(upbeat music) >> We are back, approaching the finish line here at Supercomputing 22, our last interview of the day, our last interview of the show. And I have to say Dave Nicholson, my co-host, My name is Paul Gillin. I've been attending trade shows for 40 years Dave, I've never been to one like this. The type of people who are here, the type of problems they're solving, what they talk about, the trade shows are typically, they're so speeds and feeds. They're so financial, they're so ROI, they all sound the same after a while. This is truly a different event. Do you get that sense? >> A hundred percent. Now, I've been attending trade shows for 10 years since I was 19, in other words, so I don't have necessarily your depth. No, but seriously, Paul, totally, completely, completely different than any other conference. First of all, there's the absolute allure of looking at the latest and greatest, coolest stuff. I mean, when you have NASA lecturing on things when you have Lawrence Livermore Labs that we're going to be talking to here in a second it's a completely different story. You have all of the academics you have students who are in competition and also interviewing with organizations. It's phenomenal. I've had chills a lot this week. >> And I guess our last two guests sort of represent that cross section. Armando Acosta, director of HPC Solutions, High Performance Solutions at Dell. And Matt Leininger, who is the HPC Strategist at Lawrence Livermore National Laboratory. Now, there is perhaps, I don't know you can correct me on this, but perhaps no institution in the world that uses more computing cycles than Lawrence Livermore National Laboratory and is always on the leading edge of what's going on in Supercomputing. And so we want to talk to both of you about that. Thank you. Thank you for joining us today. >> Sure, glad to be here. >> For having us. >> Let's start with you, Armando. Well, let's talk about the juxtaposition of the two of you. I would not have thought of LLNL as being a Dell reference account in the past. Tell us about the background of your relationship and what you're providing to the laboratory. >> Yeah, so we're really excited to be working with Lawrence Livermore, working with Matt. But actually this process started about two years ago. So we started looking at essentially what was coming down the pipeline. You know, what were the customer requirements. What did we need in order to make Matt successful. And so the beauty of this project is that we've been talking about this for two years, and now it's finally coming to fruition. And now we're actually delivering systems and delivering racks of systems. But what I really appreciate is Matt coming to us, us working together for two years and really trying to understand what are the requirements, what's the schedule, what do we need to hit in order to make them successful >> At Lawrence Livermore, what drives your computing requirements I guess? You're working on some very, very big problems but a lot of very complex problems. How do you decide what you need to procure to address them? >> Well, that's a difficult challenge. I mean, our mission is a national security mission dealing with making sure that we do our part to provide the high performance computing capabilities to the US Department of Energy's National Nuclear Security Administration. We do that through the Advanced Simulation computing program. Its goal is to provide that computing power to make sure that the US nuclear rep of the stockpile is safe, secure, and effective. So how we go about doing that? There's a lot of work involved. We have multiple platform lines that we accomplish that goal with. One of them is the advanced technology systems. Those are the ones you've heard about a lot, they're pushing towards exit scale, the GPU technologies incorporated into those. We also have a second line, a platform line, called the Commodity Technology Systems. That's where right now we're partnering with Dell on the latest generation of those. Those systems are a little more conservative, they're right now CPU only driven but they're also intended to be the everyday work horses. So those are the first systems our users get on. It's very easy for them to get their applications up and running. They're the first things they use usually on a day to day basis. They run a lot of small to medium size jobs that you need to do to figure out how to most effectively use what workloads you need to move to the even larger systems to accomplish our mission goals. >> The workhorses. >> Yeah. >> What have you seen here these last few days of the show, what excites you? What are the most interesting things you've seen? >> There's all kinds of things that are interesting. Probably most interesting ones I can't talk about in public, unfortunately, 'cause of NDA agreements, of course. But it's always exciting to be here at Supercomputing. It's always exciting to see the products that we've been working with industry and co-designing with them on for, you know, several years before the public actually sees them. That's always an exciting part of the conference as well specifically with CTS-2, it's exciting. As was mentioned before, I've been working with Dell for nearly two years on this, but the systems first started being delivered this past August. And so we're just taking the initial deliveries of those. We've deployed, you know, roughly about 1600 nodes now but that'll ramp up to over 6,000 nodes over the next three or four months. >> So how does this work intersect with Sandia and Los Alamos? Explain to us the relationship there. >> Right, so those three laboratories are the laboratories under the National Nuclear Security Administration. We partner together on CTS. So the architectures, as you were asking, how do we define these things, it's the labs coming together. Those three laboratories we define what we need for that architecture. We have a joint procurement that is run out of Livermore but then the systems are deployed at all three laboratories. And then they serve the programs that I mentioned for each laboratory as well. >> I've worked in this space for a very long time you know I've worked with agencies where the closest I got to anything they were actually doing was the sort of guest suite outside the secure area. And sometimes there are challenges when you're communicating, it's like you have a partner like Dell who has all of these things to offer, all of these ideas. You have requirements, but maybe you can't share 100% of what you need to do. How do you navigate that? Who makes the decision about what can be revealed in these conversations? You talk about NDA in terms of what's been shared with you, you may be limited in terms of what you can share with vendors. Does that cause inefficiency? >> To some degree. I mean, we do a good job within the NSA of understanding what our applications need and then mapping that to technical requirements that we can talk about with vendors. We also have kind of in between that we've done this for many years. A recent example is of course with the exit scale computing program and some things it's doing creating proxy apps or mini apps that are smaller versions of some of the things that we are important to us. Some application areas are important to us, hydrodynamics, material science, things like that. And so we can collaborate with vendors on those proxy apps to co-design systems and tweak the architectures. In fact, we've done a little bit that with CTS-2, not as much in CTS as maybe in the ATS platforms but that kind of general idea of how we collaborate through these proxy applications is something we've used across platforms. >> Now is Dell one of your co-design partners? >> In CTS-2 absolutely, yep. >> And how, what aspects of CTS-2 are you working on with Dell? >> Well, the architecture itself was the first, you know thing we worked with them on, we had a procurement come out, you know they bid an architecture on that. We had worked with them, you know but previously on our requirements, understanding what our requirements are. But that architecture today is based on the fourth generation Intel Xeon that you've heard a lot about at the conference. We are one of the first customers to get those systems in. All the systems are interconnected together with the Cornell Network's Omni-Path Network that we've used before and are very excited about as well. And we build up from there. The systems get integrated in by the operations teams at the laboratory. They get integrated into our production computing environment. Dell is really responsible, you know for designing these systems and delivering to the laboratories. The laboratories then work with Dell. We have a software stack that we provide on top of that called TOSS, for Tri-Lab Operating System. It's based on Redhead Enterprise Linux. But the goal there is that it allows us, a common user environment, a common simulation environment across not only CTS-2, but maybe older systems we have and even the larger systems that we'll be deploying as well. So from a user perspective they see a common user interface, a common environment across all the different platforms that they use at Livermore and the other laboratories. >> And Armando, what does Dell get out of the co-design arrangement with the lab? >> Well, we get to make sure that they're successful. But the other big thing that we want to do, is typically when you think about Dell and HPC, a lot of people don't make that connection together. And so what we're trying to do is make sure that, you know they know that, hey, whether you're a work group customer at the smallest end or a super computer customer at the highest end, Dell wants to make sure that we have the right setup portfolio to match any needs across this. But what we were really excited about this, this is kind of our, you know big CTS-2 first thing we've done together. And so, you know, hopefully this has been successful. We've made Matt happy and we look forward to the future what we can do with bigger and bigger things. >> So will the labs be okay with Dell coming up with a marketing campaign that said something like, "We can't confirm that alien technology is being reverse engineered." >> Yeah, that would fly. >> I mean that would be right, right? And I have to ask you the question directly and the way you can answer it is by smiling like you're thinking, what a stupid question. Are you reverse engineering alien technology at the labs? >> Yeah, you'd have to suck the PR office. >> Okay, okay. (all laughing) >> Good answer. >> No, but it is fascinating because to a degree it's like you could say, yeah, we're working together but if you really want to dig into it, it's like, "Well I kind of can't tell you exactly how some of this stuff is." Do you consider anything that you do from a technology perspective, not what you're doing with it, but the actual stack, do you try to design proprietary things into the stack or do you say, "No, no, no, we're going to go with standards and then what we do with it is proprietary and secret."? >> Yeah, it's more the latter. >> Is the latter? Yeah, yeah, yeah. So you're not going to try to reverse engineer the industry? >> No, no. We want the solutions that we develop to enhance the industry to be able to apply to a broader market so that we can, you know, gain from the volume of that market, the lower cost that they would enable, right? If we go off and develop more and more customized solutions that can be extraordinarily expensive. And so we we're really looking to leverage the wider market, but do what we can to influence that, to develop key technologies that we and others need that can enable us in the high forms computing space. >> We were talking with Satish Iyer from Dell earlier about validated designs, Dell's reference designs for for pharma and for manufacturing, in HPC are you seeing that HPC, Armando, and is coming together traditionally and more of an academic research discipline beginning to come together with commercial applications? And are these two markets beginning to blend? >> Yeah, I mean so here's what's happening, is you have this convergence of HPC, AI and data analytics. And so when you have that combination of those three workloads they're applicable across many vertical markets, right? Whether it's financial services, whether it's life science, government and research. But what's interesting, and Matt won't brag about, but a lot of stuff that happens in the DoE labs trickles down to the enterprise space, trickles down to the commercial space because these guys know how to do it at scale, they know how to do it efficiently and they know how to hit the mark. And so a lot of customers say, "Hey we want what CTS-2 does," right? And so it's very interesting. The way I love it is their process the way they do the RFP process. Matt talked about the benchmarks and helping us understand, hey here's kind of the mark you have to hit. And then at the same time, you know if we make them successful then obviously it's better for all of us, right? You know, I want to secure nuclear stock pile so I hope everybody else does as well. >> The software stack you mentioned, I think Tia? >> TOSS. >> TOSS. >> Yeah. >> How did that come about? Why did you feel the need to develop your own software stack? >> It originated back, you know, even 20 years ago when we first started building Linux clusters when that was a crazy idea. Livermore and other laboratories were really the first to start doing that and then push them to larger and larger scales. And it was key to have Linux running on that at the time. And so we had the. >> So 20 years ago you knew you wanted to run on Linux? >> Was 20 years ago, yeah, yeah. And we started doing that but we needed a way to have a version of Linux that we could partner with someone on that would do, you know, the support, you know, just like you get from an EoS vendor, right? Security support and other things. But then layer on top of that, all the HPC stuff you need either to run the system, to set up the system, to support our user base. And that evolved into to TOSS which is the Tri-Lab Operating System. Now it's based on the latest version of Redhead Enterprise Linux, as I mentioned before, with all the other HPC magic, so to speak and all that HPC magic is open source things. It's not stuff, it may be things that we develop but it's nothing closed source. So all that's there we run it across all these different environments as I mentioned before. And it really originated back in the early days of, you know, Beowulf clusters, Linux clusters, as just needing something that we can use to run on multiple systems and start creating that common environment at Livermore and then eventually the other laboratories. >> How is a company like Dell, able to benefit from the open source work that's coming out of the labs? >> Well, when you look at the open source, I mean open source is good for everybody, right? Because if you make a open source tool available then people start essentially using that tool. And so if we can make that open source tool more robust and get more people using it, it gets more enterprise ready. And so with that, you know, we're all about open source we're all about standards and really about raising all boats 'cause that's what open source is all about. >> And with that, we are out of time. This is our 28th interview of SC22 and you're taking us out on a high note. Armando Acosta, director of HPC Solutions at Dell. Matt Leininger, HPC Strategist, Lawrence Livermore National Laboratories. Great discussion. Hopefully it was a good show for you. Fascinating show for us and thanks for being with us today. >> Thank you very much. >> Thank you for having us >> Dave it's been a pleasure. >> Absolutely. >> Hope we'll be back next year. >> Can't believe, went by fast. Absolutely at SC23. >> We hope you'll be back next year. This is Paul Gillin. That's a wrap, with Dave Nicholson for theCUBE. See here in next time. (soft upbear music)

>>Mm. Every CEO is trying to get hybrid, right? Most people, they've been working remotely for the better part of two years now, and we've spent a lot of time and thought on how to accommodate remote workers and providing tools to make them feel connected and more productive. We've also built remote and hybrid models into our hiring ethos, making it a feature, not a drawback. But what about the underlying infrastructure that powers hybrid work? How is that evolving to be as flexible, scalable and cost effective with the lowest latency possible? Recent survey data from Enterprise Technology Research shows that 56% of executives believe productivity continues to improve, with only 14% citing recent declines in productivity. 26% say it's holding steady. The question is, how do we maintain those positives and minimise the negatives? And what role does the network and underlying infrastructure play in evolving new work models? Welcome to the network powering hybrid work on the Cube, made possible by Cisco. My name is Dave Volonte, and I'll be your host today. In this programme, you're gonna hear from experts that are going to discuss and introduce new innovations that are specifically designed to energise and support hybrid work. My first guest is Lawrence Wang, who's the vice president of product management at Cisco. And we're going to dig into WiFi six e and what it all means to the future of work. Lawrence, welcome. Good to see you. >>Hey, great to be here. Dave. Thanks for having me. I'm excited to be here today. >>You bet. Okay. My first big question is what's the big rush? It feels like we were just talking about the shift from y 55 to WiFi six just a few years ago. What's going on there? >>Yeah. I mean, you're right, right. We assets at Cisco. We introduced our first WiFi six access points back in 2019, and one of the things that we've seen is a tremendous rate of adoption moving from WiFi five to WiFi six over the past couple of years. In fact, it's one of our fastest transitions that we've seen between wireless standards. And a lot of the drivers, you know, for that were really just about, you know, making sure that there's better WiFi experiences for, you know, people in the office making sure that they can support. You know more of that. Have you got a set of clients? Reduce the amount of congestion. And over time, what we've seen is that migration has been tremendous. But it also means that we're starting to reach that capacity where five gigahertz is starting to become more crowded and so many of our customers are looking at. Well, what can I actually do to continue to expand? You know that you know that traffic, the number of lanes that I can actually support for wireless traffic And for many of them, they're looking to WiFi succeed as the answer to help them do that simply because six gigahertz as part of that standard introduces a whole new spectrum or a whole new highway that we can get client devices as long as >>well, So it sounds like you're thinking about a different role for offices and campuses going forward. So what your listeners expect to see kind of in the in the near term and the midterm and even a long term near term when they get back into the office and in the long term, how do you see this playing out? >>Yeah, that's an interesting question, right When you think about this context of hybrid work, work is not a place that you go to, but it's really a place that you could be where ultimately you are trying to get work done. It really is reporting that quality of experience, no matter where you choose to work from. And, yes, while the campus is going to evolve and play a different role, it is a critical part of that hybrid work future. And the way I see it here is that the role of the campus is going to change over time. It's not going to be the same that we saw prior to two years ago, and I think for many of our customers about what does it mean to invest in that infrastructure for us to continue to adapt, to support the ways that their employees that are expected or want to work? And a big part of that is investing in infrastructure to support new ways of working? >>Well, you know, Lawrence, I mean, I've personally been lucky because we go to studio and I've been able to come into the office since the pandemic started, but I know a lot of people. They're really excited to get back, to work in person and face to face events and the like. And I know others that say, You know what? I'm moving and I'm always gonna work remotely. I'll never work for another company that forces me to go in the office again. So this sounds like a tall order for it organisations to accommodate that diversity. How do you think they will be able to plan for and manage all this new complexity? >>Yeah. I mean, I think the reality is, you know, talent. It doesn't know any zip codes, right? And I think one of the boons of being able to support a more distributed workforce is to be able to bring in great talent no matter where they're based out of. And I think for I t team. So I think the interesting thing will be what are the drivers to bring people back into the office right? There has to be a purpose that's more meaningful than simply It's a place that I go to every single day. You know, what are the tools and applications I bring in to help support collaboration, And I think important part of making this a great experience in the context of hybrid work is that you do have to make the office a meaningful place for employees to gather, but also making sure that as you connect people around the world as part of the global employee workforce that they still have an equitable experience. So for it teams, it is about thinking about how do I actually manage this infrastructure that's more distributed? But I start to invest in my central campuses and at the same time making sure that I have great quality experiences for everyone. Unified security policies, visibility across all the clients and applications. But there's also increasing pressure from their its core constituency. We know that people are asking more of it. They want them to support you, use cases like safe return office that they want to help you contributor to global corporate initiatives like driving towards zero greenhouse gas emissions. So any number of these activities or initiatives is putting more pressure on teams. >>Interesting. I mean, so I gotta ask you, please don't hate me for this question. But was this just luck on Cisco's part that you got solutions ready for this sort of hybrid work model so quickly. In other words, was it something that you were maybe planning that was going to take years for the market to be ready for And it just got compressed because of the pandemic? Or was this architecture that allows you to be flexible? How did you land here and what appears to be a pretty strong position? >>Yeah, I mean, at Cisco, I think one of the things that we think about is, you know, it's always amazing when you look back at something and then you write the story. But I think if we're being honest with ourselves, if you look at what happened from where we were two years ago to where we are today, including our competitors and customers, I think that no one could have predicted the world that we're operating and living in. And so for us, the question becomes, How did we help our customers support this transition? And ultimately it's about investing in architectures and platforms that are flexible, that allows our customers support use cases that they were thinking of, as well as ones that they never anticipated, and I think that's really the exciting thing about what we've been doing here as part of our hybrid work investments now areas that, you know, I think we double down on and in some ways accelerated because of this. When I think about you know what our customers care about when they start bringing people back into the office. It is about some of these emerging use cases, whether it's more dynamic, way finding, be able to understand the density or the air quality of a given environment. And these are some of the technologies that we have embedded in some of our new, you know, WiFi 60 access points along with our management infrastructure era. So I think that it gives our customers and partners a lot more flexibility than what they had before to really adapt to the changing needs of today and even beyond. >>Well, that's something we've certainly learned throughout the pandemic. Is the ability to be flexible is fundamental? I gotta ask you, what's your preferred mode of work? You go back into the office, you're gonna stay remote. >>Great question. You know, I have come to appreciate, you know, working from home. You know, over the past couple years, got to spend a little more time with my kids at lunch. But I will say I am looking forward to the day when I can have the voice of being back in the office a few days a week as well as I continue to be remote as well as continued to visit my customers and partners all over this great country in the world. So looking forward to that, >>so you're a true hybrid. I guess I'm a hybrid, too. I like being in the office, but I'm travelling a lot when the world returns to the new abnormal anyway. Large. Thanks so much for kicking off the programme with me. Now in a minute, we're going to dig into the core of the network and understand the role it plays in supporting new and flexible work models. You're watching the network powering hybrid work made possible by Cisco on the Cube, your leader in global enterprise tech coverage. Mhm. Yeah,

good thumbnail for your video all right thank you all for the patience we are now ready to start filming did you want to take a picture alex yes i do lawrence let me get myself prepared for that okay lawrence we're going to take a screenshot of your input for a thumbnail asset if you can look at the screen and give me a big smile in three two one gotcha great excellent okay and with that i am all good to go and you are lawrence we'll do a five count i'll count you down 543 silent 2-1 and then just follow my lead okay sounds great all right leonard we good okay you're off here we go on dave in five four three every ceo is trying to get hybrid right most people they've been working remotely for the better part of two years now and we've spent a lot of time and thought on how to accommodate remote workers and providing tools to make them feel connected and more productive we've also built remote and hybrid models into our hiring ethos making it a feature not a drawback but what about the underlying infrastructure that powers hybrid work how is that evolving to be as flexible scalable and cost effective with the lowest latency possible recent survey data from enterprise technology research shows that 56 percent of executives believe productivity continues to improve with only 14 percent citing recent declines in productivity 26 percent say it's holding steady the question is how do we maintain those positives and minimize the negatives and what role does the network and underlying infrastructure play in evolving new work models welcome to the network powering hybrid work on the cube made possible by cisco my name is dave vellante and i'll be your host today and in this program you're going to hear from experts that are going to discuss and introduce new innovations that are specifically designed to energize and support hybrid work my first guest is lawrence wang who's the vice president of product management at cisco and we're going to dig into wi-fi 6e and what it all means to the future of work lawrence welcome good to see you hey great to be here dave thanks for having me i'm excited to be here today yeah you bet okay my my first big question is you know what's the big rush it feels like we were just talking about the shift from wi-fi you know five to wi-fi six just a few years ago what's going on there yeah i mean you're right right we as since at cisco we introduced our first wi-fi six access points back in 2019 and one of the things that we've seen is a tremendous rate of adoption moving from wi-fi five to wi-fi six over the past couple of years in fact it's one of our fastest transitions that we've seen between wireless standards and a lot of the drivers you know for that we're really just about you know making sure that there's better wi-fi experiences for you know uh people in the office making sure that they can support uh you know more of that you know set of clients reduce the amount of congestion in our time what we've seen is that migration has been tremendous but it also means that you know we're starting to reach that capacity where you know five gigahertz is starting to become more crowded and so many of our customers are looking at well what can i actually do to continue to expand you know that you know that traffic the number of lanes that i can actually support for wireless traffic and for many of them they're looking to wi-fi 6e as the answer to help them do that simply because six gigahertz as part of that standard introduces a whole new spectrum or a whole new highway that we can get client devices on well so it sounds like you're thinking about a different role for offices and campuses going forward so what should listeners expect to see kind of in the in the near term in the midterm and even the long term near term when they get back into the office and in the long term how do you see this playing out yeah i mean that's an interesting question right when you think about you know this context of hybrid work you know work is not a place that you go to but it's really a place that uh you could be where ultimately you are trying to get work done uh it really really is supporting you know that you know quality of experience no matter where you choose to work from and yes yeah while the campus is going to evolve and play a different role it is a critical part of that hybrid work future and the way i see it here is that you know the role of the campus is going to change over time it's not going to be the same that we saw prior to uh you know two years ago and i think for many of our customers about you know what does it mean to invest in that infrastructure for us to continue to adapt to support you know the ways that you know their employees are expected or want to work and a big part of that is investing in infrastructure to support your new ways of working well you know lawrence i mean i've personally been lucky because we go to studio and i've been able to come into the office since the pandemic started but i know a lot of people they're really excited to get back to work in person and face-to-face events and the like and i know others that say you know what i'm moving and i'm always going to remo work remotely i'll never work for another company that forces me to go in the office again so this sounds like a tall order for it organizations to accommodate that diversity how do you think they will be able to plan for and manage all this new complexity yeah i mean i think the reality is uh you know talent it doesn't know any zip codes right and i think one of the boons of you know being able to support a more distributed workforce is to be able to bring in great talent no matter where they're based out of and i think for it teams i think the interesting thing will be you know what are the drivers to bring people back into the office right there has to be a purpose uh that's more meaningful than simply it's a place that i go to every single day you know what are the you know tools and you know applications i bring in to help support collaboration and i think an important part of you know making this a great experience in the context of hybrid work is that you do have to make the office a meaningful place for employees to gather but also making sure that as you connect people around the world as part of your global employee workforce that they still have an equitable experience so for iet teams it is about you know thinking about how do i actually manage this infrastructure that's more distributed but i still have to invest in my you know central campuses and at the same time making sure that i have great quality experiences for everyone unified security policies you know visibility across all the clients and applications but there's also increasing pressure from their it's core constituency we know that people are asking more of it they want them to support new use cases like safe return office that they want it to help you a contributor to you know global corporate initiatives like driving towards uh you know zero uh greenhouse gas emissions so any number of these activities or initiatives is putting more pressure on ig teams yeah interesting i mean so i gotta ask you please don't hate me for this question but was this just luck on cisco's part that you got solutions ready for this sort of hybrid work model so quickly in other words was it something that you were maybe planning that was going to take years for the market to be ready for and it just got compressed because of the pandemic or is this architecture that allows you to be flexible how did you land here in what appears to be a pretty strong position yeah i mean at cisco i think one of the things that you know we think about is you know it's always amazing when you look back at something and then you write the story but i i think if we're being honest with ourselves if you look at what happened from where we were two years ago to where we are today including our competitors and customers i think that no one could have predicted the world that we're operating and living in and so for us the question becomes how did we help our customers support this transition and ultimately it's about investing in architectures and platforms that are flexible that allows our customers support you know use cases that they were thinking of as well as ones that they never anticipated and i think that's really the exciting thing about you know what we've been doing here as part of our hybrid work investments now areas that you know i think you know we double down on and you know in some ways accelerated because of this when i think about you know what our customers care about when they start bringing people back into the office it is about some of these emerging use cases whether it's you know more dynamic way finding being able to understand the density or the air quality of a given environment and these are some of the technologies that we've embedded in some of our you know new uh you know wi-fi 60 access points along with you know our management infrastructure here so i think that it gives our customers and partners a lot more flexibility than what you know they had before to really adapt to the changing needs of today and even beyond well that's something we've certainly learned throughout the pandemic is is the ability to be flexible is fundamental i got to ask you what's your preferred mode of work you going back into the office are you going to stay remote great question you know i have come to appreciate uh you know working from home you know over uh you know the past couple years got to spend a little more time with my kids at lunch but i will say i am looking forward to the day when i can have the choice of being back in the office a few days a week as well as continue to be remote as well as continue to visit my customers and partners uh you know all over this great country in the world so looking forward to that yeah so so you're a true hybrid i guess i'm a hybrid too i like being in the office but i'm traveling a lot when the world returns to the new abnormal anyway lawrence thanks so much for kicking off the program with me now in a minute we're going to dig into the core of the network and understand the role it plays in supporting new and flexible work models you're watching the network powering hybrid work made possible by cisco on thecube your leader in global enterprise tech coverage

>> live from Boston, Massachusetts. It's the queue covering your red. Have some twenty nineteen brought to you by bread. Welcome back a few, but our way Our red have some twenty nineteen >> center along with Sue Mittleman. I'm John Walls were now joined by Robin Goldstone, who's HBC solution architect at the Lawrence Livermore National Laboratory. Hello, Robin >> Harrier. Good to see you. I >> saw you on the Keystone States this morning. Fascinating presentation, I thought. First off for the viewers at home who might not be too familiar with the laboratory If you could please just give it that thirty thousand foot level of just what kind of national security work you're involved with. >> Sure. So yes, indeed. We are a national security lab. And you know, first and foremost, our mission is assuring the safety, security reliability of our nuclear weapons stockpile. And there's a lot to that mission. But we also have broader national security mission. We work on counterterrorism and nonproliferation, a lot of of cyber security kinds of things. And but even just general science. We're doing things with precision medicine and and just all all sorts >> of interesting technology. Fascinating >> Es eso, Robin, You know so much and i t you know, the buzzword. The vast months years has been scaled on. We talk about what public loud people are doing. It's labs like yours have been challenged. Challenge with scale in many other ways, especially performance is something that you know, usually at the forefront of where things are you talked about in the keynote this morning. Sierra is the latest generation supercomputer number two, you know, supercomputer. So you know, I don't know how many people understand the petaflop one hundred twenty five flops and the like, but tell us a little bit about, you know, kind of the why and the what of that, >> right? So So Sierra's a supercomputer. And what's unique about these systems is that we're solving. There's lots of systems that network together. Maybe you're bigger number of servers than us, but we're doing scientific simulation, and that kind of computing requires a level of parallelism and very tightly coupled. So all the servers are running a piece of the problem. They all have to sort of operate together. If any one of them is running slow, it makes the whole thing goes slow. So it's really this tightly couple nature of super computers that make things really challenging. You know, we talked about performance. If if one servers just running slow for some reason, you know everything else is going to be affected by that. So we really do care about performance. And we really do care about just every little piece of the hardware you know, performing as it should. So So I >> think in national security, nuclear stockpiles. Um I mean, there is nothing more important, obviously, than the safety and security of the American people were at the center of that. Right? You're open source, right? You know, how does that work? How does that? Because as much trust and faith and confidence we have in the open source community. This is an extremely important responsibility that's being consigned more less to this open source community. >> Sure. You know, at first, people do have that feeling that we should be running some secret sauce. I mean, our applications themselves or secret. But when it comes to the system software and all the software around the applications, I mean, open source makes perfect sense. I mean, we started out running really closed source solutions in some cases, the perp. The hardware itself was really proprietary. And, of course, the vendors who made the hardware proprietary. They wanted their software to be proprietary. But I think most people can resonate when you buy a piece of software and the vendor tells you it's it's great. It's going to do everything you needed to do and trust us, right? Okay, But at our scale, it often doesn't work the way it's It's supposed to work. They've never tested it. Our skill. And when it breaks, now they have to fix. They're the only ones that can fix it. And in some cases we found it wasn't in the vendors decided. You know what? No one else has one quite like yours. And you know, it's a lot of work to make it work for you. So we're just not going to fix and you can't wait, right? And so open source is just the opposite of that, right? I mean, we have all that visibility in that software. If it doesn't work for our needs, we can make it work for our needs, and then we can give it back to the community. Because even though people are doing things that the scale that we are today, Ah, lot of the things that we're doing really do trickle down and can be used by a lot of other people. >> But it's something really important because, as you said, you used to be and I was like, OK, the Cray supercomputer is what we know, You know, let's use proprietary interfaces and I need the highest speed and therefore it's not the general purpose stuff. You moved X eighty six. Lennox is something that's been in the shower computers. Why? But it's a finely tuned version there. Let's get you know, the duct tape and baling wire. And don't breathe on it once you get it running. You're running well today and you talk a little bit about the journey with Roland. You know, now on the Super Computers, >> right? So again, there's always been this sort of proprietary, really high end supercomputing. But about in the late nineteen nineties, early two thousand, that's when we started building these these commodity clusters. You know, at the time, I think Beta Wolf was the terminology for that. But, you know, basically looking at how we could take these basic off the shelf servers and make them work for our applications and trying to take advantage of a CZ much commodity technologies we can, because we didn't want to re invent anything. We want to use as much as possible. And so we've really written that curve. And initially it was just red hat. Lennox. There was no relative time, but then when we started getting into the newer architectures going from Mexico six. Taxi, six, sixty for and Itanium, you know the support just wasn't there in basic red hat and again, even though it's open source and we could do everything ourselves, we don't want to do everything ourselves. I mean, having an organization having this Enterprise edition of Red Hat having a company stand behind it. The software is still open. Source. We can look at the source code. We can modify it if we want, But you know what at the end of the day, were happy to hand over some of our challenge is to Red Hat and and let them do what they do best. They have great, you know, reach into the into the colonel community. They can get things done that we can't necessarily get done. So it's a great relationship. >> Yes. So that that last mile getting it on Sierra there. Is that the first time on one kind of the big showcase your computer? >> Sure. And part of the reason for that is because those big computers themselves are basically now mostly commodity. I mean, again, you talked about a Cray, Some really exotic architecture. I mean, Sierra is a collection of Lennox servers. Now, in this case, they're running the power architecture instead of X eighty six. So Red hat did a lot of work with IBM to make sure that that power was was fully supported in the rail stack. But so, you know, again that the service themselves somewhat commodity were running and video GP use those air widely used everywhere. Obviously big deal for machine learning and stuff that the main the biggest proprietary component we're still dealing was is thie interconnect. So, you know, I mentioned these clusters have to be really tightly coupled. They that performance has to be really superior and most importantly, the latent see right, they have to be super low late and see an ethernet just doesn't cut it >> So you run Infinite Band today. I'm assuming we're >> running infinite band on melon oxen finna ban on Sierra on some of our commodity clusters. We run melon ox on other ones. We run intel. Omni Path was just another flavor of of infinite band. You know, if we could use it, if we could use Ethernet, we would, because again, we would get all the benefit in the leverage of what everybody else is doing, but just just hasn't hasn't quite been able to meet our needs in that >> area now, uh, find recalled the history lesson. We got a bit from me this morning. The laboratory has been around since the early fifties, born of the Cold War. And so obviously open source was, you know? Yeah, right, you know, went well. What about your evolution to open source? I mean, ahs. This has taken hold. Now, there had to be a tipping point at some point that converted and made the laboratory believers. But if you can, can you go back to that process? And was it of was it a big moment for you big time? Or was it just a kind of a steady migration? tour. >> Well, it's interesting if you go way back. We actually wrote the operating systems for those early Cray computers. We wrote those operating systems in house because there really was no operating system that will work for us. So we've been software developers for a long time. We've been system software developers, but at that time it was all proprietary in closed source. So we know how to do that stuff. The reason I think really what happened was when these commodity clusters came along when we showed that we could build a, you know, a cluster that could perform well for our applications on that commodity hardware. We started with Red Hat, but we had to add some things on top. We had to add the software that made a bunch of individual servers function as a cluster. So all the system management stuff the resource manager of the thing that lets a schedule jobs, batch jobs. We wrote that software, the parallel file system. Those things did not exist in the open source, and we helped to write those things, and those things took on lives of their own. So luster. It's a parallel file system that we helped develop slow, Erm, if anyone outside of HBC probably hasn't heard of it, but it's a resource manager that again is very widely popular. So the lab really saw that. You know, we got a lot of visibility by contributing this stuff to the community. And I think everybody has embracing. And we develop open source software at all different layers. This >> software, Robin, you know, I'm curious how you look at Public Cloud. So, you know, when I look at the public odd, they do a lot with government agencies. They got cloud. You know, I've talked to companies that said I could have built a super computer. Here's how long and do. But I could spend it up in minutes. And you know what I need? Is that a possibility for something of yours? I understand. Maybe not the super high performance, But where does it fit in? >> Sure, Yeah. I mean, certainly for a company that has no experience or no infrastructure. I mean, we have invested a huge amount in our data center, and we have a ton of power and cooling and floor space. We have already made that investment, you know, trying to outsource that to the cloud doesn't make sense. There are definitely things. Cloud is great. We are using Gove Cloud for things like prototyping, or someone wants a server, that some architecture, that we don't have the ability to just spin it up. You know, if we had to go and buy it, it would take six months because you know, we are the government. But be able to just spin that stuff up. It's really great for what we do. We use it for open source for building test. We use it to conferences when we want to run a tutorial and spin up a bunch of instances of, you know, Lennox and and run a tutorial. But the biggest thing is at the end of the day are our most important work. Clothes are on a classified environment, and we don't have the ability to run those workloads in the cloud. And so to do it on the open side and not be ableto leverage it on the close side, it really takes away some of the value of because we really want to make the two environments look a similar is possible leverage our staff and and everything like that. So that's where Cloud just doesn't quite fit >> in for us. You were talking about, you know, the speed of, Of of Sierra. And then also mentioning El Capitan, which is thie the next generation. You're next, You know, super unbelievably fast computer to an extent of ten X that off current speed is within the next four to five years. >> Right? That's the goal. I >> mean, what those Some numbers that is there because you put a pretty impressive array up there, >> right? So Series about one hundred twenty five PETA flops and are the big Holy Grail for high performance computing is excess scale and exit flop of performance. And so, you know, El Capitan is targeted to be, you know, one point two, maybe one point five exit flops or even Mohr again. That's peak performance. It doesn't necessarily translate into what our applications, um, I can get out of the platform. But the reason you keep sometimes I think, isn't it enough isn't one hundred twenty five five's enough, But it's never enough because any time we get another platform, people figure out how to do things with it that they've never done before. Either they're solving problems faster than they could. And so now they're able to explore a solution space much faster. Or they want to look at, you know, these air simulations of three dimensional space, and they want to be able to look at it in a more fine grain level. So again, every computer we get, we can either push a workload through ten times faster. Or we can look at a simulation. You know, that's ten times more resolved than the one that >> we could do before. So do this for made and for folks at home and take the work that you do and translate that toe. Why that exponential increase in speed will make you better. What you do in terms of decision making and processing of information, >> right? So, yeah, so the thing is, these these nuclear weapons systems are very complicated. There's multi physics. There's lots of different interactions going on, and to really understand them at the lowest level. One of the reasons that's so important now is we're maintaining a stockpile that is well beyond the life span that it was designed for. You know, these nuclear weapons, some of them were built in the fifties, the sixties and seventies. They weren't designed to last this long, right? And so now they're sort of out of their design regime, and we really have to understand their behaviour and their properties as they age. So it opens up a whole nother area, you know, that we have to be able to floor and and just some of that physics has never been explored before. So, you know, the problems get more challenging the farther we get away from the design basis of these weapons, but also were really starting to do new things like eh, I am machine learning things that weren't part of our workflow before. We're starting to incorporate machine learning in with simulation again to help explore a very large problem space and be ableto find interesting areas within a simulation to focus in on. And so that's a really exciting area. And that is also an area where, you know, GPS and >> stuff just exploded. You know, the performance levels that people are seeing on these machines? Well, we thank you for your work. It is critically important, azaz, we all realize and wonderfully fascinating at the same time. So thanks for the insights here on for your time. We appreciate that. >> All right, Thanks for >> thanking Robin Goldstone. Joining us back with more here on the Cube. You're watching our coverage live from Boston of Red Hat Summit twenty nineteen.

>> Live from Las Vegas, it's theCUBE covering the AWS Accenture Executive Summit. Brought to you by Accenture. >> Welcome back, everyone, to theCUBE's live coverage of the AWS Executive Summit, here at The Venetian. I'm your host, Rebecca Knight. We have three guests for this segment. We have Lawrence Fong, general manager, information technology at Cathay Pacific; Peter Yen, managing director, Hong Kong Accenture; and Massimo Morin, head world wide business development travel at AWS. Thank you so much, gentlemen, for coming on theCUBE. >> Thank you. >> Thank you. >> So we're going to be talking about applying blockchain to a travel rewards program at Cathay Pacific, but I want to start with you, Lawrence. Let's describe the business problem that you were trying to solve. The Asia Miles program is already, sort of a world-class program, very competitive. But it still had it's kinks. So, what were you trying to do to make it better? >> Okay, first of all, Asia Miles is a lifestyle, you know, frequent flyer loyalty program, and almost every year they're running over 460 marketing campaign a year. So, you can imagine how much work they have to do. So, from the customer point of view, they have a pin point of whatever activities of redemption or for award, all these kind of thing. It's going to take a long time for them to get their miles. So, from the customer point of view, this is not really ideal. And on the other hand, at the back office, because we're running so many marketing campaign. So, there's a lot of back office operation and lot of, where people work and all this kind of thing. So, it's also not, I think, a very good operation efficiency. So, from the customer point of view, from the back office point of view, so that's the key pinpoint we want to be solved. >> Right. So, it was tedious to operate for both the customer and for the business itself. So, why was blockchain the technology? That could solve it? >> Well, we study one of the key features, or component of blockchain, it's called 'smart contract'. And we could see the smart contract would be able to help bringing our customer and Asia Miles, and also our merchant together. So, by using blockchain, the miles, the redemption, all this will happen almost in a second. >> So, how did this work, Lawrence? I mean, in terms of getting, working together with Cathay Pacific, how did you work together to create this new program? >> Okay. Effectively, it's a very co-create process. It started with a conversation with Lawrence. We had the idea, so Lawrence was courageous enough to let us try. We did a very short, quick pilot. We proved the concept. Then we went into a very rapid development cycle, as well. And then, within weeks, we get the product done, and then we launch and go to the market. >> So, Peter, is that generally the way it goes, in terms of this co-creative process? I mean, we're hearing so much, that Accenture and AWS have these solutions that they can bring to clients, and then, is it sort of happening in the background or are you on the ground together, sort of dreaming up ways to make this better and make the technology work? >> Well, we used to call this the new way of doing things, but I think now this is the way of doing things, right? Because it is the perfect combination. The client has perfect knowledge about the business, we understand the technology, and we have enablement partners like Amazon. So, we just work together and make it happen. >> So, from Amazon, so we hear blockchain you automatically think Bitcoin. You just do. But this is actually a very different kind of use case for blockchain, and it's one that really is so pertinent. Can you talk a little, Massimo, about other uses cases that you're seeing? >> So, indeed that you are right. Blockchain has been very nebulous, and always associated to Bitcoins, but there are actually some uses cases that are much more relevant, especially in the travel industry where you complex transaction, multi-party, where you are actually going to do transparency and data integrity. For example, we had a proof of concept to to read IATA about a one ID project that allows a travel agency to register themselves with this authority and get the key, and then seamlessly doing transaction with travel providers by identifying themselves through blockchain. That allows them to actually be recognized, and you have a seamless process with the new NDC, new distribution capabilities coming along. That is going to be extremely important. This is one type. Another type is when you wanted the immutability of the data. For example, when you have planes an you want to see you getting leases, on and off lease, and you want to see all the maintenance that occur there, and you want that that doesn't change. You want to use a trusted system that is transparent, and that is not changeable. And that provide a lot of value. And the third use case that I personally like, is automatic contract. So, when, for example, you have corporate buyers, that buy travel products from a travel provider, like Cathay Pacific, and you wanted that, you buy the ticket. But when is the airline going to get the money? That reconciliation is like, with the frequent flyer miles, you want to be done as soon as possible. Other cases is, is the passengers flying around? If it doesn't fly, well, what happened to the taxes? Taxes should be actually returning back to the customer. So, with automatic contracts, you would be able actually to reconcile that behind the scene. These are use cases that are very valuable in travel industry. >> So, does this immediate reconciliation and this trust, I mean , trust is such an important, thick concept right now. What are you hearing? From both the clients' side and the provider's side. I mean, where are we? >> Yeah, that's true. I think trust is one of the key elements of, you know, doing reconciliation. So, what we are doing now is still within our legal system. So, we trust each other. But, looking forward, I think one of the key areas that blockchain will help a lot, is the entire supply chain. But, when we talk about the supply chain, there's so many stakeholder. So, building a trust, of course, of domestic holder will be a challenge. I think that's something, you know, of course the industry has to put more thought onto it. >> What are we seeing so far? So, this was implemented in April of this year. What has been the return on investments so far? >> It's phenomenal. For those marketing campaign, we're using blockchain. These new capabilities, we had a triple digit growth, in terms of our sales, and also, because we also use kind of a game to gamify the whole thing. So, we create a lot of traction in there, you know? A lot of excitement. So, the number of people and the number of customer engaged in those marketing campaigns also have more than, you know, more than double, you know, growth. >> Peter, what's most exciting to you about this process? >> The most exciting thing is that, as you heard from Lawrence, is indeed generating performance and results. And the process of co-creating a successful solution is a very rewarding experience. >> So, I mean, and then AWS is, in terms of the co-creative process, where does AWS fit into this? >> So, we are their neighbor, and I'm glad that you're able, Cathay Pacific and Accenture, as using AWS for this. So, we have standard templates, blockchain templates that actually take away all the heavy lifting of putting place to platform to found the blockchain. So, actually, the customer and the partner can focus on the business need that they have attend. And this is all open-source, so you can see how it works. And it's so transparent, that we are very glad to enable our customer to do transformative things like this. >> So, the word is out that blockchain is not just for Bitcoin anymore. So, where do we go from here? We're talking about the travel industry, but are the learnings that Cathay Pacific has had and Accenture, in terms of how applicable are they to other industries? And how are you sharing what you've learned in a collaborate, co-creative process? >> Well, all of that, in Asia Miles, now we are taking what we learned from the blockchain, we are going to apply to the cargo industry, and also apply to the airport operation. Particular, the baggage, the consideration baggage between different people, of course they're all the blockchain. >> Great. >> Actually, many clients are now talking about this Cathay Pacific case, and they have very creative ideas, how to borrow the concept and apply to their own business. So, we should see more and more application of this solution. >> And we are seeing acceleration of adoption of cloud technology throughout the travel industry, with airline, and technology providers out there. And I'm very glad that there are taught leadership, for example, from Cathay Pacific, to take this hypothetical use cases and taking the lead on showing how it is done and sharing with the industry. We are looking for those travel leaders that will help the industry to move forward. >> That's true. >> Because it's very challenging industry with very low margin, and any improvement in customer service is going to go a long way. And we are glad to be part of that. >> And is that what it is? I mean, as you said, it sort of seen, even the incremental improvement and how that can be, just, so transformational for a company's bottom line. >> Yep. >> Yes. >> Yep. Absolutely. >> Well, Massimo, Peter, Massimo, Peter, Lawrence, thank you so much for joining us on theCUBE. It's been a really fun conversation. >> Thank you. >> Thank you very much. >> I'm Rebecca Knight. We will have more of theCUBE's live coverage of the AWS Executive Summit coming up in just a little bit. (thrilling music)

>> Narrator: Live from Las Vegas it's theCUBE! Covering AWS Reinvent 2017 presented by AWS, Intel, and our ecosystem of partners. >> And we are back live here in Las Vegas. We are at the Sands as Reinvent day two wraps up. AWS here for four days and we'll be here live again tomorrow, by the way on theCUBE continuing our coverage. We're wrapping up here today saving the best for last. No doubt about that. Stu Miniman and John Walls were joined by a couple of folks from SoftwareONE. Mike Gersten, immediately to my right. Global Innovation and Strategy. Mike, good to see you, sir. >> Yeah, likewise, thanks for having us. >> And Lawrence Schwartz on the far side there. The CMO at SoftwareONE, Lawrence, good to see you. >> Pleasure to see you again. >> Tell us a little bit, first off, about not only what you do but why you're here. >> Sure, yeah. So, SoftwareONE, we're in the business of making sure that people are spending the right amount of money on their software. Not too much, and you know making sure they're not underspending either. So all that optimization to spend. We also help customer implement their technology. We're at this show because we help customers do that in a Cloud environment so obviously natural to be at AWS. We help them do that on premise as well and we find a lot of our customers here. People we've been talking to for a long time. New people as well trying to move over. So it's a great environment for us. We kind of see what's going on in the innovation side from AWS too so... >> And so Mike, what do you make of the show in general. I'm just curious about your take, two day take. We've been here a couple of days. By now it's sunk in a little bit, I would think. >> It's incredible. You know, we were here last year and there was roughly 30,000 attendees. We're here again, there's over 45,000 attendees. I walk the floor here, I see dozens of providers that I didn't see here last year. Some of them are one guy with a six foot table, who's got some pretty interesting technology. So I would say that the pace with which this ecosystem is growing isn't showing any signs of slowing down. >> One of the things we've been hearing for a while is, boy, Amazon keeps innovating but it's been adding to complexity. The Amazon catalog itself, you know, 30,000 line items there. Then you add on top of that the marketplace and I'm like I'm pretty sure it's infinite at this point. And marketplace has been, you know, a huge driver in growth. I have to expect that marketplace impacted your business quite a bit in a good way, I would think. >> Yeah, for us that's probably one of the most exciting announcements that we've heard this week is around the marketplace specifically. We have a 30 year history selling software so to see now AWS taking what they did in the online retail business and in essence doing it for software in the marketplace is a good opportunity for us to connect our global catalog to their global catalog and provide a much wider range of software options for customers. >> And Mike, I wonder if I could... Can I ask you? Explain to our audience that might not have been in the keynote, gone to a break, what is it about this announcement that is so special from Amazon? So today they have about 4,000 or a little bit over 4,000 applications that sit in the marketplace and the idea is that any customer ought to be able to go up to the marketplace and with the click of a button, procure some software, have it put into a, maybe a reserved instance or some hosted infrastructure from Amazon and then be off to the races. No configuration, no support, no installation. >> Yeah, that was my tongue in cheek "so it's an infinite marketplace." >> It's an infinite-- >> As of today, right? Lawrence, one of the things we've been kind of wrestling with the last few years is this term, multi-Cloud. We hear an update from Andy every year as to how they look at it. Of course, I think it's, "everything is everything" is Amazon >> Right, right, yeah. and of course I think they've made an announcement about everything. And we still have a couple of days left. How are customers, you know, your customers looking at that multi Cloud, what are you seeing? Give us a little insight as to... and how does SoftwareONE help? >> Yeah, what's interesting for us is because that's what we see all the time, and we were talking about this a little bit beforehand and all of the customers that we have, we have tens of thousands of customers, we don't have any real conversations where people are talking about a single Cloud that they're working with, right. They're working with multiple. Maybe they're more in one today than another, but they're kind of looking at multiple solutions. So it's part of the business of what they do. And in a lot of cases it's just another extension of what's happening, you know, on premise today or in the data center. And so they always have to think about that. So, it's a part of it. There's lots of reasons for them to kind of go into that multi Cloud environment. Some of it might be for redundancy, some of it for flexibility on contracting. Some of it is for things like GDPR where they're worried about where their data sits and some of the local requirements. So it's part of the conversations that we always have and it's good to see some of the solutions that they're doing here where they think about that and they've really thought about how different ways customers can go in there and look at it, a really dispersed environment, so... >> So I mean how does the... In a multi Cloud world, I mean, how does that changing in terms of people optimizing their software, making these decisions that you're trying to steer, you're trying to advise them on. What's the impact that that's having kind of on what they're deciding to do going forward? >> There's a couple of things. First of all, I couldn't agree more with Lawrence. Tens of thousands of customers. I can't think of a time where I've talked to a customer that wasn't multi Cloud. So it's almost I would say all customers are multi Cloud. The challenge for our customers is how do you take all the different Cloud environments you're working with that use different vernacular, bring it into one system that then is using a common language to, you know, a common language around the resources that sit in those Cloud environments. A common language around how you map those resources to your organizational structure or how you manage your business. So that you're looking at your Cloud resources, you're planning for them financially but in the context of your business, using a common vernacular across all Cloud providers. That's a difficult thing to do if you're just going to a point solution from one of the publishers. >> And so why do that? I mean, why not simplify? Why not, why not just keep it in one environment or maybe two environment? Why branch out? Why take it to a different sphere? >> Well, I think, Lawrence touched on some of the reasons which is some of it's price Some of it is I've got legacy applications that don't work in one Cloud infrastructure but will work in another Cloud infrastructure. Some of it is security. Some of it is just simply I don't have any control over it. People are acquiring Cloud infrastructure via credit card within departments. You can't say, "You have to use Amazon "or you have to use Microsoft." You're not controlling that. >> You know we've talked before. SoftwareONE has a different legacy than say, what I'd say the Cloud management providers that are out there. But some of the things are very similar that you're attacking because everybody, I think, has identified this multi Cloud and it's the big elephant and everybody's trying to take bites out of it. Can you maybe give us a little bit of a compare contrast about... Think there's all these companies out there that start with Cloud and have one or two other words with them. How's SoftwareONE? What's similar and what's different? >> Yeah, I think when you look at that, there's certainly a lot of vendors here do a good job of starting to think about that. But a lot of vendors have started with the Cloud and kind of built around that and for companies that are born in the Cloud and that's all they focus on, that might be a great solution. But a lot of the enterprises that we deal with, our larger customers, that mix of what's on premise and what's in the Cloud, is still a minority is going to be in the Cloud. It is gonna be definitely less than 50 percent for a lot of the companies. Even smaller for some of the big places. So if you get really really good visibility, even in a multi Cloud environment, on only 20 or 30 percent of your environment, then you're not getting the whole big picture of what's happening, particularly on the expense side and where you're spending the money. So what we bring to the table that's a little bit unique here is we come from the history of doing this for many years on premise. We give a good visibility into what they're doing, how their assets are being utilized, giving them thoughts and contributions on how they price it and what they buy to it. So we give them that good view of on premise as well as what's happening in the Cloud. So now when they make decisions, they're getting that wholistic view. So marketing might come in there and they might have a software catalog that's part in Cloud and part of it's on premise. Their CRM might be on premise. So if they're looking at, What's my overall budget and spend there? How do I consolidate it? How do I make it better? You just can't look at the SAS applications and what's in the Cloud or what's in Amazon. You've really gotta get that full picture and that's what we can bring to bare. And the other thing is, a lot of the solutions that you see, a lot of the vendors are very focused on one particular country or environment. SoftwareONE is really spread out across the globe. We're in 80 plus countries. So when you're looking at okay, now I've gotta figure out who's buying whatever in Switzerland and the UK and the US, how do I simplify procurement for it? How do I get visibility across all of that? I'm prim in the Cloud. That becomes a much more complex question and those are the things that we can help enterprises with that's a little bit above and beyond what you might see on some of the kind of pure Cloud focused players. >> Mike, I had a interesting session I got to sit in with Amazon talking about how they are helping customers with innovation. And one of the things they put forth is, you know, companies have usually hundreds or thousands of applications but at least the premise they put forth is there's usually a handful of companies that are the strategic ones. There's maybe a next tier that are kind of important and then there's whole lots of other stuff. Maybe they're not all applications But they're putting out. But they're coming to Amazon and saying, "You're innovating. "You're moving fast. "How do we do that? "How do we help with the digital transformation?" How does SoftwareONE get involved in kind of the innovation, helping them along that journey? >> It's true that we work with over 9,000 publishers and I would say that the top seven or eight make up the lion's share of both our revenue and our customer's spend. However, if you take the what we call the tail end spend, if you take not just those top tier providers and not the middle tier but all of those small little applications they're using departmentally, they don't seem to add up to a lot when you look at them each department or each geography. When you bring them together for the enterprise, it's a large spend and it's very hard for our customers to get control of that. So when we talk about innovation, I would not suggest that you innovate just around the top five to 10 publishers. You have to be able to provide a cost management solution across the entire portfolio for customers, across the entire life cycle, that's on premises, that's multi Cloud, hybrid Cloud, and that's from acquisition through disposition and that includes the tail end spend. >> So is a lot of that when you give the visibility into the client as to what they're doing across the enterprise? They might not realize how deeply involved they are and that could give them leverage for pricing and then the lend. >> The best example is SAS Today, because SAS has enabled shadow IT in a way that we've never seen. Now people are just buying whatever application they want in their department with their credit card. Well, the IT department, the procurement department, the compliance group, they have no idea where that spend is coming from. They haven't discovered those unknown SAS subscriptions and you can't budget for it. You can't manage what you can't see. >> What's the shocker then? I mean, when you come in, just in general, to a business, what's the eye opening moment for them you think in terms of what you're uncovering or what you're showing them about their own process that you think they would know but you give them a little aha. >> Yeah, I think one example... we work with a lot of the companies, but one not that far from here. We work with LA Metro, the county and what they do there and on transportation. And they were looking at their environment and their spend in the Cloud and once we gave them our platform to kind of see what was going on, give them full visibility on what's happening with their VMs, what's happening in the Cloud, they saw that they're basically spending two to three X what they needed to before hand. Right before they really took a look, a good look at it. I think they were surprised by that, but it was a really good opportunity to take a good hard look at what VMs I might need to spend down, what ones do I need to throttle, what ones aren't being active, and again, you want to make sure you're right sized for what you're doing, instead of just over provisioning and kind of taking a guess at it if you will and overspending at the end of the day. >> Interestingly enough, just to add on to that, I was talking to a CIO that we work with maybe a month ago. We surveilled all of our customers on their spend. By and large, most of them know they're overspending on software. The estimates go anywhere between 25 and 35 percent, especially in the Cloud. But they know they're overspending. So some of them don't... they just can't solve the problem so they just budget for the overspend. So I was meeting with her and I said to her, "Do you know you're overspending?" She said, "Yeah, we're definitely overspending about 30%." I said, "What are you doing about that?" She says, "I just put it into my budget." I says, "That's crazy. Why wouldn't you want to solve that problem?" And the irony is that she's actually the CIO for a tax and accounting firm. (laughter) But they're just burying it. So, yeah. >> Yeah, that is funny. So, Andy Jassy did quite an extensive keynote. Lots of announcements. Kind of gave you the wild card. Something that jumped out at you, you wanna build on, any announcements or any pieces of Andy's presentation. >> Yeah, I think overall he kept talking about innovation and what they're doing. I think for us, we were talking a little bit about the marketplace. But you also see things they're doing on the database side. Are they strengthening aurora? Making post gray more attractive as an alternative to some of the legacy systems. And that complements well what we see as a migration and people wanna do, right. If you really strengthen the offering, it makes it more attractive and then certainly makes it interesting for the ecosystem which we're part of to help contribute that for people to move over there. I also really liked his analogy there. He kept going back to the musicians and kind of the relationship they have or thinking that compared to developers. Having all the instruments that you need to kind of build what you want and having that flexibility of choice and I think it's a great analogy. I think the flip side to that is: Hey, if you've got a jam session here and you're bringing in all of these different instruments: a guitar player, a tuba player, whatever it is to build this up, you also have to look at what do you have in house? You probably already have a pretty good size orchestra. Some of it might be legacy. Some people might be playing the harpsichord, the recorder, whatever it is. And you've got to figure out how does, In some cases, how do I blend that together? If I'm bringing them in, is it just for a jam session or do I need them here for a full set or for like a year long concert? And if you're not careful, you could end up spending a lot of money on bringing in all of these different players and I think that's an interesting way to think about this is it's great to have the flexibility but how do you make sure you have the visibility, the cost controls, so that doesn't overdo or overspend what you wanna do to get that creativity that you need. >> Everybody's gotta play in the same key too, right? Alright, let's all get on the same page Same page of music. >> So SoftwareONE is a global company. I know you both do a lot of travel. Give us kind of... We're here in the center of AWS. 43,000 devoted, super excited, passionate people but what are you seeing out there in the globe? Where does AWS specifically, Public Cloud in general, still need to push? What are some of the concerns, challenges, things that you see out there? >> Geographically? >> Yeah. >> Well, I mean certainly in APAC there's the challenge that any Cloud infrastructure provider is gonna face and that's Jolicloud. Jolicloud is a fairly dominant player in China and Japan, and they have a good presence throughout APAC. I think that AWS is making strong strides in Asia. Clearly the market leader worldwide. Everybody is chasing them. With over a thousand features and enhancements announced just within the last year, the pricing changes happening at such rapid fire that I think it's difficult for the other guys to keep up with them. So I'd say there's no question they're the market leader globally. Asia Pacific is probably their biggest challenge. >> Lawrence? >> I concur with a lot of that. I mean, we've seen in our own company a lot of activities starting in India and even in South America. Some good relationships with AWS. Some early adoption there. But yeah, I think those comments on APAC, I think you've got some good experiences there. >> Well, gentlemen, thanks for joining us. We appreciate the time here on theCUBE. Good luck with the rest of the show and I'll be kind of curious to see where this goes. The vibe is good, right? >> The vibe's unbelievable. >> Fantastic. >> And you've got a big runway so good luck with that. >> Thank you. >> Alright. >> Alright gentlemen. That's it for our coverage here on theCUBE. Today, day two here at Reinvent. Back with more live tomorrow morning 11:00 Pacific time. We'll be with you 2:00 on the East Coast and we'll see you right here. Until then have a good night. (upbeat music)

(lively music) >> Narrator: Live from Las Vegas, it's the CUBE. Covering Dell EMC World 2017. Brought to you by Dell EMC. >> We are back in Las Vegas. Welcome back to the CUBE's coverage of Dell EMC World. I'm your host Rebecca Knight along with my co-host Keith Townsend. We are joined by Lawrence Weitzman. He is the managing executive for Technology Transformation Solutions within BCX as well as Burtus vanHeerden, I hop I'm saying that right. The executive for Dell Technologies within BCX. So, thank you both, so much, for joining us. >> Thank you. >> Big news today. A partnership to revolutionize cloud in South Africa. Tell us a little bit about that. >> Yes, I think from a BCX prospective, our customer base has been looking for a business critical cloud in South Africa for a long time. That's both our corporate enterprise customer base and the public sector customer base. They're looking for 24/7 support by a local partner. But backed by an international player. We believe our partnership with Virtusstream would definitely, be a game change in the South African cloud industry. >> So what appealed, specifically, about Virtustream. Because there's a lot of international cloud providers. What's specific about Virtustream? >> I think there's two components being the fact that it provides the reliability, the security of a private cloud environment but it also allows us the flexibility and scalability as well as economic benefits of a multi tailored public cloud. >> What type of solutions are you looking to offer to your customers as a result of this partnership? >> We going to look at, mostly, ACP application hosting and Oracle hosting to start off with our offering. >> And where's the value between what BCX will offer versus Virtustream to the customer? Are you guys going to manage SAP applications on top of Virtustream? Where is that relationship? >> BCX has got a number of tier four data centers within South Africa, so we have three tier four data centers so we would be providing the facilities to host the applications. We also, are a big managed services provider in South Africa so we would be providing some of the many services on behalf of Virtustream as well. >> Tell us a little bit about the customer base in South Africa. Educate us on the market overall. >> We've got basically, three different types of customers. We've got a big public sector business as well as large corporate entities or the lesser entities within the country. A huge amount of financial services and insurance. A big amount of retail customers, as well as mining and manufacturing. And then the third category is, from an economic perspective, a huge amount of smaller (mumbles) market companies. As a group, we've got access to about 15,000 customers which we'll be targeting. >> What's the drive for those customers? What are the specific challenges? Has BCX solved for them in the past and what new capability will you be able to offer from a business perspective? >> I think from a past history perspective, BCX is entering the IT company. We provide system integration. We provide data center hosting, cloud business. We recently, became part of the Telkom group. Telkom is the national carrier within South Africa. We can provide an interim digital solution to our customer base across all our customers. >> Burtus, I was wondering if you could just talk to us, a little bit, about down the road? What you hope we'll be talking about a year from now at the next Dell EMC World or even five years from now. What you hope this partnership will involve into? >> We're moving away from colleges selling boxes into this cloud world. Thinking about the cloud world. I think everybody's out there with Microsoft and Azure, those types of solutions. This is a data center. This is an enterprise, mission critical, type of work load that we can add clients on. In a year from now, yes. We, probably, got to talk about the first five or six clients that we got on the cloud but after that, we expect it to accelerate. It's about providing something new to our clients. That's what they want. They don't want to pay too much over a proper solution but being mission critical, being performance based and being pay as you use type of solution. This is what Virtustream brings and that's what our clients want. >> How difficult is it to get your clients to think differently about technology and to get the buy in that you need to really, make this successful? >> This journey with Virtustream, started about a year ago. We've been visiting clients, we've been taking to clients. They're excited about what we can do. They want it in country. We've been providing many services for a long time. Our credentials, in terms of that, is not questionable. >> Rebecca: They know you're legit, yes. (laughs) >> It's good but can we do a thing? With the (mumbles), sometimes in hosting our solutions in Europe or elsewhere, it's a challenge for the clients. But having it local and us being part of the biggest network provider in South Africa, we can provide those services locally. That's what the client want. They want the data in country, they want to know, they want to be able to touch and feel even though it's a cloud solution yes. >> A year of conversation in country, what have been some of the major hurdles that you guys have had to go through to get this solution in country? Facilities, networking, what have been some of the, specific, victories? >> We have all the infrastructure. We have the network and we have the facility. We have the first two tier four data centers in Africa for that matter. So, there's only three at this point in time. We're ready for that though. The discussion with Virtustream, I think, was more about who will provide the service? Cause they were looking for a place to provide these services and we changed the discussion to, we will be providing their tools on their day off. Working with them for the last year, I think they've seen what we can do, what we can provide and yes, that's how the relationship was formed. >> This conference has been about digital transformation and adding value. You guys are talking about adding value at this infrastructure layer. Allowing customers the freedom to push investments somewhere else. What have been the interesting conversations you're taking away from this conference, here, in the US, that you're going to go back and have conversations with your customers potentially? >> I think there's obviously, a number of discussions. The innovation, it's so exciting to see what's being done. My background's closer to the data center, not the marketing side of the world. The innovation that we've seen, in terms of what gets done with the technology. It's the first, I mean, what I've seen so far. What's the message received from that point of view? I think we're close enough to the technology. In terms of what you do with that, it's a next level of interest I think. >> So Lawrence, any interesting customer use cases that you've seen here that you're excited to take back home? >> I think, for us, it's more about the vertical solutions that you can derive and we've got a big mining and manufacturing customer base so for us, the IoT solutions states and moving to the age of computing, I think, is one of the bigger opportunities for us as an organization. There's a number of those so we're very excited. >> Were is the South African customer in terms of having these distinct strategies? As you said, an IoT strategy, a data storage strategy, an AI strategy? Are they thinking about all these things as holistically as they should be? Is there anything that concerns you that you're seeing? >> No, I think the customer base is, definitely thinking about it. Whether we are at a point where the cloud adoption has happened as quickly as we had anticipated as an organization? Probably not. People are definitely, buying more (mumbles) solutions and wanting that security and ability to come and throttle somebody's throat (laughing) if the solution, really doesn't work. That remains key from a South African customer perspective. >> One of the other things we've heard about is technology as a recruiting and retention tool for companies. We've heard a lot of statistics thrown around about how people will leave jobs if they don't think the technology is all that. And CEO's view it as a real way to keep employees happy and engaged and excited to come to work in the morning. Is that as true in South Africa as it is in Silicone Valley and in Texas? >> To be quite honest, I don't think it's quite there at the moment. I think from a South African perspective, at the moment, companies are sweating a lot of assets so people are not investing that much in that type. They'd rather invest their money in the business critical applications and digitizing the organizations then looking to much at the work space at the moment. But I think that's something that will definitely, start changing as people start demanding it. >> You guys are offering a capability not previously available in South Africa. How do you see customers using this capability as a competitive advantage across the different industry's you serve, mining, industry? >> It's up to your vices. We have an advantage, partly with Virtustream offering the solution. It will take the client, pull it to a new level or new way to operate the environment and stuff like that. That's a client advantage that will be available now. >> As well as cost savings. I think there's a different cost saving benefit to our customer base as well as performance. >> When you talk about those two different and I don't know if they're competing priorities but there are two pressures that manage our space today. Keeping the budget but then also, driving optimal performance. Where do customers fit? What are they most concerned about? What are some of the things on their minds? >> I think it's a combination of both. It depends on which sector it sits in at the moment where the cost is a bigger driver From the retail perspective, I think cost is a bigger driver. Driving down costly innovation of putting a new technologies there. It's our business to go and make sure that we provide a value proposition to the customer to drive both of these objectives. >> And where do you think, in terms of innovation, in talking about, we were just saying about the conversations that you're having. The innovation that's taking place and how exciting is is and how we are seeing these industry's being completely transformed by AI and IoT. When you think about innovation in the work force and just in terms of how employees do their jobs every day. What is most exciting to you? >> I think it's the ability to work from anywhere. I think that's (mumbles) of being a national carrier, that's where our ability and having that connectivity available is their to provide our customers with that solution. It's, most definitely, there's a big move in South Africa towards working from anywhere to a bit more working from home. >> So, not many people do that in South Africa? >> Lawrence: Not too many people. >> Not too many, okay. >> In different industries, we-- >> It's, definitely taken hold, yeah. >> Definitely starting to take hold, yeah. We, ourselves, are moving towards a more mobile office environment and doing it ourselves as (mumbles) as well, yeah. >> One big thing on IoT in the edge. Mining, obviously, big challenges in the edge. You guys are now teamed up with a huge Telkom in South Africa. Where are the opportunities when it comes to the edge in providing new capabilities for the IoT in combination with the offering from Virtustream and BCX? >> I think it's about the different types of assistance that we provide. We look at the management execution systems for (mumbles). The ERP systems and looking at new technologies around how do you provide safety underground. Significance with underground mines, how do we provide worker safety in the underground. It's about how do we get that performance out of getting the data out quicker and being able to analyze and deal with any issues. >> Burtus, Lawrence, thank you so much for joining us. It' been a real pleasure having you on the program. >> Thanks for having us. >> Thank you. >> I'm Rebecca Knight along with Keith Townsend. We'll be back with more from Dell EMC World just after this. (lively music)

(inspirational music) >> The history of high performance computing is unique and storied. You know, it's generally accepted that the first true supercomputer was shipped in the mid 1960s by Controlled Data Corporations, CDC, designed by an engineering team led by Seymour Cray, the father of Supercomputing. He left CDC in the 70's to start his own company, of course, carrying his own name. Now that company Cray, became the market leader in the 70's and the 80's, and then the decade of the 80's saw attempts to bring new designs, such as massively parallel systems, to reach new heights of performance and efficiency. Supercomputing design was one of the most challenging fields, and a number of really brilliant engineers became kind of quasi-famous in their little industry. In addition to Cray himself, Steve Chen, who worked for Cray, then went out to start his own companies. Danny Hillis, of Thinking Machines. Steve Frank of Kendall Square Research. Steve Wallach tried to build a mini supercomputer at Convex. These new entrants, they all failed, for the most part because the market at the time just wasn't really large enough and the economics of these systems really weren't that attractive. Now, the late 80's and the 90's saw big Japanese companies like NEC and Fujitsu entering the fray and governments around the world began to invest heavily in these systems to solve societal problems and make their nations more competitive. And as we entered the 21st century, we saw the coming of petascale computing, with China actually cracking the top 100 list of high performance computing. And today, we're now entering the exascale era, with systems that can complete a billion, billion calculations per second, or 10 to the 18th power. Astounding. And today, the high performance computing market generates north of $30 billion annually and is growing in the high single digits. Supercomputers solve the world's hardest problems in things like simulation, life sciences, weather, energy exploration, aerospace, astronomy, automotive industries, and many other high value examples. And supercomputers are expensive. You know, the highest performing supercomputers used to cost tens of millions of dollars, maybe $30 million. And we've seen that steadily rise to over $200 million. And today we're even seeing systems that cost more than half a billion dollars, even into the low billions when you include all the surrounding data center infrastructure and cooling required. The US, China, Japan, and EU countries, as well as the UK, are all investing heavily to keep their countries competitive, and no price seems to be too high. Now, there are five mega trends going on in HPC today, in addition to this massive rising cost that we just talked about. One, systems are becoming more distributed and less monolithic. The second is the power of these systems is increasing dramatically, both in terms of processor performance and energy consumption. The x86 today dominates processor shipments, it's going to probably continue to do so. Power has some presence, but ARM is growing very rapidly. Nvidia with GPUs is becoming a major player with AI coming in, we'll talk about that in a minute. And both the EU and China are developing their own processors. We're seeing massive densities with hundreds of thousands of cores that are being liquid-cooled with novel phase change technology. The third big trend is AI, which of course is still in the early stages, but it's being combined with ever larger and massive, massive data sets to attack new problems and accelerate research in dozens of industries. Now, the fourth big trend, HPC in the cloud reached critical mass at the end of the last decade. And all of the major hyperscalers are providing HPE, HPC as a service capability. Now finally, quantum computing is often talked about and predicted to become more stable by the end of the decade and crack new dimensions in computing. The EU has even announced a hybrid QC, with the goal of having a stable system in the second half of this decade, most likely around 2027, 2028. Welcome to theCUBE's preview of SC22, the big supercomputing show which takes place the week of November 13th in Dallas. theCUBE is going to be there. Dave Nicholson will be one of the co-hosts and joins me now to talk about trends in HPC and what to look for at the show. Dave, welcome, good to see you. >> Hey, good to see you too, Dave. >> Oh, you heard my narrative up front Dave. You got a technical background, CTO chops, what did I miss? What are the major trends that you're seeing? >> I don't think you really- You didn't miss anything, I think it's just a question of double-clicking on some of the things that you brought up. You know, if you look back historically, supercomputing was sort of relegated to things like weather prediction and nuclear weapons modeling. And these systems would live in places like Lawrence Livermore Labs or Los Alamos. Today, that requirement for cutting edge, leading edge, highest performing supercompute technology is bleeding into the enterprise, driven by AI and ML, artificial intelligence and machine learning. So when we think about the conversations we're going to have and the coverage we're going to do of the SC22 event, a lot of it is going to be looking under the covers and seeing what kind of architectural things contribute to these capabilities moving forward, and asking a whole bunch of questions. >> Yeah, so there's this sort of theory that the world is moving toward this connectivity beyond compute-centricity to connectivity-centric. We've talked about that, you and I, in the past. Is that a factor in the HPC world? How is it impacting, you know, supercomputing design? >> Well, so if you're designing an island that is, you know, tip of this spear, doesn't have to offer any level of interoperability or compatibility with anything else in the compute world, then connectivity is important simply from a speeds and feeds perspective. You know, lowest latency connectivity between nodes and things like that. But as we sort of democratize supercomputing, to a degree, as it moves from solely the purview of academia into truly ubiquitous architecture leverage by enterprises, you start asking the question, "Hey, wouldn't it be kind of cool if we could have this hooked up into our ethernet networks?" And so, that's a whole interesting subject to explore because with things like RDMA over converged ethernet, you now have the ability to have these supercomputing capabilities directly accessible by enterprise computing. So that level of detail, opening up the box of looking at the Nix, or the storage cards that are in the box, is actually critically important. And as an old-school hardware knuckle-dragger myself, I am super excited to see what the cutting edge holds right now. >> Yeah, when you look at the SC22 website, I mean, they're covering all kinds of different areas. They got, you know, parallel clustered systems, AI, storage, you know, servers, system software, application software, security. I mean, wireless HPC is no longer this niche. It really touches virtually every industry, and most industries anyway, and is really driving new advancements in society and research, solving some of the world's hardest problems. So what are some of the topics that you want to cover at SC22? >> Well, I kind of, I touched on some of them. I really want to ask people questions about this idea of HPC moving from just academia into the enterprise. And the question of, does that mean that there are architectural concerns that people have that might not be the same as the concerns that someone in academia or in a lab environment would have? And by the way, just like, little historical context, I can't help it. I just went through the upgrade from iPhone 12 to iPhone 14. This has got one terabyte of storage in it. One terabyte of storage. In 1997, I helped build a one terabyte NAS system that a government defense contractor purchased for almost $2 million. $2 million! This was, I don't even know, it was $9.99 a month extra on my cell phone bill. We had a team of seven people who were going to manage that one terabyte of storage. So, similarly, when we talk about just where are we from a supercompute resource perspective, if you consider it historically, it's absolutely insane. I'm going to be asking people about, of course, what's going on today, but also the near future. You know, what can we expect? What is the sort of singularity that needs to occur where natural language processing across all of the world's languages exists in a perfect way? You know, do we have the compute power now? What's the interface between software and hardware? But really, this is going to be an opportunity that is a little bit unique in terms of the things that we typically cover, because this is a lot about cracking open the box, the server box, and looking at what's inside and carefully considering all of the components. >> You know, Dave, I'm looking at the exhibitor floor. It's like, everybody is here. NASA, Microsoft, IBM, Dell, Intel, HPE, AWS, all the hyperscale guys, Weka IO, Pure Storage, companies I've never heard of. It's just, hundreds and hundreds of exhibitors, Nvidia, Oracle, Penguin Solutions, I mean, just on and on and on. Google, of course, has a presence there, theCUBE has a major presence. We got a 20 x 20 booth. So, it's really, as I say, to your point, HPC is going mainstream. You know, I think a lot of times, we think of HPC supercomputing as this just sort of, off in the eclectic, far off corner, but it really, when you think about big data, when you think about AI, a lot of the advancements that occur in HPC will trickle through and go mainstream in commercial environments. And I suspect that's why there are so many companies here that are really relevant to the commercial market as well. >> Yeah, this is like the Formula 1 of computing. So if you're a Motorsports nerd, you know that F1 is the pinnacle of the sport. SC22, this is where everybody wants to be. Another little historical reference that comes to mind, there was a time in, I think, the early 2000's when Unisys partnered with Intel and Microsoft to come up with, I think it was the ES7000, which was supposed to be the mainframe, the sort of Intel mainframe. It was an early attempt to use... And I don't say this in a derogatory way, commodity resources to create something really, really powerful. Here we are 20 years later, and we are absolutely smack in the middle of that. You mentioned the focus on x86 architecture, but all of the other components that the silicon manufacturers bring to bear, companies like Broadcom, Nvidia, et al, they're all contributing components to this mix in addition to, of course, the microprocessor folks like AMD and Intel and others. So yeah, this is big-time nerd fest. Lots of academics will still be there. The supercomputing.org, this loose affiliation that's been running these SC events for years. They have a major focus, major hooks into academia. They're bringing in legit computer scientists to this event. This is all cutting edge stuff. >> Yeah. So like you said, it's going to be kind of, a lot of techies there, very technical computing, of course, audience. At the same time, we expect that there's going to be a fair amount, as they say, of crossover. And so, I'm excited to see what the coverage looks like. Yourself, John Furrier, Savannah, I think even Paul Gillin is going to attend the show, because I believe we're going to be there three days. So, you know, we're doing a lot of editorial. Dell is an anchor sponsor, so we really appreciate them providing funding so we can have this community event and bring people on. So, if you are interested- >> Dave, Dave, I just have- Just something on that point. I think that's indicative of where this world is moving when you have Dell so directly involved in something like this, it's an indication that this is moving out of just the realm of academia and moving in the direction of enterprise. Because as we know, they tend to ruthlessly drive down the cost of things. And so I think that's an interesting indication right there. >> Yeah, as do the cloud guys. So again, this is mainstream. So if you're interested, if you got something interesting to talk about, if you have market research, you're an analyst, you're an influencer in this community, you've got technical chops, maybe you've got an interesting startup, you can contact David, david.nicholson@siliconangle.com. John Furrier is john@siliconangle.com. david.vellante@siliconangle.com. I'd be happy to listen to your pitch and see if we can fit you onto the program. So, really excited. It's the week of November 13th. I think November 13th is a Sunday, so I believe David will be broadcasting Tuesday, Wednesday, Thursday. Really excited. Give you the last word here, Dave. >> No, I just, I'm not embarrassed to admit that I'm really, really excited about this. It's cutting edge stuff and I'm really going to be exploring this question of where does it fit in the world of AI and ML? I think that's really going to be the center of what I'm really seeking to understand when I'm there. >> All right, Dave Nicholson. Thanks for your time. theCUBE at SC22. Don't miss it. Go to thecube.net, go to siliconangle.com for all the news. This is Dave Vellante for theCUBE and for Dave Nicholson. Thanks for watching. And we'll see you in Dallas. (inquisitive music)

perfect all right we're good uh muhammad you ready yeah i have a watery eyes always so i always tell my interviewers or the producers that sometimes it shouldn't there shouldn't be a problem in the 10-minute window but well yeah so do that while i'm talking you'll see it on the return feed it's a little delayed but and most people have tears when they see dave vellante yeah i i have that effect on people thanks for that okay we all said we good leonard why don't you go alex bye-bye yeah alex got the i just got the thumbs up we're good okay muhammad here we go on dave in five four three we continue now with the network powering hybrid work now we just heard from lawrence wang on the rapid move to wi-fi 6e which is going to increase wi-fi efficiency enable routers and devices to more efficiently use bandwidth and that additional spectrum that lawrence talked about that means more wi-fi channels which is really going to help reduce overlap between networks and make a noticeable difference especially in crowded places we're here now with muhammad imam who's senior director of product management for catalyst switching this is a multi-billion dollar business for cisco if you ever listen to cisco's earnings calls you'll hear the cfo scott heron he'll talk about the catalyst 9000 and double-digit growth and switching this is the fastest ramping product in cisco's history so muhammad that's got to make you feel pretty good yes indeed thank you david and thank you for having me here yeah great to have you so uh look catalyst 9000 it's been really successful what does the 9000x bring to the table for your customers yeah absolutely and um indeed the catalyst 9000 family of switches have been extremely popular with our customers as you said fastest ramping product in cisco's history and the last four or five years we have really evolved the catalyst 9000 family of switches to a very comprehensive product portfolio um addressing the various enterprise use cases that that we that we address but now we see increase in demand on the networks and that really stems from some of the most recent trends that we are seeing right part of it is hybrid workspaces is going to be a video dominant hybrid workspace right a lot of cases is going to be high definition 4k 8k videos we are seeing cloud-based applications everywhere right my spreadsheet is used to be on excel sheet now it's either an office 365 or smartsheets my files used to be on my computer now it's on in the dropbox right so these are trends that are really uh putting pressure on our networks we are also seeing trends where vr headsets are becoming common they are being used for trainings and education use cases webex hologram in certain industries we are seeing robotics are becoming more and more popular and they come with a lot of um applications that are very latency sensitive and as lawrence mentioned earlier wi-fi 6e is really making over the year multi gigabit wi-fi possible right and for all of these different trends and the recent technologies that that are evolving we really need the network that can really address and deliver for these applications and that's where we are bringing the catalyst 9000 x that addresses the increase in network demand we are expanding the catalyst 9000 family with top-of-line premium introductions in the access layer of the switches of the network as well as in the aggregation and core layers so we are bringing 400 gig high-speed core and enterprise core and edge layers of the network we are bringing point-to-point ip ipsec security which will give you 100 gig of ipsec encryption um high density of multi-gigabit which is becoming very common as we evolve our wi-fi networks because we don't want our wired infrastructure to be the bottleneck when the wireless infrastructure is capable of going more than a gig high density of 90 watt powering the smart buildings use cases right right um these are all different use cases that are being enabled by the catalyst 9000 and the new getless 9000x family is really addressing some of these new trends and applications well it's good because the metaverse is coming too and we're going to need some help with that right who knows how much bandwidth will need for metabolism absolutely yeah guarantee will be a lot more but so i want to i want to hear more about the the new products that you've just launched and maybe how these offerings are going to help with this new hybrid work model that we've just been discussing absolutely so let me start with the catalyst 9300 we are introducing the catalyst 9300x which is the highest density full multi-gigabit platform with 100 gig uplinks and 90 watt of power on every port available right that's an industry first that we are bringing on the catalyst 9300 family it is also capable of one terabit per second of a stacking which is also unheard of in the industry this will serve our customers with all the new trends that we talked about including the hybrid world um and some of the new trends that are going to come in the next decade but 9300x is not just a high-end campus switch it can also be a lean branch and a box solution where you don't really need an sd van but you do need an encryption point to point from the catalyst 93 from your front branch with the catalyst 9300x to the data center or to the cloud so for the first time we are introducing the ipsec based encryption natively in the hardware and that means no compromise on performance and you can get up to 100 gig of encrypted traffic with the catalyst 9300x second is the catalyst 9400 we are introducing soup 2 and soup 2 xl with 100 gig uplinks enhancing and the the scale and performance giving our customers options for fully loaded line rate multi give it board on a 10 slot chassis right it will give you two to three times bandwidth boost to your existing line cards since it completely removes the over subscriptions and you know the soup 2 on the catalyst 9400 is coming up with the version of the asic that we used in the past on the catalyst 9600 that means it's also bringing the core capabilities that we used that we today have on 9600 on the catalyst 9400 and that brings high density 10 gig um ports on the catalyst 9400 without over subscription right with the core capabilities then we have the catalyst 9600 where we are introducing is supervisor 2 which really triples the bandwidth per slot on the catalyst 98600 it introduces 400 gig uplink and truly drives the transition to 200 gig in the core get 6k customers uh with excel scale requirements now they can transition to the cat 9k with soup 2. and by the way we are also introducing a combo line card on the catalyst 9600 which means now you don't have to burn a whole slot for your uplink pores in fact you can get up to 400 gig of uplink with this new line card um so that's that's a bunch of things that we are bringing on the catalyst 9600 in line with catalyst 9600 we are also introducing catalyst 9500x 100 gig box with 400 gig uplinks in a fixed form factor and all the benefits that i just talked about on the on the supervisor 2 and 9600 it's also available in a fixed form factor on catalyst 9500x got it so that's in summary kind of the multiple uh product lines that we are introducing yeah it's a lot to unpack there i mean your the big theme there of course is optionality you got a lot of choices for customers i love the encrypt everything without a trade-off you know no performance impact and anytime you can reduce my oversubscription it's going to make me happy you know muhammad we've reported in our breaking analysis segments the importance of custom silicon and not every company has the resources or the expertise to develop their own silicon cisco of course does catalyst 9k is bringing silicon 1 based products with this launch tell us more about that why is this important yeah that's really exciting development that we have on the cad 9k family because you know the silicon one is a powerful asic that enables high performance and high scale with modern silicon architecture bringing the architect a converged architecture for switching as well as routing cad 9k as we know has been running on a uadp asic which has been a programmable asic it has served us really well so far on the cat9k family but with the silicon one we are taking it to another level silicon one brings the capabilities of uadp asic and unlocks the excel scale and high performance in the enterprise switches this is a critical and foundational element to meet the core requirement for the next ticket silicon one is a 12.8 terabits per second chip supports up to 10 million routes supports much deeper buffers brings multi-slice voq architectures with this new architecture silicon 1a6 has paved the way to transition the cad 6k xl deployments to cat 9k right so that's kind of the the um the silicon one uh importance in the ket99k family that we are bringing now yeah and it brings differentiation a lot of people kind of sometimes don't appreciate that but but when you have the control like that you can do things that you might not be able to do with off-the-shelf silicon but so but i i want to ask you what about customers that previously purchased from you as you evolve the portfolio to 9k x how do you protect their investment yeah thank you for asking that question because when we started building the cad 9k we always thought about investment protection for our customers so if you buy today how you will have a very long life for that for that product and you will be able to unlock new powers on that platform that you have purchased maybe five years back right that's exactly what we are doing with the catalyst 199000x talking about modular right on the modular side the supervisors that that that we are introducing now are backward compatible with the line cars that you already have in some cases the lime card throughput is doubling and tripling because now you have a new machine that is going to power these line cards right so you don't have to change your line card you just change your supervisor and you have much higher performance and scale with this new supervisor similarly on the stackables you can stack with the existing catalyst 9300s for example and you will be able to you don't have to rip and replace everything it's not a forklift upgrade for our customers you can continue benefiting from your existing catalyst 9000 deployments and add to the power with the catalyst 9000x components as well as new platforms that we are introducing nice that's key this just speaks to the software content that you guys i know you have a lot of software engineers running around and this is welcome to the 2020s folks new world you know i i muhammad zero trust was kind of a buzzword before the pandemic but it's really become a mainstream topic today we talked about the infrastructure we know security has to be built in from the start it can't be bolted on and zero trust is really top of mind for customers how are their security requirements changing as a result of hybrid work and and how do you make sure that as we shift to hybrid that these new security requirements are addressed what are you doing there absolutely and we know as you said security is top of mind for our customers in fact security has been highlighted as the number one reason why a lot of customers pick cisco and cat9k we have a comprehensive zero truss architecture with software defined access where we started with segmentation and expanded into endpoint classification and visibility now we are taking that to the next level and we are introducing talus powered truss assessment for unmanaged endpoints to further make the the workplace is stronger with zero trust and software defined access truss analytics it detects traffic from end points that are exhibiting unusual um behavior by pretending to be um using a mag spoofing or probe is spoofing or man the metal techniques when truss analytics detects such anomalies it signals endpoint analytics to lower the trusted score so we have a trusted score system when when the trusted score goes down it shows up on the dashboard and the network admin can completely deny or limit the access to the network from these endpoints from other security aspect that we are introducing and i touched on that briefly earlier is um for non-sdvan internet only branches where we are where where services security services might be in the cloud right that's a trend that we are seeing to secure that connectivity from a lean branch to the cloud we are introducing the ipsec capability with the catalyst 9300x and that's built in as as we just talked about and as far as the automation is concerned for these use cases they are we are bringing those automation with our command center the cisco dna center and we are bringing the full life cycle of automation as well as assurance for the secure connectivity that is being provided with the with the cisco dna center well a couple takeaways there for me i mean endpoint security has really become much more important up for obvious reasons when you have remote workers the built-in ipsec just that really emphasizes that you got to have it you know built in from the ground up you can't just bolt it on and the automation is key the number one problem that csos face is you know lack of talent so automation you know definitely helps helps with that so okay muhammad thank you so much really appreciate you coming on in a moment we'll look at private 5g and what's been happening at mobile world congress you're watching cube's coverage of the network powering hybrid work made possible by cisco

>>Hello, and welcome back to the cubes coverage of coop con cloud native con 2021. We're here in person at a real event. I'm John farrier host of the cube, but Dave Nicholson, Michael has got great guests here. Two founders of brand new startup, one week old cable on ASCII and Dave Lawrence, uh, with chain guard, former Google employees, open source community members decided to start a company with five other people on total five total. Congratulations. Welcome to the cube. >>Thank you. Thank you for >>Having us. So tell us like a product, you know, we know you don't have a price. So take us through the story because this is one of those rare moments. We got great chance to chat with you guys just a week into the new forms company and the team. What's the focus, what's the vision. >>How far back do you want to go with this story >>And why you left Google? So, you know, we're a gin and tonics. We get a couple of beers I can do that. We can do that. Let's just take over the world. >>Yeah. So we both been at Google, uh, for awhile. Um, the last couple of years we've been really worried about and focused on open-source security risk and supply chain security in general and software. Um, it's been a really interesting time as you probably noticed, uh, to be in that space, but it wasn't that interesting two years ago or even a year and a half ago. Um, so we were doing a bunch of this work at Google and the open source. Nobody really understood it. People kind of looked at us funny at talks and conferences. Um, and then beginning of this year, a bunch of attacks started happening, uh, things in the headlines like solar winds, solar winds attack, like you say, it attack all these different ransomware things happening. Uh, companies and governments are getting hit with supply chain attacks. So overnight people kind of started caring and being really worried about the stuff that we've been doing for a while. So it was a pretty cool thing to be a part of. And it seemed like a good time to start a company and keep your >>Reaction to this startup. How do you honestly feel, I suppose, feeling super excited. Yeah. >>I am really excited. I was in stars before Google. So then I went to Google where there for seven, I guess, Dan, a little bit longer, but I was there for seven years on the product side. And then yeah, we, we, the open source stuff, we were really there for protecting Google and we both came from cloud before that working on enterprise product. So then sorta just saw the opportunity, you know, while these companies trying to scramble and then sort of figure out how to better secure themselves. So it seemed like a perfect, >>The start-up bug and you back in the start up, but it's the timing's perfect. I got to say, this is a big conversation supply chain from whether it's components and software now, huge attack vector, people are taking advantage of it super important. So I'm really glad you're doing it. But first explain to the folks watching what is supply chain software? What's the challenge? What is the, what is the supply chain security challenge or problem? >>Sure. Yeah, it's the metaphor of software supply chain. It's just like physical supply chain. That's where the name came from. And it, it really comes down to how the code gets from your team's keyboard, your team's fingers on those keyboards into your production environment. Um, and that's just the first level of it. Uh, cause nobody writes all of the code. They use themselves. We're here at cloud native con it's hundreds of open source vendors, hundreds of open libraries that people are reusing. So your, your trust, uh, radius and your attack radius extends to not just your own companies, your own developers, but to everyone at this conference. And then everyone that they rely on all the way out. Uh, it's quite terrifying. It's a surface, the surface area explode pretty quickly >>And people are going and the, and the targeting to, because everyone's touching the code, it's open. It's a lot of action going on. How do you solve the problem? What is the approach? What's the mindset? What's the vision on the problems solving solutions? >>Yeah, that's a great question. I mean, I think like you said, the first step is awareness. Like Dan's been laughing, he's been, he felt like a crazy guy in the corner saying, you know, stop building software underneath your desk and you know, getting companies, >>Hey, we didn't do, why don't you tell them? I was telling him for five years. >>Yeah. But, but I think one of his go-to lines was like, would you pick up a thumb drive off the side of the street and plug it into your computer? Probably not. But when you download, you know, an open source package or something, that's actually can give you more privileges and production environments and it's so it's pretty scary. Um, so I think, you know, for the last few years we've been working on a number of open source projects in this space. And so I think that's where we're going to start is we're going to look at those and then try to grow out the community. And we're, we're watching companies, even like solar winds, trying to piece these parts together, um, and really come up with a better solution for themselves. >>Are there existing community initiatives or open source efforts that are underway that you plan to participate in or you chart? Are you thinking of charting a new >>Path? >>Oh, it's that looks like, uh, Thomas. Yeah, the, the SIG store project we kicked off back in March, if you've covered that or familiar with that at all. But we kicked that off back in March of 2021 kind of officially we'd look at code for awhile before then the idea there was to kind of do what let's encrypted, uh, for browsers and Webster, um, security, but for code signing and open source security. So we've always been able to get code signing certificates, but nobody's really using them because they're expensive. They're complicated, just like less encrypted for CAS. They made a free one that was automated and easy to use for developers. And now people do without thinking about it in six stores, we tried to do the same thing for open source and just because of the headlines that were happening and all of the attacks, the momentum has just been incredible. >>Is it a problem that people just have to just get on board with a certain platform or tool or people have too many tools, they abandoned them there, their focus shifts is there. Why what's the, what's the main problem right now? >>Well, I think, you know, part of the problem is just having the tools easy enough for developers are going to want to use them and it's not going to get in our way. I think that's going to be a core piece of our company is really nailing down the developer experience and these toolings and like the co-sign part of SIG store that he was explaining, like it's literally one command line to sign, um, a package, assign a container and then one line to verify on the other side. And then these organizations can put together sort of policies around who they trust and their system like today it's completely black box. They have no idea what they're running and takes a re >>You have to vape to rethink and redo everything pretty much if they want to do it right. If they just kind of fixing the old Europe's sold next solar with basically. >>Yeah. And that's why we're here at cloud native con when people are, you know, the timing is perfect because people are already rethinking how their software gets built as they move it into containers and as they move it into Kubernetes. So it's a perfect opportunity to not just shift to Kubernetes, but to fix the way you build software from this, >>What'd you say is the most prevalent change mindset change of developers. Now, if you had to kind of, kind of look at it and say, okay, current state-of-the-art mindset of a developer versus say a few years ago, is it just that they're doing things modularly with more people? Or is it more new approaches? Is there a, is there a, >>I think it's just paying attention to your building release process and taking it seriously. This has been a theme for, since I've been in software, but you have these very fancy production data centers with physical security and all these levels of, uh, Preston prevention and making sure you can't get in there, but then you've got a Jenkins machine that's three years old under somebody's desk building the code that goes into there. >>It gets socially engineered. It gets at exactly. >>Yeah. It's like the, it's like the movies where they, uh, instead of breaking into jail, they hide in the food delivery truck. And it's, it's that, that's the metaphor that I like perfectly. The fence doesn't work. If your truck, if you open the door once a week, it doesn't matter how big defenses. Yeah. So that's >>Good Dallas funny. >>And I, I think too, like when I used to be an engineer before I joined Google, just like how easy it is to bring in a third party package or something, you know, you need like an image editing software, like just go find one off the internet. And I think, you know, developers are slowly doing a mind shift. They're like, Hey, if I introduce a new dependency, you know, there's going to be, I'm going to have to maintain this thing and understand >>It's a little bit of a decentralized view too. Also, you got a little bit of that. Hey, if you sign it, you own it. If it tracks back to you, okay, you are, your fingerprints are, if you will, or on that chain of >>Custody and custody. >>Exactly. I was going to say, when I saw chain guard at first of course, I thought that my pant leg riding a bike, but then of course the supply chain things coming in, like on a conveyor belt, conveyor, conveyor belt. But that, that whole question of chain of custody, it isn't, it isn't as simple as a process where someone grabs some code, embeds it in, what's going on, pushes it out somewhere else. That's not the final step typically. Yeah. >>So somebody else grabs that one. And does it again, 35 more times, >>The one, how do you verify that? That's yeah, it seems like an obvious issue that needs to be addressed. And yet, apparently from what you're telling us for quite a while, people thought you were a little bit in that, >>And it's not just me. I mean, not so Ken Thompson of bell labs and he wrote the book >>He wrote, yeah, it was a seatbelt that I grew >>Up on in the eighties. He gave a famous lecture called uh, reflections on trusting trust, where he pranked all of his colleagues at bell labs by putting a back door in a compiler. And that put back doors into every program that compiled. And he was so clever. He even put it in, he made that compiler put a backdoor into the disassembler to hide the back door. So he spent weeks and, you know, people just kind of gave up. And I think at that point they were just like, oh, we can't trust any software ever. And just forgot about it and kept going on and living their lives. So this is a 40 year old problem. We only care about it now. >>It's totally true. A lot of these old sacred cows. So I would have done life cycles, not really that relevant anymore because the workflows are changing. These new Bev changes. It's complete dev ops is taken over. Let's just admit it. Right. So if we have ops is taken over now, cloud native apps are hitting the scene. This is where I think there's a structural industry change, not just the community. So with that in mind, how do you guys vector into that in terms of a market entry? What's just thinking around product. Obviously you got a higher, did you guys raise some capital in process? A little bit of a capital raise five, no problem. Todd market, but product wise, you've got to come in, get the beachhead. >>I mean, we're, we're, we're casting a wide net right now and talking to as many customers like we've met a lot of these, these customer potential customers through the communities, you know, that we've been building and we did a supply chain security con helped with that event, this, this Monday to negative one event and solar winds and Citibank were there and talking about their solutions. Um, and so I think, you know, and then we'll narrow it down to like people that would make good partners to work with and figure out how they think they're solving the problem today. And really >>How do you guys feel good? You feel good? Well, we got Jerry Chen coming off from gray lock next round. He would get a term sheet, Jerry, this guy's got some action on it in >>There. Probably didn't reply to him on LinkedIn. >>He's coming out with Kronos for him. He just invested 200 million at CrossFit. So you guys should have a great time. Congratulations on the leap. I know it's comfortable to beat Google, a lot of things to work on. Um, and student startups are super fun too, but not easy. None of the female or, you know, he has done it before, so. Right. Cool. What do you think about today? Did the event here a little bit smaller, more VIP event? What's your takeaway on this? >>It's good to be back in person. Obviously we're meeting, we've been associating with folks over zoom and Google meets for a while now and meeting them in person as I go, Hey, no hard to recognize behind the mask, but yeah, we're just glad to sort of be back out in a little bit of normalization. >>Yeah. How's everything in Austin, everyone everyone's safe and good over there. >>Yeah. It's been a long, long pandemic. Lots of ups and downs, but yeah. >>Got to get the music scene back. Most of these are comes back in the house. Everything's all back to normal. >>Yeah. My hair doesn't normally look like this. I just haven't gotten a haircut since this also >>You're going to do well in this market. You got a term sheet like that. Keep the hair, just to get the money. I think I saw your LinkedIn profile and I was wondering it's like, which version are we going to get? Well, super relevant. Super great topic. Congratulations. Thanks for coming on. Sharing the story. You're in the queue. Great jumper. Dave Nicholson here on the cube date, one of three days we're back in person of course, hybrid event. Cause the cube.net for all more footage and highlights and remote interviews. So stay tuned more coverage after this short break.

>>Welcome to this cube conversation. I'm Dave Nicholson and we're having this conversation in advance of cube con cloud native con north America, 2021. Uh, we are going to be talking specifically about a subject near and dear to my heart, and that is security. We have a very special guest from red hat, the security lead from the office of the CTO. New kinds. Welcome. Welcome to the cube Luke. >>Oh, it's great to be here. Thank you, David. Really looking forward to this conversation. >>So you have a session, uh, at a CubeCon slash cloud native con this year. And, uh, frankly, I look at the title and based on everything that's going on in the world today, I'm going to accuse you of clickbait because the title of your session is a secure supply chain vision. Sure. What other than supply chain has is in the news today, all of these things going on, but you're talking about the software supply chain. Aren't you tell, tell us about, tell us about this vision, where it came from Phyllis in. >>Yes, very much. So I do agree. It is a bit of a buzzword at the moment, and there is a lot of attention. It is the hot topic, secure supply chains, thanks to things such as the executive order. And we're starting to see an increase in attacks as well. So there's a recent statistic came out that was 620%. I believe increase since last year of supply chain attacks involving the open source ecosystem. So things are certainly ramping up. And so there is a bit of clickbait. You got me there. And um, so supply chains, um, so it's predominantly let's consider what is a supply chain. Okay. And we'll, we'll do this within the context of cloud native technology. Okay. Cause there's many supply chains, you know, many, many different software supply chains. But if we look at a cloud native one predominantly it's a mix of people and machines. >>Okay. So you'll have your developers, uh, they will then write code. They will change code and they'll typically use our, a code revision control system, like get, okay, so they'll make their changes there. Then push those changes up to some sort of repository, typically a get Harbor or get level, something like that. Then another human will then engage and they will review the code. So somebody that's perhaps a maintain will look at the code and they'll improve that a code. And then at the same time, the machine start to get involved. So you have your build servers that run tests and integration tests and they check the code is linted correctly. Okay. And then you have this sort of chain of events that start to happen. These machines, these various actors that start to play their parts in the chain. Okay. So your build system might generate a container image is a very common thing within a cloud native supply chain. >>Okay. And then that image is typically deployed to production or it's hosted on a registry, a container registry, and then somebody else might utilize that container image because it has software that you've packaged within that container. Okay. And then this sort of prolific expansion of use of coasts where people start to rely on other software projects for their own dependencies within their code. Okay. And you've got this kind of a big spaghetti of actors that are dependent on each other and feed him from each other. Okay. And then eventually that is deployed into production. Okay. So these machines are a lot of them non open source code. Okay. Even if there is a commercial vendor that manages that as a service, it's all based on predominantly open source code. Okay. And the security aspects with the supply chain is there's many junctures where you can exploit that supply chain. >>So you can exploit the human, or you could be a net ferrous human in the first place you could steal somebody's identity. Okay. And then there's the build systems themselves where they generate these artifacts and they run jobs. Okay. And then there are the production system, which pulls these down. Okay. And then there's the element of which we touched upon around libraries and dependencies. So if you look at a lot of projects, they will have approximately around a hundred, perhaps 500 dependencies that they all pull in from. Okay. So then you have the supply chains within each one of those, they've got their own set of humans and machines. And so it's a very large spaghetti beast of, of, of sort of dependence and actors and various identities that make up. >>Yeah. You're, you're describing a nightmarish, uh, scenario here. So, uh, so, so I definitely appreciate the setup there. It's a chain of custody nightmare. Yeah. >>Yes. Yeah. But it's also a wonderful thing because it's allowed us to develop in the paradigms that we have now very fast, you know, you can, you can, you can prototype and design and build and ship very fast, thanks to these tools. So they're wonderful. It's not to say that they're, you know, that there is a gift there, but security has arguably been left as a bit of an afterthought essentially. Okay. So security is always trying to it's at the back of the race. It's always trying to catch up with you. See what I mean? So >>Well, so is there a specific reason why this is particularly timely? Um, in, you know, when we, when we talk about deployment of cloud native applications, uh, something like 75% of what we think of is it is still on premesis, but definitely moving in the direction of what we loosely call cloud. Um, is why is this particularly timely? >>I think really because of the rampant adoption that we see. So, I mean, as you rightly say, a lot of, uh, it companies are still running on a, sort of a, more of a legacy model okay. Where deployments are more monolithic and statics. I mean, we've both been around for a while when we started, you would, you know, somebody would rack a server, they plug a network cable and you'd spend a week deploying the app, getting it to run, and then you'd walk away and leave it to a degree. Whereas now obviously that's really been turned on its head. So there is a, an element of not everybody has adopted this new paradigm that we have in development, but it is increasing, there is rapid adoption here. And, and many that aren't many that rather haven't made that change yet to, to migrate to a sort of a cloud type infrastructure. >>They certainly intend to, well, they certainly wished to, I mean, there's challenges there in itself, but it, I would say it's a safe bet to say that the prolific use of cloud technologies is certainly increasing as we see in all the time. So that also means the attack vectors are increasing as we're starting to see different verticals come into this landscape that we have. So it's not just your kind of a sort of web developer that are running some sort of web two.site. We have telcos that are starting to utilize cloud technology with virtual network functions. Uh, we have, um, health banking, FinTech, all of these sort of large verticals are starting to come into cloud and to utilize the cloud infrastructure model that that can save them money, you know, and it can make them, can make their develop more agile and, you know, there's many benefits. So I guess that's the main thing is really, there's a convergence of industries coming into this space, which is starting to increase the security risks as well. Because I mean, the security risks to a telco are a very different group to somebody that's developing a web platform, for example. >>Yeah. Yeah. Now you, you, uh, you mentioned, um, the sort of obvious perspective from the open source perspective, which is that a lot of this code is open source code. Um, and then I also, I assume that it makes a lot of sense for the open source community to attack this problem, because you're talking about so many things in that chain of custody that you described where one individual private enterprise is not likely to be able to come up with something that handles all of it. So, so what's your, what's your vision for how we address this issue? I know I've seen in, um, uh, some of the content that you've produced an allusion to this idea that it's very similar to the concept of a secure HTTP. And, uh, and so, you know, imagine a world where HTTP is not secure at any time. It's something we can't imagine yet. We're living in this parallel world where, where code, which is one of the four CS and cloud security, uh, isn't secure. So what do we do about that? And, and, and as you share that with us, I want to dive in as much as we can on six store explain exactly what that is and, uh, how you came up with this. >>Yes, yes. So, so the HTTP story's incredibly apt for where we are. So around the open source ecosystem. Okay. We are at the HTTP stage. Okay. So a majority of code is pulled in on trusted. I'm not talking about so much here, somebody like a red hat or, or a large sort of distributor that has their own sign-in infrastructure, but more sort of in the, kind of the wide open source ecosystem. Okay. The, um, amount of code that's pulled in on tested is it's the majority. Okay. So, so it is like going to a website, which is HTTP. Okay. And we sort of use this as a vision related to six store and other projects that are operating in this space where what happened effectively was it was very common for sites to run on HTTP. So even the likes of Amazon and some of the e-commerce giants, they used to run on HTTP. >>Okay. And obviously they were some of the first to, to, uh, deploy TLS and to utilize TLS, but many sites got left behind. Okay. Because it was cumbersome to get the TLS certificate. I remember doing this myself, you would have to sort of, you'd have to generate some keys, the certificate signing request, you'd have to work out how to run open SSL. Okay. You would then go to an, uh, a commercial entity and you'd probably have to scan your passport and send it to them. And there'll be this kind of back and forth. Then you'll have to learn how to configure it on your machine. And it was cumbersome. Okay. So a majority just didn't bother. They just, you know, they continue to run their, their websites on protected. What effectively happened was let's encrypt came along. Okay. And they disrupted that whole paradigm okay. >>Where they made it free and easy to generate, procure, and set up TLS certificates. So what happened then was there was a, a very large change that the kind of the zeitgeists changed around TLS and the expectations of TLS. So it became common that most sites would run HTTPS. So that allowed the browsers to sort of ring fence effectively and start to have controls where if you're not running HTTPS, as it stands today, as it is today is kind of socially unacceptable to run a site on HTTP is a bit kind of, if you go to HTTP site, it feels a bit, yeah. You know, it's kind of, am I going to catch a virus here? It's kind of, it's not accepted anymore, you know, and, and it needed that disruptor to make that happen. So we want to kind of replicate that sort of change and movement and perception around software signing where a lot of software and code is, is not signed. And the reason it's not signed is because of the tools. It's the same story. Again, they're incredibly cumbersome to use. And the adoption is very poor as well. >>So SIG stores specifically, where did this, where did this come from? And, uh, and, uh, what's your vision for the future with six? >>Sure. So six door, six doors, a lockdown project. Okay. It started last year, July, 2020 approximately. And, uh, a few people have been looking at secure supply chain. Okay. Around that time, we really started to look at it. So there was various people looking at this. So it's been speaking to people, um, various people at Purdue university in Google and, and other, other sort of people trying to address this space. And I'd had this idea kicking around for quite a while about a transparency log. Okay. Now transparency logs are actually, we're going back to HTTPS again. They're heavily utilized there. Okay. So when somebody signs a HTTPS certificate as a root CA, that's captured in this thing called a transparency log. Okay. And a transparency log is effectively what we call an immutable tamper proof ledger. Okay. So it's, it's kind of like a blockchain, but it's different. >>Okay. And I had this idea of what, if we could leverage this technology okay. For secure supply chain so that we could capture the provenance of code and artifacts and containers, all of these actions, these actors that I described at the beginning in the supply chain, could we utilize that to provide a tamper resistant publicly or DePaul record of the supply chain? Okay. So I worked on a prototype wherever, uh, you know, some, uh, a week or two and got something basic happening. And it was a kind of a typical open source story there. So I wouldn't feel right to take all of the glory here. It was a bit like, kind of, you look at Linux when he created a Linux itself, Linus, Torvalds, he had an idea and he shared it out and then others started to jump in and collaborate. So it's a similar thing. >>I, um, shared it with an engineer from Google's open source security team called Dan Lawrence. Somebody that I know of been prolific in this space as well. And he said, I'd love to contribute to this, you know, so can I work this? And I was like, yeah, sure though, you know, the, the more, the better. And then there was also Santiago professor from Purdue university took an interest. So a small group of people started to work on this technology. So we built this project that's called Rico, and that was effectively the transparency log. So we started to approach projects to see if they would like to, to utilize this technology. Okay. And then we realized there was another problem. Okay. Which was, we now have a storage for signed artifacts. Okay. A signed record, a Providence record, but nobody's signing anything. So how are we going to get people to sign things so that we can then leverage this transparency log to fulfill its purpose of providing a public record? >>So then we had to look at the signing tools. Okay. So that's where we came up with this really sort of clever technology where we've managed to create something called ephemeral keys. Okay. So we're talking about a cryptographic key pair here. Okay. And what we could do we found was that we could utilize other technologies so that somebody wouldn't have to manage the private key and they could generate keys almost point and click. So it was an incredibly simple user experience. So then we realized, okay, now we've got an approach for getting people to sign things. And we've also got this immutable, publicly audited for record of people signing code and containers and artifacts. And that was the birth of six store. Then. So six store was created as this umbrella project of all of these different tools that were catering towards adoption of signing. And then being able to provide guarantees and protections by having this transparency log, this sort of blockchain type technology. So that was where we really sort of hit the killer application there. And things started to really lift off. And the adoption started to really gather steam then. >>So where are we now? And where does this go into the future? One of the, one of the wonderful things about the open source community is there's a sense of freedom in the creativity of coming up with a vision and then collaborating with others. Eventually you run headlong into expectations. So look, is this going to be available for purchase in Q1? What's the, >>Yeah, I, I will, uh, I will fill you in there. Okay. So, so with six door there's, um, there's several different models that are at play. Okay. I'll give you the, the two predominant ones. So one, we plan, we plan to run a public service. Okay. So this will be under the Linux foundation and it'll be very similar to let's encrypt. So you as a developer, if you want to sign your container, okay. And you want to use six door tooling that will be available to you. There'll be non-profit three to use. There's no specialties for anybody. It's, it's there for everybody to use. Okay. And that's to get everybody doing the right thing in signing things. Okay. The, the other model for six stories, this can be run behind a firewall as well. So an enterprise can stand up their own six store infrastructure. >>Okay. So the transparency log or code signing certificates, system, client tools, and then they can sign their own artifacts and secure, better materials, all of these sorts of things and have their own tamper-proof record of everything that's happened. So that if anything, untoward happens such as a key compromise or somebody's identity stolen, then you've got a credible source of truth because you've got that immutable record then. So we're seeing, um, adoption around both models. We've seen a lot of open source projects starting to utilize six store. So predominantly key, um, Kubernetes is a key one to mention here they are now using six store to sign and verify their release images. Okay. And, uh, there's many other open-source projects that are looking to leverage this as well. Okay. And then at the same time, various people are starting to consider six door as being a, sort of an enterprise signing solution. So within red hat, our expectations are that we're going to leverage this in open shift. So open shift customers who wish to sign their images. Okay. Uh, they want to sign their conflicts that they're using to deploy within Kubernetes and OpenShift. Rather they can start to leverage this technology as open shift customers. So we're looking to help the open source ecosystem here and also dog food, this, and make it available and useful to our own customers at red hat. >>Fantastic. You know, um, I noticed the red hat in the background and, uh, and, uh, you know, I just a little little historical note, um, red hat has been there from the beginning of cloud before, before cloud was cloud before there was anything credible from an enterprise perspective in cloud. Uh, I, I remember in the early two thousands, uh, doing work with tree AWS and, uh, there was a team of red hat folks who would work through the night to do kernel level changes for the, you know, for the Linux that was being used at the time. Uh, and so a lot of, a lot of what you and your collaborators do often falls into the category of, uh, toiling in obscurity, uh, to a certain degree. Uh, we hope to shine light on the amazing work that you're doing. And, um, and I, for one appreciate it, uh, I've uh, I've, I've suffered things like identity theft and, you know, we've all had brushes with experiences where compromise insecurity is not a good thing. So, um, this has been a very interesting conversation. And again, X for the work that you do, uh, do you have any other, do you have any other final thoughts or, or, uh, you know, points that we didn't cover on this subject that come to mind, >>There is something that you touched upon that I'd like to illustrate. Okay. You mentioned that, you know, identity theft and these things, well, the supply chain, this is critical infrastructure. Okay. So I like to think of this as you know, there's, sir, they're serving, you know, they're solving technical challenges and, you know, and the kind of that aspect of software development, but with the supply chain, we rely on these systems. When we wake up each morning, we rely on them to stay in touch with our loved ones. You know, we are our emergency services, our military, our police force, they rely on these supply chains, you know, so I sort of see this as there's a, there's a bigger vision here really in protecting the supply chain is, is for the good of our society, because, you know, a supply chain attack can go very much to the heart of our society. You know, it can, it can be an attack against our democracies. So I, you know, I see this as being something that's, there's a humanistic aspect to this as well. So that really gets me fired up to work on this technology., >>it's really important that we always keep that perspective. This isn't just about folks who will be attending CubeCon and, uh, uh, uh, cloud con uh, this is really something that's relevant to all of us. So, so with that, uh, fantastic conversation, Luke, it's been a pleasure to meet you. Pleasure to talk to you, David. I look forward to, uh, hanging out in person at some point, whatever that gets me. Uh, so with that, uh, we will sign off from this cube conversation in anticipation of cloud con cube con 2021, north America. I'm Dave Nicholson. Thanks for joining us.

>>mhm Yes. >>Welcome back to the Cube coverage of Red Hat summit 21 2021. I'm john for host of the Cubans virtual this year as we start preparing to come out of Covid a lot of great conversations here happening around technology. This is the emerging technology with Red hat segment. We've got three great guests steve watt manager, distinguished engineer at Red Hat hurl saying senior software engineer Red Hat and luke Hines, who's the senior software engineer as well. We got the engineering team steve, you're the the team leader, emerging tech within red hat. Always something to talk about. You guys have great tech chops that's well known in the industry and I'll see now part of IBM you've got a deep bench um what's your, how do you view emerging tech um how do you apply it? How do you prioritize, give us a quick overview of the emerging tech scene at Redhead? >>Yeah, sure. It's quite a conflated term. The way we define emerging technologies is that it's a technology that's typically 18 months plus out from commercialization and this can sometimes go six months either way. Another thing about it is it's typically not something on any of our product roadmaps within the portfolio. So in some sense, it's often a bit of a surprise that we have to react to. >>So no real agenda. And I mean you have some business unit kind of probably uh but you have to have first principles within red hat, but for this you're looking at kind of the moon shot, so to speak, the big game changing shifts. Quantum, you know, you got now supply chain from everything from new economics, new technology because that kind of getting it right. >>Yeah, I think we we definitely use a couple of different techniques to prioritize and filter what we're doing. And the first is something will pop up and it will be like, is it in our addressable market? So our addressable market is that we're a platform software company that builds enterprise software and so, you know, it's got to be sort of fit into that is a great example if somebody came up came to us with an idea for like a drone command center, which is a military application, it is an emerging technology, but it's something that we would pass on. >>Yeah, I mean I didn't make sense, but he also, what's interesting is that you guys have an open source D N A. So it's you have also a huge commercial impact and again, open sources of one of the 4th, 5th generation of awesomeness. So, you know, the good news is open source is well proven. But as you start getting into this more disruption, you've got the confluence of, you know, core cloud, cloud Native, industrial and IOT edge and data. All this is interesting, right. This is where the action is. How do you guys bring that open source community participation? You got more stakeholders emerging there before the break down, how that you guys manage all that complexity? >>Yeah, sure. So I think that the way I would start is that, you know, we like to act on good ideas, but I don't think good ideas come from any one place. And so we typically organize our teams around sort of horizontal technology sectors. So you've got, you know, luke who's heading up security, but I have an edge team, cloud networking team, a cloud storage team. Cloud application platforms team. So we've got these sort of different areas that we sort of attack work and opportunities, but you know, the good ideas can come from a variety of different places. So we try and leverage co creation with our customers and our partners. So as a good example of something we had to react to a few years ago, it was K Native right? So the sort of a new way of doing service um and eventing on top of kubernetes that was originated from google. Whereas if you look at Quantum right, ibms, the actual driver on quantum science and uh that originated from IBM were parole. We'll talk about exactly how we chose to respond to that. Some things are originated organically within the team. So uh luke talking about six law is a great example of that, but we do have a we sort of use the addressable market as a way to sort of focus what we're doing and then we try and land it within our different emerging technologies teams to go tackle it. Now. You asked about open source communities, which are quite interesting. Um so typically when you look at an open source project, it's it's there to tackle a particular problem or opportunity. Sometimes what you actually need commercial vendors to do is when there's a problem or opportunity that's not tackled by anyone open source project, we have to put them together to create a solution to go tackle that thing. That's also what we do. And so we sort of create this bridge between red hat and our customers and multiple different open source projects. And this is something we have to do because sometimes just that one open source project doesn't really care that much about that particular problem. They're motivated elsewhere. And so we sort of create that bridge. >>We got two great uh cohorts here and colleagues parole on the on the Quantum side and you got luke on the security side. Pro I'll start with you. Quantum is also a huge mentioned IBM great leadership there. Um Quantum on open shift. I mean come on. Just that's not coming together for me in my mind, it's not the first thing I think of. But it really that sounds compelling. Take us through, you know, um how this changes the computing landscape because heterogeneous systems is what we want and that's the world we live in. But now with distributed systems and all kinds of new computing modules out there, how does this makes sense? Take us through this? >>Um yeah john's but before I think I want to explain something which is called Quantum supremacy because it plays very important role in the road map that's been working on. So uh content computers, they are evolving and they have been around. But right now you see that they are going to be the next thing. And we define quantum supremacy as let's say you have any program that you run or any problems that you solve on a classical computer. Quantum computer would be giving you the results faster. So that is uh, that is how we define content supremacy when the same workload are doing better on content computer than they do in a classical computer. So the whole the whole drive is all the applications are all the companies, they're trying to find avenues where Quantum supremacy are going to change how they solve problems or how they run their applications. And even though quantum computers they are there. But uh, it is not as easily accessible for everyone to consume because it's it's a very new area that's being formed. So what, what we were thinking, how we can provide a mechanism that you can you don't connect this deal was you have a classical world, you have a country world and that's where a lot of thought process been. And we said okay, so with open shift we have the best of the classical components. You can take open shift, you can develop, deploy around your application in a country raised platform. What about you provide a mechanism that the world clothes that are running on open shift. They are also consuming quantum resources or they are able to run the competition and content computers take the results and integrate them in their normal classical work clothes. So that is the whole uh that was the whole inception that we have and that's what brought us here. So we took an operator based approach and what we are trying to do is establish the best practices that you can have these heterogeneous applications that can have classical components. Talking to our interacting the results are exchanging data with the quantum components. >>So I gotta ask with the rise of containers now, kubernetes at the center of the cloud native value proposition, what work clothes do you see benefiting from the quantum systems the most? Is there uh you guys have any visibility on some of those workloads? >>Uh So again, it's it's a very new, it's very it's really very early in the time and uh we talk with our customers and every customers, they are trying to identify themselves first where uh these contacts supremacy will be playing the role. What we are trying to do is when they reach their we should have a solution that they that they could uh use the existing in front that they have on open shift and use it to consume the content computers that may or may not be uh, inside their own uh, cloud. >>Well I want to come back and ask you some of the impact on the landscape. I want to get the look real quick because you know, I think security quantum break security, potentially some people have been saying, but you guys are also looking at a bunch of projects around supply chain, which is a huge issue when it comes to the landscape, whether its components on a machine in space to actually handling, you know, data on a corporate database. You guys have sig store. What's this about? >>Sure. Yes. So sick store a good way to frame six store is to think of let's encrypt and what let's encrypt did for website encryption is what we plan to do for software signing and transparency. So six Door itself is an umbrella organization that contains various different open source projects that are developed by the Six door community. Now, six door will be brought forth as a public good nonprofit service. So again, we're very much basing this on the successful model of let's Encrypt Six door will will enable developers to sign software artifacts, building materials, containers, binaries, all of these different artifacts that are part of the software supply chain. These can be signed with six door and then these signing events are recorded into a technology that we call a transparency log, which means that anybody can monitor signing events and a transparency log has this nature of being read only and immutable. It's very similar to a Blockchain allows you to have cryptographic proof auditing of our software supply chain and we've made six stores so that it's easy to adopt because traditional cryptographic signing tools are a challenge for a lot of developers to implement in their open source projects. They have to think about how to store the private keys. Do they need specialist hardware? If they were to lose a key then cleaning up afterwards the blast radius. So the key compromise can be incredibly difficult. So six doors role and purpose essentially is to make signing easy easy to adopt my projects. And then they have the protections around there being a public transparency law that could be monitored. >>See this is all about open. Being more open. Makes it more secure. Is the >>thief? Very much yes. Yes. It's that security principle of the more eyes on the code the better. >>So let me just back up, is this an open, you said it's gonna be a nonprofit? >>That's correct. Yes. Yes. So >>all of the code is developed by the community. It's all open source. anybody can look at this code. And then we plan alongside the Linux Foundation to launch a public good service. So this will make it available for anybody to use if your nonprofit free to use service. >>So luke maybe steve if you can way into on this. I mean, this goes back. If you look back at some of the early cloud days, people were really trashing cloud as there's no security. And cloud turns out it's a more security now with cloud uh, given the complexity and scale of it, does that apply the same here? Because I feel this is a similar kind of concept where it's open, but yet the more open it is, the more secure it is. And then and then might have to be a better fit for saying I. T. Security solution because right now everyone is scrambling on the I. T. Side. Um whether it's zero Trust or Endpoint Protection, everyone's kind of trying everything in sight. This is kind of changing the paradigm a little bit on software security. Could you comment on how you see this playing out in traditional enterprises? Because if this plays out like the cloud, open winds, >>so luke, why don't you take that? And then I'll follow up with another lens on it which is the operate first piece. >>Sure. Yes. So I think in a lot of ways this has to be open this technology because this way we have we have transparency. The code can be audited openly. Okay. Our operational procedures can be audit openly and the community can help to develop not only are code but our operational mechanisms so we look to use technology such as cuba netease, open ship operators and so forth. Uh Six store itself runs completely in a cloud. It is it is cloud native. Okay, so it's very much in the paradigm of cloud and yeah, essentially security, always it operates better when it's open, you know, I found that from looking at all aspects of security over the years that I've worked in this realm. >>Okay, so just just to add to that some some other context around Six Law, that's interesting, which is, you know, software secure supply chain, Sixth floor is a solution to help build more secure software secure supply chains, more secure software supply chain. And um so um there's there's a growing community around that and there's an ecosystem of sort of cloud native kubernetes centric approaches for building more secure software. I think we all caught the solar winds attack. It's sort of enterprise software industry is responding sort of as a whole to go and close out as many of those gaps as possible, reduce the attack surface. So that's one aspect about why 6th was so interesting. Another thing is how we're going about it. So we talked about um you mentioned some of the things that people like about open source, which is one is transparency, so sunlight is the best disinfectant, right? Everybody can see the code, we can kind of make it more secure. Um and then the other is agency where basically if you're waiting on a vendor to go do something, um if it's proprietary software, you you really don't have much agency to get that vendor to go do that thing. Where is the open source? If you don't, if you're tired of waiting around, you can just submit the patch. So, um what we've seen with package software is with open source, we've had all this transparency and agency, but we've lost it with software as a service, right? Where vendors or cloud service providers are taking package software and then they're making it available as a service but that operationalize ng that software that is proprietary and it doesn't get contributed back. And so what Lukes building here as long along with our partners down, Lawrence from google, very active contributor in it. Um, the, is the operational piece to actually run sixth or as a public service is part of the open source project so people can then go and take sixth or maybe run it as a smaller internal service. Maybe they discover a bug, they can fix that bug contributed back to the operational izing piece as well as the traditional package software to basically make it a much more robust and open service. So you bring that transparency and the agency back to the SAS model as well. >>Look if you don't mind before, before uh and this segment proportion of it. The importance of immune ability is huge in the world of data. Can you share more on that? Because you're seeing that as a key part of the Blockchain for instance, having this ability to have immune ability. Because you know, people worry about, you know, how things progress in this distributed world. You know, whether from a hacking standpoint or tracking changes, Mutability becomes super important and how it's going to be preserved in this uh new six doorway. >>Oh yeah, so um mutability essentially means cannot be changed. So the structure of something is set. If it is anyway tampered or changed, then it breaks the cryptographic structure that we have of our public transparency service. So this way anybody can effectively recreate the cryptographic structure that we have of this public transparency service. So this mutability provides trust that there is non repudiation of the data that you're getting. This data is data that you can trust because it's built upon a cryptographic foundation. So it has very much similar parallels to Blockchain. You can trust Blockchain because of the immutable nature of it. And there is some consensus as well. Anybody can effectively download the Blockchain and run it themselves and compute that the integrity of that system can be trusted because of this immutable nature. So that's why we made this an inherent part of Six door is so that anybody can publicly audit these events and data sets to establish that there tamper free. >>That is a huge point. I think one of the things beyond just the security aspect of being hacked and protecting assets um trust is a huge part of our society now, not just on data but everything, anything that's reputable, whether it's videos like this being deep faked or you know, or news or any information, all this ties to security again, fundamentally and amazing concepts. Um I really want to keep an eye on this great work. Um Pearl, I gotta get back to you on Quantum because again, you can't, I mean people love Quantum. It's just it feels like so sci fi and it's like almost right here, right, so close and it's happening. Um And then people get always, what does that mean for security? We go back to look and ask them well quantum, you know, crypto But before we get started I wanted, I'm curious about how that's gonna play out from the project because is it going to be more part of like a C. N. C. F. How do you bring the open source vibe to Quantum? >>Uh so that's a very good question because that was a plan, the whole work that we are going to do related to operators to enable Quantum is managed by the open source community and that project lies in the casket. So casket has their own open source community and all the modification by the way, I should first tell you what excuse did so cute skin is the dedicate that you use to develop circuits that are run on IBM or Honeywell back in. So there are certain Quantum computers back and that support uh, circuits that are created using uh Houston S ticket, which is an open source as well. So there is already a community around this which is the casket. Open source community and we have pushed the code and all the maintenance is taken care of by that community. Do answer your question about if we are going to integrate it with C and C. F. That is not in the picture right now. We are, it has a place in its own community and it is also very niche to people who are working on the Quantum. So right now you have like uh the contributors who who are from IBM as well as other uh communities that are specific specifically working on content. So right now I don't think so, we have the map to integrated the C. N. C. F. But open source is the way to go and we are on that tragic Torri >>you know, we joke here the cube that a cubit is coming around the corner can can help but we've that in you know different with a C. But um look, I want to ask you one of the things that while you're here your security guru. I wanted to ask you about Quantum because a lot of people are scared that Quantum is gonna crack all the keys on on encryption with his power and more hacking. You're just comment on that. What's your what's your reaction to >>that? Yes that's an incredibly good question. This will occur. Okay. And I think it's really about preparation more than anything now. One of the things that we there's a principle that we have within the security world when it comes to coding and designing of software and this aspect of future Cryptography being broken. As we've seen with the likes of MD five and Sha one and so forth. So we call this algorithm agility. So this means that when you write your code and you design your systems you make them conducive to being able to easily swap and pivot the algorithms that use. So the encryption algorithms that you have within your code, you do not become too fixed to those. So that if as computing gets more powerful and the current sets of algorithms are shown to have inherent security weaknesses, you can easily migrate and pivot to a stronger algorithms. So that's imperative. Lee is that when you build code, you practice this principle of algorithm agility so that when shot 256 or shot 5 12 becomes the shar one. You can swap out your systems. You can change the code in a very least disruptive way to allow you to address that floor within your within your code in your software projects. >>You know, luke. This is mind bender right there. Because you start thinking about what this means is when you think about algorithmic agility, you start thinking okay software countermeasures automation. You start thinking about these kinds of new trends where you need to have that kind of signature capability. You mentioned with this this project you're mentioning. So the ability to actually who signs off on these, this comes back down to the paradigm that you guys are talking about here. >>Yes, very much so. There's another analogy from the security world, they call it turtles all the way down, which is effectively you always have to get to the point that a human or a computer establishes that first point of trust to sign something off. And so so it is it's a it's a world that is ever increasing in complexity. So the best that you can do is to be prepared to be as open as you can to make that pivot as and when you need to. >>Pretty impressive, great insight steve. We can talk for hours on this panel, emerging tech with red hat. Just give us a quick summary of what's going on. Obviously you've got a serious brain trust going on over there. Real world impact. You talk about the future of trust, future of software, future of computing, all kind of going on real time right now. This is not so much R and D as it is the front range of tech. Give us a quick overview of >>Yeah, sure, yeah, sure. The first thing I would tell everyone is go check out next that red hat dot com, that's got all of our different projects, who to contact if you're interested in learning more about different areas that we're working on. And it also lists out the different areas that we're working on, but just as an overview. So we're working on software defined storage, cloud storage. Sage. Well, the creator of Cf is the person that leads that group. We've got a team focused on edge computing. They're doing some really cool projects around um very lightweight operating systems that and kubernetes, you know, open shift based deployments that can run on, you know, devices that you screw into the sheet rock, you know, for that's that's really interesting. Um We have a cloud networking team that's looking at over yin and just intersection of E B P F and networking and kubernetes. Um and then uh you know, we've got an application platforms team that's looking at Quantum, but also sort of how to advance kubernetes itself. So that's that's the team where you got the persistent volume framework from in kubernetes and that added block storage and object storage to kubernetes. So there's a lot of really exciting things going on. Our charter is to inform red hats long term technology strategy. We work the way my personal philosophy about how we do that is that Red hat has product engineering focuses on their product roadmap, which is by nature, you know, the 6 to 9 months. And then the longer term strategy is set by both of us. And it's just that they're not focused on it. We're focused on it and we spend a lot of time doing disambiguate nation of the future and that's kind of what we do. We love doing it. I get to work with all these really super smart people. It's a fun job. >>Well, great insights is super exciting, emerging tack within red hat. I'll see the industry. You guys are agile, your open source and now more than ever open sources, uh, product Ization of open source is happening at such an accelerated rate steve. Thanks for coming on parole. Thanks for coming on luke. Great insight all around. Thanks for sharing. Uh, the content here. Thank you. >>Our pleasure. >>Thank you. >>Okay. We were more, more redhead coverage after this. This video. Obviously, emerging tech is huge. Watch some of the game changing action here at Redhead Summit. I'm john ferrier. Thanks for watching. Yeah.

>>Yeah. >>Okay. Now we're going to look deeper into the intersection of technology and money and actually a force for good mobile. And the infrastructure around it has made sending money as easy as sending a text. But the capabilities that enable this to happen are quite amazing, especially because as users, we don't see the underlying complexity of the transactions. We just enjoy the benefits. And there's many parts of the world that historically have not been able to enjoy the benefits. And the ecosystems that are developing around these new platforms are truly transformative. And with me to explain, the business impacts of these innovations is all a person who is the head of mobile financial services at Ericsson Ola. Welcome to the program. Thanks for coming on. >>Thank you. Dave, Thank you for having me here in the program and really excited to tell me. Tell us about the product that we have within Ericsson. >>Okay, well, let's get right into it. I mean, your firm has developed the Ericsson wallet platform. What is that? Yes, >>so? So the wallet platform is one of the product, but, I mean, you can say offer here by Ericsson and the platform is built on enabled financial services not for only the bank segment, but also for the unbanked. And we have, you know, the function that we are providing as such Here is, uh, both transfer the service provided payment. You have the cash in the cash out. You have a lot of other feature that we kind of a neighbor through the ecosystem as such. And, uh, I would really like you say, to emphasize on on the use, and they really I'll say, uh, connectivity that we have in this platform here because, uh, looking at you can say the pandemic as such here. Now, we really have made you can say tremendous Shane here through all the functions etcetera feature that we have here. >>Yeah, so, I mean, I'm surrounded by banks in Massachusetts, right? No problem. I'm Boston, right? So But there's a lot of places in the world that that aren't I take for granted some of the capabilities that are there, but so part of this is to enable people who don't have access to those types of services. So maybe you could talk about that and talk about some of the things that you're enabling with the platform, >>right? So So you just think of their You can say unbanked people here, But we have across the emerging market. I think we have one point, you know, seven billion unbanked people here, but we actually can, through wallet platform enabled through getting a bank account, etcetera, and so on here and what we're actually providing you can say in this, uh, this feature is here is that you can pay your electricity bill, for example, Here, you can pay your your bill and you you can go through merchants. You can do the cashed out. You can do multiple thing here, just like I mean to to enable the the question that financial inclusion as well. So I mean I mean from from my point of view, where we're sitting, as I said, we also sitting in Sweden, we have bank account. We have something called swish where we send you can say money back, back and forward between the family, etcetera. So, on this type of transaction, we can and have enabled for all you can say, the user that I come across the the platform here and the kind of growth that we have within this usage here and and we're seeing also. I mean, we leverage here to get with a speed today on a fantastic scale that we actually have here with our our both you can say feature performers going, I will say, Really in in in in a in the direction that we couldn't imagine here you can say a few years back here. So it is fantastic transformation that we undergo here through through the platform of the technology that we have. >>You know, it reminds me of sort of the early days of mobile people talked about being able to connect, you know, remote users in places like Africa or other parts of the world that that haven't been able to enjoy things like a landline. Uh, and so I presume you're seeing a lot of interest in in those types of regions. Maybe you could talk about that a little bit. >>Yeah. Yeah, correct. I mean, I mean, we we see all of this region here, but for for example, Uh uh. Now, we we, uh we were not only entering, you can say the the, uh, specifically the African region, but also you can say the Middle East and the the the A C a specific and also actually Latin America. I mean, a lot of this country here are looking into you can say the expansion, how they can evolve. You can say the financial inclusion from what they have today, when they are, and you can say firm telecom provider, they would like to have an asset of different use case here, and we're seeing that transformation. But we have right now from just voice, you can say SMS and five year etcetera so on. This is the platform that we have to sort of enable the transaction for for a mobile financial system. But we would like also to see that the kind of operator or evolving the business with much more feature here. And this is another. You can say I was attraction to attract the user with the mobile transfer system. So we we we see this kind of expanding very heavily in this this kind of market. >>I think this is really transformative. I mean, in terms of people's lives. I mean, first of all, you're talking about the convenience of being able to move money as bits as opposed to paper, but as well I would think supporting entrepreneurship and business is getting started. I mean, there's a whole set of cultural and societal impacts that that you're having. How do you see that >>we we also providing you say I mean the world to such is also supporting, say microloans and need as an entrepreneur is to sort of start you can say any kind of company, but you need to kind of business around here. So we have seen that we have sort of enterprise services across function and the whole asset that we are that we are into today >>talking a little bit >>about >>partnerships and the ecosystems. I know you've got big partnerships with HPD. We're going to get to that. They're kind of a technology operator, but But what about, you know, other partnerships, like, I'm imagining that if I'm gonna pay my my my bill with this, you've got other providers that got to connect into your platform. So So how are those ecosystem partnerships evolving? >>Well, we are kind of the enabler, but we are providing to the operator the partnerships is then going through the operator. It could be any kind of you can say external instrument that we have today and the kind of you can go directly to the bank. You can go directly to any court provider. You have these amongst the court, etcetera and so on. But these are all partners of the and you can stay connected through there. You can say operator assault today. So what we're doing actually, with our platform is to kind of make the enable them to kind of provide the food ecosystem as partnership to to operate as us today. Here, So that that's kind of the baseline that we see how you can say we are sort of supporting of building the full ecosystem around the platform in order to connect here has come to both the like, the card. As I said here, the merchant, the bank, any kind of type of you can say I will say service provider here, but that we can see could enable the ecosystem >>okay. And so I mean, I don't want to geek out here, but it sounds like it's an open system that my developers can plug into through a p i s They're not gonna throw cold water on that. They're going to embrace it. So yeah, this is actually easy for me to integrate with, Is that correct? >>Correct. Correct. And they open API that we're actually providing today. I think that you can say there are five thousands of you can say developer, just you can say connecting to our system. And actually, we're also providing both sandbox and and other application in order to support this developers in order to to kind of create this ecosystem here. So it's a multiple things that we we see through you can say, hear, hear the both the partners partnership the open API or you can say the development that is doing through through the channels. So I mean, it's a fascinating, amazing development that we see up front here right now. >>Now, what's H. P s role in all this? What are they providing? How are you partnering with them? >>So it's very good question, I would say. And we we look back, you can say and we we have evaluated a lot of you say that the provider fruit year here, And, uh, you can just imagine the the kind of, uh, stability that we need to provide when it comes to the financial inclusion system here because what we need to have a very strong uptake of, uh, making sure that we don't both go with the performance and the stability and what we have seen in our lab is that hypocrisy today is we have domestically evolved how you can say our stability assessed on the system. And right now we are leveraging the the dog is with the microservices here, together with HV on the platform that you're providing. So I will say that the transformation we have done in the stability that we have get through the food. You can say HP system is really fantastic at the moment. >>Well, and you know, I'm no security expert, but I talked to a lot of security experts and what I what I do know is they tell me that that you can't just bolt security on. It's got to be designed in from the start. I would imagine that that's part of the HPD partnership. But what about security? Can I fully trust this platform >>now? It's It's very, very valid question. I would say we we have one of the most you can say secure system here were also running multiple external. You can say, uh, system validation there is called The PNDs s certification is a certification, But we we have external auditor, you can say trying to breach the system. Look at the process that we are developing making sure that we have You can say all of you can say the documentation really in shape and seeing that we follow the procedure when we are both developing the code and and also when we're looking into all the a p I s that were actually exposed to to to our end users. So I would say that we haven't had any bridge on our system and we we really working tightly. I'll say both together with I'll say, H b and and of course, the the customer, such and? And every time we do a Lawrence, we also make you can say final security validation on the system here in order to sort of see that we have and and two and because the application that is completely secure, So so that that that that's a very, very important topic. For from our point of view, >>Yeah, because it's the usual. I don't even want to think about that. Like I set up front. It's It's got to be hidden from me, all that complexity. But there's sort of the same question around compliance and privacy. I mean, often security, privacy. There's sort of two sides of the same coin, but compliance privacy You've got to worry about K. Y. C Know your customer? Uh, there's a lot of complexity around that, and and so that's another key piece. >>Mhm Now. Like you said, the K Y C is an important part that we have fully support in our system and we validate. You can say all the uses We we also are running, You can say with our credit scoring companies that the you can say our operator or are partnering with. So this combined, you can say, with both the K Y C and then and the credit scoring. But there were performing that. Let's make us a very you can say unique, stable platform as such. >>Okay, last question is, is what about going forward? What's the road map look like? What can you share? What should we expect going forward in terms of the impact that this will have on society and how the technology will evolve. >>Well, what is he going forward? And that's a very interesting question, because what we what we see right now is how we we we kind of have changed the life for for so many. You can say unbanked people here and we would like to have You can say, uh, any kind of assets that going forward here, any kind of you can see that the digital currency is a bouldering through both government. You can see over top players like Google. You can say, What's up all of these things. Here we want to be the one, but also connecting. You can say this type of platform together and see that we could be the heart of the ecosystem going forward here, independent in what kind of you can say customer we're aiming for. So I would say this This is kind of the role that we will play in the future here, depending on what kind of currency it would be. So it's very interesting future we see. With this, you can say abroad digital currency in the market and the trends that we are now right now, evolving on >>very exciting when we're talking about elevating, you know, potentially billions of people all, uh, thanks very much for sharing this innovation with the audience. And best of luck with this incredible platform. Congratulations. >>Thank you so much, Dave. And once again, thank you for having me here, and I'll talk to you soon again. Thank you. >>Thank you. It's been our pleasure. And thank you for watching. This is Dave Valenti. >>Yeah. Mhm. Yeah. Mhm. Okay.

>> Narrator: From around the globe, it's theCUBE with digital coverage of Exascale day, made possible by Hewlett Packard Enterprise. >> Hey, welcome back Jeff Frick here with the cube come due from our Palo Alto studios, for their ongoing coverage in the celebration of Exascale day 10 to the 18th on October 18th, 10 with 18 zeros, it's all about big powerful giant computing and computing resources and computing power. And we're excited to invite back our next guest she's been on before. She's Dr. Arti Garg, head of advanced AI solutions and technologies for HPE. Arti great to see you again. >> Great to see you. >> Absolutely. So let's jump into before we get into Exascale day I was just looking at your LinkedIn profile. It's such a very interesting career. You've done time at Lawrence Livermore, You've done time in the federal government, You've done time at GE and industry, I just love if you can share a little bit of your perspective going from hardcore academia to, kind of some government positions, then into industry as a data scientist, and now with originally Cray and now HPE looking at it really from more of a vendor side. >> Yeah. So I think in some ways, I think I'm like a lot of people who've had the title of data scientists somewhere in their history where there's no single path, to really working in this industry. I come from a scientific background. I have a PhD in physics, So that's where I started working with large data sets. I think of myself as a data scientist before the term data scientist was a term. And I think it's an advantage, to be able to have seen this explosion of interest in leveraging data to gain insights, whether that be into the structure of the galaxy, which is what I used to look at, or whether that be into maybe new types of materials that could advance our ability to build lightweight cars or safety gear. It's allows you to take a perspective to not only understand what the technical challenges are, but what also the implementation challenges are, and why it can be hard to use data to solve problems. >> Well, I'd just love to get your, again your perspective cause you are into data, you chose that as your profession, and you probably run with a whole lot of people, that are also like-minded in terms of data. As an industry and as a society, we're trying to get people to do a better job of making database decisions and getting away from their gut and actually using data. I wonder if you can talk about the challenges of working with people who don't come from such an intense data background to get them to basically, I don't know if it's understand the value of more of a data kind decision making process or board just it's worth the effort, cause it's not easy to get the data and cleanse the data, and trust the data and get the right context, working with people that don't come from that background. And aren't so entrenched in that point of view, what surprises you? How do you help them? What can you share in terms of helping everybody get to be a more data centric decision maker? >> So I would actually rephrase the question a little bit Jeff, and say that actually I think people have always made data driven decisions. It's just that in the past we maybe had less data available to us or the quality of it was not as good. And so as a result most organizations have developed organize themselves to make decisions, to run their processes based on a much smaller and more refined set of information, than is currently available both given our ability to generate lots of data, through software and sensors, our ability to store that data. And then our ability to run a lot of computing cycles and a lot of advanced math against that data, to learn things that maybe in the past took, hundreds of years of experiments in scientists to understand. And so before I jumped into, how do you overcome that barrier? Just I'll use an example because you mentioned, I used to work in industry I used to work at GE. And one of the things that I often joked about, is the number of times I discovered Bernoulli's principle, in data coming off a GE jet engines you could do that overnight processing these large data but of course historically that took hundreds of years, to really understand these physical principles. And so I think when it comes to how do we bridge the gap between people who are adapt at processing large amounts of data, and running algorithms to pull insights out? I think it's both sides. I think it's those of us who are coming from the technical background, really understanding the way decisions are currently made, the way process and operations currently work at an organization. And understanding why those things are the way they are maybe their security or compliance or accountability concerns, that a new algorithm can't just replace those. And so I think it's on our end, really trying to understand, and make sure that whatever new approaches we're bringing address those concerns. And I think for folks who aren't necessarily coming from a large data set, and analytical background and when I say analytical, I mean in the data science sense, not in the sense of thinking about things in an abstract way to really recognize that these are just tools, that can enhance what they're doing, and they don't necessarily need to be frightening because I think that people who have been say operating electric grids for a long time, or fixing aircraft engines, they have a lot of expertise and a lot of understanding, and that's really important to making any kind of AI driven solution work. >> That's great insight but that but I do think one thing that's changed you come from a world where you had big data sets, so you kind of have a big data set point of view, where I think for a lot of decision makers they didn't have that data before. So we won't go through all the up until the right explosions of data, and obviously we're talking about Exascale day, but I think for a lot of processes now, the amount of data that they can bring to bear, is so dwarfs what they had in the past that before they even consider how to use it they still have to contextualize it, and they have to manage it and they have to organize it and there's data silos. So there's all this kind of nasty processes stuff, that's in the way some would argue has been kind of a real problem with the promise of BI, and does decision support tools. So as you look at at this new stuff and these new datasets, what are some of the people in process challenges beyond the obvious things that we can think about, which are the technical challenges? >> So I think that you've really hit on, something I talk about sometimes it was kind of a data deluge that we experienced these days, and the notion of feeling like you're drowning in information but really lacking any kind of insight. And one of the things that I like to think about, is to actually step back from the data questions the infrastructure questions, sort of all of these technical questions that can seem very challenging to navigate. And first ask ourselves, what problems am I trying to solve? It's really no different than any other type of decision you might make in an organization to say like, what are my biggest pain points? What keeps me up at night? or what would just transform the way my business works? And those are the problems worth solving. And then the next question becomes, if I had more data if I had a better understanding of something about my business or about my customers or about the world in which we all operate, would that really move the needle for me? And if the answer is yes, then that starts to give you a picture of what you might be able to do with AI, and it starts to tell you which of those data management challenges, whether they be cleaning the data, whether it be organizing the data, what it, whether it be building models on the data are worth solving because you're right, those are going to be a time intensive, labor intensive, highly iterative efforts. But if you know why you're doing it, then you will have a better understanding of why it's worth the effort. And also which shortcuts you can take which ones you can't, because often in order to sort of see the end state you might want to do a really quick experiment or prototype. And so you want to know what matters and what doesn't at least to that. Is this going to work at all time. >> So you're not buying the age old adage that you just throw a bunch of data in a data Lake and the answers will just spring up, just come right back out of the wall. I mean, you bring up such a good point, It's all about asking the right questions and thinking about asking questions. So again, when you talk to people, about helping them think about the questions, cause then you've got to shape the data to the question. And then you've got to start to build the algorithm, to kind of answer that question. How should people think when they're actually building algorithm and training algorithms, what are some of the typical kind of pitfalls that a lot of people fall in, haven't really thought about it before and how should people frame this process? Cause it's not simple and it's not easy and you really don't know that you have the answer, until you run multiple iterations and compare it against some other type of reference? >> Well, one of the things that I like to think about just so that you're sort of thinking about, all the challenges you're going to face up front, you don't necessarily need to solve all of these problems at the outset. But I think it's important to identify them, is I like to think about AI solutions as, they get deployed being part of a kind of workflow, and the workflow has multiple stages associated with it. The first stage being generating your data, and then starting to prepare and explore your data and then building models for your data. But sometimes I think where we don't always think about it is the next two phases, which is deploying whatever model or AI solution you've developed. And what will that really take especially in the ecosystem where it's going to live. If is it going to live in a secure and compliant ecosystem? Is it actually going to live in an outdoor ecosystem? We're seeing more applications on the edge, and then finally who's going to use it and how are they going to drive value from it? Because it could be that your AI solution doesn't work cause you don't have the right dashboard, that highlights and visualizes the data for the decision maker who will benefit from it. So I think it's important to sort of think through all of these stages upfront, and think through maybe what some of the biggest challenges you might encounter at the Mar, so that you're prepared when you meet them, and you can kind of refine and iterate along the way and even upfront tweak the question you're asking. >> That's great. So I want to get your take on we're celebrating Exascale day which is something very specific on 1018, share your thoughts on Exascale day specifically, but more generally I think just in terms of being a data scientist and suddenly having, all this massive compute power. At your disposal yoy're been around for a while. So you've seen the development of the cloud, these huge data sets and really the ability to, put so much compute horsepower against the problems as, networking and storage and compute, just asymptotically approach zero, I mean for as a data scientist you got to be pretty excited about kind of new mysteries, new adventures, new places to go, that we just you just couldn't do it 10 years ago five years ago, 15 years ago. >> Yeah I think that it's, it'll--only time will tell exactly all of the things that we'll be able to unlock, from these new sort of massive computing capabilities that we're going to have. But a couple of things that I'm very excited about, are that in addition to sort of this explosion or these very large investments in large supercomputers Exascale super computers, we're also seeing actually investment in these other types of scientific instruments that when I say scientific it's not just academic research, it's driving pharmaceutical drug discovery because we're talking about these, what they call light sources which shoot x-rays at molecules, and allow you to really understand the structure of the molecules. What Exascale allows you to do is, historically it's been that you would go take your molecule to one of these light sources and you shoot your, x-rays edit and you would generate just masses and masses of data, terabytes of data it was each shot. And being able to then understand, what you were looking at was a long process, getting computing time and analyzing the data. We're on the precipice of being able to do that, if not in real time much closer to real time. And I don't really know what happens if instead of coming up with a few molecules, taking them, studying them, and then saying maybe I need to do something different. I can do it while I'm still running my instrument. And I think that it's very exciting, from the perspective of someone who's got a scientific background who likes using large data sets. There's just a lot of possibility of what Exascale computing allows us to do in from the standpoint of I don't have to wait to get results, and I can either stimulate much bigger say galaxies, and really compare that to my data or galaxies or universes, if you're an astrophysicist or I can simulate, much smaller finer details of a hypothetical molecule and use that to predict what might be possible, from a materials or drug perspective, just to name two applications that I think Exascale could really drive. >> That's really great feedback just to shorten that compute loop. We had an interview earlier in some was talking about when the, biggest workload you had to worry about was the end of the month when you're running your financial, And I was like, why wouldn't that be nice to be the biggest job that we have to worry about? But now I think we saw some of this at animation, in the movie business when you know the rendering for whether it's a full animation movie, or just something that's a heavy duty three effects. When you can get those dailies back to the, to the artist as you said while you're still working, or closer to when you're working versus having this, huge kind of compute delay, it just changes the workflow dramatically and the pace of change and the pace of output. Because you're not context switching as much and you can really get back into it. That's a super point. I want to shift gears a little bit, and talk about explainable AI. So this is a concept that a lot of people hopefully are familiar with. So AI you build the algorithm it's in a box, it runs and it kicks out an answer. And one of the things that people talk about, is we should be able to go in and pull that algorithm apart to know, why it came out with the answer that it did. To me this just sounds really really hard because it's smart people like you, that are writing the algorithms the inputs and the and the data that feeds that thing, are super complex. The math behind it is very complex. And we know that the AI trains and can change over time as you you train the algorithm it gets more data, it adjusts itself. So it's explainable AI even possible? Is it possible at some degree? Because I do think it's important. And my next question is going to be about ethics, to know why something came out. And the other piece that becomes so much more important, is as we use that output not only to drive, human based decision that needs some more information, but increasingly moving it over to automation. So now you really want to know why did it do what it did explainable AI? Share your thoughts. >> It's a great question. And it's obviously a question that's on a lot of people's mind these days. I'm actually going to revert back to what I said earlier, when I talked about Bernoulli's principle, and just the ability sometimes when you do throw an algorithm at data, it might come the first thing it will find is probably some known law of physics. And so I think that really thinking about what do we mean by explainable AI, also requires us to think about what do we mean by AI? These days AI is often used anonymously with deep learning which is a particular type of algorithm that is not very analytical at its core. And what I mean by that is, other types of statistical machine learning models, have some underlying theory of what the population of data that you're studying. And whereas deep learning doesn't, it kind of just learns whatever pattern is sitting in front of it. And so there is a sense in which if you look at other types of algorithms, they are inherently explainable because you're choosing your algorithm based on what you think the is the sort of ground truth, about the population you're studying. And so I think we going to get to explainable deep learning. I think it's kind of challenging because you're always going to be in a position, where deep learning is designed to just be as flexible as possible. I'm sort of throw more math at the problem, because there may be are things that your sort of simpler model doesn't account for. However deep learning could be, part of an explainable AI solution. If for example, it helps you identify what are important so called features to look at what are the important aspects of your data. So I don't know it depends on what you mean by AI, but are you ever going to get to the point where, you don't need humans sort of interpreting outputs, and making some sets of judgments about what a set of computer algorithms that are processing data think. I think it will take, I don't want to say I know what's going to happen 50 years from now, but I think it'll take a little while to get to the point where you don't have, to maybe apply some subject matter understanding and some human judgment to what an algorithm is putting out. >> It's really interesting we had Dr. Robert Gates on a years ago at another show, and he talked about the only guns in the U.S. military if I'm getting this right, that are automatic, that will go based on what the computer tells them to do, and start shooting are on the Korean border. But short of that there's always a person involved, before anybody hits a button which begs a question cause we've seen this on the big data, kind of curve, i think Gartner has talked about it, as we move up from kind of descriptive analytics diagnostic analytics, predictive, and then prescriptive and then hopefully autonomous. So I wonder so you're saying will still little ways in that that last little bumps going to be tough to overcome to get to the true autonomy. >> I think so and you know it's going to be very application dependent as well. So it's an interesting example to use the DMZ because that is obviously also a very, mission critical I would say example but in general I think that you'll see autonomy. You already do see autonomy in certain places, where I would say the States are lower. So if I'm going to have some kind of recommendation engine, that suggests if you look at the sweater maybe like that one, the risk of getting that wrong. And so fully automating that as a little bit lower, because the risk is you don't buy the sweater. I lose a little bit of income I lose a little bit of revenue as a retailer, but the risk of I make that turn, because I'm going to autonomous vehicle as much higher. So I think that you will see the progression up that curve being highly dependent on what's at stake, with different degrees of automation. That being said you will also see in certain places where there's, it's either really expensive or it's humans aren't doing a great job. You may actually start to see some mission critical automation. But those would be the places where you're seeing them. And actually I think that's one of the reasons why you see actually a lot more autonomy, in the agriculture space, than you do in the sort of passenger vehicle space. Because there's a lot at stake and it's very difficult for human beings to sort of drive large combines. >> plus they have a real they have a controlled environment. So I've interviewed Caterpillar they're doing a ton of stuff with autonomy. Cause they're there control that field, where those things are operating, and whether it's a field or a mine, it's actually fascinating how far they've come with autonomy. But let me switch to a different industry that I know is closer to your heart, and looking at some other interviews and let's talk about diagnosing disease. And if we take something specific like reviewing x-rays where the computer, and it also brings in the whole computer vision and bringing in computer vision algorithms, excuse me they can see things probably fast or do a lot more comparisons, than potentially a human doctor can. And or hopefully this whole signal to noise conversation elevate the signal for the doctor to review, and suppress the noise it's really not worth their time. They can also review a lot of literature, and hopefully bring a broader potential perspective of potential diagnoses within a set of symptoms. You said before you both your folks are physicians, and there's a certain kind of magic, a nuance, almost like kind of more childlike exploration to try to get out of the algorithm if you will to think outside the box. I wonder if you can share that, synergy between using computers and AI and machine learning to do really arduous nasty things, like going through lots and lots and lots and lots of, x-rays compared to and how that helps with, doctor who's got a whole different kind of set of experience a whole different kind of empathy, whole different type of relationship with that patient, than just a bunch of pictures of their heart or their lungs. >> I think that one of the things is, and this kind of goes back to this question of, is AI for decision support versus automation? And I think that what AI can do, and what we're pretty good at these days, with computer vision is picking up on subtle patterns right now especially if you have a very large data set. So if I can train on lots of pictures of lungs, it's a lot easier for me to identify the pictures that somehow these are not like the other ones. And that can be helpful but I think then to really interpret what you're seeing and understand is this. Is it actually bad quality image? Is it some kind of some kind of medical issue? And what is the medical issue? I think that's where bringing in, a lot of different types of knowledge, and a lot of different pieces of information. Right now I think humans are a little bit better at doing that. And some of that's because I don't think we have great ways to train on, sort of sparse datasets I guess. And the second part is that human beings might be 40 years of training a model. They 50 years of training a model as opposed to six months, or something with sparse information. That's another thing that human beings have their sort of lived experience, and the data that they bring to bear, on any type of prediction or classification is actually more than just say what they saw in their medical training. It might be the people they've met, the places they've lived what have you. And I think that's that part that sort of broader set of learning, and how things that might not be related might actually be related to your understanding of what you're looking at. I think we've got a ways to go from a sort of artificial intelligence perspective and developed. >> But it is Exascale day. And we all know about the compound exponential curves on the computing side. But let's shift gears a little bit. I know you're interested in emerging technology to support this effort, and there's so much going on in terms of, kind of the atomization of compute store and networking to be able to break it down into smaller, smaller pieces, so that you can really scale the amount of horsepower that you need to apply to a problem, to very big or to very small. Obviously the stuff that you work is more big than small. Work on GPU a lot of activity there. So I wonder if you could share, some of the emerging technologies that you're excited about to bring again more tools to the task. >> I mean, one of the areas I personally spend a lot of my time exploring are, I guess this word gets used a lot, the Cambrian  explosion of new AI accelerators. New types of chips that are really designed for different types of AI workloads. And as you sort of talked about going down, and it's almost in a way where we were sort of going back and looking at these large systems, but then exploring each little component on them, and trying to really optimize that or understand how that component contributes to the overall performance of the whole. And I think one of the things that just, I don't even know there's probably close to a hundred active vendors in the space of developing new processors, and new types of computer chips. I think one of the things that that points to is, we're moving in the direction of generally infrastructure heterogeneity. So it used to be when you built a system you probably had one type of processor, or you probably had a pretty uniform fabric across your system you usually had, I think maybe storage we started to get tearing a little bit earlier. But now I think that what we're going to see, and we're already starting to see it with Exascale systems where you've got GPUs and CPUs on the same blades, is we're starting to see as the workloads that are running at large scales are becoming more complicated. Maybe I'm doing some simulation and then I'm running I'm training some kind of AI model, and then I'm inferring it on some other type, some other output of the simulation. I need to have the ability to do a lot of different things, and do them in at a very advanced level. Which means I need very specialized technology to do it. And I think it's an exciting time. And I think we're going to test, we're going to break a lot of things. I probably shouldn't say that in this interview, but I'm hopeful that we're going to break some stuff. We're going to push all these systems to the limit, and find out where we actually need to push a little harder. And I some of the areas I think that we're going to see that, is there We're going to want to move data, and move data off of scientific instruments, into computing, into memory, into a lot of different places. And I'm really excited to see how it plays out, and what you can do and where the limits are of what you can do with the new systems. >> Arti I could talk to you all day. I love the experience and the perspective, cause you've been doing this for a long time. So I'm going to give you the final word before we sign out and really bring it back, to a more human thing which is ethics. So one of the conversations we hear all the time, is that if you are going to do something, if you're going to put together a project and you justify that project, and then you go and you collect the data and you run that algorithm and you do that project. That's great but there's like an inherent problem with, kind of data collection that may be used for something else down the road that maybe you don't even anticipate. So I just wonder if you can share, kind of top level kind of ethical take on how data scientists specifically, and then ultimately more business practitioners and other people that don't carry that title. Need to be thinking about ethics and not just kind of forget about it. That these are I had a great interview with Paul Doherty. Everybody's data is not just their data, it's it represents a person, It's a representation of what they do and how they lives. So when you think about kind of entering into a project and getting started, what do you think about in terms of the ethical considerations and how should people be cautious that they don't go places that they probably shouldn't go? >> I think that's a great question out a short answer. But I think that I honestly don't know that we have a great solutions right now, but I think that the best we can do is take a very multifaceted, and also vigilant approach to it. So when you're collecting data, and often we should remember a lot of the data that gets used isn't necessarily collected for the purpose it's being used, because we might be looking at old medical records, or old any kind of transactional records whether it be from a government or a business. And so as you start to collect data or build solutions, try to think through who are all the people who might use it? And what are the possible ways in which it could be misused? And also I encourage people to think backwards. What were the biases in place that when the data were collected, you see this a lot in the criminal justice space is the historical records reflect, historical biases in our systems. And so is I there are limits to how much you can correct for previous biases, but there are some ways to do it, but you can't do it if you're not thinking about it. So I think, sort of at the outset of developing solutions, that's important but I think equally important is putting in the systems to maintain the vigilance around it. So one don't move to autonomy before you know, what potential new errors you might or new biases you might introduce into the world. And also have systems in place to constantly ask these questions. Am I perpetuating things I don't want to perpetuate? Or how can I correct for them? And be willing to scrap your system and start from scratch if you need to. >> Well Arti thank you. Thank you so much for your time. Like I said I could talk to you for days and days and days. I love the perspective and the insight and the thoughtfulness. So thank you for sharing your thoughts, as we celebrate Exascale day. >> Thank you for having me. >> My pleasure thank you. All right she's Arti I'm Jeff it's Exascale day. We're covering on the queue thanks for watching. We'll see you next time. (bright upbeat music)

>>Hello, everyone. My name is John Jane Shake. I work from Iran. Tous Andi. I am here this afternoon very gratefully with Anders Vulcan, who is VP of technology strategy for cloud bees, a Miranda's partner and a well known company in the space that we're going to be discussing. Anders is also a well known entity in this space, which is continuous integration and continuous delivery. Um, you've seen already today some sessions that focus on specific implementations of continuous integration and delivery, um, particularly around security. And, uh, we think this is a critically important topic for anyone in the cloud space, particularly in this increasingly complicated kubernetes space. To understand, um, Miranda's thanks, Uh, if I can recapitulate our own our own strategy and, uh, and language that with complexity on uncertainty consistently increasing with the depth of the technology stacks that we have to deal with consistently, um um elaborating themselves that navigating this requires, um first three implementation of automation to increase speed, which is what C and C d do. Um, and that this speed ba leveraged toe let us ship and iterate code faster. Since that's ultimately the business that all of us air in one way or another. I would like, I guess, toe open this conversation by asking Onders what does he think of that core strategy? >>You know, I think you know, hitting the security thing, right? Right off the bat. You know, security doesn't happen by accident. You know, security is not something that you know, Like a like a server in a restaurant. You know, Sprinkles a little bit of Parmesan cheese right before they serve you the the food. It's not something you Sprinkle on at the end. It's something that has to be baked in from the beginning, not just in the kitchen, but in the supply chain from from from the very beginning. So the you know it's a feature, and if you don't build it, if you're not going to get an outcome that you're not gonna be happy with and I think the you know it's increasingly it's obviously increasingly important and increasingly visible. You know, the you know, the kinds of security problems that we that we see these days can can be, you know, life altering, for for people that are subject to them and and can be, you know, life or death for a company that that's exposed to it. So it's it's it's very, very important. Thio pay attention to it and to work to achieve that as an explicit outcome of the software delivery process. And I think, you know, C i n c d as as process as tooling as culture plays a big part in that because ah, lot of it has to do with, you know, set things up, right? Um run them the same way over and over, you know, get the machine going. Turned the crane. Now, you wanna you wanna make improvements over over time. You know, it's not just, you know, set it and forget it. You know, we got that set up. We don't have to worry about it anymore, but it really is a question of, you know, get the human out of the loop a lot of the times because if if you're dealing with configuring complex systems, you wanna make sure that you get them set up configured, you know, documented Ideally, you know, as code, whether it's a domain specific language or or something like that. And then that's something that you contest against that you can verify against that you can that you can difficult. And then that becomes the basis for for your, you know, for yourself, for pipelines, for your automation around, you know, kind of the software factory floor. So I think automation is a key aspect of that because it, you know, it takes a lot of the drudgery out of it, for one thing, So now the humans have more time to spend on doing on the on the creative things on the things that we're good at a zoo. Humans and it also make sure that, you know, one of the things that computers are really good at is doing the same thing over and over and over and over. Eso that kind of puts that responsibility into the hands of the entity that that knows how to do that well, which is which is the machine eso I think it's, you know, it's a light. It's a deep, deep topic, obviously, but, you know, automation plays into it. Uh, you know, small batch sizes play into it, you know, being able to test very frequently whether that's testing in. You're kind of you're C I pipeline where you're sort of doing building mostly unit testing, maybe some integration testing, but also in layering in the mawr. Serious kinds of testing in terms of security scanning, penetration, testing, vulnerability, scanning. You know those sorts of things which, you know, maybe you do on every single see I Bill. But most people don't because those things tend toe take a little bit longer on. And you know you want your sea ice cycle to be as fast as possible because that's really in service of the developer who has committed code and wants toe kind of see the thumbs up from the system saying it. And, um, so most organizations most organizations are are are focusing on, you know, making sure that there's a follow on pipeline to follow on set of tests that happened after the C I passes successfully and and that's, you know, where a lot of the security scanning and those sorts of things happen. >>It's a It's an interesting problem. I mean, you mentioned, um, what almost sounds like a Lawrence Lessig Ian kind of idea that, you know, code is law in enterprises today, code particularly see, I code ends up being policy, but At the same time, there's, Ah, it seems to me there's a an alternative peril, which is, as you increase speed, particularly when you become more and more dependent on things like containers and layering technology to provide components and capabilities that you don't have to build yourself to your build pipeline, that there are new vulnerabilities, potentially that creep in and can creep in despite automation. Zor at least 1st. 1st order automation is attempts toe to prevent them from creeping in. You don't wanna you wanna freeze people on a six month old version of a key container image. But on the other hand, if the latest version has vulnerabilities, that could be a problem. >>Yeah, I mean, it's, you know, it's it's a it's a it's a double edged sword. It's two sides of the same coin. I think you know, when I talked to a lot of security people, um, you know, people to do it for a living is supposed to mean I just talk about it, um, that Z not completely true. But, um, the ah, lot of times the problem is old vulnerabilities. The thing that I think keeps a lot of people up at night isn't necessarily that the thing at the tip of the releases for particular, you know, well known open source, library or something like that. But that's gonna burn you all the vast majority of the time. And I want to say, like, 80 85% of the time. The vulnerability is that you that you get hosed by are ones that have been known about for years. And so I think the if I had to pick. So if you know, in that sort of two sides of that coin, if I had to pick, I would say Be aggressive in making sure that your third party dependencies are updated frequently and and continuously right, because that is the biggest, biggest cause of of of security vulnerabilities when it comes to third party code. Um, now you know the famous saying, You know, move fast and break things Well, there's certain things you don't want to break. You know you don't want to break a radiation machine that's going to deliver radio radiotherapy to someone because that will endanger their health. So So those sorts of systems, you know, naturally or subject a little bit more kind of caution and scrutiny and rigor and process those sorts of things. The micro service that I run that shows my little avatar when I log in, that one probably gets a little less group. You know, Andre rightfully so. So I think a lot of it has to do. And somebody once said in a I think it was, Ah, panel. I was on a PR say conference, which was, which was kind of a wise thing to say it was Don't spend a million dollars protecting a $5 assets. You know, you wanna be smart and you wanna you wanna figure out where your vulnerabilities they're going to come from and in my experience, and and you know, what I hear from a lot of the security professionals is pay attention to your supply chain. You're you want to make sure that you're up to date with the latest patches of, of all of your third party, you know, open source or close source. It doesn't really matter. I mean, if anything, you know, open source is is more open. Eso You could inspect things a little bit better than the close source, but with both kinds of streams of code that you consume and and use. You wanna make sure that you're you're more up to date as opposed to a less up to date? Um, that generally will be better. Now, can a new version of the library cause problems? You know, introduce bugs? You know, those sorts of things? Yes. That's why we have tests. That's what we have automated tests, regression, sweets, You know, those sorts of things. And so you wanna, you know, you wanna live in a in a world where you feel the confidence as a as a developer, that if I update this library from, you know, one debt owed at 3 to 1 debt owed at 10 to pick up a bunch of, you know, bug fixes and patches and those sorts of things. But that's not going to break some on demand in the test suites that that will run against that ought to cover that that sort of functionality. And I'd rather be in that world of Oh, yeah, we tried to update to that, but it But it broke the tests and then have to go spend time on that, then say, Oh, it broke the test. So let's not update. And then six months later, you do find out. Oh, geez. There was a problem in one that owed at three. And it was fixed in one. That about four. If only we had updated. Um, you know, you look at the, um you look at some of the highest profile security breaches that are out there that you sort of can trace toe third party libraries. It's almost always gonna be that it was out of date and hadn't been patched. That's so that's my you know, opinionated. Take on that. Sure. >>What are the parts of modern C I c D. As opposed to what one would encounter 56 years ago? Maybe if we can imagine that is being before the micro services and containers revolution really took off. >>You know, I think e think you're absolutely right that, you know, not the whole world is not doing. See, I Yeah, and certainly the whole world is not doing city yet. Um, you know, I think you know, as you say, we kind of live in a little bit of an ivory tower. You know, we live in an echo chamber in a little bit of a bubble Aziz vendors in this space. The truth is that I would say less than 50% of the software organizations out there do real. See, I do real CD. The number's probably less than that. Um, you know, I don't have anything to back that up other than just I talked to a lot of folks and work with, you know, with a lot of organizations and like, Yeah, that team does see I that team does Weekly builds You know, those sorts of things. It's it's really all over the place, Onda. Lot of times there's There's definitely, in my experience, a high correlation there with the amount of time that a team or a code base has been around, and the amount of sort of modern technologies and processes and and and so on that are that are brought to it on. And that sort of makes sense. I mean, if you if you're starting with the green field with a blank sheet of paper, you're gonna adopt, you know, the technologies and the processes and the cultures of today. A knot of 5, 10 15 15 years ago, Um but but most organizations air moving in that direction. Right? Andi, I think you know what? What? What? What's really changed in the last few years is the level of integration between the various tools between the various pieces and the amount of automation that you could bring to bear. I mean, I you know, I remember, you know, five or 10 years ago having all kinds of conversations with customers and prospects and and people of conferences and so on and they said, Oh, yeah, we'd like to automate our our software development life cycle, but, you know, we can't We have a manual thing here. We have a manual thing there. We do this kind of testing that we can automate it, and then we have this system, but it doesn't have any guy. So somebody has to sit and click on the screen. And, you know, and I used to say e used to say I don't accept No for an answer of can you automate this right? Everything. Anything can be automated. Even if you just get the little drinking bird. You know that just pokes the mouse. Everyone something. You can automate it, and I Actually, you know, I had one customer who was like, Okay, and we had a discussion and and and and they said, Well, we had this old Windows tool. We Its's an obscure tool. It's no longer updated, but it's it's it's used in a critical part of the life cycle and it can't be automated. And I said, Well, just install one of those Windows tools that allows you to peek and poke at the, you know, mass with my aunt I said so I don't accept your answer. And I said, Well, unfortunately, security won't allow us to install those tools, Eh? So I had to accept No, at that point, but But I think the big change were one of the biggest changes that's happened in the last few years is the systems now have all I'll have a p i s and they all talk to each other. So if you've gotta, you know, if you if you've got a scanning tool, if you've got a deployment tool, if you have a deployment, you know, infrastructure, you know, kubernetes based or, you know, kind of sitting in front of our around kubernetes thes things. I'll talk to each other and are all automated. So one of the things that's happened is we've taken out a lot of the weight states. A lot of the pauses, right? So if you you know, if you do something like a value stream mapping where you sit down and I'll date myself here and probably lose some of the audience with this analogy. But if you remember Schoolhouse Rock cartoons in in the late seventies, early eighties, there was one which was one of my favorites, and and the guy who did the music for this passed away last year, sadly, But, uh, the it was called How a bill Becomes a Law and they personified the bill. So the bill, you know, becomes a little person and, you know, first time passed by the house and then the Senate, and then the president either signs me or doesn't and or he vetoes, and it really sort of did this and what I always talk about with respect to sort of value stream mapping and talking about your processes, put a GoPro camera on your source codes head, and then follow that source code all the way through to your customer understand all of the stuff that happens to it, including nothing, right? Because a lot of times in that elapsed time, nothing keeps happening, right. If we build software the way we were sorry. If we build cars the way we build software, we would install the radio in a car, and then we would park it in a corner of the factory for three weeks. And then we might remember to test the radio before we ship the car out to the customer. Right, Because that's how a lot of us still develop some for. And I think one thing that's changed in the in the last few years is that we don't have these kind of, Well, we did the bill. So now we're waiting for somebody to create an environment and rack up some hardware and install an operating system and install. You know, this that and the other. You know, that that went from manual to we use Scheffer puppet to do it, which then went to we use containers to do it, which then went to we use containers and kubernetes to do it. So whole swaths of elapsed time in our software development life cycles basically went to nothing, right and went to the point where we can weaken, weaken, configure them way to the left and and and follow them all the way through. And that the artifact that we're delivering isn't necessarily and execute herbal. It could be a container, right? So now that starts to get interesting for us in terms of being able to test against that container scan against that container, def. Against that container, Um, you know, and it, you know, it does bring complexity to in terms of now you've got a layered file system in there. Well, what all is in there, you know, And so there's tools for scanning those kinds of things, But But I think that one of the biggest things that's happened is a lot of the natural pause. Points are no longer natural. Pause points their unnatural pause points, and they're now just delays in yourself for delivery. And so what? What a lot of organizations are working on is kind of getting to the point where those sorts of things get get automated and connected, and that's now possible. And it wasn't 55 or 10 years ago. >>So It sounds like a great deal of the speed benefit, which has been quantified many different ways. But is once you get one of these systems working, as we've all experienced enormous, um, is actually done by collapsing out what would have been unused time in a prior process or non paralyze herbal stuff has been made parallel. >>I remember doing a, uh, spent some time with a customer, and they did a value stream mapping, and they they found out at the end that of the 30 days of elapsed time they were spending three days on task. Everything else was waiting, waiting for a build waiting foran install, waiting for an environment, waiting for an approval, having meetings, you know, those sorts of things. And I thought to myself, Oh, my goodness, you know, 90% of the elapsed time is doing nothing. And I was talking to someone Gene Kim, actually, and I said, Oh my God, it was terrible that these you know, these people are screwed and he says, 0 90%. That's actually pretty good, you know? So So I think you know, if you if you think today, you know, if you If you if you look at the teams that are doing just really pure continuous delivery, you know, write some code committed, gets picked up by the sea ice system and passes through CIA goes through whatever coast, see I processing, you need to do security scanning and so on. It gets staged and it gets pushed into production. That stuff can happen in minutes, right? That's new. That's different. Now, if you do that without having the right automated gates in place around security and and and and those sorts of things you know, then you're living a little bit dangerously, although I would argue not necessarily any more dangerously, than just letting that insecure coat sit around for a week before your shipment, right? It's not like that problem is going to fix itself if you just let it sit there, Um, but But, you know, you definitely operated at a higher velocity. Now that's a lot of the benefit that you're tryingto trying to get out of it, right? You can get stuff out to the market faster, or if you take a little bit more time, you get more out to the market in, in in the same amount of time you could turn around and fix problems faster. Um, if you have a vulnerability, you can get it fixed and pushed out much more quickly. If you have a competitive threat that you need to address, you can you know, you could move that that much faster if you have a critical bug. You know, I mean, all security issues or bugs, sort of by definition. But, you know, if you have a functionality bug, you can you can get that pushed out faster. Eso So I think kind of all factors of the business benefit from from this increase in speed. And I think developers due to because anybody you know, any human that has a context switch and step away from something for for for, you know, duration of time longer than a few minutes, you know, you're gonna you're gonna you're gonna you're gonna have to load back up again. And so that's productivity loss. Now, that's a soft cost. But man, is it Is it expensive and is a painful So you see a lot of benefit there. Think >>if you have, you know, an organization that is just starting this journey What would you ask that organization to consider in orderto sort of move them down this path? >>It's by far the most frequent and almost always the first question I get at the end of the talk or or a presentation or something like that is where do we start? How do I know where to start? And and And there's a couple of answers to that. What one is Don't boil the ocean, right? Don't try to fix everything all at once. You know that because that's not agile, right? The be agile about your transformation Here, you know, pick, pick a set of problems that you have and and make a, you know, basically make a burn down list and and do them in order. So find find a pain point that you have right and, you know, just go address that and and try to make it small and actionable and especially early on when you're trying to affect change. And you're tryingto convinced teams that this is the way to go and you may have some naysayers, or you may have people who are skeptical or have been through these processes before that have been you know failures released, not the successes that they that they were supposed to be. You know, it's important to have some wind. So what I always say is look, you know, if you have a pebble in your shoe, you've got a pain point. You know how to address that. You know, you're not gonna address that by changing out your wardrobe or or by buying a new pair of shoes. You know, you're gonna address that by taking your shoe off, shaking it until the pebble falls out there putting the shoe back on. So look for those kinds of use cases, right? So if you're engineers are complaining that whenever I check in the build is broken and we're not doing see, I well, then let's look at doing C I Let's do see eye, right? If you're not doing that. And for most organizations, you know, setting up C I is a very manageable, very doable thing. There's lots of open source tooling out there. There's lots of commercial tooling out there. Thio do that to do it for small teams to do it for large teams and and everything in between. Um, if the problem is Gosh, Every time we push a change, we break something. You know where every time something works in staging it doesn't work in production. Then you gotta look at Well, how are these systems being configured? If you're If you're configuring them manually, stop automate the configuration of them. Um, you know, if you're if you're fixing system manually, don't you know, as a friend of mine says, don't fix, Repave? Um, you know, you don't wanna, you know, there's a story of, you know how how Google operates in their data centers. You know, they don't they don't go look for a broken disk drive and swap it out. You know, when it breaks, they just have a team of people that, like once a month or something, I don't know what the interval is. They just walked through the data center and they pull out all the dead stuff and they throw it out, and what they did was they assume that if the scale that they operate, things are always going to break physical things are always going to break. You have to build a software to assume that breakage and any system that assumes that we're going to step in when a disk drive is broken and fix it so that we can get back to running just isn't gonna work at scale. There's a similarity. There's sort of ah, parallel to that in in software, which is you know, any time you have these kinds of complex systems, you have to assume that they're gonna break and you have to put the things in place to catch those things. The automated testing, whether it's, you know, whether you have 10,000 tests that you that you've written already or whether you have no tests and you just need to go right, your first test that that journey, you've got to start somewhere. But my answer thio their questions generally always just start small, pick a very specific problem. Build a plan around it, you know, build a burned down list of things that you wanna address and just start working your way down that the same way that you would for any, you know, kind of agile project, your transformation of your own processes of your own internal systems. You should use agile processes for those as well, because if you if you go off for six months and and build something. By the time you come back, it's gonna be relevant. Probably thio the problems that you were facing six months ago. >>A Then let's consider the situation of, ah, company that's using C I and maybe sea ice and C d together. Um, and they want to reach what you might call the next level. Um, they've seen obvious benefits they're interested in, you know, in increasing their investment in, you know and cycles devoted to this technology. You don't have to sell them anymore, but they're looking for a next direction. What would you say that direction should be? I >>think oftentimes what organizations start to do is they start to look at feedback loops. So on DAT starts to go into the area of sort of metrics and analytics and those sorts of things. You know what we're we're always concerned about? You know, we're always affected by things like meantime to recovery. Meantime, the detection, what are our cycle times from, you know, ideation, toe codecommit. What's the cycle? Time from codecommit the production, those sorts of things. And you know you can't change what you don't measure eso so a lot of times the next step after kind of getting the rudimentary zoo of C I Orsini or some combination of both in places start to measure. Stop you, Um, and and then but But there. I think you know, you gotta be smart about it, because what you don't want to do is kind of just pull all the metrics out that exists. Barf them up on the dashboard. And the giant television screens say boom metrics, right. You know, Mike, drop go home. That's the wrong way to do it. You want to use metrics very specifically to achieve outcomes. So if you have an outcome that you want to achieve and you can tie it to a metric start looking at that metric and start working that problem once you saw that problem, you can take that metric. And you know, if that's the metric you're showing on the big you know, the big screen TV, you can pop that off and pick the next one and put it up there. I I always worry when you know a little different when you're in a knock or something like that. When when you're looking at the network stuff and so on. But I'm always leery of when I walk into to a software development organization. You know, just a Brazilian different metrics, this whole place because they're not all relevant. They're not all relevant at the same time. Some of them you wanna look at often, some of them you just want to kind of set an alarm on and make sure that, you know, I mean, you don't go down in your basement every day to check that the sump pump is working. What you do is you put a little water detector in there and you have an alarm go off if the water level ever rises above a certain amount. Well, you want to do the same thing with metrics, right? Once you've got in the water out of your basement, you don't have to go down there and look at it all the time. You put the little detector in, and then you move on and you worry about something else. And so organizations as they start to get a little bit more sophisticated and start to look at the analytics, the metrics, um, start to say, Hey, look, if our if our cycle time from from, you know, commit to deploy is this much. And we want it to be this much. What happens during that time, And where can we take slices out of that? You know, without without affecting the outcomes in terms of quality and so on, or or if it's, you know, from from ideation, toe codecommit. You know what? What can we do there? Um, you start to do that. And and then as you get those sort of virtuous cycles of feedback loops happening, you know, you get better and better and better, but you wanna be careful with metrics, you know, you don't wanna, you know, like I said, you don't wanna barf a bunch of metrics up just to say, Look, we got metrics. Metrics are there to serve a particular outcome. And once you've achieved that outcome, and you know that you can continue to achieve that outcome, you turn it into an alarm or a trigger, and you put it out of sight. And you know that. You know, you don't need to have, like, a code coverage metric prominently displayed you you pick a code coverage number that you're happy with you work to achieve that. Once you achieve it, you just worry about not going below that threshold again. So you can take that graph off and just put a trigger on this as if we ever get below this, you know, raising alarm or fail a build or fail a pipeline or something like that and then start to focus on improving another man. Uh, or another outcome using another matter >>makes enormous sense. So I'm afraid we are getting to be out of time. I want to thank you very much on this for joining us today. This has been certainly informative for me, and I hope for the audience, um, you know, thank you very, very much for sharing your insulin.