said in his presentation rough quote we've already deployed ipu's using fpgas in a in very high volume at microsoft azure and we've recently announced partnerships with baidu jd cloud and vmware so let's look at vmware vmware is the other you know really big platform player in this race in 2020 vmware announced project monterrey you might recall that it's based on the aforementioned fpgas from intel so vmware is in the mix and it chose to work with intel most likely for a variety of reasons one of the obvious ones is all the software that's running on on on vmware it's been built for x86 and there's a huge install base there the other is pat was heading vmware at the time and and you know when project monterey was conceived so i'll let you connect the dots if you like regardless vmware has a nitro like offering in our view its optionality however is limited by intel but at least it's in the game and appears to be ahead of the competition in this space aws notwithstanding because aws is clearly in the lead now what about microsoft and google suffice it to say that we strongly believe that despite the comments that intel made about shipping fpgas and volume to microsoft that both microsoft and google as well as alibaba will follow aws's lead and develop an arm-based platform like nitro we think they have to in order to keep pace with aws now what about the rest of the data center pack well dell has vmware so despite the split we don't expect any real changes there dell is going to leverage whatever vmware does and do it better than anyone else cisco is interesting in that it just revamped its ucs but we don't see any evidence that it has a nitro like plans in its roadmap same with hpe now both of these companies have history and capabilities around silicon cisco designs its own chips today for carrier class use cases and and hpe as we've reported probably has some remnants of the machine hanging around but both companies are very likely in our view to follow vmware's lead and go with an intel based design what about ibm well we really don't know we think the best thing ibm could do would be to move the ibm cloud of course to an arm-based nitro-like platform we think even the mainframe should move to arm as well i mean it's just too expensive to build a specialized mainframe cpu these days now oracle they're interesting if we were running oracle we would build an arm-based nitro-like database cloud where oracle the database runs cheaper faster and consumes less energy than any other platform that would would dare to run oracle and we'd go one step further and we would optimize for competitive databases in the oracle cloud so we would make oci run the table on all databases and be essentially the database cloud but you know back to sort of fpgas we're not overly excited about about the market amd is acquiring xi links for 35 billion dollars so i guess that's something to get excited about i guess but at least amd is using its inflated stock price to do the deal but we honestly we think that the arm ecosystem will will obliterate the fpga market by making it simpler and faster to move to soc with far better performance flexibility integration and mobility so again we're not too sanguine about intel's acquisition of altera and the moves that amd is making in in the long term now let's take a deeper look at intel's vision of the data center of the future here's a chart that intel showed depicting its vision of the future of the data center what you see is the ipu's which are intelligent nixed and they're embedded in the four blocks shown and they're communicating across a fabric now you have general purpose compute in the upper left and machine intelligent on the bottom left machine intelligence apps and up in the top right you see storage services and then the bottom right variation of alternative processors and this is intel's view of how to share resources and go from a world where everything is controlled by a central processing unit to a more independent set of resources that can work in parallel now gelsinger has talked about all the cool tech that this will allow intel to incorporate including pci and gen 5 and cxl memory interfaces and or cxl memory which are interfaces that enable memory sharing and disaggregation and 5g and 6g connectivity and so forth so that's intel's view of the future of the data center let's look at arm's vision of the future and compare them now there are definite similarities as you can see especially on the right hand side of this chart you've got the blocks of different process processor types these of course are programmable and you notice the high bandwidth memory the hbm3 plus the ddrs on the two sides kind of bookending the blocks that's shared across the entire system and it's connected by pcie gen 5 cxl or ccix multi-die socket so you know you may be looking to say okay two sets of block diagrams big deal well while there are similarities around disaggregation and i guess implied shared memory in the intel diagram and of course the use of advanced standards there are also some notable differences in particular arm is really already at the soc level whereas intel is talking about fpgas neoverse arms architecture is shipping in test mode and we'll have end market product by year end 2022 intel is talking about maybe 2024 we think that's aspirational or 2025 at best arm's road map is much more clear now intel said it will release more details in october so we'll pay attention then maybe we'll recalibrate at that point but it's clear to us that arm is way further along now the other major difference is volume intel is coming at this from a high data center perspective and you know presumably plans to push down market or out to the edge arm is coming at this from the edge low cost low power superior price performance arm is winning at the edge and based on the data that we shared earlier from aws it's clearly gaining ground in the enterprise history strongly suggests that the volume approach will win not only at the low end but eventually at the high end so we want to wrap by looking at what this means for customers and the partner ecosystem the first point we'd like to make is follow the consumer apps this capability the capabilities that we see in consumer apps like image processing and natural language processing and facial recognition and voice translation these inference capabilities that are going on today in mobile will find their way into the enterprise ecosystem ninety percent of the cost associated with machine learning in the cloud is around inference in the future most ai in the enterprise and most certainly at the edge will be inference it's not today because it's too expensive this is why aws is building custom chips for inferencing to drive costs down so it can increase adoption now the second point is we think that customers should start experimenting and see what you can do with arm-based platforms moore's law is accelerating at least the outcome of moore's law the doubling of performance every of the 18 to 24 months it's it's actually much higher than that now when you add up all the different components in these alternative processors just take a look at apple's a5 a15 chip and arm is in the lead in terms of performance price performance cost and energy consumption by moving some workloads onto graviton for example you'll see what types of cost savings you can drive for which applications and possibly generate new applications that you can deliver to your business put a couple engineers in the task and see what they can do in two or three weeks you might be surprised or you might say hey it's too early for us but you'll find out and you may strike gold we would suggest that you talk to your hybrid cloud provider as well and find out if they have a nitro we shared that vmware they've got a clear path as does dell because they're you know vmware cousins what about your other strategic suppliers what's their roadmap what's the time frame to move from where they are today to something that resembles nitro do they even think about that how do they think about that do they think it's important to get there so if if so or if not how are they thinking about reducing your costs and supporting your new workloads at scale now for isvs these consumer capabilities that we discussed earlier all these mobile and and automated systems and cars and and things like that biometrics another example they're going to find their way into your software and your competitors are porting to arm they're embedding these consumer-like capabilities into their apps are you we would strongly recommend that you take a look at that talk to your cloud suppliers and see what they can do to help you innovate run faster and cut costs okay that's it for now thanks to my collaborator david floyer who's been on this topic since early last decade thanks to the community for your comments and insights and hey thanks to patrick morehead and daniel newman for some timely interviews from your event nice job fellas remember i published each week on wikibon.com and siliconangle.com these episodes are all available as podcasts just search for breaking analysis podcasts you can always connect with me on twitter at d vallante or email me at david.velante at siliconangle.com i appreciate the comments on linkedin and clubhouse so follow us if you see us in a room jump in and let's riff on these topics and don't forget to check out etr.plus for all the survey data this is dave vellante for the cube insights powered by etr be well and we'll see you next time

>>Welcome to the cubes coverage of Dell Technologies world 2021. The digital experience. I'm lisa martin. I've got two guests here with me today. Adam Glick is here. Senior Director of portfolio marketing for Apex at Dell Technologies. Adam welcome to the cube >>lisa. It's great to be here with you >>likewise. And Andrew Glinka is here VP of Competitive intelligence at Dell Technologies as well. Andrew welcome to you as well. >>Thank you. Glad to be here. >>So the last Dell Technologies world was only about six months or so ago and sadly I was sitting in the same room doing that. We're not in Vegas at the convention center but hopefully one day we will be soon. But a lot of news there um Adam was about Apex and this big transformation about what Dell wants to do, give us a little bit of a history and what's transpired in the last six months. >>Well, a lot of things have happened in the past six months with what we were calling Project Apex before probably the first most obvious one is we've removed project from the name as we've made the offering generally available. We've also added a lot to it. There's a lot of new pieces of technology that are part of Project Apex now, we've talked about bringing in the cloud, bringing the custom solutions, hear a lot about that at Dell Technologies where all this time and really practicing that all up together in a single experience for customers, giving them something that's super simple agile and gives them all the control that they want to use their infrastructure where they want it all of that as a service. >>Big changes Andrew. Let's go over to you now. Talk to me about some of the players in the market. >>Well, he has a service market is growing incredibly fast and will continue to grow over the next number of years. And what we're seeing is a lot of players trying to enter that market because it is growing so fast. So you have some of the traditional infrastructure players that are entering like HP has their offer out in the market and pure storage and that happened many others. And you also have the public cloud providers like amazon web services, google Microsoft azure that are starting to develop um on prem tech capabilities to kind of validate this hybrid cloud as a service, all things everywhere model. So uh rapidly growing market a lot changing in a lot of players entering this space very quickly. >>So a lot of acceleration we've seen with respect to digital transformation Andrew in the last year. So talk to me about how Apex compares to those infrastructure players, you mentioned peer storage, Netapp HP. Talk to me about the comparison there. >>Yeah, so one of the things is we continue to develop, Apex is we're going to offer the broadest portfolio of as a service solutions for customers, all with different consumption models. So we'll be offering outcome based meter based as well as custom solutions, which is a little bit different than what others can provide all delivered using market leading technology and all Dell supported. So we're not using third party to deliver any of the asset service, it's all Dell supported, um some other very tactical things like single rate, so we don't charge for over usage or charge extra, which is different than some um and also it's all self service. So through the console you can place an order for a new system or upgraded system and you're avoiding the lengthy sale cycles and all the back and forth. So just a couple of questions you can get the outcome that you're looking for. >>Adam. Talk to me about how apex compares to the public cloud providers, customers obviously have that choice as well. AWS google cloud platform. What's the comparison contrast there? >>So when we think about what's going on with public cloud providers, we really look at them as partners and people that we work with. There's a Venn diagram if you think about it and the reality is that although there is some overlap between, there's also a lot of differentiated value that we look at, that we bring their and it's how do we work together on those pieces? So the most obvious of those is when you're thinking about things like a hybrid cloud and how people work together to make sure that they've got a cloud that meets their needs, both on prem in their Coehlo locations out of the edge as well as whatever they're doing with public >>cloud. >>And so we're looking at how do we bring all those pieces together? And there are certain things that work better in certain places, certain ones that work better than others. We do a lot of things around the simplicity of billing to make that easy for customers, giving them really high performance ways to to work well that really meet the needs of a lot of workloads that might need regulatory needs or might have specific performance mapping, high performance computing, things like that. But it works together. And that's really the point is that what customers tell us is that they have needs for on premises, They have needs for things in their private cloud and follows. They also have needs in the public cloud. And how do they bring that together? And so we're working to say, how do we bridge that gap to make the best possible outcome for customers? We work on partnerships with the partnership that we announced with Equinix to bring together co location facilities around the world and bring apex services customers easily when they want to say reduce the latency between what they're running and what they control within their own hardware stacks and what might be running in the public cloud. It's kind of a merger of both that really helps customers get the best of all that they need because at the end of the day that's the goal is helping our customers get the best I. T. Outcomes for their businesses as possible. >>Right? And you mentioned Hybrid cloud and we talk about that so often customers are in that hybrid world for many reasons. So basically what you're saying is there is partnerships that Dell Technologies has with Apex and the other hyper scholars so that when customers come in, if they're most likely already using some of those other platforms, they actually could come in and work with Apex too, develop a solution that works very synergistically. >>Yeah, we're helping them pull together what they need. And if you take a look, 72 of organizations say that they're taking a hybrid cloud approach, they want to be able to bring the best of both worlds to what they're doing and really choose what's right for them. Where do they need to be able to really control what's happening with their data? Where do they want to be able to maintain and control the costs that they have and also be able to access the other services that might be out there that they would need. So how do they bring those together? And those ways that we work together for the benefit of customers? And we bridge those two pieces is really what we're aiming to do here. >>Excellent. So Andrew, let's go back over you. I want to talk about workloads here because you know when we look at some of the numbers, the 8020 rule with the cloud, 80 of those workloads still on prem customers needing to determine which workloads should go to the cloud. How does apex work with customers to facilitate making those decisions? Um about the workloads that are best suited for apex versus club? >>Well, I think that's the beauties, it's very flexible. And so some of those traditional workloads that are still on prem can be run as a service without a whole lot of change. So you don't have to re platform, you don't have to reengineer them and you can move them into an as a service model, continue to run them easily. But then there's a whole lot of new development like high performance computing and Ai And machine learning, particularly at an edge where Gartner says by 2025 75 of all data will be processed at the edge. So as these new capabilities are being built out, uh customers have been asking us to start to run that infrastructure in these new workloads and and at as a service model and so high performance computing ai. Ml these edge workloads are fantastic use cases just get started with as a service and can certainly extend back into some of the more traditional workloads that they've been running >>adam. Can you talk to us a little bit about what's transpired in the last six months from the customers lens as we talked a little bit about, we talked a lot in the last year about the acceleration of digital transformation and so many businesses having to pivot multiple times in the last year. A lot of acceleration of those getting to cloud for, for to survive. Talk to me about the customer experience, what you see in the last six months. >>So what we've heard a lot from our customers is that they're really looking for the benefits of consumption as a service that especially as you see the financial impacts that happened over the past year, People looking at ways to preserve capital and what are the ways that they can go and maintain what they want to do or perhaps even grow and accelerate. Take advantage of those new opportunities in ways that don't require large capital purchases and the ability to go in and purchase as a service is something we've heard from multiple customers is something that is really attractive to them as they look at. Hey, there's no opportunities they've opened up and how do they be able to expand on those as well as how do they be able to preserve the capital? They have, be able to continue with the projects that they're looking at but be able to take a more agile approach for those things. And so the as a service offerings that we've been talking to our customers about have been really something they've been excited about and they come to us kind of, hey, what do you have? What's the roadmap? How can we have more of those kinds of things? And that's why we're so excited Dell Technologies world to be talking about how we're bringing even more apex services as a service available to our customers. >>And I'm just curious in the last year since we've seen so many industries, every industry really rocked by the very dynamic market, but some of the things like healthcare and government, I'm just curious if you've seen any industries in particular really take a leading edge here and working with you in apex. >>one of the most >>interesting things that I've seen from the customers that I've been talking to is that it really is broad ranging that I've talked to customers who are governmental customers who are interested in expanding what they're doing with it but very concerned about things like data, locality and data sovereignty. That's very interesting to them. I've talked to manufacturing organizations, they're looking at how do they expand their operations in asian manufacturing for instance. And they're going from, how do they operate within the United States to how do they expand their operations? Be able to do that in a more quick fashion? What they're doing? Talk to healthcare organizations, they're looking at, how do they be able to bring digital healthcare and as you to think about what's happening more virtually that people are doing, What does that mean in terms of health care? Both from people who are actually doing virtual visits with their doctors as well as even things like digital surgery. So there's so many things that are happening really. I could talk to you about dozens of industries. But the takeaway that I've had is that there's no real one industry, it's really something that has impacted just operations globally and different folks. Look at different things in different ways. I talked to a company that does train that actually train company. They do logistics and they're looking at edge scenarios and how do they do train inspections faster to be able to provide better turnaround times for their trains because there's a limited amount of track and so if they miss a maintenance window like that's time that they not only have to wait for the next window, they have to wait for all the other trains to pass too. So it's really breathtaking, just the scope of all that's changing in it and all the opportunities that are coming up as people think about what consuming it services as a service can mean for them. >>Yeah, amazing opportunities. And you talked about, you know, the virtual and there's so much of it that's going to persist in in a good way, silver linings, right? Um and you want to go back over to you talk to me when we, when we talked about apex at Dell technologies world 2026 months ago, this was kind of revolutionary and really looking at it as a really big change to Dell's future strategy. Talk to me about that. >>Well, it's a change for the entire company, so having to rethink how we deliver all these services and outcomes to customers. So it's it's not just about the product. The product is now the service and the service is the product, so it's very different in how we approach it. Thinking more about how we can help our customers achieve these outcomes um and help deliver these services that get them there, which is a little different than just developing the products themselves. And so that's been a big thing that we've been taking on and making sure that we deliver these outcomes for our customers. >>Yeah. And then adam last question for you talk to me about kind of same perspective of looking at this as as how Dell intends to compete in the future and what customers can expect. Also how can they engage? Is this something that is available with Channel Partners? Dell Direct? >>So this is the beginning of a huge journey and transformation as Andrew spoke about, like this is a transformation of not only what we're providing, but a transformation across all of Dell. We're looking at how do we expand the X portfolio to bring a portfolio of options to our customers? You know, we're starting with with storage and cloud and some are custom solutions, but we really have a vision of how do we bring all of Dell's business products and into services for our customers? You know, it's a huge transformation, it's something I'm incredibly excited about because it really aligns what we do with what our customers do. We've never had an opportunity to be so closely connected with our customers and create great outcomes for them. So the transformation, like we're just at the beginning of this and it's an incredible path that we're on that's providing amazing value for the people that we've already started working with. For people that want to find out more about it. You can certainly come to our website, Dell technologies dot com slash apex. People who have a relationship with Dell already contact their sales representative will be more than happy to talk to them about what their current needs are and what effects can do to help them continue their digital transformation and create better outcomes for their organization. >>Excellent, Adam Andrew, Thank you for joining me today to talk about what's going on. Project apex to apex the tremendous amount of opportunities that it's helping customers in any industry uncover. We look forward to seeing down the road some of those great customer outcomes that come from this. I thank you both for joining me today. >>Thank you very much. Thank you >>for Adam Glick and Andrew Glinka. I'm lisa martin. You're watching the cubes coverage of Dell Technologies World 2021 The Digital Experience.

>>from around the globe. It's the Cube with digital coverage of enterprise data automation, an event Siri's brought to you by Iot. Tahoe, everybody, We're back. We're talking about enterprise data automation. The hashtag is data automated, and we're going to really dig into data migrations, data, migrations. They're risky. They're time consuming, and they're expensive. Yousef con is here. He's the head of partnerships and alliances at I o ta ho coming again from London. Hey, good to see you, Seth. Thanks very much. >>Thank you. >>So your role is is interesting. We're talking about data migrations. You're gonna head of partnerships. What is your role specifically? And how is it relevant to what we're gonna talk about today? >>Uh, I work with the various businesses such as cloud companies, systems integrators, companies that sell operating systems, middleware, all of whom are often quite well embedded within a company. I t infrastructures and have existing relationships. Because what we do fundamentally makes migrating to the cloud easier on data migration easier. A lot of businesses that are interested in partnering with us. Um, we're interested in parting with, So >>let's set up the problem a little bit. And then I want to get into some of the data. You know, I said that migration is a risky, time consuming, expensive. They're they're often times a blocker for organizations to really get value out of data. Why is that? >>Uh, I think I mean, all migrations have to start with knowing the facts about your data, and you can try and do this manually. But when that you have an organization that may have been going for decades or longer, they will probably have a pretty large legacy data estate so that I have everything from on premise mainframes. They may have stuff which is probably in the cloud, but they probably have hundreds, if not thousands of applications and potentially hundreds of different data stores. Um, now they're understanding of what they have. Ai's often quite limited because you can try and draw a manual maps, but they're outdated very quickly. Every time that data changes the manual that's out of date on people obviously leave organizations over time, so that kind of tribal knowledge gets built up is limited as well. So you can try a Mackel that manually you might need a db. Hey, thanks. Based analyst or ah, business analyst, and they won't go in and explore the data for you. But doing that manually is very, very time consuming this contract teams of people, months and months. Or you can use automation just like what's the bank with Iot? And they managed to do this with a relatively small team. Are in a timeframe of days. >>Yeah, we talked to Paul from Webster Bank. Awesome discussion. So I want to dig into this migration and let's let's pull up graphic it will talk about. We'll talk about what a typical migration project looks like. So what you see here it is. It's very detailed. I know it's a bit of an eye test, but let me call your attention to some of the key aspects of this Ah, and then use. If I want you to chime in. So at the top here, you see that area graph that's operational risk for a typical migration project, and you can see the timeline and the the milestones. That blue bar is the time to test so you can see the second step data analysis talking 24 weeks so, you know, very time consuming. And then Let's not get dig into the stuff in the middle of the fine print, but there's some real good detail there, but go down the bottom. That's labor intensity in the in the bottom and you can see high is that sort of brown and and you could see a number of data analysis, data staging data prep, the trial, the implementation post implementation fixtures, the transition toe B A B a year, which I think is business as usual. Those are all very labor intensive. So what do you take aways from this typical migration project? What do we need to know yourself? >>I mean, I think the key thing is, when you don't understand your data upfront, it's very difficult to scope to set up a project because you go to business stakeholders and decision makers and you say Okay, we want to migrate these data stores. We want to put them in the cloud most often, but actually, you probably don't know how much data is there. You don't necessarily know how many applications that relates to, you know, the relationships between the data. You don't know the flow of the data. So the direction in which the data is going between different data stores and tables, so you start from a position where you have pretty high risk and alleviate that risk. You could be stacking project team of lots and lots of people to do the next base, which is analysis. And so you set up a project which has got a pretty high cost. The big projects, more people, the heavy of governance, obviously on then there, then in the phase where they're trying to do lots and lots of manual analysis manage. That, in a sense, is, as we all know, on the idea of trying to relate data that's in different those stores relating individual tables and columns. Very, very time consuming, expensive. If you're hiring in resource from consultants or systems integrators externally, you might need to buy or to use party tools, Aziz said earlier. The people who understand some of those systems may have left a while ago. See you even high risks quite cost situation from the off on the same things that have developed through the project. Um, what are you doing with it, Ayatollah? Who is that? We're able to automate a lot of this process from the very beginning because we can do the initial data. Discovery run, for example, automatically you very quickly have an automated validator. A data map on the data flow has been generated automatically, much less time and effort and much less cars. Doctor Marley. >>Okay, so I want to bring back that that first chart, and I want to call your attention to the again that area graph the blue bars and then down below that labor intensity. And now let's bring up the the the same chart. But with a set of an automation injection in here and now. So you now see the So let's go Said Accelerated by Iot, Tom. Okay, great. And we're going to talk about this. But look, what happens to the operational risk. A dramatic reduction in that. That graph. And then look at the bars, the bars, those blue bars. You know, data analysis went from 24 weeks down to four weeks and then look at the labor intensity. The it was all these were high data analysis data staging data prep. Try a lot post implementation fixtures in transition to be a you. All of those went from high labor intensity. So we've now attack that and gone to low labor intensity. Explain how that magic happened. >>I think that the example off a data catalog. So every large enterprise wants to have some kind of repository where they put all their understanding about their data in its Price States catalog, if you like, um, imagine trying to do that manually. You need to go into every individual data store. You need a DB a business analyst, rich data store they need to do in extracted the data table was individually they need to cross reference that with other data school, it stores and schemers and tables. You probably were the mother of all lock Excel spreadsheets. It would be a very, very difficult exercise to do. I mean, in fact, one of our reflections as we automate lots of data lots of these things is, um it accelerates the ability to water may, But in some cases, it also makes it possible for enterprise customers with legacy systems um, take banks, for example. There quite often end up staying on mainframe systems that they've had in place for decades. Uh, no migrating away from them because they're not able to actually do the work of understanding the data g duplicating the data, deleting data isn't relevant and then confidently going forward to migrate. So they stay where they are with all the attendant problems assistance systems that are out of support. Go back to the data catalog example. Um, whatever you discover invades, discovery has to persist in a tool like a data catalog. And so we automate data catalog books, including Out Way Cannot be others, but we have our own. The only alternative to this kind of automation is to build out this very large project team or business analysts off db A's project managers processed analysts together with data to understand that the process of gathering data is correct. To put it in the repository to validate it except etcetera, we've got into organizations and we've seen them ramp up teams off 2030 people costs off £234 million a year on a time frame, 15 20 years just to try and get a data catalog done. And that's something that we can typically do in a timeframe of months, if not weeks. And the difference is using automation. And if you do what? I've just described it. In this manual situation, you make migrations to the cloud prohibitively expensive. Whatever saving you might make from shutting down your legacy data stores, we'll get eaten up by the cost of doing it. Unless you go with the more automated approach. >>Okay, so the automated approach reduces risk because you're not gonna, you know you're going to stay on project plan. Ideally, it's all these out of scope expectations that come up with the manual processes that kill you in the rework andan that data data catalog. People are afraid that their their family jewels data is not going to make it through to the other side. So So that's something that you're you're addressing and then you're also not boiling the ocean. You're really taking the pieces that are critical and stuff you don't need. You don't have to pay for >>process. It's a very good point. I mean, one of the other things that we do and we have specific features to do is to automatically and noise data for a duplication at a rover or record level and redundancy on a column level. So, as you say before you go into a migration process. You can then understand. Actually, this stuff it was replicated. We don't need it quite often. If you put data in the cloud you're paying, obviously, the storage based offer compute time. The more data you have in there that's duplicated, that is pure cost. You should take out before you migrate again if you're trying to do that process of understanding what's duplicated manually off tens or hundreds of bases stores. It was 20 months, if not years. Use machine learning to do that in an automatic way on it's much, much quicker. I mean, there's nothing I say. Well, then, that costs and benefits of guitar. Every organization we work with has a lot of money existing, sunk cost in their I t. So have your piece systems like Oracle or Data Lakes, which they've spent a good time and money investing in. But what we do by enabling them to transition everything to the strategic future repositories, is accelerate the value of that investment and the time to value that investment. So we're trying to help people get value out of their existing investments on data estate, close down the things that they don't need to enable them to go to a kind of brighter, more future well, >>and I think as well, you know, once you're able to and this is a journey, we know that. But once you're able to go live on, you're infusing sort of a data mindset, a data oriented culture. I know it's somewhat buzzword, but when you when you see it in organizations, you know it's really and what happens is you dramatically reduce that and cycle time of going from data to actually insights. Data's plentiful, but insights aren't, and that is what's going to drive competitive advantage over the next decade and beyond. >>Yeah, definitely. And you could only really do that if you get your data estate cleaned up in the first place. Um, I worked with the managed teams of data scientists, data engineers, business analysts, people who are pushing out dashboards and trying to build machine learning applications. You know, you know, the biggest frustration for lots of them and the thing that they spend far too much time doing is trying to work out what the right data is on cleaning data, which really you don't want a highly paid thanks to scientists doing with their time. But if you sort out your data stays in the first place, get rid of duplication. If that pans migrate to cloud store, where things are really accessible on its easy to build connections and to use native machine learning tools, you're well on the way up to date the maturity curve on you can start to use some of those more advanced applications. >>You said. What are some of the pre requisites? Maybe the top few that are two or three that I need to understand as a customer to really be successful here? Is it skill sets? Is it is it mindset leadership by in what I absolutely need to have to make this successful? >>Well, I think leadership is obviously key just to set the vision of people with spiky. One of the great things about Ayatollah, though, is you can use your existing staff to do this work. If you've used on automation, platform is no need to hire expensive people. Alright, I was a no code solution. It works out of the box. You just connect to force on your existing stuff can use. It's very intuitive that has these issues. User interface? >>Um, it >>was only to invest vast amounts with large consultants who may well charging the earth. Um, and you already had a bit of an advantage. If you've got existing staff who are close to the data subject matter experts or use it because they can very easily learn how to use a tool on, then they can go in and they can write their own data quality rules on. They can really make a contribution from day one, when we are go into organizations on way. Can I? It's one of the great things about the whole experience. Veritas is. We can get tangible results back within the day. Um, usually within an hour or two great ones to say Okay, we started to map relationships. Here's the data map of the data that we've analyzed. Harrison thoughts on where the sensitive data is because it's automated because it's running algorithms stater on. That's what they were really to expect. >>Um, >>and and you know this because you're dealing with the ecosystem. We're entering a new era of data and many organizations to your point, they just don't have the resources to do what Google and Amazon and Facebook and Microsoft did over the past decade To become data dominant trillion dollar market cap companies. Incumbents need to rely on technology companies to bring that automation that machine intelligence to them so they can apply it. They don't want to be AI inventors. They want to apply it to their businesses. So and that's what really was so difficult in the early days of so called big data. You have this just too much complexity out there, and now companies like Iot Tahoe or bringing your tooling and platforms that are allowing companies to really become data driven your your final thoughts. Please use it. >>That's a great point, Dave. In a way, it brings us back to where it began. In terms of partnerships and alliances. I completely agree with a really exciting point where we can take applications like Iot. Uh, we can go into enterprises and help them really leverage the value of these type of machine learning algorithms. And and I I we work with all the major cloud providers AWS, Microsoft Azure or Google Cloud Platform, IBM and Red Hat on others, and we we really I think for us. The key thing is that we want to be the best in the world of enterprise data automation. We don't aspire to be a cloud provider or even a workflow provider. But what we want to do is really help customers with their data without automated data functionality in partnership with some of those other businesses so we can leverage the great work they've done in the cloud. The great work they've done on work flows on virtual assistants in other areas. And we help customers leverage those investments as well. But our heart, we really targeted it just being the best, uh, enterprised data automation business in the world. >>Massive opportunities not only for technology companies, but for those organizations that can apply technology for business. Advantage yourself, count. Thanks so much for coming on the Cube. Appreciate. All right. And thank you for watching everybody. We'll be right back right after this short break. >>Yeah, yeah, yeah, yeah.

>> From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. (smooth music) >> Hi, I'm Stu Miniman, and welcome to this special exclusive presentation from theCUBE. We're digging into Pensando and their Future Proof Your Enterprise event. To help kick things off, welcoming in a friend of the program, Scott Raynovich. He is the principal analyst at Futuriom coming to us from Montana. I believe first time we've had a guest on the program in the state of Montana, so Scott, thanks so much for joining us. >> Thanks, Stu, happy to be here. >> All right, so we're going to dig a lot into Pensando. They've got their announcement with Hewlett Packard Enterprise. Might help if we give a little bit of background, and definitely I want Scott and I to talk a little bit about where things are in the industry, especially what's happening in networking, and how some of the startups are helping to impact what's happening on the market. So for those that aren't familiar with Pensando, if you followed networking I'm sure you are familiar with the team that started them, so they are known, for those of us that watch the industry, as MPLS, which are four people, not to be confused with the protocol MPLS, but they had very successfully done multiple spin-ins for Cisco, Andiamo, Nuova and Insieme, which created Fibre Channel switches, the Cisco UCS, and the ACI product line, so multiple generations to the Nexus, and Pensando is their company. They talk about Future Proof Your Enterprise is the proof point that they have today talking about the new edge. John Chambers, the former CEO of Cisco, is the chairman of Pensando. Hewlett Packard Enterprise is not only an investor, but also a customer in OEM piece of this solution, and so very interesting piece, and Scott, I want to pull you into the discussion. The waves of technology, I think, the last 10, 15 years in networking, a lot it has been can Cisco be disrupted? So software-defined networking was let's get away from hardware and drive towards more software. Lots of things happening. So I'd love your commentary. Just some of the macro trends you're seeing, Cisco's position in the marketplace, how the startups are impacting them. >> Sure, Stu. I think it's very exciting times right now in networking, because we're just at the point where we kind of have this long battle of software-defined networking, like you said, really pushed by the startups, and there's been a lot of skepticism along the way, but you're starting to see some success, and the way I describe it is we're really on the third generation of software-defined networking. You have the first generation, which was really one company, Nicira, which VMware bought and turned into their successful NSX product, which is a virtualized networking solution, if you will, and then you had another round of startups, people like Big Switch and Cumulus Networks, all of which were acquired in the last year. Big Switch went to Arista, and Cumulus just got purchased by... Who were they purchased by, Stu? >> Purchased by Nvidia, who interestingly enough, they just picked up Mellanox, so watching Nvidia build out their stack. >> Sorry, I was having a senior moment. It happens to us analysts. (chuckling) But yeah, so Nvidia's kind of rolling up these data center and networking plays, which is interesting because Nvidia is not a traditional networking hardware vendor. It's a chip company. So what you're seeing is kind of this vision of what they call in the industry disaggregation. Having the different components sold separately, and then of course Cisco announced the plan to roll out their own chip, and so that disaggregated from the network as well. When Cisco did that, they acknowledged that this is successful, basically. They acknowledged that disaggregation is happening. It was originally driven by the large public cloud providers like Microsoft Azure and Amazon, which started the whole disaggregation trend by acquiring different components and then melding it all together with software. So it's definitely the future, and so there's a lot of startups in this area to watch. I'm watching many of them. They include ArcOS, which is a exciting new routing vendor. DriveNets, which is another virtualized routing vendor. This company Alkira, which is going to do routing fully in the cloud, multi-cloud networking. Aviatrix, which is doing multi-cloud networking. All these are basically software companies. They're not pitching hardware as part of their value add, or their integrated package, if you will. So it's a different business model, and it's going to be super interesting to watch, because I think the third generation is the one that's really going to break this all apart. >> Yeah, you brought up a lot of really interesting points there, Scott. That disaggregation, and some of the changing landscape. Of course that more than $1 billion acquisition of Nicira by VMware caused a lot of tension between VMware and Cisco. Interesting. I think back when to Cisco created the UCS platform it created a ripple effect in the networking world also. HP was a huge partner of Cisco's before UCS launched, and not long after UCS launched HP stopped selling Cisco gear. They got heavier into the networking component, and then here many years later we see who does the MPLS team partner with when they're no longer part of Cisco, and Chambers is no longer the CEO? Well, it's HPE front and center there. You're going to see John Chambers at HPE Discover, so it was a long relationship and change. And from the chip companies, Intel, of course, has built a sizeable networking business. We talked a bit about Mellanox and the acquisitions they've done. One you didn't mention but caused a huge impact in the industry, and something that Pensando's responding to is Amazon, but Annapurna Labs, and Annapurna Labs, a small Israeli company, and really driving a lot of the innovation when it comes to compute and networking at Amazon. The Graviton, Compute, and Nitro is what powers their Outposts solutions, so if you look at Amazon, they buy lots of pieces. It's that mixture of hardware and software. In early days people thought that they just bought kind of off-the-shelf white boxes and did it cheap, but really we see Amazon really hyper optimizes what they're doing. So Scott, let's talk a little bit about Pensando if we can. Amazon with the Nitro solutions built to Outposts, which is their hybrid solution, so the same stack that they put in Amazon they can now put in customers' data center. What Pensando's positioning is well, other cloud providers and enterprise, rather than having to buy something from Amazon, we're going to enable that. So what do you think about what you've seen and heard from Pensando, and what's that need in the market for these type of solutions? >> Yes, okay. So I'm glad you brought up Outposts, because I should've mentioned this next trend. We have, if you will, the disaggregated open software-based networking which is going on. It started in the public cloud, but then you have another trend taking hold, which is the so-called edge of the network, which is going to be driven by the emergence of 5G, and the technology called CBRS, and different wireless technologies that are emerging at the so-called edge of the network, and the purpose of the edge, remember, is to get closer to the customer, get larger bandwidth, and compute, and storage closer to the customer, and there's a lot of people excited about this, including the public cloud providers, Amazon's building out their Outposts, Microsoft has an Edge stack, the Azure Edge Stack that they've built. They've acquired a couple companies for $1 billion. They acquired Metaswitch, they acquired Affirmed Networks, and so all these public cloud providers are pushing their cloud out to the edge with this infrastructure, a combination of software and hardware, and that's the opportunity that Pensando is going after with this Outposts theme, and it's very interesting, Stu, because the coopetition is very tenuous. A lot of players are trying to occupy this edge. If you think about what Amazon did with public cloud, they sucked up all of this IT compute power and services applications, and everything moved from these enterprise private clouds to the public cloud, and Amazon's market cap exploded, right, because they were basically sucking up all the money for IT spending. So now if this moves to the edge, we have this arms race of people that want to be on the edge. The way to visualize it is a mini cloud. Whether this mini cloud is at the edge of Costco, so that when Stu's shopping at Costco there's AI that follows you in the store, knows everything you're going to do, and predicts you're going to buy this cereal and "We're going to give you a deal today. "Here's a coupon." This kind of big brother-ish AI tracking thing, which is happening whether you like it or not. Or autonomous vehicles that need to connect to the edge, and have self-driving, and have very low latency services very close to them, whether that's on the edge of the highway or wherever you're going in the car. You might not have time to go back to the public cloud to get the data, so it's about pushing these compute and data services closer to the customers at the edge, and having very low latency, and having lots of resources there, compute, storage, and networking. And that's the opportunity that Pensando's going after, and of course HPE is going after that, too, and HPE, as we know, is competing with its other big mega competitors, primarily Dell, the Dell/VMware combo, and the Cisco... The Cisco machine. At the same time, the service providers are interested as well. By the way, they have infrastructure. They have central offices all over the world, so they are thinking that can be an edge. Then you have the data center people, the Equinixes of the world, who also own real estate and data centers that are closer to the customers in the metro areas, so you really have this very interesting dynamic of all these big players going after this opportunity, putting in money, resources, and trying to acquire the right technology. Pensando is right in the middle of this. They're going after this opportunity using the P4 networking language, and a specialized ASIC, and a NIC that they think is going to accelerate processing and networking of the edge. >> Yeah, you've laid out a lot of really good pieces there, Scott. As you said, the first incarnation of this, it's a NIC, and boy, I think back to years ago. It's like, well, we tried to make the NIC really simple, or do we build intelligence in it? How much? The hardware versus software discussion. What I found interesting is if you look at this team, they were really good, they made a chip. It's a switch, it's an ASIC, it became compute, and if you look at the technology available now, they're building a lot of your networking just in a really small form factor. You talked about P4. It's highly programmable, so the theme of Future Proof Your Enterprise. With anything you say, "Ah, what is it?" It's a piece of hardware. Well, it's highly programmable, so today they position it for security, telemetry, observability, but if there's other services that I need to get to edge, so you laid out really well a couple of those edge use cases and if something comes up and I need that in the future, well, just like we've been talking about for years with software-defined networking, and network function virtualization, I don't want a dedicated appliance. It's going to be in software, and a form factor like Pensando does, I can put that in lots of places. They're positioning they have a cloud business, which they sell direct, and expect to have a couple of the cloud providers using this solution here in 2020, and then the enterprise business, and obviously a huge opportunity with HPE's position in the marketplace to take that to a broad customer base. So interesting opportunity, so many different pieces. Flexibility of software, as you relayed, Scott. It's a complicated coopetition out there, so I guess what would you want to see from the market, and what is success from Pensando and HPE, if they make this generally available this month, it's available on ProLiant, it's available on GreenLake. What would you want to be hearing from customers or from the market for you to say further down the road that this has been highly successful? >> Well, I want to see that it works, and I want to see that people are buying it. So it's not that complicated. I mean I'm being a little superficial there. It's hard sometimes to look in these technologies. They're very sophisticated, and sometimes it comes down to whether they perform, they deliver on the expectation, but I think there are also questions about the edge, the pace of investment. We're obviously in a recession, and we're in a very strange environment with the pandemic, which has accelerated spending in some areas, but also throttled back spending in other areas, and 5G is one of the areas that it appears to have been throttled back a little bit, this big explosion of technology at the edge. Nobody's quite sure how it's going to play out, when it's going to play out. Also who's going to buy this stuff? Personally, I think it's going to be big enterprises. It's going to start with the big box retailers, the Walmarts, the Costcos of the world. By the way, Walmart's in a big competition with Amazon, and I think one of the news items you've seen in the pandemic is all these online digital ecommerce sales have skyrocketed, obviously, because people are staying at home more. They need that intelligence at the edge. They need that infrastructure. And one of the things that I've heard is the thing that's held it back so far is the price. They don't know how much it's going to cost. We actually ran a survey recently targeting enterprises buying 5G, and that was one of the number one concerns. How much does this infrastructure cost? So I don't actually know how much Pensando costs, but they're going to have to deliver the right ROI. If it's a very expensive proprietary NIC, who pays for that, and does it deliver the ROI that they need? So we're going to have to see that in the marketplace, and by the way, Cisco's going to have the same challenge, and Dell's going to have the same challenge. They're all racing to supply this edge stack, if you will, packaged with hardware, but it's going to come down to how is it priced, what's the ROI, and are these customers going to justify the investment is the trick. >> Absolutely, Scott. Really good points there, too. Of course the HPE announcement, big move for Pensando. Doesn't mean that they can't work with the other server vendors. They absolutely are talking to all of them, and we will see if there are alternatives to Pensando that come up, or if they end up singing with them. All right, so what we have here is I've actually got quite a few interviews with the Pensando team, starting with I talked about MPLS. We have Prem, Jane, and Sony Giandoni, who are the P and the S in MPLS as part of it. Both co-founders, Prem is the CEO. We have Silvano Guy who, anybody that followed this group, you know writes the book on it. If you watched all the way this far and want to learn even more about it, I actually have a few copies of Silvano's book, so if you reach out to me, easiest way is on Twitter. Just hit me up at @Stu. I've got a few copies of the book about Pensando, which you can go through all those details about how it works, the programmability, what changes and everything like that. We've also, of course, got Hewlett Packard Enterprise, and while we don't have any customers for this segment, Scott mentioned many of the retail ones. Goldman Sachs is kind of the marquee early customer, so did talk with them. I have Randy Pond, who's the CFO, talking about they've actually seen an increase beyond what they expected at this point of being out of stealth, only a little over six months, even more, which is important considering that it's tough times for many startups coming out in the middle of a pandemic. So watch those interviews. Please hit us up with any other questions. Scott Raynovich, thank you so much for joining us to help talk about the industry, and this Pensando partnership extending with HPE. >> Thanks, Stu. Always a pleasure to join theCUBE team. >> All right, check out thecube.net for all the upcoming, as well as if you just search "Pensando" on there, you can see everything we had on there. I'm Stu Miniman, and thank you for watching theCUBE. 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>> Narrator: From around the globe, its theCUBE! With digital coverage of enterprise data automation. An event series brought to you by Io-Tahoe. >> Okay, we're back, welcome back to Data Automated, Ajay Vohora is CEO of Io-Tahoe. Ajay, good to see you, how are things in London? >> Things are doing well, things are doing well, we're making progress. Good to see you, hope you're doing well, and pleasure being back here on theCUBE. >> Yeah, it's always great to talk to you, we're talking enterprise data automation, as you know, within our community we've been pounding the whole DataOps conversation. A little different, though, we're going to dig into that a little bit, but let's start with, Ajay, how are you seeing the response to COVID, and I'm especially interested in the role that data has played in this pandemic. >> Yeah, absolutely, I think everyone's adapting, both socially and in business, the customers that I speak to, day in, day out, that we partner with, they're busy adapting their businesses to serve their customers, it's very much a game of ensuring that we can serve our customers to help their customers, and the adaptation that's happening here is trying to be more agile, trying to be more flexible, and there's a lot of pressure on data, lot of demand on data to deliver more value to the business, to serve that customer. >> Yeah, I mean data, machine intelligence and cloud are really three huge factors that have helped organizations in this pandemic, and the machine intelligence or AI piece, that's what automation is all about, how do you see automation helping organizations evolve, maybe faster than they thought they might have to? >> For sure, I think the necessity of these times, there's, as they say, there's a lot of demand on doing something with data, data, a lot of businesses talk about being data-driven. It's interesting, I sort of look behind that when we work with our customers, and it's all about the customer. My peers, CEOs, investors, shareholders, the common theme here is the customer, and that customer experience starts and ends with data. Being able to move from a point that is reacting to what the customer is expecting, and taking it to that step forward where you can be proactive to serve what that customer's expectation to, and that's definitely come alive now with the current time. >> Yeah, so as I said, we were talking about DataOps a lot, the idea being DevOps applied to the data pipeline, but talk about enterprise data automation, what is it to you and how is it different from DataOps? >> Yeah, great question, thank you. I think we're all familiar with, got more and more awareness around DevOps as it's applied to processes, methodologies that have become more mature over the past five years around DevOps, but managing change, managing application life cycles, managing software development, DevOps has been great, but breaking down those silos between different roles, functions, and bringing people together to collaborate. And we definitely see that those tools, those methodologies, those processes, that kind of thinking, lending itself to data with DataOps is exciting, we're excited about that, and shifting the focus from being IT versus business users to, who are the data producers and who are the data consumers, and in a lot of cases it can sit in many different lines of business. So with DataOps, those methods, those tools, those processes, what we look to do is build on top of that with data automation, it's the nuts and bolts of the algorithms, the models behind machine learning, the functions, that's where we invest our R&D. And bringing that in to build on top of the methods, the ways of thinking that break down those silos, and injecting that automation into the business processes that are going to drive a business to serve its customer. It's a layer beyond DevOps, DataOps, taking it to that point where, way I like to think about it is, is the automation behind the automation. We can take, I'll give you an example of a bank where we've done a lot of work to move them into accelerating their digital transformation, and what we're finding is that as we're able to automate the jobs related to data, and managing that data, and serving that data, that's going into them as a business automating their processes for their customer. So it's definitely having a compound effect. >> Yeah, I mean I think that DataOps for a lot of people is somewhat new, the whole DevOps, the DataOps thing is good and it's a nice framework, good methodology, there is obviously a level of automation in there, and collaboration across different roles, but it sounds like you're talking about sort of supercharging it if you will, the automation behind the automation. You know, organizations talk about being data-driven, you hear that thrown around a lot. A lot of times people will sit back and say "We don't make decisions without data." Okay, but really, being data-driven is, there's a lot of aspects there, there's cultural, but there's also putting data at the core of your organization, understanding how it affects monetization, and as you know well, silos have been built up, whether it's through M&A, data sprawl, outside data sources, so I'm interested in your thoughts on what data-driven means and specifically how Io-Tahoe plays there. >> Yeah, sure, I'd be happy to put that through, David. We've come a long way in the last three or four years, we started out with automating some of those simple, to codify, but have a high impact on an organization across a data lake, across a data warehouse. Those data-related tasks that help classify data. And a lot of our original patents and IP portfolio that were built up is very much around there. Automating, classifying data across different sources, and then being able to serve that for some purpose. So originally, some of those simpler challenges that we help our customers solve, were around data privacy. I've got a huge data lake here, I'm a telecoms business, so I've got millions of subscribers, and quite often a chief data office challenge is, how do I cover the operational risk here, where I've got so much data, I need to simplify my approach to automating, classifying that data. Reason is, can't do that manually, we can't throw people at it, and the scale of that is prohibitive. Quite often, if you were to do it manually, by the time you've got a good picture of it, it's already out of date. So in starting with those simple challenges that we've been able to address, we've then gone on and built on that to see, what else do we serve? What else do we serve for the chief data officer, chief marketing officer, and the CFO, and in these times, where those decision-makers are looking for, have a lot of choices in the platform options that they take, the tooling, they're very much looking for that Swiss army knife, being able to do one thing really well is great, but more and more, where that cost pressure challenge is coming in, is about how do we offer more across the organization, bring in those business, lines of business activities that depend on data, to not just with IT. >> So we like, in theCUBE sometimes we like to talk about okay, what is it, and then how does it work, and what's the business impact? We kind of covered what it is, I'd love to get into the tech a little bit in terms of how it works, and I think we have a graphic here that gets into that a little bit. So guys, if you could bring that up, I wonder, Ajay, if you could tell us, what is the secret sauce behind Io-Tahoe, and if you could take us through this slide. >> Ajay: Sure, I mean right there in the middle, the heart of what we do, it is the intellectual property that were built up over time, that takes from heterogeneous data sources, your Oracle relational database, your mainframe, your data lake, and increasingly APIs and devices that produce data. And now creates the ability to automatically discover that data, classify that data, after it's classified then have the ability to form relationship across those different source systems, silos, different lines of business, and once we've automated that, then we can start to do some cool things, such as put some context and meaning around that data. So it's moving it now from being data-driven, and increasingly where we have really smart, bright people in our customer organizations who want to do some of those advanced knowledge tasks, data scientists, and quants in some of the banks that we work with. The onus is on them, putting everything we've done there with automation, classifying it, relationship, understanding data quality, the policies that you can apply to that data, and putting it in context. Once you've got the ability to power a professional who's using data, to be able to put that data in context and search across the entire enterprise estate, then they can start to do some exciting things, and piece together the tapestry, the fabric, across their different system. Could be CRM, ELP systems, such as SAP, and some of the newer cloud databases that we work with, Snowflake is a great one. >> Yeah, so this is, you're describing sort of one of the reasons why there's so many stovepipes in organizations, 'cause data is kind of locked into these silos and applications, and I also want to point out that previously, to do discovery, to do that classification that you talked about, form those relationships, to glean context from data, a lot of that, if not most of that, in some cases all of that would've been manual. And of course it's out of date so quickly, nobody wants to do it because it's so hard, so this again is where automation comes into the idea of really becoming data-driven. >> Sure, I mean the efforts, if I look back maybe five years ago, we had a prevalence of data lake technologies at the cutting edge, and those have started to converge and move to some of the cloud platforms that we work with, such as Google and AWS. And I think very much as you've said it, those manual attempts to try and grasp what is such a complex challenge at scale, quickly runs out of steam, because once you've got your fingers on the details of what's in your data estate, it's changed. You've onboarded a new customer, you've signed up a new partner, a customer has adopted a new product that you've just launched, and that slew of data keeps coming, so it's keeping pace with that, the only answer really here is some form of automation. And what we've found is if we can tie automation with what I said before, the expertise, the subject matter experience that sometimes goes back many years within an organization's people, that augmentation between machine learning, AI, and that knowledge that sits inside the organization really tends to allot a lot of value in data. >> Yeah, so you know well, Ajay, you can't be as a smaller company all things to all people, so the ecosystem is critical. You're working with AWS, you're working with Google, you got Red Hat, IBM as partners. What is attracting those folks to your ecosystem, and give us your thoughts on the importance of ecosystem. >> Yeah, that's fundamental, I mean when I came into Io-Tahoe here as CEO, one of the trends that I wanted us to be part of was being open, having an open architecture that allowed one thing that was close to my heart, which was as a CEO, a CIO, well you've got a budget vision, and you've already made investments into your organization, and some of those are pretty long term bets, they could be going out five, 10 years sometimes, with a CRM system, training up your people, getting everybody working together around a common business platform. What I wanted to ensure is that we could openly plug in, using APIs that were available, to a lot of that sunk investment, and the cost that has already gone into managing an organization's IT, for business users to perform. So, part of the reason why we've been able to be successful with some of our partners like Google, AWS, and increasingly a number of technology players such as Red Hat, MongoDB is another one that we're doing a lot of good work with, and Snowflake, there is, those investments have been made by the organizations that are our customers, and we want to make sure we're adding to that, and then leveraging the value that they've already committed to. >> Okay, so we've talked about what it is and how it works, now I want to get into the business impact, I would say what I would be looking for, from this, would be can you help me lower my operational risk, I've got tasks that I do, many are sequential, some are in parallel, but can you reduce my time to task, and can you help me reduce the labor intensity, and ultimately my labor cost, so I can put those resources elsewhere, and ultimately I want to reduce the end to end cycle time, because that is going to drive telephone number ROI, so am I missing anything, can you do those things, maybe you can give us some examples of the ROI and the business impact. >> Yeah, I mean the ROI, David, is built upon three things that I've mentioned, it's a combination of leveraging the existing investment with the existing estate, whether that's on Microsoft Azure, or AWS, or Google, IBM, and putting that to work, because the customers that we work with have made those choices. On top of that, it's ensuring that we have got the automation that is working right down to the level of data, at a column level or the file level. So we don't deal with metadata, it's being very specific, to be at the most granular level. So as we run our processes and the automation, classification, tagging, applying policies from across different compliance and regulatory needs an organization has to the data, everything that then happens downstream from that is ready to serve a business outcome. It could be a customer who wants that experience on a mobile device, a tablet, or face to face, within a store. And being able to provision the right data, and enable our customers to do that for their customers, with the right data that they can trust, at the right time, just in that real time moment where a decision or an action is being expected, that's driving the ROI to be in some cases 20x plus, and that's really satisfying to see, that kind of impact, it's taking years down to month, and in many cases months of work down to days, and some cases hours, the time to value. I'm impressed with how quickly out of the box, with very little training a customer can pick up our tool, and use features such as search, data discovery, knowledge graph, and identifying duplicates, and redundant data. Straight off the bat, within hours. >> Well it's why investors are interested in this space, I mean they're looking for a big, total available market, they're looking for a significant return, 10x is, you got to have 10x, 20x is better. So that's exciting, and obviously strong management, and a strong team. I want to ask you about people, and culture. So you got people process technology, we've seen with this pandemic that the processes are really unpredictable, and the technology has to be able to adapt to any process, not the reverse, you can't force your process into some static software, so that's very very important, but at the end of the day, you got to get people on board. So I wonder if you could talk about this notion of culture, and a data-driven culture. >> Yeah, that's so important, I mean, current times is forcing the necessity of the moment to adapt, but as we start to work our way through these changes and adapt and work with our customers to adapt to these changing economic times, what we're seeing here is the ability to have the technology complement, in a really smart way, what those business users and IT knowledge workers are looking to achieve together. So, I'll give you an example. We have quite often with the data operations teams, in the companies that we are partnering with, have a lot of inbound inquiries on a day to day level, "I really need this set of data because I think it can help "my data scientists run a particular model," or "What would happen if we combine these two different "silos of data and get some enrichment going?" Now those requests can sometimes take weeks to realize, what we've been able to do with the power of (audio glitches) technology, is to get those answers being addressed by the business users themselves, and now, with our customers, they're coming to the data and IT folks saying "Hey, I've now built something in a development environment, "why don't we see how that can scale up "with these sets of data?" I don't need terabytes of it, I know exactly the columns and the feats in the data that I'm going to use, and that cuts out a lot of wastage, and time, and cost, to innovate. >> Well that's huge, I mean the whole notion of self-service in the lines of business actually feeling like they have ownership of the data, as opposed to IT or some technology group owning the data because then you've got data quality issues, or if it doesn't line up with their agenda, you're going to get a lot of finger pointing, so that is a really important piece of it. I'll give you a last word, Ajay, your final thoughts if you would. >> Yeah, we're excited to be on this path, and I think we've got some great customer examples here, where we're having a real impact in a really fast pace, whether it's helping them migrate to the cloud, helping them clean up their legacy data lake, and quite often now, the conversation is around data quality. As more of the applications that we enable to work more proficiently could be data, RPA, could be robotic process automation, a lot of the APIs that are now available in the cloud platforms, a lot of those are dependent on data quality and being able to automate for business users, to take accountability of being able to look at the trend of their data quality over time and get those signaled, is really driving trust, and that trust in data is helping in turn, the IT teams, the data operations teams they partner with, do more, and more quickly. So it comes back to culture, being able to apply the technology in such a way that it's visual, it's intuitive, and helping just like DevOps has with IT, DataOps, putting the intelligence in at the data level, to drive that collaboration. We're excited. >> You know, you remind me of something, I lied, I don't want to go yet, if it's okay. I know we're tight on time, but you mentioned a migration to the cloud, and I'm thinking about the conversation with Paula from Webster Bank. Migrations are, they're a nasty word for organizations, and we saw this with Webster, how are you able to help minimize the migration pain and why is that something that you guys are good at? >> Yeah, I mean there are many large, successful companies that we've worked with, Webster's a great example. Where I'd like to give you the analogy where, you've got a lot of bright people in your teams, if you're running a business as a CEO, and it's a bit like a living brain. But imagine if those different parts of your brain were not connected, that would certainly diminish how you're able to perform. So, what we're seeing, particularly with migration, is where banks, retailers, manufacturers have grown over the last 10 years, through acquisition, and through different initiatives to drive customer value. That sprawl in their data estate hasn't been fully dealt with. It's sometimes been a good thing to leave whatever you've acquired or created in situ, side by side with that legacy mainframe, and your Oracle ERP. And what we're able to do very quickly with that migration challenge is shine a light on all the different parts of data application at the column level, or at the file level if it's a data lake, and show an enterprise architect, a CDO, how everything's connected, where there may not be any documentation. The bright people that created some of those systems have long since moved on, or retired, or been promoted into other roles, and within days, being able to automatically generate and keep refreshed the states of that data, across that landscape, and put it into context, then allows you to look at a migration from a confidence that you're dealing with the facts, rather than what we've often seen in the past, is teams of consultants and business analysts and data analysts, spend months getting an approximation, and a good idea of what it could be in the current state, and try their very best to map that to the future target state. Now with Io-Tahoe being able to run those processes within hours of getting started, and build that picture, visualize that picture, and bring it to life. The ROI starts off the bat with finding data that should've been deleted, data that there's copies of, and being able to allow the architect, whether it's we have working on GCP, or in migration to any of the clouds such as AWS, or a multicloud landscape, quite often now. We're seeing, yeah. >> Yeah, that visi-- That visibility is key to sort of reducing operational risk, giving people confidence that they can move forward, and being able to do that and update that on an ongoing basis means you can scale. Ajay Vohora, thanks so much for coming to theCUBE and sharing your insights and your experiences, great to have you. >> Thank you David, look forward to talking again. >> All right, and keep it right there everybody, we're here with Data Automated on theCUBE, this is Dave Vellante, and we'll be right back right after this short break. (calm music)

>> From around the globe. It's theCUBE, with digital coverage of DockerCon Live 2020. brought to you by Docker and its ecosystem partners. >> Hello and welcome to DockerCon 2020. I'm John Furrier here in the DockerCon virtual studios. It's CUBE studios it's theCUBE virtual meets DuckerCon 2020 virtual event with my coach, Jenny Barocio and Peter McKee, as well as Brett Fisher, over on the captains who's doing his sessions. This is the wrap up of the long day of continuous amazing action packed DockerCon 2020. Jenny and Peter, what a day we still got the energy. We can go another 24 hours, let's do it now. This is a wrap up. So exciting day, tons of sessions, great feedback. Twitter's on fire the chats and engagements are on fire, but this is the time where we do the most coveted piece, the community awards, so Jenny, this is the time for you to deliver the drum roll for the community awards, take it away. >> Okay, (mumbles) It's the past few years and have been able to recognize those in the community that deliver so much to everyone else. And even though we're wrapping up here, there is still other content going on because we just couldn't stop till five o'clock. Peter what's happening right now? >> Yeah, so over in the Devs in Action channel, we have earning Docker Daemon with rootless mode. That's still going on, should be a great talk. And then in the How To channel, we have transforming open source into live service with Docker. They're still running now, two great talks. >> Awesome, and then the captains are still going. I think they probably started the after party already, although this channel's going to wait till, you know, 30 more minutes for that one. So if you're an after party mode, definitely go check out after we announced the awards, Brett and Marcos and Jeff and the captain's channel. So, we have some great things to share. And I mentioned it in my last segment, but nothing happens without the collective community. DockerCon is no exception. So, I really just want to take a moment again to thank the Docker team, the attendees, our sponsors and our community leaders and captains. They've been all over the virtual conference today, just like they would have been at a real conference. And I love the energy. You know, as an organizer planning a virtual event, there's always the concern of how it's going to work. Right, this is new for lots of people, but I'm in Florida and I'm thrilled with how everyone showed up today. Yeah, for sure. And to the community done some excellent things, Marcus, over them in the Captain's channel, he has built out PWD play with Docker. So, if you haven't checked that out, please go check that out. We going to be doing some really great things with that. Adding some, I think I mentioned earlier in the day, but we're adding a lot of great content into their. A lot more labs, so, please go check that out. And then talking about the community leaders, you know, they bring a lot to the community. They put there their free time in, right? No one paying them. And they do it just out of sheer joy to give back to the community organizing events. I don't know if you ever organized an event Jenny I know you have, but they take a lot of time, right? You have to plan everything, you have to get sponsors, you have to find out place to host. And now with virtual, you have to figure out how you're going to deliver the feel of a meetup in virtually. And we just had our community summit the other day and we heard from the community leaders, what they're doing, they're doing some really cool stuff. Live streaming, Discord, pulling in a lot of tools to be able to kind of recreate that, feel of being together as a community. So super excited and really appreciate all the community leaders for putting in the extra effort one of these times. >> Yeah, for really adapting and continuing in their mission and their passion to share and to teach. So, we want to recognize a few of those awesome community leaders. And I think we get to it right now Peter, are you ready? >> Set, let's go for it, right away. >> All right, so, the first community leaders are from Docker Bangalore and they are rocking it. Sangam Biradar, Ajeet singh Raina and Saiyam Pathak, thank you all so much for your commitment to this community. >> All right, and the next one we have is Docker Panang. Thank you so much to Sujay Pillai, did a great job. >> Got to love that picture and that shirt, right? >> Yeah. >> All right, next up, we'd love to recognize Docker Rio, Camila Martins, Andre Fernande, long time community leaders. >> Yeah, if I ever get a chance that's. I have a bunch of them that I want to go travel and visit but Rio is on top of list I think. >> And then also-- >> Rio maybe That could be part of the award, it's, you get to. >> I can deliver. >> Go there, bring them their awards in person now, as soon as we can do that again. >> That would be awesome, that'd be awesome. Okay, the next one is Docker Guatemala And Marcos Cano, really appreciate it and that is awesome. >> Awesome Marcos has done, has organized and put on so many meetups this last year. Really, really amazing. All right, next one is Docker Budapest and Lajos Papp, Karoly Kass and Bence Lvady, awesome. So, the mentorship and leadership coming out of this community is fantastic and you know, we're so thrilled to write, now is you. >> All right, and then we go to Docker Algeria. Yeah we got some great all over the country it's so cool to see. But Ayoub Benaissa, it's been great look at that great picture in background, thank you so much. >> I think we need we need some clap sound effects here. >> Yeah where's Beth. >> I'm clapping. >> Lets, lets. >> Alright. >> Last one, Docker Chicago, Mark Panthofer. After Chicago, Docker Milwaukee and Docker Madison one meet up is not enough for Mark. So, Mark, thank you so much for spreading your Docker knowledge throughout multiple locations. >> Yeah, and I'll buy half a Docker. Thank you to all of our winners and all of our community leaders. We really, really appreciate it. >> All right, and the next award I have the pleasure of giving is the Docker Captain's Award. And if you're not familiar with captains, Docker captains are recognized by Docker for their outstanding contributions to the community. And this year's winner was selected by his fellow captains for his tireless commitment to that community. On behalf of Docker and the captains. And I'm sure the many many people that you have helped, all 13.3 million of them on Stack Overflow and countless others on other platforms, the 2020 tip of the Captain's Hat award winner is Brandon Mitchell, so so deserving. And luckily Brandon made it super easy for me to put together this slide because he took his free DockerCon selfie wearing his Captains' Hat, so it worked out perfectly. >> Yeah, I have seen Brandon not only on Stack Overflow, but in our community Slack answering questions, just in the general area where everybody. The questions are random. You have everybody from intermediate to beginners and Brandon is always in there answering questions. It's a huge help. >> Yeah, always in there answering questions, sharing code, always providing feedback to the Docker team. Just such a great voice, both in and out for Docker. I mean, we're so proud to have you as a captain, Brandon. And I'm so excited to give you this award. All right, so, that was the most fun, right? We get to do the community awards. Do you want to do any sort of recap on the day? >> What was your favorite session? What was your favorite tweet? Favorite tweet was absolutely Peter screenshotting his parents. >> Mom mom my dear mom, it's sweet though, that's sweet. I appreciate it, can't believe they gave me an award. >> Yeah, I mean, have they ever seen you do a work presentation before? >> No, they've seen me lecture my kids a lot and I can go on about life's lessons and then I'm not sure if it's the same thing but yeah. >> I don't think so. >> No they have never see me. >> Peter you got to get the awards for the kids. That's the secret to success, you know, and captain awards and the community household awards for the kids. >> Yeah, well I am grooming my second daughter, she teaches go to afterschool kids and never thought she would be interested in programming cause when she was younger she wasn't interested in, but yes, super interested in now I have to, going to bring her into the community now, yeah. >> All right, well, great awards. Jenny is there any more awards, we good on the awards? >> Nope, we are good on the awards, but certainly not the thank yous is for today. It's an absolute honor to put on an event like this and have the community show up, have our speakers show up have the Docker team show up, right? And I'm just really thrilled. And I think the feedback has been phenomenal so far. And so I just really want to thank our speakers and our sponsors and know that, you know, while DockerCon may be over, like what we did today here and it never ends. So, thank you, let's continue the conversation. There's still things going on and tons of sessions on demand now, you can catch up, okay. >> One more thing, I have to remind everybody. I mentioned it earlier, but I got to say it again go back, watch the keynote. And I'll say at this time there is an Easter egg in there. I don't think anybody's found it yet. But if you do, tweet me and might be a surprise. >> Well you guys-- >> Are you watching your tweet feed right now? Because you're going to get quite a few. >> Yeah, it's probably blowing up right now. >> Well you got to get on a keynote deck for sure. Guys, it's been great, you guys have been phenomenal. It's been a great partnership, the co-creation this event. And again, what's blows me away is the global reach of the event, the interaction, the engagement and the cost was zero to attend. And that's all possible because of the sponsors. Again, shout out to Amazon web services, Microsoft Azure Engine X, Cockroach Labs and sneak of Platinum sponsors. And also we had some ecosystem sponsors. And if you liked the event, go to the sponsors and say hello and say, thank you. They're all listed on the page, hit their sessions and they really make it possible. So, all this effort on all sides have been great. So, awesome, I learned a lot. Thanks everyone for watching. Peter you want to get a final word and then I'll give Jenny the final, final word. >> No again, yes, thank you, thank you everybody. It's been great, theCUBE has been phenomenal. People behind the scenes has been just utterly professional. And thank you Jenny, if anybody doesn't know, you guys don't know how much Jenny shepherds this whole process through she's our captain internally making sure everything stays on track and gets done. You cannot even imagine what she does. It's incredible, so thank you, Jenny. I really, really appreciate it. >> Jenny, take us home, wrap this up 2020, dockerCon. >> All Right. >> In the books, but it's going to be on demand. It's 365 days a year now, come on final word. >> It's not over, it's not over. Community we will see you tomorrow. We will continue to see you, thank you to everyone. I had a great day, I hope everyone else did too. And happy DockerCon 2020, see you next year. >> Okay, that's a wrap, see on the internet, everyone. I'm John, for Jenny and Peter, thank you so much for your time and attention throughout the day. If you were coming in and out, remember, go see those sessions are on a calendar, but now they're a catalog of content and consume and have a great evening. Thanks for watching. (upbeat music)

>> Announcer: From theCUBE Studios (upbeat music) in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. >> Hi, and welcome to a special CUBE Conversation. I'm Stu Miniman, coming to you from our Boston Area studio, and today, March 31st, 2020, is World Backup Day. Joining me is one of our CUBE alumni, Simon Taylor, who's the CEO of HYCU. Simon, we had you a couple weeks ago in our studio, of course. Today we have you joining us remotely. Thank you so much for joining us, and great to see you. >> Great to see you, as well Stu, as always. >> So, there's certain dates that everybody circles on the calendar and gets ready. In your industry, I have to imagine, normally World Backup Day would be a huge party, cake, and everything like that. Just, in all jest, it's my understanding, HYCU did not create World Backup Day, but it is gratuitous to talk about that, and it's something that's been around for a few years. Let's start there, thank you for joining. >> Yeah, absolutely Stu, and again, thanks for having me back on. You're going to get sick of having me on your wonderful program if we keep visiting too much, but I do appreciate it. I'm actually calling in today, as you can imagine, from Vermont, as we sort of escape the city here and get out in the countryside away from all the hectic and the crisis. You know, it's speaking of the crisis, I think that World Backup Day really could not have come at a better time, in some senses. It's so important, and I think it was created to help the world remember that their data loss is such a major issue, and that if we don't watch out for our data, if we don't backup our data, if we don't put proper data protection practices into place, we really can have a problem. And I think when we are moving to work-from-home environments, when we are moving out of the office, when the world is in such a state of flux, as it is today with Coronavirus, these are the moments when you want to really know that your data is protected, that you're safe. You know, we're seeing a rise in ransomware attacks. We're seeing all sorts of things that are tangential to the crisis with COVID-19, and I think, you know, us all taking a moment to kind of realize what an issue data loss is in the world, there just couldn't be a more important time to do that than during a crisis like this one. >> Yeah, Simon, unfortunately, it's scary times also for the IT department because bad actors are definitely making even more attacks right now, in the midst of the global pandemic, something that people are concerned about. When I've been looking out at the community, there's been conversations about, you know, "What does this mean for digital transformation, "and cloud adoption?" And some of the things I'm hearing, especially over in Europe, is there were certain companies, and if you look at certain countries, take Germany for one example, where they might have been a little bit slow to say, "Uh, I'm not sure "if I want to do the cloud." Well, if everybody's working from home for a little bit, and IT needs to keep the business running, there's been a push even faster to the cloud, and one of the main things we're going to talk about today is your partnership with Microsoft Azure. So love to hear what you're hearing from your customers out there, especially ones that normally it's, "Oh, I'm going to make my plan," and we know how fast, or slow, the enterprise normally moves, and now there's a little bit of an acceleration to say, "Hey, we need to get involved in the cloud, and my backup, my data protection is absolutely even more critical when I go to the public cloud." >> Oh my gosh, Stu, absolutely. You're right on all counts. I mean, one of the most horrific issues that we're seeing over, and over, and over again with our customers, and it's such a shame, is that there are bad actors out there. There are bad individuals out there who are trying to take advantage of this crisis, and what they're doing is they're understanding that they can now exploit the fact there's so much work from home. We're seeing more man-in-the-middle attacks. We're seeing more customers who are calling us up and saying, "I've just been hit with a ransomware, "all my data's locked down. "Somebody didn't follow protocol when they were working "from home, and boom, all of the sudden we're being asked "to pay a million dollars in bitcoin, "and what do I do?" I'm really, really proud of my team for stepping up during the crisis. We've actually seen more than 10 different customers, just in the last month, who've called us up and have said, "You know, I'm supposed to pay this bitcoin ransom. "Can you get my data back?" In all 10 out of 10 cases, because of how natively integrated HYCU is into the platforms we support, we were actually able to recover that data within the next few hours to days, get it back for them before they had to pay out those ransoms. So again, not just a plug for HYCU, a plug for backup and recovery in general. A plug for everybody who's thinking about, "How do I keep myself safe when I'm moving to the cloud?" Absolutely, this is the time to keep yourself safe with proper data protection strategies. You know, I think the second thing that you bring up, very rightly so, is that there were a lot of countries, Germany's one of them but there's many, who had sort of been on the back foot during this crisis, and had always expected that on-prem was going to be a majority of their infrastructure for the foreseeable future. They were all dipping their toe in the cloud water, the cloud pond, as it were, but you didn't see a lot of folks in Europe who were 100% committing to cloud. Well, wow, has that changed. You know, as we moved to work from home, you need a lot of that dynamic scaling that only true cloud environments, public cloud, can provide. But I think the second thing, and maybe more importantly, is we don't want to see our IT departments having to go into the office. We don't want to see them having to put themselves, and potentially their families at risk, simply to go in and manage data. So being able to work off of infrastructure-as-a-service, hugely critical during the crisis, and to the fact that HYCU is a natively integrated service into those different enterprise and public clouds means that you can do all of it remotely. And I think this is where the whole HYCU simplicity is a pillar, and a guiding principle for the company has become so important. I can't tell you how many customers have called us up and said, "I wanted to be at home with my family. "The other backup companies, the legacy deployments we had, "just simply wouldn't have allowed me to stay at home. "I would have needed to go back to the office. "Do you have something that's as-a-service?" That certainly brings me to, I think, your third point, which is we are absolutely thrilled here today, on World Backup Day, in the midst of this crisis, to be announcing the launch of HYCU for Azure. And again, this is a natively integrated service that customers can literally just VPN to their set data center, go directly to their cloud, go directly to Azure, in the marketplace turn on HYCU for Azure, and boom, you're going to have all of that wonderful, natively integrated, purpose filled backup recovery as a service. You're going to have all of that application support. You're going to have all of the things you've become, sort of used to, Stu, when we talk about HYCU, natively integrated into Azure as well. And again, I think because of this crisis, because we want people to stay at home, we want to flatten that curve, the fact that we've got this new service for Azure, which is so important for everybody, I think is just critical at this particular time. >> Yeah, definitely hugely important. We've been talking to you and HYCU for a number of years, Simon. Of course, started out very focused on, really, a Nutanix environment, broadened out to really the virtualization environment, and you're really going with your customers heavily into a cloud environment. So, Azure, really important. When I was at Microsoft Ignite last year, CEO Satya Nadella, I could sum up his main them in one word, and that was trust. So, number one, it was a knock against a certain company in the cloud that mainly drive their revenue from ads, but when he talked about customers and partners, he wanted Microsoft to really be the company that people trust in that environment. We've seen Microsoft, one of the biggest movers from an application standpoint, the real push to Office 365, got people to really embrace and trust SaaS. Would love to hear your early customers who you've been working through for this announcement, why this is so important that HYCU, not only supporting and integrating with Azure, but in the Azure marketplace, and what your customers are telling you. >> Gosh, that's such a great question, Stu. You know, first, just talking about Satya Nadella, I really think the world of him. I think he does truly believe it, when he, you know, if you've read his book, "Hit Refresh", you do start to see a man who truly cares, not just about the bottom line, or even the top line, for that matter, but really strives to drive real customer value. And I think one of the things he really did at Microsoft is he talks a lot about how the solutions that they're selling have real world effects across so many different industries. It's the net result of the technology that I think he cares about, as opposed to just the sum of its parts. So it's really, really interesting, I think, when we think about him and his leadership style, to think about how HYCU kind of fits into that. And you know, one of the things I'm really proud to announce is that here, on World Backup Day, in the midst of this horrible pandemic, what we're doing, as we launch HYCU for Azure is we're actually going to give it entirely free, no cost, no strings attached, to the entire world for the next three months. And the reason we're choosing to do that is we believe that data protection is so important, that in a situation like this, it's incredibly important that people don't take life threatening risks, things that could threaten not only them, but their families, going in to the office to do this. You know, and I think one of the great things about HYCU and also HYCU with Protege, our multi-cloud data management platform, is that you can now migrate your data from on-prem to the cloud with the touch of a button from home. You can literally go sign up, it's free of charge for all the HYCU backup you want for the next three months. You know, get on there and protect your data, that's number one. You know, that adds real value to customers in the midst of this crisis. Number two is you can use HYCU Protege to then migrate entire workloads, keep them safe, whether it's applications, whether it's databases. You know, we want customers to know that they can trust a third party, like HYCU, to be able to automate the process of migration to the cloud, and then you know, in the midst of a crisis like this everybody's thinking about disaster recovery. Well, guess what? We can even more data back on-prem, using a runbook, and we can actually drive true disaster recovery preparedness, as well, all for Azure customers. You know, Stu, you and I were talking about this offline a few minutes ago, but the reality is, we've interviewed our customers, and 72% of them, and that's in 71 countries now around the world, funny enough, but 72% of those customers are Azure customers, as well. So when we talk about our on-prem business, 72% of our on-prem business is also using Azure. So the ability to dynamically move these workloads to the cloud, move it back again for DR, as well as protect that data wherever it's sitting, and do all of that from home, with simplicity, and for the next three months no cost, I think that's how we're trying to drive value and trust into the Azure marketplace. >> Yeah, first of all, Simon, that's really a lot of good pieces here. It almost becomes a little bit trite when we talk about, "Oh, well, I want to build optionality "into my product, I want to be ready to change "and adjust things." But the environment and landscape that we're living with today is we understand, companies need to be able to react really fast, and they need to be able to adjust with this changing landscape. So what they're doing last month, versus what they're doing today, versus what they might doing in a couple of months, you know, I don't want to get locked in. I don't want to make any big decision. So therefore, it's great to see you're giving customers flexibility there. They've got both the free usage of the software, but also that migration built in to HYCU Protege. You know, how do I move my data around? How do I make sure it's still protected? So important that, you know, we've been talking for years about the ability to make changes fast and to move with speed, but you know, I think today's landscape really just put the point on (laughs), you know, we've been planning for this, in some ways, and this might have been the exact thing we're planning for, but this is the reason that this technology's so important. >> It's so well said, Stu. I mean, honestly, just like you said, we started out with the purpose-built back up recovery for Nutanix, and then we added GCP, we added VMware, now of course, we're launching Azure, but in each case, we said it's got to be natively integrated, it's got to be super simple, we've got to automate every process we can. We want to make sure that customers can wake up in the morning, log in to their cloud infrastructure, whether it's GCP, now Azure, you know, turn this on as a service. We always say, "There's nothing to download "when it's a true service," right? And I think that's so important now. It used to be kind of a talking point, but I think now people are really seeing the true value, which is when you don't need to go in to your data center, when you don't need to VPN in, when you don't need to figure out all the rest of this architecture. Well, when people are moving enormous amounts of data, and buying so much VDI, and deploying all these work-from-home modules to, sort of, protect their infrastructure, and create and environment that works for the current conditions, the last thing they have to do is put themselves at risk for the backup. I think because this is purpose-built, because it's a true service, because it's a natural extension, really, of the cloud provider they've chosen, or multiple, I think we make that really, really easy for customers, and we're very proud of the work we've done on that front. >> All right, Simon, just want to give you the opportunity. You know, what kind of feedback have you had from customers over the last couple of weeks, specifically? You talked about how important Azure was for them, of course, prior to this announcement, but just anecdotally, we'd love to hear just viewpoints as to customers you're talking and working with in these challenging times. >> Sure, sure, so first of all, everybody's hard pressed. I mean, there's a crunch everywhere. You know, people are feeling this sort of potential for a really, really systemic downturn into the economy, but at the same time, there were really urgent needs in terms of acquiring mission-critical infrastructure to support the move to work from home. And I think that's caused massive shifts in the way people are thinking about purchasing technology, and specifically infrastructure technology in the marketplace. People truly want services now. You know, before it was something that maybe drove the valuation of a company, et cetera, et cetera, but now people are saying, "Hey, it's nothing to do with that at all. "I just want a service that I can scale up, "and I can scale down. "I want it now, I want it fast, and I want it simple." So I think anything that's natively integrated, and is acting as a SaaS, true SaaS offering, has a real advantage in today's marketplace. I think the second thing is, that as customers are moving in droves to VDI, you know, I think there's a lot of talk right now about whether it's ever going to move 100% back. I think as people are discovering how effective and powerful we can be as we work from home, I mean, Stu, look at us right now having this very conversation, I think it's amazing what we're able to achieve with the technology that's out there, and I think that's really reduced the panic, and I think it's something that people aren't talking about. That there's such, imagine what the panic would have been if we didn't have Zoom, if we weren't able to do a GoToMeeting, if we weren't able to log in with a VPN and access our infrastructure. I mean, the entire world would have shut down like this. Now there's arguments being made that it may still shut down, et cetera, but you know we have at least delayed that process. I think we've created a lot of support for the economy and the environment through all of the technology that the marketplace is presenting to customers. And I think the next step in that is making sure that we recognize a couple of things. You know, we're seeing, again, a huge rise in ransomware attacks. There are many, many bad actors out there looking to exploit and take advantage of this situation, which is why I say you don't need to buy our product, but please, if you've got Azure, go and turn on the backup. Well, why wouldn't you? Protect your data, make sure it's recoverable. God forbid anything bad happens, or you do get attacked, make sure you can get that data back from a third party. Make sure it's really easy to recover. Make sure all your mission-critical applications and databases are supported. And I think if we do those things, and we work together to protect our customers, and for just a very short period of time, really don't worry so much about how much money we're going to make off of them, but think about how to protect them, truly, I think that's where the value is, and I think that's how we as human beings, can sort of do a better job of protecting each other. >> All right, well, Simon, thank you so much for all the updates. Happy World Backup Day. You know, I definitely look forward to chatting with you soon, and thanks for joining, and please be safe. >> Stu, always a pleasure. Please stay healthy, as well, take care. >> All right, I'm Stu Miniman, and you've been watching theCUBE here with some of our remote interviews. 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