from Gillette Stadium in Foxborough Massachusetts it's the cube covering Vita winter warmer 2019 brought to you by silicon angle media hi I'm Stu minimun and this is the cube at V tug winter warmer 2019 at Gillette Stadium home of the New England Patriots the AFC Championship team going to the Super Bowl third year in a row yet again Randall right yeah paying it's my Los Angeles Rams oh so happy to welcome to the program Randall hunt who's a software engineer with AWS did a keynote this morning I believe it was a hundred AWS features in 50 minutes and felt like you we added a couple more than 100 and went a little over 50 minutes but I think we probably hit 57 minutes that was what the slide counter said but yeah I added a couple of the updates since reinvent you know reinvent is not the end of our innovation we continued releasing new stuff after that all right so our program we're not going to be showing JavaScript we're gonna take a deep breath and slow down a little bit because you know our audience absolutely knows Amazon I tell you this show remember like four years ago first time AWS presented me at Microsoft and AWS here and people heard cloud 101 and I was like come on I could have given this presentation and they were walking around like oh my god I just you know found out that you know who you know horseless carriages and I can do that do them and things like this so you know cloud we've been there for a decade but we're still I believe you know day zero day one is what Amazon always likes this is day one it's always day one so there's no way we can shove the entire reinventing keynote into this discussion so you know want to start first Tulsa rent a little bit about yourself your role what you work on and what customers you talk to sure so I studied physics and then I found out physicists don't really make any money so I became a software engineer and I worked at NASA I worked at SpaceX and worked with this company called MongoDB back then it was called Tianjin and then I am an Amazon I was my second time around in Amazon I'm a software engineer there but I'm also a Technical Evangelist and what that means is I get to travel around the world and make make all of the demos and chat with all of our customers and kind of solicit feedback from them and then kind of try to act as the voice of the customer for the service teams whenever I can get them to listen yeah so probably not going to go into open source versus software licensing of things with you because we want to make sure that we can publish I tell you space is one of those things I love it when I've interviewed people that have been in space I've talked to lots of companies that have our code in space Amazon you have I loved you know robotics and space are hard and we make it easy and I kind of laugh cuz I was an engineer as an undergrad I mean I studied a little bit of you know what it takes to break gravity and understand I always love watching you know all the shows about space and track SpaceX would you work for and things like that give me a break you haven't made space easy well I think space as a whole is getting easier this industry is becoming more approachable one of the things that we launched to reinvent this year was a ground station and this is something where if you have an S band or UHF you know satellite and leo which is low Earth orbit or mio which is medium Earth orbit you can basically down stream that data to one of these ground stations which is you know essentially attach to a region you know in this case us East 2 which is in a like Ohio area and you can go and say hey just stream this data into s3 for me or you know let me access this from my V PC which is pretty gnarly if you think about it you know you have a you have an IP address which is a satellite in space yeah I love I worked on replication technology 15 years ago and it was like okay can the application take the ping off the satellite or you know how do we do this so look we're leveraging satellites a little bit more I understand it's a great tagline to make those useful and more readily just you know it's amazing you think about when you think about my availability zones and regions it's now you know that things aren't just on the Terra Firma well I'm looking forward to the first availability zone on the on the moon or on Mars that that'll be you know when we have utopia planitia 1a that'll be the really cool AZ alright we heard the first blue origins working to Mars no well the latency you know if you have 300,000 and fit three hundred fifty thousand kilometers on average between the Earth and the moon so you know you can go around the earth it would speed of light 7.5 times every second to go to the moon is a fool I hang it's like six seven seconds or so so the latency requirements become a little bit harder there I roll more my wrong pin I have I have the Grace Hopper nanosecond which is the wit which is you know curled up and if you follow the white thing it's how long light would take to travel that and it does it in two nanoseconds so you got me I'm a physics lover and love space as does a lot of our audience so bring it down to the thing one of the things that amazon has done really well is I don't need to be a physics geek to be able to use this technology we're having arguments as to you know if I'm starting out or if I want to restart my career today do I go code or heck you know let me just use lambda and all these wonderful things that Amazon have and I might not even need to know traditional coding I mean when I learned programming you know it was you learned logic and wrote lines of code and then when you went to coding it's pulling pieces and modifying things and in the future it's it seems like serverless goes even further along that spectrum I definitely think there's opportunities for folks who have just you know I don't want to say modest coding abilities but people who were kind of you know industry adjacent scientists you know data scientists folks like that who may not necessarily be software engineers or have the they couldn't recite in Big O notation for mergesort and things like that from scratch you know but they know how to write basic code there's a lot of opportunity now for those developers and I'll call them developers to go and write a lambda function and just have it accomplishing a large portion of their business logic for their whole company I think the you know you have a spectrum of compute options you have you know ec2 on the one side and then you have containers and then as you move towards service you get this this you know spectrum between Fargate and lambda and lambda being the the chief level of abstraction but I I think in a couple cases you can you know even go further than that with things like amplify which is a service that well it's an open source project that we launched and it's also a service that we launched and it takes together a bunch of different AWS services things like app sank and kognito and lambda and it merges them all together with one CLI call you can go and say hey spin up a static site for me like a Hugo static site or something and it'll build the code pipeline build all that stuff for you without you having to you know worry about all the stuff and if developers are starting new today you know I remember when I started I really had to go deep on some of the networking stuff you know I had to learn all these different routers and like how to program them and these like the industry router so you know the million dollar ones and having to rack and stack this stuff and the knowledge is not really needed to operate of large-scale enterprise you know if you if you know a Ralph's table and you you you know V pcs you know you can run you know a multi-billion dollar company if you want yeah it's been interesting to watch too and you know I think the last five years the proliferation of services in AWS got to a point where is like oh my gosh if I wanted to kind of configure a server for my datacenter or configure an equivalent something that I wanted at AWS there was more choices in the public cloud than there was there and people like oh my gosh how do I learn it how do I do this but what we start to see is it's more don't need to do that because what do I want to do if there's an application that I can run where services that will help make it easier for me to do that because the whole it's not let me replicate what I was doing here and do it there but I have to kind of start with a clean sheet of paper and say okay well what what's the goal what data do I need what applications do I need to build and start there I'm curious what you see and how do you help companies through that so that this is a really common scenario so I this is a kind of key point here is enterprises and companies have existed since before the cloud was really around so why do we keep seeing so much uptick why do we keep seeing so many customers moving into the cloud and how do we make it easier for customers to get into the cloud with their existing workloads so along that same spectrum if you have greenfield projects if I were running my own company and I were doing everything I would absolutely start in the cloud and I would build everything as kind of cloud native and if you want to migrate these existing workloads that's part of the one of the things that we launched this year in partnership with VMware is VMware kind of interface for AWS so you can use your native vCenter and vSphere kind of control plane to access EBS to access route 53 and ec2 and all the other kind of underlying stuff that you are interested in run it you can even do RDS on VMware in my environment so that line is definitely blurring between my stuff and my stuff somewhere else and when people are talking about migrating workloads right you know you can take the lowest hanging fruit the most orthogonal piece of your infrastructure and you can say hey let me take this piece as an experimental proof of concept workload and what kind of lift and shift it into the cloud and then let me build the accoutrement the glue and all the other stuff that kind of is associated with that workload cloud native and you'll get additional agility your you know 1:1 ops person can manage this whole suite of things across 19 20 regions of AWS and you know there's kind of global availability and all this kind of good stuff that typically comes with the cloud and in addition to that as you keep moving more and more workloads over it's not like it's a static thing you know you can evolve you can adjust the application you can add new features and you can build new stuff as your move these applications over to the cloud yeah and it's interesting because just the dynamics are changing so much so there's been there's still so much movement to the cloud and then oh well some people I'm pulling stuff back and then you see you have a WS outposts so later 2019 we expect to Amazon to have you know footprint in people's environments and then you know Jeff just to make things even more complicated well the whole edge computing IOT and the like which you know everything from snowball and these pieces so the answer is it gets even more complicated but you know your your AWS I know is trying to help simplify this for use right the board I think I can say anything at all about AWS it's that if a customer is asking us to build something we are gonna do our best to make that customer happy we take customer feedback so incredibly seriously in all of our meetings all of our service team meetings you know we that voice of the customer is very strong and so if people are saying hey I want a AWS in my own datacenter you know that's kind of the genesis of outpost and it's this idea that well we have this control plane we have this hardware let's figure out how we can get it to more customers and customers are saying hey I want into my data center I want to just be able to plug in some fiber and plug in some power and I want it to work and that's the idea right we're gonna when I think of every company that I've watched there's usually something that people will gripe about and what I've been very impressed with Amazon Amazon absolutely listens and moves pretty fast to be able to address things and if you see you know if I'm a competitor of Amazon I'm like oh well you know this is the way that we get in there you know where we think we have an advantage chances are that Amazon is addressing it looking to you know move past it and you know absolutely the Amazon of 2019 is sure not the Amazon of 2018 or you know when you thought about it you know 2015 and it's big challenge for people as to because usually I think of something and you never get a second chance to make a first impression but it changes so much right everything changes that you know I need to revisit it it's like oh well this is the way I do things well Amazon has five different ways you can do that now um you know which one fits you best and I think that's important is different applications gonna have different characteristics that you want to be able to pull in and run in different ways yeah you know honestly I'm a huge fan of service I I think service is where a ton of different workloads are going to move into the future and I just see more and more companies migrating their existing you know everything from elastic Beanstalk applications so like vdq you know VMware images into the service environment and I like seeing that kind of uptick and someone recently I I can't remember who it was someone sent me a screenshot of their console with their ec2 instances in 2010 and maybe it was part of this 10-year challenge thing on Twitter where it's 2009 versus 2019 but they sent me you know they're in one large and the screenshot of the console from back then and they sent me a screenshot of 2019 and Wow things really have changed and you don't really notice it as much when you're using it every day but I can imagine you know their their Ops teams where they haven't logged into the console in three years because you know everything is done kind of in an automated fashion they set up their auto scaling group you know three years ago and then the only time they ever log in is to update to new instance types or something for the cost savings and I get messages on Twitter sometimes from people who are like whoa console got an update this is so cool and then sometimes we we get messages from people where you know we changed the EBS volume snapshotting things we had somebody who had it was like 130,000 EBS snapshots or something and they were like hey you removed my ability for me to select multiple snapshots it what it's like well you have a hundred and thirty thousand so we went in into the UI and we added a little icon that works better for large groups of snapshots you know if there's a customer pain point we will do everything we can to address it all right Randall Hunt really appreciate you sharing with us your experience what's going on with customers and absolutely that 10-year challenge we know things change fast we used to measure in decades I say now it's usually more like you know 18 to 24 months before between everything AWS in 2029 it's gonna be crazy and I can't I can't imagine what its gonna look like then all right well the cube we started broadcasting from in 2010 we appreciate you staying with us through 2019 check out the cube net for all of our programming I'm Stu minimun and thanks so much for watching the key

>> Live from Washington, DC. It's theCUBE. Covering AWS Public Sector Summit 2018. Brought to you by Amazon Web Services, and its ecosystem partners. >> Welcome back to The District everybody. We're here covering the AWS Public Sector Summit, #AWSPSSummit. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante and I'm here with my co-host Stuart Miniman. Gus Hunt is here, he's the Managing Director of Accenture. Great to see you. >> Great, thanks. Dave, Stu, appreciate being here. >> Thanks for coming on. Last night we were at the Accenture Event, it was hosted by Teresa Carlson and Accenture, a jam packed high-level audience. It was really, really fabulous. You couldn't make it, cause you got stuck in-- >> Weather-wise, got trapped in Atlanta. >> Unfortunately, Gus, you missed a lot, it was very good. But bring us up to speed on just sort of the state of where we're at with Accenture. You guys are heavily involved with the CIA implementation. We can talk about that a little bit. But start with Accenture, what you guys got going on in the Government. >> So Accenture Federal Services, which is the part I'm within, supports all of our federal agencies across the board. And we do enormous amount of work in the Cloud Services. In fact, Accenture itself is the largest partner of AWS in the world, right, providing cloud services directly engaged with Amazon. We have our Accenture Amazon Business Group, for example, that we leverage across the board. So we are really heavily steep, both in what it takes to help companies and our federal clients move to the cloud, but also how to take real advantage of it, how to gain the efficiencies that they need, and how to do this very securely. Because so much of I think the concerns that get expressed by people are a misunderstanding about whether or not the cloud is secure, versus how to do it securely in the cloud, if you understand the nuance difference there. >> Right, right. So, well, explain that. Let's double-click on that nuance there. A lot of people so early on it was concerns about the cloud, and then it kind of flipped and said, well, obviously the cloud's going to be more secure than what I could do as an organization. We heard what the CIA said today. They said, "On the worst day in the public cloud, "security's far better than in it is "in my client service systems." So help us unpack that a little. >> So, I'll take you back a few years. I spent 20 years in Federal Government working for CIA. I retired from there as their Chief Technology Officer. And I led basically the C2S deal that we put together in order to bring cloud services into the agency. And we did that fundamentally for four reasons. One was velocity. We had to get our speed of abilities, delivery capabilities up to match that what was happening in the private sector, in the cloud. The second was efficiencies. We had to find a way to really tap into the extraordinary efficiencies being driven by the cloud world and the cloud environment, with this continuous drop in price and storage, and computing, and things like that. How do we leverage that to our advantage and enable us now instead of to keep pace in the world when we knew that data was doing like this, and that the ability to exploit data is what the business is all about, right? >> And that was going like that at the time. >> With the cost, what we didn't want was the cost to do this, right? This is where the cloud was going to play a critical role to enable us to really keep pace with the explosion of data big data, and yet through storage and compute in the cloud, be able to do this at a fairly level cost curve, that was the objective. The third was to drive innovation, right? So we had to be able to innovate as fast as the private sector was able to innovate, to deliver new capabilities continuously all the time, and do those things. And the final reason really was about security, right? To your point, we're getting back to, the question that was originally asked was that the cloud, when we investigated the cloud, it turned out that the cloud was much more secure as a basic platform than almost anything that anybody could deliver inside their own data center across the board. And if you leverage the cloud in a particular way, security, it becomes a much more secure environment for people to operate in and do work in, then you could possibly achieve inside of your own data centers, your own data center environments. >> Gus, I'm hearing things like speed, innovation and security. I'm thinking, can you tell us a little bit about developers inside the agency? Do they have a DevOps initiative, as part of achieving those goals? >> Absolutely. So we actually got started doing Agile Development back in 2005. And what happened was, curiously enough with Agile development using scrum techniques is what we applied. We were able to build software capabilities much faster than we could actually get them hosted. So we had an impedance mismatch, a velocity mismatch, between the ability to build capabilities with Agile Development and to go. Now, when we got started in the cloud world here, DevOps was a relatively new term, but now of course DevOps just permeates everything that gets done. Accenture Federal Services, we teach DevOps for the intelligence community across the board, we teach Agile Development, we're heavily engaged. But our big move now is into DevSecOps, right? So the new impedance mismatch is the fact that I can deliver and build software very quickly. I can host it very quickly in the cloud, but my problem is that my security people who have to credit and approve the ability to run these things, are not working in sync very well with what happens in the space there. It's not that they're not great people, it's just that the methodologies that have been applied, now are causing a delay. So this is where DevSecOps comes into play and this is our big push in Accenture Federal Services. all of our clients in the cloud is to adopt DevSecOps so that we can have security tied directly into the entire development cycle all the way through, so that there are no surprises, right? We know exactly what the status is all along, and if you know anything about cyber security, in particular, both things, security on at the end is the worst possible thing you can do. And fixing cyber security holes at the end is 30 times more expensive than having just done it up front in the beginning across the board. So we are heavily invested in driving both Agile Development and DevSecOps now, in support of our cloud customers. >> Can you talk, Gus, about just as an observer, you're obviously deep into federal, but just the delta between commercial and federal? Certainly within federal you see pockets of highly advanced, whether it's security or analytics, et cetera, but across the board the Federal Government systems are obviously a lot of money is spent on maintenance, a lot of time and effort. Is Federal still learning, the public sector still learning from the commercial sector? Is it flipping? What's your take on that? >> So it's interesting. So when I retired and went out to work, from the public sector into the private sector, there's this really interesting point of view that's out there. When I was in the Federal Government, we really thought that the private sector was way ahead of us. And so we spent lot of time working with the financial service people who were brilliant, and working with Amazon and all of the people and all of the things that they were doing, because they were brilliant. So it was a really interesting engagement. But when I got to the other side, it's looked at the other way, right? They want to know what's going on because, particularly from a cyber-security optic, from a security optic, the Federal Government is viewed in many ways and particularly the intelligence community itself, is viewed as being far ahead of what goes on in the rest of the world. And in terms of analytics and things, the federal government has terrific capabilities, and has built terrific systems to do these things. So it's an interesting optic. Each one looking at the other from the outside in, is observing things and the reality is, is that like anything in life, you have this distribution. There are those that are terrific on one end of the spectrum and those that are nascent on the other end of the spectrum. This is true in the public sector, it's true in the private sector across the board. And it's just getting people together. I think the most important thing is to find a way to get us together so we share information really effectively, so that we understand what's going on, we can educate and we can all elevate ourselves up the chain, to deliver better capabilities, both for our clients and our customers, and to the citizens of our country. >> Yeah, and that public private partnership really isn't formalized. Frankly, it's companies like Accenture that are the glue there, don't you think? >> Yes, exactly. I think that that's a key point. It's companies like Accenture, companies like Amazon, who have engagements across the spectrum and on a global basis, that are able to see and experience things that most companies can't do 'cause they don't have that global perspective. One of the biggest issues we see is that most companies view the world through their narrow optic of their local sets of problems and issues, and this is what catches up with them, particularly in the cyber realm, for example. Which is they're looking at the world through the their own little narrow soda straw. And the global view of an AWS and the global view of an Accenture can be brought to bear to help us with our federal clients, for example, to see the issues more broadly and engage more effectively in a public private sector discourse. >> So there are threats everywhere, obviously. Increasingly people are talking about the weaponization of social media. Obviously, there's critical infrastructure, which we've talked about for years. Where do you see the priorities going? Where is the focus, the spending? Is it on response? Is it on keeping the bad guys out? What do you sense? >> I would say that most of the spending today is focused on trying to keep bad guys out. And that model, while critically important, has got to change, right? Because as you notice while important to do and absolutely essential, it has been wholly insufficient in actually dealing with the problem. We have to move ourselves into a completely different posture in the world today. We have to adopt very much proactive capabilities, hunt for things, do critical reviews and pen testing, discover your vulnerabilities before the adversary does. Adopt cloud services because they can change the security game. If we write cloud native code and distribute it in multiple availability zones and fully leverage elasticity and software to find networking, we can turn it into a shell game where the adversary has to find me, not the other way around. We can become what I call the polymorphic attack surface, as opposed to us having to do with polymorphic viruses, and things like that, that we have to find that are constantly trying to hide themselves from us. And so, it's adopting those things that then drive us to a state of resilience, which have to get to. Resilience is the ability to have an event and keep on operating. As opposed to what happens today, where you have an event and everything gets shut down, and all hands on deck and panic ensues. >> So, Gus, we've talked a little bit about some of the constraints and why some people might be concerned. Wondering if we could talk about some of the opportunities. What kind of innovation are you seeing from partners and customers that you're working with, that they're driving when they do adopt cloud? >> Innovation just across the board, or? >> Yeah, any cool things they're doing, there's edge technologies, you got IOT. >> I would say that the big drivers of innovation, of course, are the ones that everybody else talks about. Which is really what's happening in the machine learning and AI space. And that is really critical because those are the things that will enable us to both deal and act with issues, particularly in my realm, the cyber realm at machine speed across the board, and stop things before they can actually become problematic. But it's also going to be the mechanism by which we can enable the human population across the board to better themselves. So you take that and you combine it with the Internet of Things, which is growing explosively across the board, to begin to automate and drive efficiencies and enable remote health care and all those things like that. We're really at the cusp, I believe, of a true renaissance, if you will, of enabling society in ways that we can't possibly begin to imagine, just looking at it from where we are today. >> A lot of talk, you know, about machine intelligence. I didn't say AI, so I don't have to do a shot. Where do you see that fitting in, generally, and then maybe specifically in cyber? And the second part of that question is you're seeing this DevOps and SecOps worlds coming together? >> Yeah, right. So we talked previously about DevSecOps. Just to go back to that real quickly. That's an absolute essential. We have to get the business, the beauty of Agile Development and DevOps was it got the business and the infrastructure people who had to run things successfully all the time, and the developers who needed to do things very quickly, all at the table to engage and ensuring that they could do that. The gap in there was the security people. So with DevSecOps, you've got the security people brought in right up front across the board there. That move into DevSecOps is more than just essential, it's a must-do, I believe, for all organizations here as they move themselves into the future, and to find a way to adopt it. How did you phrase it? You didn't use the word AI, you said? >> Machine intelligence. >> Machine intelligence directive. I think that those capabilities are maturing very, very rapidly, and I think that what you're going to see is a rapid shift in two ways. One is that while machine intelligence is great, the machine is only as smart as the data and the information that are fed to it, right? If you feed a machine a bunch of information that's highly biased, you're going to get highly biased information out. So there's two things you have to have. One, the intelligence is going to grow inside the machines, but two, there's going to be and must be a parallel thread where you have to have some form of social consciousness and social awareness that ensures that the machines themselves don't develop unconscious biases that are then leveraged, and used to the disadvantage of citizens in society, or other people and things like that. And so machine intelligence is going to grow, but that same ability is emerging, and in fact it's something we talk about at Accenture and have written papers on, about the fact that we have to have this social conscience or social awareness around Artificial Intelligence, the machine learning, to ensure that it is most effectively used to the benefit of the citizens of the country. >> Right, well, in this notion of polymorphic attack surface, presumably it just can't be humans moving stuff around. >> No, that's where machinery and automation come into play, they have to act at machine speed. It's the only thing that can act at machine speed. Humans will always be involved. Okay, you're never going to get away from the human factor. What these things do is they do the heavy lifting, and then enable humans to focus on what their brains are really, really good at, which is making hard decisions about what's actually going on, and what they actually need to do in many cases. We can automate some things, but a lot of it is still going to require really smart people to engage. >> So when you look back at your original four objectives with respect to the cloud velocity, efficiencies, trying to keep the costs where they are or lower them, driving innovation and security, how would you grade, maybe the agency, the industry, whatever you feel comfortable attaching? >> Great question. I'm going to avoid giving you a specific answer like this. >> Fair enough. >> Again there's a spectrum of engagement, across the board. Some agencies are doing really well and have been leaders in the space, and I would argue that my old agency is one of those, really. There are others that are also leaders in the space and are engaging and adopting cloud services, they're pushing very heavily down these pathways we talked about. They're embracing these technologies because they realize what they can do. And then there are others that are lagging behind, but they are lagging behind for any number of several reasons that are out there. So first and foremost is the fact that there's a massive legacy set of workloads and capabilities out there, and it's very hard to figure out what are those that I want to engage in to move to the cloud and do things. So IT modernization dollars were put into play by the federal government in order to help federal agencies do this, modernize their IT with the goal of moving themselves to the cloud, so that they could drive the efficiencies and adopt the things that are going to be there. There's also the concerns we mentioned about security. There's too much fear, uncertainty and doubt, and I think misunderstanding about the cloud, and that was great. I missed the talk today from my old agency, but I'm glad to hear them talk about the fact that I've said this for the longest time, the basic cloud is much more secure than almost everything new. And if I apply and build and develop cloud native capabilities, I can actually leverage the cloud to my advantage to dramatically change the game and deliver cyber resilience into my customers set. So this is the messaging that we want to be able to do. The only way that people are going to do this in the end, because of this big backlog of capabilities, is they have to remember that they got into where their current state is one application, one system at a time. And the only way they're going to get out of it is one application, one system at a time. They just have to begin to think about what are the ones that matter and how they want to go about that. >> No quick fixes there, but a lot of hard work and thoughtfulness. Gus, thanks so much for coming to theCUBE. Really great to have you, appreciate you sharing your insight and your knowledge. >> Delighted, Dave. >> Pleasure. >> Stu, thanks so much. >> Okay, keep it right there everybody. Stu and I will be back, John Furrier is here as well with our next guest. We're live at the AWS Public Sector Summit. You're watching theCUBE. >> Thanks, guys.

>> Announcer: Live from Washington, DC it's theCUBE. Covering .conf2017. Brought to you by Splunk. >> Welcome back here on theCUBE we continue our coverage of .conf2017 here at the Splunk event with about seven thousand plus Splunkers. Along with Dave Vellante, John Walls. I like that Splunkers. >> You a Splunker? >> Not sure I'd be qualified. >> I'm learning how. >> I'm not qualified. >> to be come one. >> I don't think. >> I think we're kind of in the cheap seats of Splukism right now. Certainly there's a definitely vibe and I think that there's this whole feeling of positivity amongst our community right, that is to get a sense of that here. >> Dave: Hot company, data centers booming. >> It's all happenin', so we are in the Walter Washington Convention Center day two of the convention. We're joined now by of Stephen Hunt who is the CIO of an organization called Team Rubicon. Stephen thanks for joining us here on theCUBE. Good to have you Sir. >> Thank you for having me. >> And CTO too correct? >> And CTO. >> So first off let's talk about Team Rubicon. Veterans based organization, you team up with disaster emergency responders, first responders, to come in a crisis management times of disasters I'm sure extremely busy right now. Gave birth to this organization back in 2010 after the Haiti earthquakes. So tell us a little bit more about your mission and what you're doing now I assume you're up to your ears and all kinds of work, unfortunately. >> Yeah so our, just speaking to our mission, our purpose is to leverage the skills a military vets and first responders in disaster. The capacity and skills that vets bring after active duty in the in the services, is remarkable resource that we've learned to tap to help people in need around the world. This is one of our or this is our busiest time right now. You know we're responding in the greater Houston area in Florida, the Florida Keys, British Virgin Islands, Puerto Rico, Mexico, Turks and Caicos. And it's just it's incredible what we're able to do and in aiding people from the point of search and rescue to recovery and resilience, there's a broad spectrum of activities that are our people engage in to make that all happen and across a diversity of locations. It's been truly remarkable and challenging in ways that we never imagined right now. >> And I should add that you're a veteran yourself. Paratrooper, 82nd Airborne, a reservist, but also have an engineering background MIT Lincoln Laboratories for 20 some plus years. So you've got this interesting combination of experiences that have brought you into a company that is also a beneficiary of the Splunk for Good Program part of the Splunk pledge Program. So are you bring a pretty interesting portfolio to the job here Stephen. >> It's a bit unusual I do understand how a lot of the world works, not because I'm the smartest person in the room, I have a bit of a head start there's a lot of experience there and so bringing my engineering skills to the field, as well as to the business office and how we operate. And working with companies like Splunk, you know I can see, pretty quickly, what's hard, what's easy. I understand that Splunk needs our requirements in order to deliver product that's meaningful to us and our mission. So tying that all together it is a bit unusual for an NGO to have someone like me around. I got involved simply to help people. When they told me at some point are that we're going to build a business to help people, I said I don't come here to build a business. And it took me a little while to get oriented around the fact that as we expand the brand as we bring it around the globe, it takes a strong business model and a strong technical model in how we project humanitarian aid in austere settings. >> In order to scale right. >> So Tell us more about the organization how large is the organization, you know, where do you get the resources, how is it funded. >> So we're almost a 100% privately funded. So corporations, foundations, individual donors from across the country and across the world. We have about sixty thousand members and these are volunteers in and globally, so how in the world do you do that? Well, it turns out we grew up at about the same time the cloud industry grew up, we've been around seven years. And I would like to say that I'm some kind of genius and I said well we should follow the cloud, it was a judgment call and it was what we could manage. Today we have about thirty five to forty cloud software products that drive everything from donor management, volunteer management, how we deal with our beneficiaries, as well as our employees. And and it's not just about product in mission it's about protection and seeing through what's happening at the company at scale. We have about anywhere from eight hundred to 15 hundred people sign up to join, to become a part of Team Rubicon every week. >> Dave: Every week? >> And we couldn't do that without scale, without cloud technology it's been truly remarkable. >> And the volunteers or or all veterans, is that right? >> About 80, 75 to 80% military vets, first responders and others. >> Okay, so they just they make time to take time off from work, or whatever it is and go volunteer. They'll get permission from whom ever. Their employers, their wives and husbands. >> The payment that we provide is a renewed sense of purpose. When you know you take off the uniform there is a certain part of your identity that goes on the hanger and people don't see in you that's missing and we get that back. Through service and being around like minded individuals it's just amazing when we bring all of our people together and they align to work to this common mission. >> So in the in the take a recent examples in Florida and Houston are they predominantly people that are proximate to those areas? Are you are you having to fly people in, how does that all work? We literally have people coming in from all over the world. Generally, with the way we run operations to keep them cost effective as we look first within 450 miles of an affected area, and and bring in people in close proximity. If there is need greater than that, then we expand the scope of the distance if you will. Logistically, where we bring folks in. we're all the way now to bring in people from Australia, Norway, Canada, as well as the UK and working alongside each other seamlessly and that's really due to our standards and training. You can imagine when we scale it's not just the technology but it's how you use it, in the field, and in the business environment in the office. >> Are they responsible for figuring out where they sleep, where they eat, I mean how does that all work. >> Yeah, we set that up, in the early days we kind of took care of it ourselves, you know we reach into our own pockets and the small groups run around the planet and help people. It was kind of a club, now it's a whole different story. When we're bringing in 500 people a day, we need to know how they're fed, is this safety, security and protection, not just physically, but also emotionally. You want to make sure that we're really looking after people before, during and after they deploy and help people. So we put them up, and typically it's not the Ritz, you know might be a cot in a warehouse somewhere. But I've stayed at hotels with Team Rubicon members and maybe sometimes eight in the room. My old job Wasn't like that, all these guys are fighting to see who's going to sleep on the floor. I mean it's it's a really interesting you know. >> You have very different dynamic I'm sure. So you talk about these global operations expanding what four or five countries you mentioned with thoughts of one larger. I know communications are huge part of that you have a partnership now with a a prominent satellite firm you know in Inmarsat and how is that coming to benefit your operations and does Splunk come in the play with that global communications opportunity? >> Inmarsat and Splunk have been truly remarkable impacting and working toward greater impact in how we deliver aid around the globe. And make a couple of very clear points and deliver a metric here. We're running maybe 15 simultaneous operations distributed across all those areas I just discussed earlier. And historically, in all the time that I've been with Team Rubicon we've always had outages when it comes to communicating with our staff in these austere settings. You know we have to life safety is everything. That's the most important thing on my list, is the welfare of the people I'm looking after, and our employees, volunteers and our beneficiaries. When we can't communicate if something goes wrong it's a problem Inmarsat has set us up with communications gear in such a way that even though running all these operations at our most challenging time, I haven't had one complaint. About not being able to communicate. And what's Splunk is doing, is integrating with the Inmarsat backend to provide us the status of all of that equipment and and so from a perspective where are they all located, what is the status of the you know the data usage to make sure that somebody doesn't get arbitrarily shut off, you know that strategic view of what's happening across the globe. And this was something that we've negotiated or Inmarsat asked us to do, and Splunk is stepping up to take care of that for us so that we can ensure life safety and coordination happen seamlessly. Just one more point about this, if you could communicate with everyone everyday you're planning team isn't sitting idle wondering what it needs to do next. So this tertiary effect, is really driven our planning team to perform in a way that guides material and resources that I didn't really think about, But it's quite remarkable. >> So, you please, I thought you finished, I apologize. >> No, it's OK. >> I'm excited. >> It's fantastic. >> So the tech let's get into the tech side of this. You got SaaS apps, you got logistics, you got comms, you got analytics stuff, you got planning, you got collaboration and probably a hundred other things that I haven't mentioned. Maybe talk about you put your CTO hat on. >> Oh no, absolutely, so one of the things I say to our people, you know the technology is important but people are more important. And and so how we work with technology, its adoption as a CIO is critical. I need to say that when we're provided quality top tier software technologies to support education and training, as I mentioned, volunteer management, information management and security. And they were adopted naturally and they take off like a fire on a dry day, it means Splunk and other companies produced a great product. And we've seen this time and again with our ecosystem. So it's a general statement about the cloud technologies. Many companies have just done an exceptional job at building products that our people can work with. So I don't really complain too much about adoption across the board or struggle with it, I should say. So Google, Microsoft, Splunk, Cornerstone OnDemand, Salamander, Everbridge, Palantir. >> Be careful it's like naming the kids you're going to leave somebody out. So many of these great benefactors. >> Yeah, they're used to it but we work with all and our new COO came in, I apologize, I was CIO/CTO of Team Rubicon USA for about three years and I just moved over to Team Rubicon global to help orchestrate our global footprint. And we've set up licensing and a model for where instances of software are located to meet the legal regulatory framework for doing business internationally. And but the the COO of USA, and I'm so proud of what USA is doing right now, it's just blowing up. I mean what they're accomplishing as the largest Team Rubicon entity. But he looked at me, he said, Steve we got to get rid of some of these software products, and I said well, tell me what you don't want to do and I'll delete it, happy to. And instead the numbers gone up by 10 you know since that conversation. So there's some great challenges with and great opportunities, but as you know when your capacity increases, working with data and information your risk also goes up. So we work hard it impacting the behaviors of all of our people, it doesn't happen in a month or two months it takes years. So that everyone is security minded and making good decisions about how we work with information and data, you know whether it's a collective view provided by a product like Splunk which gives us this global view of information. You know if we have people working in a in a dangerous area and all of a sudden we know where all of our people are we just don't post that up on the open internet right. That's a bad idea just to give you a simple example. Down to the PII of our members and employees. And we're becoming very good at that. And for an NGO that's unusual and we're going to be driving an independent security audit fairly soon, to push it even further with the Board of Directors and executives, and so the business team can make decisions about how what we do technically based on you know liability in business model, right for how we work, but for me, the highest priority's protection of everyone. >> Well, it is a wonderful organization and we sincerely Dave and I both thank you for your service, present and future tense, for your service absolutely. Team Rubicon they will accept contributions, both time and treasure so visit the website Team Rubicon and see what you might be able to do to lend help to the cause, great cause that it is. Thank you Stephen. Back with more from .conf2017 here in DC, right after this.

>> Announcer: Live from San Francisco, it's theCUBE covering Spark Summit 2017, brought to you by Databricks. >> Welcome back to theCUBE, we're talking about data signs and engineering at scale, and we're having a great time, aren't we, George? >> We are! >> Well, we have another guest now we're going to talk to, I'm very pleased to introduce Matt Hunt, who's a technologist at Bloomberg, Matt, thanks for joining us! >> My pleasure. >> Alright, we're going to talk about a lot of exciting stuff here today, but I want to first start with, you're a long-time member of the Spark community, right? How many Spark Summits have you been to? >> Almost all of them, actually, it's quite amazing to see the 10th one, yes. >> And you're pretty actively involved with the user group on the east coast? >> Matt: Yeah, I run the New York users group. >> Alright, well, what's that all about? >> We have some 2,000 people in New York who are interested in finding out what goes on, and which technologies to use, and what are people working on. >> Alright, so hopefully, you saw the keynote this morning with Matei? >> Yes. >> Alright, any comments or reactions from the things that he talked about as priorities? >> Well, I've always loved the keynotes at the Spark Summits, because they announce something that you don't already know is coming in advance, at least for most people. The second Spark Summit actually had people gasping in the audience while they were demoing, a lot of senior people-- >> Well, the one millisecond today was kind of a wow one-- >> Exactly, and I would say that the one thing to pick out of the keynote that really stood out for me was the changes in improvements they've made for streaming, including potentially being able to do sub-millisecond times for some workloads. >> Well, maybe talk to us about some of the apps that you're building at Bloomberg, and then I want you to join in, George, and drill down some of the details. >> Sure. And Bloomberg is a large company with 4,000-plus developers, we've been working on apps for 30 years, so we actually have a wide range of applications, almost all of which are for news in the financial industry. We have a lot of homegrown technology that we've had to adapt over time, starting from when we built our own hardware, but there's some significant things that some of these technologies can potentially really help simplify over time. Some recent ones, I guess, trade anomaly detection would be one. How can you look for patterns of insider trading? How can you look for bad trades or attempts to spoof? There's a huge volume of trade data that comes in, that's a natural application, another one would be regulatory, there's a regulatory system called MiFID, or MiFID II, the regulations required for Europe, you have to be able to record every trade for seven years, provide daily reports, there's clearly a lot around that, and then I would also just say, our other internal databases have significant analytics that can be done, which is just kind of scraping the surface. >> These applications sound like they're oriented towards streaming solutions, and really low latency. Has that been a constraint on what you can build so far? >> I would definitely say that we have some things that are latency constrained, it tends to be not like high frequency trading, where you care about microseconds, but milliseconds are important, how long does it take to get an answer, but I would say equally important with latency is efficiency, and those two often wind up being coupled together, though not always. >> And so when you say coupled, is it because it's a trade-off, or 'cause you need both? >> Right, so it's a little bit of both, for a number of things, there's an upper threshold for the latency that we can accept. Certain architectural changes imply higher latencies, but often, greater efficiencies. Micro-batching often means that you can simplify and get greater throughput, but at a cost of higher latency. On the other hand, if you have a really large volume of things coming in, and your method of processing them isn't efficient enough, it gets too slow simply from that, and that's why it's not just one or the other. >> So in getting down to one millisecond or below, can they expose knobs where you can choose the trade-offs between efficiency and latency, and is that relevant for the apps that you're building? >> I mean, clearly if you can choose between micro-batching and not micro-batching, that's a knob that you can have, so that's one explicit one, but part of what's useful is, often when you sit down to try and determine what is the main cause of latency, you have to look at the full profile of a stack of what it's going through, and then you discover other inefficiencies that can be ironed out, and so it just makes it faster overall. I would say, a lot of what the Databricks guys in the Spark community have worked on over the years is connected to that, Project Tungsten and so on, well, all these things that make things much slower, much less efficient than they need to be, and we can close that gap a lot, I would say that from the very beginning. >> This brings up something that we were talking about earlier, which is, Matei has talked for a long time about wanting to take N 10 control of continuous apps, for simplicity and performance, and so there's this, we'll write with transactional consistency, so we're assuring the customer of exactly one's semantics when we write to a file system or database or something like that. But, Spark has never really done native storage, whereas Matei came here on the show earlier today and said, "Well, Databricks as a company "is going to have to do something in that area," and he talks specifically about databases, and he said, he implied that Apache Spark, separate from Databricks, would also have to do more in state management, I don't know if he was saying key value store, but how would that open up a broader class of apps, how would it make your life simpler as a developer? >> Right. Interesting and great question, this is kind of a subject that's near and dear to my own heart, I would say. So part of that, when you take a step back, is about some of the potential promise of what Spark could be, or what they've always wanted to be, which is a form of a universal computation engine. So there's a lot of value, if you can learn one small skillset, but it can work in a wide variety of use cases, whether it's streaming or at rest or analytics, and plug other things in. As always, there's a gap in any such system between theory and reality, and how much can you close that gap, but as for storage systems, this is something that, you and I have talked about this before, and I've written about it a fair amount too, Spark is historically an analytic system, so you have a bunch of data, and you can do analytics on it, but where's that data come from? Well, either it's streaming in, or you're reading from files, but most people need, essentially, an actual database. So what constitutes the universal system? You need file store, you need a distributive file store, you need a database with generally transactional semantics because the other forms are too hard for people to understand, you need analytics that are extensible, and you need a way to stream data in, and there's how close can you get to that, versus how much do you have to fit other parts that come together, very interesting question. >> So, so far, they've sort of outsourced that to DIY, do-it-yourself, but if they can find a sufficiently scalable relational database, they can do the sort of analytical queries, and they can sort of maintain state with transactions for some amount of the data flowing through. My impression is that, like Cassandra would be the, sort of the database that would handle all updates, and then some amount of those would be filtered through to a multi-model DBMS. When I say multi-model, I mean handles transactions and analytics. Knowing that you would have the option to drop that out, what applications would you undertake that you couldn't use right now, where the theme was, we're going to take big data apps into production, and then the competition that they show for streaming is of Kafka and Flink, so what does that do to that competitive balance? >> Right, so how many pieces do you need, and how well do they fit together is maybe the essence of that question, and people ask that all the time, and one of the limits has been, how mature is each piece, how efficient is it, and do they work together? And if you have to master 5,000 skills and 200 different products, that's a huge impediment to real-world usage. I think we're coalescing around a smaller set of options, so in the, Kafka, for example, has a lot of usage, and it seems to really be, the industry seems to be settling on that is what people are using for inbound streaming data, for ingest, I see that everywhere I go. But what happens when you move from Kafka into Spark, or Spark has to read from a database? This is partly a question of maturity. Relational databases are very hard to get right. The ones that we have have been under development for decades, right? I mean, DB2 has been around for a really long time with very, very smart people working on it, or Oracle, or lots of other databases. So at Bloomberg, we actually developed our own databases for relational databases that were designed for low latency and very high reliability, so we actually just opensourced that a few weeks ago, it's called ComDB2, and the reason we had to do that was the industry solutions at the time, when we started working on that, were inadequate to our needs, but we look at how long that took to develop for these other systems and think, that's really hard for someone else to get right, and so, if you need a database, which everyone does, how can you make that work better with Spark? And I think there're a number of very interesting developments that can make that a lot better, short of Spark becoming and integrating a database directly, although there's interesting possibilities with that too. How do you make them work well together, we could talk about for a while, 'cause that's a fascinating question. >> On that one topic, maybe the Databricks guys don't want to assume responsibility for the development, because then they're picking a winner, perhaps? Maybe, as Matei told us earlier, they can make the APIs easier to use for a database vendor to integrate, but like we've seen Splice Machine and SnappyData do the work, take it upon themselves to take data frames, the core data structure, in Spark, and give it transactional semantics. Does that sound promising? >> There're multiple avenues for potential success, and who can use which, in a way, depends on the audience. If you look at things like Cassandra and HBase, they're distributing key value stores that additional things are being built on, so they started as distributed, and they're moving towards more encompassing systems, versus relational databases, which generally started as single image on single machine, and are moving towards federation distribution, and there's been a lot with that with post grads, for example. One of the questions would be, is it just knobs, or why don't they work well together? And there're a number of reasons. One is, what can be pushed down, how much knowledge do you have to have to make that decision, and optimizing that, I think, is actually one of the really interesting things that could be done, just as we have database query optimizers, why not, can you determine the best way to execute down a chain? In order to do that well, there are two things that you need that haven't yet been widely adopted, but are coming. One is the very efficient copy of data between systems, and Apache Arrow, for example, is very, very interesting, and it's nearing the time when I think it's just going to explode, because it lets you connect these systems radically more efficiently in a standardized way, and that's one of the things that was missing, as soon as you hop from one system to another, all of a sudden, you have the semantic computational expense, that's a problem, we can fix that. The other is, the next level of integration requires, basically, exposing more hooks. In order to know, where should a query be executed and which operator should I push down, you need something that I think of as a meta-optimizer, and also, knowledge about the shape of the data, or statistics underlying, and ways to exchange that back and forth to be able to do it well. >> Wow, Matt, a lot of great questions there. We're coming up on a break, so we have to wrap things up, and I wanted to give you at least 30 seconds to maybe sum up what you'd like to see your user community, the Spark community, do over the next year. What are the top issues, things you'd love to see worked on? >> Right. It's an exciting time for Spark, because as time goes by, it gets more and more mature, and more real-world applications are viable. The hardest thing of all is to get, anywhere you in any organization's to get people working together, but the more people work together to enable these pieces, how do I efficiently work with databases, or have these better optimizations make streaming more mature, the more people can use it in practice, and that's why people develop software, is to actually tackle these real-world problems, so, I would love to see more of that. >> Can we all get along? (chuckling) Well, that's going to be the last word of this segue, Matt, thank you so much for coming on and spending some time with us here to share the story! >> My pleasure. >> Alright, thank you so much. Thank you George, and thank you all for watching this segment of theCUBE, please stay with us, as Spark Summit 2017 will be back in a few moments.

(gentle music) >> Hello everyone. Welcome to this CUBE conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE. We got a great remote guest coming in. Joseph Nelson, co-founder and CEO of RoboFlow hot startup in AI, computer vision. Really interesting topic in this wave of AI next gen hitting. Joseph, thanks for coming on this CUBE conversation. >> Thanks for having me. >> Yeah, I love the startup tsunami that's happening here in this wave. RoboFlow, you're in the middle of it. Exciting opportunities, you guys are in the cutting edge. I think computer vision's been talked about more as just as much as the large language models and these foundational models are merging. You're in the middle of it. What's it like right now as a startup and growing in this new wave hitting? >> It's kind of funny, it's, you know, I kind of describe it like sometimes you're in a garden of gnomes. It's like we feel like we've got this giant headstart with hundreds of thousands of people building with computer vision, training their own models, but that's a fraction of what it's going to be in six months, 12 months, 24 months. So, as you described it, a wave is a good way to think about it. And the wave is still building before it gets to its full size. So it's a ton of fun. >> Yeah, I think it's one of the most exciting areas in computer science. I wish I was in my twenties again, because I would be all over this. It's the intersection, there's so many disciplines, right? It's not just tech computer science, it's computer science, it's systems, it's software, it's data. There's so much aperture of things going on around your world. So, I mean, you got to be batting all the students away kind of trying to get hired in there, probably. I can only imagine you're hiring regiment. I'll ask that later, but first talk about what the company is that you're doing. How it's positioned, what's the market you're going after, and what's the origination story? How did you guys get here? How did you just say, hey, want to do this? What was the origination story? What do you do and how did you start the company? >> Yeah, yeah. I'll give you the what we do today and then I'll shift into the origin. RoboFlow builds tools for making the world programmable. Like anything that you see should be read write access if you think about it with a programmer's mind or legible. And computer vision is a technology that enables software to be added to these real world objects that we see. And so any sort of interface, any sort of object, any sort of scene, we can interact with it, we can make it more efficient, we can make it more entertaining by adding the ability for the tools that we use and the software that we write to understand those objects. And at RoboFlow, we've empowered a little over a hundred thousand developers, including those in half the Fortune 100 so far in that mission. Whether that's Walmart understanding the retail in their stores, Cardinal Health understanding the ways that they're helping their patients, or even electric vehicle manufacturers ensuring that they're making the right stuff at the right time. As you mentioned, it's early. Like I think maybe computer vision has touched one, maybe 2% of the whole economy and it'll be like everything in a very short period of time. And so we're focused on enabling that transformation. I think it's it, as far as I think about it, I've been fortunate to start companies before, start, sell these sorts of things. This is the last company I ever wanted to start and I think it will be, should we do it right, the world's largest in riding the wave of bringing together the disparate pieces of that technology. >> What was the motivating point of the formation? Was it, you know, you guys were hanging around? Was there some catalyst? What was the moment where it all kind of came together for you? >> You know what's funny is my co-founder, Brad and I, we were making computer vision apps for making board games more fun to play. So in 2017, Apple released AR kit, augmented reality kit for building augmented reality applications. And Brad and I are both sort of like hacker persona types. We feel like we don't really understand the technology until we build something with it and so we decided that we should make an app that if you point your phone at a Sudoku puzzle, it understands the state of the board and then it kind of magically fills in that experience with all the digits in real time, which totally ruins the game of Sudoku to be clear. But it also just creates this like aha moment of like, oh wow, like the ability for our pocket devices to understand and see the world as good or better than we can is possible. And so, you know, we actually did that as I mentioned in 2017, and the app went viral. It was, you know, top of some subreddits, top of Injure, Reddit, the hacker community as well as Product Hunt really liked it. So it actually won Product Hunt AR app of the year, which was the same year that the Tesla model three won the product of the year. So we joked that we share an award with Elon our shared (indistinct) But frankly, so that was 2017. RoboFlow wasn't incorporated as a business until 2019. And so, you know, when we made Magic Sudoku, I was running a different company at the time, Brad was running a different company at the time, and we kind of just put it out there and were excited by how many people liked it. And we assumed that other curious developers would see this inevitable future of, oh wow, you know. This is much more than just a pedestrian point your phone at a board game. This is everything can be seen and understood and rewritten in a different way. Things like, you know, maybe your fridge. Knowing what ingredients you have and suggesting recipes or auto ordering for you, or we were talking about some retail use cases of automated checkout. Like anything can be seen and observed and we presume that that would kick off a Cambrian explosion of applications. It didn't. So you fast forward to 2019, we said, well we might as well be the guys to start to tackle this sort of problem. And because of our success with board games before, we returned to making more board game solving applications. So we made one that solves Boggle, you know, the four by four word game, we made one that solves chess, you point your phone at a chess board and it understands the state of the board and then can make move recommendations. And each additional board game that we added, we realized that the tooling was really immature. The process of collecting images, knowing which images are actually going to be useful for improving model performance, training those models, deploying those models. And if we really wanted to make the world programmable, developers waiting for us to make an app for their thing of interest is a lot less efficient, less impactful than taking our tool chain and releasing that externally. And so, that's what RoboFlow became. RoboFlow became the internal tools that we used to make these game changing applications readily available. And as you know, when you give developers new tools, they create new billion dollar industries, let alone all sorts of fun hobbyist projects along the way. >> I love that story. Curious, inventive, little radical. Let's break the rules, see how we can push the envelope on the board games. That's how companies get started. It's a great story. I got to ask you, okay, what happens next? Now, okay, you realize this new tooling, but this is like how companies get built. Like they solve their own problem that they had 'cause they realized there's one, but then there has to be a market for it. So you actually guys knew that this was coming around the corner. So okay, you got your hacker mentality, you did that thing, you got the award and now you're like, okay, wow. Were you guys conscious of the wave coming? Was it one of those things where you said, look, if we do this, we solve our own problem, this will be big for everybody. Did you have that moment? Was that in 2019 or was that more of like, it kind of was obvious to you guys? >> Absolutely. I mean Brad puts this pretty effectively where he describes how we lived through the initial internet revolution, but we were kind of too young to really recognize and comprehend what was happening at the time. And then mobile happened and we were working on different companies that were not in the mobile space. And computer vision feels like the wave that we've caught. Like, this is a technology and capability that rewrites how we interact with the world, how everyone will interact with the world. And so we feel we've been kind of lucky this time, right place, right time of every enterprise will have the ability to improve their operations with computer vision. And so we've been very cognizant of the fact that computer vision is one of those groundbreaking technologies that every company will have as a part of their products and services and offerings, and we can provide the tooling to accelerate that future. >> Yeah, and the developer angle, by the way, I love that because I think, you know, as we've been saying in theCUBE all the time, developer's the new defacto standard bodies because what they adopt is pure, you know, meritocracy. And they pick the best. If it's sell service and it's good and it's got open source community around it, its all in. And they'll vote. They'll vote with their code and that is clear. Now I got to ask you, as you look at the market, we were just having this conversation on theCUBE in Barcelona at recent Mobile World Congress, now called MWC, around 5G versus wifi. And the debate was specifically computer vision, like facial recognition. We were talking about how the Cleveland Browns were using facial recognition for people coming into the stadium they were using it for ships in international ports. So the question was 5G versus wifi. My question is what infrastructure or what are the areas that need to be in place to make computer vision work? If you have developers building apps, apps got to run on stuff. So how do you sort that out in your mind? What's your reaction to that? >> A lot of the times when we see applications that need to run in real time and on video, they'll actually run at the edge without internet. And so a lot of our users will actually take their models and run it in a fully offline environment. Now to act on that information, you'll often need to have internet signal at some point 'cause you'll need to know how many people were in the stadium or what shipping crates are in my port at this point in time. You'll need to relay that information somewhere else, which will require connectivity. But actually using the model and creating the insights at the edge does not require internet. I mean we have users that deploy models on underwater submarines just as much as in outer space actually. And those are not very friendly environments to internet, let alone 5g. And so what you do is you use an edge device, like an Nvidia Jetson is common, mobile devices are common. Intel has some strong edge devices, the Movidius family of chips for example. And you use that compute that runs completely offline in real time to process those signals. Now again, what you do with those signals may require connectivity and that becomes a question of the problem you're solving of how soon you need to relay that information to another place. >> So, that's an architectural issue on the infrastructure. If you're a tactical edge war fighter for instance, you might want to have highly available and maybe high availability. I mean, these are words that mean something. You got storage, but it's not at the edge in real time. But you can trickle it back and pull it down. That's management. So that's more of a business by business decision or environment, right? >> That's right, that's right. Yeah. So I mean we can talk through some specifics. So for example, the RoboFlow actually powers the broadcaster that does the tennis ball tracking at Wimbledon. That runs completely at the edge in real time in, you know, technically to track the tennis ball and point the camera, you actually don't need internet. Now they do have internet of course to do the broadcasting and relay the signal and feeds and these sorts of things. And so that's a case where you have both edge deployment of running the model and high availability act on that model. We have other instances where customers will run their models on drones and the drone will go and do a flight and it'll say, you know, this many residential homes are in this given area, or this many cargo containers are in this given shipping yard. Or maybe we saw these environmental considerations of soil erosion along this riverbank. The model in that case can run on the drone during flight without internet, but then you only need internet once the drone lands and you're going to act on that information because for example, if you're doing like a study of soil erosion, you don't need to be real time. You just need to be able to process and make use of that information once the drone finishes its flight. >> Well I can imagine a zillion use cases. I heard of a use case interview at a company that does computer vision to help people see if anyone's jumping the fence on their company. Like, they know what a body looks like climbing a fence and they can spot it. Pretty easy use case compared to probably some of the other things, but this is the horizontal use cases, its so many use cases. So how do you guys talk to the marketplace when you say, hey, we have generative AI for commuter vision. You might know language models that's completely different animal because vision's like the world, right? So you got a lot more to do. What's the difference? How do you explain that to customers? What can I build and what's their reaction? >> Because we're such a developer centric company, developers are usually creative and show you the ways that they want to take advantage of new technologies. I mean, we've had people use things for identifying conveyor belt debris, doing gas leak detection, measuring the size of fish, airplane maintenance. We even had someone that like a hobby use case where they did like a specific sushi identifier. I dunno if you know this, but there's a specific type of whitefish that if you grew up in the western hemisphere and you eat it in the eastern hemisphere, you get very sick. And so there was someone that made an app that tells you if you happen to have that fish in the sushi that you're eating. But security camera analysis, transportation flows, plant disease detection, really, you know, smarter cities. We have people that are doing curb management identifying, and a lot of these use cases, the fantastic thing about building tools for developers is they're a creative bunch and they have these ideas that if you and I sat down for 15 minutes and said, let's guess every way computer vision can be used, we would need weeks to list all the example use cases. >> We'd miss everything. >> And we'd miss. And so having the community show us the ways that they're using computer vision is impactful. Now that said, there are of course commercial industries that have discovered the value and been able to be out of the gate. And that's where we have the Fortune 100 customers, like we do. Like the retail customers in the Walmart sector, healthcare providers like Medtronic, or vehicle manufacturers like Rivian who all have very difficult either supply chain, quality assurance, in stock, out of stock, anti-theft protection considerations that require successfully making sense of the real world. >> Let me ask you a question. This is maybe a little bit in the weeds, but it's more developer focused. What are some of the developer profiles that you're seeing right now in terms of low-hanging fruit applications? And can you talk about the academic impact? Because I imagine if I was in school right now, I'd be all over it. Are you seeing Master's thesis' being worked on with some of your stuff? Is the uptake in both areas of younger pre-graduates? And then inside the workforce, What are some of the devs like? Can you share just either what their makeup is, what they work on, give a little insight into the devs you're working with. >> Leading developers that want to be on state-of-the-art technology build with RoboFlow because they know they can use the best in class open source. They know that they can get the most out of their data. They know that they can deploy extremely quickly. That's true among students as you mentioned, just as much as as industries. So we welcome students and I mean, we have research grants that will regularly support for people to publish. I mean we actually have a channel inside our internal slack where every day, more student publications that cite building with RoboFlow pop up. And so, that helps inspire some of the use cases. Now what's interesting is that the use case is relatively, you know, useful or applicable for the business or the student. In other words, if a student does a thesis on how to do, we'll say like shingle damage detection from satellite imagery and they're just doing that as a master's thesis, in fact most insurance businesses would be interested in that sort of application. So, that's kind of how we see uptick and adoption both among researchers who want to be on the cutting edge and publish, both with RoboFlow and making use of open source tools in tandem with the tool that we provide, just as much as industry. And you know, I'm a big believer in the philosophy that kind of like what the hackers are doing nights and weekends, the Fortune 500 are doing in a pretty short order period of time and we're experiencing that transition. Computer vision used to be, you know, kind of like a PhD, multi-year investment endeavor. And now with some of the tooling that we're working on in open source technologies and the compute that's available, these science fiction ideas are possible in an afternoon. And so you have this idea of maybe doing asset management or the aerial observation of your shingles or things like this. You have a few hundred images and you can de-risk whether that's possible for your business today. So there's pretty broad-based adoption among both researchers that want to be on the state of the art, as much as companies that want to reduce the time to value. >> You know, Joseph, you guys and your partner have got a great front row seat, ground floor, presented creation wave here. I'm seeing a pattern emerging from all my conversations on theCUBE with founders that are successful, like yourselves, that there's two kind of real things going on. You got the enterprises grabbing the products and retrofitting into their legacy and rebuilding their business. And then you have startups coming out of the woodwork. Young, seeing greenfield or pick a specific niche or focus and making that the signature lever to move the market. >> That's right. >> So can you share your thoughts on the startup scene, other founders out there and talk about that? And then I have a couple questions for like the enterprises, the old school, the existing legacy. Little slower, but the startups are moving fast. What are some of the things you're seeing as startups are emerging in this field? >> I think you make a great point that independent of RoboFlow, very successful, especially developer focused businesses, kind of have three customer types. You have the startups and maybe like series A, series B startups that you're building a product as fast as you can to keep up with them, and they're really moving just as fast as as you are and pulling the product out at you for things that they need. The second segment that you have might be, call it SMB but not enterprise, who are able to purchase and aren't, you know, as fast of moving, but are stable and getting value and able to get to production. And then the third type is enterprise, and that's where you have typically larger contract value sizes, slower moving in terms of adoption and feedback for your product. And I think what you see is that successful companies balance having those three customer personas because you have the small startups, small fast moving upstarts that are discerning buyers who know the market and elect to build on tooling that is best in class. And so you basically kind of pass the smell test of companies who are quite discerning in their purchases, plus are moving so quick they're pulling their product out of you. Concurrently, you have a product that's enterprise ready to service the scalability, availability, and trust of enterprise buyers. And that's ultimately where a lot of companies will see tremendous commercial success. I mean I remember seeing the Twilio IPO, Uber being like a full 20% of their revenue, right? And so there's this very common pattern where you have the ability to find some of those upstarts that you make bets on, like the next Ubers of the world, the smaller companies that continue to get developed with the product and then the enterprise whom allows you to really fund the commercial success of the business, and validate the size of the opportunity in market that's being creative. >> It's interesting, there's so many things happening there. It's like, in a way it's a new category, but it's not a new category. It becomes a new category because of the capabilities, right? So, it's really interesting, 'cause that's what you're talking about is a category, creating. >> I think developer tools. So people often talk about B to B and B to C businesses. I think developer tools are in some ways a third way. I mean ultimately they're B to B, you're selling to other businesses and that's where your revenue's coming from. However, you look kind of like a B to C company in the ways that you measure product adoption and kind of go to market. In other words, you know, we're often tracking the leading indicators of commercial success in the form of usage, adoption, retention. Really consumer app, traditionally based metrics of how to know you're building the right stuff, and that's what product led growth companies do. And then you ultimately have commercial traction in a B to B way. And I think that that actually kind of looks like a third thing, right? Like you can do these sort of funny zany marketing examples that you might see historically from consumer businesses, but yet you ultimately make your money from the enterprise who has these de-risked high value problems you can solve for them. And I selfishly think that that's the best of both worlds because I don't have to be like Evan Spiegel, guessing the next consumer trend or maybe creating the next consumer trend and catching lightning in a bottle over and over again on the consumer side. But I still get to have fun in our marketing and make sort of fun, like we're launching the world's largest game of rock paper scissors being played with computer vision, right? Like that's sort of like a fun thing you can do, but then you can concurrently have the commercial validation and customers telling you the things that they need to be built for them next to solve commercial pain points for them. So I really do think that you're right by calling this a new category and it really is the best of both worlds. >> It's a great call out, it's a great call out. In fact, I always juggle with the VC. I'm like, it's so easy. Your job is so easy to pick the winners. What are you talking about its so easy? I go, just watch what the developers jump on. And it's not about who started, it could be someone in the dorm room to the boardroom person. You don't know because that B to C, the C, it's B to D you know? You know it's developer 'cause that's a human right? That's a consumer of the tool which influences the business that never was there before. So I think this direct business model evolution, whether it's media going direct or going direct to the developers rather than going to a gatekeeper, this is the reality. >> That's right. >> Well I got to ask you while we got some time left to describe, I want to get into this topic of multi-modality, okay? And can you describe what that means in computer vision? And what's the state of the growth of that portion of this piece? >> Multi modality refers to using multiple traditionally siloed problem types, meaning text, image, video, audio. So you could treat an audio problem as only processing audio signal. That is not multimodal, but you could use the audio signal at the same time as a video feed. Now you're talking about multi modality. In computer vision, multi modality is predominantly happening with images and text. And one of the biggest releases in this space is actually two years old now, was clip, contrastive language image pre-training, which took 400 million image text pairs and basically instead of previously when you do classification, you basically map every single image to a single class, right? Like here's a bunch of images of chairs, here's a bunch of images of dogs. What clip did is used, you can think about it like, the class for an image being the Instagram caption for the image. So it's not one single thing. And by training on understanding the corpora, you basically see which words, which concepts are associated with which pixels. And this opens up the aperture for the types of problems and generalizability of models. So what does this mean? This means that you can get to value more quickly from an existing trained model, or at least validate that what you want to tackle with a computer vision, you can get there more quickly. It also opens up the, I mean. Clip has been the bedrock of some of the generative image techniques that have come to bear, just as much as some of the LLMs. And increasingly we're going to see more and more of multi modality being a theme simply because at its core, you're including more context into what you're trying to understand about the world. I mean, in its most basic sense, you could ask yourself, if I have an image, can I know more about that image with just the pixels? Or if I have the image and the sound of when that image was captured or it had someone describe what they see in that image when the image was captured, which one's going to be able to get you more signal? And so multi modality helps expand the ability for us to understand signal processing. >> Awesome. And can you just real quick, define clip for the folks that don't know what that means? >> Yeah. Clip is a model architecture, it's an acronym for contrastive language image pre-training and like, you know, model architectures that have come before it captures the almost like, models are kind of like brands. So I guess it's a brand of a model where you've done these 400 million image text pairs to match up which visual concepts are associated with which text concepts. And there have been new releases of clip, just at bigger sizes of bigger encoding's, of longer strings of texture, or larger image windows. But it's been a really exciting advancement that OpenAI released in January, 2021. >> All right, well great stuff. We got a couple minutes left. Just I want to get into more of a company-specific question around culture. All startups have, you know, some sort of cultural vibe. You know, Intel has Moore's law doubles every whatever, six months. What's your culture like at RoboFlow? I mean, if you had to describe that culture, obviously love the hacking story, you and your partner with the games going number one on Product Hunt next to Elon and Tesla and then hey, we should start a company two years later. That's kind of like a curious, inventing, building, hard charging, but laid back. That's my take. How would you describe the culture? >> I think that you're right. The culture that we have is one of shipping, making things. So every week each team shares what they did for our customers on a weekly basis. And we have such a strong emphasis on being better week over week that those sorts of things compound. So one big emphasis in our culture is getting things done, shipping, doing things for our customers. The second is we're an incredibly transparent place to work. For example, how we think about giving decisions, where we're progressing against our goals, what problems are biggest and most important for the company is all open information for those that are inside the company to know and progress against. The third thing that I'd use to describe our culture is one that thrives with autonomy. So RoboFlow has a number of individuals who have founded companies before, some of which have sold their businesses for a hundred million plus upon exit. And the way that we've been able to attract talent like that is because the problems that we're tackling are so immense, yet individuals are able to charge at it with the way that they think is best. And this is what pairs well with transparency. If you have a strong sense of what the company's goals are, how we're progressing against it, and you have this ownership mentality of what can I do to change or drive progress against that given outcome, then you create a really healthy pairing of, okay cool, here's where the company's progressing. Here's where things are going really well, here's the places that we most need to improve and work on. And if you're inside that company as someone who has a preponderance to be a self-starter and even a history of building entire functions or companies yourself, then you're going to be a place where you can really thrive. You have the inputs of the things where we need to work on to progress the company's goals. And you have the background of someone that is just necessarily a fast moving and ambitious type of individual. So I think the best way to describe it is a transparent place with autonomy and an emphasis on getting things done. >> Getting shit done as they say. Getting stuff done. Great stuff. Hey, final question. Put a plug out there for the company. What are you going to hire? What's your pipeline look like for people? What jobs are open? I'm sure you got hiring all around. Give a quick plug for the company what you're looking for. >> I appreciate you asking. Basically you're either building the product or helping customers be successful with the product. So in the building product category, we have platform engineering roles, machine learning engineering roles, and we're solving some of the hardest and most impactful problems of bringing such a groundbreaking technology to the masses. And so it's a great place to be where you can kind of be your own user as an engineer. And then if you're enabling people to be successful with the products, I mean you're working in a place where there's already such a strong community around it and you can help shape, foster, cultivate, activate, and drive commercial success in that community. So those are roles that tend themselves to being those that build the product for developer advocacy, those that are account executives that are enabling our customers to realize commercial success, and even hybrid roles like we call it field engineering, where you are a technical resource to drive success within customer accounts. And so all this is listed on roboflow.com/careers. And one thing that I actually kind of want to mention John that's kind of novel about the thing that's working at RoboFlow. So there's been a lot of discussion around remote companies and there's been a lot of discussion around in-person companies and do you need to be in the office? And one thing that we've kind of recognized is you can actually chart a third way. You can create a third way which we call satellite, which basically means people can work from where they most like to work and there's clusters of people, regular onsite's. And at RoboFlow everyone gets, for example, $2,500 a year that they can use to spend on visiting coworkers. And so what's sort of organically happened is team numbers have started to pull together these resources and rent out like, lavish Airbnbs for like a week and then everyone kind of like descends in and works together for a week and makes and creates things. And we call this lighthouses because you know, a lighthouse kind of brings ships into harbor and we have an emphasis on shipping. >> Yeah, quality people that are creative and doers and builders. You give 'em some cash and let the self-governing begin, you know? And like, creativity goes through the roof. It's a great story. I think that sums up the culture right there, Joseph. Thanks for sharing that and thanks for this great conversation. I really appreciate it and it's very inspiring. Thanks for coming on. >> Yeah, thanks for having me, John. >> Joseph Nelson, co-founder and CEO of RoboFlow. Hot company, great culture in the right place in a hot area, computer vision. This is going to explode in value. The edge is exploding. More use cases, more development, and developers are driving the change. Check out RoboFlow. This is theCUBE. I'm John Furrier, your host. Thanks for watching. (gentle music)

>>Good afternoon everybody. I'm John Walls and welcome back to our coverage here on the cube of AWS Reinvent 22. We are bringing you another segment with the Global Startup Program, which is part of the AWS Start Showcase, and it's a pleasure to welcome two new guests here to the showcase. First, immediately to my right Han w lre. Good to see you Han. Good to see you. The leader of the Enterprise Solutions Architecture at aws. And on the far right, Rolin Lee, who is the co-founder and CEO of Heim Doll Data. Roland, good to see you. Great >>To be here. >>All right, good. Thanks for joining us. Well first off, for those at home, I may not be familiar with Heim Doll. What do you do? Why are you here? But I'll let you take it from there. >>Well, we're one of the sponsors here at AWS and great to be here. We offer a data access layer in the form of a proxy, and what it does is it provides complete visibility and the capability to enhance the interaction between the application and one's current database. And as a result, you'll, the customer will improve database scale, database security and availability. And all these features don't require any application changes. So that's sort of our marketing pitch, if you will, all these types of features to improve the experience of managing a database without any application >>Changes. And, and where's the cloud come into play then, for you then, where, where did it come into play for you? >>So we started out actually helping out customers on premise, and a lot of enterprise customers are moving over to the cloud, and it was just a natural progression to do that. And so aws, which is a key part of ours, partners with us to help solve customer problems, especially on the database side, as the application being application performance tends to have issues between the interaction between the application database and we're solving that issue. >>Right. Sohan, I mean, Roan just touched on it about OnPrem, right? There's still some kickers and screamers out there that, that don't, haven't bought in or, or they're about to, but you're about to get 'em. I, I'm sure. But talk about that, that conversion or that transition, if you would, from going OnPrem into a hybrid environment or to into the, the bigger cloud environment and and how difficult that is sometimes. Yes. Maybe to get people to, to make that kind of a leap. >>Well, I would say that a lot of customers are wanting to focus more on product innovation experimentation, and also in terms of having to manage servers and patching, you know, it's to take away from that initiative that they're trying to do. So with aws, we provide undifferentiated heavy lifting so that they can focus on product innovation. And one of the areas talking about Heim is that from the database side, we do provide Amazon rds, which is database and also Aurora, to give them that lift so they don't have to worry about patching servers and setting up provisioning servers as well. >>Right. So Roland, can you get the idea across to people very simply, let us take care of the, the hard stuff and, and that will free you up to do your product innovations, to do your experimentations to, to really free up your team, basically to do the fun stuff and, and let us sweat over the, the, the details basically. Right? >>Exactly. Our, our motto is not only why build when, when you can buy. So a lot of it has to do with offering the, the value in terms of price and the features such as it's gonna benefit a team. Large companies like amazon.com, Google, they have huge teams that can build data access layers and proxies. And what we're trying to do here is commercialize those cuz those are built in house and it's not readily available for customers to use. And you'd need some type of interface between the application and the database. And we provide that sort of why build when you can buy. >>Well, I was gonna say why h right? I mean what's your special sauce? Because everybody's got something, obviously a market differentiator that you're bringing into place here. So you started to touch on a little bit there for me, but, but dive a little deeper there. I mean, what, what is it that, that you're bringing to the table with AWS that you think puts you above the crowd? >>Well, lemme give you a use case here. In typical events like let's say Black Friday where there's a surge traffic that can overwhelm the database, the Heim doll data access layer database proxy provides an auto scaling distributed architecture such that it can absorb those surges and traffic and help scale the database while keeping the data fresh and up to date. And so basically traffic based on season time of day, we can, we can adjust automatically and all these types of features that we offer, most notably automated query caching, ReadWrite split for asset compliance don't require any code changes, which typically requires the application developer to make those changes. So we're saving months, maybe years of development and maintenance. >>Yeah, a lot of gray hairs too, right? Yeah, you're, you're solving a lot of problems there. What about database trends in just in general Hunt, if you will. I mean, this is your space, right? I mean, what we're hearing about from Heindel, you know, in terms of solutions they're providing, but what are you seeing just from the macro level in terms of what people are doing and thinking about the database and how it relates to the cloud? Right. >>And some of the things that we're seeing is that we're seeing an explosion of data, relevant data that customers need to be able to consume and also process as well. So with the explosion of data, there's also, we see customers trying to modernize their application as well through microservices, which does change the design patterns of like the applications we call the access data patterns as well. So again, going back to that, a differentiated heavy lifting, we do have something called purpose built databases, right? It's the right tool for the right purpose. And so it depends on what their like rpo, rto their access to data pattern. Is it a base, is it an acid? So we want to be able to provide them the options to build and also innovate. So with that, that's why we have the Amazon rds, the also the, we also have Redshift, we also have Aurora and et cetera. The Rediff is more of the BI side, but usually when you ingest the data, you have some level of processing to get more insight. So with that, that's why customers are moving more of towards the managed service so that they can give that lift and then focusing on that product and innovation. Yeah. >>Have we kind of caught up or are we catching up to this just the tsunami of data to begin with, right? Because I mean, that was it, you know, what, seven, eight years ago when, when that data became kind of, or becoming king and, and reams and reams and reams and all, you know, can't handle it, right? And, and are we now able to manage that process and manage that flow and get the right data into the right hands at the right time? We're doing better with that. >>I would say that it, it definitely has grown in size of the amount of data that we're ingesting. And so with the scalability and agility of the cloud, we're able to, I would say, adapt to the rapid changes and ingestions of the data. So, so that's why we have things like Aurora servers to have that or auto scale so they can do like MySQL or Postgres and then they can still, like what you know, I'm trying to do is basically don't have to co do like any code changes. It would be a data migration. They still use the same underlying database on also mechanisms, but here we're providing them at scale on the cloud. >>Yeah. Our proxies, they must have for all databases. I mean, is that, is that essential these days? >>Well, good question John. I would say yes. And this is often built in house, as I mentioned, for large companies, they do build some type of data access layer or proxy and, or some utilize some orm, some object relational map to do it. And what again, what we're trying to do is offer this, put this out into the market commercially speaking, such that it can be readily used for, for all the customers to use rather than building it from scratch all the time. >>You know what I didn't ask you was Roy, how does AWS come into play for you then? And, and as in the startup mode, the focus that they've had in startups in general, but in you in particular, I mean, talk about that partnership or that relationship and the value that you're extracting from that. >>The ad AWS partnership has been absolutely wonderful. The collaboration, they have one of the best managed service databases. The value that it that adds in terms of the durability, the manageability, what the Heim doll data does is it compliments Amazon rds, Amazon Redshift very well in the sense that we're not replacing the database. What we're doing is we are allowing the customer to get the most out of the managed service database, whether it be Redshift or Aurora Serverless, rds, all without code changes. And or the analogy that I would give John is a car, a race car may be very fast, but it takes a driver to get to those fast speeds. We're the driver, the Hyundai proxy provides that intelligence so that you can get the most out of that database engine. >>And, and Hfi would then touch on, first off AWS and the emphasis that you have put on startups and are obviously, you know, kind of putting your money where your mouth is, right? With, with the way you've encouraged and nurtured that environment. And they would be about Heim doll in general about where you see this going or what you would like to have, where you want to take this in the next say 12 months, 18 months. >>I think it's more of a better together story of how we can basically coil with our partners, right? And, and basically focusing on helping our customers drive that innovation and be collaboration. So as Heim, as a independent service vendor isv, most customers can leverage that through a marketplace where basically it integrates very nicely with aws. So that gives 'em that lift and it goes back to the undifferentiated heavy lifting on the Hein proxy side, if you will, because then you have this proxy in the middle where then it helps them with their SQL performance. And I've seen use cases where customers were, have some legacy system that they may not have time to modernize the application. So they use this as a lift to keep, keep going as they try to modernize. But also I've seen customers who use are trying to use it as a, a way to give that performance lift because they may have a third party software that they cannot change the code by putting this in there that helps optimize their lines of business or whatever that is, and maybe can be online store or whatever. So I would say it was a better together type of story. >>Yeah. Which is, there's gotta be a song in there somewhere. So peek around the corner and if you wanna be headlights here right now in terms of 12, 18 months, I mean, what, you know, what what next to solve, right? You've already taken, you've slayed a few dragons along the way, but there are others I'm sure is it always happens in innovation in this space. Just when you solve a problem you've just dealt or you have to deal with others that pop up as maybe unintended consequences or at least a new challenge. So what would that be in your world right now? What, what do you see, you know, occupying your sleepless nights here for the next year or so? >>Well, for, for HOMEDALE data, it's all about improving database performance and scale. And those workloads change. We have O ltp, we have OLA with artificial intelligence ml. There's different type of traffic profiles and we're focused on improving those data profiles. It could be unstructured structured. Right now we're focused on structured data, which is relational databases, but there's a lot of opportunity to improve the performance of data. >>Well, you're driving the car, you got a good navigator. I think the GPS is working. So keep up the good work and thank you for sharing the time today. Thank you. Thank you, joy. Do appreciate it. All right, you are watching the cube. We continue our coverage here from AWS Reinvent 22, the Cube, of course, the leader in high tech coverage.

>>the Cube presents H P E discovered 2022. Brought to you by H P E. >>Hi, buddy Dave Balon and Jon Ferrier Wrapping up the cubes. Coverage of day two, hp Discover 2022. We're live from Las Vegas. Vishal Lall is here. He's the senior vice president and general manager for HP ES Green Lake Cloud Services Solutions. Michelle, good to see you again. >>Likewise. David, good to see you. It was about a year ago that we met here. Or maybe nine months >>ago. That's right. Uh, September of last year. A new role >>for you. Is that right? I was starting that new role when I last met you. Yeah, but it's been nine months. Three quarters? What have you learned so far? I mean, it's been quite a right, right? I mean, when I was starting off, I had, you know, about three priorities we've executed on on all of them. So, I mean, if you remember back then they we talked about, you know, improving a cloud experience. We talked about data and analytics being a focus area and then building on the marketplace. I think you heard a lot of that over the last couple of days here. Right? So we've enhanced our cloud experience. We added a private cloud, which was the big announcement yesterday or day before yesterday that Antonio made so that's been I mean, we've been testing that with customers. Great feedback so far. Right? And we're super excited about that. And, uh, you know, uh, down there, the test drive section people are testing that. So we're getting really, really good feedback. Really good acceptance from customers on the data and Analytics side. We you know, we launched the S three connector. We also had the analytics platform. And then we launched data fabric as a service a couple of days ago, right, which is kind of like back into that hybrid world. And then on the marketplace side, we've added a tonne of partners going deep with them about 80 plus partners now different SVS. So again, I think, uh, great. I think we've accomplished a lot over the last three quarters or so lot more to be done. Though >>the marketplace is really interesting to us because it's a hallmark of cloud. You've got to have a market price. Talk about how that's evolving and what your vision is for market. Yes, >>you're exactly right. I mean, having a broad marketplace provides a full for the platform, right? It's a chicken and egg. You need both. You need a good platform on which a good marketplace can set, but the vice versa as well. And what we're doing two things there, Right? One Is we expanding coverage of the marketplace. So we're adding more SVS into the marketplace. But at the same time, we're adding more capabilities into the marketplace. So, for example, we just demoed earlier today quickly deploy capabilities, right? So we have an I S p in the marketplace, they're tested. They are, uh, the work with the solution. But now you can you can collect to deploy directly on our infrastructure over time, the lad, commerce capabilities, licencing capabilities, etcetera. But again, we are super excited about that capability because I think it's important from a customer perspective. >>I want to ask you about that, because that's again the marketplace will be the ultimate arbiter of value creation, ecosystem and marketplace. Go hand in hand. What's your vision for what a successful ecosystem looks like? What's your expectation now that Green Lake is up and running. I stay up and running, but like we've been following the announcement, it just gets better. It's up to the right. So we're anticipating an ecosystem surge. Yeah. What are you expecting? And what's your vision for? How the ecosystem is going to develop out? Yeah. I >>mean, I've been meeting with a lot of our partners over the last couple of days, and you're right, right? I mean, I think of them in three or four buckets right there. I s V s and the I S P is coming to two forms right there. Bigger solutions, right? I think of being Nutanix, right, Home wall, big, bigger solutions. And then they are smaller software packages. I think Mom would think about open source, right? So again, one of them is targeted to developers, the other to the I t. Tops. But that's kind of one bucket, right? I s P s, uh, the second is around the channel partners who take this to market and they're asking us, Hey, this is fantastic. Help us understand how we can help you take this to market. And I think the other bucket system indicators right. I met with a few today and they're all excited about. They're like, Hey, we have some tooling. We have the manage services capabilities. How can we take your cloud? Because they build great practise around extent around. Sorry. Aws around? Uh, sure. So they're like, how can we build a similar practise around Green Lake? So again, those are the big buckets. I would say. Yeah, >>that's a great answer. Great commentary. I want to just follow up on that real quick. You don't mind? So a couple things we're seeing observing I want to get your reaction to is with a i machine learning. And the promise of that vertical specialisation is creating unique opportunities on with these platforms. And the other one is the rise of the managed service provider because expertise are hard to come by. You want kubernetes? Good luck finding talent. So managed services seem to be exploding. How does that fit into the buckets? Or is it all three buckets or you guys enable that? How do you see that coming? And then the vertical piece? >>A really good question. What we're doing is through our software, we're trying to abstract a lot of the complexity of take communities, right? So we are actually off. We have actually automated a whole bunch of communities functionality in our software, and then we provide managed services around it with very little. I would say human labour associated with it is is software manage? But at the same time we are. What we are trying to do is make sure that we enable that same functionality to our partners. So a lot of it is software automation, but then they can wrap their services around it, and that way we can scale the business right. So again, our first principle is automated as much as we can to software right abstract complexity and then as needed, uh, at the Manus Services. >>So you get some functionality for HP to have it and then encourage the ecosystem to fill it in or replicated >>or replicated, right? I mean, I don't think it's either or it should be both right. We can provide many services or we should have our our partners provide manage services. That's how we scale the business. We are the end of the day. We are product and product company, right, and it can manifest itself and services. That discussion was consumed, but it's still I p based. So >>let's quantify, you know, some of that momentum. I think the last time you call your over $800 million now in a are are you gotta You're growing at triple digits. Uh, you got a big backlog. Forget the exact number. Uh, give us a I >>mean, the momentum is fantastic Day. Right. So we have about $7 billion in total contract value, Right? Significant. We have 1600 customers now. Unique customers are running Green Lake. We have, um, your triple dip growth year over year. So the last quarter, we had 100% growth year over year. So again, fantastic momentum. I mean, the other couple, like one other metric I would like to talk about is the, um the stickiness factor associated tension in our retention, right? As renewal's is running in, like, high nineties, right? So if you think about it, that's a reflection of the value proposition of, like, >>that's that's kind of on a unit basis, if you will. That's the number >>on the revenue basis on >>revenue basis. Okay? >>And the 1600 customers. He's talking about the size and actually big numbers. Must be large companies that are. They're >>both right. So I'll give you some examples, right? So I mean, there are large companies. They come from different industries. Different geography is we're seeing, like, the momentum across every single geo, every single industry. I mean, just to take some examples. BMW, for example. Uh, I mean, they're running the entire electrical electric car fleet data collection on data fabric on Green Lake, right? Texas Children's Health on the on the healthcare side. Right On the public sector side, I was with with Carl Hunt yesterday. He's the CEO of County of Essex, New Jersey. So they are running the entire operations on Green Lake. So just if you look at it, Barclays the financial sector, right? I mean, they're running 100,000 workloads of three legs. So if you just look at the scale large companies, small companies, public sector in India, we have Steel Authority of India, which is the largest steel producer there. So, you know, we're seeing it across multiple industries. Multiple geography is great. Great uptake. >>Yeah. We were talking yesterday on our wrap up kind of dissecting through the news. I want to ask you the question that we were riffing on and see if we can get some clarity on it. If I'm a customer, CI or C so or buyer HP have been working with you or your team for for years. What's the value proposition? Finish this sentence. I work with HPV because blank because green like, brings new value proposition. What is that? Fill in that blank for >>me. So I mean, as we, uh, talked with us speaking with customers, customers are looking at alternatives at all times, right? Sometimes there's other providers on premises, sometimes as public cloud. And, uh, as we look at it, uh, I mean, we have value propositions across both. Right. So from a public cloud perspective, some of the challenges that our customers cr around latency around, uh, post predictability, right? That variability cost is really kind of like a challenge. It's around compliance, right? Uh, things of that nature is not open systems, right? I mean, sometimes, you know, they feel locked into a cloud provider, especially when they're using proprietary services. So those are some of the things that we have solved for them as compared to kind of like, you know, the other on premises vendors. I would say the marketplace that we spoke about earlier is huge differentiator. We have this huge marketplace. Now that's developing. Uh, we have high levels of automation that we have built, right, which is, uh, you know, which tells you about the TCO that we can drive for the customers. What? The other thing that is really cool that be introduced in the public in the private cloud is fungible itty across infrastructure. Right? So basically on the same infrastructure you can run. Um, virtual machines, containers, bare metals, any application he wants, you can decommission and commission the infrastructure on the fly. So what it does, is it no matter where it is? Uh, on premises, right? Yeah, earlier. I mean, if you think about it, the infrastructure was dedicated for a certain application. Now we're basically we have basically made it compose herbal, right? And that way, what? Really? Uh, that doesnt increases utilisation so you can get increased utilisation. High automation. What drives lower tco. So you've got a >>horizontal basically platform now that handle a variety of work and >>and these were close. Can sit anywhere to your point, right? I mean, we could have a four node workload out in a manufacturing setting multiple racks in a data centre, and it's all run by the same cloud prints, same software train. So it's really extensive. >>And you can call on the resources that you need for that particular workload. >>Exactly what you need them exactly. Right. >>Excellent. Give you the last word kind of takeaways from Discover. And where when we talk, when we sit down and talk next year, it's about where do you want to be? >>I mean, you know, I think, as you probably saw from discovered, this is, like, very different. Antonio did a live demo of our product, right? Uh, visual school, right? I mean, we haven't done that in a while, so I mean, you started. It >>didn't die like Bill Gates and demos. No, >>no, no, no. I think, uh, so I think you'll see more of that from us. I mean, I'm focused on three things, right? I'm focused on the cloud experience we spoke about. So what we are doing now is making sure that we increase the time for that, uh, make it very, you know, um, attractive to different industries to certifications like HIPAA, etcetera. So that's kind of one focus. So I just drive harder at that adoption of that of the private out, right across different industries and different customer segments. The second is more on the data and analytics I spoke about. You will have more and more analytic capabilities that you'll see, um, building upon data fabric as a service. And this is a marketplace. So that's like it's very specific is the three focus areas were driving hard. All right, we'll be watching >>number two. Instrumentation is really keen >>in the marketplace to I mean, you mentioned Mongo. Some other data platforms that we're going to see here. That's going to be, I think. Critical for Monetisation on the on on Green Lake. Absolutely. Uh, Michelle, thanks so much for coming back in the Cube. >>Thank you. Thanks for coming. All >>right, keep it right. There will be John, and I'll be back up to wrap up the day with a couple of heavies from I d. C. You're watching the cube. Mhm. Mm mm. Mhm.

>>Mhm Yes. Hello and welcome back to the cubes coverage of red hat summit 2021 virtual. I'm john for your host of the cube we're here with Hillary Hunter, the VP and CTO and IBM fellow of IBM cloud at IBM. Hillary, Great to see you welcome back, You're no stranger to us in the cube your dentist few times. Thanks for coming on. >>Thanks so much for having me back. Great to talk more today >>I believe I B M is the premier sponsor for red hat summit this year. No, I mean I think they're somewhat interested in what's happening. >>Yeah, you know, somebody is such a great event for us because it brings together clients that, you know, we work together with red head on and gives us a chance to really talk about that overall journey to cloud and everything that we offer around cloud and cloud adoption um, and around redheads capabilities as well. So we look forward to the summit every year for sure. >>You know, the new IBM red hat relationship obviously pretty tight and successful seeing the early formations and customer attraction and just kind of the momentum, I'll never forget that Red hat something was in SAN Francisco. I sat down with Arvin at that time, uh, Red hat was not part of IBM and it was interesting. He was so tied into cloud native. It was almost as if he was dry running the acquisition, which he announced just moments later after that. But you can see the balance. The Ceo at IBM really totally sees the cloud. He sees that experience. He sees the customer impact. This has been an interesting year, especially with Covid and with the combination of red hat and IBM, this cloud priority for IT leaders is more important than ever before. What's your, what's your take on this? Because clearly you guys are all in on cloud, but not what people think, what's your, what's your view on this? >>Yeah. You know, from, from the perspective of those that are kind of data oriented IBM Institute for Business Value, did lots of studies over the last year, you know, saying that over 60% of leaders feel, you know, increased urgency to get to the cloud, um they're intending to accelerate their program to the cloud, but I think, you know, just even as consumers where each very conscious that our digital behaviors have changed a lot in the last year and we see that in our enterprise client base where um everything from, you know, a bank, we work that that that had to stand up their countries equivalent of the payroll protection program in a matter of weeks, which is just kind of unheard of to do something that robust that quickly or um, you know, retail obviously dealing with major changes, manufacturing, dealing with major changes and all consumers wanting to consume things on an app basis and such, not going into brick and mortar stores and such. And so everything has changed and months, I would say have sort of timeframes of months have been the norm instead of years for um, taking applications forward and modernizing them. And so this journey to cloud has compressed, It's accelerated. And as one client I spoke with said, uh, in the midst of last year, you know, it is existential that I get to cloud with urgency and I think That's been that has been the theme of 2020 and now also 2021. And so it is, it is the core technology for moving faster and dealing with all the change that we're all experiencing. >>That's just so right on point. But I got I want to ask you because this is the key trend enterprises are now realizing that cloud native architecture is based on open source specifically is a key architectural first principle now. >>Yeah. >>What's your, what, what would you say to the folks out there who were listening to this and watching this video, Who were out in the enterprise going, hey, that's a good call. I'm glad I did it. So I don't have any cognitive dissidence or I better get there faster. >>Yeah. You know, open source is such an important part of this conversation because I always say that open source moves at the rate and pays a global innovation, which is kind of a cute phrase that I really don't mean it in anyways, cute. It really is the case that the purpose of open sources for people globally to be contributing. And there's been innovation on everything from climate change to you know, musical applications to um things that are the fundamentals of major enterprise mission critical workloads that have happened is everyone is adopting cloud and open source faster. And so I think that, you know this choice to be on open source is a choice really, you know, to move at the pace of global innovation. It's a choice too um leverage capabilities that are portable and it's a choice to have flexibility in deployment because where everyone's I. T is deployed has also changed. And the balance of sort of where people need the cloud to kind of come to life and be has also changed as everyone's going through this period of significant change. >>That's awesome. IBM like Red has been a long supporter and has a history of supporting open source projects from Lenox to kubernetes. You guys, I think put a billion dollars in Lenox way back when it first started. Really power that movement. That's going back into the history books there. So how are you guys all collaborating today to advance the open source solutions for clients? >>Yeah, we remain very heavily invested in open source communities and invested in work jointly with Red Hat. Um you know, we enabled the technology known as um uh Rackham the short name for the Red Hat advanced cluster management software, um you know, in this last year, um and so, you know, provided that capability um to to become the basis of that that product. So we continue to, you know, move major projects into open source and we continue to encourage external innovators as well to create new capabilities. And open source are called for code initiatives for developers as an example, um have had specific programs around um uh social justice and racial issues. Um we have a new call for code out encouraging open source projects around climate change and sustainable agriculture and all those kind of topics and so everything from you know, topics with developers to core product portfolio for us. Um We have a very uh very firm commitment in an ongoing sustained contribution on an open source basis. >>I think that's important. Just to call out just to kind of take a little sidebar here. Um you guys really have a strong mission driven culture at IBM want to give you props for that. Just take a minute to say, Congratulations call for code incredible initiative. You guys do a great job. So congratulations on that. Appreciate. >>Thank you. Thank you. >>Um as a sponsor of Red Hat Summit this year, I am sponsoring the zone Read at um you have you have two sessions that you're hosting, Could you talk about what's going on? >>Yeah, the the two sessions, so one that I'm hosting is around um getting what we call 2.5 x value out of your cloud journey. Um and really looking at kind of how we're working with clients from the start of the journey of considering cloud through to actually deploying and managing environments and operating model on the cloud um and where we can extract greater value and then another session um that I'm doing with Roger Primo, our senior vice President for strategy at IBM We're talking about lessons and clouded option from the Fortune 500, so we're talking there about coca cola european bottling partners, about lumen technologies um and um also about wonderman Thompson, um and what they're doing with us with clouds, so kind of two sessions, kind of one talking a sort of a chalkboard style um A little bit of an informal conversation about what is value meaning cloud or what are we trying to get out of it together? Um And then a session with roger really kind of focused on enterprise use cases and real stories of cloud adoption. >>Alright so bottom line what's going to be in the sessions, why should I attend? What's the yeah >>so you know honest honestly I think that there's kind of this um there's this great hunger I would say in the industry right now to ascertain value um and in all I. T. Decision making, that's the key question right? Um not just go to the cloud because everyone's going to the cloud or not just adopt you know open source technologies because it's you know something that someone said to do, but what value are we going to get out of it? And then how do we have an intentional conversation about cloud architecture? How do we think about managing across environments in a consistent way? Um how do we think about extracting value in that journey of application, modernization, um and how do we structure and plan that in a way? Um that results in value to the business at the end of the day, because this notion of digital transformation is really what's underlying it. You want a different business outcome at the end of the day and the decisions that you take in your cloud journey picking. Um and open hybrid, multi cloud architecture leveraging technologies like IBM cloud satellite to have a consistent control plan across your environments, um leveraging particular programs that we have around security and compliance to accelerate the journey for regulated industries etcetera. Taking intentional decisions that are relevant to your industry that enable future flexibility and then enable a broad ecosystem of content, for example, through red hat marketplace, all the capabilities and content that deploy onto open shift, et cetera. Those are core foundational decisions that then unlock that value in the cloud journey and really result in a successful cloud experience and not just I kind of tried it and I did or didn't get out of it what I was expecting. So that's really what, you know, we talk about in these in these two sessions, um and walk through um in the second session than, you know, some client use cases of, of different levels and stages in that cloud journey, some really core enterprise capabilities and then Greenfield whitespace completely new capabilities and cloud can address that full spectrum. >>That's exciting not to get all nerdy for a second here, But you know, you bring up cloud architecture, hybrid cloud architecture and correct me if I'm wrong if you're going to address it because I think this is what I'm reporting and hearing in the industry against the killer problem everyone's trying to solve is you mentioned, um, data, you mentioned control playing for data, you mentioned security. These are like horizontally scalable operating model concepts. So if you think about an operating system, this is this is the architecture that becomes the cloud model hybrid model because it's not just public cloud cloud native or being born in the cloud. Like a startup. The integration of operating at scale is a distributed computing model. So you have an operating system concept with some systems engineering. Yeah, it sounds like a computer to me, right. It sounds like a mainframe. Sounds like something like that where you're thinking about not just software but operating model is, am I getting that right? Because this is like fundamental. >>Yeah, it's so fundamental. And I think it's a great analogy, right? I think it's um you know, everyone has kind of, their different description of what cloud is, what constitutes cloud and all that kind of thing, but I think it's great to think of it as a system, it's a system for computing and what we're trying to do with cloud, what we're trying to do with kubernetes is to orchestrate a bunch of, you know, computing in a consistent way, as, you know, other functions within a single server do. Um What we're trying to do with open shift is, you know, to enable um clients to consume things in a consistent way across many different environments. Again, that's the same sort of function um conceptually as, you know, an operating system or something like that is supposed to provide is to have a platform fundamentally, I think the word platform is important, right? Have a platform that's consistent across many environments and enables people to be productive in all those environments where they need to be doing their computing. >>We were talking before we came on camera about cloud history and we were kind of riffing back and forth around, oh yeah, five years ago or six years ago was all the conversations go to the cloud now, it's like serious conscience around the maturity of cloud and how to operate that scale in the cloud, which is complex, it's complex system and you have complexity around system complexity and novelty complexity, so you have kind of all these new things happening. So I want to ask you because you're an IBM fellow and you're on the cloud side at IBM with all this red hat goodness you've got going on, Can you give us a preview of the maturity model that you see the IBM season, that red hats doing so that these architectures can be consistent across the platforms, because you've got def sec ops, you've got all these new things, you've got security and data at scale, it's not that obviously it's not easy, but it has to be easier. What's what's the preview of the maturity model? >>Yeah, you know, it really is about kind of a one plus one equals three conversation because red hats approach to provide a consistent platform across different environments in terms of Lennox and Kubernetes and the open shift platform um enables that first conversation about consistency and maturity um in many cases comes from consistency, being able to have standards and consistency and deployment across different environments leads to efficiency. Um But then IBM odds on that, you know, a set of conversations also around data governance, um consistency of data, cataloguing data management across environments, machine learning and ai right bringing in A. I. For I. T. Operations, helping you be more efficient to diagnose problems in the IT environment, other things like that. And then, you know, in addition, you know, automation ultimately right when we're talking about F. R. I. T. Ops, but also automation which begins down at the open shift level, you know with use of answerable and other things like that and extends them up into automation and monitoring of the environment and the workloads and other things like that. And so it really is a set of unlocking value through increasing amounts of insight, consistency across environments, layering that up into the data layer. Um And then overall being able to do that, you know efficiently um and and in a consistent way across the different environments, you know, where cloud needs to be deployed in order to be most effective, >>You know, David Hunt and I always talk about IBM and all the years we've been covering with the Cube, I mean we've pretty much been to every IBM events since the Cube was founded and we're on our 11th year now watching the progression, you guys have so much expertise in so many different verticals, just a history and the expertise and the knowledge and the people. They're so smart. Um I have to ask you how you evolved your portfolio with the cloud now um as it's gone through, as we are in the 2021 having these mature conversations around, you know, full integration, large scale enterprise deployments, Critical Mission Mission Critical Applications, critical infrastructure, data, cybersecurity, global scale. How are you evolve your portfolio to better support your clients in this new environment? >>Yeah, there's a lot in there and you hit a lot of the keywords already. Thank you. But but I think that you know um we have oriented our portfolio is such that all of our systems support Red hat um and open shift, um our cloud, we have redhead open shift as a managed service and kubernetes is at the core of what we're doing as a cloud provider and achieving our own operational efficiencies um from the perspective of our software portfolio, our core products are delivered in the form of what we refer to as cloud packs on open shift and therefore deploy across all these different environments where open shift is supported, um products available through Red hat marketplace, you know, which facilitates the billing and purchasing an acquisition and installation of anything within the red hat ecosystem. And I think, you know, for us this is also then become also a journey about operational efficiency. We're working with many of our clients is we're kind of chatting about before about their cloud operating model, about their transformation um and ultimately in many cases about consumption of cloud as a service. Um and so um as we, you know, extend our own cloud capabilities, you know, out into other environment through distributed cloud program, what we refer to as as IBM cloud satellite, you know, that enables consistent and secure deployment of cloud um into any environment um where someone needs, you know, cloud to be operated. Um And that operating model conversation with our clients, you know, has to do with their own open shift environments that has to do with their software from IBM, it has to do their cloud services. And we're really ultimately looking to partner with clients to find efficiency in each stage of that journey and application modernization in deployment and then in getting consistency across all their environments, leveraging everything from uh the red hat, you know, ACM capabilities for cluster management up through a i for beauty shops and automation and use of a common console across services. And so it's an exciting time because we've been able to align our portfolio, get consistency and delivery of the red half capabilities across our full portfolio and then enable clients to progress to really efficient consumption of cloud. >>That's awesome. Great stuff there. I got to ask you the question that's on probably your customers minds. They say, okay, Hillary, you got me sold me on this. I get what's going on, I just gotta go faster. How do I advance my hybrid cloud model faster? What are you gonna do for me? What do you have within the red hat world and IBM world? How are you gonna make me go faster? That's in high quality way? >>Yeah. You know, we often like to start with an assessment of the application landscape because you move faster by moving strategically, right? So assessing applications and the opportunity to move most quickly into a cloud model, um, what to containerized first, what to invest in lift and shift perspective, etcetera. So we we help people look at um what is strategic to move and where the return on investment will be the greatest. We help them also with migrations, Right? So we can help jump in with additional skills and establish a cloud center of competency and other things like that. That can help them move faster as well as move faster with us. And I think ultimately choosing the right portfolio for what is defined as cloud is so important, having uh, an open based architecture and cloud deployment choice is so important so that you don't get stuck in where you made some of your initial decisions. And so I think those are kind of the three core components to how we're helping our clients move as quickly as possible and at the rate and pace that the current climate frankly demands of everyone. >>You know, I was joking with a friend the other night about databases and how generations you have an argument about what is it database, what's it used for. And then when you kind of get to that argument, all agree. Then a new database comes along and then it's for different functions. Just the growth in the internet and computing. Same with cloud, you kind of see a parallel thing where it's like debate, what is cloud? Why does he even exist? People have different definitions. That was, you know, I mean a decade or so ago. And then now we're at almost another point where it's again another read definition of, okay, what's next for cloud? It's almost like an inflection point here again. So with that I got to ask you as a fellow and IBM VP and Cto, what is the IBM cloud because if I'm going to have a discussion with IBM at the center of it, what does it mean to me? That's what people would like to know. How do you respond to that? >>Yeah. You know, I think two things I think number one to the, to the question of accelerating people's journeys to the cloud, we are very focused within the IBM cloud business um on our industry specific programs on our work with our traditional enterprise client base and regulated industries, things like what we're doing in cloud for financial services, where we're taking cloud, um and not just doing some sort of marketing but doing technology, which contextualize is cloud to tackle the difficult problems of those industries. So financial services, telco uh et cetera. And so I think that's really about next generation cloud, right? Not cloud, just for oh, I'm consuming some sauce, and so it's going to be in the cloud. Um but SAS and I SV capabilities and an organization's own capabilities delivered in a way appropriate to their industry in in a way that enables them to consume cloud faster. And I think along those lines then kind of second thing of, you know, whereas cloud headed the conversation in the industry around confidential computing, I think is increasingly important. Um It's an area that we've invested now for several generations of technology capability, confidential computing means being able to operate even in a cloud environment where there are others around um but still have complete privacy and authority over what you're doing. And that extra degree of protection is so important right now. It's such a critical conversation um with all of our clients. Obviously those in things like, you know, digital assets, custody or healthcare records or other things like that are very concerned and focused about data privacy and protection. And these technologies are obvious to them in many cases that yes, they should take that extra step and leverage confidential computing and additional data protection. But really confidential computing we're seeing growing as a topic zero trust other models like that because everyone wants to know that not only are they moving faster because they're moving to cloud, but they're doing so in a way that is without any compromise in their total security, um and their data protection on behalf of their clients. So it's exciting times. >>So it's so exciting just to think about the possibilities because trust more than ever now, we're on a global society, whether it's cyber security or personal interactions to data signing off on code, what's the mutability of it? I mean, it's a complete interplay of all the fun things of uh of the technology kind of coming together. >>Absolutely, yeah. There is so much coming together and confidential computing and realizing it has been a decade long journey for us. Right? We brought our first products actually into cloud in 2019, but its hardware, it's software, it services. It's a lot of different things coming together. Um but we've been able to bring them together, bring them together at enterprise scale able to run entire databases and large workloads and you know um pharmaceutical record system for Germany and customer records for daimler and um you know what we're doing with banks globally etcetera and so you know it's it's wonderful to see all of that work from our research division and our developers and our cloud teams kind of come together and come to fruition and and really be real and be product sizable. So it's it's very exciting times and it's it's a conversation that I think I encourage everyone to learn a little bit more about confidential computing. >>Hillary hunter. Thank you for coming on the cube. Vice President CTO and IBM fellow which is a big distinction at IBM. Congratulations and thanks for coming on the Cuban sharing your insight. Always a pleasure to have you on an expert always. Great conversation. Thanks for coming on. >>Thanks so much for having me. It was a pleasure. >>Okay, so cubes coverage of red Hat Summit 21 of course, IBM think is right around the corner as well. So that's gonna be another great event as well. I'm john Feehery, a host of the cube bringing all the action. Thanks for watching. Yeah.

>> Live from San Francisco. It's the Cube covering artists. A conference twenty nineteen brought to you by for scout. >> Hey, Welcome back, everybody. Jefe Rick here with the Cube were in the force caboose that Arcee and Mosconi center forty thousand people walking around talking about security is by far the biggest security of it in the world. We're excited to be here. And welcome back a Cube. Alumni has been playing in the security space for a very long time. He's Bradman bury the GDP from Booz Allen >> Hamilton. Brad, great to see you. >> Hey, thanks for having me here today. Absolutely. Yeah. I've, uh I've already walked about seven miles today, and, uh, just glad to be here to have >> a conversation. Yeah, the fit bitten. The walking trackers love this place, right? You feel your circles in a very short period of time. >> I feel very fit fit after today. So thank >> you. But it's pretty interesting rights, >> and you're in it. You're in a position where you're >> advising companies, both government and and commercial companies, you know, to come into an environment like this and just be overwhelmed by so many options. Right? And you can't buy everything here, and you shouldn't buy everything here. So how do you help? How do you hope your client's kind of navigate this crazy landscape. >> It's interesting, so you mentioned forty thousand people. Aziz, you see on the show, should share room floor behind us, Thousands of product companies, and, frankly, our clients are confused. Um, you know, there's a lot of tools, lot technologies. There's no silver bullet, and our clients are asking a couple of fundamental problem. A couple of fundamental questions. One. How effective in mine and then once them effective, you know, how can I be more efficient with my cyber pretty spent? >> So it's funny, effective. So how are they measuring effective, Right? Because that's a that's a kind of a changing, amorphous thing to target as well. >> That's I mean, that's that's That's the that's the key question in cybersecurity is how effective my, you know, there's lots of tools and technologies. We do a lot of instant response, but commercially and federally and in general, when looking at past reaches, its not a problem. In most cases, everyone has the best of the best and tools and technologies. But either they're drowning in data on DH or the tools aren't configured properly, so you know we're spending a lot of time helping our client's baseline their current environment. Help them look at their tool configurations, help them look at their screw. The operation center helping them figure out Can they detect the most recent threats? And how quickly can we respond? >> Right? And then how did they prioritize? That's the thing that always amazes me, because then you can't do everything right. And and it's fascinating with, you know, the recent elections and, you know, kind of a state funded threats. Is that what the bad guys are going on going after? Excuse me? Isn't necessarily your personal identifying information or your bank account, but all kinds of things that you may not have thought were that valuable yesterday, >> right? I mean, you know, it's funny. We talk a lot about these black swan events, and so you look at not Petra and you know what? Not Pecchia. There was some companies that were really hit in a very significant way, and, you know, everyone, everyone is surprised, right and way. See it time after time, folks caught off guard by, you know, these unanticipated attack vectors. It's a big problem. But, you know, I think you know, our clients are getting better. They're starting to be more proactive. There start. They're starting to become more integrated communities where they're taking intelligence and using that to better tune and Taylor there screw the operation programs. And, you know, they're starting to also used take the tools and technologies in their environment, better tie them and integrate them with their operational processes and getting better. >> Right. So another big change in the landscape. You said you've been coming here for years. Society, right? And yeah. And it's just called Industrial. I owe to your Jean. Call it. Yeah. And other things. A lot more devices should or should not be connected. Well, are going to be connected. They were necessarily designed to be connected. And you also work on the military side as well. Right? And these have significant implications. These things do things, whether it's a turbine, whether it's something in the hospital, this monitoring that hard or whether it's, you know, something in a military scenarios. So >> how are you seeing >> the adoption of that? Obviously the benefits far out way you know, the potential downfalls. But you gotta protect for the downfall, >> you know? Yo, Tio, we've u o T is one of the most pressing cyber security challenges that our client's case today. And it's funny. When we first started engaging in the OT space, there was a big vocabulary mismatch. You had thesis, Oh, organizations that we're talking threat actors and attack vectors, and then you had head of manufacturing that we're talking up time, availability and reliability and they were talking past each other. I think now we're at an attorney point where both communities air coming together to recognize that this is a really an imminent threat to the survival of their organization and that they've got to protect they're ot environment. They're starting by making sure that they have segmentation in place. But that's not enough. And you know, it's interesting when we look into a lot of the OT environments, you know, I call it the Smithsonian of it. And so, you know, I was looking at one of our client environments and, you know, they had, Ah, lot of Windows and T devices like that's great. I'm a Windows NT expert. I was using that between nineteen ninety four in nineteen ninety six, and you know, I mean, it's everybody's favorite vulnerability. Right on Rodeo. I'm your guy. So, you know, one of the challenges that we're facing is how do you go into these legacy environments that have very mission critical operations and, you know, integrates cyber security to protect and ensure their mission. And so we're working with companies like for Scott, you know, that provide Asian agent lis capabilities, that that allow us to better no one understand what's in the environment and then be able to apply policies to be able to better protect and defend them. But certainly it's a major issue that everyone's facing. We spent a lot of time talking about issues in manufacturing, but but think about the utilities. Think about the power grid. Think about building control systems. H back. You know, I was talking to a client that has a very critical mission, and I asked them all like, what's your biggest challenge? You face today? And I was thinking for something. I was thinking they were going to be talking about their mission control system. Or, you know, some of some of the rial, you know, critical critical assets they have. But what he said, My biggest challenge is my, my age back, and I'm like, really, He's like my age back goes down, My operation's gonna be disrupted. I'm going out to Coop halfway across the country, and that could result in loss of life. It's a big issue. >> Yeah, it's wild. Triggered all kinds. I think Mike earlier today said that a lot of a lot of the devices you don't even know you're running in tea. Yeah, it's like a little tiny version of Inti that's running underneath this operating system that's running this device. You don't even know it. And it's funny. You talked about the HBC. There was a keynote earlier today where they talk about, you know, if a data center HBC goes down first. I think she said, sixty seconds stuff starts turning off, right? So, you know, depending on what that thing is powering, that's a pretty significant data point. >> Yeah, you know, I think where we are in the journey and the OT is, you know, we started by creating the burning platform, making sure that there was awareness around hate. There is a problem. There is a threat. I think we've moved beyond that. WeII then moved into, you know, segmenting the BOT environment, A lot of the major nation state attacks that we've seen started in the enterprise and move laterally into the OT environment. So we're starting to get better segmentation in place. Now we're getting to a point where we're moving into, you know, the shop floors, the manufacturing facilities, the utilities, and we're starting Teo understand what's on the network right in the world This has probably been struggling with for years and have started to overcome. But in the OT environment, it's still a problem. So understanding what's connected to the network and then building strategy for how we can really protecting defendant. And the difference is it's not just about protecting and defending, but it's insuring continuity of mission. It's about being resilient, >> right and being able to find if there's a problem down the problem. I mean, we're almost numb. Tow the data breach is right there in the paper every day. I mean, I think Michael is really the last big when everyone had a connection fit down. Okay, it's another another data breach. So it's a big It's a big issue. That's right. So >> one of the things you talked about last time we had >> John was continuous diagnostic and mitigation. I think it's a really interesting take that pretty clear in the wording that it's not. It's not by something, put it in and go on vacation. It was a constant, an ongoing process, and I have to really be committed to >> Yeah, you know, I think that, you know, our clients, the federally and commercially are moving beyond compliance. And if you rewind the clock many years ago, everyone was looking at these compliance scores and saying Good to go. And in reality, if you're if you're compliant, you're really looking in the rear view mirror. And it's really about, you know, putting in programs that's continually assessing risk, continuing to take a continues to look at your your environment so that you can better understand what are the risks, one of the threats and that you can prioritize activity in action. And I think the federal government is leading the way with some major programs. I got a VHS continuous diagnostic in mitigation where they're really looking Teo up armor dot gov and, you know, really take a more proactive approach. Teo, you know, securing critical infrastructure, right? Just >> curious because you you kind >> of split the fence between the federal clients and the commercial clients. Everybody's, you know, kind of points of view in packs away they see the world. >> What if you could share? >> Kind of, maybe what's more of a federal kind of centric view that wasn't necessarily shared on the commercial side of they prioritize. And what's kind of the one of the commercial side that the feds are missing? I assume you want to get him both kind of thinking about the same thing, but there's got to be a different set of priorities. >> Yeah, you know, I think after some of the major commercial breaches, Way saw the commercial entities go through a real focused effort. Teo, take the tools that they have in the infrastructure to make sure that they're better integrated. Because, you know, in this mass product landscape, there's lots of seems that the adversaries livin and then better tie the tooling in the infrastructure with security operations and on the security operation side, take more of an intelligence driven approach, meaning that you're looking at what's going on out in the wild, taking that information be able to enrich it and using that to be more proactive instead of waiting for an event to pop up on the screen hunt for adversaries in your network. Right now, we're seeing the commercial market really refining that approach. And now we're seeing our government clients start to adopt an embrace commercial. Best practices. >> Write some curious. I love that line. Adversaries live in the scene. Right? We're going to an all hybrid world, right? Public cloud is kicking tail. People have stuff in public, cloud their stuff in their own cloud. They have, you know, it's very kind of hybrid ecosystems that sounds like it's making a whole lot of scenes. >> Yeah, you know, it. You know, just went Just when we think we're getting getting there, you know, we're getting the enterprise under control. We've got asset management in place, You know. We're modernizing security operations. We're being Mohr Hunt driven. More proactive now the attacks services expanding. You know, earlier we talked about the OT environment that's introducing a much broader and new attack service. But now we're talking about cloud and it's not just a single cloud. There's multiple cloud providers, right? And now we're not. Now we're talking about software is a service and multiple software's of service providers. So you know, it's not just what's in your environment now. It's your extended enterprise that includes clouds. So far is the service. Excuse me, ot Io ti and the problem's getting much more complex. And so it's going to keep us busy for the next couple of years. I think job security's okay, I think where I think we're gonna be busy, all >> right, before I let you go, just kind of top trends that you're thinking about what you guys are looking at a za company as we had in twenty >> nineteen, you know, a couple of things. You know, Who's Alan being being deeply rooted in defense and intelligence were working, Teo, unlocking our tradecraft that we've gained through years of dealing with the adversary and working to figure out howto better apply that to cyber defense. Things like advanced threat hunting things like adversary red teaming things like being able to do base lining to assess the effectiveness of an organisation. And then last but not least, a i a. I is a big trend in the industry. It's probably become one of the most overused but buzzwords. But we're looking at specific use cases around artificial intelligence. How do you, you know better Accelerate. Tier one tier, two events triaging in a sock. How do you better detect, you know, adversary movement to enhance detection in your enterprise and, you know, eyes, you know, very, you know, a major major term that's being thrown out at this conference. But we're really looking at how to operationalize that over the next three to five years, >> right? Right. And the bad guys have it too, right? And never forget tomorrow's Law. One of my favorite, not quoted enough laws, right, tend to overestimate in the short term and underestimate in the long term, maybe today's buzzword. But three to five years A I's gonna be everywhere. Absolutely. Alright. Well, Brad, thanks for taking a few minutes of your day is done by. Good >> to see you again. All right, >> all right. He's Brad. I'm Jeff. You're watching. The Cube were in Arcee conference in downtown San Francisco. Thanks >> for watching. We'LL see you next time.

>> Narrator: From Hell's Kitchen in New York City, it's theCUBE, on the ground at Serverlessconf brought to you by SiliconAngle Media >> Hi, I'm Stu Miniman, here with theCUBE at Serverless Conference in New York City, Hell's Kitchen. Happy to have with me, first time guest on the program Sam Kroonenburg, we had your brother on the program at the AWS Summit not far from here, at the Javits Center in New York City, but you're also one of the co-founders its the two brothers for A Cloud Guru. Thanks so much for joining me, and thank you for allowing us to come get some phenomenal content here. >> Yeah, no problem. Thank you for coming for the conference today. >> Alright, so Sam, take me back, you know, we talked to your brother a little bit about, well it was an interesting story, he said actually I got turned down for a job from Amazon and ended up creating a training company. But you built this and you built it on Serverless. >> I did yeah. >> So walk us through a little bit the thought process, the timing, you know, aren't you a little bit ahead of your time on that? >> Yeah, it was mid 2015, it was a strange time. We decided we wanted to build this school, this online learning platform, but the challenge we had was that we didn't have a lot of time, we both had families, kids, you know, mortgages, financial commitments. Basically I had four weeks. I had four weeks of leave owing to me, from my employer at the time. My wife and I had been planning this big family holiday with the kids for years and we were about to take it, and I remember having this phone call with Ryan and we were talking about how there were these people taking these online courses and they were really liking them. And we thought, what if we could build this school to teach people cloud computing. It was such a buzz and we just thought, there's something in this. But the challenge was the timing. I remember my wife turned to me and she said, "Look you've got to do it, we'll cancel the holiday, "take the four weeks and give it a try." So that's what we did, we actually flew down to live with Aaron, my in-laws and help look after the kids and I locked myself in a bedroom for four weeks and tried to build an online school. And that was there was no epiphany to go Serverless there was no grand plan. It was, we had a constraint, which was time. I had no time to build this thing. And so ended up using some of the latest technologies like AWS Lambda, API Gateway, a whole bunch of Serverless technologies because I saw that they would help me build this faster. And I could get something to market in the four weeks that I had. I actually spent the first couple of days trying to skin and configure Moodle, the learning management system and I tore my hair out and yeah, ended up putting this thing together with Serverless technologies. >> Ryan just walked by-- >> Oh, there he is. >> It's a llama unicorn with a cat or something like that. >> I'm going to put in the background. >> In the back of our video. Sam, what's your brother doing here? >> He's always trying to troll me. >> So talk to us, you know one of the things the maturation, kind of the speed of change in the industry for new technologies is just so fast these days. Take us through from those early days to you know Serverless today. What's your experience been? What would you say to people that look at this technology? >> I think it's a lot easier to get into now than it was two years ago. The ecosystem has grown around it, the core technologies are pretty much the same as they were two years ago, function as a service, execute functions in the cloud very similar, but the tooling around it, the ecosystem around it has grown. There's great deployment tools, orchestration systems that have come along. It's a lot easier to just get in now and early on, when we started we had to roll a lot of things ourselves, which took a lot of time, and that's what you're trying to stop, is losing time. Yeah, so there's that and the community has really grown, there's a lot of support in the community now. >> So if you had to do it all over, you could have done it in a weekend, rather than the four weeks. >> Yeah, instead of the four weeks. >> Yeah, I mean what's-- >> That's the interesting thing about what happened to us, we would not exist, our business would not exist if it wasn't for Serverless technologies. I literally couldn't, we could not have, built that school. It's not like it was the most amazing school when we launched it, but it was enough. It was just enough to get people using it, to get to market, to start to build a business around it. >> Alright, talk to me about this event. So, its the 5th Serverlessconf, not unheard of a company that does training to get involved with physical events, 'cause you bring them together, you know, what's the thought process, talk to us a little bit about that journey and this event itself. >> Yeah, I mean, a lot of this is organic for us. We built, it was early last year, you know we're part of the Serverless communities, a lot of pioneering going on here, a lot of people facing the same challenges. And we thought, well there's no event to bring all of these people together. And there's a lot of very fast pace of change here, a lot of rapid ideation and new technologies. Let's bring everyone together and see what we can do. That's what we did with Serverlessconf. We've never run a conference before, we just hired a warehouse in Brooklyn, a bunch of Australians and British guys coming over and we just invited a bunch of people on Twitter and 250 people turned out to the first one. It just got bigger and bigger from there. So this is actually the 5th Serverlessconf now. >> Well, its a hot week again, so we appreciate that the air conditioning works at this one. >> Yes, we have air conditioning at this one. >> 460 people here, you brought in some great speakers, we had a number of them on our program this week, speak to us, I mean you've got sponsors here, you've got good speakers, give us some of the highlights. >> We've got all of the main Cloud vendors are here, Google, IBM, Microsoft, Amazon and it's actually the product teams who build this stuff. That's what I love about this event, it's actually the people who build it. It's vendor neutral, it's really cool. You get great thought leaders from the community, Simon Wardley was a highlight this morning, his talk on Value Chain Mapping and Strategy was really interesting. Randall Hunt from AWS X Space X, talking about the continuous integration process when building rockets. Space X was absolutely fascinating and what bugs in production mean when you're building a rocket. It means the rocket blows up. Really interesting variety of talks from those tooling providers, companies like us who are just building on Serverless and then Serverless tooling companies and vendors. Really fascinating. >> Alright, Sam what should we be looking for in the future from Serverless and from A Cloud Guru? >> We're going to be doing a whole lot more Serverless content. You're going to see a lot of really interesting new content through our site, a lot of teaching on Serverless, we're going to be doing more Serverless Conferences. You'll see a lot from us, not just us, but from the wider community who come to the conference, who we know well, a lot of the experts, we're going to be doing a lot of work with those people. >> Well Sam Kroonenburg, really appreciate you joining us, appreciate the media sponsorship to allow theCube to come get some great content and share it with our communities, hope to see you at many more events in the future. >> Thank you for coming. >> Thank you so much. Sam Kroonenburg, I'm Stu Miniman. Thank you for watching theCUBE. (upbeat music)

>> Announcer: Live from Las Vegas, it's The Cube covering Dell EMC World 2017 brought to you by Dell EMC. >> Welcome back here on The Cube, the Flagship broadcast of SiliconANGLE TV. We rap up our coverage today, day two of Dell EMC World 2017. We're live in Las Vegas. I'm John Walls along with Rebecca Knight and joining us now all the way from Tobacco Road Patrick Williams, who is the IT Infrastructure Architect at North Carolina State University in beautiful Raleigh, North Carolina. Patrick, thank you for joining us. >> Thank you. >> Tell us first of all, you know, academically, you're the first, somebody from that community that we have a chance to speak with over the past two days. What are you seeing here that you are going to find of interest that you might want to take back with you to Raleigh, that maybe you're going to put into practice? >> Right, so we're really taking a look at the technologies that we have in play, and there's been a lot of new announcements at the conference this year, so we have Unity Storage, we have Data Domain and there's been announcements pretty much across that product spectrum, so we've been looking, going to breakout sessions talking to the experts and trying to take a look at the technology and see how we can take advantage of the new features that are offered in our environment. >> So before the cameras were rolling, you were setting the scene a little bit and describing the kinds of data needs, security needs that you have for a busy, thriving, and large college campus. Can you lay that out for our viewers? >> Right so for a college campus, one of the biggest concerns is around security, so there's a mandate or desire, probably as part of the academic culture to be as open as possible because the goal is to exchange ideas and to share resources between the university and across our set of institutions. So contrast that with the reality that we have to maintain a high level of security now, so there's obviously a lot of incidents. We are a Google Mail university and as you know, there was recently an attack on Gmail, right? So one of the things that we've had to do is to say, "We're going to implement Two Factor Authentication. "We're going to develop a classification system "around how we assess and manage data," so depending on the category, there's different levels of security that are in put in place in our (mumbles) environment, while also trying to remain as open as possible. >> So you have a lot of competing interests, it seems, in trying to balance those interests, is how much of your job? >> 100%. (laughing) Yeah, so what I would say is that in order to be able to get proposals forward, I have to be able to make the case on all sides of the equation, so I have to make the correct academic case. I have to make the correct business case. I have to make the correct cultural case and if I can make those cases coincide, then we can succeed and move things forward and get proposals. >> 'Cause you're saying that at NC State, it's not central IT. You're in IT, but there are some more schools that have options, they can make their own decisions, and so I would think coordination, integration, are not barriers, but certainly challenges. >> That's right, so we are, we call ourselves a central IT group; however, there is no mandate for each of the colleges to use central IT services, so our goal is to create kind of a foundational set of services that the consumers then in come and build on top of rather than building their own resources and we like to see that grow kind of organically rather than to mandate it, use of central services, and we've actually had great success. So we've had a lot of resources to come back from the edge into the central folds and be able to grow that centrally, put a higher level of resiliency on top of those services and satisfy our customers. >> In terms of one of the challenges, though, cost is a huge one, and then making sure that things do come within budget and not a penny over. Can you talk a little bit about some of those obstacles and how you've overcome them? >> Right, so cost is everything for us. Our budgets have been flat for the past three years, but the demand for growth in capacity and existing environments and the demand for new services is ongoing. What we've been able to do is to work really hard on assessing our resources. We've implemented Cloud IQ a year ago when it was first announced to get a kind of a long-term view of our environment and kind of track our growth, and that has enabled us to put the right data in the appropriate tier and be able to maximize our investment and that's really helped us be able to continue to grow our environments as we move forward. >> When you're talking about the different clients or constituencies you're trying to please: you've got the students, the faculty, the administration, and the staff, what do students want, what do faculty want, and how do you give them what they want? >> That's right. So students, is really interesting because the student perspective has really changed over the past couple of years and it caught us off-guard. We have a pervasive data network on our campus. We have all the dorms wired. We have about 21,000 students total. About 8000 stay on campus. All those dorms were hard-wired, but we did not have wifi enabled in all the dorms and we survey students every year. Last year we surveyed them and we got very bad marks because that, even a jack was not enough for them. If you look at what you typically show up with now, how many devices have a hard-wired jack, none, right? So they show up with four devices. They couldn't use any of them on our data network and their response on the survey was, the one that I remember the most was, "Our lives depend on wifi," that was the quote. >> Of course. >> We, of course, immediately went and looked at how we roll out 4000 access points right away. We did that over a summer. That was able to succeed. We also have a very unique set of challenges in that because I mentioned that, we only have 4000 students, slightly more than that, that stay on campus. The majority of them move back and forth between classes so 10 AM when 5000 people walk by one access point. >> When they've just woken up. >> That's right. >> 10 AM. >> Or log in to check their email, et cetera. So those are unique challenges so what we had to do is what are the tools to track the application resources? What's normal application performance? What's a normal peak and what's a breakout that's outside of the normal, and how do we profile that and we want to be well ahead of the demand so that we can put those resources in place ahead of the need. >> So what do you do about the challenge of future deployments? Your budget's going to be somewhat constrained. You know your needs are increasing. You know your constituents have new and growing demand. So, I mean, tough nut to crack, isn't it? You're trying to make your cloud strategy. What are you going to do with that? The 4GG server coming on board now, how do you find, or how do you balance that from the academic perspective? >> You mentioned that and also I didn't mention that one of our data centers is aging and so on top of all that, we're also starting to see, put a strain on our data center resources. What we really hope to be able to do is to leverage some type of a hybrid cloud strategy. The challenge for us has been, what is our application profile? If you look at applications that are a great fit in cloud and applications that are not a great fit in cloud, the traditional backend applications, the core infrastructure applications are not necessarily a great fit, and so what we're trying to figure out is what is the best hybrid solution that will help you move our environment forward and still leverage existing resources. >> So looking ahead, what does the college campus of the future, the technology-enabled college campus of the future look like? Give us a picture. >> I think one of the best examples i can give is our Hunt Library, so we opened a new library on what we call our Centennial Campus a few years ago. It was designed from the ground up as kind of a new model of what does the next generational library look like because it's not, if you think of a library now, you don't think of a traditional, okay, here's a building and stacks and stacks and stacks of books. So they put the books off in a corner and there is a large robotic library that's designed to handle the books and the bulk of it is about collaborative spaces, so there are high-end collaborative work stations, consolidated areas. There are students that are in the design school. If you want to go and practice your DJ skills, you can do that there as well, so that's where things are really headed. >> So Patrick, before we let you go, my final question is, when are you going to beat Carolina and Duke at basketball? >> We're waiting, so we have that US Championship banners from the '80s and I'm tired of looking at that, so we're really looking forward to-- >> Those days are long-gone. >> Right. >> Right, Patrick Williams, NC State, thank you for being with us here on The Cube. Safe travels back home and continued success at Raleigh. >> Thank you. >> Appreciate the time. >> Alright. >> Good. That raps it up here on The Cube, day two is in the books. We'll see you back here tomorrow morning at 11:30 central time, that's 2:30 on the East Coast, for more interviews live from Las Vegas, until then. For Rebecca Knight, I'm John Walls. Have a good night.

[Announcer] Live from Las Vegas. It's the Cube, covering NAB 2017. Brought to you by HGST. >> Welcome back to the Cube. We are live in Las Vegas at the very exciting NAB show 2017. And I'm very excited to introduce you to our next guest, Andy Shenkler. Andy is the EVP, Chief Solutions and Technology Officer, for Sony DADC New Media Solutions. Andy, welcome to the Cube. Thank you very much for having me. You are a veteran, not only of the media and entertainment industry, but of NAB with this year's theme of the M.E.T Effect. That's the convergence of media entertainment technology. What are some of your initial thoughts about the show this year. >> Well, I haven't had a lot of time to visit the whole show yet, it's only opening day. (laughs) I think that over the last 20 years, of even attending these events, it's been heavily focused on kind of cameras and the backend production technology. And over the last several years, we've seen cloud technology, software driven, IP, interaction take place. Even with the thematic change of it being M.E.T., that's clearly coalescing even more. It's no longer a this is a thing that's coming. It's here. And how do people really take advantage of that as they kind of move forward. >> I'd love to get your perspective as you were saying, you've been in the media and entertainment space for about 20 years. >> Yup. >> Around the time of Nabster. Which is like we were saying before, it's hard to believe that was 20 years ago. I'd love to just get, a high level picture of, You must have seen massive evolution in media and entertainment. Tell us a little about that, some of things that really stood out to you. Over those two decades, as milestones. >> There's clearly the ones that we all as consumers know, right. The iPods and iTunes and the advent of Netflix and Amazon Video and things of that nature. And I think those are the very tangible ones. From behind the scenes, I think it's the challenges that the businesses had to go through, right. How do you actually deal with rights problems that are global in nature, right. You suddenly have a world that's portable. You suddenly have problems where I downloaded something or I want to consume a piece of content that I really enjoy, I get on a plane and I'm suddenly in a territory where I no longer have the right to watch that. Those are significant challenges that have to be overcome. And it's not always just technology, right. There's huge legal issues and things like that. And so there's a real striation between what we as consumers expect to find and what the business needs to do to change to accommodate that ever growing, that consumption rate that people want. >> Absolutely. So tell us about the supply chain solutions that Sony DADC is delivering for the media and entertainment industry. >> Sure. So, we started about nine years ago, and it's not that certainly supply chain solutions aren't nine years old. And I think our perspective on it was one where we were fortunate to start with a white piece of paper, rather than transform a legacy business. And when we did that, we said what does the solution five years from now need to look like? And so we run full supply chain offerings for companies like Sony Pictures, BBC Worldwide, Village Roadshow, PlayStation, Funimation, things of that nature. And we're talking about distribution of content to roughly 15 hundred endpoints globally. So that's multiple languages, multiple versions, trying to keep all of that stuff on track. And really the way we approached the problem was, I know it sounds terrible but, really to get human out of the mix from the perspective of what's actually not good for people to do. Looking at millions of permutations of data is not really a strong suit for people. It's a good strong suit for a computer. It had up to that point in time being relegated to Excel spreadsheets and emails. And we tried to eliminate a lot of that by putting systemic decision-making in place. And that's really what's allowed us to scale at a fairly aggressive pace. >> So are we talking about artificial intelligence, machine learning? >> I wouldn't go so far as to say that. >> Okay. >> Much more rules-based engines, logic around it. So let's take an example. Maybe you have a motion picture, we'll say like a Spider-Man. Spider-Man is made and it's available in 15 countries. Each one of those countries have different compliance and rules, cultural rules. Maybe you can't show certain imagery or you can't have somebody drinking in Saudi Arabia or something like that. So now you've left, you've left customer service reps to have a conversation that a I need you to send this to all of these places. How are they suppose to know all of the possible combinations of things. Then on top of that, not just knowing it, how are they suppose to interrogate a library of millions of assets and say, oh yeah, I figured out all the different combinations of things to make that happen. And do so within the timeline, >> Right, yup. >> to hit a business goal. That worked great in the beginning, when it was, we're going to get 50 titles out. Now we deliver 60, 70, 80 thousand titles a month. Suddenly, that is no longer sustainable for a human project. You couldn't get enough people in this building to go through that much content. >> Got it. So it's really kind of rules-based. So you've got users of the Sony technology, film studios, broadcasters, music labels. Give us an example of say, on the broadcast side, about what they're looking to do with managing assets to meet consumer demand and ensure that it's with this multi-channel distribution model, they're meeting consumer demands, wherever those consumers are. >> So I think from a broadcast perspective, which even in that world, that's blending, there is no traditional broadcaster as we know it anymore, even a broadcaster has VOD services, they might have some sort of mobile provisioning, OTT. And so therein lies there challenge, right. They've put in large infrastructure over many years, They continue to reinvest in that. Along come a Netflix of Google, whomever, with global licensing, the ability to move incredibly rapidly. And so they're looking at it and and saying, how do I compete, how do I stay relevant in this space. Market share as we know, is starting to move away from the broadcast side, linear television per se. And so where we come into play is, we say, we've already got massive amount of content available, you've licensed it already. Let us make that available, let us run that infrastructure for you. Your focus should not be on, how do I make sure that the power plant stays up. But rather, how do I market, how do I differentiate, how do I create a compelling proposition to consumers, so that I can effectively compete as this grows. >> Okay, so you're really helping them to scale on ways that they would never would have been able to do on their own. >> I think we're just helping them get there sooner. It's not to say that they could never do it. I think that's a lot of ego, a lot of hubris. It's very much that we've leveraged kind of our position as Sony, as what we have done for a lot of partners in this space. And we've said, there's a reasonable way to kind of level the playing field. >> Right. >> Right. A supply chain should not be the level of differentiation, right. We don't simply say, oh well, here's a really good manufacturing supply chain, there's only one company who should use it. It should be leveraged by many, many facilities. And so we take that same view from a digital perspective. Traditionally, we've been sending content out all around the world. We've now moved to a model that says, why don't we just host it all singularly, in any format that you want. Your choice, any spec, any DRM, but it's centralized. So for one of our customers in fact, They aired something in Japan, and 24 minutes later, it's available everywhere else. >> Wow. >> That couldn't be done if I also had last mile bandwidth considerations to take into account. And we believe that that 24 minutes is sawed by about half. We think we can get that down to under 10 minutes. >> Question for you. And the speed theme, >> Umhmm. >> Has come up a number of times today, >> Sure. >> with different folks that we've talked about. If we look at a Netflix, as you have brought up for example, from an audience perspective, the audience is so empowered, and we have access to anything we wanted, whenever we want it, bing watching, streaming, we're time shifting. >> Right. >> So you think, wow, Netflix has a great advantage because they know so much about the audience. At the same time, until they started creating unique content, they couldn't really change the content. Versus on the flip side in the film industry, They haven't really historically known their audience. >> Umhmm. >> It's been more of, probably, qualitative data and decisions, at the same time, they can change content. So, do you work with the streaming services, as well as the traditional film studios. Do they have a similar challenge that can be solved by using media as a service? >> So for ones who want to use everything that we offer end to end, again, that level playing field, we give everybody visibility. We believe data transparency is pretty important. We recognize that people hold on to data as kind of the the keys to the kingdom at this point. Certainly Netflix does and they're leveraging it quite well, right. It's hard to find fault with what they're doing from a business perspective. At the same time, as a consumer, you really don't want to have to be potentially loyal to a particular brand, right. That's not how capitalism works, but that's a different problem. But people who run on our platform, we think that there is a good balance. And both sides should have visibility to a lot of that data because it should help each other. They should really, a rising tide should float all boats, and not just create this imbalance. Because it becomes difficult to amortize costs if there's one and only one solution in the market. And that's really how we try and approach that problem. >> So in terms of, what kind of volume of content are we talking about here? >> So we store today, just over 20 petabytes of content, roughly a million hours worth of. This is premium content, so this is not user generated. This is not like youTube clips of somebody's cat. There's probably a couple. There's probably a couple in there. >> (Lisa laughs) >> No grumpy cat in there? >> There might be a few in there but that's not primarily what's what it is. We're talking about high end premium content. And in about 23 languages. So the variations that we have are very high. Now, a lot of times, people will say well, it's easy to get to a million hours because people do bad data. And so they'll store something, they'll store something like Spider-Man with a hypen in the middle or a space or all together. We're actually very, very focused on not having that. So these are all unique assets. So it's a very large library when you look on it on a global scale. >> So how can a a linear network versus a streaming network access a million hours of content. >> We actually don't differentiate between a linear and a streaming network. Because at the end of the day, we're a complete IP solution. The ability to uplink through satellite is fine, it's just another method of transport. But really all they do is, they come to us with their licenses and then we provision the assets for them in their specifications. And we make it available to them anywhere. It's pretty straight forward. We try and take a lot of the heavy lifting off their plate, reduce their infrastructure costs, reduce the team sizes from a scaling perspective so they don't have to grow so much. We really and try to flat rate a lot of this to make it easy and predictable. >> Fantastic. Last question since we're running out of time here. >> Sure. >> I know that you guys have really migrated the media supply chain to the cloud, going all in with AWS. You had mentioned that that had started about a year ago. Tell us about what you're doing with AWS and how has that influenced the genesis of media as a service? >> So I think what I should tell you first is that, when I went to the team to talk about this, I borrowed a line from The Hunt for Red October, where they said Cortez reached a new world and burned his new ship so that his men could not go back. (Lisa laughs) >> We got rid of our data centers first and then told the team we're going AWS. So there was no going back. We were making this move, there wasn't going to be hesitation and an all in model is the only model that worked for us. They hybrid model is just not cost-effective. We had to embrace something that was future proof and seemed like the right one. Where we've benefited from it is, clearly, there is economic advantages. But some of the other advantages, are like what I was talking about before, 24 minute time from receipt to availability everywhere, would have been unthinkable in a completely contained environment, where I had to have huge lead time for scalability. I had to know in advance that I would need more storage or more transporting capacity or more bandwidth. I no longer need to have that level of information upfront. I live in a world of unpredictability. People come in with requests all the time, that I didn't know an hour ago was going to be asked for. I'm finally in a position to be able to offer a solution to all of them that says, go ahead, do whatever you like, our system will manage it and we have confidence in the AWS infrastructure to be able to support that. >> Well sounds like a fantastic partnership that's going to be-- >> It's very good, we're very happy with it. >> Really enabling a lot of, more content creation, more uses of this content in the future. >> And we really want to see that. We want to see people create differentiated solutions for consumers without having to worry about how the sausage gets made. >> Exactly. Nobody wants to know that. >> Nobody wants to know that. (Lisa laughs) >> Well Andy, thank you so much for joining us on the Cube. >> Thank you. >> And sharing your insight. I know you just got to the show not too long ago so we wish you and your feet healthy next few days. >> Thank you very much. >> And we look forward to seeing you back on the Cube sometime soon. >> I appreciate it. Look forward to being with you. >> Alright, we want to thank you for watching. Again, Lisa Martin, live at NAB in Las Vegas. Stick around, we'll be right back. (techno music)