>>Yeah, it's the queue covering the virtual vertical Big Data Conference 2020. Brought to you by vertical. >>Hi, everybody. And welcome to this cube special presentation of the vertical virtual Big Data conference. The Cube is running in parallel with Day One and day two of the vertical of Big Data event. By the way, the Cube has been every single big data event in It's our pleasure to be here in the virtual slash digital event as well. Gabriel Chapman is here. He's the director of Flash Blade Products Solutions Marketing at Pure Storage. Great to see you. Thanks for coming on. >>Great to see you too. How's it going? >>It's going very well. I mean, I wish we were meeting in Boston at the Encore Hotel, but, uh, you know, and hopefully we'll be able to meet it, accelerate at some point, future or one of the sub shows that you guys are doing the regional shows, but because we've been covering that show as well. But I really want to get into it. And the last accelerate September 2019 pure and vertical announced. Ah, partnership. I remember a joint being ran up to me and said, Hey, you got to check this out. The separation of compute and storage by EON mode now available on Flash Blade. So, uh and and I believe still the only company that can support that separation and independent scaling both on Prem and in the cloud. So I want to ask, what were the trends and analytical database and cloud led to this partnership? You know, >>realistically, I think what we're seeing is that there's been a kind of a larger shift when it comes to modern analytics platforms towards moving away from the traditional, you know, Hadoop type architecture where we were doing on and leveraging a lot of directors that storage primarily because of the limitations of how that solution was architected. When we start to look at the larger trends towards you know how organizations want to do this type of work on premises, they're looking at solutions that allow them to scale the compute storage pieces independently and therefore, you know, the flash blade platform ended up being a great solution to support America in their transition Tian mode. Leveraging essentially is an S three object store. >>Okay, so let's let's circle back on that you guys in your in your announcement of the flash blade, you make the claim that Flash Blade is the industry's most advanced file and object storage platform ever. That's a bold statement. So defend that What? >>I would like to go beyond that and just say, you know, So we've really kind of looked at this from a standpoint of, you know, as as we've developed Flash Blade as a platform and keep in mind, it's been a product that's been around for over three years now and has been very successful for pure storage. The reality is, is that fast file and fast object as a combined storage platform is a direction that many organizations are looking to go, and we believe that we're a leader in that fast object best file storage place in realistically, which we start to see more organizations start to look at building solutions that leverage cloud storage characteristics. But doing so on Prem for a multitude of different reasons. We've built a platform that really addresses a lot of those needs around simplicity around, you know, making things this year that you know, fast matters for us. Ah, simple is smart. Um we can provide, you know, cloud integrations across the spectrum. And, you know, there's a subscription model that fits into that as well. We fall that that falls into our umbrella of what we consider the modern day takes variance. And it's something that we've built into the entire pure portfolio. >>Okay, so I want to get into the architecture a little bit of flash blade and then understand the fit for, uh, analytic databases generally, but specifically for vertical. So it is a blade, so you got compute and network included. It's a key value store based system. So you're talking about scale out. Unlike, unlike, uh, pure is sort of, you know, initial products which were scale up, Um, and so I want on It is a fabric based system. I want to understand what that all means to take us through the architecture. You know, some of the quote unquote firsts that you guys talk about. So let's start with sort of the blade >>aspect. Yeah, the blade aspect of what we call the flash blade. Because if you look at the actual platform, you have, ah, primarily a chassis with built in networking components, right? So there's ah, fabric interconnect with inside the platform that connects to each one of the individual blades. Individual blades have their own compute that drives basically a pure storage flash components inside. It's not like we're just taking SSD is and plugging them into a system and like you would with the traditional commodity off the shelf hardware design. This is very much an engineered solution that is built towards the characteristics that we believe were important with fast filing past object scalability, massive parallel ization. When it comes to performance and the ability to really kind of grow and scale from essentially seven blades right now to 150 that's that's the kind of scale that customers are looking for, especially as we start to address these larger analytics pools. They are multi petabytes data sets, you know that single addressable object space and, you know, file performance that is beyond what most of your traditional scale up storage platforms are able to deliver. >>Yes, I interviewed cause last September and accelerate, and Christie Pure has been attacked by some of the competitors. There's not having scale out. I asked him his thoughts on that, he said Well, first of all, our flash blade is scale out. He said, Look, anything that adds complexity, you know we avoid. But for the workloads that are associated with flash blade scale out is the right sort of approach. Maybe you could talk about why that is. Well, >>realistically, I think you know that that approach is better when we're starting to work with large, unstructured data sets. I mean, flash blade is unique. The architected to allow customers to achieve superior resource utilization for compute and storage, while at the same time, you know, reducing significantly the complexity that has arisen around this kind of bespoke or siloed nature of big data and analytics solutions. I mean, we're really kind of look at this from a standpoint of you have built and delivered are created applications in the public cloud space of dress, you know, object storage and an unstructured data. And for some organizations, the importance is bringing that on Prem. I mean, we do see about repatriation coming on a lot of organizations as these data egress, charges continue to expand and grow, um, and then organizations that want even higher performance and what we're able to get into the public cloud space. They are bringing that data back on Prem They are looking at from a stamp. We still want to be able to scale the way we scale in the cloud. We still want to operate the same way we operate in the cloud, but we want to do it within control of our own, our own borders. And so that's, you know, that's one of the bigger pieces to that. And we start to look at how do we address cloud characteristics and dynamics and consumption metrics or models? A zealous the benefits and efficiencies of scale that they're able to afford but allowing customers to do that with inside their own data center. >>So you're talking about the trends earlier. You have these cloud native databases that allowed of the scaling of compute and storage independently. Vertical comes in with eon of a lot of times we talk about these these partnerships as Barney deals of you know I love you, You love me. Here's a press release and then we go on or they're just straight, you know, go to market. Are there other aspects of this partnership that they're non Barney deal like, in other words, any specific engineering. Um, you know other go to market programs? Could you talk about that a little bit? Yeah, >>it's it's It's more than just that what we consider a channel meet in the middle or, you know, that Barney type of deal. It's realistically, you know, we've done some first with Veronica that I think, really Courtney, if they think you look at the architecture and how we did, we've brought to market together. Ah, we have solutions. Teams in the back end who are, you know, subject matter experts. In this space, if you talk to joy and the people from vertical, they're very high on our very excited about the partnership because it often it opens up a new set of opportunities for their customers to leverage on mode and get into some of the the nuance task specs of how they leverage the depot depot with inside each individual. Compute node in adjustments with inside their reach. Additional performance gains for customers on Prem and at the same time, for them, that's still tough. The ability to go into that cloud model if they wish to. And so I think a lot of it is around. How do we partner is to companies? How do we do a joint selling motions? How do we show up in and do white papers and all of the traditional marketing aspects that we bring to the market? And then, you know, joint selling opportunities exist where they are, and so that's realistically. I think, like any other organization that's going to market with a partner on MSP that they have, ah, strong partnership with. You'll continue to see us, you know, talking about are those mutually beneficial relationships and the solutions that we're bringing to the market. >>Okay, you know, of course, he used to be a Gartner analyst, and you go to the vendor side now, but it's but it's, but it's a Gartner analyst. You're obviously objective. You see it on, you know well, there's a lot of ways to skin the cat There, there their strengths, weaknesses, opportunities, threats, etcetera for every vendor. So you have you have vertical who's got a very mature stack and talking to a number of the customers out there who are using EON mode. You know there's certain workloads where these cloud native databases makes sense. It's not just the economics of scaling and storage independently. I want to talk more about that. There's flexibility aspect as well. But Vertical really has to play its its trump card, which is Look, we've got a big on premise state, and we're gonna bring that eon capability both on Prem and we're embracing the cloud now. There obviously have been there to play catch up in the cloud, but at the same time, they've got a much more mature stack than a lot of these other cloud native databases that might have just started a couple of years ago. So you know, so there's trade offs that customers have to make. How do you sort through that? Where do you see the interest in this? And and what's the sweet spot for this partnership? You know, we've >>been really excited to build the partnership with vertical A and provide, you know, we're really proud to provide pretty much the only on Prem storage platform that's validated with the yang mode to deliver a modern data experience for our customers together. You know, it's ah, it's that partnership that allows us to go into customers that on Prem space, where I think that there's still not to say that not everybody wants to go there, but I think there's aspects and solutions that worked very well there. But for the vast majority, I still think that there's, you know, the your data center is not going away. And you do want to have control over some of the many of the assets with inside of the operational confines. So therefore, we start to look at how do we can do the best of what cloud offers but on prim. And that's realistically, where we start to see the stronger push for those customers. You still want to manage their data locally. A swell as maybe even worked around some of the restrictions that they might have around cost and complexity hiring. You know, the different types of skills skill sets that are required to bring applications purely cloud native. It's still that larger part of that digital transformation that many organizations are going for going forward with. And realistically, I think they're taking a look at the pros and cons, and we've been doing cloud long enough where people recognize that you know it's not perfect for everything and that there's certain things that we still want to keep inside our own data center. So I mean, realistically, as we move forward, that's, Ah, that better option when it comes to a modern architecture that can do, you know, we can deliver an address, a diverse set of performance requirements and allow the organization to continue to grow the model to the data, you know, based on the data that they're actually trying to leverage. And that's really what Flash was built for. It was built for a platform that could address small files or large files or high throughput, high throughput, low latency scale of petabytes in a single name. Space in a single rack is we like to put it in there. I mean, we see customers that have put 150 flash blades into production as a single name space. It's significant for organizations that are making that drive towards modern data experience with modern analytics platforms. Pure and Veronica have delivered an experience that can address that to a wide range of customers that are implementing uh, you know, particularly on technology. >>I'm interested in exploring the use case. A little bit further. You just sort of gave some parameters and some examples and some of the flexibility that you have, um, and take us through kind of what the customer discussions are like. Obviously you've got a big customer base, you and vertical that that's on Prem. That's the the unique advantage of this. But there are others. It's not just the economics of the granular scaling of compute and storage independently. There are other aspects of take us through that sort of a primary use case or use cases. Yeah, you >>know, I mean, I could give you a couple customer examples, and we have a large SAS analyst company which uses vertical on last way to authenticate the quality of digital media in real time, You know, then for them it makes a big difference is they're doing their streaming and whatnot that they can. They can fine tune the grand we control that. So that's one aspect that that we address. We have a multinational car car company, which uses vertical on flash blade to make thousands of decisions per second for autonomous vehicle decision making trees. You know, that's what really these new modern analytics platforms were built for, um, there's another healthcare organization that uses vertical on flash blade to enable healthcare providers to make decisions in real time. The impact lives, especially when we start to look at and, you know, the current state of affairs with code in the Corona virus. You know, those types of technologies, we're really going to help us kind of get of and help lower invent, bend that curve downward. So, you know, there's all these different areas where we can address that the goals and the achievements that we're trying to look bored with with real time analytics decision making tools like and you know, realistically is we have these conversations with customers they're looking to get beyond the ability of just, you know, a data scientist or a data architect looking to just kind of driving information >>that we're talking about Hadoop earlier. We're kind of going well beyond that now. And I guess what I'm saying is that in the first phase of cloud, it was all about infrastructure. It was about, you know, uh, spin it up. You know, compute and storage is a little bit of networking in there. >>It >>seems like the next new workload that's clearly emerging is you've got. And it started with the cloud native databases. But then bringing in, you know, AI and machine learning tooling on top of that Ah, and then being able to really drive these new types of insights and it's really about taking data these bog this bog of data that we've collected over the last 10 years. A lot of that is driven by a dupe bringing machine intelligence into the equation, scaling it with either cloud public cloud or bringing that cloud experience on Prem scale. You know, across organizations and across your partner network, that really is a new emerging workloads. You see that? And maybe talk a little bit about what you're seeing with customers. >>Yeah. I mean, it really is. We see several trends. You know, one of those is the ability to take a take this approach to move it out of the lab, but into production. Um, you know, especially when it comes to data science projects, machine learning projects that traditionally start out as kind of small proofs of concept, easy to spin up in the cloud. But when a customer wants to scale and move towards a riel you know, derived a significant value from that. They do want to be able to control more characteristic site, and we know machine learning, you know, needs toe needs to learn from a massive amounts of data to provide accuracy. There's just too much data retrieving the cloud for every training job. Same time Predictive analytics without accuracy is not going to deliver the business advantage of what everyone is seeking. You know, we see this. Ah, the visualization of Data Analytics is Tricia deployed is being on a continuum with, you know, the things that we've been doing in the long in the past with data warehousing, data Lakes, ai on the other end. But this way, we're starting to manifest it and organizations that are looking towards getting more utility and better elasticity out of the data that they are working for. So they're not looking to just build apps, silos of bespoke ai environments. They're looking to leverage. Ah, you know, ah, platform that can allow them to, you know, do ai, for one thing, machine learning for another leverage multiple protocols to access that data because the tools are so much Jeff um, you know, it is a growing diversity of of use cases that you can put on a single platform I think organizations are looking for as they try to scale these environment. >>I think it's gonna be a big growth area in the coming years. Gable. I wish we were in Boston together. You would have painted your little corner of Boston orange. I know that you guys have but really appreciate you coming on the cube wall to wall coverage. Two days of the vertical vertical virtual big data conference. Keep it right there. Right back. Right after this short break, Yeah.

hi everybody and welcome to this cube special presentation of the verdict of virtual Big Data conference the cube is running in parallel with day 1 and day 2 of the verdict big data event by the way the cube has been at every single big data event and it's our pleasure to be here in the virtual / digital event as well Gabriel Chapman is here is the director of flash blade product solutions marketing at pure storage gave great to see you thanks for coming on great to see you - how's it going it's going very well I mean I wish we were meeting in Boston at the Encore Hotel but you know and and hopefully we'll be able to meet it accelerate at some point you cheer or one of the the sub shows that you guys are doing the regional shows but because we've been covering that show as well but I really want to get into it and the last accelerate September 2019 pure and Vertica announced a partnership I remember a joint being ran up to me and said hey you got to check this out the separation of Butte and storage by a Eon mode now available on flash played so and and I believe still the only company that can support that separation and independent scaling both on permit in the cloud so Gabe I want to ask you what were the trends in analytical database and cloud that led to this partnership you know realistically I think what we're seeing is that there's been in kind of a larger shift when it comes to modern analytics platforms towards moving away from the the traditional you know Hadoop type architecture where we were doing on and leveraging a lot of direct attached storage primarily because of the limitations of how that solution was architected when we start to look at the larger trends towards you know how organizations want to do this type of work on premises they're looking at solutions that allow them to scale the compute storage pieces independently and therefore you know the flash play platform ended up being a great solution to support Vertica in their transition to Eon mode leveraging is essentially as an s3 object store okay so let's let's circle back on that you guys in your in your announcement of a flash blade you make the claim that flash blade is the industry's most advanced file and object storage platform ever that's a bold statement so defend that it's supposed to yeah III like to go beyond that and just say you know so we've really kind of looked at this from a standpoint of you know as as we've developed flash blade as a platform and keep in mind it's been a product that's been around for over three years now and has you know it's been very successful for pure storage the reality is is that fast file and fast object as a combined storage platform is a direction that many organizations are looking to go and we believe that we're a leader in that fast object of best file storage place in realistically would we start to see more organizations start to look at building solutions that leverage cloud storage characteristics but doing so on prem or multitude different reasons we've built a platform that really addresses a lot of those needs around simplicity around you know making things assure that you know vast matters for us simple is smart we can provide you know cloud integrations across the spectrum and you know there's a subscription model that fits into that as well we fall that that falls into our umbrella of what we consider the modern data experience and it's something that we've built into the entire pure portfolio okay so I want to get into the architecture a little bit of Flash blade and then better understand the fit for analytic databases generally but specifically Vertica so it is a blade so you got compute and a network included it's a key value store based system so you're talking about scale out unlike unlike viewers sort of you know initial products which were scale up and so I want to under in as a fabric base system I want to understand what that all mean so take us through the architecture you know some of the quote-unquote firsts that you guys talk about so let's start with sort of the blade aspect yeah the blade aspect meaning we call it a flash blade because if you look at the actual platform you have a primarily a chassis with built in networking components right so there's a fabric interconnect with inside the platform that connects to each one of the individual blades the individual blades have their own compute that drives basically a pure storage flash components inside it's not like we're just taking SSDs and plugging them into a system and like you would with the traditional commodity off-the-shelf hardware design this is a very much an engineered solution that is built towards the characteristics that we believe were important with fast file and fast object scalability you know massive parallelization when it comes to performance and the ability to really kind of grow and scale from essentially seven blades right now to a hundred and fifty that's that's the kind of scale that customers are looking for especially as we start to address these larger analytic spools they have multi petabyte datasets you know that single addressable object space and you know file performance that is beyond what most of your traditional scale-up storage platforms are able to deliver yes I interviewed cause last September and accelerate and and Christopher's been you know attacked by some of the competitors is not having a scale out I asked him his thoughts on that he said well first of all our Flash blade is scale-out and he said look anything that that that adds the complexity you know we avoid but for the workloads that are associated with Flash blade scale-out is the right sort of approach maybe you could talk about why that is well you know realistically I think you know that that approach is better when we're starting to learn to work with large unstructured data sets I mean flash plays uniquely architected to allow customers to achieve you know a superior resource utilization for compute and storage well at the same time you know reducing significantly the complexity that is arisen around these kind of bespoke or siloed nature of big data and analytic solutions I mean we really kind of look at this from a standpoint of you have built and delivered or created applications in the public cloud space that address you know object storage and and unstructured data and and for some organizations the importance is bringing that on Prem I mean we do seek repatriation that coming on on for a lot of organizations as these data egress charges continue to expand and grow and then organizations that want even higher performance in the what we're able to get into the public cloud space they are bringing that data back on Prem they are looking at from a standpoint we still want to be able to scale the way we scale on the cloud we still want to operate the same way we operate in the cloud but we want to do it within control of our own you know our own borders and so that's you know that's one of the bigger pieces to that is we start to look at how do we address cloud characteristics and dynamics and consumption metrics or models as well as the benefits and efficiencies of scale that they're able to afford but allowing customers that do that with inside their own data center yes are you talking about the trends earlier you had these cloud native databases that allowed the scaling of compute and storage independently of Vertica comes in with eon of a lot of times we talk about these these partnerships as Barney deals of you know I love you you love me here's a press release and then we go on or they're just straight you know go to market are there other aspects of this partnership that are that are non Barney deal like in other words any specific you know engineering you know other go to market programs can you talk about that a little bit yeah it's it's it's more than just you know I then what we consider a channel meet in the middle or you know that Barney type of deal it's the realistically you know we've done some first with Vertica that I think are really important if they think you look at the architecture and how we do have we've brought this to market together we have solutions teams in the back end who are you know subject matter experts in this space if you talk to joy and the people from vertigo they're very high on or very excited about the partnership because it often it opens up a new set of opportunities for their customers to to leverage Eon mode and you know get into some of the the nuanced aspects of how they leverage the depot for Depot with inside each individual compute node and adjustments with inside there I reach additional performance gains for customers on Prem and at the same time for them there's still the ability to go into that cloud model if they wish to and so I think a lot of it is around how do we partner as two companies how do we do a joint selling motions you know how do we show up and and you know do white papers and all of the the traditional marketing aspects that we bring devote to the market and then you know joint selling opportunities as exists where they are and so that's realistically I think like any other organization that's going to market with a partner or an ISP that they have a strong partnership with you'll continue to see us you know talking about our chose mutually beneficial relationships and the solutions that we're bringing to the market okay you know of course he used to be a Gartner analyst and you go over to the vendor side now but as but as it but as a gardener analyst you're obviously objective you see it all you know well there's a lot of ways to skin a cat there are there are there are strengths weaknesses opportunities threats etc for every vendor so you have you have Vertica who's got a very mature stack and and talking to a number of the customers out there we're using Eon mode you know there's certain workloads where these cloud native databases make sense it's not just the economics of scaling compute and storage independently I want to talk more about that there's flexibility aspects as well but Vertica really you know has to play its trump card which is look we've got a big on-premise state and we're gonna bring that you know Eon capability both on Prem and we're embracing the cloud now they're obviously you have to they had to play catch-up in the cloud but at the same time they've got a much more mature stack than a lot of these other you know cloud native databases that might have just started a couple of years ago so you know so there's trade-offs that customers have to make how do you sort through that where do you see the interest in this and and and what's the sweet spot for this partnership you know we've been really excited to build the partnership with Vertica and we're providing you know we're really proud to provide pretty much the only on Prem storage platform that's validated with the vertical yawn mode to deliver a modern data experience for our customers together you know it's it's that partnership that allows us to go into customers that on Prem space where I think that they're still you know not to say that not everybody wants to go the cloud I think there's aspects and solutions that work very well there but for the vast majority I still think that there's you know the your data center is not going away and you do want to have control over some of the many of the different facets with inside the operational confines so therefore we start to look at how do we can do the best of what cloud offers but on Prem and that's realistically where we start to see the stronger push for those customers who still want to manage their data locally as well as maybe even work around some of the restrictions that they might have around cost and complexity hiring you know the different types of skills skill sets that are required to bring you know applications purely cloud native it's still that larger part of that digital transformation that many organizations are going for going forward with and realistically I think they're taking a look at the pros and cons and we've been doing cloud long enough for people recognize that you know it's not perfect for everything and that there's certain things that we still want to keep inside our own data center so I mean realistically as we move forward that's that that better option when it comes to a modern architecture they can do it you know we can deliver and address a diverse set of performance requirements and allow the organization to continue to grow the model to the data you know based on the data that they're actually trying to leverage and that's really what flash Wood was built or it was built for a platform that can address small files or large files or high throughput high throughput low latency scale to petabytes in a single namespace in a single rack as we like to put it in there I mean we see customers that have put you know 150 flash blades into production as a single namespace it's significant for organizations that are making that drive towards modern data experience with modern analytics platforms pure and Vertica have delivered an experience that can address that to a wide range of customers that are implementing you know the verdict technology I'm interested in exploring the use case a little bit further you just sort of gave some parameters and some examples and some of the flexibility that you have in but take us through kind of what the discuss the customer discussions are like obviously you've got a big customer base you and Vertica that that's on prem that's the the the unique advantage of this but there are others it's not just the economics of the the granular scaling of compute and storage independently there are other aspects so to take us through that sort of a primary use case or use cases yeah you know I mean I can give you a couple customer examples and we have a large SAS analyst company which uses verdict on flash play to authenticate the quality of digital media in real time and you know then for them it makes a big difference is they're doing they're streaming and whatnot that they can they can fine tune and grandly control that so that's one aspect that that we get address we have a multi national car con company which uses verdict on flash blade to make thousands of decisions per second for autonomous vehicle decision-making trees that you know that's what really these new modern analytics platforms were built or there's another healthcare organization that uses Vertica on flash blade to enable healthcare providers to make decisions in real time the impact Ives especially when we start to look at and you know the current state of affairs with Kovac in the coronavirus you know those types of technologies are really going to help us kind of get love and and help lower and been you know bend that curve downward so you know there's all these different areas where we can address the goals and the achievements that we're trying to look bored with with real-time analytic decision making tools like Berta and you know realistically as we have these conversations with customers they're looking to get beyond the ability of just you know you know a data scientist or a data architect looking to just kind of drive in information we were talking about Hadoop earlier we're kind of going well beyond that now and I guess what I'm saying is that in the first phase of cloud it was all about infrastructure it was about you know spinning up you know compute and storage a little bit of networking in there seems like the the a next a new workload that's clearly emerging is you've got and it started with the cloud databases but then bringing in you know AI and machine learning tooling on top of that and then being able to really drive these new types of insights and it's really about taking data these bogs this bog of data that we've collected over the last 10 years a lot of that you know driven by Hadoop bringing machine intelligence into the equation scaling it with either cloud public cloud or bringing that cloud experience on prams scale you know across your organizations and across your partner network that really is a new emerging work load do you see that and maybe talk a little bit about you know what you're seeing with customers yeah I mean it really is we see several trends you know one of those is the ability to take a take this approach to move it out of the lab but into production you know especially when it comes to you know data science projects machine learning projects that traditionally start out as kind of small proofs of concept easy to spin up in the cloud but when a customer wants to scale and move towards a real you know it derived a significant value from that they do want to be able to control more characteristics right and we know machine learning you know needs to needs to learn from a massive amounts of data to provide accuracy there's just too much data to retrieve in the cloud for every training job at the same time predictive analytics without accuracy is not going to deliver the business advantage of what everyone is seeking you know we see this the visualization of data analytics is traditionally deployed as being on a continuum with you know the things that we've been doing in the long you know in the past you know with data warehousing data lakes AI on the other end but but this way we're starting to manifest it in organizations that are looking towards you know getting more utility and better you know elasticity out of the data that they are working for so they're not looking to just build ups you know silos of bespoke AI environments they're looking to leverage you know a platform that can allow them to you know do a I for one thing machine learning for another leverage multiple protocols to access that data because the tools are so much different you know it is a growing diversity of of use cases that you can put on a single platform I think organizations are looking for as they try to scale these environments I think there's gonna be a big growth area in the coming years gay ball I wish we were in Boston together you would have painted your little corner of Boston Orange I know that you guys are sharing but I really appreciate you coming on the cube wall-to-wall coverage two days at the vertical Vertica virtual big data conference keep you right there but right back right after this short break [Music]

hi everybody and welcome to this cube special presentation of the verdict of virtual Big Data conference the cube is running in parallel with day 1 and day 2 of the verdict big data event by the way the cube has been at every single big data event and it's our pleasure to be here in the virtual / digital event as well Gabriel Chapman is here is the director of flash blade product solutions marketing at pure storage gave great to see you thanks for coming on great to see you - how's it going it's going very well I mean I wish we were meeting in Boston at the Encore Hotel but you know and and hopefully we'll be able to meet it accelerate at some point you cheer or one of the the sub shows that you guys are doing the regional shows but because we've been covering that show as well but I really want to get into it and the last accelerate September 2019 pure and Vertica announced a partnership I remember a joint being ran up to me and said hey you got to check this out the separation of Butte and storage by a Eon mode now available on flash played so and and I believe still the only company that can support that separation and independent scaling both on permit in the cloud so Gabe I want to ask you what were the trends in analytical database and cloud that led to this partnership you know realistically I think what we're seeing is that there's been in kind of a larger shift when it comes to modern analytics platforms towards moving away from the the traditional you know Hadoop type architecture where we were doing on and leveraging a lot of direct attached storage primarily because of the limitations of how that solution was architected when we start to look at the larger trends towards you know how organizations want to do this type of work on premises they're looking at solutions that allow them to scale the compute storage pieces independently and therefore you know the flash play platform ended up being a great solution to support Vertica in their transition to Eon mode leveraging is essentially as an s3 object store okay so let's let's circle back on that you guys in your in your announcement of a flash blade you make the claim that flash blade is the industry's most advanced file and object storage platform ever that's a bold statement so defend that it's supposed to yeah III like to go beyond that and just say you know so we've really kind of looked at this from a standpoint of you know as as we've developed flash blade as a platform and keep in mind it's been a product that's been around for over three years now and has you know it's been very successful for pure storage the reality is is that fast file and fast object as a combined storage platform is a direction that many organizations are looking to go and we believe that we're a leader in that fast object of best file storage place in realistically would we start to see more organizations start to look at building solutions that leverage cloud storage characteristics but doing so on prem or multitude different reasons we've built a platform that really addresses a lot of those needs around simplicity around you know making things assure that you know vast matters for us simple is smart we can provide you know cloud integrations across the spectrum and you know there's a subscription model that fits into that as well we fall that that falls into our umbrella of what we consider the modern data experience and it's something that we've built into the entire pure portfolio okay so I want to get into the architecture a little bit of Flash blade and then better understand the fit for analytic databases generally but specifically Vertica so it is a blade so you got compute and a network included it's a key value store based system so you're talking about scale out unlike unlike viewers sort of you know initial products which were scale up and so I want to under in as a fabric base system I want to understand what that all mean so take us through the architecture you know some of the quote-unquote firsts that you guys talk about so let's start with sort of the blade aspect yeah the blade aspect meaning we call it a flash blade because if you look at the actual platform you have a primarily a chassis with built in networking components right so there's a fabric interconnect with inside the platform that connects to each one of the individual blades the individual blades have their own compute that drives basically a pure storage flash components inside it's not like we're just taking SSDs and plugging them into a system and like you would with the traditional commodity off-the-shelf hardware design this is a very much an engineered solution that is built towards the characteristics that we believe were important with fast file and fast object scalability you know massive parallelization when it comes to performance and the ability to really kind of grow and scale from essentially seven blades right now to a hundred and fifty that's that's the kind of scale that customers are looking for especially as we start to address these larger analytic spools they have multi petabyte datasets you know that single addressable object space and you know file performance that is beyond what most of your traditional scale-up storage platforms are able to deliver yes I interviewed cause last September and accelerate and and Christopher's been you know attacked by some of the competitors is not having a scale out I asked him his thoughts on that he said well first of all our Flash blade is scale-out and he said look anything that that that adds the complexity you know we avoid but for the workloads that are associated with Flash blade scale-out is the right sort of approach maybe you could talk about why that is well you know realistically I think you know that that approach is better when we're starting to learn to work with large unstructured data sets I mean flash plays uniquely architected to allow customers to achieve you know a superior resource utilization for compute and storage well at the same time you know reducing significantly the complexity that is arisen around these kind of bespoke or siloed nature of big data and analytic solutions I mean we really kind of look at this from a standpoint of you have built and delivered or created applications in the public cloud space that address you know object storage and and unstructured data and and for some organizations the importance is bringing that on Prem I mean we do seek repatriation that coming on on for a lot of organizations as these data egress charges continue to expand and grow and then organizations that want even higher performance in the what we're able to get into the public cloud space they are bringing that data back on Prem they are looking at from a standpoint we still want to be able to scale the way we scale on the cloud we still want to operate the same way we operate in the cloud but we want to do it within control of our own you know our own borders and so that's you know that's one of the bigger pieces to that is we start to look at how do we address cloud characteristics and dynamics and consumption metrics or models as well as the benefits and efficiencies of scale that they're able to afford but allowing customers that do that with inside their own data center yes are you talking about the trends earlier you had these cloud native databases that allowed the scaling of compute and storage independently of Vertica comes in with eon of a lot of times we talk about these these partnerships as Barney deals of you know I love you you love me here's a press release and then we go on or they're just straight you know go to market are there other aspects of this partnership that are that are non Barney deal like in other words any specific you know engineering you know other go to market programs can you talk about that a little bit yeah it's it's it's more than just you know I then what we consider a channel meet in the middle or you know that Barney type of deal it's the realistically you know we've done some first with Vertica that I think are really important if they think you look at the architecture and how we do have we've brought this to market together we have solutions teams in the back end who are you know subject matter experts in this space if you talk to joy and the people from vertigo they're very high on or very excited about the partnership because it often it opens up a new set of opportunities for their customers to to leverage Eon mode and you know get into some of the the nuanced aspects of how they leverage the depot for Depot with inside each individual compute node and adjustments with inside there I reach additional performance gains for customers on Prem and at the same time for them there's still the ability to go into that cloud model if they wish to and so I think a lot of it is around how do we partner as two companies how do we do a joint selling motions you know how do we show up and and you know do white papers and all of the the traditional marketing aspects that we bring devote to the market and then you know joint selling opportunities as exists where they are and so that's realistically I think like any other organization that's going to market with a partner or an ISP that they have a strong partnership with you'll continue to see us you know talking about our chose mutually beneficial relationships and the solutions that we're bringing to the market okay you know of course he used to be a Gartner analyst and you go over to the vendor side now but as but as it but as a gardener analyst you're obviously objective you see it all you know well there's a lot of ways to skin a cat there are there are there are strengths weaknesses opportunities threats etc for every vendor so you have you have Vertica who's got a very mature stack and and talking to a number of the customers out there we're using Eon mode you know there's certain workloads where these cloud native databases make sense it's not just the economics of scaling compute and storage independently I want to talk more about that there's flexibility aspects as well but Vertica really you know has to play its trump card which is look we've got a big on-premise state and we're gonna bring that you know Eon capability both on Prem and we're embracing the cloud now they're obviously you have to they had to play catch-up in the cloud but at the same time they've got a much more mature stack than a lot of these other you know cloud native databases that might have just started a couple of years ago so you know so there's trade-offs that customers have to make how do you sort through that where do you see the interest in this and and and what's the sweet spot for this partnership you know we've been really excited to build the partnership with Vertica and we're providing you know we're really proud to provide pretty much the only on Prem storage platform that's validated with the vertical yawn mode to deliver a modern data experience for our customers together you know it's it's that partnership that allows us to go into customers that on Prem space where I think that they're still you know not to say that not everybody wants to go the cloud I think there's aspects and solutions that work very well there but for the vast majority I still think that there's you know the your data center is not going away and you do want to have control over some of the many of the different facets with inside the operational confines so therefore we start to look at how do we can do the best of what cloud offers but on Prem and that's realistically where we start to see the stronger push for those customers who still want to manage their data locally as well as maybe even work around some of the restrictions that they might have around cost and complexity hiring you know the different types of skills skill sets that are required to bring you know applications purely cloud native it's still that larger part of that digital transformation that many organizations are going for going forward with and realistically I think they're taking a look at the pros and cons and we've been doing cloud long enough for people recognize that you know it's not perfect for everything and that there's certain things that we still want to keep inside our own data center so I mean realistically as we move forward that's that that better option when it comes to a modern architecture they can do it you know we can deliver and address a diverse set of performance requirements and allow the organization to continue to grow the model to the data you know based on the data that they're actually trying to leverage and that's really what flash Wood was built or it was built for a platform that can address small files or large files or high throughput high throughput low latency scale to petabytes in a single namespace in a single rack as we like to put it in there I mean we see customers that have put you know 150 flash blades into production as a single namespace it's significant for organizations that are making that drive towards modern data experience with modern analytics platforms pure and Vertica have delivered an experience that can address that to a wide range of customers that are implementing you know the verdict technology I'm interested in exploring the use case a little bit further you just sort of gave some parameters and some examples and some of the flexibility that you have in but take us through kind of what the discuss the customer discussions are like obviously you've got a big customer base you and Vertica that that's on prem that's the the the unique advantage of this but there are others it's not just the economics of the the granular scaling of compute and storage independently there are other aspects so to take us through that sort of a primary use case or use cases yeah you know I mean I can give you a cup of customer examples and we have a large SAS analyst company which uses verdict on flash play to authenticate the quality of digital media in real time and you know then for them it makes a big difference is they're doing they're streaming and whatnot that they can they can fine tune and grandly control that so that's one aspect that we get address we have a multi national car con company which uses verdict on flash blade to make thousands of decisions per second for autonomous vehicle decision-making trees that you know that's what really these new modern analytics platforms were built or there's another healthcare organization that uses Vertica on flash blade to enable healthcare providers to make decisions in real time the impact Ives especially when we start to look at and you know the current state of affairs with Kovac in the coronavirus you know those types of technologies are really going to help us kind of get love and and help lower and been you know bend that curve downward so you know there's all these different areas where we can address the goals and the achievements that we're trying to look bored with with real-time analytic decision making tools like Berta and you know realistically as we have these conversations with customers they're looking to get beyond the ability of just you know you know a data scientist or a data architect looking to just kind of drive in information we were talking about Hadoop earlier we're kind of going well beyond that now and I guess what I'm saying is that in the first phase of cloud it was all about infrastructure it was about you know spinning up you know compute and storage a little bit of networking in there seems like the the a next a new workload that's clearly emerging is you've got and it started with the cloud databases but then bringing in you know AI and machine learning tooling on top of that and then being able to really drive these new types of insights and it's really about taking data these bogs this bog of data that we've collected over the last 10 years a lot of that you know driven by Hadoop bringing machine intelligence into the equation scaling it with either cloud public cloud or bringing that cloud experience on prams scale you know across your organizations and across your partner network that really is a new emerging work load do you see that and maybe talk a little bit about you know what you're seeing with customers yeah I mean it really is we see several trends you know one of those is the ability to take a take this approach to move it out of the lab but into production you know especially when it comes to you know data science projects machine learning projects that traditionally start out as kind of small proofs of concept easy to spin up in the cloud but when a customer wants to scale and move towards a real you know it derived a significant value from that they do want to be able to control more characteristics right and we know machine learning you know needs to needs to learn from a massive amounts of data to provide accuracy there's just too much data to retrieve in the cloud for every training job at the same time predictive analytics without accuracy is not going to deliver the business advantage of what everyone is seeking you know we see this the visualization of data analytics is traditionally deployed as being on a continuum with you know the things that we've been doing in the long you know in the past you know with data warehousing data lakes AI on the other end but but this way we're starting to manifest it in organizations that are looking towards you know getting more utility and better you know elasticity out of the data that they are working for so they're not looking to just build ups you know silos of bespoke AI environments they're looking to leverage you know a platform that can allow them to you know do a I for one thing machine learning for another leverage multiple protocols to access that data because the tools are so much different you know it is a growing diversity of of use cases that you can put on a single platform I think organizations are looking for as they try to scale these environments I think there's gonna be a big growth area in the coming years gay ball I wish we were in Boston together you would have painted your little corner of Boston Orange I know that you guys are sharing but I really appreciate you coming on the cube wall-to-wall coverage two days at the vertical Vertica virtual big data conference keep you right there but right back right after this short break [Music]

>> Live from Las Vegas, it's theCUBE covering VMworld 2018. Brought to you by VMware and its ecosystem partners. >> Welcome to theCUBE. I'm Lisa Martin with Justin Warren on day one of VMworld 2018. This is the twentieth anniversary of VMware. Lots of momentum this morning kicking things off. Justin and I are happy to be joined by some folks from NetApp. We have Nancy Hart, the Head of Marketing for Cloud Infrastructure. >> Good afternoon. >> Welcome to theCUBE. >> Thank you Julie, it's so great to be here. And an alumni, Gabe Chapman. I love your Twitter handle @bacon_is_king. Senior Manager of NetApp HCI. Hey, Gabe. >> Hi, how are you doing? >> Good. Guys, lots of momentum. Pat Gelsinger was probably one of my favorite keynotes cause he's really energetic. He even went full-in with his faux tap this morning. I was impressed. >> Impressive. >> You guys have some news. >> Yes. >> Tell us about what's new with NetApp and VMware today. >> Fantastic, exciting times at NetApp these days. NetApp is really focused on becoming the data authority for hybrid cloud. Part of that is what we're excited to announce today here at VMworld, is a NetApp-verified architecture for VMware private cloud for HCI. What you heard today in Pat's keynote was a lot about connection on-premises private clouds with hyperscalers public clouds. That's what we're doing in our partnership with VMware here and this validated architecture for private clouds. Exciting news for us. In addition, we're also really be thrilled to be announcing new storage nodes for our NetApp HCI product and SolidFire product, as well. Lots going on today. >> Wow, that's really cool. >> Gabe, you've been in the field a lot. What are some of the things that you're hearing? Some of the signage around here is about VMware's making things possible, making momentum possible. What are some of the things that you're seeing in the field in terms of customer's momentum? Leveraging HCI from NetApp to drive new business models, new revenue streams. >> I think one of the things I see commonly is that the hyperconverge as a platform has been around for about six, seven years now. Customers are seeing that some of the first generational approaches have got them to a certain level in terms of addressing simplicity and kind of that turnkey infrastructure stack, but where they would like to go next is more cloud integrated, more scalability, more enterprise class or enterprise scale technology. Therefore, they're kind of looking at the NetApp HCI product and the architecture that we've brought to market, and seeing the potential to not only do things on-premise that they'd normally do in terms of a infrastructure platform but also move in to new services. How do we integrate with existing investments that they've had? How do we become connected into the hybrid cloud model with the hyperscalers themselves and really push towards a all-encompassing cloud infrastructure platform other than just a box. >> Yeah, one of the things I noticed in the keynote today that, I think, relates to that, and I'm interested to hear, Nancy and Gabe, a little bit more about what customers are doing here, because it seems that the idea of it must be all cloud or all on-site, that's gone away now. It's very much hybrid cloud world, multi cloud world, where customers have choice. Are you hearing that from customers? Clearly, there seems to be some demand here because we've seen the change in messaging. >> Absolutely, and I think what you're seeing is customers want the option to take advantage of all the resources. Regardless if those resources are on-premises or in public clouds, and that's what we're doing here at NetApp with our own HCI solution. As the market evolves under our feet, Gabe talked about those first generation vendors weren't quite enough, that our customers are choosing NetApp cause they want more then what they can get from those first generation vendors. What you really want to see is that convergence continues to march on and that there is more to collapse into this stack, particularly that connection up into the public cloud. Customers are definitely looking today, they're making buying decisions today based on that option. >> Right, and clearly, there's lots of customers who have substantial investment already in NetApp so being able to use what've you already got and extend it with a vendor that you're already familiar with and you know how it works. There's a lot of value there. >> We're a trusted vendor. NetApp is a trusted enterprise vendor with the reliability and customers can come to us with confidence and choose NetApp with confidence. >> We were with you guys at SAP just a couple months ago at the beginning of the summer and #datadriven was everywhere, I'm seeing it in Twitter. We often hear many things about data is power, data is currency, data is fuel. Data is all of those things if it can be harnessed and acted upon in real time. How does NetApp HCI, what are some of the differentiators? Obviously, we talked about the trusted partnership, but how does NetApp help customers actually live a data-driven life within their organization? >> I think a lot of times it starts with understanding where your data lives. How you manage it, manipulate it, and secure it. We have things like GPDR that comes (mumbles). All the sudden, everybody's scrambling to come up with a solution or a reference architecture or some way that integrates with it. I think, naturally, NetApp being the product technology company that it's been and it's lived and breathed data all its life. We understand our customer's unique requirements around governance, around security, around mobility, and we've built technologies that don't lock you into any one mode of consumption. If you bought a filer, if you bought an HCI system, if you bought an object store platform, the data fabric piece is the glue that binds and allows data mobility and portability across multiple platforms. Not only from the edge to the core, but also to the cloud and kind of gives you that larger, bigger picture. We believe that as we start to see this transition, especially edge computing, especially as we look at things like NVMe over fabrics and getting in to new levels and also services that we are delivering across the hyperscalers. A cohesive picture and story around where your data lives, how you manage it, and who can access it is empowering customers to make their transition into the multi cloud space. >> Right, clearly that transition, I think, is what people weren't really understanding three or four years ago. It was like enterprises aren't going to be there in one spot. You can't just turn it on in five seconds, these things take time. >> (mumbles) flipped, yeah. >> With our data fabric we're able to cover the entire NetApp portfolio from edge to core to cloud. As you say, enterprises and different departments in those enterprises will make their own transition and go down their own journey of digital transformation in their own time. NetApp can really be that trusted partner for all these enterprises. >> With so much choice comes, I think, inherently a lot of complexity. I thought they did a great job this morning in the keynote, Pat Gelsinger and team, of really talking about their announcements, what VMware has done in their history pretty clearly. I can imagine from a customer's perspective, if it's an enterprise organization who doesn't want to get Uber-ized, they probably don't know where to start. Talk to us about sort of the business-level conversations that NetApp has with not just your existing customers who know they can come to NetApp to trust you but also some of those maybe newer businesses or newer enterprise businesses to NetApp. How can they come to you and say help us understand? We probably have, what did they say this morning? The average customer's eight clouds. How do you help them to sort of digest that, embrace it, and be able to maximize it so that their data can be available as soon as they need it? >> What it is is data's at the heart of the enterprise and how people help customers change their world with data, but there has to be a direct business outcome for that. When enterprise customers learn to mine the value of their data they can really build new revenue streams, they can create new touchpoints with their own customers to drive their businesses. For example, one of our early NetApp HCI customers was down in Australia. A company called Consatel, a service provider down in Australia. They were really struggling to set up new businesses and new services to their own customer base. When the conversation, when they worked with NetApp what they were able to do was deploy new services three times faster over their last vendor. Think about what that did for their top line. If this company Consatel could deploy new services, new revenue opportunities three times faster. >> Blowing their competitors out of the water. >> Blowing their competitors out of the water. That's a business-level conversation. This is not a conversation about technology. Yes, under the covers, there's some amazing, fantastic technology, but it has to serve the business. Consatel has now been so successful with NetApp HCI that they now are expanding into brand new geo and geo regions and bringing new services to a whole new set of customers and a whole new customer base working with us. >> That's what I'm hearing in the conversations that I have with customers. I'm interested to hear from yourself and Gabe as to whether you're hearing this across the board. You've got one example here of customers who are concerned more with additional revenues. New revenue streams, new ways of making money top line and not so much about cost savings. That was something that was being, we were concentrating on that maybe three or four years ago. That seems to have been de-emphasized now and people are much more interested in seeking out new ways to use things. New sources of revenue and focusing on top line. Is that something that you're seeing across the board or is that only leading edge companies that are looking at that? >> We see it across the board, I think, with a lot of customers across many different verticals. For instance, Children's Mercy Hospital bought our NetApp HCI product for a virtual desktop implementation and they did so for a lot of reasons. One of them being the traditional TCO/ROI discussion. But also allows them to provide a platform that isn't just a silo of resources because of the unique aspects and differentiation that we have on our platform. We're able to go and do mixed workloads and do consolidation so they're realizing savings and gains across collapsing silos, bringing multiple applications on the same, common infrastructure. The same way they would've gone and swiped their credit card at Amazon. When you do that, you don't care if you're putting a SQL database, an Oracle or what not. They're going to give you the resource that you need. We want to mimic that locally on-prem for customers. Then, also have that integration with cloud services. If we're building a cloud service that runs on Amazon or Google, or if we're integrating with VMware as it runs on AWS or whatever, we want to be able to extend those services from local on-premises environments into the cloud and back based on that. I think that's really where the value is. There's no turnkey public cloud in a hybrid cloud integration piece. It's a journey and you have to analyze all the applications and the way you've done business. NetApp, having been working in the enterprise space as a trusted advisor for such a long time, we understand the customer's needs. We've been in the cloud space for a number of years already and we kind of understand that space. We're bridging the gap at the data level and helping to expand that more at the infrastructure level as well and as we branch into new services as time goes on. >> You've got that challenge of every customer being different but there's also trends that are common across the industry and NetApp being the size and having the history that it does, you've seen all of these things before and you know that yes, this is unique to you as a customer, but also we've seen this in other customers. This would be of value to you and you can bring that to those customers. >> Not only that, we have this product called Active IQ and it tends to be a service and support and monitoring application but, like you said, we have a very large customer base and using features and functionalities in AI we're able to use the data that we get from Active IQ as a community wisdom in effect and then make suggestions to those users as well. NetApp does have a very large install base. What can we learn from that install base, how can we help existing customers run their operations better with that community wisdom? >> We've always referred to it as actionable intelligence for your data. We've all played Tetris as a kid, it's playing Tetris with your data, Tetris with your workloads, and making sure that they all line up so that you get all four blocks break at the same time and get the high score. It's really taking and really, truly mining your infrastructure, mining your workloads and your information, and making sure that you're getting the most effective resource utilization that you possibly can. Across not just virtual machine workloads but also data workloads and understanding what you have on the floor versus what you need six months from now to one year from now. That Active IQ platform is really an integral part to really understanding customer's data resource utilization, etc. >> As someone who has played storage Tetris, any help that you can do is very, very welcome. >> I got to bring that back. That's the second reference I've heard to that in the last couple days. One of the things that Pat Gelsinger and team talked about this morning during the general session was superpowers and the need to enable enterprises to be able to harness their superpowers and maximize AI, machine learning, IoT, the edge. How was NetApp and VMware uniquely positioned to help your customers be able to take that actionable intelligence, Gabe, that you mentioned on that data to drive the new business models and revenue streams? >> I think our superpower would be, information is power, so that's our superpower is being data-driven and understanding how we take the customer's data, leverage it to its most effective use, and allocate it and protect it properly. There's a whole bunch of different areas around what we're doing there. Ours would be understanding data, understanding how customers want to use it, and what kind of information they want to extract from it. I'll have to come up with a fancy term for, maybe data thrivers is my superpower. That could be definitely one part of it. >> You could make a logo out of that. >> That sounds pretty good. >> The Thriver. >> The Thriver, I like it. >> We're data thrivers. >> I like it. >> I think so. >> NetApp has been a partner of VMware's for a very long time. You have a large ecosystem of partners, as well. What you guys announced today, talk to us about some of the benefits or really the opportunities that's going to give to NetApp's channel partners. >> There's a lot of opportunity here for our channel partners. As our customers take this journey, they're going to turn to their trusted advisors, their partners, to help them take that journey as well. What we've done here with what we announced with the VMware private cloud for HCI, this is a significant opportunity for our channel partners to work with their customers and take them down that path to be that data thriver. To harness that superpower. New opportunities for all. Customers need someone to help them show the way and channel partners are really the community to do that. >> For those channel partners who are keen to go and do this, how should they engage with you? How should they start talking to NetApp about helping their customers to go down this journey? >> Honestly, we're making the announcement this week. That's the first step is come by our booths. >> It's a thing, yeah. >> If they're here, obviously. We have a very large channel organization. We have outreach, we'll have training, we'll have, the path to hybrid clouds starts with turnKey private cloud and that's kind of what we've done here. We're working on that turnkey private cloud with our partner VMware and NetApp together to kind of facilitate that first step. Then we go out and work with our channel partner organizations to find the customers that want to go down that path. Then they can bring their additional add-on to it. There's a lot of opportunity to go out and really push and help customers make this transition between the two different worlds and obviously we can go to netapp.com and come and take a look. We have plenty of information there, too. >> Just as we wrap up here, I'm curious, Nancy, to get your perspective, from a cloud infrastructure perspective or vision, the announcements that VMware made today. Big news with AWS. Launched that last year. Talked about a lot of expansion going to apache. A lot of work in Australia. >> Yep. >> What does that as well as some other product enhancements they announced today, what does that mean to NetApp? >> I think for NetApp and for our customers, cause really let's stay focused on NetApp's customers, some of the announcements you saw Pat make today provides new options, new opportunities for NetApp's customers globally. As there's these new features, new functionalities to that turnkey solution for private cloud, what you saw is VMware expanding that relationship with AWS just gives new options and new opportunities. >> Hopefully, people can go and maybe by tomorrow get a data thriver pin or sticker. >> Going to have to run out to Kinko's real quick and make some stickers. >> Maybe print it on some bacon. >> Actually, I think we have pretzel necklaces in our booth to go for the beer crawl. >> Oh wow. What time is that? >> Soon, not soon enough. >> Nancy and Gabe, thanks so much for stopping by theCUBE and chatting with Justin and me. Very exciting to hear NetApp's continued transformation and what you're helping customers achieve. >> Thank you for your time. >> Thank you. >> Thank you very much. >> We want to thank you for watching theCUBE. For Justin Warren, I'm Lisa Martin. We're at VMworld, day one, stick around we'll be right back. (electronic tones)

(logo snapping) >> Hey, welcome back everybody. Jeff Frick here with the Cube. We're in downtown San Francisco with International Women's Day. Stuff going on all around the world. Check social media. It's pretty exciting and definitely a movement. We decided to come down to the Accenture event. 400 people here at the hotel, Nikko. A lot of panels, a lot of great content, and we're excited to have our next quests. We have Paul Chapman. He's the CIO of Box. Paul, it's great to see you. And J.D. Sassaman, Senior Workshop Manager at Autodesk for the Pier 9 Tech Center. So J.D. jump in. I have to ask, J.D. What is the Pier 9 Tech Center? >> Yeah, it's a fantastic place, right here in downtown San Francisco. We have a wood shop, metal shop, robot arms, digital fabrication, rapid prototyping. It's literally a physical place to fabricate, prototype, iterate, and research within Autodesk. >> It's so cool. I don't think most people think of Autodesk as, you think as a software company, but not necessarily that you can touch, shave, >> Yeah. >> and drill, you know play with toys. >> Absolutely. It's where the rubber hits the road. You can design all day but if you can't make it, and we can't test what the customers are doing with the software to valid that we're making software that drives that thing getting build in the world, then we missing something. So there's where these centers, you know, they help Autodesk be authentically in touch with what our clients are doing. >> So part of today's topic was to put out this report, there's forty kind of factors that influence people, businesses, and culture, and diversity. And one of the big three buckets is about culture and leadership, be bold leadership. And it's pretty interesting in your panel, you talked about Box and being that kind of millennial-lead company. A lot of millennials compared to HP and some of the older companies. You had a quote. I wrote it down. You talked about a maniacal focus on culture fit. So Paul, I wonder if you can dive into a little bit about why that's important and how does it manifest itself in the day-to-day operations at Box? >> Something that we always done from the very beginning is, we've always been a people first company. And so what's really important is part of that is when you're hiring people into the company, they also have to fit the culture of the company. As we know, one of the hardest thing to hold on to when you're growing scale a company, is the culture. And so we not only hire for in sort of experience and capability, but also for the culture fit. And we maniacally do focus on that. Now, it can slow down our hiring process, but ultimately it's about preserving that culture. And the culture people first is very much about inclusion. It's very much about our employee resource groups. It's very much about the way we recruit, the way we hire, where we hire from as well. You know I think that millennials, you mentioned having driven millennial culture, millennials will actually interview the company for their values, for their views, for you know. Inclusion would be one of those things as well. So it's, >> Jeff: Right. >> actually even, I think it's going to become harder for companies to even recruit in the future if they don't have a, you know, diversity inclusion as, not as a side project, not as something that happens on the side, but as something that's baked into the company's cultures. >> Right. This is kind of ying and yang, right? 'Cause like you said, it probably slows down your hiring process. There's a lot of pressure to hire people knowing >> Paul: Yeah. >> you can get all the talent they want, but at the other time, you want retention. And you want people that are going to be around for awhile >> Paul: Yeah. >> when you do hire them, will be good contributors to the company >> Paul: That's right. >> for a long, long time. So, I image short-term lost, long-term gain when you stick to that. >> That's absolutely right. Who you work with and who work for is very, very important. And we have a very open social, collaborative culture. And I think generally what that does, and I worked in a number of organizations, is that it creates for a very motivated workforce and very productive workforce. >> J.D., I want to ask you kind about the growth of purpose-driven. You know, we've see it >> J.D.: Yep. >> again and again, I give a lot of credit to the younger kids coming up in terms of purpose being much higher on their rank of priorities of how they make their decisions. I wonder if you can talk, have you seen that in Autodesk in some of your new hires and is it changing the way you guys do things? >> Yeah, sure. And I think even more, more visibly for us, we have such a turn of residences who come and do work in research and prototyping at the shop. That we see a bigger volume there than I do in hiring, and what I really see is a similar. They want to know that we have a commitment to a culture of collaboration. That innovation isn't just a buzz word but is really going to be facilitated. By putting people in the place, with the machines, with the technical capabilities, but also with other people, who are going to think about their problem differently. And I think, you know we back that up with physical practices. We do a lot as a technical team that supports all those residences. By creating spaces to be curious and to learn, and irregardless how much technical expertise you have coming in, we want to learn from you and you want to learn from us. And when the team that's supporting that space really embodies that, people feel it. And they know that it's real. And they know this is a place that I come and ask questions I don't know answers to and not feel dumb about it. But go on the journey with you to find the answers. And that's really what we're facilitating, is people coming in with good questions. >> Right. _ And making a space where you could possibly find an answer you don't expect. And that comes from that culture. So we see that with the turn of people coming through the space, that they need to get it, and they need to know this is a place that they can really push the limits of where they've been before. >> And then how, have you seen the kind of top down push for that culture, in terms of supporting it, evolving it, you know, >> Paul: Yeah. >> over time, from the very top levels? >> J.D.: That's interesting. >> No, now I'll take a run if. Even just go to our company's values, and everybody, you know, has an employee badge. We have our company values in the back of every single badge. And one of our company values, there's a couple, actually we have 10 values in there. And I think they're all great values. One of them is make Mom proud. Okay, it's about, you know, before you make any decision, before you do anything, is this a decision that would make your Mom proud? The next one that is, I think, also goes to the culture of our company, is bring your blank self to work. And you can fill in blank with whatever you want to fill it in with. So these are values that have been thought through from the top of the company, that permeates all the way through the organization. And as you know, an organization, your values and your mission are very, very important to that culture. >> Jeff: Right. >> So we even just reworked our recruitment philosophy based upon hiring on diversity and inclusion as well. So these are things that are absolutely supported from the top down inside our organization. >> And how has that manifested? Do people quote the values in reference to company awards? Do people, how does it actually go from just the back of, you know, the back of your badge to implementation to everyday world? >> We have them in performance reviews. When people are, you know people sort of do their performance reviews in, and part of that is, how is this person upholding our values. And so, we've installed this, you know, deep understanding of the values of the company because that's what effectively holds us together from a culture stand point as well. >> Jeff: Right. >> Yeah, it's interesting I think with Pier 9 we've seen a real chicken and egg. Pier 9 was an experiment when it started five years ago. And I think what's happened is the experiment went well. And that leadership started to see this kind of experiment is bringing in a value that as a software company, we haven't been able to reach before, which is having people in the space innovating and collaborating building community in that way. So it's been interesting to see it trickle up. And I say it's been really been grass-root, and what I see is that now, you know, when they're recruiting at Autodesk, they bring the people to Pier 9 because it's an employee benefit. So, and we see how the videos that Pier 9 are getting made from the marketing department and has influenced how the videos are getting made when we talk about all throughout the company. So it's been very interesting, you know, they brought, they started the experiment that they thought would be valuable, and now the company is found out more and more what that value is. And now they're looking at it. I do we expand that with our network of technology centers? I do we reach more people? And what else does this feed back to the larger corporation? >> Right >> Yeah. >> If anything you just touched on it with your be the underscore person is, is even diversity within the regular, just the regular hires that maybe, just the regular white guy from 10 years ago, >> Paul: Yeah. >> before it would be fit in a box, right. We hired you, now fit in a box. We talked about, it's amazing to me the impact of clothing. >> Paul: Yeah. >> We talked about it in an earlier interview. You know, you're a great person. You do all this stuff. Now we hired you, we'll put you in a box. >> Yeah. >> Yeah. >> As oppose to now, there's kind of whole person concept, which is even diverse inside of the attributes >> Paul: That's it. >> that you're leveraging from the individual >> Paul: Yeah. >> employees to get more value. Seems to be just a really >> Paul: Yeah. >> significant trend that then is going to drive that innovation. To use that whole asset. >> Yeah, you know, I'll even add that, as I mentioned earlier, employee resource groups, right. Heavy support for creating employee resource groups. In fact, we just created a new one for, Belong, you know, this is for people that are maybe immigrants into the country that are now under fear and concern with the what's going on with certain immigration policies and laws and so on. >> Jeff: Right, right. >> And we have Box Women's Network, Box Women's Technology Network, we have Black Excellence Network, we have all these various different employee resource groups, but also what's happening is that these groups are also helping people to get connected with other people across the organization. And as companies grow and you have thousands of employees, how do you get connected with other people across your organization that are in a similar situation as yourself. And we're finding that it's helping build relations, helping to build connections. I think our cognitive thought, our problem-solving, and so on is actually significantly improved because of this. >> Alright, so we're getting the wrap sign. It's a busy day. I want to give you the last word before we cut off. If we sit down a year from now, at International Women's Day, what are you working on, what are your priorities, both as individually as well as, you know, from a company point of view for the next 12 months? J.D., I'll start with you. >> Yeah. I'm actually launching an organization right now called, The Workbench Alliance. It's a professional organization for women, gender non-binary folks, trans-women, super inclusive, working at the intersection of craft, technology, and design. It's a lot of what we facilitate at Pier 9, and I'm looking at how we build a professional network to promote, create visibility, and really more and more community around these sort of converging industries. Supporting each other and you know, kind of employee resource group, but outside the corporation, which I think it's going to benefit, certainly benefit Autodesk, but benefit everybody. >> Jeff: Right, right. >> You know, I'll go on one topic and that's machine learning. I think we that we're at a point, it's almost the tip of an iceberg, but we have over the last few years created more, and more, and more data. And now we're mining that data for intelligence. Machine learning is getting smarter, and smarter, and smarter. So not only are we looking at leveraging that ourselves at Box to add more value to the content that our customers store with us, but also I think it's an opportunity to do things around hiring on diversity. You know, I think there's a lot of learning we can do to weed out unconscious bias. How we screen, the screening process, the finding process, the recruitment process. So I'm a big believer of machine learning helping us in a lot of different ways. >> Alright. Well, J.D., Paul, thanks for taking a minute, >> Alright. >> from your day. I really enjoyed the conversation. >> Alright, thank you >> Great, thank you. >> I'm Jeff Frick, we're at the International Women's Day. The Accenture at downtown San Francisco. Thanks for watching. Catch you next time. (electronic beat theme music)

>> Narrator: Live, from Las Vegas its theCUBE. Covering NetApp Insight 2017. Brought to you by NetApp. >> Hello everyone, welcome back to our live coverage, exclusive coverage at NetApp Insight 2017, it's theCUBE's coverage. I'm John Furrier, co-host, theCUBE co-founder of SiliconANGLE Media, with my co-host, Keith Townsend at CTO Advisor. Our next two guests is Gabe Chapman, Senior Manager, NetApp HCI, and Sidney Sonnier, who's the IT consultant at 4th and Bailey, also a member of the A-Team, a highly regarded, top-credentialed expert. Welcome to theCUBE, guys. Good to see you. >> Hey >> Thanks for having us. >> Thank you, good to be here. >> So love the shirt, by the way, great logo, good font, good, comes up great on the camera. >> Thank you. >> We're talking about the rise of the cloud and everything in between, kind of the segment. As a NetApp, A-Team member, and customer. It's here, cloud's here. >> Sidney: Yes >> But it's not yet big in the minds of the Enterprise because they got, it's a path to get there. So, there's public cloud going on, >> Sidney: Right. >> Hybrid clouds, everyone gets that. >> Sidney: Right. >> There's a lot of work to do at home inside a data center. >> Yes, there is, there's an extreme amount of work. And, like you said, these are very exciting times, because we have a blend of all of the technologies and being at an event like this allows us to look at those technologies, look at that fabric, look at that platform, and how we can merge all of those things into an arena that can allow any customer to dynamically move on-prem, off-prem, public cloud, private cloud, but still be able to manage and securely keep all their data in one specific place. >> Gabe, I want to get your thoughts, as he brings up a good point. Architecture's king, it's the cloud architect. Devop has gone mainstream. Pretty much, we all kind of can look at that and say, okay QED, Don, and everyone else put their plans together, but the Enterprises and the folks doing cloud, cloud service providers and everyone else, they have issues, and their plates are full. They have an application development mandate. Get more developers, new kinds of developers, retrain, re-platforming, new onboarding, open source is booming. They have security departments that are unbundling from IT in a way and fully staffed, reporting to the board of directors, top security challenges, data coverage, and then over the top is IoT, industrial IoT. Man, their plate's full. >> Sidney: Right. >> So architecture's huge, and there's a lot of unknown things going on that need to be automated. So it's a real challenge for architects. What's your thoughts. >> So you know, my thoughts about that is, I like to make this joke that there's no book called, The Joy of Menial Tasks. And there are so many of those menial tasks that we do on a day-in and day-out basis, in terms of the Enterprise, whether it's storage, whether it's virtualization, whether it's, whatever it is, right? And I think we've seen this massive shift towards automation and orchestration, and fundamentally the technologies that we're provisioning in today. APIs are king, and they're going to be kind of the focal point, as we move forward. Everything has to have some form of API in it. We have to be making a shift in a transition towards infrastructure as code. At the end of the day the hardware has relevance. It still does, it always will. But the reality is to abstract away the need for that relevance and make it as simple as possible. That's where we have things like hyper converged infrastructure being so at the forefront for so many organizations, NetApp making a foray into this space, as well, is to push, to simplify as much as possible, the day-to-day minutiae, and the infrastructure provisioning. And then, transition those resources over towards getting those next-generation data center applications up, running, and functional. >> Old adage that's been in the industry around making things simple, as our cubbies like an aircraft carrier. But when you go below the water lines, everyone in little canoes paddling, bumping into each other. These silos, if you will. >> Gabe: Right. >> And this is really the dynamic around cloud architecture, is where the operating model's changing. So, you got to be prepared to handle things differently. And in storage, the old days, is, I won't say, easy, but you guys made it easy. A lot of great customers. NetApp has a long history of, but it's not the storage anymore. It's the data fabric as you guys are talking about. It's the developer enablement. It's getting these customers to drive for themselves. It's not about the engine anymore, although, you've got to have a good engine, call it tech, hardware, software together. But the ultimate outcome is the people driving the solutions are app guys. They're just the lines of businesses are under huge pressure and huge need. >> I think you can look at it this way. It's like we're kind of data-driven. You'll see Gene talk about that as part of our messaging. We can no longer be just a storage company. We need to be a data company and a data management organization as we start to have those conversations. Yes, you're going to go in there and talk to the storage administrations and storage teams, but there are 95% of the other people inside of the Enterprise, inside information technology, within different lines of business. They're the ones that we have the most relevant discussions with. That's where our message probably resonates more strongly in the data-driven aspect, or the management, or analytics, and all those other spaces. And I think that's the white space and growth area potential for NetApp, is the fact that we can go in there and have very authoritative discussions with customers around their data needs, and understanding governance. You have things like GPRD, and AMIA. That's a giant open ecosystem for, it has so many requirements and restrictions around it, and everybody's just now starting to wrap their head around it. So building a program around something like that, as well. So there's challenges for everybody. And there's even challenges for vendors like ourselves, because we had, we were mode one. Now we're mode two. So it's kind of like making that transition. And the old speeds, the speeds were always, hey, how fast can you go, what's the files look like, with replication, blah, blah, blah. Now you've got solid, solid state storage. You got SolidFire. Now people want outcomes as a service. Not outcomes anymore, like a cliché, things are happening very dynamically. And last week at Big Data NYC, our event, around the big data world, you couldn't get anymore clear that there's no more room for hype. They want real solutions now. Realtime is critical. And, now watching the keynotes here at NetApp, it's not speed that's featured, although there's a lot of work going on under the hood, it's really about competitive advantage. You're hearing words like data as a competitive advantage. >> Sidney: Yes. >> Sidney, you're in the field, you're in the front lines. Make sense of this. >> The sense that we have to make is, we made up some great points. >> Gabe: Yes. >> Getting the business engaged is one thing, because you still, with the cloud and the cloud architecture, you still have a lot of individuals who are not necessarily sold on it, all the way. So even from a technical perspective. So those guys that are down in the bottom of the boat, so to speak, you still have to kind of convince them because they feel somewhat uncomfortable about it. They have not all the way accepted it. The business is kind of accepted it in pockets. So being, having been on a customer's side and then going to more of a consulting side of things, you understand those pain points. So by getting those businesses engaged and then also engaging those guys to say, listen, it's freeing, the relevance of cloud architecture is not to eliminate a position, it's more to move the mundane tasks that you were more accustomed to using and move you closer to the business so that you can be more effective, and feel more of a participant, and have more value in that business. So that's-- >> So it's creating a value role for the-- >> Right, Right. >> The nondifferentiated tasks >> Absolutely. >> That were being mundane tasks, as you called them. >> Yes. >> You can then put that person now on, whether analytics or ... >> All those IoT things like you were mentioning on those advance projects, and use and leverage the dynamic capability of the cloud being able to go off-prem or on-prem. >> Alright, so what's the guiding principle for a cloud architecture? We'll have to get your thoughts on this because we talked about, in a segment earlier, with Josh, around a good devops person sees automation opportunities and they jump on it like a grenade. There it is, take care of that business and automate it. How do you know what to automate? How do you architect around the notion of we might be continually automating things to shift the people and the process to the value? >> I think what it boils down to is the good cloud architect looks and sees where there are redundancies, things that can be eliminated, things that can be minimized, and sees where complexity is, and focuses to simplify as much of it as possible, right? So my goal has always been to abstract away the complexity, understand that it's there and have the requirements and the teams that can functionally build those things, but then make it look to you as if it were your iPhone, right? I don't know how the app store works. I just download the apps and use it. A good cloud architect does the same thing for their customers. Internally and externally, as well. >> So where does NetApp fit in there, from a product perspective? As a cloud architect, you're always wondering what should I build versus what should I buy? When I look at the open source projects out there, I see a ton of them. Should I go out and dive head deep into one of these projects? Should I look towards a vendor like NetApp to bring to bear that simplified version? Where is the delineation for those? >> So the way we see it is traditionally, there's kind of four consumption models that exists. There's an as-a-service model, or just-in-time model. There are, we see converged, hyper converged as a consumption continuum that people leverage and utilize. There are best-of-breach solutions. Because if I want an object store, I want an object store, and I want it to do exactly what it does. That's an engineering solution. But then there's the as-a-service, I mean, I'm sorry, there's a software-defying component, as well. And those are the, kind of the four areas. If you look at the NetApp product lines, we have an ONTAP set of products, and we have an Element OS set of products, and we have solutions that fit into each one of those consumption continuums, based on what the customer's characteristics are like. You may have a customer that likes configurability. So they would look at a traditional FlexPod with a FAS and say that that's a great idea for me for, in terms of provisioning infrastructure. You may get other customers that are looking at, I want the next-generation data center. I want to provide block storage as a service. So they would look at something like SolidFire. Or, you have the generalist team that looks at simplicity as the key running factor, and time-to-value. And they look at hyper converged infrastructure. So there's a whole set. For me, when I have a conversation with a customer around build versus buy, I want to understand why they would like to build it versus buy it. Because I think that a lot of times, people think, oh, I just download the software and I put it on a box. I'm like, well, right, that's awesome. Now you're in the supply-chain management business. Is that your core competency? Because I don't think it is, right? And so there's a whole bunch of things. It's like firmware management and all these things. We abstract away all of that complexity. That's the reason we charge up for a product, Is the fact that we do all that heavy lifting for the customer. We provide them with an engineered solution. I saw a lot of that when we really focused significantly on the OpenStack space, where we would come up and compete against SEP. And I'm like, well how many engineers do you want to dedicate to keeping SEP up and running? I could give you a turnkey solution for a price premium, but you will never have to dedicate any engineers to it. So that's the trade-off. >> So on that point, I just want to followup. A followup to that is you vision OpenStack, which, big fans of, as you know, we love OpenStack. In the beginning, the challenge with the dupe in OpenStack early on, although that kind of solved, the industry's evolved, is that the early stage was the cost of ownership problem. Which means you had the early tire kickers. Early pioneers doing to work. And they iterated through it. So the question around modernization, which came up as a theme here, what are some modernization practices that I could take as a potential customer, or customer of NetApp, whether I'm an existing customer or a future customer, I want to modernize but I don't want to, I want to manage cost of ownership. And I want to have an architect that's going to allow me to manage my data for that competitive advantage. So I want the headroom of know that it's not just about putting a data link out there, I got to make data realtime, and I don't know when and where it's going to be available. So I need kind of like a fabric or a layer, but I got to have a modern infrastructure. What do I do, what's the playbook? >> So that's where that data fabric, again, comes in. It's like one of the keynotes we heard earlier in the General Session yesterday. We have customers now who are interested in buying infrastructure like we buy electricity. Or like we buy Internet service at home. So by us having this fabric, and it being associated with a brand like NetApp, we're, it's opening up to the point where, what do you really want to do? That's the question we come to you and ask. And if you're into the modernization, we can provide you all the modernization tools right within this fabric, and seamlessly transition from one provider to the next, or plug into another platform or the next, or even put it on-prem. Whatever you want to do. But this will allow the effective management of the entire platform in one location, where you don't have to worry about a big team. You can take your existing team, and that's where that internal support will come in and allow people to kind of concentrate and say, oh, this is some really interesting stuff. Coming from the engineering side of things, being on that customer side, and when you go into customers, you can connect with those guys and help them to leverage this knowledge that they already have because they're familiar with the products. They know the brand. So that makes it more palatable for them to accept. >> So from the cloud architect's perspective, as you look at it, you look at the data-driven fabric or data fabric, and you're like, wow, this is a great idea. Practically, where's the starting point? Is this a set of products? Is it an architecture? Where do I start to bite into this apple? >> So ultimately, I think, you look at it, and I approach it the same way, I would say, like, I can't just go and buy devops. >> Right. >> Right, but data fabric is still, it's a concept, but it's enabled by a suite of technology products. And we look at NetApp across our portfolio and see all the different products that we have. They all have a data fabric element to them, right? Whether it's a FAS, and Snapmirror and snapping to, and ONTAP cloud, it's running in AWS. Whether it's how we're going to integrate with Azure, now with our NFS service that we're providing in there, whether it's hyper converged infrastructure and the ability to move data off there. Our friend Dave McCrory talked about data having gravity, right, he coined that term. And it does, it does have gravity, and you need to be able to understand where it sits. We have analytics in place that help us craft that. We have a product called OCI that customers use. And what it does, it gives them actionable intelligence about where their data sits, where things may be inefficient. We have to start making that transition to, not just providing storage, but understanding what's in the storage, the value that it has, and using it more like currency. We heard George talk about data as currency, it really is kind of the currency, and information is power, right? >> Yeah, Gabe, I mean Gabe, this is right on the money. I mean cryptocurrency and blockchain is a tell sign of what's coming around the corner. A decentralized and distributed environment that's coming. That wave is way out there, but it's coming fast. So you, I want you to take a minute to talk about the cloud component. >> Sidney: Sure. >> Because you mentioned cloud. Talk about your relationship to the clouds, because multi cloud is coming, too. It's not yet there yet, but just because you have a cloud, something in every cloud means multi cloud in the sense of moving stuff around. And then talk about the customer perspective. Because if I'm a customer, I'm saying to myself, okay, I have NetApp, I got files everywhere, I've got ONTAP, they understand the management game, they know how to manage data on-prem, but now I got this cloud thing going on, and I got this shiny new toy start-up over there that's promised me the moon. But I got to make a decision. You're laughing, I know you're thinking about it. This is the dilemma. Do I stay with what I know? >> Right. >> And what I know, is that relevant for where I'm going? A lot of times start-ups will have that pitch. >> Oh, yeah. >> Right >> So address the cloud and then talk about the impact of the customer around the choice. >> Ultimately, it boils down to me in many respects. When I have a conversation with a customer, if I'm going to go for the bright and shiny, right, there has to be a very compelling business interest to do so. If I've built a set of tools and processes around data governance, management, implementation, movement, et cetera, around a bunch of on-premises technologies and I want that same effect or that same look and feel in the public cloud, then that's how we transition there. I want to make it look like I'm using it here locally but it's not on my site, it's somewhere else. It's being managed by somebody else, from a physical standpoint. I'm just consuming that information. But I also know I have to go back and retool everything I've spent in the last 15 and 20 years building because something new and neat comes along. If that new and neat thing comes along, it abstracts away, or it makes a significant cost reduction or something like that, then obviously, you're going to validate that or look at and vet that technology out. But reality is, is that we kind of have these-- >> Well, they don't want to recode, they don't want to retool, they'll rewrite code, but if you look at the clouds, AWS, Azure, and Google, top three in my mind, >> Sidney: Right. >> They all implement everything differently. They got S3 over there, they got it over here, so like, I got it resting on-prem but then I got to hire a devops team that's trained for Azure, Sidney, this is the reality. I mean, evolution might take care of this, but right now, customers have to know that. >> We're at a point right now where customers, businesses we go to, realtime is very important. Software as a service is the thing now. So if you have a customer who is just clicking on a button, and if they can't see that website or whatever your business is, that's a problem. You're going to lose money. You're going to lose customers, you're going to lose revenue. So what you have to do is, as a business, discover what you have internally. And once you discover that and really understand it as a business, not just the tech team, but the business actually understands that. Move that forward and then blend some cloud technology in that with a data fabric, because you're leveraging what you already have. Most of the time, they usually have some sort of NetApp appliance of some sort. And then some of the new appliances that we do have, you can either say, have a small spin, put it next to an old appliance, or use some of the OCI, or something of that nature, to help you migrate to a more dynamic, and the thing about it is, is to just make it more a fluid transition. That's what you're looking to do. Uptime is everything. >> Yeah. >> Totally. >> This fabric will allow you to have that uptime so that you can propel your business and sustain your business. Because you want to be able to still use what you have, and still get that ROI out of that technology, but at the same token, you want to be more dynamic than the competition, so that you can increase that business and still grow the business, but now lose any business. >> Sidney, you bring up a good point. In fact, we should do a followup segment on this, because, what I'm hearing you say, and I've heard this many times in theCUBE, but it's happening, and certainly, we're doing our part on theCUBE to help, but the tech guys, whether they're ops or devs, they're becoming more business savvy. They've got to get closer to the business. >> Sidney: You have to. >> But they don't want to get an MBA, per se, but they have to become street MBA. >> Sidney: Right. >> They got to get that business degree through scar tissue. >> Yes. You can't just be the tech anymore, you have to understand why your business is making this effort, why it's investing this technology, why they would look to go to the public cloud, if you can't deliver a service, and try to emulate that. We've seen that time and time again, the concept of shadow IT, and a shift away from resources. And if you want to be relevant longterm, and not just the guy that sits in the closet, and then plugs in the wires, start learning about your business. Learn about how the business is run and how it generates revenue and see what you can do to affect that. >> Yeah, and the jobs aren't going away. This nonsense about automation killing jobs. >> No, it's not. >> And they use the mainframe as an example, not really relevant, but kind of, but there are other jobs. I mean, look at cyber security, huge data aspect, impact story. >> Sure, it's huge. >> That paradigm is changing realtime. So good stuff, a lot of good business conferences we should do a followup on. I'll give you guys a final word in this segment. If you could each weigh in on what cloud architects should be doing right now. I mean, besides watching theCUBE, and watching you guys here. They got to have the 20-mile stare. They got to understand the systems that are in place. It's almost like an operating system model. They got to see the big picture. Architecting on paper seems easy, but right now it's hard. What's your advice for cloud architects? >> I mean, I say continue to follow the trends. Continue to expose yourself to new technologies. I mean, I'm really interested in things like serverless and those type technologies, and how we integrate our platforms into those types of solutions. Because, that's kind of the next wave of things that are coming along, as we become more of an API-driven ecosystem, right? So if it's infrastructure, if it's code, if it's everything is just in time instance of spin up, how do I have the communications between those technologies? You've just got to stay well ahead of the curve and, you know ... >> John: Sidney, your thoughts? >> My thoughts are along those lines. Not only from a technical perspective but also like you were talking about, that business perspective. Understand your business needs. Because even though, and be able to provide a portfolio, or a suite of tools that will help that business take that next step. And that's where that value. So it's kind of like a blend. You're more of a hybrid. Where you're coming in, not only as a technical person, but you're coming in to assist the business and develop it and help it take it's next step. >> John: And IT is not a department, anymore, it's everywhere. >> No it's not, not. >> It's integrated. >> It is the business. >> Yes. >> Guys, great conversation here on the future of the cloud architect, here inside theCUBE at NetApp Insight 2017 here at the Mandalay Bay in Las Vegas, theCUBE's coverage. We'll be right back with more after this short break. (techno music) (fast and furious music)

[Music] from the cube studios in Palo Alto in Boston it's the cube covering the IBM think brought to you by IBM hi everybody welcome back to the cubes coverage wall-to-wall coverage of the IBM think 20/20 digital event experience my name is Dave Volante we'll be going really all week and and focusing on the impact of the pandemic how IBM is responding how customers are likely to respond I'm really excited Luke Niazi is here's the global managing director of consumer industries at IBM Luke good to see you nice do you see even that nice to be on the cool I mean if I think about consumer all the assumptions that we made about consumer behavior they're really up in the air right now I wonder if you could share with us what your current thinking is I mean the consumer has powered this global economy years what are you thinking about the consumer right now in the consumer behavior well was he some a massive shift in terms of the immediacy let me this back a little bit Dave and give you a bit of context we did some research at the beginning of the year that we launched the National Retail Federation and we surveyed over 19,000 people globally and that survey showed that they were do be on a shifts that are appearing first of all there was a shift in of the purpose given consumer of the 19,000 people that we surveyed 40% of them said that they were making decisions that were purpose different compared to 41% that make visions that were convenience and that's people who care about sustainability and where products are coming and the other big thing that we saw was popping in micro moments increase digital shopping and of anytime anywhere now of course with the and Emmy we are seeing an acceleration and fastening of those first of all beyond the immediate move panic buying that occurred we've seen a big big shift in online buying and we think like Ron and driver also a reinforcement of this move to more sustainable product and services yeah I mean so right now you have I guess buying for what's available you need something it might not be available as a consumer you're making a lot of trade-offs okay well I'll go for you know alcohol-based hand sanitizer you know as opposed to just conventional hand sanitizer as an example oh well I'll make some trade-offs in tissue paper etcetera etcetera and maybe there's some boredom buying I don't have you've seen that your people are shut-in but though all kinds of of daily changes weekly changes so how do you see this exiting how do you see compute consumer behavior you know changing as we exit this pandemic in waves and we're only sure how we're going to exit well let me kind of break it down in terms of what's been going on right now so of course we saw this massive waves of you know a shift to sanitary products a shift or groceries then we've seen a shift about how can I keep my kids entertained while they're at home and kind of more discretionary choices being much lower so when you kind of look at that in terms of actual impact on business we've seen grocery say in the u.s. up by about twenty seven and we've seen a move on digital in the u.s. about three percent of the of the US population shifts about buys online that's do 43 percent during this period and of course we think that these are things that are going to sustain what it's done is it's accelerate the type of purchases that people are doing in a digital context and we think that that is you know continued by some thoughts the data on the pandemic looks like it's been to continue for many months and and in ways those that we've seen the shifted digital and initially people are kind of looking for things anywhere but it's going to be combined with a kind of a new type of delivery model there's much more buy online pick up in center distribution center pick up our part whether that's you know your groceries or whether that's health related so it's going to change the delivery models it also means of course that stores are going to change a great great deal at the moment grocery stores all have social distancing with the protection of the store associates been you know a key element of that you're gonna see not the same amount of people in those stores going forward and you know a different configuration and application of technology also in store to keep monitoring both the safety of the employees and the safety of the customers but also make sure that occupancy levels are appropriate etc so big shifts the digital the big shifts to different types of delivery models you know big shifts of safety related technology of course what we're also seeing and this is the difficult piece which is if you have discretionary spend fashion apparel luxury the open those volumes are very very significant I mean look I've actually been quite impressed with some providers that have pivoted very quickly to things like curbside pickup and have really responded you know quite fast to that at the same time I've seen others where I mean it's clear that they really didn't have the infrastructure or the processes of their asking hey how how did we do do you mind taking a quick survey because they need to iterate how can I be M help those that really weren't that prepared and it sort of band-aided together some solutions get to the point post pandemic before this thing ends where they really need to be what are you guys doing with client yeah so well first and foremost as the pandemic we focused very much on resilience making sure that our clients but operators as robustly as possible in fact you know 95 percent to our services are being delivered it just began and remotely right what then happened was how do I deal with these massive volumes of airing in my two centers where by the way I have less staff because the people are I having to even themselves safe and social distance and so we deployed immediately beyond our resiliency solutions all centers that are helping our clients booth by aura ties and scream one of our major retail clients in the u.s. said you know I thought that the Watson Chapman knowledge ease were going to be helpful they weren't just helpful they saved us and so that kind of things occurring in the immediate that's the next piece of course you then start see is that finds have realized that both their digital panels and their fulfillment models have not been able to keep up nobody is being able to keep up with the demand that's not even Amazon's been able to keep up and what was you know a 24 or 48 hour delivery slot those those kind of slots have gone out the window so we are going to see a wave of reinvest in enhancing digital channels and we will leverage no both our our services business as well as our cloud knowledge ease to support that and then underpinning that you you're also seeing a need to rebalance the supply chain because of course where products come from have changed where is vsauce is now having to move much more from a global supply chain to a global local supply chain and we're having to balance supply with more local providers and so is a there's a demand supply balancing to be done that means that eyes are and i think about the practicalities of that but they were investing in next-generation technologies to support that for IBM that things like our IBM sterling portfolio but it's also the activation of our supply chain AI this massive demand set by and of imbalancing and we've been helping certain clients look at that and move stock most appropriate locations we've been doing that to help clients kind of rethink that there's this budgeting so we're gonna see a lot of that we have all of the intelligence of by chain and we're going to see no investment in the intelligence of buy chain just like we see this investment at baring in the change in the commerce engines last thing to say is wrap in trace is going to be hugely important reckon trace of all products and where they come from where they were handled and people and so technologies like lock pane and what we do with food trusts are also going to be a really important element yeah another really piece of digital I mean the cube we go to physical events and we've been saying that hang that this is not going to go back to 2019 the people are going to learn through this experience that there's really some additional value that they they can create through digital you think you think about consumer that's a much much more complex environment tens of thousands and fully hundreds of thousands or even millions of fights the product dimension chat thoughts you know the entire experience that we talked about a curbside pickup lead times people you know managing demand with lead times you can only or limiting the volume you mentioned supply chain track and trace block pain so a whole new set of digital assumptions are going to emerge or are emerging I don't want to make it sound like there's a there's some kind of binary beginning an end to this thing this is this is going to be a slow but yet fast iteration of constant iteration and continuous improvement yeah it is what am i - the newer faculty were talking earlier this week and they said look as difficult the environment is right now and of course we've been focused on our current operations and fulfilling our customers as best we can it's actually bringing us through a whole new window about who we think the priority is of our investment and how we look at that going forward and you know he's almost saying well I'm gonna have to zero based budgeting approach and against that we're gonna see a much better investment in almost regardless of what your model is whether you are digital first or physical first you're gonna see much better focus on kind of dealing with the pasady and the variability that we've experienced because organizations weren't geared up for that and you're going to see them the investment in the intelligence and the supply chain who support that backed up with trust and traceability and now back to the points that I start at the beginning of this session it means that the trends that we saw and we assess actually are going to be almost perpetuated because we think this move to sustainable and more local sourcing more balanced sourcing will continue to be a big factor and we think that this kind of idea of shopping in the micro moment but shopping in a much more digital way is here to stay the consequence of that is it's gonna have a what a big impact on the physical environments and unfortunately there aren't gonna do there are going to be as easy in this with certain sectors that are not going to be able to sustain the the big shift in the model so obviously physical down for the immediate and probably mid and maybe even long term digital up you one of your areas of expertise is agribusiness we thought you note you know tumour in general I wonder if you could share with us what you're what you're seeing there I'm inferring more more local sourcing which obviously has some impacts on what's available at different times a year potentially on on pricing thoughts on agribusiness and how they're responding yeah well it's it's fascinating you know if you take it into first of all of course you know agriculture has been impacted right now by not so much for the professional farming which has a large-scale mechanization before a lot of farming in large parts of Asia or Latin parts of Latin America or parts of Africa and even parts of Europe there's a lot of transitionary labor that occurs in order to be able to harvest crops and so that's a that's a really difficult immediate problem we've seen you people volunteering in certain countries like here in the UK where I live either people volunteering you can't work in their current job see how can I help that's kind of it an immediate thing that's needed right now but the broader topic in the work that my teams do is that actually the application of digital technologies and science who is behind what it is in other industries and there's such a great opportunity by leveraging digital only be more effective in actually hitting the most out of farming land without over farming the land and so we're working quite a lot on digital economics of buying base ability you truly from farmed or and no but have been together data sources that were not in the same base to be able to help build effectively an AgrAbility for the benefit the farmers and cross those things were going to see farmers empowered with more information in it more insight so simple things like The Weather Channel application that we have from our weather comm we're deploying that to millions of farmers in Africa and Asia and on top of that we're being able to and for the deployment of other related information though how to farm but also we could start to look at how to provide safety related information etcetera to those farmers so so we are going to see through effective use of technology increase appropriate digitization of no farming processes and there'll be in a very practical level what I'd put onto my phone so so definitely this is a big thing and and of course as you know the traceability that we do with our food resan isn't just about safety and talk about how food was produced how far it's traveled what conditions was it handled in what's a co2 footprint and so that traceability engine can actually accelerate also this is and as I referred to earlier Luca mean as we're discussing you know the moment-by-moment the assumptions are changing you know the narrative this weekend of course at least in the US was pay we've got it now get out there and and many are saying this not all but but just effect mass unity that it's really going to be the only way vaccines aren't coming anytime soon young people will go out retail environment of course you're gonna have social distancing people that are compromised or older aren't going to go out the clearly volumes are going to be down but it's a very fluid situation so business resiliency and flexibility is critical here and it sounds like you're helping organizations really build that into their operating model that is critical yeah absolutely and you know for some of the grantees that I haven't boomer you what you're seeing in things like a chorale fashion luxury is a a move to try to drive that engagement to you the customer in a much more digital sense so how do I interact with the brand how do I experience the band how can I all the way through to my purchase digitally when I don't have the ability to get stores so this digital transformation agenda will affect pretty much all major segments obviously the foods by chain the health by chain is the focus right now but we will see on the increasing digitization and a need to rebalance the in-store experience even for the segments so there will be a lot of transformation to be done a while of course having to deal with the cost balancing that need in these industries as they effectively shift more towards digital yeah you're right I mean the cost structure may dramatically change yet at the same time it may be critical for or maintaining or even gaining market share so a lot of potential disruption Luke I'll give you the final word your thoughts bring us home well you know first of all you know people's well-being in safety is our paramount purpose and that's what we've been looking at the outset but I think people would be positive that there is a lot of opportunity in which we can deliver the things that they need in a safe way in a secure way in a digital way that is able to cope with the environments that we see today and may prevail and it's about winning that intelligence and innovation into both the promise and the digital channels and into the supply chains all the way through to the track and trace which is what we focus on well look thanks so much for coming on the cube was great to have you with your your insights on the IBM very clearly has its hands and a lot of these different industries and it's great to have your industry expertise sharing with our audience I really appreciate your time take care thank you all right thank you for watching everybody this is Dave Volante for our continuous coverage of IBM think digital event experience 2020 you're watching the cube right back right after this short break you [Music] you

six five four three two one hi everybody and welcome to this cube special presentation of the verdict of virtual big data conference the cube is running in parallel with day 1 and day 2 of the verdict the big data event by the way the cube has been at every single big data event and it's our pleasure to be here in the virtual / digital event as well Gabriel Chapman is here is the director of flash blade product solutions marketing at pure storage Gabe great to see you thanks for coming on great to see you - how's it going it's going very well I mean I wish we were meeting in Boston at the Encore hotel but you know and and hopefully we'll be able to meet it accelerate at some point you cheer or one of the the sub shows that you guys are doing the regional shows but because we've been covering that show as well but I really want to get into it and the last accelerate September 2019 pure and Vertica announced a partnership I remember a joint being ran up to me and said hey you got to check this out the separation of Butte and storage by a Eon mode now available on flash played so and and I believe still the only company that can support that separation and independent scaling both on prime and in the cloud so gave I want to ask you what were the trends in analytical database and plowed that led to this partnership you know realistically I think what we're seeing is that there's been kind of a larger shift when it comes to modern analytics platforms towards moving away from the the traditional you know Hadoop type architecture where we were doing on and leveraging a lot of direct mass storage primarily because of the limitations of how that solution was architected when we start to look at the larger trends towards you know how organizations want to do this type of work on premises they're looking at solutions that allow them to scale the compute storage pieces independently and therefore you know the flash blade platform ended up being a great solution to support Vertica in their transition to Eon mode leveraging >> essentially as an s3 object store okay so let's let's circle back on that you guys in your in your announcement of a flash blade you make the claim that flash blade is the industry's most advanced file and object storage platform ever that's a bold statement I defend that it's supposed to yeah I I like to go beyond that and just say you know so we've really kind of looked at this from a standpoint of you know as as we've developed flash Wade as a platform and keep in mind it's been a product that's been around for over three years now and has you know it's been very successful for pure storage the reality is is that fast file and fast object as a combined storage platform is a direction that many organizations are looking to go and we believe that we're a leader in that fast object of best file storage place in realistically which we start to see more organizations start to look at building solutions that leverage cloud storage characteristics but doing so on prem for a multitude of different reasons we've built a platform that really addresses a lot of those needs around simplicity around you know making things assure that you know vast matters for us simple is smart we can provide you know cloud integrations across the spectrum and you know there's a subscription model that fits into that as well we fall that falls into our umbrella of what we consider the modern day day experience and it's something that we've built into the entire pure portfolio okay so I want to get into the architecture a little bit of Flash blade and then better understand the fit for analytic databases generally but specifically for Vertica so it is a blade so you got compute and a network included it's a key value store based system so you're talking about scale out unlike unlike viewers sort of you know initial products which were scale up and so I want to as a fabric base system I want to understand what that all mean so take us through the architecture you know some of the quote-unquote firsts that you guys talk about so let's start with sort of the blade aspect yeah the blade aspect mean we call it a flash blade because if you look at the actual platform you have a primarily a chassis with built in networking components right so there's a fabric interconnect with inside the platform that connects to each one of the individual blades the individual blades have their own compute that drives basically a pure storage flash components inside it's not like we're just taking SSDs and plugging them into a system and like you would with the traditional commodity off-the-shelf hardware design this is a very much an engineered solution that is built towards the characteristics that we believe were important with fast file and fast object scalability you know massive parallelization when it comes to performance and the ability to really kind of grow and scale from essentially seven blades right now to a hundred and fifty that's that's the kind of scale that customers are looking for especially as we start to address these larger analytics pools mayo multi petabyte datasets you know that single addressable object space and you know file performance that is beyond what most of your traditional scale-up storage platforms are able to deliver yeah I saw you interviewed cause last September and accelerate and and Christopher's been you know attacked by some of the competitors is not having a scale out I asked them his thoughts on that he said well first of all our flash plate is scale out he said look anything that that that adds the complexity you know we avoid but for the workloads that are associated with Flash blade scale out is the right sort of approach maybe you could talk about why that is well you know realistically I think you know that that approach is better when we're starting to learn to work with large unstructured data sets I mean flash plays uniquely architected to allow customers to achieve you know a superior resource utilization for compute and storage well at the same time you know reducing significantly the complexity that is arisen around these kind of bespoke or siloed nature of big data and analytic solutions I mean we really kind of look at this from a standpoint of you have built and delivered or created applications in the public cloud space that address you know object storage and and unstructured data and and for some organizations the importance is bringing that on Prem I mean we do seek repatriation that coming on for a lot of organizations as these data egress charges continue to expand and grow and then organizations that want even higher performance in the what we're able to get into the public cloud space they are bringing that data back on Prem they are looking at from a standpoint we still want to be able to scale the way we scale on the cloud we still want to operate the same way we operate in the cloud but we want to do it within control of our own you know our own borders and so that's you know that's one of the bigger pieces to that is we start to look at how do we address cloud characteristics and dynamics and consumption metrics or models as well as the benefits and efficiencies of scale that they're able to afford but allowing customers that do that with inside their own data center so you're talking about the trends earlier you had these cloud native databases that allowed the scaling of compute and storage independently Vertica comes in with Eon a lot of times we talk about these these partnerships as Barney deals of you know I love you you love me here's a press release and then we go on or they're just straight you know go to market are there other aspects of this partnership that are that are non Barney deal like in other words any specific you know engineering you know other go to market programs could you talk about that a little bit yeah it's it's it's more than just you know I then what we consider a channel meet in the middle or you know that Barney type of deal it's realistically you know we've done some first with Vertica that I think are really important if they think you look at the architecture and how we do how we've brought this to market together we have solutions teams in the back end who are you know subject matter experts in this space if you talk to joy and the people from vertigo they're very high on they're very excited about the partnership because it often it opens up a new set of opportunities for their customers to to leverage Eon mode and you know get into some of the the nuanced aspects of how they leverage the Depot or Depot with inside each individual compute node and adjustments with inside there I reach additional performance gains for customers on Prem and it's the same time for them there's still the ability to go into that cloud model if they wish to and so I think a lot of it is around how do we partner as two companies how do we do a joint selling motions you know how do we show up and and you know do white papers and all of the the traditional marketing aspects that we bring into the market and then you know joint selling opportunities exist where they are and so that's realistically I think like any other organization that's going to market with a partner or an ISP that they have a strong partnership with you'll continue to see us you know talking about our shows mutually beneficial relationships and the solutions that we're bringing it to the market okay you know of course he used to be a Gartner analyst and you go over to the vendor side now but as but as it but as a gardener analyst you're obviously objective you see it all and you know well there's a lot of ways to skin a cat there are there are there are strengths weaknesses opportunities threats etc for every vendor so you have you have Vertica who's got a very mature stack and and talking to a number of the customers out there who are using Eon mode you know there's certain workloads where these cloud native databases make sense it's not just the economics of scaling compute and storage independently I want to talk more about that there's flexibility aspects as well but Vertica really you know has to play its trump card which is look we've got a big on-premise state and we're gonna bring that you know Eon capability both on Prem and we're embracing the cloud now they're obviously having they had to play catch-up in the cloud but at the same time they've got a much more mature stack than a lot of these other you know cloud native databases that might have just started a couple years ago so you know so there's trade-offs that customers have to make how do you sort through that where do you see the interest in this and and and what's the sweet spot for this partnership you know we've been really excited to build the partnership with Vertica and we're providing you know we're really proud to provide pretty much the only on Prem storage platform that's validated with the vertical Aeon mode to deliver a modern data experience for our customers together you know it's it's that partnership that allows us to go into customers that on Prem space where I think that they're still you know not to say that not everybody wants to go the cloud I think there's aspects and then solutions that work very well there but for the vast majority I still think that there's you know the your data center is not going away and you do want to have control over some of the many of the different facets with inside the operational confines so therefore we start to look at how do we can do the best of what cloud offers but on Prem and that's realistically where we start to see the stronger push for those customers you still want to manage their data locally as well as maybe even work around some of the restrictions that they might have around cost and complexity hiring you know the different types of skills skill sets that are required to bring you know applications purely cloud native it's still that larger part of that digital transformation that many organizations are going for going forward with and realistically I think they're taking a look at the pros and cons and we've been doing cloud long enough where people recognize that you know it's not perfect for everything and that there's certain things that we still want to keep inside our own data center so I mean realistically as we move forward that's that that better option when it comes to a modern architecture they can do it you know we can deliver and address a diverse set of performance requirements and allowed the organization to continue to grow the model to the data you know based on the data that they're actually trying to leverage and that's really what flash Wood was built for it was built for a platform that can address small files or large files or high throughput high throughput low latency scale to petabytes in a single namespace in a single rack as we like to put it in there I mean we see customers that have put you know 150 flash blades into production as a single namespace it's significant for organizations that are making that drive towards modern data experience with modern analytics platforms pure and Vertica have delivered an experience that can address that to a wide range of customers that are implementing you know the verdict technology I'm interested in exploring the the use case a little bit further you just sort of gave some parameters and some examples and some of the flexibility that you have in but take us through kind of what to discuss the customer discussions are like obviously you've got a big customer base you and Vertica that that's on prem that's the the unique advantage of this but there are others it's not just the economics of the granular scaling of compute and storage independently there are other aspects so to take us through that sort of a primary use case or use cases yeah you know I mean I can give you a couple customer examples and we have a large SAS analyst company which uses verdict on flash play to authenticate the quality of digital media in real time and you know then for them it makes a big difference is they're doing they're streaming and whatnot that they can they can fine tune and grandly control that so that's one aspect that we need to address we have a multi national car company which uses verdict on flash blade to make thousands of decisions per second for autonomous vehicle decision making trees you know that's what really these new modern analytics platforms were built for there's another healthcare organization that uses Vertica on flash blade to enable healthcare providers to make decisions in real time the impact vibes especially when we start to look at and you know the current state of affairs little Co vid and the coronavirus you know those types of technologies are really going to help us kind of get love and and help lower and been you know bend that curve downward so you know there's all these different areas where we can address the goals and the achievements that we're trying to look bored with with real-time analytic decision making tools like birth and you know realistically as we have these conversations with customers they're looking to get beyond the ability of just you know you know a data scientist or a data architect looking to just kind of drive in information you know you know I'm gonna set this model up and we'll come back in a day now we need to make these and the performs characteristics the Aeon mode and vertical allows for can get us towards this almost near real-time analytics decision-making process and that the customers and that's the kind of conversations that we're having with customers who really need to be able to turn this around very quickly instead of waiting well I think you're hitting on something that is actually pretty relevant and that is that near real-time analytic you know database we were talking about Hadoop earlier we're kind of going well beyond that now and I guess what I'm saying is that in the first phase of cloud it was all about infrastructure it was about you know spinning up you know compute and storage a little bit of networking in there seems like the the a next a new workload that's clearly emerging is you've got and it started with the cloud native databases but then bringing in you know AI and machine learning tooling on top of that and then being able to really drive these new types of insights and it's really about taking data these bogs this bog of data that we've collected over the last 10 years a lot of that you know driven by Hadoop bringing machine intelligence into the equation scaling it with either cloud public cloud or bringing that cloud experience on-premise scale you know across your organizations and across your partner network that really is a new emerging work load do you see that and maybe talk a little bit about you know what you're seeing with customers yeah I mean it really is we see several trends you know one of those is the ability to take a take this approach to move it out of the lab but into production you know especially when it comes to you know data science projects machine learning projects that traditionally start out as kind of small proofs of concept easy to spin up in the cloud but when a customer wants to scale and move towards a real you know that derived a significant value from that they do want to be able to control more characteristics right and we know machine learning you know needs to needs to learn from a massive amounts of data to provide accuracy there's just too much data to retrieve in the cloud for every training job at the same time predictive analytics without accuracy is not going to deliver the business advantage of what everyone is seeking you know we see this the visualization of data analytics is traditionally deployed as being on a continuum with you know the things that we've been doing in the long you know in the past you know with data warehousing data lakes AI on the other end but but this way we're starting to manifest it in organizations that are looking towards you know getting more utility and better you know elasticity out of the data that they are working for so they're not looking to just build ups you know silos of bespoke AI environments they're looking to leverage you know a platform that can allow them to you know do a I for one thing machine learning for another leverage multiple protocols to access that data because the tools are so much different you know it is a growing diversity of of use cases that you can put on a single platform I think organizations are looking for as they try to scale these environments I think there's gonna be a big growth area in the coming years Gabe well I wish we were in Boston together you would have painted your little corner of Boston Orange I know that you guys are sure but I really appreciate you coming on the cube and thank you very much have a great day you too okay thank you everybody for watching this is the cubes coverage wall-to-wall coverage two days of the vertical Vertica virtual Big Data conference keep her at their very back right after this short break

>> live from Boston, Massachusetts. It's the Cube covering A W s reinforce 2019 brought to you by Amazon Web service is and its ecosystem partners come >> back, Everyone live Coverage of AWS reinforced their first conference, The Cube here in Boston. Messages some jumper. MacOS David Lattin escapes Jesse rusting >> CT on co >> founder of Extra Cube alumni. Great to see you again. VM World Reinvent >> Now the new conference reinforce not a team. A >> summit reinforced a branded event around Cloud security. This is in your wheelhouse. >> Thank you for having me. Yeah, it's a spectacular event. Unbelievable turnout. I think there's 8000 people here. Maybe more. I know that's what they were expecting for an event that was conceived of, or at least announced barely six months ago. The turnout's just >> wait. Many conversation in the past on the Cube and others cloud security now having its own conference. It's not like a like a security conference like Black at Def Con, which is like a broader security. This is really focused on cloud security and the nuances involved for on premises and cloud as it's evolving. It's certainly a lot more change coming on this kind of spins into your direction you would talking this year in the front end. >> It absolutely does. First, it speaks to market demand. Clearly, there was demand for a cloud security focused conference, and that's why this exists. Every survey that I've seen lists security extremely high on the list of anxieties or even causes for delay for shifting workloads to the cloud. So Amazon takes security extremely seriously. >> And then my own personal >> view is that cloud security has been somewhat nascent and immature. And we're seeing, you know, hopefully kind of Ah, somewhere rapid, a >> lot of motivation in that market. Certainly a lot of motivated people want to see it go faster and there spitting in building that out. So I gotta ask >> you before you get off the show, I actually say something if I may. I mean, it's been a long time coming. Yeah, this to your point, Jesse. There was a real need for it, and I think Amazon deserves a lot of credit for that. But at the same time, I think Amazon. There's a little criticism there. I mean, I think that the message that reinvent that's always been we got the best security. We got the most features as I come on in, and the whole theme here of the shared responsibility model, which I'd love to get into, I think was somewhat misunderstood by some of those high high level messaging. So I didn't want to put that out there as a topic that we might touch on. Great. Let's talk about it. Okay, so I do think it was misunderstood. The shared responsibility model. I think the messaging was Hey, the cloud is more secure than your existing data centers. Come on in. And I think a lot of people naively entered waters and then realized, Oh, wait a minute. There's a lot that we still have toe secure. We can't just set it and forget it. I mean, you agree with that? >> I I think that's a controversial topic. I do agree with it. I think it continues to be misunderstood. Shared responsibility model in some ways is Amazon saying We're going the security infrastructure and we're going to give you the tools. But organizations air still expected to follow best practices, certainly, and implement their own, hopefully best in class security operations. >> It's highly nuanced. You can say sharing data see increases visibility into into threats and also of making quality alerts. But I think it's a little bit biased, Dave for Amazon to satiate responsibility because they're essentially want to share in the security posture because they're saying we'll do this. You do that as inherently shared. So why wouldn't they say that? >> Well, I guess we're gonna say way want to own everything? Well, I guess my weight So this show is that I really like their focus on that. I think they shone a light on it and for the goodness of the the industry in the community they have. But it is a bit >> nuanced, and they've said some controversial, perhaps even trajectory statements. In the keynote yesterday, I was I was amused to hear that security is everybody everyone's job, which is something I wholeheartedly believe in. But at the same time, you know, David said that he didn't believe Stephen Step Rather said that he didn't believe in depth set cops, and that seemed a little bit of odds because I but I think they're probably really Steven Schmidt. Steven >> so eight of us. But at the same time, there was a narrative around. Security is code. So, yes, there were some contradictions in messaging, so this smaller remains small ones. They were nuanced but remains some confusion. And that's why people look to the ecosystem to help acorns. And this goes back to >> my earlier point. I I believe that cloud security is really quite nascent. When we look at the way we look at the landscape of vendors, we see a number of vendors that really are kind of on Prem security solutions. They're trying to shoehorn into the cloud way, see a lot of essentially vulnerability scanning and static image scanning. But wait, don't see, in my opinion, that much really best in class security so solutions. And I think until relatively recently it was very hard to enable some of them. And that's why I'd love to talk about the VPC traffic marrying announcement, because I think that was actually the most impactful announcement >> that I want to get to it. So So this is ah, a new on the way. By the way, the other feedback up ahead on the Cube is the sessions here have been so good because you can dig deeper than what you can get it re invent given tries. This is a good example. Explained that the that story because this has been one of the most important stories, the traffic mirroring >> well, unlike >> reinvent. I think this show is Is Maura about education than it is about announcements? No, Amazon announced. A few new service is going into G ET, but these were service is, for the most part, that we already knew you were coming here like God Watchtower in security hub. But the BBC traffic mirroring was really the announcement of this show. And, gosh, it's been a long time in coming 11 closely held belief I've had for a long time is that in the fullness of time, there's really nothing of value that that you can do on Prem that you wouldn't eventually be able to do in the cloud. And it's just been a head scratcher for me. WIFE. For so many years, we've been unable to get any sort of view, mirror or tap of the traffic for diagnostic or analytic purpose is something you could do on prim so easily, with a span porter and network tap and in the cloud we've been having to do kind of back flips and workarounds and software taps and things like that. But with this announcement, it's finally here. It's native >> explain VPC Chapman. What is it for? The folks watching might not know it. Why it's wife. What is it and why is it important? >> So BBC traffic marrying is a network tap that is built into E. C. To networking. What it means is that you can configure a V p c traffic mirror four individual E C two instances actually down to the e n I. Level. You can configure filters and you can send that to a target for analysis purposes. And this analysis could be for diagnostics. But I think much more important is for security. Extra hop is is really began as a network analytics platform way do network detection and response. So this type of this ability to analyze the traffic in real time to run predictive models against it to detect in real time suspicious behaviors and potential threats, I think is absolutely game changing for someone security posture. >> And you guys have been on the doorstep of this day in day out. So this is like a great benefit to you guys. As a company, I can see that. I see That's a great thing for you guys. What's the impact of the customers? Because what is the good news that comes out of the traffic nearing for them? What's the impact of their environment? >> Well, it's all about >> friction. First, I wantto clarify that we've been running in a WS for over six years, six or seven years, so we've had that solution. But it's required some friction in the deployment process because our customers had to install some sort of software tap, which was usually an agent, that was analyzing that there was really gathering the packets in some sort of promiscuous mood and then sending them to us in a tunnel. Where is now? This is This is built into the service into the infrastructure. There's no performance penalty at all. You can configure it. You have I am rolls and policies to secure it. All of the friction goes away. I think, for the kind of the first time in in cloud history, you can now get extremely high quality network security analytics with practically the flip of a switch. >> So It's not another thing do manage. It's like you say, inherit to the network. John and I have heard this this week at this event from practitioners that they want to see less just incremental security products and Maur step function and what they mean by that is way want products that actually take action or give us a script that we can implement, or or actually fix the problem for us. Will this announcement on others that you guys were involved in take that next step more proactive security that these guys so a couple of thoughts >> on that first, the answer is yes, it can, and you're absolutely right. Remediation is extremely important, especially for attacks that they're fast and destructive. When you think about kind of the when you think about attack patterns, their attacks are low and slow. Their attacks their advanced in persistent but the taxes, air fast and destructive movie the speed that is really beyond the ability for humans to respond. And for those sorts of attacks, I think you absolutely need some sort of automated remediation. The most common solutions are some form of blocking the traffic, quarantining the traffic or maybe locking the accounts, and you're kind of blocking. Quarantining and locking are my top three, and then various forms of auditing and forensics go along the way. Amazon actually has a very good tool box for that already. And there are security orchestration, products that can help. And for products like extra hop, the ability to feed a detection into an action is actually a trivial form of integration that we offer out of the box. So the answer is yes. >> But let me go >> back to kind of the incrementalist approach as well that you mentioned. I kind of think about the space and really, really broad strokes and organizations for the last 10 years or so have really highly invested in prevention and protection. So a lot of this is your perimeter defense and in point protection, and the technologies have gotten better. Firewalls have turned into next generation firewalls and antivirus agents have turned into next generation anti virus or in point detection and response. But I strongly believe that network security has and in some ways just kind of lagged behind, and it's really ripe for innovation. And that's why that's what we've really spent the last decade >> building. And that's why you're excited about the traffic BPC traffic nearing because it allows for parallel analytics and so more real time, >> more real >> time. But the network has great properties that nothing else has. When you think about network security with the network itself is close to ground Truth as you can get, it's very hard to tamper with, and it's impossible to turn off those air great properties for cyber security. And you can't say that about something like that. Logs, which are from time to time disabled and scrubbed on. You certainly can't say that about en Pointe agents, which are often worked around and in some cases even used as a better for attack. >> I'm gonna ask you Okay, on that point, I get that. So the next question would come to my mind is okay with the surface here. With coyote expanding and with cloud, you have a sprawling surface area. So the surface area is growing just by default by natural evolution, connecting to the cloud people of back hauling their data into the cloud. All this is good stuff. >> Absolutely. Call it the attack surface, and it is absolutely glowing perhaps in an exponential >> about that dynamic, one sprawling attack air. Because that's just the environment now. And what's the best practice to kind of figure out security posture? Great, great >> question. People talk a lot about the dissolution of the perimeter, and I think I think that's a bit of the debate. And regardless of your views on that, we can all believe that the perimeter is changing and that workloads are moving around and that users are becoming more mobile. But I think an extremely important point is that every enterprise just about is hybrid. So we actually need protection for a hybrid attack surface. And that's an area where I believe extra hop offers a great solution because we have a solution that runs on premises in physical data centers are on campuses, which, no matter how much work, would you move to the cloud. You still have some sort of user on some sort of laptop or some sort of work station in some sort of campus environment, way workin in private cloud environments that are virtualized. And then, of course, we work in public cloud environments, and another announcement that we just made it this show, which I also think is game changing, is our revealed ex cloud offering. So this is an SAS. This is a sass based, network detection and response solution, which means that I talked about removing friction by marrying the traffic. But in this case, all >> you have to >> do is mirror the traffic, pointed to our sass, and we'll do all of the management mean that So is that in the streets for you that is in the marketplace. We launched it yesterday, >> So it's great integration point for you guys. Get it, get on board more customers. >> And I think I think solutions like ours are absolutely best practices and required to secure this hybrid attacks in the >> marketplace. What was that experience like, you know, Amazon >> was actually great to work with. I don't mean to say that with disbelief. You work with you work with such a large company. You kind of have certain expectations, and they exceeded all of my expectations in terms of their responsiveness. They worked with us extremely closely to get into the marketplace. They made recommendations with partners who could help accelerate our efforts. But >> in addition to the >> marketplace, we actually worked with them closely on the VPC traffic marrying feature. There was something we began talking with them about a SW far back, as I think last December, even before reinvent, they were extremely responsive to our feedback. They move very, very quickly. They've actually just >> been a delight to work. There's a question about you talking about the nana mutability of logs, and they go off line sometimes. And yet the same time there's been tens of $1,000,000,000 of value creation from that industry. Are there things that our magic there or things that you can learn from the analytics of analyzing logs that you could bring over to sort of what you're positioning is a more modern and cloud like approach? Or is there some kind of barrier to entry doing that? Can you shed some light on Jesse? That's >> a great question, and this is where I'll say it's a genius of the end situation, not a tyranny of the or so I'm not telling people. Don't collect your logs or analyze them. Of course you should do that, you know that's the best practice. But chances are that that space, you know, the log analysis and the, you know, the SIM market has become so mature. Chances are you're already doing that. And I'm not gonna tell organizations that they shouldn't have some sort of point protection. Of course you should. But what I am saying is that the network itself is a very fundamental data source that has all of those properties that are really good for cyber security and the ability that analyze what's going on in your environment in real time. Understand which users air involved? Which resource is air accessed? And are these behavioral patterns of suspicious and do they represent potential threats? I think that's very powerful. I have a I have a whole threat research team that we've built that just runs attacks, simulations and they run attack tools so that we can take behavioral profiles and understand what these look like in the environment. We build predictive models around how we expect you re sources and users and end points to behave. And when they deviate from those models, that's how we know something suspicious is going on. So this is definitely a a genius of the end situation. John >> reminds me of your you like you're very fond of saying, Hey, what got you here is not likely to move you forward. And that's kind of the takeaway for practitioners is >> yeah. I mean, you gotta build on your success. I mean, having economies of scale is about not having Disick onyx of scale, meaning you always constantly reinventing your product, not building on the success. And then you're gonna have more success if you can't trajectory if you it's just basic competitive strategy product strategy. But the thing that's interesting here is is that as you get more successful and you continue to raise the bar, which is an Amazon term, they work with you better. So if you're raising the bar and you did your own network security probably like OK, now we get parallel traffic mirroring so that >> that's true. But I think we've also heard the Amazon is I think they caught maniacally customer focused, right? And so I think that this traffic marrying capability really is due to customer demand. In fact, when you when you were if you were at the Kino when they made the announcement, that was the announcement where I feel like every phone in the in the whole auditorium went up. That's the announcement where I think there's a lot of excitement and for security practitioners in particular, and SEC ops teams I think this. I think this really reduces some anxiety they have, because cloud workloads really tend to be quite opaque. You have logs, you have audit logs, but it's very difficult to know what actually going on there and who is actually accessing that environment. And, even more important, where is my data going? This is where we can have all sorts of everything from a supply chain attack to a data exfiltration on. It's extremely important to to be able to have that visibility into these clouds >> way agree. We've been saying on the cue many, many years now that the network is the last bottleneck, really, where that script gets flipped upside down where Workloads air dictating Dev ops. Now the network piece is here, so I think this is going to create a lot of innovation. That's our belief. Love to follow up Mawr in Palo Alto. When we get back on this hybrid cloud, I think that's a huge opportunity. I think there's a create a blind spot for companies because that's where the the attackers will go, because they'll know that the hybrids rolling out and that'll be a vulnerability area >> one that's, you know, it's an arms race. Network security is not new. It's been around for decades. But the attack the attackers in the attacks have become more sophisticated, and as a result, you know the defenders need to raise their game as well. This is why, on the one hand, there's there's so much hype and I think machine learning in some ways is oversold. But in other ways, it is a great tool in our arsenal. You know, the machine learning the predictive models, the behavioral models, they really do work. And it really is the next evolution for defensive >> capabilities. Thanks for coming on. Great insight. >> One last question. The beer. Extra guys have been here way did in the past. It's been a while since >> we've done that, but it comes from early days when when I founded the company, people would ask you in the name extra hoppy. Oh, are you guys an online brewery? And we were joking. We said no, that that was extra hops way embraced it and We actually worked with a local brewer that has since been acquired by a major beverage brands. I >> don't know that. I just heard way built our own >> label, and it was the ex Rob Wired P. A. It was it was extremely well received. Every time we visit a customer they'd ask us to bring here. >> That's pretty. You gotta go back to proven formula. Thanks for the insights. Let's follow up when we get back in Palo Alto in our studio on his high breathing's a compelling conversation network Security Network analytics innovation areas where all the action's happening here in Boston, 80 best reinforced. Keep coverage. We'll be right back.

>> (Narrator) From the Computer Museum in Mountain View, California, it's theCUBE. Covering ACG Silicon Valley GROW! Awards. Brought to you by ACG Silicon Valley. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're at the ACGSV 14th Annual GROW! Awards About 300 people. It's their annual event to give out a couple innovation awards. We're excited to be here, it's our 3rd year. And we're happy to have a board member on. He's Andy Armstrong, a partner at SingerLewark. Andy, great to see you. >> Hey, excited to be here. >> (Jeff) So you said you've been on the board for about a year. >> Yes. >> Why on the board? What is this organization about? Why are you excited to be part of it? >> So actually, this last year's been incredible for me with my affiliation with the group. So the board, I was able to join so I could co-sponsor and lead the young accelerator program with Jim Chapman. And what we do is, we take young start-up companies and work with them. We create a panel of experts that is about 5-6 experts and we sit down for two hour increments with these companies and really try to work out some of the issues that they might be beating their head against the wall. And we kind of help them try to jump over those hurdles that they're facing and take them to the next level. >> How old are they generally when they're in this process? In terms of number of employees or age or, how do you bucket it? >> Pretty young start up companies. I would say some are pre-revenue. Others, they might have 5 to 10 employees and they maybe have anywhere from pre-revenue to a million dollars worth of revenue, just kind of moving up the ladder so to speak. >> Right, and they don't have to be a client of your guys to participate. >> Absolutely not, no. Really we're looking for kind of open-minded executives that are really wanting to take advantage and tap in to some of the phenomenal executives that are part of ACG, as well as here in Silicon Valley. >> Right, and then you said your firm is also very involved in southern California. So there's a number of chapters of ACG. >> Absolutely. There's chapters of ACG throughout the country. The president of ACGLA for example is one of my partners down in my firm in LA. My marketing director runs one of the largest ACG conferences in the country, which is down in LA every September, so. >> Yeah, we're heavily involved as a firm in ACG. >> So we're pretty tech focused up here. Obviously, were in the Computer History Museum and I'm curious in southern California, what are some of the industries that you guys really help and leverage? >> You know, we work a lot with down there a lot of public companies. We do a lot of public company audits. We also work with what we call our family and entrepreneurially owned companies. So we like to say that's the life blood of SingerLewark, in terms of working with companies, again big or small, mom and pop, but that's really what the focus is down there. >> Right. So, biggest surprise in working with some of these entrepreneurs. It's always fun to work with people that are getting started, they're so enthusiastic. What are some of the kind of surprises as you've worked through some of those sessions with them? >> You know, maybe not surprises, but just the realization of, they're young. They're hitting their head against the wall just like you and I do sometimes. >> Right. >> And I think it's fun to get in to that environment in the accelerator because it's what I like to call a safe environment for them. It's not like they're coming in to pitch for an investment. They're coming in and kind of airing some dirty laundry and just kind of opening up and being honest with us. And that's where they get the most out of that program. >> Right and I would imagine they get quite a bit also from their peers in that environment as well. >> Um >> (Jeff) Maybe not. (laughter) >> Yeah, well in terms of the peers on our panel, absolutely. I don't know in terms of the peers, in terms of how much they're networking with their competitors so to speak. >> (Jeff) Right, right. >> It's phenomenal the experience that each one of these companies has. >> Competitions a big part of what drives us up here, for sure, so. You know, can be a partner in one area, you can be a competitor in the other, and you know, there's so many places and so much opportunity in a lot of the growth areas as well. So there's a lot of room to run. >> Yeah, absolutely. It's great. >> Well, Andy, I'll give you the last word. What are you looking forward to tonight? >> You know, it's fun just to get into a room full of top executives, very successful people here in the Bay Area. To get to kind of rub shoulders and meet and talk to them and just appreciate the success that ACG has had in working with these kind of people. >> Yeah, they bring in good ones for sure. Pat Gelsinger, will be keynoting tonight. He's been on theCUBE many times, really doing great things at VMware. So it should be a good evening. >> (Andy) It's really exciting. >> Alright, well, he's Andy Armstrong and I'm Jeff Frick. You're watching theCUBE from the 14th Annual ACGSV Awards. Thanks for watching. (tech music)