>> Announcer: Live from Barcelona, Spain, it's theCUBE. Covering Cisco Live 2020 brought to you by Cisco and it's ecosystem partners. >> Hi, everyone, welcome back to theCUBE's live coverage, it's our fourth day of four days of coverage here in Barcelona, Spain for Cisco Live 2020. I'm John Furrier with my co-host Stu Miniman and two great guests here in the DevNet studio where the theCUBE is sitting all week long, been packed with action, Mandy Whaley, Senior Director Developer Experience, Cisco DevNet and Par Merat, Senior Director welcome back to this CUBE. Good to see you guys. >> Thank you. >> Thank you. >> Glad to be here. >> So, we have had a lot of history with you guys from day one. >> Mandy: Yes. >> Watching DevNet from an idea of "Hey, we should do developer thing." And you also have DevNet Create which is a separate, more developer focused. DevNet and Cisco's developer environment. We've been there from the beginning, what a progression! Congratulations on the success. >> Thank you. Thank you so much, it's great to be here in Barcelona with everybody here, you know, learning in the workshops, and we just love these times to connect with our community at Cisco Live, and At DevNet Create, which you mentioned, which is coming up in March. So its right on the corner. >> DevNet Zone which we're in has been really robust, it's been the talk of the show every year, and it gets bigger and the sessions are packed, because people are learning developers, new developers as well as Cisco engineers who are certified, are coming getting new skills as the modern cloud hybrid environments require new skills. It's a technology shift. >> Yeah, exactly and what we have in the DevNet Zone are different ways that the engineers and developers can engage with that technology shifts. So, we have demos around IoT and security, and showing how, you know, to prevent threats from attacking the industrial routers and things like that. We have coding workshops from beginning, intro to Python, intro to Gets, all the way up through advanced, like, Kubernetes topics and things like that. So, people can really dive in with what they're looking for. And this year, we are really excited because we have the new DevNet certifications with those exams coming out right around the corner in February. So, a lot of people are here saying, "I am ready to skill up for those exams, "I am starting to dive into these topics." >> Well, Susie Wee was on, she's the chief of DevNet, among other things, and she said, there's going to be a DevNet 500. The first 500 certifications of DevNet are going to be, kind of, like, the hall of fame or, you know, inaugural or founder certifications. So, can you explain what does it mean? It's not a DevNet certification badge. It's a series of different, can go deeper than that? >> Yeah, just like we have our, you know, existing Network Certifications which are so respected and loved around the world, people get CCIE tattoos and things. Just like there is an associate and professional and expert level on the networking track, there's now a DevNet Associate, a DevNet Professional and coming soon DevNet Expert. And then there's also Specialist badges which help you add specific skills like data center automation, IoT web access. So, it's a whole new set of certifications that are more focused on the software. So they're about 80% software skills, 20% knowledge of networking, and then how you really connect up and down the stack. >> So these are new certifications, they're not replacing anything else >> No, no, no they're all the same stuff? >> They are new, they are part of the same program, they have the same rigor, the same kind of test. They actually have ways to interweave with the existing networking certifications, because we want people to do both skill path, right, to build this new IT team of the future. And so, it's a completely new set of exams. The exams are going to be available to take February 24th, and you can start signing up now. So, with the DevNet 500, you know, that's going to be a special recognition for the first 500 people who get DevNet certifications. It'll be life-time achievement, they'll always be in a DevNet 500, right? And I've had people coming up and telling me, you know "I'm signed up for the first day, "I'm taking my exams on the first day, "I'm trying to get into that." >> Stu and I always want to be on the list, so I think we might be on the 500 study up there (laughs). >> Of course, yeah, And what's really great is with the certifications, we've heard from people in the Zone that, they have been coming and taking classes and learning the skills, but they didn't have a specific way to map that to their career path to get rewarded at work, you know, to have that sort of progression. And so with the certifications they will really will have that. And it's also really important for our partners and Par Merat is doing lot of work with certifications and partners. >> Yeah, Par, definitely, I would love to hear a little bit, we've interviewed on theCUBE over the years some of the DevNet partners from a technology standpoint, of course the channel ecosystem hugely important to Cisco's business. Give us the update as to, you know, DevNet partnering as well as, what will these certifications mean to about the technology and go-to-market partners? >> Yeah, the wonderful thing about this is, it really demonstrates Cisco's embracement of software, and making sure that we are providing that common language for software developers and networkers to bring the two together. And what we've found is that our partners are at different levels of maturity along that progression of programmability. And this new DevNet specialization, which is anchored in the individuals that are now certified at that partner, allow them to demonstrate from a go-to-market standpoint, from a recognition standpoint, that as a practice they have these skills. And look, at the end of the day, it's all about delivering what our customers need. And our customers are asking us for significant help in automation, digital transformation, they're trying to drive new business outcomes. And this will provide that recognition on who to partner with in the market. >> Yeah, this is so important I remember when Cisco helped a lot of the the partner ecosystem build data center practices. Went from the silos and now embracing, you've got the hardware the software, we're talking multicloud. It's the practice that is needed today going forward to help customers with with where they are going. >> It really is. And another benefit that we are finding in talking to our partners is where packaging this up and rolling it out, is not only will it help them from a recognition standpoint, from a practice stand point and from a competitive differentiation standpoint. But it will also help them attract talent. I mean, it's no secret, there is a talent shortage right now. If you talk to any CEO that's top of mind, and how these partners are able to attract these new skills and attract smart people. Smart people like working on smart things, right? And so this has really been a big traction point for them as well. >> It's also giving ways to really specifically train for new job roles. So some of the ways that you can combine the new DevNet certifications with the network engineering certifications. We've looked at it and said, you know, there's a role of network automation developer. That's a new role. Everyone we ask in one of our sessions, "Who needs that person on their team?" So many customers, partners raise their hands saying, "We want the Network Automation Developers on our team." And you can combine your CCNP Enterprise with a DevNet certification and build up the skills to be that Network Automation Developers >> Certainly it's been great buzz. I've got to get your guys' thoughts because certainly it's great for careers and you guys are betting on the people, and the people are betting on Cisco. This is what's going on, it's a maturity of DevNet, almost. It's like a pinch-me moment for you guys, but you continue to grow. I've got to ask you, what are some of the cool things that you're showing here? As you mature, you still have the start here session, which is intro to Python and other things, pretty elementary, and then there's more advanced things. What are some of the new things that's going on that you could share? >> So some of the new things we've got going on, one of my favorites is the IoT and security demonstration. There's an industrial robot arm that's picking and placing things, and you can see how it's connected to the network and then something goes wrong with that robot arm. And then you can actually show how you can use the software and security tools to see was there code trying to access, you know, something that that robot was using, that's getting in the way of it working? So you could detect threats and move forward on that. We also have a whole automation journey that starts from modeling your network to testing, to how you would deploy automation, to a deep dive on telemetry and then ends with multi-domain automation. So really helping engineers, like, look at that whole progression, that's been really popular. >> Par, talk about the specialization, which ones are more, I'd say popular or entry level, which ones are people coming into getting certified first, network engineering, automation first? Or what's the-- >> Yeah, so the program's going to to roll out with three different levels. One is a specialized level, the second is an advanced level, and then we'll look to that third level. Again, they're anchored in the individual certs. And so as we look for that entry level, it's really all about automation, right? I mean, some things you take for granted, but you still need these new skills to be able to automate and scale, and have repeatable, scalable benefits from that. The second tier will be more cross-domain and that's where we're really thinking that additional skill set is needed to deliver dashboard experience, compliance experiences, and then that next level, again, will anchor towards the expert level that's coming out. But one thing I want to point out is, in addition to just having the certified people on staff, they also have to demonstrate that they have a practice around it. So it's not just enough to say, "I passed an exam." As we work with them to roll out the practice and they earn the badge, they're demonstrating that they have the full methodology in place so that it really, there's a lot behind it. >> So that means we can't be in the 500 list then even if we pass (laughs). >> Well, you might be able to be in the 500 list, but I don't know that theCUBE would end up being specialized. >> It's good banner advertising. No, seriously all fun, it's all fun. Cisco Live in Europe. Is there a difference between European and U.S.? Are you seeing any differences in geographic talent? >> You know what, the first couple of years that we did it, I think there was a bigger difference. It felt like there were different topics that were very popular in the U.S., slightly different in Europe. Last year and this year I feel, like they have converged. It's the same focus on DevOps, automation, security is a huge focus in both places. And it also feels like the interest and level of the people attending has also converged. It's really similar. Congratulations, it's been fun to watch the rise and success of DevNet, continues to be strong, obviously in the hub here, and the DevNet zone behind us, packed sessions. >> Mandy: Yes, yes. >> What's the biggest surprise for you guys in terms of things that you didn't expect or some of the success, what's jumped out? >> Yeah, I think, you know, one of the points that I want to make sure we also cover and it has been an added benefit. We were hoping it would happen, we just didn't realize it would happen this soon. We're attracting new companies, new partners, so the specialization won't just be available for our traditional VARs. This is also available for our non resellers and we are finding different companies accessing DevNet resources and learning these skills. So that's been a really great benefit of DevNet overall. >> Definitely, my favorite surprises are when I show up at the community events and I hear from someone I met last year what they went back and did, and the change that they drove in their company. And I think we're seeing those across the board of people who start a grassroots movement, take back some new ideas, really create change, and then they come back and we get to hear about that from them. Those are my favorite surprises. >> And I tell you, we've known for years how important the developer is, but I think the timing on this has been perfect because it is no longer just, Oh, the developer has some tools that they'd liked in the corner. The developer connected to the business and driving things forward. >> Mandy: Exactly. So perfect timing, congratulations on the certification-- >> The other thing that's been great is that Cisco itself, we now have APIs across the whole portfolio and up and down the stack. So that's been a wonderful thing to see come together because it opens up possibilities for all these developers. >> So Cisco is API first company? >> We are building APIs everywhere we can, and the community is taking them and finding creative things to build. >> Well, it's been fun to watch you guys change Cisco, but also impact customers has been great to watch. Par many thanks for coming on, appreciate it. >> Yeah, thank you. >> theCUBE's live coverage here in Barcelona for Cisco Live 2020 I'm John Furrier with Dave Vellante, Stu Miniman. Be right back with more after this short break. (upbeat music)

>> Announcer: Live from Barcelona, Spain, it's theCUBE. Covering Cisco Live 2020 brought to you by Cisco and it's ecosystem partners. >> Hi, everyone, welcome back to theCUBE's live coverage, it's our fourth day of four days of coverage here in Barcelona, Spain for Cisco Live 2020. I'm John Furrier with my co-host Stu Miniman and two great guests here in the DevNet studio where the theCUBE is sitting all week long, been packed with action, Mandy Whaley, Senior Director Developer Experience, Cisco DevNet and Par Merat, Senior Director welcome back to this CUBE. Good to see you guys. >> Thank you. >> Thank you. >> Glad to be here. >> So, we have had a lot of history with you guys from day one. >> Mandy: Yes. >> Watching DevNet from an idea of "Hey, we should do developer thing." And you also have DevNet Create which is a separate, more developer focused. DevNet and Cisco's developer environment. We've been there from the beginning, what a progression! Congratulations on the success. >> Thank you. Thank you so much, it's great to be here in Barcelona with everybody here, you know, learning in the workshops, and we just love these times to connect with our community at Cisco Live, and At DevNet Create, which you mentioned, which is coming up in March. So its right on the corner. >> DevNet Zone which we're in has been really robust, it's been the talk of the show every year, and it gets bigger and the sessions are packed, because people are learning developers, new developers as well as Cisco engineers who are certified, are coming getting new skills as the modern cloud hybrid environments require new skills. It's a technology shift. >> Yeah, exactly and what we have in the DevNet Zone are different ways that the engineers and developers can engage with that technology shifts. So, we have demos around IoT and security, and showing how, you know, to prevent threats from attacking the industrial routers and things like that. We have coding workshops from beginning, intro to Python, intro to Gets, all the way up through advanced, like, Kubernetes topics and things like that. So, people can really dive in with what they're looking for. And this year, we are really excited because we have the new DevNet certifications with those exams coming out right around the corner in February. So, a lot of people are here saying, "I am ready to skill up for those exams, "I am starting to dive into these topics." >> Well, Susie Wee was on, she's the chief of DevNet, among other things, and she said, there's going to be a DevNet 500. The first 500 certifications of DevNet are going to be, kind of, like, the hall of fame or, you know, inaugural or founder certifications. So, can you explain what does it mean? It's not a DevNet certification badge. It's a series of different, can go deeper than that? >> Yeah, just like we have our, you know, existing Network Certifications which are so respected and loved around the world, people get CCIE tattoos and things. Just like there is an associate and professional and expert level on the networking track, there's now a DevNet Associate, a DevNet Professional and coming soon DevNet Expert. And then there's also Specialist badges which help you add specific skills like data center automation, IoT web access. So, it's a whole new set of certifications that are more focused on the software. So they're about 80% software skills, 20% knowledge of networking, and then how you really connect up and down the stack. >> So these are new certifications, they're not replacing anything else >> No, no, no they're all the same stuff? >> They are new, they are part of the same program, they have the same rigor, the same kind of test. They actually have ways to interweave with the existing networking certifications, because we want people to do both skill path, right, to build this new IT team of the future. And so, it's a completely new set of exams. The exams are going to be available to take February 24th, and you can start signing up now. So, with the DevNet 500, you know, that's going to be a special recognition for the first 500 people who get DevNet certifications. It'll be life-time achievement, they'll always be in a DevNet 500, right? And I've had people coming up and telling me, you know "I'm signed up for the first day, "I'm taking my exams on the first day, "I'm trying to get into that." >> Stu and I always want to be on the list, so I think we might be on the 500 study up there (laughs). >> Of course, yeah, And what's really great is with the certifications, we've heard from people in the Zone that, they have been coming and taking classes and learning the skills, but they didn't have a specific way to map that to their career path to get rewarded at work, you know, to have that sort of progression. And so with the certifications they will really will have that. And it's also really important for our partners and Par Merat is doing lot of work with certifications and partners. >> Yeah, Par, definitely, I would love to hear a little bit, we've interviewed on theCUBE over the years some of the DevNet partners from a technology standpoint, of course the channel ecosystem hugely important to Cisco's business. Give us the update as to, you know, DevNet partnering as well as, what will these certifications mean to about the technology and go-to-market partners? >> Yeah, the wonderful thing about this is, it really demonstrates Cisco's embracement of software, and making sure that we are providing that common language for software developers and networkers to bring the two together. And what we've found is that our partners are at different levels of maturity along that progression of programmability. And this new DevNet specialization, which is anchored in the individuals that are now certified at that partner, allow them to demonstrate from a go-to-market standpoint, from a recognition standpoint, that as a practice they have these skills. And look, at the end of the day, it's all about delivering what our customers need. And our customers are asking us for significant help in automation, digital transformation, they're trying to drive new business outcomes. And this will provide that recognition on who to partner with in the market. >> Yeah, this is so important I remember when Cisco helped a lot of the the partner ecosystem build data center practices. Went from the silos and now embracing, you've got the hardware the software, we're talking multicloud. It's the practice that is needed today going forward to help customers with with where they are going. >> It really is. And another benefit that we are finding in talking to our partners is where packaging this up and rolling it out, is not only will it help them from a recognition standpoint, from a practice stand point and from a competitive differentiation standpoint. But it will also help them attract talent. I mean, it's no secret, there is a talent shortage right now. If you talk to any CEO that's top of mind, and how these partners are able to attract these new skills and attract smart people. Smart people like working on smart things, right? And so this has really been a big traction point for them as well. >> It's also giving ways to really specifically train for new job roles. So some of the ways that you can combine the new DevNet certifications with the network engineering certifications. We've looked at it and said, you know, there's a role of network automation developer. That's a new role. Everyone we ask in one of our sessions, "Who needs that person on their team?" So many customers, partners raise their hands saying, "We want the Network Automation Developers on our team." And you can combine your CCNP Enterprise with a DevNet certification and build up the skills to be that Network Automation Developers >> Certainly it's been great buzz. I've got to get your guys' thoughts because certainly it's great for careers and you guys are betting on the people, and the people are betting on Cisco. This is what's going on, it's a maturity of DevNet, almost. It's like a pinch-me moment for you guys, but you continue to grow. I've got to ask you, what are some of the cool things that you're showing here? As you mature, you still have the start here session, which is intro to Python and other things, pretty elementary, and then there's more advanced things. What are some of the new things that's going on that you could share? >> So some of the new things we've got going on, one of my favorites is the IoT and security demonstration. There's an industrial robot arm that's picking and placing things, and you can see how it's connected to the network and then something goes wrong with that robot arm. And then you can actually show how you can use the software and security tools to see was there code trying to access, you know, something that that robot was using, that's getting in the way of it working? So you could detect threats and move forward on that. We also have a whole automation journey that starts from modeling your network to testing, to how you would deploy automation, to a deep dive on telemetry and then ends with multi-domain automation. So really helping engineers, like, look at that whole progression, that's been really popular. >> Par, talk about the specialization, which ones are more, I'd say popular or entry level, which ones are people coming into getting certified first, network engineering, automation first? Or what's the-- >> Yeah, so the program's going to to roll out with three different levels. One is a specialized level, the second is an advanced level, and then we'll look to that third level. Again, they're anchored in the individual certs. And so as we look for that entry level, it's really all about automation, right? I mean, some things you take for granted, but you still need these new skills to be able to automate and scale, and have repeatable, scalable benefits from that. The second tier will be more cross-domain and that's where we're really thinking that additional skill set is needed to deliver dashboard experience, compliance experiences, and then that next level, again, will anchor towards the expert level that's coming out. But one thing I want to point out is, in addition to just having the certified people on staff, they also have to demonstrate that they have a practice around it. So it's not just enough to say, "I passed an exam." As we work with them to roll out the practice and they earn the badge, they're demonstrating that they have the full methodology in place so that it really, there's a lot behind it. >> So that means we can't be in the 500 list then even if we pass (laughs). >> Well, you might be able to be in the 500 list, but I don't know that theCUBE would end up being specialized. >> It's good banner advertising. No, seriously all fun, it's all fun. Cisco Live in Europe. Is there a difference between European and U.S.? Are you seeing any differences in geographic talent? >> You know what, the first couple of years that we did it, I think there was a bigger difference. It felt like there were different topics that were very popular in the U.S., slightly different in Europe. Last year and this year I feel, like they have converged. It's the same focus on DevOps, automation, security is a huge focus in both places. And it also feels like the interest and level of the people attending has also converged. It's really similar. Congratulations, it's been fun to watch the rise and success of DevNet, continues to be strong, obviously in the hub here, and the DevNet zone behind us, packed sessions. >> Mandy: Yes, yes. >> What's the biggest surprise for you guys in terms of things that you didn't expect or some of the success, what's jumped out? >> Yeah, I think, you know, one of the points that I want to make sure we also cover and it has been an added benefit. We were hoping it would happen, we just didn't realize it would happen this soon. We're attracting new companies, new partners, so the specialization won't just be available for our traditional VARs. This is also available for our non resellers and we are finding different companies accessing DevNet resources and learning these skills. So that's been a really great benefit of DevNet overall. >> Definitely, my favorite surprises are when I show up at the community events and I hear from someone I met last year what they went back and did, and the change that they drove in their company. And I think we're seeing those across the board of people who start a grassroots movement, take back some new ideas, really create change, and then they come back and we get to hear about that from them. Those are my favorite surprises. >> And I tell you, we've known for years how important the developer is, but I think the timing on this has been perfect because it is no longer just, Oh, the developer has some tools that they'd liked in the corner. The developer connected to the business and driving things forward. >> Mandy: Exactly. So perfect timing, congratulations on the certification-- >> The other thing that's been great is that Cisco itself, we now have APIs across the whole portfolio and up and down the stack. So that's been a wonderful thing to see come together because it opens up possibilities for all these developers. >> So Cisco is API first company? >> We are building APIs everywhere we can, and the community is taking them and finding creative things to build. >> Well, it's been fun to watch you guys change Cisco, but also impact customers has been great to watch. Par many thanks for coming on, appreciate it. >> Yeah, thank you. >> theCUBE's live coverage here in Barcelona for Cisco Live 2020 I'm John Furrier with Dave Vellante, Stu Miniman. Be right back with more after this short break. (upbeat music)

>>Welcome back, everyone live here at Supercomputing 22 in Dallas, Texas. I'm John for host of the Queue here at Paul Gillin, editor of Silicon Angle, getting all the stories, bringing it to you live. Supercomputer TV is the queue right now. And bringing all the action Bresniker, chief architect of Hewlett Packard Labs with HP Cube alumnis here to talk about Supercomputing Road to Quantum. Kirk, great to see you. Thanks for coming on. >>Thanks for having me guys. Great to be >>Here. So Paul and I were talking and we've been covering, you know, computing as we get into the large scale cloud now on premises compute has been one of those things that just never stops. No one ever, I never heard someone say, I wanna run my application or workload on slower, slower hardware or processor or horsepower. Computing continues to go, but this, we're at a step function. It feels like we're at a level where we're gonna unleash new, new creativity, new use cases. You've been kind of working on this for many, many years at hp, Hewlett Packard Labs, I remember the machine and all the predecessor r and d. Where are we right now from your standpoint, HPE standpoint? Where are you in the computing? It's as a service, everything's changing. What's your view? >>So I think, you know, you capture so well. You think of the capabilities that you create. You create these systems and you engineer these amazing products and then you think, whew, it doesn't get any better than that. And then you remind yourself as an engineer. But wait, actually it has to, right? It has to because we need to continuously provide that next generation of scientists and engineer and artists and leader with the, with the tools that can do more and do more frankly with less. Because while we want want to run the program slower, we sure do wanna run them for less energy. And figuring out how we accomplish all of those things, I think is, is really where it's gonna be fascinating. And, and it's also, we think about that, we think about that now, scale data center billion, billion operations per second, the new science, arts and engineering that we'll create. And yet it's also what's beyond what's beyond that data center. How do we hook it up to those fantastic scientific instruments that are capable to generate so much information? We need to understand how we couple all of those things together. So I agree, we are at, at an amazing opportunity to raise the aspirations of the next generation. At the same time we have to think about what's coming next in terms of the technology. Is the silicon the only answer for us to continue to advance? >>You know, one of the big conversations is like refactoring, replatforming, we have a booth behind us that's doing energy. You can build it in data centers for compute. There's all kinds of new things. Is there anything in the paradigm of computing and now on the road to quantum, which I know you're involved, I saw you have on LinkedIn, you have an open rec for that. What paradigm elements are changing that weren't in play a few years ago that you're looking at right now as you look at the 20 mile stair into quantum? >>So I think for us it's fascinating because we've had a tailwind at our backs my whole career, 33 years at hp. And what I could count on was transistors got at first they got cheaper, faster and they use less energy. And then, you know, that slowed down a little bit. Now they're still cheaper and faster. As we look in that and that Moore's law continues to flatten out of it, there has to be something better to do than, you know, yet another copy of the prior design opening up that diversity of approach. And whether that is the amazing wafer scale accelerators, we see these application specific silicon and then broadening out even farther next to the next to the silicon. Here's the analog computational accelerator here is now the, the emergence of a potential quantum accelerator. So seeing that diversity of approaches, but what we have to happen is we need to harness all of those efficiencies and yet we still have to realize that there are human beings that need to create the application. So how do we bridge, how do we accommodate the physical of, of new kinds of accelerator? How do we imagine the cyber physical connection to the, to the rest of the supercomputer? And then finally, how do we bridge that productivity gap? Especially not for people who like me who have been around for a long time, we wanna think about that next generation cuz they're the ones that need to solve the problems and write the code that will do it. >>You mentioned what exists beyond silicon. In fact, are you looking at different kinds of materials that computers in the future will be built upon? >>Oh absolutely. You think of when, when we, we look at the quantum, the quantum modalities then, you know, whether it is a trapped ion or a superconducting, a piece of silicon or it is a neutral ion. There's just no, there's about half a dozen of these novel systems because really what we're doing when we're using a a quantum mechanical computer, we're creating a tiny universe. We're putting a little bit of material in there and we're manipulating at, at the subatomic level, harnessing the power of of, of quantum physics. That's an incredible challenge. And it will take novel materials, novel capabilities that we aren't just used to seeing. Not many people have a helium supplier in their data center today, but some of them might tomorrow. And understanding again, how do we incorporate industrialize and then scale all of these technologies. >>I wanna talk Turkey about quantum because we've been talking for, for five years. We've heard a lot of hyperbole about quantum. We've seen some of your competitors announcing quantum computers in the cloud. I don't know who's using these, these computers, what kind of work they're being used, how much of the, how real is quantum today? How close are we to having workable true quantum computers and what can you point to any examples of how it's being, how that technology is being used in the >>Field? So it, it remains nascent. We'll put it that way. I think part of the challenge is we see this low level technology and of course it was, you know, professor Richard Fineman who first pointed us in this direction, you know, more than 30 years ago. And you know, I I I trust his judgment. Yes. You know that there's probably some there there especially for what he was doing, which is how do we understand and engineer systems at the quantum mechanical level. Well he said a quantum mechanical system's probably the way to go. So understanding that, but still part of the challenge we see is that people have been working on the low level technology and they're reaching up to wondering will I eventually have a problem that that I can solve? And the challenge is you can improve something every single day and if you don't know where the bar is, then you don't ever know if you'll be good enough. >>I think part of the approach that we like to understand, can we start with the problem, the thing that we actually want to solve and then figure out what is the bespoke combination of classical supercomputing, advanced AI accelerators, novel quantum quantum capabilities. Can we simulate and design that? And we think there's probably nothing better to do that than than an next to scale supercomputer. Yeah. Can we simulate and design that bespoke environment, create that digital twin of this environment and if we, we've simulated it, we've designed it, we can analyze it, see is it actually advantageous? Cuz if it's not, then we probably should go back to the drawing board. And then finally that then becomes the way in which we actually run the quantum mechanical system in this hybrid environment. >>So it's na and you guys are feeling your way through, you get some moonshot, you work backwards from use cases as a, as a more of a discovery navigational kind of mission piece. I get that. And Exoscale has been a great role for you guys. Congratulations. Has there been strides though in quantum this year? Can you point to what's been the, has the needle moved a little bit a lot or, I mean it's moving I guess to some, there's been some talk but we haven't really been able to put our finger on what's moving, like what need, where's the needle moved I >>Guess in quantum. And I think, I think that's part of the conversation that we need to have is how do we measure ourselves. I know at the World Economic Forum, quantum Development Network, we had one of our global future councils on the future of quantum computing. And I brought in a scene I EEE fellow Par Gini who, you know, created the international technology roadmap for semiconductors. And I said, Paulo, could you come in and and give us examples, how was the semiconductor community so effective not only at developing the technology but predicting the development of technology so that whether it's an individual deciding if they should change careers or it's a nation state deciding if they should spend a couple billion dollars, we have that tool to predict the rate of change and improvement. And so I think that's part of what we're hoping by participating will bring some of that road mapping skill and technology and understanding so we can make those better reasoned investments. >>Well it's also fun to see super computing this year. Look at the bigger picture, obviously software cloud natives running modern applications, infrastructure as code that's happening. You're starting to see the integration of, of environments almost like a global distributed operating system. That's the way I call it. Silicon and advancements have been a big part of what we see now. Merchant silicon, but also dpu are on the scene. So the role role of silicon is there. And also we have supply chain problems. So how, how do you look at that as a a, a chief architect of h Hewlett Packard Labs? Because not only you have to invent the future and dream it up, but you gotta deal with the realities and you get the realities are silicon's great, we need more of that quantums around the corner, but supply chain, how do you solve that? What's your thoughts and how do you, how, how is HPE looking at silicon innovation and, and supply chain? >>And so for us it, it is really understanding that partnership model and understanding and contributing. And so I will do things like I happen to be the, the systems and architectures chapter editor for the I eee International Roadmap for devices and systems, that community that wants to come together and provide that guidance. You know, so I'm all about telling the semiconductor and the post semiconductor community, okay, this is where we need to compute. I have a partner in the applications and benchmark that says, this is what we need to compute. And when you can predict in the future about where you need to compute, what you need to compute, you can have a much richer set of conversations because you described it so well. And I think our, our senior fellow Nick Dubey would, he's coined the term internet of workflows where, you know, you need to harness everything from the edge device all the way through the extra scale computer and beyond. And it's not just one sort of static thing. It is a very interesting fluid topology. I'll use this compute at the edge, I'll do this information in the cloud, I want to have this in my exoscale data center and I still need to provide the tool so that an individual who's making that decision can craft that work flow across all of those different resources. >>And those workflows, by the way, are complicated. Now you got services being turned on and off. Observability is a hot area. You got a lot more data in in cycle inflow. I mean a lot more action. >>And I think you just hit on another key point for us and part of our research at labs, I have, as part of my other assignments, I help draft our AI ethics global policies and principles and not only tell getting advice about, about how we should live our lives, it also became the basis for our AI research lab at Shewl Packard Labs because they saw, here's a challenge and here's something where I can't actually believe, maintain my ethical compliance. I need to have engineer new ways of, of achieving artificial intelligence. And so much of that comes back to governance over that data and how can we actually create those governance systems and and do that out in the open >>That's a can of worms. We're gonna do a whole segment on that one, >>On that >>Technology, on that one >>Piece I wanna ask you, I mean, where rubber meets the road is where you're putting your dollars. So you've talked a lot, a lot of, a lot of areas of, of progress right now, where are you putting your dollars right now at Hewlett Packard Labs? >>Yeah, so I think when I draw, when I draw my 2030 vision slide, you know, I, for me the first column is about heterogeneous, right? How do we bring all of these novel computational approaches to be able to demonstrate their effectiveness, their sustainability, and also the productivity that we can drive from, from, from them. So that's my first column. My section column is that edge to exoscale workflow that I need to be able to harness all of those computational and data resources. I need to be aware of the energy consequence of moving data, of doing computation and find all of that while still maintaining and solving for security and privacy. But the last thing, and, and that's one was a, one was a how one was aware. The last thing is a who, right? And is is how do we take that subject matter expert? I think of a, a young engineer starting their career at hpe. It'll be very different than my 33 years. And part of it, you know, they will be undaunted by any, any scale. They will be cloud natives, maybe they metaverse natives, they will demand to design an open cooperative environment. So for me it's thinking about that individual and how do I take those capabilities, heterogeneous edge to exito scale workflows and then make them productive. And for me, that's, that's where we were putting our emphasis on those three. When, where and >>Who. Yeah. And making it compatible for the next generation. We see the student cluster competition going on over there. This is the only show that we cover that we've been to that is from the dorm room to the boardroom and this cuz Supercomputing now is elevating up into that workflow, into integration, multiple environments, cloud, premise, edge, metaverse. This is like a whole nother world. >>And, and, but I think it's, it's the way that regardless of which human pursuit you're in, you know, everyone is going to be demand simulation and modeling ai, ML and massive data m l and massive data analytics that's gonna be at heart of, of everything. And that's what you see. That's what I love about coming here. This isn't just the way we're gonna do science. This is the way we're gonna do everything. >>We're gonna come by your booth, check it out. We've talked to some of the folks, hpe obviously HPE Discover this year, GreenLake with center stage, it's now consumption is a service for technology. Whole nother ballgame. Congratulations on, on all this. I would say the massive, I won't say pivot, but you know, a change >>It >>Is and how you guys >>Operate. And you know, it's funny sometimes you think about the, the pivot to as a services benefiting the customer, but as someone who has supported designs over decades, you know, that ability to to to operate and at peak efficiency, to always keep in perfect operating order and to continuously change while still meeting the customer expectations that actually allows us to deliver innovation to our customers faster than when we are delivering warranted individual packaged products. >>Kirk, thanks for coming on Paul. Great conversation here. You know, the road to Quantum's gonna be paved through computing supercomputing software integrated workflows from the dorm room to the boardroom to Cube, bringing all the action here at Supercomputing 22. I'm Jacque Forer with Paul Gillin. Thanks for watching. We'll be right back.

>>Okay, we're back. I'm Dave Valante with The Cube and you're watching Evolving Influx DB into the smart data platform made possible by influx data. Anna East Otis Georgio is here. She's a developer advocate for influx data and we're gonna dig into the rationale and value contribution behind several open source technologies that Influx DB is leveraging to increase the granularity of time series analysis analysis and bring the world of data into realtime analytics. Anna is welcome to the program. Thanks for coming on. >>Hi, thank you so much. It's a pleasure to be here. >>Oh, you're very welcome. Okay, so IO X is being touted as this next gen open source core for Influx db. And my understanding is that it leverages in memory, of course for speed. It's a kilo store, so it gives you compression efficiency, it's gonna give you faster query speeds, it gonna use store files and object storages. So you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features, but what are the high level value points that people should understand? >>Sure, that's a great question. So some of the main requirements that IOCs is trying to achieve and some of the most impressive ones to me, the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want, whether that's lift tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metrics queries, we also wanna have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import, super useful. Also, broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like sql, Python, and maybe even pandas in the future. >>Okay, so a lot there. Now we talked to Brian about how you're using Rust and and which is not a new programming language and of course we had some drama around Russ during the pandemic with the Mozilla layoffs, but the formation of the Russ Foundation really addressed any of those concerns. You got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really, adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with rust, but why rust as an alternative to say c plus plus for example? >>Sure, that's a great question. So Rust was chosen because of his exceptional performance and rebi reliability. So while rust is synt tactically similar to c c plus plus and it has similar performance, it also compiles to a native code like c plus plus. But unlike c plus plus, it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers and dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like c plus plus. So Russ like helps meet that requirement of having no limits on card for example, because it's, we're also using the Russ implementation of Apache Arrow and this control over memory and also Russ, Russ Russ's packaging system called crates IO offers everything that you need out of the box to have features like AY and a weight to fixed race conditions to protect against buffering overflows and to ensure thread safe ay caching structures as well. So essentially it's just like has all the control, all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high ity use cases. >>Yeah, and the more I learned about the the new engine and the, and the platform IOCs et cetera, you know, you, you see things like, you know, the old days not even to even today you do a lot of garbage collection in these, in these systems and there's an inverse, you know, impact relative to performance. So it looks like you're really, you know, the community is modernizing the platform, but I wanna talk about Apache Arrow for a moment. It's designed to address the constraints that are associated with analyzing large data sets. We, we know that, but please explain why, what, what is Arrow and and what does it bring to Influx db? >>Sure, yeah. So Arrow is a, a framework for defining in memory calmer data and so much of the efficiency and performance of IOCs comes from taking advantage of calmer data structures. And I will, if you don't mind, take a moment to kind of illustrate why calmer data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our stove. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value, maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the stove. Well usually our room temperature is regulated so those values don't change very often. >>So when you have calm oriented st calm oriented storage, essentially you take each row, each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same, then you'll, you might be able to imagine how equal values will then neighbor each other and when they neighbor each other in the storage format. This provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you wanna define like the min and max value of the temperature in the room across a thousand different points, you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of calmer oriented storage. >>So if you had a row oriented storage, you'd first have to look at every field like the temperature in, in the room and the temperature of the stove. You'd have to go across every tag value that maybe describes where the room is located or what model the stove is. And every timestamp you'd then have to pluck out that one temperature value that you want at that one times stamp and do that for every single row. So you're scanning across a ton more data and that's why row oriented doesn't provide the same efficiency as calmer and Apache Arrow is in memory calmer data, calmer data fit framework. So that's where a lot of the advantages come >>From. Okay. So you've basically described like a traditional database, a row approach, but I've seen like a lot of traditional databases say, okay, now we've got, we can handle colo format versus what you're talking about is really, you know, kind of native it, is it not as effective as the, is the form not as effective because it's largely a, a bolt on? Can you, can you like elucidate on that front? >>Yeah, it's, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why, why RO row oriented storage isn't as efficient as calm, calmer oriented storage. >>Yeah. Got it. So let's talk about Arrow data fusion. What is data fusion? I know it's written in rust, but what does it bring to to the table here? >>Sure. So it's an extensible query execution framework and it uses Arrow as its in memory format. So the way that it helps influx DB IOx is that okay, it's great if you can write unlimited amount of cardinality into influx cbis, but if you don't have a query engine that can successfully query that data, then I don't know how much value it is for you. So data fusion helps enable the, the query process and transformation of that data. It also has a PANDAS API so that you could take advantage of PDA's data frames as well and all of the machine learning tools associated with pandas. >>Okay. You're also leveraging par K in the platform course. We heard a lot about Par K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Par K and why is it important? >>Sure. So Par K is the calm oriented durable file format. So it's important because it'll enable bulk import and bulk export. It has compatibility with Python and pandas so it supports a broader ecosystem. Parque files also take very little disc disc space and they're faster to scan because again they're column oriented in particular, I think PAR K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the, the benefits of par k. >>Got it. Very popular. So and these, what exactly is influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >>Sure. So Influx DB first has contributed a lot of different, different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing with flux. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up, then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >>Yeah. Got it. You got that virtuous cycle going, the people call it the flywheel. Give us your last thoughts and kind of summarize, you know, where what, what the big takeaways are from your perspective. >>So I think the big takeaway is that influx data is doing a lot of really exciting things with Influx DB IOCs and I really encourage if you are interested in learning more about the technologies that Influx is leveraging to produce IOCs, the challenges associated with it and all of the hard work questions and I just wanna learn more, then I would encourage you to go to the monthly tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel. Look for the influx D DB underscore IAC channel specifically to learn more about how to join those office hours and those monthly tech tech talks as well as ask any questions they have about IOCs, what to expect and what you'd like to learn more about. I as a developer advocate, I wanna answer your questions. So if there's a particular technology or stack that you wanna dive deeper into and want more explanation about how influx TB leverages it to build IOCs, I will be really excited to produce content on that topic for you. >>Yeah, that's awesome. You guys have a really rich community, collaborate with your peers, solve problems, and you guys super responsive, so really appreciate that. All right, thank you so much and East for explaining all this open source stuff to the audience and why it's important to the future of data. >>Thank you. I really appreciate it. >>All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yokum. He's the director of engineering for Influx Data and we're gonna talk about how you update a SaaS engine while the plane is flying at 30,000 feet. You don't wanna miss this.

>>This past May, The Cube in collaboration with Influx data shared with you the latest innovations in Time series databases. We talked at length about why a purpose built time series database for many use cases, was a superior alternative to general purpose databases trying to do the same thing. Now, you may, you may remember the time series data is any data that's stamped in time, and if it's stamped, it can be analyzed historically. And when we introduced the concept to the community, we talked about how in theory, those time slices could be taken, you know, every hour, every minute, every second, you know, down to the millisecond and how the world was moving toward realtime or near realtime data analysis to support physical infrastructure like sensors and other devices and IOT equipment. A time series databases have had to evolve to efficiently support realtime data in emerging use cases in iot T and other use cases. >>And to do that, new architectural innovations have to be brought to bear. As is often the case, open source software is the linchpin to those innovations. Hello and welcome to Evolving Influx DB into the smart Data platform, made possible by influx data and produced by the Cube. My name is Dave Valante and I'll be your host today. Now in this program we're going to dig pretty deep into what's happening with Time series data generally, and specifically how Influx DB is evolving to support new workloads and demands and data, and specifically around data analytics use cases in real time. Now, first we're gonna hear from Brian Gilmore, who is the director of IOT and emerging technologies at Influx Data. And we're gonna talk about the continued evolution of Influx DB and the new capabilities enabled by open source generally and specific tools. And in this program you're gonna hear a lot about things like Rust, implementation of Apache Arrow, the use of par k and tooling such as data fusion, which powering a new engine for Influx db. >>Now, these innovations, they evolve the idea of time series analysis by dramatically increasing the granularity of time series data by compressing the historical time slices, if you will, from, for example, minutes down to milliseconds. And at the same time, enabling real time analytics with an architecture that can process data much faster and much more efficiently. Now, after Brian, we're gonna hear from Anna East Dos Georgio, who is a developer advocate at In Flux Data. And we're gonna get into the why of these open source capabilities and how they contribute to the evolution of the Influx DB platform. And then we're gonna close the program with Tim Yokum, he's the director of engineering at Influx Data, and he's gonna explain how the Influx DB community actually evolved the data engine in mid-flight and which decisions went into the innovations that are coming to the market. Thank you for being here. We hope you enjoy the program. Let's get started. Okay, we're kicking things off with Brian Gilmore. He's the director of i t and emerging Technology at Influx State of Bryan. Welcome to the program. Thanks for coming on. >>Thanks Dave. Great to be here. I appreciate the time. >>Hey, explain why Influx db, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >>No, no, not at all. I mean, I think it's, for us, it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like sql, you know, query support, things like that, we have to figure out a way to, to execute those for them in a way that will scale long term. And then we also, we wanna make sure we're innovating, we're sort of staying ahead of the market as well and sort of anticipating those future needs. So, you know, this is really a, a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine, but you know, initially the customers who are using us are gonna see just great improvements in performance, you know, especially those that are working at the top end of the, of the workload scale, you know, the massive data volumes and things like that. >>Yeah, and we're gonna get into that today and the architecture and the like, but what was the catalyst for the enhancements? I mean, when and how did this all come about? >>Well, I mean, like three years ago we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product, you know, and, and sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was, that was, that was a long journey I guess, you know, phase one was, you know, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to, to optimize for like multi-tenant, multi-cloud, be able to, to host it in a truly like sass manner where we could use, you know, some type of customer activity or consumption as the, the pricing vector, you know, And, and that was sort of the birth of the, of the real first influx DB cloud, you know, which has been really successful. >>We've seen, I think like 60,000 people sign up and we've got tons and tons of, of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a, on a daily basis, you know, and having that sort of big pool of, of very diverse and very customers to chat with as they're using the product, as they're giving us feedback, et cetera, has has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that and then also making these big leaps as we're doing with this, with this new engine. >>Right. So you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really wanna understand how much of a pivot this is and what, what does it take to make that shift from, you know, time series, you know, specialist to real time analytics and being able to support both? >>Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. You know, time series data is always gonna be fundamental and sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. You know, the time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics, if we're being honest though, I think our, our user base is well aware that the way we were architected was much more towards those sort of like backwards looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a, and a, you know, a time to response on the queries, and can we get that to the point where the results sets are coming back so quickly from the time of query that we can like limit that window down to minutes and then seconds. >>And now with this new engine, we're really starting to talk about a query window that could be like returning results in, in, you know, milliseconds of time since it hit the, the, the ingest queue. And that's, that's really getting to the point where as your data is available, you can use it and you can query it, you can visualize it, and you can do all those sort of magical things with it, you know? And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the, the real time queries, the, the multiple language query support, but, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a a limited number of customers, strategic customers and strategic availability zones to start. But you know, everybody over time. >>So you're basically going from what happened to in, you can still do that obviously, but to what's happening now in the moment? >>Yeah, yeah. I mean if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the, by the underlying data collection, the architecture, the infrastructure, the, you know, the, the devices and you know, the sort of highly distributed nature of all of this. So yeah, I mean, getting, getting a customer or a user to be able to use the data as soon as it is available is what we're after here. >>I always thought, you know, real, I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >>Yeah, it's, it's, I mean it is operationally or operational real time is different, you know, and that's one of the things that really triggered us to know that we were, we were heading in the right direction, is just how many sort of operational customers we have. You know, everything from like aerospace and defense. We've got companies monitoring satellites, we've got tons of industrial users, users using us as a processes storing on the plant floor, you know, and, and if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're gonna do here is we're gonna start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems, certainly not their, their historians and databases. >>I, is this available, these innovations to influx DB cloud customers only who can access this capability? >>Yeah. I mean commercially and today, yes. You know, I think we want to emphasize that's a, for now our goal is to get our latest and greatest and our best to everybody over time. Of course. You know, one of the things we had to do here was like we double down on sort of our, our commitment to open source and availability. So like anybody today can take a look at the, the libraries in on our GitHub and, you know, can ex inspect it and even can try to, you know, implement or execute some of it themselves in their own infrastructure. You know, we are, we're committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. >>And so just, you know, being careful, maybe a little cautious in terms of, of, of how big we go with this right away, just sort of both limits, you know, the risk of, of, you know, any issues that can come with new software rollouts. We haven't seen anything so far, but also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products, but once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's gonna be exciting time for the whole ecosystem. >>Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are gonna help deliver on this vision. What, what should we know there? >>Well, I mean, I think foundationally we built the, the new core on Rust. You know, this is a new very sort of popular systems language, you know, it's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well. And if it does find error conditions, I mean we, we've loved working with Go and, you know, a lot of our libraries will continue to, to be sort of implemented in Go, but you know, when it came to this particular new engine, you know, that power performance and stability rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parque for persistence. I think for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our, our time series merged Trees, this is a big break from that, you know, arrow on the sort of in MI side and then Par K in the on disk side. >>It, it allows us to, to present, you know, a unified set of APIs for those really fast real time inquiries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that PARQUE format, which is also cool because there's an entire ecosystem sort of popping up around Parque in terms of the machine learning community, you know, and getting that all to work, we had to glue it together with aero flight. That's sort of what we're using as our, our RPC component. You know, it handles the orchestration and the, the transportation of the Coer data. Now we're moving to like a true Coer database model for this, this version of the engine, you know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like blurring that line between real time and historical data. It's, you know, it's, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >>Yeah. Again, I mean, it's funny you mentioned Rust. It is, it's been around for a long time, but it's popularity is, is you know, really starting to hit that steep part of the S-curve. And, and we're gonna dig into to more of that, but give us any, is there anything else that we should know about Bryan? Give us the last word? >>Well, I mean, I think first I'd like everybody sort of watching just to like take a look at what we're offering in terms of early access in beta programs. I mean, if, if, if you wanna participate or if you wanna work sort of in terms of early access with the, with the new engine, please reach out to the team. I'm sure you know, there's a lot of communications going out and you know, it'll be highly featured on our, our website, you know, but reach out to the team, believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're, we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to because we can flip a lot of stuff on, especially in cloud through feature flags. >>But if there's something new that you wanna try out, we'd just love to hear from you. And then, you know, our goal would be that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to, to sort of build the next versions of your business. Because you know, the whole database, the ecosystem as it expands out into to, you know, this vertically oriented stack of cloud services and enterprise databases and edge databases, you know, it's gonna be what we all make it together, not just, you know, those of us who were employed by Influx db. And then finally I would just say please, like watch in ICE in Tim's sessions, like these are two of our best and brightest, They're totally brilliant, completely pragmatic, and they are most of all customer obsessed, which is amazing. And there's no better takes, like honestly on the, the sort of technical details of this, then there's, especially when it comes to like the value that these investments will, will bring to our customers and our communities. So encourage you to, to, you know, pay more attention to them than you did to me, for sure. >>Brian Gilmore, great stuff. Really appreciate your time. Thank you. >>Yeah, thanks Dave. It was awesome. Look forward to it. >>Yeah, me too. Looking forward to see how the, the community actually applies these new innovations and goes, goes beyond just the historical into the real time really hot area. As Brian said in a moment, I'll be right back with Anna East dos Georgio to dig into the critical aspects of key open source components of the Influx DB engine, including Rust, Arrow, Parque, data fusion. Keep it right there. You don't wanna miss this >>Time series Data is everywhere. The number of sensors, systems and applications generating time series data increases every day. All these data sources producing so much data can cause analysis paralysis. Influx DB is an entire platform designed with everything you need to quickly build applications that generate value from time series data influx. DB Cloud is a serverless solution, which means you don't need to buy or manage your own servers. There's no need to worry about provisioning because you only pay for what you use. Influx DB Cloud is fully managed so you get the newest features and enhancements as they're added to the platform's code base. It also means you can spend time building solutions and delivering value to your users instead of wasting time and effort managing something else. Influx TVB Cloud offers a range of security features to protect your data, multiple layers of redundancy ensure you don't lose any data access controls ensure that only the people who should see your data can see it. >>And encryption protects your data at rest and in transit between any of our regions or cloud providers. InfluxDB uses a single API across the entire platform suite so you can build on open source, deploy to the cloud and then then easily query data in the cloud at the edge or on prem using the same scripts. And InfluxDB is schemaless automatically adjusting to changes in the shape of your data without requiring changes in your application. Logic. InfluxDB Cloud is production ready from day one. All it needs is your data and your imagination. Get started today@influxdata.com slash cloud. >>Okay, we're back. I'm Dave Valante with a Cube and you're watching evolving Influx DB into the smart data platform made possible by influx data. Anna ETOs Georgio is here, she's a developer advocate for influx data and we're gonna dig into the rationale and value contribution behind several open source technologies that Influx DB is leveraging to increase the granularity of time series analysis analysis and bring the world of data into real-time analytics and is welcome to the program. Thanks for coming on. >>Hi, thank you so much. It's a pleasure to be here. >>Oh, you're very welcome. Okay, so IX is being touted as this next gen open source core for Influx db. And my understanding is that it leverages in memory of course for speed. It's a kilo store, so it gives you a compression efficiency, it's gonna give you faster query speeds, you store files and object storage, so you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features, but what are the high level value points that people should understand? >>Sure, that's a great question. So some of the main requirements that IOx is trying to achieve and some of the most impressive ones to me, the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want, whether that's live tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metrics queries, we also wanna have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import super useful. Also broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like sql, Python, and maybe even pandas in the future. >>Okay, so lot there. Now we talked to Brian about how you're using Rust and which is not a new programming language and of course we had some drama around Rust during the pandemic with the Mozilla layoffs, but the formation of the Rust Foundation really addressed any of those concerns. You got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really, the adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with rust, but why rust as an alternative to say c plus plus for example? >>Sure, that's a great question. So Russ was chosen because of his exceptional performance and reliability. So while Russ is synt tactically similar to c plus plus and it has similar performance, it also compiles to a native code like c plus plus. But unlike c plus plus, it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers. And dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like c plus plus. So Russ like helps meet that requirement of having no limits on ality, for example, because it's, we're also using the Russ implementation of Apache Arrow and this control over memory and also Russ Russ's packaging system called crates IO offers everything that you need out of the box to have features like AY and a weight to fix race conditions, to protection against buffering overflows and to ensure thread safe async cashing structures as well. So essentially it's just like has all the control, all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high ity use cases. >>Yeah, and the more I learn about the, the new engine and, and the platform IOCs et cetera, you know, you, you see things like, you know, the old days not even to even today you do a lot of garbage collection in these, in these systems and there's an inverse, you know, impact relative to performance. So it looks like you really, you know, the community is modernizing the platform, but I wanna talk about Apache Arrow for a moment. It it's designed to address the constraints that are associated with analyzing large data sets. We, we know that, but please explain why, what, what is Arrow and and what does it bring to Influx db? >>Sure, yeah. So Arrow is a, a framework for defining in memory calmer data. And so much of the efficiency and performance of IOx comes from taking advantage of calmer data structures. And I will, if you don't mind, take a moment to kind of of illustrate why column or data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our stove. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value, maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the stove. Well usually our room temperature is regulated so those values don't change very often. >>So when you have calm oriented st calm oriented storage, essentially you take each row, each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same, then you'll, you might be able to imagine how equal values will then enable each other and when they neighbor each other in the storage format, this provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you wanna define like the men and max value of the temperature in the room across a thousand different points, you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of calmer oriented storage. >>So if you had a row oriented storage, you'd first have to look at every field like the temperature in, in the room and the temperature of the stove. You'd have to go across every tag value that maybe describes where the room is located or what model the stove is. And every timestamp you'd then have to pluck out that one temperature value that you want at that one time stamp and do that for every single row. So you're scanning across a ton more data and that's why Rowe Oriented doesn't provide the same efficiency as calmer and Apache Arrow is in memory calmer data, commoner data fit framework. So that's where a lot of the advantages come >>From. Okay. So you basically described like a traditional database, a row approach, but I've seen like a lot of traditional database say, okay, now we've got, we can handle colo format versus what you're talking about is really, you know, kind of native i, is it not as effective? Is the, is the foreman not as effective because it's largely a, a bolt on? Can you, can you like elucidate on that front? >>Yeah, it's, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why, why RO row oriented storage isn't as efficient as calm, calmer oriented storage. Yeah. >>Got it. So let's talk about Arrow Data Fusion. What is data fusion? I know it's written in Rust, but what does it bring to the table here? >>Sure. So it's an extensible query execution framework and it uses Arrow as it's in memory format. So the way that it helps in influx DB IOCs is that okay, it's great if you can write unlimited amount of cardinality into influx Cbis, but if you don't have a query engine that can successfully query that data, then I don't know how much value it is for you. So Data fusion helps enable the, the query process and transformation of that data. It also has a PANDAS API so that you could take advantage of PANDAS data frames as well and all of the machine learning tools associated with Pandas. >>Okay. You're also leveraging Par K in the platform cause we heard a lot about Par K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Parque and why is it important? >>Sure. So parque is the column oriented durable file format. So it's important because it'll enable bulk import, bulk export, it has compatibility with Python and Pandas, so it supports a broader ecosystem. Par K files also take very little disc disc space and they're faster to scan because again, they're column oriented in particular, I think PAR K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the, the benefits of par k. >>Got it. Very popular. So and he's, what exactly is influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >>Sure. So Influx DB first has contributed a lot of different, different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing with flux. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up, then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >>Yeah. Got it. You got that virtuous cycle going, the people call the flywheel. Give us your last thoughts and kind of summarize, you know, where what, what the big takeaways are from your perspective. >>So I think the big takeaway is that influx data is doing a lot of really exciting things with Influx DB IOx and I really encourage, if you are interested in learning more about the technologies that Influx is leveraging to produce IOCs, the challenges associated with it and all of the hard work questions and you just wanna learn more, then I would encourage you to go to the monthly Tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel look for the influx DDB unders IAC channel specifically to learn more about how to join those office hours and those monthly tech tech talks as well as ask any questions they have about iacs, what to expect and what you'd like to learn more about. I as a developer advocate, I wanna answer your questions. So if there's a particular technology or stack that you wanna dive deeper into and want more explanation about how INFLUX DB leverages it to build IOCs, I will be really excited to produce content on that topic for you. >>Yeah, that's awesome. You guys have a really rich community, collaborate with your peers, solve problems, and, and you guys super responsive, so really appreciate that. All right, thank you so much Anise for explaining all this open source stuff to the audience and why it's important to the future of data. >>Thank you. I really appreciate it. >>All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yoakum, he's the director of engineering for Influx Data and we're gonna talk about how you update a SAS engine while the plane is flying at 30,000 feet. You don't wanna miss this. >>I'm really glad that we went with InfluxDB Cloud for our hosting because it has saved us a ton of time. It's helped us move faster, it's saved us money. And also InfluxDB has good support. My name's Alex Nada. I am CTO at Noble nine. Noble Nine is a platform to measure and manage service level objectives, which is a great way of measuring the reliability of your systems. You can essentially think of an slo, the product we're providing to our customers as a bunch of time series. So we need a way to store that data and the corresponding time series that are related to those. The main reason that we settled on InfluxDB as we were shopping around is that InfluxDB has a very flexible query language and as a general purpose time series database, it basically had the set of features we were looking for. >>As our platform has grown, we found InfluxDB Cloud to be a really scalable solution. We can quickly iterate on new features and functionality because Influx Cloud is entirely managed, it probably saved us at least a full additional person on our team. We also have the option of running InfluxDB Enterprise, which gives us the ability to even host off the cloud or in a private cloud if that's preferred by a customer. Influx data has been really flexible in adapting to the hosting requirements that we have. They listened to the challenges we were facing and they helped us solve it. As we've continued to grow, I'm really happy we have influx data by our side. >>Okay, we're back with Tim Yokum, who is the director of engineering at Influx Data. Tim, welcome. Good to see you. >>Good to see you. Thanks for having me. >>You're really welcome. Listen, we've been covering open source software in the cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem. The cloud has been being built out on open source, mobile, social platforms, key databases, and of course influx DB and influx data has been a big consumer and contributor of open source software. So my question to you is, where have you seen the biggest bang for the buck from open source software? >>So yeah, you know, influx really, we thrive at the intersection of commercial services and open, so open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services temping engines. Our, our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants and like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product influx db. >>You know, but I gotta ask you, Tim, because one of the challenge that that we've seen in particular, you saw this in the heyday of Hadoop, the, the innovations come so fast and furious and as a software company you gotta place bets, you gotta, you know, commit people and sometimes those bets can be risky and not pay off well, how have you managed this challenge? >>Oh, it moves fast. Yeah, that, that's a benefit though because it, the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we, what we tend to do is, is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example, that ecosystem is driven by thousands of intelligent developers, engineers, builders, they're adding value every day. So we have to really keep up with that. And as the stack changes, we, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's, it's something that we just do every day. >>So we have a survey partner down in New York City called Enterprise Technology Research etr, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity particularly, you know, along with cloud. But, but really Kubernetes is just, you know, still up until the right consistently even with, you know, the macro headwinds and all, all of the stuff that we're sick of talking about. But, so what are you doing with Kubernetes in the platform? >>Yeah, it, it's really central to our ability to run the product. When we first started out, we were just on AWS and, and the way we were running was, was a little bit like containers junior. Now we're running Kubernetes everywhere at aws, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code so our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google and figure out how to deliver services on those three clouds with all of their differences. >>Just to follow up on that, is it, no. So I presume it's sounds like there's a PAs layer there to allow you guys to have a consistent experience across clouds and out to the edge, you know, wherever is that, is that correct? >>Yeah, so we've basically built more or less platform engineering, This is the new hot phrase, you know, it, it's, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that, that just gets all of the underlying infrastructure out of the way and, and lets them focus on delivering influx cloud. >>Yeah, and I know I'm taking a little bit of a tangent, but is that, that, I'll call it a PAs layer if I can use that term. Is that, are there specific attributes to Influx db or is it kind of just generally off the shelf paths? You know, are there, is, is there any purpose built capability there that, that is, is value add or is it pretty much generic? >>So we really build, we, we look at things through, with a build versus buy through a, a build versus by lens. Some things we want to leverage cloud provider services, for instance, Postgres databases for metadata, perhaps we'll get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can, can deliver on that has consistency that is, is all generated from code that we can as a, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions and in no time. >>So how, so sometimes you build, sometimes you buy it. How do you make those decisions and and what does that mean for the, for the platform and for customers? >>Yeah, so what we're doing is, it's like everybody else will do, we're we're looking for trade offs that make sense. You know, we really want to protect our customers data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers you don't even see that, but we don't want to try to reinvent the wheel, like I had mentioned with SQL data stores for metadata, perhaps let's build on top of what of these three large cloud providers have already perfected. And we can then focus on our platform engineering and we can have our developers then focus on the influx data, software, influx, cloud software. >>So take it to the customer level, what does it mean for them? What's the value that they're gonna get out of all these innovations that we've been been talking about today and what can they expect in the future? >>So first of all, people who use the OSS product are really gonna be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across, over 4 billion series keys that people have stored. So there's a proven ability to scale now in terms of the open source, open source software and how we've developed the platform. You're getting highly available high cardinality time series platform. We manage it and, and really as, as I mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in real time. We deploy to our platform every day repeatedly all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change new features, better ways of doing deployments, safer ways of doing deployments. >>All of that happens behind the scenes. And like we had mentioned earlier, Kubernetes, I mean that, that allows us to get that done. We couldn't do it without having that platform as a, as a base layer for us to then put our software on. So we, we iterate quickly. When you're on the, the Influx cloud platform, you really are able to, to take advantage of new features immediately. We roll things out every day and as those things go into production, you have, you have the ability to, to use them. And so in the end we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let, let us do that for you. So, >>And that makes sense, but so is the, is the, are the innovations that we're talking about in the evolution of Influx db, do, do you see that as sort of a natural evolution for existing customers? I, is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >>Yeah, it really is it, it's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are, are really the hot thing. Iot, industrial iot especially, people want to just shove tons of data out there and be able to do queries immediately and they don't wanna manage infrastructure. What we've started to see are people that use the cloud service as their, their data store backbone and then they use edge computing with R OSS product to ingest data from say, multiple production lines and downsample that data, send the rest of that data off influx cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that and being in all sorts of different regions allows for people to really get out of the, the business of man trying to manage that big data, have us take care of that. And of course as we change the platform end users benefit from that immediately. And, >>And so obviously taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IOT and the Edge? How should we be thinking about the value that you bring from a security perspective? >>Yeah, we take, we take security super seriously. It, it's built into our dna. We do a lot of work to ensure that our platform is secure, that the data we store is, is kept private. It's of course always a concern. You see in the news all the time, companies being compromised, you know, that's something that you can have an entire team working on, which we do to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You know, you look at things like software, bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that, that's just part of our jobs to make sure that the platform that we're running it has, has fully vetted software and, and with open source especially, that's a lot of work. And so it's, it's definitely new territory. Supply chain attacks are, are definitely happening at a higher clip than they used to, but that is, that is really just part of a day in the, the life for folks like us that are, are building platforms. >>Yeah, and that's key. I mean especially when you start getting into the, the, you know, we talk about IOT and the operations technologies, the engineers running the, that infrastructure, you know, historically, as you know, Tim, they, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >>That >>Connected now, right? And so you've gotta have a partner that is again, take away that heavy lifting to r and d so you can focus on some of the other activities. Right. Give us the, the last word and the, the key takeaways from your perspective. >>Well, you know, from my perspective I see it as, as a a two lane approach with, with influx, with Anytime series data, you know, you've got a lot of stuff that you're gonna run on-prem, what you had mentioned, air gaping. Sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want torus their data to, to a company that's, that's got a full platform set up for them that they can build on, send that data over to the cloud, the cloud is not going away. I think more hybrid approach is, is where the future lives and that's what we're prepared for. >>Tim, really appreciate you coming to the program. Great stuff. Good to see you. >>Thanks very much. Appreciate it. >>Okay, in a moment I'll be back to wrap up. Today's session, you're watching The Cube. >>Are you looking for some help getting started with InfluxDB Telegraph or Flux Check >>Out Influx DB University >>Where you can find our entire catalog of free training that will help you make the most of your time series data >>Get >>Started for free@influxdbu.com. >>We'll see you in class. >>Okay, so we heard today from three experts on time series and data, how the Influx DB platform is evolving to support new ways of analyzing large data sets very efficiently and effectively in real time. And we learned that key open source components like Apache Arrow and the Rust Programming environment Data fusion par K are being leveraged to support realtime data analytics at scale. We also learned about the contributions in importance of open source software and how the Influx DB community is evolving the platform with minimal disruption to support new workloads, new use cases, and the future of realtime data analytics. Now remember these sessions, they're all available on demand. You can go to the cube.net to find those. Don't forget to check out silicon angle.com for all the news related to things enterprise and emerging tech. And you should also check out influx data.com. There you can learn about the company's products. You'll find developer resources like free courses. You could join the developer community and work with your peers to learn and solve problems. And there are plenty of other resources around use cases and customer stories on the website. This is Dave Valante. Thank you for watching Evolving Influx DB into the smart data platform, made possible by influx data and brought to you by the Cube, your leader in enterprise and emerging tech coverage.

>>This past May, The Cube in collaboration with Influx data shared with you the latest innovations in Time series databases. We talked at length about why a purpose built time series database for many use cases, was a superior alternative to general purpose databases trying to do the same thing. Now, you may, you may remember the time series data is any data that's stamped in time, and if it's stamped, it can be analyzed historically. And when we introduced the concept to the community, we talked about how in theory, those time slices could be taken, you know, every hour, every minute, every second, you know, down to the millisecond and how the world was moving toward realtime or near realtime data analysis to support physical infrastructure like sensors and other devices and IOT equipment. A time series databases have had to evolve to efficiently support realtime data in emerging use cases in iot T and other use cases. >>And to do that, new architectural innovations have to be brought to bear. As is often the case, open source software is the linchpin to those innovations. Hello and welcome to Evolving Influx DB into the smart Data platform, made possible by influx data and produced by the Cube. My name is Dave Valante and I'll be your host today. Now in this program we're going to dig pretty deep into what's happening with Time series data generally, and specifically how Influx DB is evolving to support new workloads and demands and data, and specifically around data analytics use cases in real time. Now, first we're gonna hear from Brian Gilmore, who is the director of IOT and emerging technologies at Influx Data. And we're gonna talk about the continued evolution of Influx DB and the new capabilities enabled by open source generally and specific tools. And in this program you're gonna hear a lot about things like Rust, implementation of Apache Arrow, the use of par k and tooling such as data fusion, which powering a new engine for Influx db. >>Now, these innovations, they evolve the idea of time series analysis by dramatically increasing the granularity of time series data by compressing the historical time slices, if you will, from, for example, minutes down to milliseconds. And at the same time, enabling real time analytics with an architecture that can process data much faster and much more efficiently. Now, after Brian, we're gonna hear from Anna East Dos Georgio, who is a developer advocate at In Flux Data. And we're gonna get into the why of these open source capabilities and how they contribute to the evolution of the Influx DB platform. And then we're gonna close the program with Tim Yokum, he's the director of engineering at Influx Data, and he's gonna explain how the Influx DB community actually evolved the data engine in mid-flight and which decisions went into the innovations that are coming to the market. Thank you for being here. We hope you enjoy the program. Let's get started. Okay, we're kicking things off with Brian Gilmore. He's the director of i t and emerging Technology at Influx State of Bryan. Welcome to the program. Thanks for coming on. >>Thanks Dave. Great to be here. I appreciate the time. >>Hey, explain why Influx db, you know, needs a new engine. Was there something wrong with the current engine? What's going on there? >>No, no, not at all. I mean, I think it's, for us, it's been about staying ahead of the market. I think, you know, if we think about what our customers are coming to us sort of with now, you know, related to requests like sql, you know, query support, things like that, we have to figure out a way to, to execute those for them in a way that will scale long term. And then we also, we wanna make sure we're innovating, we're sort of staying ahead of the market as well and sort of anticipating those future needs. So, you know, this is really a, a transparent change for our customers. I mean, I think we'll be adding new capabilities over time that sort of leverage this new engine, but you know, initially the customers who are using us are gonna see just great improvements in performance, you know, especially those that are working at the top end of the, of the workload scale, you know, the massive data volumes and things like that. >>Yeah, and we're gonna get into that today and the architecture and the like, but what was the catalyst for the enhancements? I mean, when and how did this all come about? >>Well, I mean, like three years ago we were primarily on premises, right? I mean, I think we had our open source, we had an enterprise product, you know, and, and sort of shifting that technology, especially the open source code base to a service basis where we were hosting it through, you know, multiple cloud providers. That was, that was, that was a long journey I guess, you know, phase one was, you know, we wanted to host enterprise for our customers, so we sort of created a service that we just managed and ran our enterprise product for them. You know, phase two of this cloud effort was to, to optimize for like multi-tenant, multi-cloud, be able to, to host it in a truly like sass manner where we could use, you know, some type of customer activity or consumption as the, the pricing vector, you know, And, and that was sort of the birth of the, of the real first influx DB cloud, you know, which has been really successful. >>We've seen, I think like 60,000 people sign up and we've got tons and tons of, of both enterprises as well as like new companies, developers, and of course a lot of home hobbyists and enthusiasts who are using out on a, on a daily basis, you know, and having that sort of big pool of, of very diverse and very customers to chat with as they're using the product, as they're giving us feedback, et cetera, has has, you know, pointed us in a really good direction in terms of making sure we're continuously improving that and then also making these big leaps as we're doing with this, with this new engine. >>Right. So you've called it a transparent change for customers, so I'm presuming it's non-disruptive, but I really wanna understand how much of a pivot this is and what, what does it take to make that shift from, you know, time series, you know, specialist to real time analytics and being able to support both? >>Yeah, I mean, it's much more of an evolution, I think, than like a shift or a pivot. You know, time series data is always gonna be fundamental and sort of the basis of the solutions that we offer our customers, and then also the ones that they're building on the sort of raw APIs of our platform themselves. You know, the time series market is one that we've worked diligently to lead. I mean, I think when it comes to like metrics, especially like sensor data and app and infrastructure metrics, if we're being honest though, I think our, our user base is well aware that the way we were architected was much more towards those sort of like backwards looking historical type analytics, which are key for troubleshooting and making sure you don't, you know, run into the same problem twice. But, you know, we had to ask ourselves like, what can we do to like better handle those queries from a performance and a, and a, you know, a time to response on the queries, and can we get that to the point where the results sets are coming back so quickly from the time of query that we can like limit that window down to minutes and then seconds. >>And now with this new engine, we're really starting to talk about a query window that could be like returning results in, in, you know, milliseconds of time since it hit the, the, the ingest queue. And that's, that's really getting to the point where as your data is available, you can use it and you can query it, you can visualize it, and you can do all those sort of magical things with it, you know? And I think getting all of that to a place where we're saying like, yes to the customer on, you know, all of the, the real time queries, the, the multiple language query support, but, you know, it was hard, but we're now at a spot where we can start introducing that to, you know, a a limited number of customers, strategic customers and strategic availability zones to start. But you know, everybody over time. >>So you're basically going from what happened to in, you can still do that obviously, but to what's happening now in the moment? >>Yeah, yeah. I mean if you think about time, it's always sort of past, right? I mean, like in the moment right now, whether you're talking about like a millisecond ago or a minute ago, you know, that's, that's pretty much right now, I think for most people, especially in these use cases where you have other sort of components of latency induced by the, by the underlying data collection, the architecture, the infrastructure, the, you know, the, the devices and you know, the sort of highly distributed nature of all of this. So yeah, I mean, getting, getting a customer or a user to be able to use the data as soon as it is available is what we're after here. >>I always thought, you know, real, I always thought of real time as before you lose the customer, but now in this context, maybe it's before the machine blows up. >>Yeah, it's, it's, I mean it is operationally or operational real time is different, you know, and that's one of the things that really triggered us to know that we were, we were heading in the right direction, is just how many sort of operational customers we have. You know, everything from like aerospace and defense. We've got companies monitoring satellites, we've got tons of industrial users, users using us as a processes storing on the plant floor, you know, and, and if we can satisfy their sort of demands for like real time historical perspective, that's awesome. I think what we're gonna do here is we're gonna start to like edge into the real time that they're used to in terms of, you know, the millisecond response times that they expect of their control systems, certainly not their, their historians and databases. >>I, is this available, these innovations to influx DB cloud customers only who can access this capability? >>Yeah. I mean commercially and today, yes. You know, I think we want to emphasize that's a, for now our goal is to get our latest and greatest and our best to everybody over time. Of course. You know, one of the things we had to do here was like we double down on sort of our, our commitment to open source and availability. So like anybody today can take a look at the, the libraries in on our GitHub and, you know, can ex inspect it and even can try to, you know, implement or execute some of it themselves in their own infrastructure. You know, we are, we're committed to bringing our sort of latest and greatest to our cloud customers first for a couple of reasons. Number one, you know, there are big workloads and they have high expectations of us. I think number two, it also gives us the opportunity to monitor a little bit more closely how it's working, how they're using it, like how the system itself is performing. >>And so just, you know, being careful, maybe a little cautious in terms of, of, of how big we go with this right away, just sort of both limits, you know, the risk of, of, you know, any issues that can come with new software rollouts. We haven't seen anything so far, but also it does give us the opportunity to have like meaningful conversations with a small group of users who are using the products, but once we get through that and they give us two thumbs up on it, it'll be like, open the gates and let everybody in. It's gonna be exciting time for the whole ecosystem. >>Yeah, that makes a lot of sense. And you can do some experimentation and, you know, using the cloud resources. Let's dig into some of the architectural and technical innovations that are gonna help deliver on this vision. What, what should we know there? >>Well, I mean, I think foundationally we built the, the new core on Rust. You know, this is a new very sort of popular systems language, you know, it's extremely efficient, but it's also built for speed and memory safety, which goes back to that us being able to like deliver it in a way that is, you know, something we can inspect very closely, but then also rely on the fact that it's going to behave well. And if it does find error conditions, I mean we, we've loved working with Go and, you know, a lot of our libraries will continue to, to be sort of implemented in Go, but you know, when it came to this particular new engine, you know, that power performance and stability rust was critical. On top of that, like, we've also integrated Apache Arrow and Apache Parque for persistence. I think for anybody who's really familiar with the nuts and bolts of our backend and our TSI and our, our time series merged Trees, this is a big break from that, you know, arrow on the sort of in MI side and then Par K in the on disk side. >>It, it allows us to, to present, you know, a unified set of APIs for those really fast real time inquiries that we talked about, as well as for very large, you know, historical sort of bulk data archives in that PARQUE format, which is also cool because there's an entire ecosystem sort of popping up around Parque in terms of the machine learning community, you know, and getting that all to work, we had to glue it together with aero flight. That's sort of what we're using as our, our RPC component. You know, it handles the orchestration and the, the transportation of the Coer data. Now we're moving to like a true Coer database model for this, this version of the engine, you know, and it removes a lot of overhead for us in terms of having to manage all that serialization, the deserialization, and, you know, to that again, like blurring that line between real time and historical data. It's, you know, it's, it's highly optimized for both streaming micro batch and then batches, but true streaming as well. >>Yeah. Again, I mean, it's funny you mentioned Rust. It is, it's been around for a long time, but it's popularity is, is you know, really starting to hit that steep part of the S-curve. And, and we're gonna dig into to more of that, but give us any, is there anything else that we should know about Bryan? Give us the last word? >>Well, I mean, I think first I'd like everybody sort of watching just to like take a look at what we're offering in terms of early access in beta programs. I mean, if, if, if you wanna participate or if you wanna work sort of in terms of early access with the, with the new engine, please reach out to the team. I'm sure you know, there's a lot of communications going out and you know, it'll be highly featured on our, our website, you know, but reach out to the team, believe it or not, like we have a lot more going on than just the new engine. And so there are also other programs, things we're, we're offering to customers in terms of the user interface, data collection and things like that. And, you know, if you're a customer of ours and you have a sales team, a commercial team that you work with, you can reach out to them and see what you can get access to because we can flip a lot of stuff on, especially in cloud through feature flags. >>But if there's something new that you wanna try out, we'd just love to hear from you. And then, you know, our goal would be that as we give you access to all of these new cool features that, you know, you would give us continuous feedback on these products and services, not only like what you need today, but then what you'll need tomorrow to, to sort of build the next versions of your business. Because you know, the whole database, the ecosystem as it expands out into to, you know, this vertically oriented stack of cloud services and enterprise databases and edge databases, you know, it's gonna be what we all make it together, not just, you know, those of us who were employed by Influx db. And then finally I would just say please, like watch in ICE in Tim's sessions, like these are two of our best and brightest, They're totally brilliant, completely pragmatic, and they are most of all customer obsessed, which is amazing. And there's no better takes, like honestly on the, the sort of technical details of this, then there's, especially when it comes to like the value that these investments will, will bring to our customers and our communities. So encourage you to, to, you know, pay more attention to them than you did to me, for sure. >>Brian Gilmore, great stuff. Really appreciate your time. Thank you. >>Yeah, thanks Dave. It was awesome. Look forward to it. >>Yeah, me too. Looking forward to see how the, the community actually applies these new innovations and goes, goes beyond just the historical into the real time really hot area. As Brian said in a moment, I'll be right back with Anna East dos Georgio to dig into the critical aspects of key open source components of the Influx DB engine, including Rust, Arrow, Parque, data fusion. Keep it right there. You don't wanna miss this >>Time series Data is everywhere. The number of sensors, systems and applications generating time series data increases every day. All these data sources producing so much data can cause analysis paralysis. Influx DB is an entire platform designed with everything you need to quickly build applications that generate value from time series data influx. DB Cloud is a serverless solution, which means you don't need to buy or manage your own servers. There's no need to worry about provisioning because you only pay for what you use. Influx DB Cloud is fully managed so you get the newest features and enhancements as they're added to the platform's code base. It also means you can spend time building solutions and delivering value to your users instead of wasting time and effort managing something else. Influx TVB Cloud offers a range of security features to protect your data, multiple layers of redundancy ensure you don't lose any data access controls ensure that only the people who should see your data can see it. >>And encryption protects your data at rest and in transit between any of our regions or cloud providers. InfluxDB uses a single API across the entire platform suite so you can build on open source, deploy to the cloud and then then easily query data in the cloud at the edge or on prem using the same scripts. And InfluxDB is schemaless automatically adjusting to changes in the shape of your data without requiring changes in your application. Logic. InfluxDB Cloud is production ready from day one. All it needs is your data and your imagination. Get started today@influxdata.com slash cloud. >>Okay, we're back. I'm Dave Valante with a Cube and you're watching evolving Influx DB into the smart data platform made possible by influx data. Anna ETOs Georgio is here, she's a developer advocate for influx data and we're gonna dig into the rationale and value contribution behind several open source technologies that Influx DB is leveraging to increase the granularity of time series analysis analysis and bring the world of data into real-time analytics and is welcome to the program. Thanks for coming on. >>Hi, thank you so much. It's a pleasure to be here. >>Oh, you're very welcome. Okay, so IX is being touted as this next gen open source core for Influx db. And my understanding is that it leverages in memory of course for speed. It's a kilo store, so it gives you a compression efficiency, it's gonna give you faster query speeds, you store files and object storage, so you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features, but what are the high level value points that people should understand? >>Sure, that's a great question. So some of the main requirements that IOx is trying to achieve and some of the most impressive ones to me, the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want, whether that's live tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metrics queries, we also wanna have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import super useful. Also broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like sql, Python, and maybe even pandas in the future. >>Okay, so lot there. Now we talked to Brian about how you're using Rust and which is not a new programming language and of course we had some drama around Rust during the pandemic with the Mozilla layoffs, but the formation of the Rust Foundation really addressed any of those concerns. You got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really, the adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with rust, but why rust as an alternative to say c plus plus for example? >>Sure, that's a great question. So Russ was chosen because of his exceptional performance and reliability. So while Russ is synt tactically similar to c plus plus and it has similar performance, it also compiles to a native code like c plus plus. But unlike c plus plus, it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers. And dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like c plus plus. So Russ like helps meet that requirement of having no limits on ality, for example, because it's, we're also using the Russ implementation of Apache Arrow and this control over memory and also Russ Russ's packaging system called crates IO offers everything that you need out of the box to have features like AY and a weight to fix race conditions, to protection against buffering overflows and to ensure thread safe async cashing structures as well. So essentially it's just like has all the control, all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high ity use cases. >>Yeah, and the more I learn about the, the new engine and, and the platform IOCs et cetera, you know, you, you see things like, you know, the old days not even to even today you do a lot of garbage collection in these, in these systems and there's an inverse, you know, impact relative to performance. So it looks like you really, you know, the community is modernizing the platform, but I wanna talk about Apache Arrow for a moment. It it's designed to address the constraints that are associated with analyzing large data sets. We, we know that, but please explain why, what, what is Arrow and and what does it bring to Influx db? >>Sure, yeah. So Arrow is a, a framework for defining in memory calmer data. And so much of the efficiency and performance of IOx comes from taking advantage of calmer data structures. And I will, if you don't mind, take a moment to kind of of illustrate why column or data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our stove. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value, maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the stove. Well usually our room temperature is regulated so those values don't change very often. >>So when you have calm oriented st calm oriented storage, essentially you take each row, each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same, then you'll, you might be able to imagine how equal values will then enable each other and when they neighbor each other in the storage format, this provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you wanna define like the men and max value of the temperature in the room across a thousand different points, you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of calmer oriented storage. >>So if you had a row oriented storage, you'd first have to look at every field like the temperature in, in the room and the temperature of the stove. You'd have to go across every tag value that maybe describes where the room is located or what model the stove is. And every timestamp you'd then have to pluck out that one temperature value that you want at that one time stamp and do that for every single row. So you're scanning across a ton more data and that's why Rowe Oriented doesn't provide the same efficiency as calmer and Apache Arrow is in memory calmer data, commoner data fit framework. So that's where a lot of the advantages come >>From. Okay. So you basically described like a traditional database, a row approach, but I've seen like a lot of traditional database say, okay, now we've got, we can handle colo format versus what you're talking about is really, you know, kind of native i, is it not as effective? Is the, is the foreman not as effective because it's largely a, a bolt on? Can you, can you like elucidate on that front? >>Yeah, it's, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why, why RO row oriented storage isn't as efficient as calm, calmer oriented storage. Yeah. >>Got it. So let's talk about Arrow Data Fusion. What is data fusion? I know it's written in Rust, but what does it bring to the table here? >>Sure. So it's an extensible query execution framework and it uses Arrow as it's in memory format. So the way that it helps in influx DB IOCs is that okay, it's great if you can write unlimited amount of cardinality into influx Cbis, but if you don't have a query engine that can successfully query that data, then I don't know how much value it is for you. So Data fusion helps enable the, the query process and transformation of that data. It also has a PANDAS API so that you could take advantage of PANDAS data frames as well and all of the machine learning tools associated with Pandas. >>Okay. You're also leveraging Par K in the platform cause we heard a lot about Par K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Parque and why is it important? >>Sure. So parque is the column oriented durable file format. So it's important because it'll enable bulk import, bulk export, it has compatibility with Python and Pandas, so it supports a broader ecosystem. Par K files also take very little disc disc space and they're faster to scan because again, they're column oriented in particular, I think PAR K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the, the benefits of par k. >>Got it. Very popular. So and he's, what exactly is influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >>Sure. So Influx DB first has contributed a lot of different, different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing with flux. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up, then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >>Yeah. Got it. You got that virtuous cycle going, the people call the flywheel. Give us your last thoughts and kind of summarize, you know, where what, what the big takeaways are from your perspective. >>So I think the big takeaway is that influx data is doing a lot of really exciting things with Influx DB IOx and I really encourage, if you are interested in learning more about the technologies that Influx is leveraging to produce IOCs, the challenges associated with it and all of the hard work questions and you just wanna learn more, then I would encourage you to go to the monthly Tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel look for the influx DDB unders IAC channel specifically to learn more about how to join those office hours and those monthly tech tech talks as well as ask any questions they have about iacs, what to expect and what you'd like to learn more about. I as a developer advocate, I wanna answer your questions. So if there's a particular technology or stack that you wanna dive deeper into and want more explanation about how INFLUX DB leverages it to build IOCs, I will be really excited to produce content on that topic for you. >>Yeah, that's awesome. You guys have a really rich community, collaborate with your peers, solve problems, and, and you guys super responsive, so really appreciate that. All right, thank you so much Anise for explaining all this open source stuff to the audience and why it's important to the future of data. >>Thank you. I really appreciate it. >>All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yoakum, he's the director of engineering for Influx Data and we're gonna talk about how you update a SAS engine while the plane is flying at 30,000 feet. You don't wanna miss this. >>I'm really glad that we went with InfluxDB Cloud for our hosting because it has saved us a ton of time. It's helped us move faster, it's saved us money. And also InfluxDB has good support. My name's Alex Nada. I am CTO at Noble nine. Noble Nine is a platform to measure and manage service level objectives, which is a great way of measuring the reliability of your systems. You can essentially think of an slo, the product we're providing to our customers as a bunch of time series. So we need a way to store that data and the corresponding time series that are related to those. The main reason that we settled on InfluxDB as we were shopping around is that InfluxDB has a very flexible query language and as a general purpose time series database, it basically had the set of features we were looking for. >>As our platform has grown, we found InfluxDB Cloud to be a really scalable solution. We can quickly iterate on new features and functionality because Influx Cloud is entirely managed, it probably saved us at least a full additional person on our team. We also have the option of running InfluxDB Enterprise, which gives us the ability to even host off the cloud or in a private cloud if that's preferred by a customer. Influx data has been really flexible in adapting to the hosting requirements that we have. They listened to the challenges we were facing and they helped us solve it. As we've continued to grow, I'm really happy we have influx data by our side. >>Okay, we're back with Tim Yokum, who is the director of engineering at Influx Data. Tim, welcome. Good to see you. >>Good to see you. Thanks for having me. >>You're really welcome. Listen, we've been covering open source software in the cube for more than a decade, and we've kind of watched the innovation from the big data ecosystem. The cloud has been being built out on open source, mobile, social platforms, key databases, and of course influx DB and influx data has been a big consumer and contributor of open source software. So my question to you is, where have you seen the biggest bang for the buck from open source software? >>So yeah, you know, influx really, we thrive at the intersection of commercial services and open, so open source software. So OSS keeps us on the cutting edge. We benefit from OSS in delivering our own service from our core storage engine technologies to web services temping engines. Our, our team stays lean and focused because we build on proven tools. We really build on the shoulders of giants and like you've mentioned, even better, we contribute a lot back to the projects that we use as well as our own product influx db. >>You know, but I gotta ask you, Tim, because one of the challenge that that we've seen in particular, you saw this in the heyday of Hadoop, the, the innovations come so fast and furious and as a software company you gotta place bets, you gotta, you know, commit people and sometimes those bets can be risky and not pay off well, how have you managed this challenge? >>Oh, it moves fast. Yeah, that, that's a benefit though because it, the community moves so quickly that today's hot technology can be tomorrow's dinosaur. And what we, what we tend to do is, is we fail fast and fail often. We try a lot of things. You know, you look at Kubernetes for example, that ecosystem is driven by thousands of intelligent developers, engineers, builders, they're adding value every day. So we have to really keep up with that. And as the stack changes, we, we try different technologies, we try different methods, and at the end of the day, we come up with a better platform as a result of just the constant change in the environment. It is a challenge for us, but it's, it's something that we just do every day. >>So we have a survey partner down in New York City called Enterprise Technology Research etr, and they do these quarterly surveys of about 1500 CIOs, IT practitioners, and they really have a good pulse on what's happening with spending. And the data shows that containers generally, but specifically Kubernetes is one of the areas that has kind of, it's been off the charts and seen the most significant adoption and velocity particularly, you know, along with cloud. But, but really Kubernetes is just, you know, still up until the right consistently even with, you know, the macro headwinds and all, all of the stuff that we're sick of talking about. But, so what are you doing with Kubernetes in the platform? >>Yeah, it, it's really central to our ability to run the product. When we first started out, we were just on AWS and, and the way we were running was, was a little bit like containers junior. Now we're running Kubernetes everywhere at aws, Azure, Google Cloud. It allows us to have a consistent experience across three different cloud providers and we can manage that in code so our developers can focus on delivering services, not trying to learn the intricacies of Amazon, Azure, and Google and figure out how to deliver services on those three clouds with all of their differences. >>Just to follow up on that, is it, no. So I presume it's sounds like there's a PAs layer there to allow you guys to have a consistent experience across clouds and out to the edge, you know, wherever is that, is that correct? >>Yeah, so we've basically built more or less platform engineering, This is the new hot phrase, you know, it, it's, Kubernetes has made a lot of things easy for us because we've built a platform that our developers can lean on and they only have to learn one way of deploying their application, managing their application. And so that, that just gets all of the underlying infrastructure out of the way and, and lets them focus on delivering influx cloud. >>Yeah, and I know I'm taking a little bit of a tangent, but is that, that, I'll call it a PAs layer if I can use that term. Is that, are there specific attributes to Influx db or is it kind of just generally off the shelf paths? You know, are there, is, is there any purpose built capability there that, that is, is value add or is it pretty much generic? >>So we really build, we, we look at things through, with a build versus buy through a, a build versus by lens. Some things we want to leverage cloud provider services, for instance, Postgres databases for metadata, perhaps we'll get that off of our plate, let someone else run that. We're going to deploy a platform that our engineers can, can deliver on that has consistency that is, is all generated from code that we can as a, as an SRE group, as an ops team, that we can manage with very few people really, and we can stamp out clusters across multiple regions and in no time. >>So how, so sometimes you build, sometimes you buy it. How do you make those decisions and and what does that mean for the, for the platform and for customers? >>Yeah, so what we're doing is, it's like everybody else will do, we're we're looking for trade offs that make sense. You know, we really want to protect our customers data. So we look for services that support our own software with the most uptime, reliability, and durability we can get. Some things are just going to be easier to have a cloud provider take care of on our behalf. We make that transparent for our own team. And of course for customers you don't even see that, but we don't want to try to reinvent the wheel, like I had mentioned with SQL data stores for metadata, perhaps let's build on top of what of these three large cloud providers have already perfected. And we can then focus on our platform engineering and we can have our developers then focus on the influx data, software, influx, cloud software. >>So take it to the customer level, what does it mean for them? What's the value that they're gonna get out of all these innovations that we've been been talking about today and what can they expect in the future? >>So first of all, people who use the OSS product are really gonna be at home on our cloud platform. You can run it on your desktop machine, on a single server, what have you, but then you want to scale up. We have some 270 terabytes of data across, over 4 billion series keys that people have stored. So there's a proven ability to scale now in terms of the open source, open source software and how we've developed the platform. You're getting highly available high cardinality time series platform. We manage it and, and really as, as I mentioned earlier, we can keep up with the state of the art. We keep reinventing, we keep deploying things in real time. We deploy to our platform every day repeatedly all the time. And it's that continuous deployment that allows us to continue testing things in flight, rolling things out that change new features, better ways of doing deployments, safer ways of doing deployments. >>All of that happens behind the scenes. And like we had mentioned earlier, Kubernetes, I mean that, that allows us to get that done. We couldn't do it without having that platform as a, as a base layer for us to then put our software on. So we, we iterate quickly. When you're on the, the Influx cloud platform, you really are able to, to take advantage of new features immediately. We roll things out every day and as those things go into production, you have, you have the ability to, to use them. And so in the end we want you to focus on getting actual insights from your data instead of running infrastructure, you know, let, let us do that for you. So, >>And that makes sense, but so is the, is the, are the innovations that we're talking about in the evolution of Influx db, do, do you see that as sort of a natural evolution for existing customers? I, is it, I'm sure the answer is both, but is it opening up new territory for customers? Can you add some color to that? >>Yeah, it really is it, it's a little bit of both. Any engineer will say, well, it depends. So cloud native technologies are, are really the hot thing. Iot, industrial iot especially, people want to just shove tons of data out there and be able to do queries immediately and they don't wanna manage infrastructure. What we've started to see are people that use the cloud service as their, their data store backbone and then they use edge computing with R OSS product to ingest data from say, multiple production lines and downsample that data, send the rest of that data off influx cloud where the heavy processing takes place. So really us being in all the different clouds and iterating on that and being in all sorts of different regions allows for people to really get out of the, the business of man trying to manage that big data, have us take care of that. And of course as we change the platform end users benefit from that immediately. And, >>And so obviously taking away a lot of the heavy lifting for the infrastructure, would you say the same thing about security, especially as you go out to IOT and the Edge? How should we be thinking about the value that you bring from a security perspective? >>Yeah, we take, we take security super seriously. It, it's built into our dna. We do a lot of work to ensure that our platform is secure, that the data we store is, is kept private. It's of course always a concern. You see in the news all the time, companies being compromised, you know, that's something that you can have an entire team working on, which we do to make sure that the data that you have, whether it's in transit, whether it's at rest, is always kept secure, is only viewable by you. You know, you look at things like software, bill of materials, if you're running this yourself, you have to go vet all sorts of different pieces of software. And we do that, you know, as we use new tools. That's something that, that's just part of our jobs to make sure that the platform that we're running it has, has fully vetted software and, and with open source especially, that's a lot of work. And so it's, it's definitely new territory. Supply chain attacks are, are definitely happening at a higher clip than they used to, but that is, that is really just part of a day in the, the life for folks like us that are, are building platforms. >>Yeah, and that's key. I mean especially when you start getting into the, the, you know, we talk about IOT and the operations technologies, the engineers running the, that infrastructure, you know, historically, as you know, Tim, they, they would air gap everything. That's how they kept it safe. But that's not feasible anymore. Everything's >>That >>Connected now, right? And so you've gotta have a partner that is again, take away that heavy lifting to r and d so you can focus on some of the other activities. Right. Give us the, the last word and the, the key takeaways from your perspective. >>Well, you know, from my perspective I see it as, as a a two lane approach with, with influx, with Anytime series data, you know, you've got a lot of stuff that you're gonna run on-prem, what you had mentioned, air gaping. Sure there's plenty of need for that, but at the end of the day, people that don't want to run big data centers, people that want torus their data to, to a company that's, that's got a full platform set up for them that they can build on, send that data over to the cloud, the cloud is not going away. I think more hybrid approach is, is where the future lives and that's what we're prepared for. >>Tim, really appreciate you coming to the program. Great stuff. Good to see you. >>Thanks very much. Appreciate it. >>Okay, in a moment I'll be back to wrap up. Today's session, you're watching The Cube. >>Are you looking for some help getting started with InfluxDB Telegraph or Flux Check >>Out Influx DB University >>Where you can find our entire catalog of free training that will help you make the most of your time series data >>Get >>Started for free@influxdbu.com. >>We'll see you in class. >>Okay, so we heard today from three experts on time series and data, how the Influx DB platform is evolving to support new ways of analyzing large data sets very efficiently and effectively in real time. And we learned that key open source components like Apache Arrow and the Rust Programming environment Data fusion par K are being leveraged to support realtime data analytics at scale. We also learned about the contributions in importance of open source software and how the Influx DB community is evolving the platform with minimal disruption to support new workloads, new use cases, and the future of realtime data analytics. Now remember these sessions, they're all available on demand. You can go to the cube.net to find those. Don't forget to check out silicon angle.com for all the news related to things enterprise and emerging tech. And you should also check out influx data.com. There you can learn about the company's products. You'll find developer resources like free courses. You could join the developer community and work with your peers to learn and solve problems. And there are plenty of other resources around use cases and customer stories on the website. This is Dave Valante. Thank you for watching Evolving Influx DB into the smart data platform, made possible by influx data and brought to you by the Cube, your leader in enterprise and emerging tech coverage.

(upbeat music) >> Okay, we're back. I'm Dave Vellante with The Cube and you're watching Evolving InfluxDB into the smart data platform made possible by influx data. Anais Dotis-Georgiou is here. She's a developer advocate for influx data and we're going to dig into the rationale and value contribution behind several open source technologies that InfluxDB is leveraging to increase the granularity of time series analysis and bring the world of data into realtime analytics. Anais welcome to the program. Thanks for coming on. >> Hi, thank you so much. It's a pleasure to be here. >> Oh, you're very welcome. Okay, so IOx is being touted as this next gen open source core for InfluxDB. And my understanding is that it leverages in memory, of course for speed. It's a kilometer store, so it gives you compression efficiency it's going to give you faster query speeds, it's going to see you store files and object storages so you got very cost effective approach. Are these the salient points on the platform? I know there are probably dozens of other features but what are the high level value points that people should understand? >> Sure, that's a great question. So some of the main requirements that IOx is trying to achieve and some of the most impressive ones to me the first one is that it aims to have no limits on cardinality and also allow you to write any kind of event data that you want whether that's lift tag or a field. It also wants to deliver the best in class performance on analytics queries. In addition to our already well served metric queries we also want to have operator control over memory usage. So you should be able to define how much memory is used for buffering caching and query processing. Some other really important parts is the ability to have bulk data export and import, super useful. Also, broader ecosystem compatibility where possible we aim to use and embrace emerging standards in the data analytics ecosystem and have compatibility with things like SQL, Python and maybe even Pandas in the future. >> Okay, so a lot there. Now we talked to Brian about how you're using Rust and which is not a new programming language and of course we had some drama around Rust during the pandemic with the Mozilla layoffs but the formation of the Rust Foundation really addressed any of those concerns and you got big guns like Amazon and Google and Microsoft throwing their collective weights behind it. It's really adoption is really starting to get steep on the S-curve. So lots of platforms, lots of adoption with Rust but why Rust as an alternative to say C++ for example? >> Sure, that's a great question. So Rust was chosen because of his exceptional performance and reliability. So while Rust is syntactically similar to C++ and it has similar performance it also compiles to a native code like C++ But unlike C++ it also has much better memory safety. So memory safety is protection against bugs or security vulnerabilities that lead to excessive memory usage or memory leaks. And Rust achieves this memory safety due to its like innovative type system. Additionally, it doesn't allow for dangling pointers and dangling pointers are the main classes of errors that lead to exploitable security vulnerabilities in languages like C++. So Rust like helps meet that requirement of having no limits on cardinality, for example, because it's we're also using the Rust implementation of Apache Arrow and this control over memory and also Rust's packaging system called Crates IO offers everything that you need out of the box to have features like async and await to fix race conditions to protect against buffering overflows and to ensure thread safe async caching structures as well. So essentially it's just like has all the control all the fine grain control, you need to take advantage of memory and all your resources as well as possible so that you can handle those really, really high cardinality use cases. >> Yeah, and the more I learn about the new engine and the platform IOx et cetera, you see things like the old days not even to even today you do a lot of garbage collection in these systems and there's an inverse, impact relative to performance. So it looks like you're really, the community is modernizing the platform but I want to talk about Apache Arrow for a moment. It's designed to address the constraints that are associated with analyzing large data sets. We know that, but please explain why, what is Arrow and what does it bring to InfluxDB? >> Sure. Yeah. So Arrow is a a framework for defining in memory column data. And so much of the efficiency and performance of IOx comes from taking advantage of column data structures. And I will, if you don't mind, take a moment to kind of illustrate why column data structures are so valuable. Let's pretend that we are gathering field data about the temperature in our room and also maybe the temperature of our store. And in our table we have those two temperature values as well as maybe a measurement value, timestamp value maybe some other tag values that describe what room and what house, et cetera we're getting this data from. And so you can picture this table where we have like two rows with the two temperature values for both our room and the store. Well, usually our room temperature is regulated so those values don't change very often. So when you have calm oriented storage essentially you take each row each column and group it together. And so if that's the case and you're just taking temperature values from the room and a lot of those temperature values are the same then you'll, you might be able to imagine how equal values will then enable each other and when they neighbor each other in the storage format this provides a really perfect opportunity for cheap compression. And then this cheap compression enables high cardinality use cases. It also enables for faster scan rates. So if you want to define like the min and max value of the temperature in the room across a thousand different points you only have to get those a thousand different points in order to answer that question and you have those immediately available to you. But let's contrast this with a row oriented storage solution instead so that we can understand better the benefits of column oriented storage. So if you had a row oriented storage, you'd first have to look at every field like the temperature in the room and the temperature of the store. You'd have to go across every tag value that maybe describes where the room is located or what model the store is. And every timestamp you then have to pluck out that one temperature value that you want at that one time stamp and do that for every single row. So you're scanning across a ton more data and that's why row oriented doesn't provide the same efficiency as column and Apache Arrow is in memory column data column data fit framework. So that's where a lot of the advantages come from. >> Okay. So you've basically described like a traditional database a row approach, but I've seen like a lot of traditional databases say, okay, now we've got we can handle Column format versus what you're talking about is really kind of native is it not as effective as the former not as effective because it's largely a bolt on? Can you like elucidate on that front? >> Yeah, it's not as effective because you have more expensive compression and because you can't scan across the values as quickly. And so those are, that's pretty much the main reasons why row oriented storage isn't as efficient as column oriented storage. >> Yeah. Got it. So let's talk about Arrow data fusion. What is data fusion? I know it's written in Rust but what does it bring to to the table here? >> Sure. So it's an extensible query execution framework and it uses Arrow as its in memory format. So the way that it helps InfluxDB IOx is that okay it's great if you can write unlimited amount of cardinality into InfluxDB, but if you don't have a query engine that can successfully query that data then I don't know how much value it is for you. So data fusion helps enable the query process and transformation of that data. It also has a Pandas API so that you could take advantage of Pandas data frames as well and all of the machine learning tools associated with Pandas. >> Okay. You're also leveraging Par-K in the platform course. We heard a lot about Par-K in the middle of the last decade cuz as a storage format to improve on Hadoop column stores. What are you doing with Par-K and why is it important? >> Sure. So Par-K is the column oriented durable file format. So it's important because it'll enable bulk import and bulk export. It has compatibility with Python and Pandas so it supports a broader ecosystem. Par-K files also take very little disc space and they're faster to scan because again they're column oriented, in particular I think Par-K files are like 16 times cheaper than CSV files, just as kind of a point of reference. And so that's essentially a lot of the benefits of Par-K. >> Got it. Very popular. So and these, what exactly is Influx data focusing on as a committer to these projects? What is your focus? What's the value that you're bringing to the community? >> Sure. So InfluxDB first has contributed a lot of different things to the Apache ecosystem. For example, they contribute an implementation of Apache Arrow and go and that will support clearing Influx. Also, there has been a quite a few contributions to data fusion for things like memory optimization and supportive additional SQL features like support for timestamp, arithmetic and support for exist clauses and support for memory control. So yeah, Influx has contributed a lot to the Apache ecosystem and continues to do so. And I think kind of the idea here is that if you can improve these upstream projects and then the long term strategy here is that the more you contribute and build those up then the more you will perpetuate that cycle of improvement and the more we will invest in our own project as well. So it's just that kind of symbiotic relationship and appreciation of the open source community. >> Yeah. Got it. You got that virtuous cycle going people call it the flywheel. Give us your last thoughts and kind of summarize, what the big takeaways are from your perspective. >> So I think the big takeaway is that, Influx data is doing a lot of really exciting things with InfluxDB IOx and I really encourage if you are interested in learning more about the technologies that Influx is leveraging to produce IOx the challenges associated with it and all of the hard work questions and I just want to learn more then I would encourage you to go to the monthly Tech talks and community office hours and they are on every second Wednesday of the month at 8:30 AM Pacific time. There's also a community forums and a community Slack channel. Look for the InfluxDB underscore IOx channel specifically to learn more about how to join those office hours and those monthly tech talks as well as ask any questions they have about IOx what to expect and what you'd like to learn more about. I as a developer advocate, I want to answer your questions. So if there's a particular technology or stack that you want to dive deeper into and want more explanation about how InfluxDB leverages it to build IOx, I will be really excited to produce content on that topic for you. >> Yeah, that's awesome. You guys have a really rich community collaborate with your peers, solve problems and you guys super responsive, so really appreciate that. All right, thank you so much Anais for explaining all this open source stuff to the audience and why it's important to the future of data. >> Thank you. I really appreciate it. >> All right, you're very welcome. Okay, stay right there and in a moment I'll be back with Tim Yoakam. He's the director of engineering for Influx Data and we're going to talk about how you update a SaaS engine while the plane is flying at 30,000 feet. You don't want to miss this. (upbeat music)

>>The cube presents HPE discover 2022 brought to you by HPE. >>Welcome back to the Venetian convention center. You're watching the Cube's coverage of HPE discover 2022. The first discover live discover in three years, 2019 was the last one. The cube we were just talking about. This has been at H HP discover. Now HPE since 2011, my co-host John furrier. We're pleased to welcome Phil Maru. Who's the executive vice president and general manager of HPE Aruba. And he's joined by David Hughes, the chief product and technology officer at HPE Aruba gentleman. Welcome to the cube. Good to see you. Thank you. Thank >>You. >>Okay, so you guys talk a lot, Phil, about the intelligent edge. Yep. Okay. What do you, what do you mean by that? >>Yeah, so we, well, we're kind of focused on, is providing technology to customers that sits out at the edge and typically the edge would be, uh, any location out of the data center or out of the cloud. So for the most part, our customers would deploy our technology either in their office premises or maybe retail premises shops, uh, maybe deploying out of the home where their employees are on a factory floor. And we're really talking about technology to connect both people and devices back to, um, systems and technology throughout an organization. So, but >>I, I, you know, sometimes I call it the near edge and the far edge yeah. Near, near edge. Maybe as we saw home Depot up on the stage yesterday far, Edge's like space. Right. You're including all of that. Right. That's >>Edge. >>Yeah. And actually we, we, we, you know, we've got a broad range of technology that actually works within the data center as well. So, you know, what we are focused on is providing, uh, network technology, software and services. And, you know, for the most part, our heritage is at the edge, but it's more pervasive than that. So >>If you have the edge, you got connectivity and power, that's an edge. How much, um, is the physical world being connected now you're seeing robotics automation. Yeah. Ex and with machine learning specifically in compute, really driving a new acceleration at the edge. What you, how do you guys view that? What's your reaction? Yeah. >>I think, look, it, I think as connectivity is improving and that's both in terms of wifi connectivity, so, you know, wifi technology continues to, uh, advance and also you've got this new kind of private 5g area, just generally connectivity is becoming more pervasive and that's helping some industries that haven't previously embraced it. And I think industrial is, is one of the big ones. So, you know, historically it was difficult for kind of car manufacturers to really enable a factory floor. But now the connectivity is connectivity is better. That gives them the opportunity to be able to really change how they do things. So >>David, if you do take an outside in view, mm-hmm <affirmative>, uh, and, and, and when you talk to customers, what are they telling you and how is that informing your product strategy? >>Yeah, well, you >>Know, I think there's, there's several themes we hear. One is, you know, it's really important, better work from anywhere they wanna enable their employees, um, to get the same experience, whether they're at home or on the road or in their branch office or at headquarters. Um, you know, people are also concerned that as they deploy, deploy all of this IOT and pursuit of digital transformation, they don't want those devices to be a weak point where someone breaks into one device and moves naturally, um, across the network. So they want to have this great experience for their customers and their users, but they wanna make sure that they're not compromising security, um, in any way. And so it's about getting that balance between ease of use and, and security. That's one of the primary things we hear, >>You know, Dave, one of the things we talked about many, many years ago was when hybrid and was starting to come out multi-cloud was on the, on the table early on. Uh, we were, we were saying, Hey, the data center is just a big edge, right? I mean, if you have cloud operations and you see what's going on with GreenLake here now, the momentum hybrid cloud is cloud operations, right? An edge off data centers to a big edge on premises. And you got the edge as you have cloud operations, like say GreenLake, plugging in partners and diverse environments. You're connecting, not just branch offices that are per perimeter based. You have no perimeter and you have now other companies connecting mm-hmm <affirmative> so you got data and you got network. How do you guys see that transition as GreenLake has a very big ecosystem part of it, partners and whatnot. >>Yeah. So, you know, I think for us, um, the ecosystem of partners that we have is critical in terms of delivering what our customers need. And, you know, I think one of the really important areas is around verticals. So, um, you know, when you think about different verticals, they have similar problems, but you need to tailor the solutions. Um, to each of those, you know, we are talking a bit about devices and people. When you look at say a healthcare environment, there can be 30 devices there for each patient. And, um, so there's connecting all those devices securely, but we have partners that will help pull all of that together that may be focused on, um, you know, medical environment that may focused on stadiums. They may be focused on industrial. Um, so having partners that understand those verticals and working closely with them to deliver solutions is important in our go to market. >>So another kind of product question and related to what you just said, David, I got connectivity, speed, reliability, cost security, or maybe a missing something. But you, you said earlier, you gonna gotta balance those. How do you do that? And do you do that for the specific use cases? Like for instance, you just mentioned stadiums and 81 and how do you balance those and, and do you tailor those for the use cases? >>Yeah, well, I think it depends on the customer and different people have different views about where they need to be. So some people are, are so afraid about security. They wanna be air gapped and completely separate than the internet. That would be one extreme mm-hmm <affirmative> other people, you know, look at it and see what's happening with COVID with everyone working from home with people being able to work from Starbucks or the airport. And they're beginning to think, well, why is the branch that much different? And so what I think we are seeing is, you know, a reevaluation of how people connect to, um, the apps they're using and, uh, you know, you, you, you've probably for sure heard people talking about zero trust, talking about micro segmentation. You know, I think what we we see is that people wanna be able to build a network in a way where rather than any device being able to talk to any device or any person, which is where the internet started, we wanna build to build networks where people or devices can only talk to the destinations that are necessary for them to do their job. >>And so a lot of the technology that we are building into the network is really about making security intrinsic by limiting what can talk to what that's >>Actually micro, micro segmentations, zero trust, um, these all point to a modern, the modern network, as you say, Antonio Neri was just on the cube, talking about programmability, substrate, the words like that come to mind, what is the modern network look like? I mean, you have to be agile. You have to be programmable. You have to have security. Can you describe in your words, what does the modern network these days need to look like? How should customers think about architecting them? What are some of the table stakes and what are some of the differentiators that customers need to do to have a modern network? >>Yeah, well, you covered off a coup a few quarter, one there with clarity and so on. So let me pick one that you didn't mention. And, and I, you know, I think we are seeing, you know, a lot of interest around network as a service. And, you know, when we think about network as a service, we think about it broadly, um, you know, for consumers, we're getting more and more used to buying things as a service versus buying a thing. When you, when you get Alexa, you care about how well she answers your questions, you don't care about what CPU is or how much Ram Alexa has. And likewise with networking, people are caring about the outcomes of keeping their employees connected, keeping their, their devices and systems running. And so what for us, what NASA is all about is that shift of thinking about a network as being a collection of devices that get managed to being a framework for connectivity and running it from the point of view of those outcomes. >>And so whether, you know, it's about CapEx versus OPEX or about do it yourself, managing the network yourself versus outsourcing that, um, or it's about the, you know, Greenfield versus brownfield, each of our customers has got a different starting point, but they're all getting heading towards this destination of being able to treat their network as a service. And so that is, you know, a key area of innovation for us and whether it's big customers like home Depot that you heard about yesterday, um, where we kind of manage everything for them on a, as on a store basis, um, for connectivity, um, or, you know, the recent, um, skew based nest that we launched, which is a really scalable foundation for our partners to build nest offerings around. Um, we see this as a key part of network modernization. Yeah. >>And one of the things, again, that's great stuff. Uh, infrastructure is code, which was really kind of pioneer the DevOps movement in cloud kind of as platform level. And you got data ops now and AI at the top of the stack, we were always wondering when network as code was gonna come, uh, and where you actually have it, where it's programmable. I mean, we all know what policies do do. They're good. That's all great network as code. >>Yeah. >>And that's the concept that's like DevOps, it's like, make it work just seamlessly, just be always on. And >>Yeah. And smart, you know, people are always looking for the, for the easy button. Um, and so they want, they want things to operate easily. They want it to be easy to manage. And, you know, I actually think there's a little bit of a, um, a conflict between networkers code and the easy button, right? So it depends on the class of customers. Some customers like financials, for instance, have a huge software development organizations that are extremely capable that could, that can go with program ability that want things as code. But the majority of the, of, of the verticals that we deal with, um, don't have those big captive software organizations. And so they're really looking for automation and simplicity and they wanna outsource that problem. So in Aruba central, we have invested a lot to make it really easy for our customers to, um, get what they need, you know, is that movement of zero code. It's more like zero code. They want, they want something packaged now >>The headless networks. Yeah. Low code, no code >>Kind of thing. Yeah, that's right. And, you know, obviously for people that have the sophistication that want to, um, do the most advanced things, we have APIs. And so we support that kind of programmable way of doing things. But I'd say that that's that's, those are more specialized customers. So >>Phil, yeah. Uh, is that the strategy? I mean, David listed off a number of, of factors here is that Aruba's strategy to modernize networks to actually create the easy button through network as a service is as simple as dial tone. Is that how we >>Should think? I mean, the way I think about the strategy is I think about it as a triangle, really, along the bottom, we've got the products and services that we offer and we continue to add more products and services. We either buy companies such as silver peak a couple of years ago, or we build, uh, additional products and by, and by the way, that's in response to customers who are frustrated with some other suppliers and wanna move on mass over to, uh, companies like ourselves. So at the bottom layer of the product and services, and then the other side of the triangle one would be NAS, which we talked about, which is kind of move to buying network and as a service. And then the other side of the triangle is the platform, which for us is river central, which is part of HP GreenLake. And that's really all about, you know, kind of making it easy for customers to manage networks and Aruba central right now has got about 120,000 live customers on it. It connects to about 2 million devices and it's collecting a lot of data as well. So we anonymously collect data from all of our customers. We've got one and a half billion data points in the platform. And what we do is we let that data kind of look for anomalies and spot problems on the network before they happen for customers. >>So Aruba central predated, uh, uh, GreenLake GreenLake. Yeah. And, and so did you write to GreenLake through GreenLake APIs? How, what was the engineering work to accomplish that? >>Yeah, so really, um, Aruba central is kind of the Genesis of the GreenLake platform. So we took Aruba central and made it more generic okay. To build the GreenLake cloud platform. And you know, what we've done very recently is bring, bring Aruba into that unified infrastructure, along with storage and compute. So the same sign-on applies across all of HP's, um, products, the same way of managing licenses, managing devices. And so it provides us, uh, great foundation going forwards to, um, solve more comprehensively. Our customers automation requires. >>So, so just a quick follow. So Aruba actually was the main spring of GreenLake from the standpoint of okay. Sing, like you said, single sign on a platform that could evolve and become more, more generic. Yes. So, okay. So that was a nice little, um, bonus of the acquisition, you know, it's now the whole company >><laugh> Aruba taking over. >>Yeah. There's been a lot of work to, to, uh, you know, make it generic and, and widely applicable. Right. Yeah. Um, so, but >>You were purpose >>Built for yeah. Well it's foundational. Yes. So foundational for GreenLake, they built on top of it. Yeah. So you mentioned the data points, billions of data points. So I gotta ask you, cuz we're seeing this, um, copy more and more with machine learning, driving a lot of acceleration, cuz you can do simulations with machine learning and compute. We had Neil McDonal done earlier. He's a compute guy, you got networking. So with all this, um, these services and devices being put on and off the network humans, can't actually figure this out. You can discover what's on the network. How are you guys viewing the discovery and monitoring because there's no perimeter okay. On the network anymore. So I want to know what's out there. Um, how do you get through it? How does machine learning and AI play into this? >>Yeah. I mean, what we are trying to do is obviously flag trends for customers and say, Hey look, you know, we can either see something happening with your network. So there's a particular issue over here and we need to, I dunno, free up more capacity to solve that. Or we're looking at how their network is running and then comparing that with anonymized data from all of our other customers as well. So we're just helping find those problems. But yeah, you're right. I mean, I think it is becoming more of an issue for organizations, you know, how do you manage the network, >>But you see machine learning and AI playing a big part. >>Yeah, yeah. Yeah. I think, uh, AI massively and, and other technology advances as well that we make. So recently we, uh, also announced the availability of location awareness within our access points. And that might sound like a simple thing. But when network, when companies build out their networks, they often lose or they potentially could lose the records as to, well, where were the access points that we laid out and actually where are they not within, you know, 20 feet, but where actually are they? So we introduced kind of location, finding technology as well into our, uh, access points to make it easy for >>Customers. So Aruba one of the best, if not the best acquisition. I think that HP E has made, um, it's made by three par was, you know, good. It saved the storage business. Okay. That was more of a defensive play. Uh, but to see Aruba, it's a growth business. You guys report on it every quarter. Yeah. It's obviously a key ingredient to enable uh, uh, GreenLake and, and a that's another example, nimble was similar. We're much smaller sort of more narrow, but taking the AI ops piece and bringing it over. So it's, it was great to see HPE executing on some of its M and a as opposed to just leaving them alone and not really leveraging 'em. So guys, yeah. Congratulations really appreciate you guys coming on and explaining that. Congratulations on all the, all the great work and thanks for coming on the cube. Okay. >>Thank you guys. Yeah. Thanks for having us. >>All right, John, and I'll be back right after this short break. You're watching the cube, the leader in enterprise tech coverage from HPE Las Vegas, 2022. We'll be right back.

>>The cube presents HPE discover 2022 brought to you by HPE. >>Hey everyone. Welcome to Las Vegas. It's the cube live on the show floor at HPE discover 2022, the first in person discover in three years, there are about 8,000 people here. The keynote was standing room only Lisa Martin here. I got a powerhouse group joining me for this keynote analysis. Dave ante joins us, Keith Townsend, John farrier, guys. Lot of news. It's all about HPE GreenLake. What were some of the things Dave, that stuck out to you? >>Well, I'll tell you right now, I gotta just quote, Antonio OIR said, Neri said four years ago, I declared that the enterprise of the future would be edge centric, cloud enabled and data driven. As a result, we launched HPE GreenLake. It kind of declared victory. Now I would say that what they're talking about and what they announced, I would consider table stakes. You know, I wish it started in 2014. I wish Antonio took over in 2015 instead of 2018, but I have to give credit, he's brought a focus and uh, and a, he think he's amped it up, John. I mean, if he's really prioritizing, uh, the, as a service they're going on in all in they're burning the boats, uh, and it's good. They got a lot of work to do. They >>Got a lot of work to do three years ago, John Antonio stood on this very stage saying we, and by 2022, we're gonna be delivering our entire portfolio as a service here we are with GreenLake. What I wanna get your thoughts on Keith's as well. >>Yeah. Well, first of all, I think that the crowded house was, uh, and a sign of people wanna come back together. So it's, to me, that was the first good news I saw, which was the HP community, their customer base. They're all here. They're glad to be back and forth. So it shows that they, their customer base it's resonating their value proposition of annual recurring revenue as a service plus the contract values with GreenLake are up. So this resonance with the customers, Dave, on the new operating model, that's a great check the box there. Um, I would say that I don't think HP's, as far along as Antonio had hopes, he'd be the pandemic was a setback. Um, but GreenLake is a real shining star. It's, uh, it's producing some green if you will money for them in terms of contracts, but they still got a lot more work to do because they're in a really interesting zone, Dave, because edge the cloud, although relevant and accurate where the, the shift is going, are they really there with, with the goods? And to me, I'm looking forward to seeing this discover if they have it or not. Certainly the messaging's good, but we're gonna UN UN unpeel that onion back and look at it. But >>Keith they're on the curve, right? At least they're on the cloud curve. >>They're absolutely on the curve. They have APIs, they have consistent developer experience. They announced the developer portal. They're developer centric. You can now consume your three par storage array services via a Terraform, uh, provider. They speak the language of cloud practitioners. You might struggle a little bit if I'm a small startup, you know, why would I look towards HPE? They kind of answered that a little bit. They had evil genius as a customer on stage, not a huge organization. A lot of the pushback they've been given is that if I may startup, I can simply go to a AWS portal, launch, a free trial service and run it. HPE kind of buried the lead. They now have, at least they announced preannounced the capability to, to trial GreenLake. So they're moving in the right direction. But you know, it's, it's it's table states. Well, >>Here's the thing. Here's the dynamic day that's going on. This is something that we've got got we're first of we've been covering HPE HP for now 11 years with the cube and look at Amazon's success and look at where Amazon's struggling. If you can say that they're having crossed overs to the enterprise, uh, cuz the enterprises are now just getting up to speed. You're seeing the rise of lack of talent. It certainly changing, uh, cyber security. You can't find talent. Kubernetes, good luck with that. Try to find someone. So you're seeing the enterprise aren't really geared up or staffed up for doing what I call, you know, high end cloud. So the rise of managed services is, is what we're seeing out there right now. You want Kubernetes clusters is a great set of managed services. You want other services? So that's the tell sign that the enterprises H HP's customers are now walking before they can run. They're crawling, they're now they're walking. So it's they have time to get in the Amazon lane in my opinion. Well, you >>Think about the hallmarks of cloud, obviously there's as a service, there's consumption based pricing. There's a developer, you know, friendliness, uh, there's ecosystem, which is really, really important. I think today, a lot of the ecosystem is partners, resellers and managed service providers. And to your point, Keith table stakes are things like single sign on being able to have, you know, a console being able to do it from a, from a URL to your point about startups is really interesting because that's one of the other hallmarks of cloud is you attract startups. And Lisa, we were at the snowflake summit and I asked the same question, can snowflake attract startups with their own super cloud. And what you saw was ecosystem partners developing in the snowflake cloud and monetizing. And that's something that we're waiting to see here. And I, I think they know >>You're suggesting way you suggesting that HP's gonna attract startups. >>Well, >>I, I think that's a sign if they can do that. That's a sign. And, and right now, I mean, you heard the example that Keith Keith gave. Uh, but, but not, not many. >>Yeah. I'm hoping that H I don't think HP is gonna ever attract startups, but I think the opportunity GreenLake affords the ecosystem is build clouds or purpose driven clouds around GreenLake. Mm-hmm <affirmative> whether it's the agreement with Equinix or all the cos and semi clouds, I think GreenLake gets most small CSPs, a leg up or 80% of the way there, where they can add that 20% of the IP and build services around GreenLake. And then that can attract the, the startup >>Or entrepreneurs. So the, the big question is, okay, where are these developers gonna come from? They could come from incumbents inside of companies. You know, the, the, the DevOps crowd from the enterprise, the really ops dev crowd. Right? I mean, yeah, don't you see that as a sort of a form of innovation startup, even though it's not a true startup. >>Yeah. Even though it's not, >>So Todd's making faces over there, we <laugh> >>Look, it, look it, they have >>Listen, if they don't, if they can't >>Do that, no, this is their focus is not startups. I agree with Keith on this one, they have to take care of business, home Depot. They have big customers and they have a lot of SMBs as well. They've got a great channel. H HP's got amazing infrastructure and, and client action going on. They gotta get the operating model, right job one as a service ARR, and then contract value and, and nail that with GreenLake. >>Who's their ideal customer profile. >>Their ideal is their install base. Look what Microsoft did with 365, they were going down. Their stock price was 26. At one point go to the, they went to the cloud 365, moved everything to the cloud and look at the success they're having. HP has the same kind of installed base. They gotta bring them along. They gotta get the operating model, right. And the developers that they're targeting are the ones inside the company and, or manage services that they're gonna go to the ecosystem for. That's where the cloud native comes in. That's where thing kind of comes together. So to me, I'm bullish on the operating model, but I'm skeptical that HP can get that cloud native developer. I haven't seen it yet. I'm looking for it. We're gonna look for it here. >>A key to that is going to be consistently. I, the, one of the things I'm looking for on the tech side, I, I hate to compare what HPE is doing to what VMware did with vCloud error years ago, but vCloud error on the outside looked >>Wonderful. Yes, >>It did. Once you tried to use it, it was just flaky underneath. And that's the part I'm looking to see customers pounding on it and saying, you know what API call after API I call, can I, uh, provision 10,000 pods a day? Does it scale down? Does it scale? And is it consistent? Is it >>Fragile Al roo she's co seasoned veteran? Uh, she was at V VMware cloud. She saw that movie. She gets a Mulligan, Dave. So I think her leadership is impressive. And I think she could bring a lot to the table to your point about don't make that same mistake and they gotta get this architecture, right. If they get the operating model right with GreenLake, they can double down on that and enable the developers that are driving the digital transformation. That to me is the, the key positions that they have to nail. And they do that. The rest is just fringe work. In my opinion, >>The reason why Alma was brought in, sorry, Lisa, it was, and then you gotta chime in here was to really build out that platform so that internal people at HPE can actually build value on top of it and the ecosystem that's her priority. >>We're gonna hear a lot from the ecosystem in the next couple of days, but I wanna get your perspective on, you've been following HPE a long time, all three of you. What are some of the things that you're hearing right now that are differentiators? We were just at Dell technologies. We talking about apex. We saw the big announcement they had with snowflake. We were at snowflake two weeks ago. I wanna get all three of your opinions on what are you seeing? Where is HP leading? >>I mean, HPE and Dell will, both with Dell, with apex are go, they're both gonna differentiate with their strengths. And, you know, for Dell, that's their breadth and their, their portfolio. And for, for HPE, that's their sort of open posture. I mean, John, you, you know this well, uh, that's their, their ecosystem, which I know has to evolve. And to me, their focus, you know, Antonio laid out some of the key differentiators. I, I, I think some of them were kind of, you know, pushing the envelope a little bit. Uh, but, but I think they're focus on as a service burning the, the, the boats telling wall street, this is our business. I think that's their differentiator. Is that they're, they're all in. >>Yeah. I, I think they, they try to highlight it by re announcing their private cloud service. I don't even know why they needed to announce that they have a private cloud. GreenLake is a cloud it's is a private cloud >>With block storage, hit disaster recovery. It's like good >>With like everything you get. But I think the, the key is, is that all of that is available today and you can get it in all kinds of frame of, of formats and, and frames specifically, if I'm a customer and I wanna get outta the data center and you, you know, Dave, we go back and forth about this all the time, and I wanna repatriate some workloads to Kubernetes on prem. I don't need to spend up another data center. I can go to Equinix, get GreenLake min IO, object storage on the back end, HPE lighthouse, all those services that I need for Kubernetes and repatriate my workloads without buying a new data center. And I get it as a service. I can get that Dave from HPE GreenLake, Dell apex is on the way. The >>Other thing they're differentiating with Aruba, that's something that Dell doesn't have. Yeah. And, and that is their edge play, I think is stronger than >>Of the others. Mean the, to me, the differentiator for HP is their, their history. Their channel's amazing. They got great Salesforce and they have serious customers and they have serious customers that have serious problems, uh, cyber security, uh, infrastructure, the security paradigm's changed. Uh, the deployment is changed how they deploy applications in their customer base. So they gotta step up to that challenge. And I think their differentiator is gonna be their size, their field and their ability to bring that operating model. And the hybrid model is a steady state. That's clear multi-cloud is just hybrids stitched together, but hybrid cloud, which is basically on premises and cloud to edge operating model is the number one thing that they need to nail. And if they nail that right, they will have a poll position that they could accelerate on. And again, I'm really gonna be watching how well they could enable cloud native developers, okay. To build modern agile applications while solving those serious problems with those serious customers. So again, I think hybrids spun in their direction. I'm not gonna say they got lucky, cuz they've always been on the hybrid bandwagon since we've been covering them. But I thought they'd be for a long day, but they're lucky to have hybrid. That's good for them. And I think do what Microsoft did convert their customers over and they do that, right? >>I think the key to that is gonna be ecosystem. Again, the developers need to see, especially the data piece, they talk about the cloud operating model. I think they're really moving that direction. The data piece to me is the weakest. Like they'll, they'll make claims that we can do anything that the cloud can do. You can't run snowflake, can't run data bricks, can't run Mongo Atlas. So they gotta figure out that data layer and that's optionality of, of data stores. And they don't have that today. >>Yeah. They, they, they have an announcement coming and I can't pre-announce it, but they're, they've, I've deemed them against it. They have the vision, Emeral data services, their data fabric multi-protocol access is a great start. They need the data network behind it. They need the ability to build a super cloud, a across multiple cloud providers, bringing some Google infos love inside of, uh, right next to your data. They have the hardware, they have the infrastructure, but they don't have the services. >>That's a key thing. I think one, you just brought up great point, Keith, and that is, is that at the end of the day, Dave, we're in a market now where agility and speed can be accomplished by startups or any company and HP's customers. Okay. Can move fast too. Okay. And so whoever can extend that value. If HPE can enable value creation for their customers, that's gonna be truly their, their task at hand, they got the channel, they got some leverage, but at the end of the day, the customers have alternatives now and they can move faster to get the value that they need to solve their serious problems. Uh, like cyber, like scalable infrastructure, like infrastructures code, like data ops, like AI ops, it's all here. And it's all coming really fast. Can GreenLake carry the day. And >>By the way, everything we just said about GreenLake in terms of table stakes and everything else, it applies for Dell. >>Yeah, absolutely. >>No question. It does guys. We have, and jam packed three days. We're gonna be talking with the ecosystem. We're gonna be talking with HPE leaders with customers. You're gonna hear all of these, uh, all this information unpacked over the next three days. We will be right back with our first guest for Dave ante, Keith Townson and John furrier. I'm Lisa Martin. Our first guest joins us momentarily.

>>from around the globe. It's the Cube covering HP Discover Virtual Experience Brought to You by HP >>I Welcome to the Cube's coverage of HP Discover. 2020. The virtual experience I'm Stew Minimum course This year we're getting to talk to HP, their customers and their partners where they are around the globe. We said many times these were, you know, together, even while we're art happy to dig into a really important partnership with HP and VM Ware. Welcome to the program. First time guest on the program Christmas Satterthwaite. She is the vice president of product management for Compute with Packard Enterprise and welcome back to the program Lee Caswell. He is the vice president, product marketing for hyper converged infrastructure, her at VM Ware talking about V sphere and how that gets bundled into everything else. Chris Stanley, thanks so much for joining us. >>Thanks for having us. >>Alright, So, Chris, let's start with you. So you know, like a little bit about your background? The HP and HP relationship with VM Ware, you know, goes back to you know, the earliest days, but, you know, give us a little bit about you know where in the portfolio you focus on and and how VM Ware fit, then >>Oh, sure, sure. So I've been with H P E for 23 years now, and I'm leading the business for Alliance and Synergy and talking a little bit about the relationship with VM Ware. So we've been partnering for 19 years and we have over 200,000 joint customers together. And I'm actually often asked about the partnership and how we partner and we really partner across all fronts. So it's from the innovation for the co engineering, the working with specific customers on what solutions are good for them to servicing our customers. So we're really working across the board, and a lot of customers we work with closely are really impressed with how closely we're working together, because that's what they look for. >>Yeah, and we it's it's It's an interesting relationship to watch. Obviously, you know, long history Chris talked about on the it side, but the VM partnership is more than just the compute. Maybe gives a little bit of a view inside. You know, the joint engineering go to market efforts that you do. >>Yeah. I mean, customers always sit up straight when we talk together, because both hard companies or just raw engines of innovation and they look forward to not just the capabilities or bringing, but also the seamless way that we integrate that and make that seamless and easy for customers to digest. So certainly on the server front through V sphere, that's been a longstanding, uh, participation the VM Ware Cloud Foundation. Then this fully software defined stack became a really interesting way for us to go in partner and show joint value to customers who are trying to basically get more speed the speed. We're gonna talk about a lot that today and then finally, the confirmation that we've opened up into storage systems, right? So there's certainly a hyper converged element of it. But now what we do with Nimble three Par and now I'm Era is a really interesting way for us to take the vehicle technology that we have and extend the common operating model. So really just interesting innovation for customers that take advantage of as they look to innovate themselves. >>Krista, from from a research standpoint, you know, we were really early in watching, you know, new models of building out storage. And we said, You know, the pendulum has swung back to pull it much closer to the compute you talked about. You've got a broad portfolio and compute. You know, synergy has some really interesting, you know, ways to be able to compose things and leverage software capabilities. So maybe give >>us a >>little bit of how HP differentiates in the market cause, you know, VM Ware does partner with lots of people. But you know what separates the's point solution? Everything else out in the market? >>Sure, and synergy is a great example, because what we're seeing is really, really high interest on on synergy with VCF. And the reason for that is because customers want a software to find infrastructure that they can compose, compute storage and networking as they need to to address any workload they have. And they want to do that with a partner like VM Ware and VCF. So what we see is customers choosing those two things together and building their hybrid cloud environments on those two. When I think of some of the customers that we have, I'll give you a specific example. So Banco Santander's one of the largest banking groups in the world. And they are really trying to drive innovation across all of their, um, locations there in North America, South America, Europe, Asia. They're trying to drive innovation across. They have a big project, and they selected Synergy and VCF and as a service green lake bottle to help them transform their business. And they're really excited because what they think this is providing to them is a reduced a data center space, reduced power consumption and reduce costs. And all of that with automation, more automation than they've had in the past. More flexibility than they've had in the past. >>Yeah, I'm so glad you brought up the Green Lake because you know, those as a service models. You know, Cloud obviously has been a big discussion for the last two years, Lee, Um, you know, VM Ware is no stranger to, you know, working in multi and hybrid environments. It gives a little bit about you know what you're hearing from your customers. You know, if you meant Green Lake, how does that fit in the overall? You know, VM Ware multi cloud offering. >>Well, you know, we all know these air uncertain times, right? and customers and uncertain times. We're looking for flexibility. How do they go? And basically, you know, invest smartly, right? Look to come out of uncertain times stronger. And what we're finding is that the flexibility, you know, starting it. You know, we're really impressed with this energy platform, by the way, the idea of being able to flexibly, configure, compute and storage to tie into external arrays from that end, to have the VM Ware Cloud Foundation is a unifying, software defined data center concept that's available on Prem and then extends into the hybrid cloud. This basic gives investment protection to customers who are looking for how to invest in. You know, you mentioned Green Lake as well, and I just mentioned that innovation on Green Lake is about true consumption based purchasing miles, if you will. And that's different than just a financial engineering aspect. I mean, that's real innovation and real technical innovation in terms of how customers can go in a why infrastructure at the time that they needed relative to that compelling business models, >>and I'll chime in their Teoh, I'll tell you a little story about when I first presented the green like model. At that time, it wasn't called Green Lake, but I presented it to a bunch of customers, about 100 customers in an advisory council. And I have never had so many people come up to me afterwards trying to figure out how they can get that for themselves as I did when I had that presentation. What really resonated with people is that they wanted to take advantage of the latest and greatest technologies, but they didn't have big budgets. And when they did take advantage of those technologies, one of the challenges has been growth. So when they need to expand, that's another procurement cycle. You have a way to have the standard all love with Green Lake. You actually have that added capacity on sites and then also painful what you use s so they were attracted to all of those things. And I feel like right now and the environment were in many people had big, big projects, things they want to do, and they may have planned those ah, a capital expenditure for that. But that money may not be there, So Green Lake is one of those things that can help overcome that challenge. And what we found is when people use green like we don't see many people. Um, go back. So what? I was talking to the green like team, and I said, You know what happens if they decide not to do Green Lake and they're kind of pause, and they're like, Well, we really haven't run into that very often. So it's very, very popular, and customers were really happy with it. >>Yeah. Talking about innovation and helping customers take advantage of new technologies. You know, maybe we'll start with you and Krista. Definitely want your but been a lot of feedback about V. Sphere seven. Of course, One of the big pieces of that is how, you know, cloud native container ization kubernetes It can be pulled into the, you know, the virtualization platform. So we're talking a lot about vcf Lee. That's the you know. Wait. Get it. The community's piece today. Tell us a little bit about that and what you hear from customers. And then Chris, I'd like to understand how that fits into the HP offering. >>Yeah, you know, the data we have shows that 95% of new applications are being developed on containers. Why? Because it's the speed of ill. And so at VM Ware, we've re architected V sphere for the first time that, you know in the last five years. And you look carefully at what the EMR integrates into the hyper visor because that's what we believe is going to be really benefiting from performance efficiency and management. And so we've integrated kubernetes directly into the hyper visor itself and then to our Tom's, a portfolio. Introduce an upstream compatible kubernetes development environment so that we have developer ready infrastructure. And that's really important because at the speed of new applications, basically you need to be able to respond quickly to those and what VM Ware has always offered right, which is a resilient underlying infrastructure with an intrinsic security model built in conceptually important when containers are being spun up more quickly. All right, mark quickly. They're being portable and portable across the hybrid cloud. Those models right mean that you need and convince you get value right from this integrated model that leverages all of the experience and knowledge that people have around how to run V Center and V Sphere so really exciting, and it's available in VCF for with >>I actually see the interest. I see customers asking about an enquiring about it. Vikan, you know, definitely second everything that we just said. I think you're really you're going to see a really fast transition over because there's so much value. Add it in. >>Excellent. Okay, Crystal, while I've got you on the compute piece, you know, legally said that 95% of application new applications are being built on container ization. How has that impacted architecture, er and how you're working with? >>Yeah. So what I find is that customers are very interested in containers. What we're doing is we're helping them from a services standpoint. A consulting standpoint of many of these customers are adopting for the first time trying to figure out how they could they could leverage containers in their environment. From our standpoint, it's making sure that we have the right platforms and we're advising and consulting and helping customers get there. >>Excellent, Lee. You know, Kristen talked about a sense and under one wondering if you've got any customer examples you like to share? >>Yeah. Great. One is ah, portion. I love the portion example. Just because portion, just the epitome of speed. And so the idea of this flexibility well, you're finding rate is the flexibility, right? Starting from, let's say, from a synergy, I'm flexible on the part of their allocation, right? And then, with VCF right now being able to be flexible across the hybrid cloud and now with VCF or with ponzu, the flexibility of introducing new modern applications support on Finally Layer and Green Lake On top of that which which is also using it, gives you this idea that you know, especially in uncertain times. But, you know, regardless, the changing business environment where everyone's responding, toe app, development rushers, timelines and innovation. We've got a really interesting model now for customers to invest responsibly and be able to respond quickly. >>Hm. Excellent. Crystal, I guess. Said the other pieces were at discover any updates on the portfolio expanding the VM solution. That >>Yeah. Yeah. So I'd like to talk a little bit about our pre validated synergy vcf solution stack with built in automation. So we literally got rid of hundreds of that's pre and post employment so we could speed deployment by five times. We were talking to point in hours instead of weeks. So we're really, really excited about that. We're working together to make sure we're making things easier for customers making that journey to a hybrid cloud very, very simple. So we're really happy to have, you know, offer that to customers. >>Great Lee, Any any final words you can share on the partnership? You >>know what I might say? It's right that the pace of innovation from our companies right is so great, Right? That really v vm Ware Cloud Foundation is a way, you know, in our joint effort and joint delivery rate is a way for customers to assimilate all of this innovation. So that day zero, it's guaranteed the work. And that day two, you can lifecycle manage all the individual components from a common sec manager interface. That's the value that we're bringing together today. Is that Listen, you know, putting all this in place conceived, daunting until the VM Ware Cloud Foundation, with synergy with all of the joint value we have basically makes it manageable so that you can go and basically stop looking down it infrastructure. Look up the ass. >>All right. Christine will let you have the final word and final takeaways from HP Discover. >>Okay, sure. Thanks. Together. What we're trying to do is simplify that journey to hybrid cloud. Make sure that customers can innovate faster, provide stable operations and reduce their costs. >>Well, Chris Stanley, thank you so much for joining us. Congratulations on the progress. Looking forward. Toa watching down the road. >>All right, thanks. >>Alright, Stay tuned for lots more coverage from the Cube, HP Discover 2020. Virtual experience on stew Minimum. Thanks for watching. Yeah, >>yeah, yeah, yeah.

>> from Austin, Texas. It's Theo Cube covering your storage Accelerate 2019 Brought to you by pure storage. >> How do y'all welcome back Thio, the Cube leader In live coverage we're covering day to a pure accelerate 19 Lisa Martin With Day Volonte Welcoming to the cue for the first time from SG Mark Peters principal analyst and practice >> Oh, my apologies. So young. >> I wish I wish that was true. >> In fact, one of the first analysts I think that's true if not the first analyst ever on the Q. But, >> well, I'll say Welcome back. Thank you. We're glad to have you here. So you've been with Ishii for quite a while, You know, the storage industry inside and out, I'm sure pure. Just about to celebrate their 10th anniversary. Yesterday we heard lots of news, which is always nice for us to have father to talk about. But I'd love to get your take on this disruptive company. What they've been able to achieve in their 1st 10 years going directly through is Dave's been saying the last two days driving a truck there am sees, install, base, back of the day, your thoughts on how they've been able to achieve what they have. >> That'll last me to talk about something I really want to talk about. And I think it addresses your question. How have they been able to do it? It's by being different. Andi, I don't know. I mean, obviously you do a stack of into sheer and maybe other people have talked about that. But that is the end. When I say different, I don't necessarily mean technology. I have a kind of standard riff in this business that we get so embroiled in the technology. Do not for one second think it's not important, but we get so embroiled in that that we missed the human element or the emotional element on dhe. I think that's important. So they were very different. They created, you know, these thes armies of fans who just bought into what they did. Now, of course, that was based on initially bringing flash to the market making flasher Fordham. Well, they've extended that here with the sea announcement and other things as well, so I don't want to just focus on that, but you know, they continue to do things differently with the technology, But I think what really made them an attractive company and why they've survived 10 years on her now big sizable is because they were a different sort of company to deal with. >> Are you at all surprised that the fourth accelerate is in Austin, Texas? Dell's backyard? Yes. Well, they're disruptive. They're different. They're bold. We're okay, >> you see, But But also, did you go to the other three? >> Uh, the last two. I was trying to remind >> myself where they were. I know one was kind of on a pier in a ballpark in San Francisco. One words. You remember the one that was in that you Worf, But that was a a rusting, so cool it was. But it was a metaphor in a rusting spinning desk, right. But it was also such a different sort of place on, So I probably was also a few it D m c. But I agree. And then the last one was in some sort of constantly. Yes, So >> they were all >> different. And so I Yes, I know this is Dell's backyard. Probably literally, because I'm sure Michael owns a lot of the place. It's also kind of very normal place and so there's a little bit of me that I don't want to use the world worry. But as you grow up and of course, we've got the 10 year anniversary, we're in Austin. What's the tagline of Austin? >> I don't know. No. Keep Austin weird. Okay, >> I >> don't want to suggest appears weird, but they were always a little different, I said. That's why I think they were attracted as much as anything. Yes, that's why I had the hordes of admiring fans, all wearing their orange socks and T shirts and cheering on DDE as they get older as they get more mature as they expand their portfolio. Charlie was on stage talking not so much about scale the problem when he was asked, but more about complexity. As you get more complex, you actually get more normal on, So I don't know that weird is the word, but a bit like Austin pure needs to keep your interesting. >> I like that >> Very interesting. So >> you and I, >> we've been around a while. We were kind of students of the industry. I was commenting earlier that it's just to me very impressive that this company has achieved a new definition of escape velocity receiving a billion dollars show. First company since Nana to do it, I gotta listed three. Park couldn't do it. Compelling data domain isolani ecological left hand. Really good cos all very successful companies. Uh, >> what do you think? It's >> all coming out of >> the dot com crash. Maybe that pay part of it. Pure kind of came out of the, you know, the recession. Why >> do you >> think Pure has been able to achieve that? That you know, four x three par, for example in terms of revenues. And it's got a ways to go. They probably do 1.7 this year. I think they have aspirations for five on enough there. Publicly stated that they probably have, right? Of course. Why wouldn't they thoughts on why they were able to achieve that? What were the sort of factors genuinely know? Having no idea what you were gonna ask me. And now actually, listening to question let me You've just made me think of something that I had not really thought. So I took so long to ask the question formulated. And you are so, um, you used the word escape velocity. Let's think about planes. I mean, you know, I think it's a V one, isn't it to take off, Mitch? Maybe not the same as escape, which is in the skies. But you get the point. How long to really take off? Be independently airborne? They gave themselves. I don't know how much was by design default how it really happened? I don't know. They had an immensely long runway. You think the whole conversation about pure for years and years was Oh, yeah, yeah, they're making loads of revenue, but they lose 80 cents every time they get 50. That was the conversation for years and years. I know they've now turned that corner, and I think the difference. Actually, the more I think about it, yes. You can talk about product. Yes, you can talk about the experience. I think those things are both part of it. But the other companies you named had cool things too. They all had cool products you had. What was it? The autopilot thing with compelling. And they had lots of people cheering. Actually, in this building, I think three part was yellow and kind of cool in a different part of the market. and disruptive. But they were both trying to get to the exit fast. Whether the exit was being bought or whether it was going under. I don't know it was gonna be one or the other, and for both of them, they got bought. I don't think pure had that same intention, and it's certainly got funding and backers that allowed it to take longer. So that's a really good point. I think there's a There's a new Silicon Valley playbook. You saw it with service. Now, with Frank's limits like the Silicon Valley Mafia's Sweetman Dietzen, Bush re at Work Day, they all raised a boatload of cash and a sacrifice profits for for growth. I mean, I remember Dave Scott telling me, you know, when he came on, the board was saying, Hey, we're ready to you know, we're prepared to raise 30 million. He said, I need 80 eighties chump change today compared to what these guys were raising. Well, I mean, I think I mean, they pretty quickly raised hundreds of millions, didn't they? They weren't scraping by on 50 or 80 million, which which is what you see. You sort of want one more thought just this escape velocity idea, I think is interesting because the other thing about escape velocity is partly how long you take runway orbit, whatever. But it's the payload on, you know, The more the payload, the longer it takes the take off the ground or the more thrust you need thrust in this case, his money again. But if you think about it, this is another thing where he and I gotta say, we've been doing this a long time. The storage industry over decades has been one of the easiest industries to enter on one of the hardest to actually do well. Why is that? Because the payload is heavy. It's easy to make a box that works fast, big whatever you want in your garage. Two men on one application working for a day. It's really hard to be interoperable with every app, every other system, operational needs and so on and so forth. And so the payload to be successful. I think they understood that, too. So, you know, they didn't let ourselves get distracted by like the initial shiny, glittery we need to get out of this business. >> I love the parallels with payloads and Rockets. Because, of course, we had Leland Melvin inner keynote this morning. I'm a former NASA geek. Talk to us about your thoughts on their cloud strategy, the evolution of the partnership with a W s. We talked about that yesterday. Sort of this customers bringing this forcing function together, but being able to sort of simplify and give customers this pure management playing the software layer wherever their data is your thoughts on how their position themselves for multi cloud hybrid world. >> Okay, two thoughts, one cloud. Then you also used the word simplicity. So I want to talk about both of those things if I can, Um I don't know. I'm sorry. This is not a very good answer. I think it's the truth. I mean, you can't exist in this world if you haven't got a cloud story, and it better be hybrid or pub. Oh, are multi, whichever you prefer. I think those have very distinct meanings, by the way, but we would be here for an hour and 1/2. It'll be a cube special to really get into that. However, So you've got to do this. I mean, there is just, you know, none of the clients they're dealing with. Almost none. That's not research. I'll talk research in a second but glib statement. Everyone's got a cloud strategy. It doesn't matter which analyst company you put up the data, we'll do it. I want to talk about a cup, some research we've done in a second. But everyone will tell you a high number of people who have a cloud first strategy, whether that's overall or just the new applications or whatever. So they've got to do it. What's crucial to whether or not they succeed is not the AWS branding, because everyone's got a W s branding me people that they don't work with or will not work within the next year or two. I mean, I'm sure there's one God you look like you're anxious, you're on a roll. But simplicity is really important. So David knows we do a lot of research early yesterday, one of our cornerstone piece of researchers think all the spending intentions we do every year. One of the questions this year's Bean for a couple of years now is basically saying simple question Excuse. The overuse of the word is how much more complex is I t you know, in your experience, more or less complex. And it was two years ago. I t broadly and you know that I love this question. You know the answer on dhe. 66% of people say it is more complex now than it was two years ago. People don't want complexity. We all know that there's not enough skills around the research to back that up. A swell on dso Simplicity is really important cause who was sitting in this seat before May I think I will say that the company here was founded on simplicity. That was the point. They were to be the apple of storage. I think that's why people love them. They were just very easy to use on dso coming finally back to your question. If they can do this and keep it simple, then they have a better chance of success than others. But how do you define successful them isn't keeping their customers are getting new ones. That's a challenge. >> They do have a very high retention rate. I want to say like 140% but things like we have our dinner for two U percent attention. Yes. How did >> you do? So? So this is is interesting. It's actually 100 and 50% renewal rate. Oh, by the Mike Scarpelli CFO Math of renewal rates on a dollar value on net dollar value renewal rate subscriptions. Mike Scarpelli was the CFO of service. Now invented this model and service now had, like, 100 and whatever 1500 whatever 27. And so it's a revenue based renewal. Makes sense. Sorry for one second you're retaining more people than you >> go. 101 100 >> 50% is insane. 105 >> percent is great. Yeah, 150% is interrupted. Your question. >> Well, I'm just saying >> it's good. Good nuance, >> Yes, Thanks for clarifying its. You know, companies can say whether it's one. Appears customers are pure themselves or competitors. We are cloud. First, we have a cloud for strategy, and a company like pure can say we deliver simplicity, those air marketing terms until they're actually put in the field and delivered. So in your perspective, how does pure take what I T professionals are saying? Things are so much more complex these days? How does a pure commit and say simple, seamless, sustainable, like Charlie, Giancarlo said yesterday. And actually make that a reality. Well, I >> mean, obviously, that's their challenge, and that's what they have work to do to some degree. And this comes back to what I was saying that to some degree it becomes self fulfilling because your that's why your customers come back with more money because they bought into this on. So as long as they're kept happy, they're probably not going to go and look at 20 other people. I'm not saying they never had any of that simplicity to start off with, but it's very interesting if you go to a pure event, their customers and this might be sacrilege sitting in this environment don't talk about the product. They talk about the company, >> right? >> The experience There's that word again, off being appear customer yes on So they're into it. They brought into whatever this is, and as long as the product, please do not strike me down is good enough. I'm not saying that's all it is. I think it's a lot better that, but as long as it's good enough, but you're really well looked after a few minutes ago, when I'm saying that's why I think this market is about so much more than just how fast can you make the box? How big can you make the box? How smart can you make the box? All of those are interesting, But ultimately, I'm only looking at Dave because he's so old. Ultimately, technology is a leapfrog game. Yeah, branding is not >> Beaver >> s O. So that's a good point. But we've not seen the competitors be able to leap frog pure or be able to neutralize them the way, for example, that DMC was able to somewhat neutralize three par by saying, Oh, yeah, we have virtual ization, too, you know, are thin provisioning. Rather. Yeah. And even though they had a thin provisioning bolt on, it was it was good enough. Yes, they did the check box. You haven't seen the competitors be able to do that here? I'm not saying they won't, but are they? I think, um, I was going to say basically this on my MBA, but I don't have one, so I can't say that, but, you know, I've read that. Read the books. If you look at Harvard Business School cases, I think the mistake made by the competition was to assume that Pierre would go away, that they would each try it or that it would fail on will make fun of the fact they don't make any money for the first few years on dhe. You know, the people going to them, we're gonna be sadly mistaken when they can't handle these features, whether that be cloud or whether that be analytics or fresh blades or whatever else again to add on. They thought they would just go away that there are great parallels in history when you let competition in and you just keep thinking at each point they're going to go away. Spot the accent. British motorcycle industry. When the Japanese came in, they literally said, Well, let them. There are records. We'll let them have the 50 cc market because we don't really care about that. But we'll make the big bikes Well, Okay, well, let them have 152 100 cc because really, that doesn't matter. And 10 years later, there was no industry well, and I think what happened with the emcee in particular because, let's face it, pure hired a bunch of DMC wraps. They took your product and, as I've said before, they drove a truck to the the symmetric V n X install base Emcee responded by buying X extreme io and they said, You know what? We're sick of losing the pure. We're gonna go really aggressive into our own accounts and we're gonna keep them with flash. And then what happened is their accounts. It Hey, we're good. We don't actually really need more stores because the emcee tried to keep it is trying to keep both lines alive. And now they're conflicted, pure. You know, I had a what? We're mission. >> You thought not up a great point. Sorry. Just just because I think >> thing about that is if you look at how e. M. C using my words accurately usedto act, I think you said that, too. So I'm not criticizing Adele is they were exceptional organized marketing organization. We go that way. And if you're not going that way, you got a big problem both as a custom, Miranda's UN employees. But the problem with that is also is that way would sometimes become that way, and then it become that way on the product depending what was doing well. So, for example, they had, you know, tens of thousands of feet, all marching to the extreme. I owe beat for a few quarters, and then they would go off on to the next product pure. Just carried on, marching to its beat down that runway escape velocity question >> appoint you brought up a minute ago before we wrap her. That I think is really interesting is that you write your customers talk about the experience. I think we were talking with a customer yesterday. Dave was asking, Well, what technologies are you think he started talking about workloads? So when we're at other events, you hear other names of boxes brought up here to your point. It is all about the experience so interesting and how they're Can you continuing to just be different, but to wrap things up since they're in my ear, we're almost that time. I just wanna take a minute to ask you kind of upcoming research. What are some of the things that you're working on? Their really intriguing you and SG land. I think right >> now, from my perspective, I mean, as a company would continue to do 27,000 different things because there's so much going on in the market. So whether that's security is massive area of focus right now, even improvements in networking. So it's not just the regular run of the mill, you know, Bigger, faster, cheaper. Which is always there s o A. I, of course, in all these again, you may both know you will now doesn't mean we're always looking at buying intentions rather than counting boxes. So it's really where people are moving over the next few years. That said to May. I think what's really interesting is to other things. Number one is to what extent can. I don't think we can really measure this easily. But to what extent can we get people talking about pure again to acknowledge that emotions, attitudes, experiences are an important part of this business? I'm old enough that I'm not scared of saying it, and I think pure is a company is not scared of saying it, you know, I think a lot of companies don't want to admit that Andi all know that they have different corporate cultures and mantras and views on their customers reflect that two on The other thing just generally is the future of I t. As a whole. I know that. So, I mean, I'm doing this because none of us really know what that is, but, you know, clearly way gotta stop talking about the cloud At some point. It's just part of I t. It's not a thing as such. It's just another resource that you bring to bear. I don't know that we're yet at that point, but that's >> got to happen. >> Interesting. Thanks for looking. I'm imagine this was a crystal ball. But Mark, I wish we had more time because I know we could keep talking. But it's been a pleasure to have you >> got the whole multi cloud hybrid cloud for an hour and 1/2. >> We come back, we'll have that discussion. Like what I'll means and yeah, back anytime. >> Excellent. Thank you for joining David. Me. Thank you for David. Dante. I'm Lisa Martin. You were watching the Cube from pure accelerate 19

>> Live, from Miami Beach, Florida it's theCUBE covering VeeamON 2019. Brought to you by Veeam. >> Welcome back to Miami everybody, sunny Miami. Dave Vellante here with Peter Burris. You're watching theCUBE, the leader in live tech coverage. We go out to the events, we extract the signal from the noise, and there's a lot of noise here, and there's a lot of signal here. VeeamON 2019, this is theCUBE's third year doing Veeam's big customer show. We started doing NOLA, last year was Chicago, a very hip location here at the Fountainebleau Hotel. Carey Stanton is here. He is the Vice President of business development and corporate dev, corp-dev at Veeam and Jeff Kalat, a CUBE alum, >> Yep, you bet. >> long-time friend of theCUBE, senior director of strategic alliances at Hewlett-Packard Enterprise. Gentlemen, welcome to theCUBE, good to see you. >> Thanks for having us. >> You're very welcome. Carey let me start with you. Uh, I really want to talk about sports with you, but anyway, we won't. We'll hold that off. (laughter) >> (Carey) One day. >> Momentum. You're relatively new to Veeam. But you've been here now a couple years. Where's this momentum coming from, from your perspective, as a recent Veeam entrant. >> Yeah, no, the momentum's coming from across the board, but I think a big momentum is coming from new product innovation that we're doing with Office 365, and we're just driving up subscription business momentum that we have for the pent-up demand that we had for Euphor. But a big part is coming from our relationships like we have with HPE. We invested heavily a few years ago when we announced that joint reseller agreement. What we've done is not just continued to sell but add a plethora of new solutions to it Jeff's going to talk about what we're doing with GreenLake adding SimpliVity, adding the overall solutions that we have. But that's a team that started two years ago with two people that we now have over 20 people just working, dedicated with HPE on co-selling. And I'm happy to say that our business in first half, or I should say year-to-date is up 50% year over year on a global reseller business. >> Well Jeff, theCUBE as you know, has been documenting the ebbs and flows of HP and HPE over the last, better part of a decade. And when HP split in two, to HPE and HP Inc. One of the things that-- And then sold the software business, or a large portion of it. One of the things that went was data protection. >> (Jeff) You got it. >> (Dave) And that just opened up a whole new set of opportunities and Veeam was obviously one of those. And it's starting to pay dividends. >> You got it, yeah, to that point, that evolution through HPE.nex, we were able to focus on our core. And the benefit, the inherit benefit is that we can partner with the best of class in the marketplace. And Veeam is considered best of class. So when it comes to data availability, data protection, we're all in. And we're actually, as a company, we're actually doubling down now in our partnership with Veeam. We've actually taken them from, maybe a traditional storage alliance, and taken them to be one of our top global strategic alliances in the line of the Microsoft's, the Veeam, or as the SAP's. Because we see great momentum, we see great customer adoption and interest and we see great innovation at the product level, but also in the whole global market chain. >> Well talk a little more about that because it was, the move allowed you to form new partnerships that dramatically expanded your TAM but, I'm interested in the nature of the partnership. Is it, just go to market, is there engineering integration? Talk about that a little bit. >> Our first step when we came together and said okay let's take this to the next level, we realized we need to narrow our focus to the core customer values and we really settled on three core areas of this relationship. One is first, data protection for, around our intelligence storage, as you know, our storage portfolio 3 Par, Nimble, we've had a great relationship there, we continue to drive co-innovation at the road map level, but also drive go-to-market activities and marketing and we have feet on the street actively selling. So the first one's really expanding our work with storage. Now we're taking it, we're extending, if you will, through consumption based data management, using, well HPE has GreenLake, Greenlake we see 40% of customers by 2020 are going to be consuming their data center IT more in a consumption model. There are inherent benefits of that. What we now have offered and launched just recently Backup,is a service through our flex capacity coming out of GreenLake, providing customers the choice, if you will, to move from a, not from a capital expenditure, but, by the drink, if you will, consumption base. So that's the second core area. And the third core area is new for us, and that's around our HCI portfolio. As you know, we purchased SimpliVity. Well, SimpliVity has a lot of inherent backup, dedupe compression in line, but there actually are some Zivik use cases that we're deploying out there that show how Simplivity in a Veeam environment can actually, customers can see actually incremental values. So, those are the three key areas we're focused on as we up-level this whole relationship and partnership. >> (Dave) So Carey, please. >> I was just going to say if you think of, we talk a lot about we go after the technical decision maker in all these, hundreds of people here at the conference. And then going towards the executive, the enterprise. And it's through relationships with HPE on this, the flex capacity, being able to go to a customer and offer a true enterprise solution that they're looking for, everyone wants as a service. And so we've closed multiple deals this year thanks to having the Greenlake. So, our relationship with HPE continues to elevate and the enterprise is a result of the solutions that we're doing. Not just selling storage, but selling a complete solution. >> Rathmeyer was kind of tongue-in-cheek this morning at the analyst and media event. He was talking about how in 2013 he predicted that Veeam would be a billion dollar company by 2018. And he said he missed it by six months. One of the reasons was because you know, you got the subscription model. So that's, you know GreenLake obviously is part of that, maybe not the predominant part yet but I think you said you have 40% you're saying will consume, as a service by 2020. >> 2020, actually soon. >> (Dave) Okay so pretty substantial. >> Yeah. >> What's driving that? Is it just CFO's want to go to opex? Or is it-- >> I think it's a, there are many, the value you get without locking yourself into every three years needing to do a total forklift upgrade of your infrastructure, that's one thing. The second thing is moving it from a capital expenditure to an opex expediture. It can be planned, it can be budgeted as well. The third thing is the customer doesn't have to mess with all the technology, updating the firmware, the drivers and all that. We will do it on their behalf, right? We give them the economics of cloud on prem and that's the beauty of that. So we believe, and lock-step in alignment with Veeam, the world is hybrid in the future. So on prem is here to live forever, but increasingly we need to leverage the assets in the cloud and this is providing the ability of doing it in a consumption model. >> And it's not just the economics it's the experience as well. >> Oh totally, if you want to, if you live in a house and you're a home owner, and you want a new bathroom, you put in a bathroom. If you're a renter you end up in a long, laborious negotiation that you're going to lose. And the same kind of notion is here as people realize there's greater strategic opportunities and options from how to use their data differently. They want access to those options. And that's the basis of agility. The opex to capex is good but you've got to put it in business context. It's how you create additional options in your data oriented investments. So, as you guys are moving forward are you starting to have that conversation with customers? And relating data, data value, asset management, Backup, Restore, to this broader picture, this broader strategic union you're putting together? >> Yeah and that is a key imperative of how we get even stronger in traction is telling the bigger picture. And you look at the world of yesterday, where it's just backup and recovery, look at the advent of edge devices and the amount of data that's being put at the edge. Now look at AI and machine learning where, the data is inherently needed to project the changes and the needs that are in the future. So, I think these all tie in to the play and I believe at GreenLake our consumption model can provide great benefits, above and beyond the traditional backup and recovery. >> And I was just going to add to it, is that it also brings in our ecosystems, so the relationship, that tier one relationship we both have within Microsoft. So when you start looking at a solution that the business owner wants, they want to be able to say I need cloud, I need on prem, I need backup recovery, and so by going through GreenLake they can encompass, we have a broader ecosystem that we're able to bring in versus just single thread in these discussions where you're going in and selling a data protection story and leaving but you didn't solve that broader customer problem, and with GreenLake, they are solving that overall problem. >> Yeah, I'd just like to say nothing really happens until you make a sale. You talked about some of the growth earlier. But why Veeam? Obviously you're getting some traction in the market but there's a lot of players out there that you could partner with. And you do partner with others. But why Veeam? What makes Veeam so special? >> I think one, inherently we are lock-step in agreement of the over-arching strategy, we talked about hybrid, we talked about portfolio. Two is we've got the engagement at all levels of our organization, which all stems truly from having a unified roadmap. Innovation has to happen at the roadmap level and you need to be lock-step aligned through the value chain in the way you take it to market, the way you align your sellers, the way you deliver a value proposition that truly is valuable to our customers. It's proven from our IDC research that customers who are deploying and purchasing HPE and Veeam solutions are seeing a 250 plus percent ROI on that investment. So there's this huge customer benefit, and why not go bigger and go bigger and go bigger with them. >> (Dave) Same question to you Carey. So why HPEE, why is HPEE so special as a partner? >> I think HPE first and foremost, being that first partner that came to us to want to go all in, as Jeff was talking about, from day one, and top down. So we're not just working with a department of HPE we have it from Antonio, from Jim Jackson down the stack in the organization. We were aligned from day one. They lead with data protection, it's no longer, it's a a nice to have, it's a requirement in every one of their sales processes. We're their lead partner that they have in data protection. And what we'd been able to do and have that enterprise visibility by them assisting us on our journey. So, from across the board, whether it's through management, through technology, or just in true go-to-market, they're by far our number one partner that we have on our sell-with motion. >> So Jeff, I want to talk to the group about GreenLake. And Carey, I'd love to hear your thoughts on it as well. What are the challenges that go into a consumption-based model for a company that's traditionally sold products. As part of this overall move in all industries, all sectors, from a product to a services orientation. How do introduce metrics that are associated with the service? Because it used to be you just sold a product. And the metrics for storage are different from the metrics from backup, different from the metrics from compute. So as you've gone to GreenLake, because I love GreenLake, what kind of specialized, or specific types of things, how are you selling it to try to tie that service into the business outcomes that your customers are trying to see? >> Well clearly, I believe, some of our first wins, early wins we were able to monitor and metric the value the customers were getting, the service levels they've received and so we have a number of different methods of capturing the data, the empirical data, on the service levels and being able to use that to then, use that in the selling motion to be able to articulate the experience and the expectations that come with that. >> What are some of the harder problems that your customers are asking you to solve? And how are you approaching it together? >> Well I think that what we're talking about with GreenLake here is a real hard problem to solve, right? Consumpton based across geographic regions, across different technologies, on prem, off prem, hybrid. And we don't have another partner that we can go to market with when we hear this from the customer. So when we hear it, we know that we can lean in. And we truly are, to follow up from your question, is the fact is that HPEE is solving all this and then bringing us in as their number one partner, is the differentiator that we love. So solving those problems at an enterprise level, and at a commercial level and doing it with one partner is easy, right? We're shortening the sales cycle, increasing the value to the customer. >> Yeah, one thing I have to say and it's always, complexity is always a problem and an issue, right? So it will always be a problem and an issue and we will always be striving to improve and improve the complexity. But you know, Veeam, we're super simple, right? And we, especially when you look in our HCI portfolio and that's all about driving simplicity, if you will, in a way you can deploy IT, you can scale it. So I think complexity is, and will always be a problem. But it's a given too and it will always be there. And we will always be striving to make it even easier and easier for our joint customers. >> Well one of the challenges that you face, especially as you go to a sevices-only model, is how do you put a price on the outcomes that you're delivering as opposed to the price on the assets that the person is taking? So I think one of the biggest challenges, and it sounds like you guys are pretty close to getting this together, but it's part of a broader portfolio, is where does this, let's put it slightly differently. We've talked about this before in some of the other interviews. backup is moved from a have to have it, for maybe compliance or it just makes good sense to have it, to a strategic business capability for a company that's increasingly differentiating itself on it's data assets. That moves this conversation about, as a service, into a different group and a different, different level. And that's what I'm wondering. Those metrics have got to be a big part of the conversation. Because the entire organization is now recognizing backup is more than just a bolt-on. >> Yeah. One example, one of our close partners, we're here with them, Island. So, disaster recovery as a service, right? They standardize on Nimble and Veeam and together, that combination to them was good enough to build their business on. So there's inherent value and we expect to continue to grow and be able to expose that value. 'Cause we believe more and more customers, not just your pure enterprises but, from your mid-market all the way up, can be able to utilize and see that value and experience it. >> Just a point of clarification if I could on the HCI piece. Specifically around SimpliVity. So SimpliVity was known for it's backup use cases. >> (Jeff) Sure. Still is. >> So where does Veeam and SimpliVity fit, versus Simplivity solo. >> Yeah, yeah. Well first and foremost yes, Simplivity has inherent, great data availability features, inherent in it. That's core to it. But in reality, for customers, let's say a mixed environment, whether it be virtualized, non-vitrualized, there are inherent benefits to having Veeam in addition to SimpliVity. Another example would be customers who want to really have the access to be able to do specific file restores. So we see capabilities in running Veeam in parallel with SimpliVity. Actually I see a lot of customers that are deploying SimpliVity are also deploying Veeam and there, it's an additive value that they're seeing. And they're able to parse out features and functionality and be able to increase their level of value that couldn't be done, just purely from a Simplivity standpoint alone. >> All right Carey, we'll give you the final word. >> The final word is-- >> Bumper sticker on VeeamON. >> (laughing) >> Bumper stickers. >> I would say that, what we're doing here with HPEE, we would say we're in the first inning. What we're seeing on the innovations that we have coming out later this year with HPEE, coming into next year, and we're just thrilled to be having them a platinum sponsor of VeeamON and look forward to another successful year. >> Awesome. Guys thanks so much for coming on. I got to ask you, Boston-based person, Bruins fan? >> (Carey) Bruins, yes. >> You worried about Tuulka, at all, a 12 day layoff? >> (Carey) Nope. >> No problem. >> (Carey) Nope, Chara's going to be nice and rested and-- >> (Dave) Chara, more Chara or less Chara? >> I'm going to, yes well. I got to take more thanks. >> Okay, all right, good. We'll see, we'll see. Go Bruins. All right guys thanks so much for coming out and thank you for watching. Keep it right there we'll be back with our next guest shortly right after this break. You're watching theCUBE from VeeamON, 2019 from Miami. Be right back.

Live from New York It's theCUBE! Covering theCUBE New York City 2018 Brought to you by Silicon Angle Media and it's ecosystem partners >> Hey welcome back and we're live in theCUBE in New York city. It's our 2nd day of two days of coverage CUBE NYC. The hashtag CUBENYC Formerly Big data NYC renamed because it's about big data, it's about the server, it's about Cooper _________'s multi-cloud data. It's all about data, and that's the fundamental change in the industry. Our next guest is Yaron Haviv, who's the CTO of Iguazio, key alumni, always coming out with some good commentary smart analysis. Kind of a guest host as well as an industry participant supplier. Welcome back to theCUBE. Good to see you. >> Thank you John. >> Love having you on theCUBE because you always bring some good insight and we appreciate that. Thank you so much. First, before we get into some of the comments because I really want to delve into comments that David Richards said a few years ago, CEO of RenDisco. He said, "Cloud's going to kill Hadoop". And people were looking at him like, "Oh my God, who is this heretic? He's crazy. What is he talking about?" But you might not need Hadoop, if you can run server less Spark, Tensorflow.... You talk about this off camera. Is Hadoop going to be the open stack of the big data world? >> I don't think cloud necessary killed Hadoop, although it is working on that, you know because you go to Amazon and you know, you can consume a bunch of services and you don't really need to think about Hadoop. I think cloud native serve is starting to kill Hadoop, cause Hadoop is three layers, you know, it's a file system, it's DFS, and then you have server scheduling Yarn, then you have applications starting with map produce and then you evolve into things like Spark. Okay, so, file system I don't really need in the cloud. I use Asfree, I can use a database as a service, as you know, pretty efficient way of storing data. For scheduling, Kubernetes is a much more generic way of scheduling workloads and not confined to Spark and specific workloads. I can run with Dancerflow, I can run with data science tools, etc., just containerize. So essentially, why would I need Hadoop? If I can take the traditional tools people are now evolving in and using like Jupiter Notebooks, Spark, Dancerflow, you know, those packages with Kubernetes on top of a database as a service and some object store, I have a much easier stack to work with. And I could mobilize that whether it's in the cloud, you know on different vendors. >> Scale is important too. How do you scale it? >> Of course, you have independent scaling between data and computation, unlike Hadoop. So I can just go to Google, and use Vquery, or use, you know, DynamoDB on Amazon or Redchick, or whatever and automatically scale it down and then, you know >> That's a unique position, so essentially, Hadoop versus Kubernetes is a top-line story. And wouldn't that be ironic for Google, because Google essentially created Map Produce and Coudera ran with it and went public, but when we're talking about 2008 timeframe, 2009 timeframe, back when ventures with cloud were just emerging in the mainstream. So wouldn't it be ironic Kubernetes, which is being driven by Google, ends up taking over Hadoop? In terms of running things on Kubernetes and cloud eight on Visa Vis on premise with Hadoop. >> The poster is tend to give this comment about Google, but essentially Yahoo started Hadoop. Google started the technology  and couple of years after Hadoop started, with Google they essentially moved to a different architecture, with something called Percolator. So Google's not too associated with Hadoop. They're not really using this approach for a long time. >> Well they wrote the map-produced paper and the internal conversations we report on theCUBE about Google was, they just let that go. And Yahoo grabbed it. (cross-conversation) >> The companies that had the most experience were the first to leave. And I think it may respect what you're saying. As the marketplace realizes the outcomes of the dubious associate with, they will find other ways of achieving those outcomes. It might be more depth. >> There's also a fundamental shift in the consumption where Hadoop was about a ranking pages in a batch form. You know, just collecting logs and ranking pages, okay. The chances that people have today revolve around applying AI to business application. It needs to be a lot more concurring, transactional, real-time ish, you know? It's nothing to do with Hadoop, okay? So that's why you'll see more and more workers, mobilizing different black server functions, into service pre-canned services, etc. And Kubernetes playing a good role here is providing the trend. Transport for migrating workloads across cloud providers, because I can use GKE, the Google Kubenetes, or Amazon Kubernetes, or Azure Kubernetes, and I could write a similar application and deploy it on any cloud, or on Clam on my own private cluster. It makes the infrastructure agnostic really application focused. >> Question about Kubernetes we heard on theCUBE earlier, the VP of Project BlueData said that Kubernetes ecosystem and community needs to do a better job with Stapla, they nailed Stapflalis, Stafle application support is something that they need help on. Do you agree with that comment, and then if so, what alternatives do you have for customers who care about Stafe? >> They should use our product (laughing) >> (mumbling) Is Kubernetes struggling there? And if so, talk about your product >> So, I think that our challenge is rounded that there are many solutions in that. I think that they are attacking it from a different approach Many of them are essentially providing some block storage to different containers on really cloud 90. What you want to be able is to have multiple containers access the same data. That means either sharing through file systems, for objects or through databases because one container is generating, for example, ingestion or __________. Another container is manipulating that same data. A third container may look for something in the data, and generate a trigger or an action. So you need shared access to data from those containers. >> The rest of the data synchronizes all three of those things. >> Yes because the data is the form of state. The form of state cannot be associated with the same container, which is what most of where I am very active and sincere in those committees, and you have all the storage guys in the committees, and they think the block story just drag solution. Cause they still think like virtual machines, okay? But the general idea is that if you think about Kubernetes is like the new OS, where you have many processes, they're just scattered around. In OS, the way for us to share state between processes an OS, is whether through files, or through databases, in those form. And that's really what >> Threads and databases as a positive engagement. >> So essentially I gave maybe two years ago, a session at KubeCon in Europe about what we're doing on storing state. It's really high-performance access from those container processes to our database. Impersonate objects, files, streams or time series data, etc And then essentially, all those workloads just mount on top of and we can all share stape. We can even control the access for each >> Do you think you nailed the stape problem? >> Yes, by the way, we have a managed service. Anyone could go today to our cloud, to our website, that's in our cloud. It gets it's own Kubernetes cluster, a provision within less than 10 minutes, five to 10 minutes. With all of those services pre-integrated with Spark, Presto, ______________, real-time, these services functions. All that pre-configured on it's own time. I figured all of these- >> 100% compatible with Kubernetes, it's a good investment >> Well we're just expanding it to Kubernetes stripes, now it's working on them, Amazon Kubernetes, EKS I think, we're working on AKS and GK. We partner with Azure and Google. And we're also building an ad solution that is essentially exactly the same stock. Can run on an edge appliance in a factory. You can essentially mobilize data and functions back and forth. So you can go and develop your work loads, your application in the cloud, test it under simulation, push a single button and teleport the artifacts into the edge factory. >> So is it like a real-time Kubernetes? >> Yes, it's a real-time Kubernetes. >> If you _______like the things we're doing, it's all real-time. >> Talk about real-time in the database world because you mentioned time-series databases. You give objects store versus blog. Talk about time series. You're talking about data that is very relevant in the moment. And also understanding time series data. And then, it's important post-event, if you will, meaning How do you store it? Do you care? I mean, it's important to manage the time series. At the same time, it might not be as valuable as other data, or valuable at certain points and time, which changes it's relationship to how it's stored and how it's used. Talk about the dynamic of time series.. >> Figured it out in the last six or 12 months that since real-time is about time series. Everything you think about real-time censored data, even video is a time-series of frames, okay And what everyone wants to do is just huge amount of time series. They want to cross-correlate it, because for example, you think about stock tickers you know, the stock has an impact from news feeds or Twitter feeds, or of a company or a segment. So essentially, what they need to do is something called multi-volume analysis of multiple time series to be able to extract some meaning, and then decide if you want to sell or buy a stock, as in vacation example. And there is a huge gap in the solution in that market, because most of the time series databases were designed for operational databases, you know, things that monitor apps. Nothing that injects millions of data points per second, and cross-correlates and run real-time AI analytics. Ah, so we've essentially extended because we have a programmable database essentially under the hoop. We've extended it to support time series data with about 50 to 1 compression ratio, compared to some other solutions. You know we've break with the customer, we've done sizing, they told them us they need half a pitabyte. After a small sizing exercise, about 10 to 20 terabytes of storage for the same data they stored in Kassandra for 500 terabytes. No huge ingestion rates, and what's very important, we can do an in-flight with all those cross-correlations, so, that's something that's working very well for us. >> This could help on smart mobility. Kenex 5G comes on, certainly. Intelligent edge. >> So the customers we have, these cases that we applied right now is in financial services, two or three main applications. One is tick data and analytics, everyone wants to be smarter learning on how to buy and sell stocks or manage risk, the second one is infrastructure, monitoring, critical infrastructure, monitoring is SLA monitoring is be able to monitor network devices, latencies, applications, you now, transaction rate, or that, be able to predict potential failures or escalation We have similar applications; we have about three Telco customers using it for real-time time. Series analytics are metric data, cybersecurity attacks, congestion avoidance, SLA management, and also automotive. Fleet management, file linking, they are also essentially feeding huge data sets of time series analytics. They're running cross-correlation and AI logic, so now they can generate triggers. Now apply to Hadoop. What does Hadoop have anything to do with those kinds of applications? They cannot feed huge amounts of datasets, they cannot react in real-time, doesn't store time-series efficiently. >> Hapoop (laughing) >> You said that. >> Yeah. That's good. >> One, I know we don't have a lot of time left. We're running out of time, but I want to make sure we get this out here. How are you engaging with customers? You guys got great technical support. We can vouch for the tech chops that you guys have. We seen the solution. If it's compatible to Kubernetes, certainly this is an alternative to have really great analytical infrastructure. Cloud native, goodness of your building, You do PFC's, they go to your website, and how do you engage, how do you get deals? How do people work with you? >> So because now we have a cloud service, so also we engage through the cloud. Mainly, we're going after customers and leads, or from webinars and activities on the internet, and we sort of follow-up with those customers, we know >> Direct sales? >> Direct sales, but through lead generation mechanism. Marketplace activity, Amazon, Azure, >> Partnerships with Azure and Google now. And Azure joint selling activities. They can actually resale and get compensated. Our solution is an edge for Azure. Working on similar solution for Google. Very focused on retailers. That's the current market focus of since you think about stores that have a single supermarket will have more than a 1,000 cameras. Okay, just because they're monitoring shelves in real-time, think about Amazon go, kind of replication. Real-time inventory management. You cannot push a 1,000 camera feeds into the cloud. In order to analyze it then decide on inventory level. Proactive action, so, those are the kind of applications. >> So bigger deals, you've had some big deals. >> Yes, we're really not a raspberry pie-kind of solution. That's where the bigger customers >> Got it. Yaron, thank you so much. The CTO of Iguazio Check him out. It's actually been great commentary. The Hadoop versus Kubernetes narrative. Love to explore that further with you. Stay with us for more coverage after this short break. We're live in day 2 of CUBE NYC. Par Strata, Hadoop Strata, Hadoop World. CUBE Hadoop World, whatever you want to call it. It's all because of the data. We'll bring it to ya. Stay with us for more after this short break. (upbeat music)

Okay, this presentation includes forward looking statements that are subject to risks and uncertainties. Actual results may differ materially as a result of various risk factors including those described in the 10 k's 10 q's and eight ks. Vm ware files with the SEC, ladies and gentlemen, Sunjay Buddha for the jazz mafia from Oakland, California. Good to be with you. Welcome to late night with Jimmy Fallon. I'm an early early morning with Sanjay Poonen and two are set. It's the first time we're doing a live band and jazz and blues is my favorite. You know, I prefer a career in music, playing with Eric Clapton and that abandoned software, but you know, life as a different way. I'll things. I'm delighted to have you all here. Wasn't yesterday's keynote. Just awesome. Off the charts. I mean pat and Ray, you just guys, I thought it was the best ever keynote and I'm not kissing up to the two of you. If you know pat, you can't kiss up to them because if you do, you'll get an action item list at 4:30 in the morning that sten long and you'll be having nails for breakfast with him but bad it was delightful and I was so inspired by your tattoo that I decided to Kinda fell asleep in batter ass tattoo parlor and I thought one wasn't enough so I was gonna one up with. I love Vm ware. Twenty years. Can you see that? What do you guys think? But thank you all of you for being here. It's a delight to have you folks at our conference. Twenty 5,000 of you here, 100,000 watching. Thank you to all of the vm ware employees who helped put this together. Robin Matlock, Linda, Brit, Clara. Can I have you guys stand up and just acknowledge those of you who are involved? Thank you for being involved. Linda. These ladies worked so hard to make this a great show. Everybody on their teams. It's the life to have you all here. I know that we're gonna have a fantastic time. The title of my talk is pioneers of the possible and we're going to go through over the course of the next 90 minutes or so, a conversation with customers, give you a little bit of perspective of why some of these folks are pioneers and then we're going to talk about somebody who's been a pioneer in the world but thought to start off with a story. I love stories and I was born in a family with four boys and my parents I grew up in India were immensely creative and naming that for boys. The eldest was named Sanjay. That's me. The next was named Santosh Sunday, so if you can get the drift here, it's s a n, s a n s a n and the final one. My parents got even more creative and colon suneel sun, so you could imagine my mother going south or Sunday do. I meant Sanjay you and it was always that confusion and then I come to the United States as an immigrant at age 18 and people see my name and most Americans hadn't seen many Sundays before, so they call me Sanjay. I mean, of course it of sounds like v San, so sanjay, so for all of your V, San Lovers. Then I come to California for years later work at apple and my Latino friends see my name and it sorta sounds like San Jose, so I get called sand. Hey, okay. Then I meet some Norwegian friends later on in my life, nordics. The J is a y, so I get called San Year. Your my Italian friend calls me son Joe. So the point of the matter is, whatever you call me, I respond, but there's certain things that are core to my DNA. Those that people know me know that whatever you call me, there's something that's core to me. Maybe I like music more than software. Maybe I want my tombstone to not be with. I was smart or stupid that I had a big heart. It's the same with vm ware. When you think about the engines that fuel us, you can call us the VM company. The virtualization company. Server virtualization. We seek to be now called the digital foundation company. Sometimes our competitors are not so kind to us. They call us the other things. That's okay. There's something that's core to this company that really, really stands out. They're sort of the engines that fuel vm ware, so like a plane with two engines, innovation and customer obsession. Innovation is what allows the engine to go faster, farther and constantly look at ways in which you can actually make the better and better customer obsession allows you to do it in concert with customers and my message to all of you here is that we want to both of those together with you. Imagine if 500,000 customers could see the benefit of vsphere San Nsx all above cloud foundation being your products. We've been very fortunate and blessed to innovate in everything starting with Sova virtualization, starting with software defined storage in 2009. We were a little later to kind of really on the hyperconverged infrastructure, but the first things that we innovate in storage, we're way back in 2009 when we acquired nicer and began the early works in software defined networking in 2012 when we put together desktop virtualization, mobile and identity the first time to form the digital workspace and as you heard in the last few days, the vision of a multi cloud or hybrid cloud in a virtual cloud networking. This is an amazing vision couple that innovation with an obsession and customer obsession and an NPS. Every engineer and sales rep and everybody in between is compensated on NPS. If something is not going well, you can send me an email. I know you can send pat an email. You can send the good emails to me and the bad emails to Scott Dot Beto said Bmr.com. No, I'm kidding. We want all of you to feel like you're plugged into us and we're very fortunate. This is your vote on nps. We've been very blessed to have the highest nps and that is our focus, but innovation done with customers. I shared this chart last year and it's sort of our sesame street simple chart. I tell our sales rep, this is probably the one shot that gets used the most by our sales organization. If you can't describe our story in one shot, you have 100 powerpoints, you probably have no power and very The fact of the matter is that the data center is sort of like a human body. little point. You've got your heart that's Compute, you've got the storage, maybe your lungs, you've got the nervous system that's networking and you've got the brains of management and what we're trying to do is help you make that journey to the cloud. That's the bottom part of the story. We call it the cloud foundation, the top part, and it's all serving apps. The top part of that story is the digital workspace, so very simply put that that's the desktop, moving edge and mobile. The digital workspace meets the cloud foundation. The combination is a digital foundation Where does, and we've begun this revolution with a company. That's what we end. focus on impact, not just make an impression making an impact, and there's three c's that all of us collectively have had an impact on cost very clearly. I'm going to walk you through some of that complexity and carbon and the carbon data was just fascinating to see some of that yesterday, uh, from Pat, these fierce guarded off this revolution when we started this off 20 years ago. These were stories I just picked up some of the period people would send us electricity bills of what it looked like before and after vsphere with a dramatic reduction in cost, uh, off the tune of 80 plus percent people would show us 10, sometimes 20 times a value creation from server consolidation ratios. I think of the story goes right. Intel initially sort of fought vm ware. I didn't want to have it happen. Dell was one of the first investors. Pat Michael, do I have that story? Right? Good. It's always a job fulfilling through agree with my boss and my chairman as opposed to disagree with them. Um, so that's how it got started. And true with over the, this has been an incredible story. This is kind of the revenue that you've helped us with over the 20 years of existence. Last year was about a billion but I pulled up one of the Roi Charts that somebody wrote in 2006. collectively over a year, $50 million, It might've been my esteemed colleague, Greg rug around that showed that every dollar spent on vm ware resulted in nine to $26 worth of economic value. This was in 2006. So I just said, let's say it's about 10 x of economic value, um, to you. And I think over the years it may have been bigger, but let's say conservative. It's then that $50 million has resulted in half a trillion worth of value to you if you were willing to be more generous and 20. It's 1 trillion worth of value over the that was the heart. years. Our second core product, This is one of my favorite products. How can you not like a product that has part of your name and it. We sent incredible. But the Roi here is incredible too. It's mostly coming from cap ex and op ex reduction, but mostly cap x. initially there was a little bit of tension between us and the hardware storage players. Now I think every hardware storage layer begins their presentation on hyperconverged infrastructure as the pathway to the private cloud. Dramatic reduction. We would like this 15,000 customers have we send. We want every one of the 500,000 customers. If you're going to invest in a private cloud to begin your journey with, with a a hyperconverged infrastructure v sound and sometimes we don't always get this right. This store products actually sort of the story of the of the movie seabiscuit where we sort of came from behind and vm ware sometimes does well. We've come from behind and now we're number one in this category. Incredible Roi. NSX, little not so obvious because there's a fair amount spent on hardware and the trucks would. It looks like this mostly, and this is on the lefthand side, a opex mostly driven by a little bit of server virtualization and a network driven architecture. What we're doing is not coming here saying you need to rip out your existing hardware, whether it's Cisco, juniper, Arista, you get more value out of that or more value potentially out of your Palo Alto or load balancing capabilities, but what we're saying is you can extend the life, optimize your underlay and invest more in your overlay and we're going to start doing more and software all the way from the l for the elephant seven stack firewalling application controllers and make that in networking stack, application aware, and we can dramatically help you reduce that. At the core of that is an investment hyperconverged infrastructure. We find often investments like v San could trigger the investments. In nsx we have roi tools that will help you make that even more dramatic, so once you've got compute storage and networking, you put it together. Then with a lot of other components, we're just getting started in this journey with Nsx, one of our top priorities, but you put that now with the brain. Okay, you got the heart, the lungs, the nervous system, and the brain where you do three a's, sort of like those three c's. You've got automation, you've got analytics and monitoring and of course the part that you saw yesterday, ai and all of the incredible capabilities that you have here. When you put that now in a place where you've got the full SDDC stack, you have a variety of deployment options. Number one is deploying it. A traditional hardware driven type of on premise environment. Okay, and here's the cost we we we accumulate over 2,500 pms. All you could deploy this in a private cloud with a software defined data center with the components I've talked about and the additional cost also for cloud bursting Dr because you're usually investing that sometimes your own data centers or you have the choice of now building an redoing some of those apps for public cloud this, but in many cases you're going to have to add on a cost for migration and refactoring those apps. So it is technically a little more expensive when you factor in that cost on any of the hyperscalers. We think the most economically attractive is this hybrid cloud option, like Vm ware cloud and where you have, for example, all of that Dr Capabilities built into it so that in essence folks is the core of that story. And what I've tried to show you over the last few minutes is the economic value can be extremely compelling. We think at least 10 to 20 x in terms of how we can generate value with them. So rather than me speak more than words, I'd like to welcome my first panel. Please join me in welcoming on stage. Are Our guests from brinks from sky and from National Commercial Bank of Jamaica. Gentlemen, join me on stage. Well, gentlemen, we've got a Indian American. We've got a kiwi who now lives in the UK and we've got a Jamaican. Maybe we should talk about cricket, which by the way is a very exciting sport. It lasts only five days, but nonetheless, I want to start with you Rohan. You, um, brings is an incredible story. Everyone knows the armored trucks and security. Have you driven in one of those? Have a great story and the stock price has doubled. You're a cio that brings business and it together. Maybe we can start there. How have you effectively being able to do that in bridging business and it. Thank you Sanjay. So let me start by describing who is the business, right? Who is brinks? Brinks is the number one secure logistics and cash management services company in the world. Our job is to protect our customers, most precious assets, their cash, precious metals, diamonds, jewelry, commodities and so on. You've seen our trucks in your neighborhoods, in your cities, even in countries across the world, right? But the world is going digital and so we have to ratchet up our use of digital technologies and tools in order to continue to serve our customers in a digital world. So we're building a digital network that extends all the way out to the edges and our edges. Our branches are our messengers and their handheld devices, our trucks and even our computer control safes that we place on our customer's premises all the way back to our monitoring centers are processing centers in our data centers so that we can receive events that are taking place in that cash ecosystem around our customers and react and be proactive in our service of them and at the heart of this digital business transformation is the vm ware product suite. We have been able to use the products to successfully architect of hybrid cloud data center in North America. Awesome. I'd like to get to your next, but before I do that, you made a tremendous sacrifice to be here because you just had a two month old baby. How is your sleep getting there? I've been there with twins and we have a nice little gift for you for you here. Why don't you open it and show everybody some side that something. I think your two month old will like once you get to the bottom of all that day. I've. I'm sure something's in there. Oh Geez. That's the better one. Open it up. There's a Vm, wear a little outfit for your two month. Alright guys, this is great. Thank you all. We appreciate your being here and making the sacrifice in the midst of that. But I was amazed listening to you. I mean, we think of Jamaica, it's a vacation spot. It's also an incredible place with athletes and Usain bolt, but when you, the not just the biggest bank in Jamaica, but also one of the innovators and picking areas like containers and so on. How did you build an innovation culture in the bank? Well, I think, uh, to what rughead said the world is going to dissolve and NCB. We have an aspiration to become the Caribbean's first digital bank. And what that meant for us is two things. One is to reinvent or core business processes and to, to ensure that our customers, when they interact with the bank across all channels have a, what we call the Amazon experience and to drive that, what we actually had to do was to work in two moons. Uh, the first movement we call mode one is And no two, which is stunning up a whole set of to keep the lights on, keep the bank running. agile labs to ensure that we could innovate and transform and grow our business. And the heart of that was on the [inaudible] platform. So pks rocks. You guys should try it. We're going to talk about. I'm sure that won't be the last hear from chatting, but uh, that's great. Hey, now I'd like to get a little deeper into the product with all of you folks and just understand how you've engineered that, that transformation. Maybe in sort of the order we covered in my earlier comments in speech. Rohan, you basically began the journey with the private cloud optimization going with, of course vsphere v San and the VX rail environment to optimize your private cloud. And then of course we'll get to the public cloud later. But how did that work out for you and why did you pick v San and how's it gone? So Sunday we started down this journey, the fourth quarter of 2016. And if you remember back then the BMC product was not yet a product, but we still had the vision even back then of bridging from a private data center into a public cloud. So we started with v San because it helped us tackle an important component of our data center stack. Right. And we could get on a common platform, common set of processes and tools so that when we were ready for the full stack, vmc would be there and it was, and then we could extend past that. So. Awesome. And, and I say Dave with a name like Dave Matthews, you must have like all these musicians, like think you're the real date, my out back. What's your favorite Dave Matthew's song or it has to be crashed into me. Right. Good choice rash. But we'll get to music another time. What? NSX was obviously a big transformational capability, February when everyone knows what sky and media and wireless and all of that stuff. Networking is at the core of what you do. Why did you pick Nsx and what have you been able to achieve with it? So I mean, um, yeah, I mean there's, like I say, sky's yeah, maybe your organization. It's incredibly fast moving industry. It's very innovative. We've got a really clever people in, in, in, in house and we need to make sure our product guys and our developers can move at pace and yeah, we've got some great. We've got really good quality metric guys. They're great guys. But the problem is that traditional networking is just fundamentally slow is there's, there's not much you can do about it, you know, and you know to these agile teams here to punch a ticket, get a file, James. Yeah. That's just not reality. We're able to turn that round so that the, the, the devops ops and developers, they can just use terraform and do everything. Yeah, it's, yeah, we rigs for days to seconds and that's in the Aes to seconds with an agile software driven approach and giving them much longer because it would have been hardware driven. Absolutely. And giving the tool set to the do within boundaries. You have scenes with boundaries, developers so they can basically just do, they can do it all themselves. So you empower the developers in a very, very important way. Within a second you had, did you use our insight tools too on top of that? So yes, we're considered slightly different use case. I mean, we're, yeah, we're in the year. You've got general data protection regulations come through and that's, that's, that's a big deal. And uh, and the reality is from what an organization's compliance isn't getting right? So what we've done been able to do is any convenience isn't getting any any less, using vr and ai and Nsx, we're able to essentially micro segment off a lot of Erica our environments which have a lot, much higher compliance rate and you've got in your case, you know, plenty of stores that you're managing with visa and tens of thousands of Vms to annex. This is something at scale that both of you have been able to achieve about NSX and vsn. Pretty incredible. And what I also like with the sky story is it's very centered around Dev ops and the Dev ops use case. Okay, let's come to your Ramon. And obviously I was, when I was talking to the Coobernetti's, uh, you know, our Kubernetes Platform, team pks, and they told me one of the pioneer and customers was National Commercial Bank of Jamaica. I was like, wow, that's awesome. Let's bring you in. And when we heard your story, it's incredible. Why did you pick Coobernetti's as the container platform? You have many choices of what you could have done in terms of companies that are other choices. Why did you pick pks? So I think, well, what happened to, in our interviews cases, we first looked at pcf, which we thought was a very good platform as well. Then we looked at the integration you can get with pqrs, the security, the overland of Nsx, and it made sense for us to go in that direction because you offered 11 team or flexibility on our automation that we could drive through to drive the business. So that was the essence of the argument that we had to make. So the key part with the NSX integration and security and, and the PKS. Uh, and while we've got a few more chairs from the heckler there, I want you to know, Chad, I've got my pks socks on. That's how much I had so much fear. And if he creates too much trouble with security, we can be emotional. I'm out of the arena, you know. Anyway. Um, I wanted to put this chart up because it's very important for all of you, um, and the audience to know that vm ware is making a significant commitment to Coobernetti's. Uh, we feel that this is, as pat talked about it before, something that's going to be integrated into everything we do. It's going to become like a dial tone. Um, and this is just the first of many things you're going to see a vm or really take this now as a consistent thing. And I think we have an opportunity collectively because a lot of people think, oh, you know, containers are a threat to vm ware. We actually think it's a headwind that's going to become a tailwind for us. Just the same way public cloud has been. So thank you for being one of our pioneer and early customers. And Are you using the kubernetes platform in the context of running in a vsphere environment? Yes, we are. We're onto Venice right now. Uh, we have. Our first application will be a mobile banking APP which will be launched in September and all our agile labs are going to be on pbs moving forward medic. So it's really a good move for us. Dave, I know that you've, not yet, I mean you're looking in the context potentially about is your, one of the use cases of Nsx for you containers and how do you view Nsx in that? Absolutely. For us that was the big thing about t when it refresh rocked up is that the um, you know, not just, you know, Sda and on a, on vsphere, but sdn on openstack sdn into their container platform and we've got some early visibility of the, uh, of the career communities integration on there and yeah, it was, it was done right from the start and that's why when we talked to the pks Yeah, it's, guys again, the same sort of thing. it's, it's done right from the start. And so yeah, certainly for us, the, the NSX, everywhere as they come and control plane as a very attractive proposition. Good. Ron, I'd like to talk to you a little bit about how you viewed the public, because you mentioned when we started off this journey, we didn't have Mr. Cloud and aws, we approached to when we were very early on in that journey and you took a bet with us, but it was part of your data center reduction. You're kind of trying to almost to obliterate one data center as you went from three to one. Tell us that story and how the collaboration worked out on we amber cloud. What's the use case? So as I said, our vision was always to bridge to a So we wanted to be able to use public cloud environments to incubate new public cloud, right? applications until they stabilize to flex to the cloud. And ultimately disaster recovery in the cloud. That was the big use case for us. We ran a traditional data center environment where, you know, we run across four regions in the world. Each region had two to three data centers. One was the primary and then usually you had a disaster recovery center where you had all your data hosted, you had certain amount of compute, but it was essentially a cold center, right? It, it sat idle, you did your test once a year. That's the environment we were really looking to get out of. Once vmc was available, we were able to create the same vm ware environment that we currently have on prem in the cloud, right? The same network and security stack in both places and we were actually able to then decommission our disaster recovery data center, took it off, it's took it off and we move. We've got our, our, all of our mission critical data now in the, uh, in the, uh, aws instance using BMC. We have a small amount of compute to keep it warm, but thanks to the vm ware products, we have the ability now to ratchet that up very quickly in a Dr situation, run production in the cloud until we stabilized and then bring that workload back. Would it be fair to tell everybody here, if you are looking at a Dr or that type of bursting scenario, there's no reason to invest in a on premise private cloud. That's really a perfect use case of We, I know certainly we had breaks. this, right? Sorry. Exactly. Yeah. We will no longer have a, uh, a physical Dr a center available anywhere. So you've optimized your one data center with the private cloud stack will be in cloud foundation effectively starting off a decent and you've optimized your hybrid cloud journey, uh, with we cloud. I know we're early on in the journey with Nsx and branch, so we'll come back to that conversation may next year we discover new things about this guy I just found out last night that he grew up in the same town as me in Bangalore and went to the same school. So we will keep a diary of the schools at rival schools, but the last few years with the same school, uh, Dave, as you think about the future of where you want to this use case of network security, what are some of the things that are on your radar over the course of the next couple of months and quarters? So I think what we're really trying to do is, um, you know, computers, this is a critical thing decided technology conference, computers and networks are a bit boring, but rather we want to make them boring. We want to basically sweep them away from so that our people, our customers, our internal customers don't have to think about it were the end that we can make him, that, that compliance, that security, that whole, that whole framework around it. Um, regardless of where that work, right live as living on premise, off premise, everywhere you know. And, and even Aisha potentially out out to the edge. How big were your teams? Very quickly, as we wrap up this, how big are the teams that you have working on network is what was amazing. I talked to you was how nimble and agile you're with lean teams. How big was your team? The, the team during the, uh, the SDDC stack is six people. Six, six. Eight. Wow. There's obviously more that more. And we're working on that core data center and your boat to sleep between five and seven people. For it to brad to both for the infrastructure and containers. Yes. Rolling on your side. It's about the same. Amazing. Well, very quickly maybe 30 seconds. Where do you see the world going? Rolling. So, you know, it brings, I pay attention to two things. One is Iot and we've talked a little bit about that, but what I'm looking for there as digital signals continue to grow is injecting things like machine learning and artificial intelligence in line into that flow back so we can make more decisions closer to the source. Right. And the second thing is about cash. So even though cash volume is increasing, I mean here we are in Vegas, the number one cash city in the US. I can't ignore the digital payments and crypto currency and that relies on blockchain. So focusing on what role does blockchain play in the global world as we go forward and how can brings, continue to bring those services, blockchain and Iot. Very rare book. Well gentlemen, thank you for being with us. It's a pleasure and an honor. Ladies and gentlemen, give it up for three guests. Well, um, thank you very much. So as you saw there, it's great to be able to see and learn from some of these pioneering customers and the hopefully the lesson you took away was wherever your journey is, you could start potentially with the private cloud, embark on the journey to the public cloud and then now comes the next part which is pretty exciting, which is the journey off the desktop and removal what digital workspace. And that's the second part of this that I want to explore with a couple of customers, but before I do that, I wanted to set the context of why. What we're trying to do here also has economic value. Hopefully you saw in the first set of charts the economic value of starting with the heart, the lungs, any of that software defined data center and moving to the ultimate hybrid cloud had economic value. We feel the same thing here and it's because of fundamental shift that started off in the last seven, 10 years since iphone. The fact of the matter is when you look at your fleet of your devices across tablets, phones and laptops today is a heterogeneous world. Twenty years ago when the company started, it was probably all Microsoft devices, laptops now phones, tablets. It's a mixture and it was going to be a mixture for the rest of them. I think for the foreseeable time, with very strong, almost trillion market cap companies and in this world, our job is to ensure that heterogeneous digital workspace can be very easily managed and secured. I have a little soft corner for this business because the first three years of my five years here, I ran this business, so I know a thing about these products, but the fact of the matter is that I think the opportunity here is if you think about the 7 billion people in the world, a billion of them are working for some company or the other. The others are children or may not be employed or retired and every one of them have a phone today. Many of them phones and laptops and they're mixed and our job is to ensure that we bring simplicity to this place. You saw a little bit that cacophony yesterday and Pat's chart, and unfortunately a lot of today's world of managing and securing that disparate is a mountain of morass. Okay? No offense to any of the vendors named in there, but it shouldn't be your job to be that light piece of labor at the top of the mountain to put it all together, which costs you potentially at least $50 per user per month. We can make the significantly cheaper with a unified platform, workspace one that has all of those elements, so how have we done that? We've taken those fundamental principles at 70 percent, at least reduction of simplicity and security. A lot of the enterprise companies get security, right, but we don't get simplicity all always right. Many of the consumer companies like right? But maybe it needs some help and facebook, it's simplicity, security and we've taken both of those and said it is possible for you to actually like your user experience as opposed to having to really dread your user experience in being able to get access to applications and how we did this at vm ware, was he. We actually teamed with the Stanford Design School. We put many of our product managers through this concept of design thinking. It's a really, really useful concept. I'd encourage every one of you. I'm not making a plug for the Stanford design school at all, but some very basic principles of viability, desirability, feasibility that allow your product folks to think like a consumer, and that's the key goal in undoing that. We were able to design of these products with the type of simplicity but not compromise at all. Insecurity, tremendous opportunity ahead of us and it gives me great pleasure to bring onstage now to guests that are doing some pioneering work, one from a partner and run from a customer. Please join me in welcoming Maria par day from dxc and John Market from adobe. Thank you, Maria. Thank you Maria and John for being with us. Maria, I want to start with you. A DXC is the coming together of two companies and CSC and HP services and on the surface on the surface of it, I think it was $50,000, 100,000. If it was exact numbers, most skeptics may have said such a big acquisition is probably going to fail, but you're looking now at the end of that sort of post merger and most people would say it's been a success. What's made the dxc coming together of those two very different cultures of success? Well, first of all, you have to credit a lot of very creative people in the space. One of the two companies came together, but mostly it is our customers who are making us successful. We are choosing to take our customers the next generation digital platform. The message is resonating, the cultures have come together, the individuals have come together, the offers have come together and it's resonating in the marketplace, in the market and with our customers and with our partners. So you shouldn't have doubted it. I, I wasn't one of the skeptics, maybe others were. And my understanding is the d and the C Yes. If, and dxc is the digital and customer. if you look at the logo, it's, it's more of an infinity, so digital transformation for customers. But truthfully it's um, we wanted to have a new start to some very powerful companies in the industry and it really was a instead of CSC and HP, a new logo and a new start. And I think, you know, if this resonates very well with what I started off my keynote, which is talking about innovation and customers focused on digital and Adobe, obviously not just a household name, customers, John, many of folks who use your products, but also you folks have written the playbook on a transformation of on premise going cloud, right? A SAS products and now we've got an incredible valuations relative. How has that affected the way you think in it in terms of a cloud first type of philosophy? Uh, too much of how you implement, right? From an IT perspective, we're really focused on the employee experience. And so as we transitioned our products to the cloud, that's where we're working towards as well from an it, it's all about innovation and fostering that ability for employees to create and do some amazing products. So many of those things I talked about like design thinking, uh, right down the playbook, what adobe does every day and does it affect the way in which you build, sorry, deploy products 92. Yeah, I mean fundamentally it comes down to those basics viability and the employee experience. And we've believe that by giving employees choice, we're enabling them to do amazing work. Rhonda, Maria, you obviously you were in the process of rolling out some our technology inside dxc. So I want to focus less on the internal implementation as much as what you see from other clients I shared sort of that mountain of harassed so much different disparate tools. Is that what you hear from clients and how are you messaging to them, what you think the future of the digital workspaces. And I joined partnership. Well Sanjay, your picture was perfect because if you look at the way end user compute infrastructure had worked for years, decades in the past, exactly what we're doing with vm ware in terms of automation and driving that infrastructure to the cloud in many ways. Um, companies like yours and mine having the courage to say the old way of on prem is the way we made our license fees, the way move made our professional services in the past. And now we have to quickly take our customers to a new way of working, a fast paced digital cloud transformation. We see it in every customer that we're dealing with everyday of the week What are some of the keyboard? Every vertical. I mean we're, we're seeing a lot in the healthcare and in a variety of verticals. industry. I'm one of the compelling things that we're seeing in the marketplace right now is the next gen worker in terms of the GIG economy. I'm employees might work for one company at 10:00 in the morning and another company at We have to be able to stand those employees are 10 99 employees up very 2:00 in the afternoon. quickly, contract workers from around the world and do it securely with governance, risk and compliance quickly. Uh, and we see that driving a lot of the next generation infrastructure needs. So the users are going from a company like dxc with 160,000 employees to what we think in the future will be another 200, 300,000 of 'em, uh, partners and contract workers that we still have to treat with the same security sensitivity and governance of our w two employees. Awesome. John, you were one of the pioneer and customers that we worked with on this notion of unified endpoint management because you were sort of a similar employee base to Vm ware, 20,000 odd employees, 1000 plus a and you've got a mixture of devices in your fleet. Maybe you can give us a little bit of a sense. What percentage do you have a windows and Mac? So depending on the geography is we're approximately 50 percent windows 50 slash 50 windows and somewhat similar to how vm ware operates. What is your fleet of mobile phones look like in terms of primarily ios? We have maybe 80 slash 20 or 70 slash 20 a apple and Ios? Yes. Tablets override kinds. It's primarily ios tablets. So you probably have something in the order of, I'm guessing adding that up. Forty or 50,000 devices, some total of laptops, tablets, phones. Absolutely split 60 slash 60,000. Sixty thousand plus. Okay. And a mixture of those. So heterogeneities that gear. Um, and you had point tools for many of those in terms of managing secure in that. Why did you decide to go with workspace one to simplify that, that management security experience? Well, you nailed it. It's all about simplification and so we wanted to take our tools and provide a consistent experience from an it perspective, how we manage those endpoints, but also for our employee population for them to be able to have a consistent experience across all of their devices. In the past it was very disconnected. It was if you had an ios device, the experience might look like this if you had a window is it would look like go down about a year ago is to bring that together again, this. And so our journey that we've started to simplicity. We want to get to a place where an employee can self provision their desktop just like they do their mobile device today. And what would, what's your expectations that you go down that journey of how quickly the onboarding time should, should be for an employee? It should be within 15, 20 minutes. We need to, we need to get it very rapid. The new hire orientation process needs to really be modified. It's no longer acceptable from everything from the it side ever to just the other recruiting aspects. An employee wants to come and start immediately. They want to be productive, they want to make contributions, and so what we want to do from an it perspective is get it out of the way and enable employees to be productive as And the onboarding then could be one way you latch him on and they get workspace quickly as possible. one. Absolutely. Great. Um, let's talk a little bit as we wrap up in the next few minutes, or where do you see the world going in terms of other areas that are synergistic, that workspace one collaboration. Um, you know, what are some of the things that you hear from clients? What's the future of collaboration? We're actually looking towards a future where we're less dependent on email. So say yes to that real real time collaboration. DXC is doing a lot with skype for business, a yammer. I'll still a lot with citrix, um, our tech teams and our development teams use slack and our clients are using everything, so as an integrator to this space, we see less dependent on the asynchronous world and a lot more dependence on the synchronous world and whatever tools that you can have to create real time. Um, collaboration. Now you and I spoke a little last night talking about what does that mean to life work balance when there's always a demanding realtime collaboration, but we're seeing an uptick in that and hopefully over the next few years a slight downtick in, in emails because that is not necessarily the most direct way to communicate all the time. And, and in that process, some of that sort of legacy environment starts to get replaced with newer tools, whether it's slack or zoom or we're in a similar experience. All of the above. All of the above. Are you finding the same thing, John Environment? Yeah, we're moving away. There's, I think what you're going to see transition is email becomes more of the reporting aspect, the notification, but the day to day collaboration is me to products like slack are teams at Adobe. We're very video focused and so even though we may be a very global team around the world, we will typically communicate over some form of video, whether it be blue jeans or Jabber or Blue Jeans for your collaboration. Yeah. whatnot. We've internally, we use Webex and, and um, um, and, and zoom in and also a lot of slack and we're happy to announce, I think at the work breakouts, we'll hear about the integration of workspace one with slack. We're doing a lot with them where I want to end with a final question with you. Obviously you're very passionate about a cause that we also love and I'm passionate about and we're gonna hear more about from Malala, which is more women in technology, diversity and inclusion and you know, especially there's a step and you are obviously a role model in doing that. What would you say to some of the women here and others who might be mentors to women in technology of how they can shape that career? Um, I think probably the women here are already rocking it and doing what you need to do. So mentoring has been a huge part of my career in terms of people mentoring me and if not for the support and I'm real acceptance of the differences that I brought to the workplace. I wouldn't, I wouldn't be sitting here today. So I think I might have more advice for the men than the women in the room. You're all, you have daughters, you have sisters, you have mothers and you have women that you work every day. Um, whether you know it or not, there is an unconscious bias out there. So when you hear things from your sons or from your daughters, she's loud. She's a little odd. She's unique. How about saying how wonderful is that? Let's celebrate that and it's from the little go to the top. So that would be, that would be my advice. I fully endorse that. I fully endorse that all of us men need to hear that we have put everyone at Vm ware through unconscious bias that it's not enough. We've got to keep doing it because it's something that we've got to see. I want my daughter to be in a place where the tech world looks like society, which is not 25, 30 percent. Well no more like 50 percent. Thank you for being a role model and thank you for both of you for being here at our conference. It's my pleasure. Thank you Thank you very much. Maria. Maria and John. So you heard you heard some of that and so that remember some of these things that I shared with you. I've got a couple of shirts here with these wonderful little chart in here and I'm not gonna. Throw it to the vm ware crowd. Raise your hand if you're a customer. Okay, good. Let's see how good my arm is. There we go. There's a couple more here and hopefully this will give you a sense of what we are trying to get done in the hybrid cloud. Let's see. That goes there and make sure it doesn't hit anybody. Anybody here in the middle? Right? There we go. Boom. I got two more. Anybody here? I decided not to bring an air gun in. That one felt flat. Sorry. All. There we go. One more. Thank you. Thank you. Thank you very much, but this is what we're trying to get that diagram once again is the cloud foundation. Folks. The bottom part, done. Very simply. Okay. I'd love a world one day where the only The top part of the diagram is the digital workspace. thing you heard from Ben, where's the cloud foundation? The digital workspace makes them cloud foundation equals a digital foundation company. That's what we're trying to get done. This ties absolutely a synchronously what you heard from pat because everything starts with that. Any APP, a kind of perspective of things and then below it are these four types of clouds, the hybrid cloud, the Telco Cloud, the cloud and the public cloud, and of course on top of it is device. I hope that this not just inspired you in terms of picking up a few, the nuggets from our pioneers. The possible, but every one of the 25,000 view possible, the 100,000 of you who are watching this will take people will meet at all the vm world and before forums. the show on the road and there'll be probably 100,000 We want every one of you to be a pioneer. It is absolutely possible for that to happen because that pioneering a capability starts with every one of you. Can we give a hand once again for the five customers that were onstage with us? That's great.

[Music] [Applause] hello everyone welcome to the cube conversation here in palo alto california i'm john furrier host of thecube we got a special breaking news at scale has hired a new ceo chris lynch is the big news and taking over dave mariano with the evp of technology important because one cube alumni and also we've seen about all the big data events doing amazing work in the cloud scale data market for many many years we're very familiar at scale both david and chris lynch both cube alumni chris great to see you congratulations new ceo of atscale thanks john i really appreciate being here so um we know each other you've been on the cube before you're formerly the ceo of vertica sold to hp other ceos before that also a venture capitalist at atlas ventures for that distinguished career why this move right now what's attracted you to at scale take over the helm from the co-founder who will be partnering with you on this it's a great question um i'm still asking myself that but i think what it comes down to is i met dave years ago when i was at atlas and um it didn't work out the time for us to make an investment but i tracked the company and what they were doing and i left accomplished a little over a year ago and working with some companies out in the west coast app and be out here and i reached out to dave and said hey you want to grab dinner which we did and um by the end of the evening he was like you know you should come help us really commercialize this and take it to the next level they've been on our radar they've been on our radar for a while obviously i mean david at hadoop summit i think three four years ago and he was formerly a cloud we kind of hit it off clearly a big data um visionary and also entrepreneur but they had a unique model at that time hadoop was certainly viewed as you know the king of the castle for in big data at that time but cloud scale wasn't on everyone's radar on the mainstream they had a unique perspective has anything changed with the tech is that what's attracted to you the scaled piece of it what's the what's the secret sauce that that got you enticing so so i'm aware of the company's history that's not what got me interested um what got me interested is i think that they're the only player today in in the market that has a production product that can actually take customers from the data center to the cloud and do so transparently and i liken it to what we did at copia we virtualized file systems and frankly when we virtualized http traffic at arrow point so the idea of an abstraction layer a federation layer made sense to me and um you know as a venture capitalist i've seen the lack of adoption of big data workloads in the cloud you know there's a 200 billion dollar opportunity i think these guys are uniquely qualified to take advantage of it so that's really what drove me from a from a business perspective i see this opportunities unique versus anything i've seen on either coast we get a great reputation as an operator also someone who can manage and operate businesses and grow them and ultimately you have some great exits in your day vertica is well known in in the history of tech for two reasons one is it was probably the best deal hp ever has ever done on acquisition value-wise also it was before and during the whole vertica and autonomy autonomy acquisition was billions of dollars so and they ended up throwing that away keeping vertica and that became the flagship so you've seen how companies can take a wave and get in the right position you've done that with stone breaker in the past founder of vertica do you get the same movement here with this company it's the same playbook what's different is it the same what's the opportunity for this company so i think the opportunity for this company is different at vertica it was about executing against the excellent product that they had built in a known market they were targeted for my vision for at scale is to move beyond the data lake hadoop market and really take all the legacy warehousing vendors to the cloud cloud proof those solutions behind the firewall and begin to deliver those workloads in earnest to the cloud transparent to the user irrespective of the bi tool whether the the technology is behind the firewall in front of the firewall and i think that's a game changer certainly we've seen on the cube and the big conversation in the industry has been hybrid cloud multi-cloud but if you squint through that those trend lines it's really about integration right so you mentioned getting people to the cloud how big is that right now from an action standpoint is it is it accelerating is it early stages where is the progress bar on companies accelerating to the cloud it's it's stalled frankly because there are thousands of tens of thousands of applications in the fortune 500 that the the ability to take those applications and that data and move it to the cloud is it's on par with trying to operate do heart surgery on a patient while they're running the boston marathon so it's too difficult it's too disruptive to a business too risky what we do is we create a federation layer that basically abstracts all that complexity from the user and makes that transition transparent so to the user they don't have to care whether it's behind the firewall in front of the firewall what cloud it sits on what analytics store you're drawing from what bi tool it doesn't matter to the user so they've basically been able to separate those two things and that's going to allow people to scale and evolve into the cloud right today cloud is a revolution not an evolution it needs to be an evolution for fortune 500 companies to take advantage of it i got to ask you the hard question because ultimately let amazon they're kicking ass 10 ways from saturday they're obviously the numbers are off the chart even in public sectors just down there last week you got azure retooling and essentially they're going to try to replicate the the uh the congress of scale i think they're going to have a hard time but still no they're not going anywhere either and you get google changing the game focusing on their core competencies and where they can differentiate all that is potentially competition so this company at scale they definitely have tech chops so that's you know we know the team there so they had a lot of credit for that but 25 million dollars raised in their last round of funding total capital day 45 million how are you going to compete how are you going to take this and commercialize this opportunity and not be driftwood instead ride that wave it's a terrific question i actually think that one of the things that excites me about this opportunity it's the first opportunity as an operator that i've had that i haven't been in the david goliath thing i actually don't think that any of those people are competitors i think when atscale wins bi vendors win traditional data stores win and the cloud provider wins and ultimately the customer wins so my view is all those companies you mentioned if google wants to be relevant in the enterprise they need to get those big data workloads to their cloud we can do that we can continue to help amazon do that we can help oracle secure cloud do that we can help microsoft do that and all the time we're future proofing the legacy data stores of the teradatas and the oracles and the ibms so this is the first opportunity that i've seen where the game isn't to go disrupt and call out the competition it's to work with all these people to drive workloads to the cloud in a in a scale that hasn't been done before so you'd have to unseat anyone you've got to ride the cloud wave pretty much yeah we have to we have to demonstrate to these guys that we do what we say we we do um but my view is when we win all those participants can potentially win awesome how about uh staff funding you feel good that enough try powder in there is there another round of funding on the horizon or yeah i mean you know i haven't even started yet but you know my expectation is that in this marketplace with my track record raising capital or attracting capital will not be an issue it'll be about figuring out the business model and making sure it's right and then investing behind that business model it's enough cash now certainly do that talk about the boston california you're going to stay in boston that's news companies based in california you have a pedigree in boston certainly and being a vc down there but also you run businesses down there there's talent down there is there plans for a boston expansion a boston bi-coastal situation what's their opportunity so the company will remain headquartered in san mateo and i'll take up residence here and i'll go back and forth so my family's not moving so i'll have a residence in boston and one here um but you can absolutely expect that i'm going to leverage the ecosystem that i've grown up in and we will have a significant presence on the east coast awesome chris final question machine learning you guys were close to that for a long time at vertica you guys were doing some of the most cutting-edge machine learning before it became super popular as it is now as they call it ai now but essentially that was the beginning of the commodore store database which you guys pioneered speed and using data for competitive advantage how is that now scaled up in the market now how how robust is it how mature is it how ready is it and how does atscale take advantage of of that of that growth so i think that the world of data science in general has matured if you look at one of my proudest investments company called data robot they are the leaders in automated machine learning and their business is growing triple digits every year the level of adoption is really only gated by practitioners and people to apply the technology to these business problems but it's gaining incredible momentum for us i plan to integrate automated ai into components of our architecture which i think makes it really a game changer so of course we expect competition um but by the time that you know they get you know 100 miles behind us you know we're going to hit that what's that button that you have in those teslas you guys drive out here insane mode and it'll be automated machine learning will be powering that what's your impression of the marketplace right now is that um you know obviously you're seeing global landscape you know we see the china situation going on asia a lot of activity a lot of growth outside the united states um and obviously cloud you're seeing region specialties any thoughts on how that's going to play into it is it not relevant to you guys right now what's the what's your thoughts on the global landscape i mean i think it's it's relevant to everyone because i think it's what's driving valuations and this influx of money coming from these different places i mean if if you look at the middle east you know they're writing checks to any sort of tech company they can because they're pr trying to divest of what they know is a dead business right so that's going to drive valuations it's going to drive in my opinion um a lack of discipline and and bad behavior as we've seen you know in 2000 and other times in 2008 um i think for us as a company we're going to be disciplined and you know the fact that we can raise money and raise money attractive valuations isn't a reason to do it if you have a business model of fund that's a reason to do it so you know i don't think it'll be a distraction for us but i think it will increase you know the amount of noise in all the key markets and i think cyber we've seen it you know ai for sure um iot bitcoin all these what's the most exciting thing in the data business that's as it evolves now to the center value proposition that you see and as the ceo now of at scala you're going to capture this i think i would say two things in the in the ai machine learning space i think the fact that with democratization of data you're now actually seeing people applying machine learning way broader in organizations and way deeper than ever before and that's going to transform businesses low-tech business as well as high-tech businesses for us i think that the real opportunity exists it's a question of just taking these lit these legacy workloads and moving them to the cloud and that's not a trivial task not just technically but um you always have to be sensitive to companies ability to absorb technology i think one of the challenges is you know you're trying to transform a business that you know basically was informed as it developed in technology that was 1980. well chris congratulations on the ceo opportunity at at scale um what can people expect from you what what if you can write the narrative of the first couple moves off the line of scrimmage here what are you going to do what's your order of business what can they expect from you well the first thing i'd like to do after i meet the customers and the employees and the par existing partners is go out and get two significant partnerships i like to see a couple partnerships in cloud a couple partnerships with the classic data store vendors so that's probably going to be my first mission to get that moving and you know we'll see how quickly it goes but i think that's super important to do yeah and certainly scale right now has been a big competitive advantage here's a company at scale five year on their five year anniversary interesting gestation period for this big data world because hadoop you can look back into 2010 days hadoop was supposed to be the biggest thing since sliced bread but what happened was the world became bigger and from a date not just outside hadoop gave these guys an opportunity and their architecture fits well you see it's scaling quicker what's your what's your where's your point of scale how do you see this so i think i think that the company probably rightly so at the time hitch their wagon to hadoop but i think as you said it's it's really a subset of the data landscape and it's actually a pretty small one the real opportunity is in driving all the legacy data and analytics stores those islands of analytics and bringing them to the cloud and that like i said i think is a you know 100 billion dollar business well certainly great to see you congratulations getting back at the chief position and did a great job at vertica great journey we followed you on that one that was fantastic and then certainly watch it unfold certainly at hpe create a lot of value congratulations and at scale's got a good hire there congratulations thank you i appreciate it alright this is thecube conversation here inside the palo alto studios i'm john furrier thanks for watching [Music]