(Intro music) >> Welcome back. We're LIVE here from SuperComputing 22 in Dallas Paul Gillin, for Silicon Angle in theCUBE with my guest host Dave... excuse me. And our, our guest today, this segment is Kim Leyenaar who is a storage performance architect at Broadcom. And the topic of this conversation is, is is networking, it's connectivity. I guess, how does that relate to the work of a storage performance architect? >> Well, that's a really good question. So yeah, I have been focused on storage performance for about 22 years. But even, even if we're talking about just storage the entire, all the components have a really big impact on ultimately how quickly you can access your data. So, you know, the, the switches the memory bandwidth, the, the expanders the just the different protocols that you're using. And so, and the big part of is actually ethernet because as you know, data's not siloed anymore. You have to be able to access it from anywhere in the world. >> Dave: So wait, so you're telling me that we're just not living in a CPU centric world now? >> Ha ha ha >> Because it is it is sort of interesting. When we talk about supercomputing and high performance computing we're always talking about clustering systems. So how do you connect those systems? Isn't that, isn't that kind of your, your wheelhouse? >> Kim: It really is. >> Dave: At Broadcom. >> It's, it is, it is Broadcom's wheelhouse. We are all about interconnectivity and we own the interconnectivity. You know, you know, years ago it was, 'Hey, you know buy this new server because, you know, we we've added more cores or we've got better memory.' But now you've got all this siloed data and we've got you know, we've got this, this stuff or defined kind of environment now this composable environments where, hey if you need more networking, just plug this in or just go here and just allocate yourself more. So what we're seeing is these silos really of, 'hey here's our compute, here's your networking, here's your storage.' And so, how do you put those all together? The thing is interconnectivity. So, that's really what we specialize in. I'm really, you know, I'm really happy to be here to talk about some of the things that that we do to enable high performance computing. >> Paul: Now we're seeing, you know, new breed of AI computers being built with multiple GPUs very large amounts of data being transferred between them. And the internet really has become a, a bottleneck. The interconnect has become a bottle, a bottleneck. Is that something that Broadcom is working on alleviating? >> Kim: Absolutely. So we work with a lot of different, there's there's a lot of different standards that we work with to define so that we can make sure that we work everywhere. So even if you're just a dentist's office that's deploying one server, or we're talking about these hyperscalers that are, you know that have thousands or, you know tens of thousands of servers, you know, we're working on making sure that the next generation is able to outperform the previous generation. Not only that, but we found that, you know with these siloed things, if, if you add more storage but that means we're going to eat up six cores using that it's not really as useful. So Broadcom's really been focused on trying to offload the CPU. So we're offloading it from, you know data security, data protection, you know, we're we do packet sniffing ourselves and things like that. So no longer do we rely on the CPU to do that kind of processing for us but we become very smart devices all on our own so that they work very well in these kind of environments. >> Dave: So how about, give, give us an example. I know a lot of the discussion here has been around using ethernet as the connectivity layer. >> Yes. >> You know, in in, in the past, people would think about supercomputing as exclusively being InfiniBand based. >> Ha ha ha. >> But give, give us an idea of what Broadcom is doing in the ethernet space. What, you know, what's what are the advantages of using ethernet? >> Kim: So we've made two really big announcements. The first one is our Tomahawk five ethernet switch. So it's a 400 gigi ethernet switch. And the other thing we announced too was our Thor. So we have, these are our network controllers that also support up to 400 gigi each as well. So, those two alone, it just, it's amazing to me how much data we're able to transfer with those. But not only that, but they're super super intelligent controllers too. And then we realized, you know, hey, we're we're managing all this data, let's go ahead and offload the CPU. So we actually adopted the Rocky Standards. So that's one of the things that puts us above InfiniBand is that ethernet is ubiquitous, it's everywhere. And InfiniBand is primarily just owned by one or two companies. And, and so, and it's also a lot more expensive. So ethernet is just, it's everywhere. And now with the, with the Rocky standards, we're working along with, it's, it's, it does what you're talking about much better than, you know predecessors. >> Tell us about the Rocky Standards. I'm not familiar with it. I'm sure some of our listeners are not. What is the Rocky standard? >> Kim: Ha ha ha. So it's our DNA over converged to ethernet. I'm not a Rocky expert myself but I am an expert on how to offload the CPU. And so one of the things it does is instead of using the CPU to transfer the data from, you know the user space over to the next, you know server when you're transferring it we actually will do it ourselves. So we'll handle it ourselves. We will take it, we will move it across the wire and we will put it in that remote computer. And we don't have to ask the CPU to do anything to get involved in that. So big, you know, it's a big savings. >> Yeah, I mean in, in a nutshell, because there are parts of the InfiniBand protocol that are essentially embedded in RDMA over converged ethernet. So... >> Right. >> So if you can, if you can leverage kind of the best of both worlds, but have it in an ethernet environment which is already ubiquitous, it seems like it's, kind of democratizing supercomputing and, and HPC and I know you guys are big partners with Dell as an example, you guys work with all sorts of other people. >> Kim: Yeah. >> But let's say, let's say somebody is going to be doing ethernet for connectivity, you also offer switches? >> Kim: We do, actually. >> So is that, I mean that's another piece of the puzzle. >> That's a big piece of the puzzle. So we just released our, our Atlas 2 switch. It is a PCIE Gen Five switch. And... >> Dave: What does that mean? What does Gen five, what does that mean? >> Oh, Gen Five PCIE, it's it's a magic connectivity right now. So, you know, we talk about the Sapphire Rapids release as well as the GENUWA release. I know that those, you know those have been talked about a lot here. I've been walking around and everybody's talking about it. Well, those enable the Gen Five PCIE interfaces. So we've been able to double the bandwidth from the Gen Four up to the Gen Five. So, in order to, to support that we do now have our Atlas two PCIE Gen Five switch. And it allows you to connect especially around here we're talking about, you know artificial intelligence and machine learning. A lot of these are relying on the GPU and the DPU that you see, you know a lot of people talking about enabling. So by in, you know, putting these switches in the servers you can connect multitudes of not only NVME devices but also these GPUs and these, these CPUs. So besides that we also have the storage component of it too. So to support that, we we just recently have released our 9,500 series HBAs which support 24 gig SAS. And you know, this is kind of a, this is kind of a big deal for some of our hyperscalers that say, Hey, look our next generation, we're putting a hundred hard drives in. So we're like, you know, so a lot of it is maybe for cold storage, but by giving them that 24 gig bandwidth and by having these mass 24 gig SAS expanders that allows these hyperscalers to build up their systems. >> Paul: And how are you supporting the HPC community at large? And what are you doing that's exclusively for supercomputing? >> Kim: Exclusively for? So we're doing the interconnectivity really for them. You know, you can have as, as much compute power as you want, but these are very data hungry applications and a lot of that data is not sitting right in the box. A lot of that data is sitting in some other country or in some other city, or just the box next door. So to be able to move that data around, you know there's a new concept where they say, you know do the compute where the data is and then there's another kind of, you know the other way is move the data around which is a lot easier kind of sometimes, but so we're allowing us to move that data around. So for that, you know, we do have our our tomahawk switches, we've got our Thor NICS and of course we got, you know, the really wide pipe. So our, our new 9,500 series HBA and RAID controllers not only allow us to do, so we're doing 28 gigabytes a second that we can trans through the one controller, and that's on protected data. So we can actually have the high availability protected data of RAID 5 or RAID 6, or RAID 10 in the box giving in 27 gigabytes a second. So it's, it's unheard of the latency that we're seeing even off of this too, we have a right cash latency that is sub 8 microseconds that is lower than most of the NVME drives that you see, you know that are available today. So, so you know we're able to support these applications that require really low latency as well as data protection. >> Dave: So, so often when we talk about the underlying hardware, it's a it's a game of, you know, whack-a-mole chase the bottleneck. And so you've mentioned PCIE five, a lot of folks who will be implementing five, gen five PCIE five are coming off of three, not even four. >> Kim: I know. >> So make, so, so they're not just getting a last generation to this generation bump but they're getting a two generations, bump. >> Kim: They are. >> How does that, is it the case that it would never make sense to use a next gen or a current gen card in an older generation bus because of the mismatch and performance? Are these things all designed to work together? >> Uh... That's a really tough question. I want to say, no, it doesn't make sense. It, it really makes sense just to kind of move things forward and buy a card that's made for the bus it's in. However, that's not always the case. So for instance, our 9,500 controller is a Gen four PCIE but what we did, we doubled the PCIE so it's a by 16, even though it's a gen four, it's a by 16. So we're getting really, really good bandwidth out of it. As I said before, you know, we're getting 28, 27.8 or almost 28 gigabytes a second bandwidth out of that by doubling the PCIE bus. >> Dave: But they worked together, it all works together? >> All works together. You can put, you can put our Gen four and a Gen five all day long and they work beautifully. Yeah. We, we do work to validate that. >> We're almost out our time. But I, I want to ask you a more, nuts and bolts question, about storage. And we've heard for, you know, for years of the aerial density of hard disk has been reached and there's really no, no way to excel. There's no way to make the, the dish any denser. What is the future of the hard disk look like as a storage medium? >> Kim: Multi actuator actually, we're seeing a lot of multi-actuator. I was surprised to see it come across my desk, you know because our 9,500 actually does support multi-actuator. And, and, and so it was really neat after I've been working with hard drives for 22 years and I remember when they could do 30 megabytes a second, and that was amazing. That was like, wow, 30 megabytes a second. And then, about 15 years ago, they hit around 200 to 250 megabytes a second, and they stayed there. They haven't gone anywhere. What they have done is they've increased the density so that you can have more storage. So you can easily go out and buy 15 to 30 terabyte drive, but you're not going to get any more performance. So what they've done is they've added multiple actuators. So each one of these can do its own streaming and each one of these can actually do their own seeking. So you can get two and four. And I've even seen a talk about, you know eight actuator per disc. I, I don't think that, I think that's still theory, but but they could implement those. So that's one of the things that we're seeing. >> Paul: Old technology somehow finds a way to, to remain current. >> It does. >> Even it does even in the face of new alternatives. Kim Leyenaar, Storage Architect, Storage Performance Architect at Broadcom Thanks so much for being here with us today. Thank you so much for having me. >> This is Paul Gillin with Dave Nicholson here at SuperComputing 22. We'll be right back. (Outro music)

(upbeat music) >> Hey everyone. Welcome back to San Francisco, VMware Explorer 2022, Lisa Martin and Dave Nicholson here. We've been having some great conversations today. Lots of news coming out about VMware and its partner ecosystem. We're going to have another conversation about that next. Please welcome two guests to the program, Chance Bingen, technical marketing engineer at NetApp and Jason Massae, staff technical marketing architect, storage and vVols at VMware. Guys, welcome to the program. >> Thanks. >> Glad to be here. >> It's nice to be back in person. >> It is. It's very nice. Oh my gosh. >> And we're hearing there about 7,000 to 10,000 people here, when I was in the Keynote, this morning it was definitely standing room only. >> Yeah, yeah. You've definitely seen the numbers ticked up at the last minute. It was good to see that. It's good, I think a lot of people have really wanted to get back, get that one on one that face to face. There's nothing like being able to, you know, talk to, the experts, talk to the vendors, you know, see your comrades. I mean, that's the thing. I mean, we've seen people that I haven't seen for years, even on my own team, so really good to be back into it. >> It is and it was lots of news coming out this morning during the Keynote. My goodness. But Jason, talk to me, the NetApp and VMware folks had been in tight partnership for a long time. Talk to me about, get both of your perspective from a technical perspective about the depth of the partnership. >> Yeah, so actually NetApp was one of the original design partners for vVols. And with that, now with some of the stuff we're doing with more current stuff with virtual volumes is, NetApp is back and we've got some pretty neat stuff that we've been working on with vVols. And NetApp's got some pretty neat stuff that they've been working on to enable the customers with more features, more functionality with the virtual volume functionality. >> Yeah, absolutely. >> Give us a quick primer on what is a vVol? What is a virtual volume? How does it fit into the, into this stack of stuff that we do in IT? >> Yeah. So the easiest way to kind of think of what a vVol is or a virtual volume is you can think of it kind of like an RDM, those row device map, which is kind of a four letter word. We don't really like those, but the idea is that object, that virtual volume is native on the array and presented directly to the VM. But now what we do is we're presenting all of the storage array features up to vSphere and we're managing those storage features via policy based management. But instead of applying storage capabilities at a data store level, we're now applying them at a VM or an application level. So you can have one data store and multiple VMs, and every VM can have a different storage capability managed by a policy that the VI admin gets to manage now. So he doesn't have to go to the storage admin to say, I need a new line, or I need a new volume. He can just go in and create a policy or change a policy. And now that storage capability is applied to the VM or the application. >> Yeah. One thing I'd like to add to that is you can mentioned the word capabilities. >> So we look at the actual data protocols, whether they're file based or block based, you know, I-scuzzy, fiber channel, whatever the case might be. Those protocols have defined sets of capabilities and attributes and things they can expose. What vVols along with the VASA protocol brings to the table is the ability to expose things that are just impossible to expose via the data protocols themselves. So that the, actual nature of the array, what kind of array is it? What's it capable of doing? What is the nature of, you know, encryption? You know, is this going to be a secure, encrypted data store? Is it going to be something else? It just allows you to do so much more with the advanced capabilities that modern storage arrays have than you could ever do if you were just using the data protocols by themselves. >> Right? Yeah. Kind of under that same context. If you think about before with traditional storage, the vSphere or the array really doesn't understand what's going on underlying storage, but with vVols the array and vSphere completely understand at a disc level even, how that VM should be treated. So that helps the storage admin. Storage admin can now go in and see a specific disc of a VM and see the performance on the array. They can go in the array and see, oh, this disc on this VM has got performance issues or needs to be encrypted, or here's the size of that disc. And you couldn't easily see that with your traditional storage. So there's really a lot of benefits and it frees up a lot of time for the storage administrator and enables the VI admin to be able to do a lot of the storage management. >> So there have been, there been a lot of movements over the last decade in the realm of software defined storage. Where essentially all of the things that you are talking about are completely abstracted from the underlying hardware. In this case, you're leveraging the horsepower, if you will and the intelligence of a storage array that has a lot of horsepower and intelligence, and you're accessing those features. You mentioned encryption, whether if you're doing a snapshot or something like that, what's interesting here is it kind of maps to what we're looking at now, which is the trend in the direction of things like DPUs. >> If you go back in history long enough, we had the, you know, the TOE, NIC, TCP offload, you know, the idea of, hey, you know what, what if we had a smart device with its own brain power and we leveraged it. Well, you guys have been doing that from a vVols all perspective with NetApp filers, for lack of better term. For how long now, when did, when were they originally? >> 6.0 it was so it's been what? 11, 12 years. Something like that. >> It's been a while. So yeah, but it's been a decade or so. >> Mm-hmm >> So what's on the frontier. What's the latest there in terms of, in terms of cool stuff that's coming out. >> So actually today, in one of the things that we worked with NetApp that was part of the design partnership was, you know, the NVMe over Fabric protocol has become very popular to extend that functionality of all flash to the, an external array. And now we announce today, in including with that NVMe over Fabrics, you can now do vVols with NVMe over Fabrics. And again, that was something that we worked with NetApp to be a design partner for them. >> That's right. We're very excited about it. We've always been, you know, NVMe been something we've been very proud of for a while. Delivering the first end to end NVMe stack from inside the host, through the fabric, to the array, with the arrays front ports, all the way to the disc on the backend. So we're very excited about that. >> So target market joint NetApp, VMware customers, I presume. >> Really it's, the key here that I like to make sure customers understand is to see that vVols are on the leading edge of VMware's storage design. Some tend to think that maybe vVols wasn't the primary focus, but actually now it is the primary focus. Now I always like to give the caveat that VMFS and NFS are not going away. Those are still very much stuff that we work on. It's just that most of the engineering focus is on virtual volumes or vVols. >> Yeah. Similarly, when you talk about and you're sort of alluding to vSAN when we start talking about VMFS and things like that. >> Yeah. >> Architecturally, we've been talking to folks about the recent announcements with capabilities within AWS. You know, NetApp in AWS for VMware environments. Breaking out of the stranglehold that the, oh, you want more storage, you must buy more CPU and memory, building block process entails. The reality is no matter what you do with vSAN, you're going to have certain constraints that go away when now you have the option to leverage storage from the NetApp filers. >> Yeah, absolutely. >> So how does, how do vVols play in the cloud strategy moving forward? >> Well, so one of the things that we do with, vVols currently is mostly On-prem. But when you have the storage architecture, that vVols gives you as far as individual objects, it makes it much easier to migrate up into the cloud because you're not trying to migrate individual VMs that are on another type of system, whatever it might be, those objects are already their own entity. Right, so cloud, Tanzu, those type of things, those vVol objects are already their own entity. So it makes it very easy to migrate them on and off prem. >> So Chance talk to us a little bit about this from NetApp's perspective. You're in customer conversations, who are you talking to? Is this primarily an engineering conversation? Has this gone up the stack in terms of customers are finding themselves in this default multi-cloud environment? >> Yeah, so interestingly, when I talk to customers these days they are almost all either on a journey to a hybrid multi-cloud or they're in some kind of phase of transforming themselves into their own hyperscaler, right? They're be adopting a cloud service provider model and vVols is a perfect fit for that kind of model, because you have the ability to offer different tiers of service, different qualities of service with VM granular controls or VMDK granular controls, even. And even if you look at First Class Disc, right? Which is something that came out largely to support Tanzu, I think which fantastic use case for vVols as well there, but that gives you the ability to offer something like Amazon EBS, right? You can offer Amazon EBS in a native VMware stack using First Class Discs and vVols. And you're able to apply things like quality of service with that granular control that allows you to guarantee that customer the disc that they bought and paid for. They're going to get the IOPS that they're paying for because you're applying those QoS policies directly to that object on the array. And instead of having to worry about is the array going to be able to handle it? Are you going to have one VM that consumes all your IO, you know? You don't have to worry about that with vVols because you've got that integration with the array's native quality controls. >> And Chance what's in this for me as a customer? I'm hearing productivity, I'm hearing cost savings, control efficiency. Talk to me about the benefits in it for the folks that you're talking to. >> Yeah, absolutely. A lot of times it comes down to, you know I mentioned like the cloud service provider model, right? When you're looking to build a robust service catalog and you're able, you want to be able to meet all these like, we mentioned Tanzu, right? Containers as a service, you're able to provide the persistent volumes for your Kubernetes containers that are again, these native objects on the array and you have these fine grain controls, but it's handled at massive scale because it's all handled by storage policies, Kubernetes storage classes, which are natively mapped to VM storage policies through Tanzu. So it just, it gives you the ability to offer all of these services in a, again a rich and robust contents catalog. >> So what are you doing? So you mentioned a couple of things in terms of using array based quality of service. So give me an example of how you're avoiding issues of contention and over subscription in an environment where I'm an administrator and I've got this virtual volume that's servicing this VM or this app on this VM. What kind of visibility do I have down into the actual resources because look at the end of that chain there's a physical resource. And that physical resource represents, what? IOPS and bandwidth and latency and throughput and all of this bundle of things. So how do you avoid colliding with others who are trying to carve vVols out of this world? >> You mean like a noisy neighbor type of thing? >> Yeah. Yeah. >> So that's actually one of the big benefits that you get with vVols is that because those vial objects are native on the array, they're not sharing a loan or a volume. They're not sharing a resource. The only resource they're actually sharing is the array itself. So you don't get that typical noisy neighbor where this one's using all the resources of that volume because really you're looking out at the all encompassing array. And so a storage administrator and the VI admin have a lot more insight. The VI admin can now go to the storage admin if there's say a debugging issue, they want to find a problem. The storage admin now can see those individual objects and say, oh, well this VM, it's not really this, it's not all the discs. It's just disc number two or disc number three or they can actually see at a single disc level on the array, the performance, the latency, you know, the QS, all that stuff. >> Oh, absolutely. >> And that really is what, it frees up at the storage admin's time because the debugging is so much more simple. And it also allows the storage admin a lot more insight. Right? They know those, what's the problem. If you were typically looking at a loaner volume, they don't really know what's going on inside that and neither does the array. But with vVols, the array knows what each disc and how it's supposed to be treated based on the policies that the customer defines. So if one VM is supposed to have a certain QS and another VM isn't. The array knows that that VM, if it goes above it, it's going to be like, nope, you can't have those resources. You weren't granted those resources, but this one was. So you have much more control. And again, it's at an application or a VM level. >> And it's still, it's fairly dynamically configurable. I spoke to a customer just the other day. They are a cloud service provider. And what they do is their customers are able to go in and change their quality of service. So they go into that service portal and they say, okay, I'm paying for gold and I want platinum and they'll go in. They know that they've got a certain time where they need more IO capacity. So they'll go in, they'll pay the fee, increase that capability. And then when they don't need it anymore, they'll downgrade again. >> Okay, so that assumes some ability at the array level to do some sort of resource sharing and balancing to be able to go out and get, say more IO. Because again, fundamentally, if you have a virtual volume, that's drawing its resources from five storage devices, whether those are SSD based or NVMe or spinning disc that represents a finite it amount of resource. The assumption is if you're saying that the array is the pool that you need to worry about, that assumes the array has the ability to go beyond here, based on a policy. >> So that's how it works. It does... >> Well, essentially. I mean, you can't outrun physics. So if the array can't go faster, but the idea is that you understand the performance profile of your array and then you create your service tiers appropriately. >> Okay. >> Yeah. And one of the big benefits is like Chance was saying, if you want to change a profile that used to be a Storage vMotion to a different data store. Now it's just a policy change. The storage admin doesn't have to do anything. The VI admin just changes the policy. And then the array understands, oh, I now need to treat that different. And that's exactly what Chance was talking about in that cloud provider situation, where today I'm using a 100,000 IOPS. I need to use 200,000 tomorrow for special, whatever it is, but I only need to use it for tomorrow. So they don't have to move anything. They just change the policy for that time. And then they change it back. They don't have to do anything on the array itself. They don't have to change anything physically on the VM. It's just a policy change. And that's really where you get that dynamic control of the storage capability. >> So as business dynamics are changing and I'm thinking of like black Friday or Prime day, being able to dial things up and dial it down, they have the ability to do that with a policy. >> Yes. >> Exactly. >> So huge time savings there. >> Oh, it's huge. Yeah. >> Yeah. >> And it simplifies because now, I don't have to have multiple data stores. You can have one data store, all your VMs in there. You can limit test and dev and you can maximize business critical applications. Again, all via policy. So you've simplified your infrastructure. You've gone to more of a programmatic approach of managing your storage capabilities. But you're now managing at the VM level. >> So we mentioned that the cloud chaos (indistinct) that was mentioned this morning during the Keynote and we're saying a lot of customers are still in this cloud chaos phase. They want to get to Cloud Smart. How is this going to be one of those tools that helps customers pull the levers, dial the knobs, to be able to get to eventually, Cloud Smart. >> I could go on for this for hours. (Lisa Laughs) (Chance chuckles) This is really what simplifies storage. Because typically when you use traditional storage, you're going to have to figure out that this data store has this capability or another example, as you mentioned was Tanzu. If you're managing persistent volumes and you're not using something like vVols, if you want to get a certain storage capability, you have to either tag it or you have to create that data store with that capability. All of that goes away when you use vVols. So now that chaos of multiple data stores, multiple lines or multiple volumes, all that stuff goes away. So now you're simplifying your infrastructure, you have a programmatic approach to managing your storage and you can use it for all of your different types of workloads. So cloud, Kubernetes, persistent volumes, all that type of stuff. And again, all being managed via a simple and again, programmatic approach. So you could automate this. You know today, like you said, black Friday. Okay, Black, Friday's coming up. I want to change the policy. You could automate that. So you don't even have to go in and physically make the change of the policy now. You just say on Fridays, change it to this policy on Sunday night, change it back. >> Yep. >> Again, that's not something you can do with traditional storage. >> Okay. >> And I think from a simplification standpoint as well, you know, I was telling you about that other customer a couple days ago, they were running into the inability to grow beyond the bounds of VMFS file systems for very, very large VMs. And so what I talked to them about was look, if you go to vVols, you're not bound by file systems anymore. You have the capacity of the array and you can have VM discs up to 62 terabytes, you know, as many as you want. And it doesn't matter what they fit in because we can fit them all. So it's, to be able to, and that's some of our largest customers, the reason they go with vVols is to be able to grow beyond the bounds of traditional storage, anything like path limits, you know. That's something you have to contend with. >> Path limits, line limits, all that stuff. Typically just disappears with vVols. >> All those limits go away. Guys- >> They go away. >> Amazing. Congratulations on the work that you guys have done. Thank you so much for joining us on theCUBE talking about the value in it for customers and obviously the technical depths of the NetApp, VMware relationship. Guys, we appreciate your time. >> Yeah, thanks for having us on. >> Our pleasure. For my guests and Dave Nicholson. I'm Lisa Martin. You're watching theCUBE live from VMware Explorer 2022, Dave and I will be right back with our next guest. So stick around. (upbeat music)

>>Hey everyone. It's the cube live at VMware Explorer, 2022. We're at Mascone center and lovely, beautiful San Francisco. Dave Volante is with me, Lisa Martin. Beautiful weather here today. >>It is beautiful. I couldn't have missed this one because you know, the orange and the pure and VA right. Are history together. I had a, I had a switch sets. You >>Did. You were gonna have FOMO without a guest. Who's back. One of our longtime alumni V Stewart, VP of global technology alliances partners at pure storage one. It's great to have you back on the program, seeing you in 3d >>It's. It's so great to be here and we get a guest interviewer. So this >>Is >>Fantastic. Fly by. Fantastic. >>So talk to us, what's going on at pure. It's been a while since we had a chance to talk, >>Right. Well, well, besides the fact that it's great to see in person and to be back at a conference and see all of our customers, partners and prospects, you know, pure storage has just been on a tear just for your audience. Many, those who don't follow pure, right? We finished our last year with our Q4 being 41% year over year growth. And in the year, just under 2.2 billion, and then we come outta the gates this year, close our Q1 at 50% year over year, quarter quarterly growth. Have you ever seen a storage company or an infrastructure partner at 2 billion grow at that rate? >>Well, the thing was, was striking was that the acceleration of growth, because, you know, I mean, COVID, there were supply chain issues and you know, you saw that. And then, and we've seen this before at cloud companies, we see actually AWS as accelerated growth. So this is my premise here is you guys are actually becoming a cloud-like company building on top of, of infrastructure going from on-prem to cloud. But we're gonna talk about that. >>This is very much that super cloud premise. Well, >>It is. And, and, but I think it's it's one of the characteristics is you can actually, it, you know, we used to see companies, they go, they'd come out of escape velocity, and then they'd they'd growth would slow. I used to be at IDC. We'd see it. We'd see it. Okay. Down then it'd be single digits. You guys are seeing the opposite. >>It's it's not just our bookings. And by the way, I would be remiss if I didn't remind your audience that our second quarter earnings call is tomorrow. So we'll see how this philosophy and momentum keeps going. See, right. But besides the growth, right? All the external metrics around our business are increasing as well. So our net promoter score increased right at 85.2. We are the gold standard, not just in storage in infrastructure period. Like there's no one close to us, >>85. I mean, that's like, that's a, like apple, >>It's higher than apple than apple. It's apple higher than Tesla. It's higher than AWS shopping. And if you look in like our review of our products, flash rate is the leader in the gardener magic quadrant for, for storage array. It's been there for eight years. Port works is the leader in the GIGO OME radar for native Kubernetes storage three years in a row. Like just, it's great to be at a company that's hitting on all cylinders. You know, particularly at a time that's just got so much change going on in our >>Industry. Yeah. Tremendous amount of change. Talk about the, the VMware partnership from a momentum of velocity perspective what's going on there. And some of the things that you're accelerating. >>Absolutely. So VMware is, is the, the oldest or the longest tenured technology partner that we've had. I'm about to start my 10th year at pure storage. It feels like it was yesterday. When I joined, they were a, an Alliance partner before I joined. And so not to make that about me, but that's just like we built some of the key aspects around our first product, the flash array with VMware workloads in mind. And so we are a, a co-development partner. We've worked with them on a number of projects over years of, of late things that are top of mind is like the evolution of vials, the NV support for NVMe over fabric storage, more recently SRM support for automating Dr. With Viv a deployments, you know, and, and, and then our work around VMware ex extends to not just with VMware, they're really the catalyst for a lot of three way partnerships. So partnerships into our investments in data protection partners. Well, you gotta support V ADP for backing up the VMware space, our partnership within Nvidia, well, you gotta support NVA. I, so they can accelerate bringing those technologies into the enterprise. And so it's it, it's not just a, a, a, you know, unilateral partnership. It's a bidirectional piece because for a lot of customers, VMware's kind of like a touchpoint for managing the infrastructure. >>So how is that changing? Because you you've mentioned, you know, all the, the, the previous days, it was like, okay, let's get, make storage work. Let's do the integration. Let's do the hard work. It was kind of a race for the engineering teams to get there. All the storage companies would compete. And it was actually really good for the industry. Yeah, yeah. Right. Because it, it went from, you know, really complex, to much, much simpler. And now with the port works acquisition, it brings you closer to the whole DevOps scene. And you're seeing now VMware it's with its multi-cloud initiatives, really focusing on, you know, the applications and that, and that layer. So how does that dynamic evolve in terms of the partnership and, and where the focus is? >>So there's always in the last decade or so, right. There's always been some amount of overlap or competing with your partnerships, right. Something in their portfolios they're expanding maybe, or you expand you encroach on them. I think, I think two parts to how I would want to answer your question. The retrospective look V VMware is our number one ISV from a, a partner that we, we turn transactions with. The booking's growth that I shared with you, you could almost say is a direct reflection of how we're growing within that, that VMware marketplace. We are bringing a platform that I think customers feel services their workloads well today and gives them the flexibility of what might come in their cloud tomorrow. So you look at programs like our evergreen one subscription model, where you can deploy a consumption based subscription model. So very cloud-like only pay for what you use on-prem and turn that dial as you need to dial it into a, a cloud or, or multiple clouds. >>That's just one example. Looking forward, look, port works is probably the platform that VMware should have bought because when you look at today's story, right, when kit Culbert shared a, a cross cloud services, right, it was, it was the modern version of what VMware used to say, which was, here's a software defined data center. We're gonna standardize all your dissimilar hardware, another saying software defined management to standardize all your dissimilar clouds. We do that for Kubernetes. We talk about accelerating customers' adoption of Kubernetes by, by allowing developers, just to turn on an enable features, be its security, backup high availability, but we don't do it mono in a, you know, in a, in a homogeneous environment, we allow customers to do it heterogeneously so I can deploy VMware Tansu and connect it to Amazon EKS. I can switch one of those over to red head OpenShift, non disruptively, if I need to. >>Right? So as customers are going on this journey, particularly the enterprise customers, and they're not sure where they're going, we're giving them a platform that standardizes where they want to go. On-prem in the cloud and anywhere in between. And what's really interesting is our latest feature within the port works portfolio is called port works data services, and allows customers to deploy databases on demand. Like, install it, download the binaries. You have a cus there, you got a database, you got a database. You want Cassandra, you want Mongo, right? Yeah. You know, and, and for a lot of enterprise customers, who've kind of not, not know where to don't know where to start with port works. We found that to be a great place where they're like, I have this need side of my infrastructure. You can help me reduce cost time. Right. And deliver databases to teams. And that's how they kick off their Tansu journey. For example. >>It's interesting. So port works was the enabler you mentioned maybe VMware should above. Of course they had to get the value out of, out of pivotal. >>Understood. >>So, okay. Okay. So that, so how subsequent to the port works acquisition, how has it changed the way that you guys think about storage and how your customers are actually deploying and managing storage? >>Sure. So you touched base earlier on what was really great about the cloud and VMware was this evolution of simplifying storage technologies, usually operational functions, right? Making things simpler, more API driven, right. So they could be automated. I think what we're seeing customers do to today is first off, there's a tremendous rise in everyone wanting to do every customer, not every customer, a large portion of the customer bases, wanting to acquire technology on as OPEX. And it, I think it's really driven by like eliminate technical debt. I sign a short term agreement, our short, our shortest commitment's nine months. If we don't deliver around what we say, you walk away from us in nine months. Like you, you couldn't do that historically. Furthermore, I think customers are looking for the flexibility for our subscriptions, you know, more from between on-prem and cloud, as I shared earlier, is, is been a, a, a big driver in that space. >>And, and lastly, I would, would probably touch on our environmental and sustainability efforts. You saw this morning, Ragu in the keynote touch on what was it? Zero carbon consumption initiative, or ZCI my apologies to the veer folks. If I missed VO, you know, we've had, we've had sustainability into our products since day one. I don't know if you saw our inaugural ESG report that came out about 60 days ago, but the bottom line is, is, is our portfolio reduces the, the power directly consumed by storage race by up to 80%. And another aspect to look at is that 97% of all of the products that we sold in the last six years are still in the market today. They're not being put into, you know, into, to recycle bins and whatnot, pure storage's goal by the end of this decade is to further drive the efficiency of our platforms by another 66%. And so, you know, it's an ambitious goal, but we believe it's >>Important. Yeah. I was at HQ earlier this month, so I actually did see it. So, >>Yeah. And where is sustainability from a differentiation perspective, but also from a customer requirements perspective, I'm talking to a lot of customers that are putting that requirement when they're doing RFPs and whatnot on the vendors. >>I think we would like to all, and this is a free form VO comment here. So my apologies, but I think we'd all like to, to believe that we can reduce the energy consumption in the planet through these efforts. And in some ways maybe we can, what I fear in the technology space that I think we've all and, and many of your viewers have seen is there's always more tomorrow, right? There's more apps, more vendors, more offerings, more, more, more data to store. And so I think it's really just an imperative is you've gotta continue to be able to provide more services or store more data in this in yesterday's footprint tomorrow. A and part of the way they get to is through a sustainability effort, whether it's in chip design, you know, storage technologies, et cetera. And, and unfortunately it's, it's, it's something that organizations need to adopt today. And, and we've had a number of wins where customers have said, I thought I had to evacuate this data center. Your technology comes in and now it buys me more years of time in this in infrastructure. And so it can be very strategic to a lot of vendors who think their only option is like data center evacuation. >>So I don't want to, I, I don't wanna set you up, but I do want to have the super cloud conversation. And so let's go, and you, can you, you been around a long time, your, your technical, or you're more technical than I am, so we can at least sort of try to figure it out together when I first saw you guys. I think Lisa, so you and I were at, was it, when did you announce a block storage for AWS? The, was that 2019 >>Cloud block store? I believe block four years >>Ago. Okay. So 20 18, 20 18, 20 18. Okay. So we were there at, at accelerate at accelerate and I said, oh, that's interesting. So basically if I, if I go back there, it was, it was a hybrid model. You, you connecting your on-prem, you were, you were using, I think, priority E C two, you know, infrastructure to get high performance and connecting the two. And it was a singular experience yeah. Between on-prem and AWS in a pure customer saw pure. Right. Okay. So that was the first time I started to think about Supercloud. I mean, I think thought about it in different forms years ago, but that was the first actual instantiation. So my, my I'm interested in how that's evolved, how it's evolving, how it's going across clouds. Can you talk just conceptually about how that architecture is, is morphing? >>Sure. I just to set the expectations appropriately, right? We've got, we've got a lot of engineering work that that's going on right now. There's a bunch of stuff that I would love to share with you that I feel is right around the corner. And so hopefully we'll get across the line where we're at today, where we're at today. So the connective DNA of, of flash array, OnPrem cloud block store in the cloud, we can set up for, for, you know, what we call active. Dr. So, so again, customers are looking at these arrays is a, is a, is a pair that allows workloads to be put into the, put into the cloud or, or transferred between the cloud. That's kind of like your basic building, you know, blocking tackling 1 0 1. Like what do I do for Dr. Example, right? Or, or gimme an easy button to, to evacuate a data center where we've seen a, a lot of growth is around cloud block store and cloud block store really was released as like a software version of our hardware, Ray on-prem and it's been, and, and it hasn't been making the news, but it's been continually evolving. >>And so today the way you would look at cloud block store is, is really bringing enterprise data services to like EBS for, for AWS customers or to like, you know, is Azure premium disc for Azure users. And what do I mean by enterprise data services? It's, it's the, the, the way that large scale applications are managed, on-prem not just their performance and their avail availability considerations. How do I stage the, the development team, the sandbox team before they patch? You know, what's my cyber protection, not just data protection, how, how am I protected from a cyber hack? We bring all those capabilities to those storage platforms. And the, the best result is because of our data reduction technologies, which was critical in reducing the cost of flash 10 years ago, reduces the cost of the cloud by 50% or more and pays for the, for pays more than pays for our software of cloud block store to enable these enterprise data services, to give all these rapid capabilities like instant database, clones, instant, you know, recovery from cyber tech, things of that nature. >>Do customers. We heard today that cloud chaos are, are customers saying so, okay, you can run an Azure, you can run an AWS fine. Are customers saying, Hey, we want to connect those islands. Are you hearing that from customers or is it still sort of still too early? >>I think it's still too early. It doesn't mean we don't have customers who are very much in let's buy, let me buy some software that will monitor the price of my cloud. And I might move stuff around, but there's also a cost to moving, right? The, the egress charges can add up, particularly if you're at scale. So I don't know how much I seen. And even through the cloud days, how much I saw the, the notion of workloads moving, like kind of in the early days, like VMO, we thought there might be like a, is there gonna be a fall of the moon computing, you know, surge here, like, you know, have your workload run where power costs are lower. We didn't really see that coming to fruition. So I think there is a, is a desire for customers to have standardization because they gain the benefits of that from an operational perspective. Right. Whether they put that in motion to move workloads back and forth. I think >>So let's say, let's say to be determined, let let's say they let's say they don't move them because your point you knows too expensive, but, but, but, but you just, I think touched on it is they do want some kind of standard in terms of the workflow. Yep. You you're saying you're, you're starting to see demand >>Standard operating practices. Okay. >>Yeah. SOPs. And if they're, if they're big into pure, why wouldn't they want that? If assuming they have, you know, multiple clouds, which a lot of customers do. >>I, I, I I'll assure with you one thing that the going back to like basic primitives and I touched it touched on it a minute ago with data reduction. You have customers look at their, their storage bills in the cloud and say, we're gonna reduce that by half or more. You have a conversation >>Because they can bring your stack yeah. Into the cloud. And it's got more maturity than what you'd find from a cloud company, cloud >>Vendor. Yeah. Just data. Reduction's not part of block storage today in the cloud. So we've got an advantage there that we, we bring to bear. Yeah. >>So here we are at, at VMware Explorer, the first one of this name, and I love the theme, the center of the multi-cloud universe. Doesn't that sound like a Marvel movie. I feel like there should be superheroes walking around here. At some point >>We got Mr. Fantastic. Right here. We do >>Gone for, I dunno it >>Is. But a lot of, a lot of news this morning in the keynote, you were in the keynote, what are some of the things that you're hearing from VMware and what excites you about this continued evolution of the partnership with pure >>Yeah. Great point. So I, I think I touched on the, the two things that really caught my attention. Obviously, you know, we've got a lot of investment in V realize it was now kind of rebranded as ay, that, you know, I think we're really eager to see if we can help drive that consumption a bit higher, cuz we believe that plays into our favor as a vendor. We've we've we have over a hundred templates for the area platform right now to, you know, automation templates, whether it's, you know, levels set your platform, you know, automatically move workloads, deploy on demand. Like just so, so again, I think the focus there is very exciting for us, obviously when they've got a new release, like vSphere eight, that's gonna drive a lot of channel behaviors. So we've gotta get our, you know, we're a hundred percent channel company. And so we've gotta go get our channel ready because with about half of the updates of vSphere is, is hardware refresh. And so, you know, we've gotta be, be prepared for that. So, you know, some of the excitements about just being how to find more points in the market to do more business together. >>All right. Exciting cover the grounds. Right. I mean, so, okay. You guys announce earnings tomorrow, so we can't obviously quiet period, but of course you're not gonna divulge that anyway. So we'll be looking for that. What other catalysts are out there that we should be paying attention to? You know, we got, we got reinvent coming up in yep. In November, you guys are obviously gonna be there in, in a big way. Accelerate was back this year. How was accelerate >>Accelerate in was in Los Angeles this year? Mm. We had great weather. It was a phenomenal venue, great event, great partner event to kick it off. We happened to, to share the facility with the president and a bunch of international delegates. So that did make for a little bit of some logistic securities. >>It was like the summit of the Americas. I, I believe I'm recalling that correctly, but it was fantastic. Right. You, you get, you get to bring the customers out. You get to put a bunch of the engineers on display for the products that we're building. You know, one of the high, you know, two of the highlights there were, we, we announced our new flash blade S so, you know, higher, more performant, more scalable version of our, our scale and object and file platform with that. We also announced the, the next generation of our a I R I, which is our AI ready, AI ready infrastructure within video. So think of it like converged infrastructure for AI workloads. We're seeing tremendous growth in that unstructured space. And so, you know, we obviously pure was funded around block storage, a lot around virtual machines. The data growth is in unstructured, right? >>We're just seeing, we're seeing, you know, just tons of machine learning, you know, opportunities, a lot of opportunities, whether we're looking at health, life sciences, genome sequencing, medical imaging, we're seeing a lot of, of velocity in the federal space. You know, things, I can't talk about a lot of velocity in the automotive space. And so just, you know, from a completeness of platform, you know, flat flash blade is, is really addressing a need really kind of changing the market from NAS as like tier two storage or object is tier three to like both as a tier one performance candidate. And now you see applications that are supporting running on top of object, right? All your analytics platforms are on an object today, Absolut. So it's a, it's a whole new world. >>Awesome. And Pierce also what I see on the website, a tech Fest going on, you guys are gonna be in Seoul, Mexico city in Singapore in the next week alone. So customers get the chance to be able to in person talk with those execs once again. >>Yeah. We've been doing the accelerate tech tech fests, sorry about that around the globe. And if one of those align with your schedule, or you can free your schedule to join us, I would encourage you. The whole list of events dates are on pure storage.com. >>I'm looking at it right now. Vaon thank you so much for joining Dave and me. I got to sit between two dapper dudes, great conversation about what's going on at pure pure with VMware better together and the, and the CATA, the cat catalysis that's going on on both sides. I think that's an actual word I should. Now I have a degree biology for Vaughn Stewart and Dave Valante I'm Lisa Martin. You're watching the cube live from VMware Explorer, 22. We'll be right back with our next guest. So keep it here.

hello and welcome to the cube i'm dave nicholson chief technology officer at thecube and we're here for a very special cube conversation with andy brown from broadcom andy welcome to the cube tell us a little about yourself a little bit my about myself my name is andy brown i'm currently the senior director of software architecture and performance analysis here within the data center solutions group at broadcom i've been doing that for about seven years prior to that i held various positions within the system architecture systems engineering and ic development organization but ultimately as well i spent some time in our support organization and managing our support team but ultimately have landed in the architecture organization as well as performance analysis great so a lot of what you do is around improving storage performance tell us more about that so let me give you a brief history of uh storage from from my perspective um you know i as i mentioned i go back about 30 years in my career and that would have started back in the ncr microelectronics days and originally with parallel scuzzy so that would be if anyone would remember the 5380 controller which was one of the original parallel scuzzy controllers that existed and built by ncr microelectronics at the time i've i've seen the advent of parallel scuzzy a stint of fiber channel ultimately leading into the serialization of those of the scuzzy standard into sas as well as sata and then ultimately leading to nvme protocols and the advent of flash moving from hard drives into a flash based media and as well on on that's on the storage side on the host side moving from parallel interfaces isa if everybody could remember that moving to pci pci express that's where we land today so andy we're square in the middle of the era of both nvme and sas what kinds of challenges does that overlap represent well i think you know obviously we've seen sas around for a while it was the conversion from parallel into a serial attached scuzzy and that really sas brings with it the ability to uh connect on really a high number of devices um and uh was was kind of the original scaling of devices and and really uh also enabled uh was was one of the things that enabled flash based media given the the speed and performance that came to the table of course nvme came in as well with the promise of of even higher speeds and as we saw flash media really really take a strong role in storage uh nvme came around and and really was focused on trying to address that whereas sas originated with hard drive technology nvme was really born out of how do we how do we most efficiently deal with flash based media you know sas with its but sas still carries a benefit on scalability nvme maybe has i don't want to say challenges there but it's definitely was not designed as much to be broadly scalable across many many say hundreds or thousands of devices but definitely addressed some of the performance issues that were coming up as flash media was becoming so uh uh was was increasing the overall storage performance that we could experience if you will let's talk about host interfaces like pcie what's the significance there um really uh the all the storage in the world all of the performance in the world and on the storage side is not of much use to you unless you can really feed it into the into the beast if you will into the cpu and into this the rest of the server subsystem and that's really where pci comes into play pci uh originally was in parallel form and then moved to serial with pci express as we know it today and and really has created a pathway to to to enable not not only storage performance but any other adapter or any other networking or other other types of technologies to just open up that pathway and feed the processor if and as we've moved through from pci to pci express pci 2.0 3.0 4.0 and just opening up those pipes has really enabled just a tremendous amount of flow of data into into the compute engine allowing it to be analyzed sorted used to analyze data big data uh ai type applications just those pipes are critical in those types of applications we know we've seen dramatic increases in performance going from one generation of pcie to the next but how does that translate into the worlds of sas sata and nvme um so from a performance perspective when we look at these different types of media whether it be sata sas or nvme um of course there are performance difference inherent in that media sata being probably the lowest performing with nvme uh topping out at higher performing although sas can perform quite well as a flash based you know as a protocol connected to flash based media and of course nvme from us an individual device scaling from a by one to a by four interface really that is where nvme kind of has enabled a bigger pipe directly to the storage media uh being able to scale up to buy four whereas sas is kind of limited to buy one maybe buy two in some cases although most servers only connect the sas device by one so from a difference perspective then you're really wanting to create a solution or or enable the infrastructure to be able to consume that performance that nvme is going to give you and i think that you know that is something where our solutions have really in in the recent generations shine at their ability to really now uh keep up with uh storage performance in nvme uh as well as provide that connectivity back down into the sas and sata world as well let's talk about your perspective on raid today so uh there's been a lot of uh views and opinions on raid over the years it's been a and those have been changing over time raid has been around for a very very long time uh probably about as long as again going back over my 30-year career uh it's been around for almost the entire time obviously raid originally was viewed as as something that was uh very very necessary uh devices fail they don't last forever but the data that's on them is very very important and people care about that so raid was brought about you know knowing that individual devices that are storing that data are going to fail and really took hold as a primary mechanism of protection but as time went on uh and and as performance moved up uh both in the server and both in in the media itself if we start talking about flash uh raid really took on people people started to look at traditional server storage raid uh but with maybe a more of a negative connotation i think that because uh to be quite honest it fell behind a little bit if you look at things like parity raid raid five and rate six very very effective and efficient means of protecting your data very storage efficient but ultimately had some penalties a primarily around wright performance random rights in raid 5 volumes was not keeping up with what really needed to be there and um i think that really shifted uh opinions of raid that hey it's just it's just not it's not going to keep up and we need to move on to other avenues and and we've seen that we've seen disaggregated storage and other solutions pop up to protect your data obviously in cloud environments and things like that it's shown up and uh and they have been successful so one of the drawbacks with raid is always the performance tax associated with generating parity for parity rate what has broadcom done to address those potential bottlenecks we've really solved the raid performance issue the right performance issue we're we're in our latest generation of controllers we're exceeding a million rate five right iops which is enough to satisfy many many many applications as a matter of fact even in virtual environments aggregated solutions we have multiple applications and then as well in the rebuild arena we really have through our architecture through our hardware automation have been able to move the bar on that to where the rebuild not only the rebuild times have been brought down dramatically in sas based or in i'm sorry in flash based solutions but the performance that you can observe while those rebuilds are going on is almost immeasurable so in most applications you would almost observe no performance deficiencies during a rebuild operation which is really night and day compared to where things were just a few short years ago so the fact that you've been able to dramatically decrease the time necessary for a raid rebuild is obviously extremely important but give us your overall performance philosophy from broadcom's point of view you know over the years we have recognized that performance is is obviously critically important for our products and the ability to analyze performance from many many angles is critically important there are literally infinite ways you can look at performance in a storage subsystem what we have done in our labs and in our solutions through not only hardware scaling in our in our in our labs but also through automation scripts and things like that allowed us to collect a substantial amount of data to look at the performance of our solutions from every angle you know iops bandwidth application level performance small topologies large topologies just just many many aspects it's still honestly only scratches the surface of all the possible uh performance points that you could gather but it it has we have moved the bar dramatically in that regard and and it's something that our customers really demanded of us um you know storage technology has gotten more complex and you have to look at it from a lot different angles especially on the performance front to make sure that there are no holes there that somebody's going to run into so based on specific customer needs and requests you look at performance from a variety of different angles um what are some of the trends that you're seeing specifically in storage performance today and moving into the future yeah emerging trends within the storage industry i think that to look at the emerging trends you really need to go back and look at where we started we started uh in compute where people were you would have basically your uh your server that would be under the desk in a small business operation and individual uh businesses would have their own uh set of set of servers and and the storage would really be localized to those obviously the industry has recognized that um that to some extent disaggregation of that we we see that obviously in what's happening in cloud uh in hyper-converged storage and things like that those afford a tremendous amount of flexibility uh and and are obviously uh great players in the storage world today but what with that flexibility is come some sacrifice in performance and actually quite substantial sacrifice and what we're observing is almost uh it comes back full circle the uh the need for inbox high performing server storage that is well protected uh and and with people with confidence that people have confidence that their data is protected and that they can uh extract the performance that they need for the demanding database applications that still exist today and they still operate in in the offices around the country and around the world that really need to protect their data on a local basis in the server and i think that from a trend perspective that's what we're seeing also from the standpoint of nvme store nvme itself is really started out with hey we'll just software rate that we'll just we'll just wrap software around that we can protect the data we had so many customers come back to us saying you know what we really need hardware raid on nvme and when they came to us we were ready we had a solution ready to go and we're able to provide that and now we're seeing going on demand we are we are complementary to other storage solutions out there server storage is not going to necessarily rule the world but it is surely has a place in the broader storage spectrum and we think we have the right solution for that speaking of servers and server-based storage why would for example a dell customer care about the broadcom components in that dell server so uh uh let's say you're configuring a dell server and you're going why does why does hardware raid matter what what what's important about that well i think when you look at today's hardware raid uh first of all you're going to see dramatically better performance you're going to see dramatically better performance in it's going to enable you to put raid 5 volumes a very effective and efficient mechanism for protecting your data a storage efficient mechanism you're going to use raid 5 volumes where you weren't able to do that before because when you're in the millions of iops range you really uh can satisfy a lot of application needs out there and and then you're going to also going to have rebuilt times that are lightning fast your performance is not going to degrade when you're when you're running those application especially database applications but not not only database but streaming applications uh bandwidth uh to to protected raid volumes is is almost almost imperceptibly different from just raw bandwidth to the media so the rate rate configurations in today's dell servers really afford you the opportunity to make use of that storage where you you may not have uh you may have already written it off as well ray just doesn't is not going to get me there quite frankly uh into this in in the storage servers that dell is providing uh with with raid technology uh there are huge windows open and what you can do today with applications well all of this is obviously good news for dell and dell customers thanks again andy for joining us for this cube conversation i'm dave nicholson for the cube [Music]

(upbeat music) >> Hello and welcome to theCUBE. I'm Dave Nicholson, Chief Technology Officer at theCUBE and we are here for a very special Cube Conversation with Andy Brown from Broadcom. Andy, welcome to theCUBE, tell us a little about yourself. >> Well, a little bit about myself, my name is Andy Brown, I'm currently the Senior Director of Software Architecture and Performance Analysis here within the Data Center Solutions Group at Broadcom. I've been doing that for about seven years prior to that, I held various positions within the system architecture, systems engineering, and IC development organization, but ultimately as well as spent some time in our support organization and managing our support team. But ultimately have landed in the architecture organization as well as performance analysis. >> Great, so a lot of what you do is around improving storage performance, tell us more about that. >> So let me give you a brief history of storage from my perspective. As I mentioned, I go back about 30 years in my career and that would've started back in the NCR Microelectronics days. And originally with Parallel SCSI, so that would be, if anyone would remember the the 5380 Controller, which was one of the original Parallel SCSI controllers that existed in built by NCR Microelectronics at the time, I've seen the advent of Parallel SCSI, a stint of fiber channel, ultimately leading into the serialization of the SCSI standard into SaaS, as well as SATA, and then ultimately leading to NVMe protocols and the advent of flash moving from hard drives into a flash based media and as well on that's on the storage side on the host side, moving from parallel interfaces, ISA if everybody could remember that, moving to PCI, PCI Express and that's where we land today. >> So Andy, we are square in the middle of the era of both NVMe and SaaS. What kinds of challenges does that overlap represent? >> Well, I think obviously we've seen SaaS around for a while, it was the conversion from parallel into a serial attached SCSI and that really SaaS brings with it, the ability to connect really a high number of devices and was kind of the original scaling of devices. And really also enabled was one of the things that enabled flash based media, given the the speed and performance that came to the table. Of course NVMe came in as well with the promise of even higher speeds. And as we saw flash media really, really take a strong role in storage. NVMe came around and really was focused on trying to address that, whereas SaaS originated with hard drive technology. NVMe was really born out of how do we most efficiently deal with flash based media, SaaS with its. But SaaS still carries a benefit on scalability and NVMe maybe has, I don't want to say challenges there, but it's definitely was not designed as much to be broadly scale across many, many, say high hundreds or thousands of devices. But definitely addressed some of the performance issues that were coming up as flash media was becoming. So it was increasing the overall storage performance that we could experience if you will. >> Let's talk about host interfaces, PCIe. What's the significance there? >> Really all the storage in the world, all the performance in the world on the storage side, is not of much use to you unless you can really feed it into the beast, if you will, into the CPU and into the the rest of the service subsystem. And that's really where PCI comes into play. PCI originally was in parallel form and then moved to serial with the PCI Express as we know it today, and really has created a pathway to enable not only storage performance but any other adapter or any other networking or other types of technologies to just open up that pathway and feed the processor. And as we've moved through from PCI to PCI Express PCI 2.0 3.0 4.0, and just opening up those pipes has really enabled just a tremendous amount of flow of data into the compute engine, allowing it to be analyzed, sorted used to analyze data, big data, AI type applications. Just those pipes are critical in those types of applications. >> We know we've seen dramatic increases in performance, going from one generation of PCIe to the next. But how does that translate into the worlds of SaaS, SATA and NVMe? >> So from a performance perspective when we look at these different types of media whether it be SATA, SaaS or NVMe, of course, there are performance difference inherent in that media, SATA being probably the lowest performing with NVMe topping out at higher performing although SaaS can perform quite well as a flash based as protocol connected to flash based media. And of course, NVMe from an individual device scaling, from a by one to a by four interface, really that is where NVMe kind of has enabled a bigger pipe directly to the storage media, being able to scale up to by four whereas SaaS can limit it to by one, maybe by two in some cases, although most servers only connect the SaaS device of by one. So from a different perspective then you're really wanting to create a solution or enable the infrastructure to be able to consume that performance at NVMe is going to give you. And I think that is something where our solutions have really in the recent generation shined, at their ability to really now keep up with storage performance and NVMe, as well as provide that connectivity back down into the SaaS and SATA world as well. >> Let's talk about your perspective on RAID today. >> So there've been a lot of views and opinions on RAID over the years, it's been and those have been changing over time. RAID has been around for a very, very long time, probably about as long as again, going back over my 30 year career, it's been around for almost the entire time. Obviously RAID originally was viewed as some thing that was very, very necessary devices fail. They don't last forever, but the data that's on them is very, very important and people care about that. So RAID was brought about knowing that individual devices that are storing that data are going to fail, and really took cold as a primary mechanism of protection. But as time went on and as performance moved up both in the server and both in the media itself if we start talking about flash. RAID really took on, people started to look at traditional server storage RAID, well, maybe a more of a negative connotation. I think that because to be quite honest, it fell behind a little bit. If you look at things like parity RAID 5 and RAID 6, very, very effective efficient means of protecting your data, very storage efficient, but ultimately had some penalty a primarily around right performance, random rights in RAID 5 volumes was not keeping up with what really needed to be there. And I think that really shifted opinions of RAID that, "Hey it's just not, it's not going to keep up and we need to move on to other avenues." And we've seen that, we've seen disaggregated storage and other solutions pop up and protect your data obviously in cloud environments and things like that have shown up and they have been successful, but. >> So one of the drawbacks with RAID is always the performance tax associated with generating parody for parody RAID. What has Broadcom done to address those potential bottlenecks? >> We've really solved the RAID performance issue the right performance issue. We're in our latest generation of controllers we're exceeding a million RAID 5 right IOPS which is enough to satisfy many, many, many applications as a matter of fact, even in virtual environments aggregated solutions, we have multiple applications. And then as well in the rebuild arena, we really have through our architecture, through our hardware automation have been able to move the bar on that to where the rebuild not only the rebuild times have been brought down dramatically in SaaS based or in I'm sorry in flash based solutions. But the performance that you can observe while those rebuilds are going on is almost immeasurable. So in most applications you would almost observe no performance deficiencies during a rebuild operation which is really night and day compared to where things were just few short years ago. >> So the fact that you've been able to, dramatically decrease the time necessary for a RAID rebuild is obviously extremely important. But give us your overall performance philosophy from Broadcom's point of view. >> Over the years we have recognized that performance is obviously a critically important for our products, and the ability to analyze performance from many many angles is critically important. There are literally infinite ways you can look at performance in a storage subsystem. What we have done in our labs and in our solutions through not only hardware scaling in our labs, but also through automation scripts and things like that, have allowed us to collect a substantial amount of data to look at the performance of our solutions from every angle. IOPS, bandwidth application level performance, small topologies, large topologies, just many, many aspects. It still honestly only scratches the surface of all the possible performance points that you could gather, but we have moved them bar dramatically in that regard. And it's something that our customers really demanded of us. Storage technology has gotten more complex, and you have to look at it from a lot different angles, especially on the performance front to make sure that there are no holes there that somebody's going to run into. >> So based on specific customer needs and requests, you look at performance from a variety of different angles. What are some of the trends that you're seeing specifically in storage per performance today and moving into the future? >> Yeah, emerging trends within the storage industry. I think that to look at the emerging trends, you really need to go back and look at where we started. We started in compute where people were you would have basically your server that would be under the desk in a small business operation and individual businesses would have their own set of servers, and the storage would really be localized to those. Obviously the industry has recognized that to some extent, disaggregation of that, we see that obviously in what's happening in cloud, in hyper-converged storage and things like that. Those afford a tremendous amount of flexibility and are obviously great players in the storage world today. But with that flexibility has come some sacrifice and performance and actually quite substantial sacrifice. And what we're observing is almost, it comes back full circle. The need for inbox high performing server storage that is well protected. And with people with confidence that people have confidence that their data is protected and that they can extract the performance that they need for the demanding database applications, that still exists today, and that still operate in the offices around the country and around the world, that really need to protect their data on a local basis in the server. And I think that from a trend perspective that's what we're seeing. We also, from the standpoint of NVMe itself is really started out with, "Hey, we'll just software rate that. We'll just wrap software around that, we can protect the data." We had so many customers come back to us saying, you know what? We really need hardware RAID on NVMe. And when they came to us, we were ready. We had a solution ready to go, and we're able to provide that, and now we're seeing ongoing on demand. We are complimentary to other storage solutions out there. Server storage is not going to necessarily rule a world but it is surely has a place in the broader storage spectrum. And we think we have the right solution for that. >> Speaking of servers and server-based storage. Why would, for example, a Dell customer care about the Broadcom components in that Dell server. >> So let's say you're configuring a Dell server and you're going, why does hardware where RAID matter? What's important about that? Well, I think when you look at today's hardware RAID, first of all, you're going to see a dramatically better performance. You're going to see dramatically better performance it's going to enable you to put RAID 5 volumes a very effective and efficient mechanism for protecting your data, a storage efficient mechanism. You're going to use RAID 5 volumes where you weren't able to do that before, because when you're in the millions of IOPS range you really can satisfy a lot of application needs out there. And then you're going to also going to have rebuilt times that are lightning fast. Your performance is not going to degrade, when you're running those application, especially database applications, but not only database, but streaming applications, bandwidth to protected RAID volumes is almost imperceptively different from just raw bandwidth to the media. So the RAID configurations in today's Dell servers really afford you the opportunity to make use of that storage where you may not have already written it off as well RAID just doesn't, is not going to get me there. Quite frankly, into this in the storage servers that Dell is providing with RAID technology, there are huge windows open in what you can do today with applications. >> Well, all of this is obviously good news for Dell and Dell customers, thanks again, Andy for joining us, for this Cube Conversation, I'm Dave Nicholson for theCUBE. (upbeat music)

(upbeat music) >> Welcome everybody to this CUBE Conversation. My name is Dave Vellante, and we're here to talk about Object storage and the momentum in the space. And what Dell Technologies is doing to compete in this market, I'm joined today by Anahad Dhillon, who's the Product Manager for Dell, EMC's ECS, and new ObjectScale products. Anahad, welcome to theCUBE, good to see you. >> Thank you so much Dave. We appreciate you having me and Dell (indistinct), thanks. >> Its always a pleasure to have you guys on, we dig into the products, talk about the trends, talk about what customers are doing. Anahad before the Cloud, Object was this kind of niche we seen. And you had simple get, put, it was a low cost bit bucket essentially, but that's changing. Tell us some of the trends in the Object storage market that you're observing, and how Dell Technology sees this space evolving in the future please. >> Absolutely, and you hit it right on, right? Historically, Object storage was considered this cheap and deep place, right? Customers would use this for their backup data, archive data, so cheap and deep, no longer the case, right? As you pointed out, the ObjectSpace is now maturing. It's a mature market and we're seeing out there customers using Object or their primary data so, for their business critical data. So we're seeing big data analytics that we use cases. So it's no longer just cheap and deep, now your primary workloads and business critical workloads being put on with an object storage now. >> Yeah, I mean. >> And. >> Go ahead please. >> Yeah, I was going to say, there's not only the extend of the workload being put in, we'll also see changes in how Object storage is being deployed. So now we're seeing a tighter integration with new depth models where Object storage or any storage in general is being deployed. Our applications are being (indistinct), right? So customers now want Object storage or storage in general being orchestrated like they would orchestrate their customer applications. Those are the few key trends that we're seeing out there today. >> So I want to dig into this a little bit with you 'cause you're right. It used to be, it was cheap and deep, it was slow and it required sometimes application changes to accommodate. So you mentioned a few of the trends, Devs, everybody's trying to inject AI into their applications, the world has gone software defined. What are you doing to respond to all these changes in these trends? >> Absolutely, yeah. So we've been making tweaks to our object offering, the ECS, Elastic Cloud Storage for a while. We started off tweaking the software itself, optimizing it for performance use cases. In 2020, early 2020, we actually introduced SSDs to our notes. So customers were able to go in, leverage these SSD's for metadata caching improving their performance quite a bit. We use these SSDs for metadata caching. So the impact on the performance improvement was focused on smaller reads and writes. What we did now is a game changer. We actually went ahead later in 2020, introduced an all flash appliance. So now, EXF900 and ECS all flash appliance, it's all NVME based. So it's NVME SSDs and we leveraged NVME over fabric xx for the back end. So we did it the right way did. We didn't just go in and qualified an SSD based server and ran object storage on it, we invested time and effort into supporting NVME fabric. So we could give you that performance at scale, right? Object is known for scale. We're not talking 10, 12 nodes here, we're talking hundreds of nodes. And to provide you that kind of performance, we went to ahead. Now you've got an NVME based offering EXF900 that you can deploy with confidence, run your primary workloads that require high throughput and low latency. We also come November 5th, are releasing our next gen SDS offering, right? This takes the Troven ECS code that our customers are familiar with that provides the resiliency and the security that you guys expect from Dell. We're re platforming it to run on Kubernetes and be orchestrated by Kubernetes. This is what we announced that VMware 2021. If you guys haven't seen that, is going to go on-demand for VMware 2021, search for ObjectScale and you get a quick demo on that. With ObjectScale now, customers can quickly deploy enterprise grade Object storage on their existing environment, their existing infrastructure, things like VMware, infrastructure like VMware and infrastructure like OpenShift. I'll give you an example. So if you were in a VMware shop that you've got vSphere clusters in your data center, with ObjectScale, you'll be able to quickly deploy your Object enterprise grid Object offering from within vSphere. Or if you are an OpenShift customer, right? If you've got OpenShift deployed in your data center and your Red Hat shop, you could easily go in, use that same infrastructure that your applications are running on, deploy ObjectScale on top of your OpenShift infrastructure and make available Object storage to your customers. So you've got the enterprise grade ECS appliance or your high throughput, low latency use cases at scale, and you've got this software defined ObjectScale, which can deploy on your existing infrastructure, whether that's VMware or Red Hat OpenShift. >> Okay, I got a lot of follow up questions, but let me just go back to one of the earlier things you said. So Object was kind of cheap, deep and slow, but scaled. And so, your step one was metadata caching. Now of course, my understanding is with Object, the metadata and the data within the object. So, maybe you separated that and made it high performance, but now you've taken the next step to bring in NVME infrastructure to really blow away all the old sort of scuzzy latency and all that stuff. Maybe you can just educate us a little bit on that if you don't mind. >> Yeah, absolutely. Yeah, that was exactly the stepped approach that we took. Even though metadata is tightly integrated in Object world, in order to read the actual data, you still got to get to the metadata first, right? So we would cache the metadata into SSDs reducing that lookup that happens for that metadata, right? And that's why it gave you the performance benefit. But because it was just tied to metadata look-ups, the performance for larger objects stayed the same because the actual data read was still happening from the hard drives, right? With the new EXF900 which is all NVME based, we've optimized the our ECS Object code leveraging VME, data sitting on NVME drives, the internet connectivity, the communication is NVME over fabric, so it's through and through NVME. Now we're talking milliseconds and latency and thousands and thousands of transactions per second. >> Got it, okay. So this is really an inflection point for Objects. So these are pretty interesting times at Dell, you got the cloud expanding on prem, your company is building cloud-like capabilities to connect on-prem to the cloud across cloud, you're going out to the edge. As it pertains to Object storage though, it sounds like you're taking a sort of a two product approach to your strategy. Why is that, and can you talk about the go-to market strategy in that regard? >> Absolutely, and yeah, good observation there. So yes and no, so we continued to invest in ECS. ECS continues to stay a product of choice when customer wants that traditional appliance deployment model. But this is a single hand to shape model where you're everything from your hardware to your software the object solution software is all provided by Dell. ECS continues to be the product where customers are looking for that high performance, fine tune appliance use case. ObjectScale comes into play when the needs are software defined. When you need to deploy the storage solution on top of the same infrastructure that your applications are run, right? So yes, in the short-term, in the interim, it's a two product approach of both products taking a very distinct use case. However, in the long-term, we're merging the two quote streams. So in the long-term, if you're an ECS customer and you're running ECS, you will have an in-place data upgrade to ObjectScale. So we're not talking about no forklift upgrades, we're not talking about you're adding additional servers and do a data migration, it's a code upgrade. And then I'll give you an example, today on ECS, we're at code variation 3.6, right? So if you're a customer running ECS, ECS 3.X in the future, and so we've got a roadmap where 3.7 is coming out later on this year. So from 3.X, customers will upgrade the code data in place. Let's call it 4.0, right? And that brings them up to ObjectScale. So there's no nodes left behind, there's an in-place code upgrade from ECS to the ObjectScale merging the two code streams and the long-term, single code, short-term, two products for both solving the very distinct users. >> Okay, let me follow up, put on my customer hat. And I'm hearing that you can tell us with confidence that irrespective of whether a customer invested ECS or ObjectScale, you're not going to put me into a dead-end. Every customer is going to have a path forward as long as their ECS code is up-to-date, is that correct? >> Absolutely, exactly, and very well put, yes. No nodes left behind, investment protection, whether you've got ECS today, or you want to invest into ECS or ObjectScale in the future, correct. >> Talk a little bit more about ObjectScale. I'm interested in kind of what's new there, what's special about this product, is there unique functionality that you're adding to the product? What differentiates it from other Object stores? >> Absolutely, my pleasure. Yeah, so I'll start by reiterating that ObjectScale it's built on that Troven ECS code, right? It's the enterprise grid, reliability and security that our customers expect from Dell EMC, right? Now we're re platforming ECS who allow ObjectScale to be Kubernetes native, right? So we're leveraging that microservices-based architecture, leveraging that native orchestration capabilities of Kubernetes, things like resource isolation or seamless (indistinct), I'm sorry, load balancing and things like that, right? So the in-built native capabilities of Kubernetes. ObjectScale is also build with scale in mind, right? So it delivers limitless scale. So you could start with terabytes and then go up to petabytes and beyond. So unlike other file system-based Object offerings, ObjectScale software would have a limit on your number of object stores, number of buckets, number of objects you store, it's limitless. As long as you can provide the hardware resources under the covers, the software itself is limitless. It allows our customers to start small, so you could start as small as three node and grow their environment as your business grows, right? Hundreds of notes. With ObjectScale, you can deploy workloads at public clouds like scale, but with the reliability and control of a private cloud data, right? So, it's then your own data center. And ObjectScale is S3 compliant, right? So while delivering the enterprise features like global replication, native multi-tenancy, fueling everything from Dev Test Sandbox to globally distributed data, right? So you've got in-built ObjectScale replication that allows you to place your data anywhere you got ObjectScale (indistinct). From edge to core to data center. >> Okay, so it fits into the Kubernetes world. I call it Kubernetes compatible. The key there is automation, because that's the whole point of containers is, right? It allows you to deploy as many apps as you need to, wherever you need to in as many instances and then do rolling updates, have the same security, same API, all that level of consistency. So that's really important. That's how modern apps are being developed. We're in a new age year. It's no longer about the machines, it's about infrastructure as code. So once ObjectScale is generally available which I think is soon, I think it's this year, What should customers do, what's their next step? >> Absolutely, yeah, it's coming out November 2nd. Reach out to your Dell representatives, right? Get an in-depth demo on ObjectScale. Better yet, you get a POC, right? Get a proof of concept, have it set up in your data center and play with it. You can also download the free full featured community edition. We're going to have a community edition that's free up to 30 terabytes of usage, it's full featured. Download that, play with it. If you like it, you can upgrade that free community edition, will license paid version. >> And you said that's full featured. You're not neutering the community edition? >> Exactly, absolutely, it's full featured. >> Nice, that's a great strategy. >> We're confident, we're confident in what we're delivering, and we want you guys to play with it without having your money tied up. >> Nice, I mean, that's the model today. Gone are the days where you got to get new customers in a headlock to get them to, they want to try before they buy. So that's a great little feature. Anahad, thanks so much for joining us on theCUBE. Sounds like it's been a very busy year and it's going to continue to be so. Look forward to see what's coming out with ECS and ObjectScale and seeing those two worlds come together, thank you. >> Yeah, absolutely, it was a pleasure. Thank you so much. >> All right, and thank you for watching this CUBE Conversation. This is Dave Vellante, we'll see you next time. (upbeat music)

(upbeat music) >> Welcome everybody to this CUBE Conversation. My name is Dave Vellante, and we're here to talk about Object storage and the momentum in the space. And what Dell Technologies is doing to compete in this market, I'm joined today by Anahad Dhillon, who's the Product Manager for Dell, EMC's ECS, and new ObjectScale products. Anahad, welcome to theCUBE, good to see you. >> Thank you so much Dave. We appreciate you having me and Dell (indistinct), thanks. >> Its always a pleasure to have you guys on, we dig into the products, talk about the trends, talk about what customers are doing. Anahad before the Cloud, Object was this kind of niche we seen. And you had simple get, put, it was a low cost bit bucket essentially, but that's changing. Tell us some of the trends in the Object storage market that you're observing, and how Dell Technology sees this space evolving in the future please. >> Absolutely, and you hit it right on, right? Historically, Object storage was considered this cheap and deep place, right? Customers would use this for their backup data, archive data, so cheap and deep, no longer the case, right? As you pointed out, the ObjectSpace is now maturing. It's a mature market and we're seeing out there customers using Object or their primary data so, for their business critical data. So we're seeing big data analytics that we use cases. So it's no longer just cheap and deep, now your primary workloads and business critical workloads being put on with an object storage now. >> Yeah, I mean. >> And. >> Go ahead please. >> Yeah, I was going to say, there's not only the extend of the workload being put in, we'll also see changes in how Object storage is being deployed. So now we're seeing a tighter integration with new depth models where Object storage or any storage in general is being deployed. Our applications are being (indistinct), right? So customers now want Object storage or storage in general being orchestrated like they would orchestrate their customer applications. Those are the few key trends that we're seeing out there today. >> So I want to dig into this a little bit with you 'cause you're right. It used to be, it was cheap and deep, it was slow and it required sometimes application changes to accommodate. So you mentioned a few of the trends, Devs, everybody's trying to inject AI into their applications, the world has gone software defined. What are you doing to respond to all these changes in these trends? >> Absolutely, yeah. So we've been making tweaks to our object offering, the ECS, Elastic Cloud Storage for a while. We started off tweaking the software itself, optimizing it for performance use cases. In 2020, early 2020, we actually introduced SSDs to our notes. So customers were able to go in, leverage these SSD's for metadata caching improving their performance quite a bit. We use these SSDs for metadata caching. So the impact on the performance improvement was focused on smaller reads and writes. What we did now is a game changer. We actually went ahead later in 2020, introduced an all flash appliance. So now, EXF900 and ECS all flash appliance, it's all NVME based. So it's NVME SSDs and we leveraged NVME over fabric xx for the back end. So we did it the right way did. We didn't just go in and qualified an SSD based server and ran object storage on it, we invested time and effort into supporting NVME fabric. So we could give you that performance at scale, right? Object is known for scale. We're not talking 10, 12 nodes here, we're talking hundreds of nodes. And to provide you that kind of performance, we went to ahead. Now you've got an NVME based offering EXF900 that you can deploy with confidence, run your primary workloads that require high throughput and low latency. We also come November 5th, are releasing our next gen SDS offering, right? This takes the Troven ECS code that our customers are familiar with that provides the resiliency and the security that you guys expect from Dell. We're re platforming it to run on Kubernetes and be orchestrated by Kubernetes. This is what we announced that VMware 2021. If you guys haven't seen that, is going to go on-demand for VMware 2021, search for ObjectScale and you get a quick demo on that. With ObjectScale now, customers can quickly deploy enterprise grade Object storage on their existing environment, their existing it infrastructure, things like VMware, infrastructure like VMware and infrastructure like OpenShift. I'll give you an example. So if you were in a VMware shop that you've got vSphere clusters in your data center, with ObjectScale, you'll be able to quickly deploy your Object enterprise grid Object offering from within vSphere. Or if you are an OpenShift customer, right? If you've got OpenShift deployed in your data center and your Red Hat shop, you could easily go in, use that same infrastructure that your applications are running on, deploy ObjectScale on top of your OpenShift infrastructure and make available Object storage to your customers. So you've got the enterprise grade ECS appliance or your high throughput, low latency use cases at scale, and you've got this software defined ObjectScale, which can deploy on your existing infrastructure, whether that's VMware or Red Hat OpenShift. >> Okay, I got a lot of follow up questions, but let me just go back to one of the earlier things you said. So Object was kind of cheap, deep and slow, but scaled. And so, your step one was metadata caching. Now of course, my understanding is with Object, the metadata and the data within the object. So, maybe you separated that and made it high performance, but now you've taken the next step to bring in NVME infrastructure to really blow away all the old sort of scuzzy latency and all that stuff. Maybe you can just educate us a little bit on that if you don't mind. >> Yeah, absolutely. Yeah, that was exactly the stepped approach that we took. Even though metadata is tightly integrated in Object world, in order to read the actual data, you still got to get to the metadata first, right? So we would cache the metadata into SSDs reducing that lookup that happens for that metadata, right? And that's why it gave you the performance benefit. But because it was just tied to metadata look-ups, the performance for larger objects stayed the same because the actual data read was still happening from the hard drives, right? With the new EXF900 which is all NVME based, we've optimized the our ECS Object code leveraging VME, data sitting on NVME drives, the internet connectivity, the communication is NVME over fabric, so it's through and through NVME. Now we're talking milliseconds and latency and thousands and thousands of transactions per second. >> Got it, okay. So this is really an inflection point for Objects. So these are pretty interesting times at Dell, you got the cloud expanding on prem, your company is building cloud-like capabilities to connect on-prem to the cloud across cloud, you're going out to the edge. As it pertains to Object storage though, it sounds like you're taking a sort of a two product approach to your strategy. Why is that, and can you talk about the go-to market strategy in that regard? >> Absolutely, and yeah, good observation there. So yes and no, so we continued to invest in ECS. ECS continues to stay a product of choice when customer wants that traditional appliance deployment model. But this is a single hand to shape model where you're everything from your hardware to your software the object solution software is all provided by Dell. ECS continues to be the product where customers are looking for that high performance, fine tune appliance use case. ObjectScale comes into play when the needs are software defined. When you need to deploy the storage solution on top of the same infrastructure that your applications are run, right? So yes, in the short-term, in the interim, it's a two product approach of both products taking a very distinct use case. However, in the long-term, we're merging the two quote streams. So in the long-term, if you're an ECS customer and you're running ECS, you will have an in-place data upgrade to ObjectScale. So we're not talking about no forklift upgrades, we're not talking about you're adding additional servers and do a data migration, it's a code upgrade. And then I'll give you an example, today on ECS, we're at code variation 3.6, right? So if you're a customer running ECS, ECS 3.X in the future, and so we've got a roadmap where 3.7 is coming out later on this year. So from 3.X, customers will upgrade the code data in place. Let's call it 4.0, right? And that brings them up to ObjectScale. So there's no nodes left behind, there's an in-place code upgrade from ECS to the ObjectScale merging the two code streams and the long-term, single code, short-term, two products for both solving the very distinct users. >> Okay, let me follow up, put on my customer hat. And I'm hearing that you can tell us with confidence that irrespective of whether a customer invested ECS or ObjectScale, you're not going to put me into a dead-end. Every customer is going to have a path forward as long as their ECS code is up-to-date, is that correct? >> Absolutely, exactly, and very well put, yes. No nodes left behind, investment protection, whether you've got ECS today, or you want to invest into ECS or ObjectScale in the future, correct. >> Talk a little bit more about ObjectScale. I'm interested in kind of what's new there, what's special about this product, is there unique functionality that you're adding to the product? What differentiates it from other Object stores? >> Absolutely, my pleasure. Yeah, so I'll start by reiterating that ObjectScale it's built on that Troven ECS code, right? It's the enterprise grid, reliability and security that our customers expect from Dell EMC, right? Now we're re platforming ECS who allow ObjectScale to be Kubernetes native, right? So we're leveraging that microservices-based architecture, leveraging that native orchestration capabilities of Kubernetes, things like resource isolation or seamless (indistinct), I'm sorry, load balancing and things like that, right? So the in-built native capabilities of Kubernetes. ObjectScale is also build with scale in mind, right? So it delivers limitless scale. So you could start with terabytes and then go up to petabytes and beyond. So unlike other file system-based Object offerings, ObjectScale software would have a limit on your number of object stores, number of buckets, number of objects you store, it's limitless. As long as you can provide the hardware resources under the covers, the software itself is limitless. It allows our customers to start small, so you could start as small as three node and grow their environment as your business grows, right? Hundreds of notes. With ObjectScale, you can deploy workloads at public clouds like scale, but with the reliability and control of a private cloud data, right? So, it's then your own data center. And ObjectScale is S3 compliant, right? So while delivering the enterprise features like global replication, native multi-tenancy, fueling everything from Dev Test Sandbox to globally distributed data, right? So you've got in-built ObjectScale replication that allows you to place your data anywhere you got ObjectScale (indistinct). From edge to core to data center. >> Okay, so it fits into the Kubernetes world. I call it Kubernetes compatible. The key there is automation, because that's the whole point of containers is, right? It allows you to deploy as many apps as you need to, wherever you need to in as many instances and then do rolling updates, have the same security, same API, all that level of consistency. So that's really important. That's how modern apps are being developed. We're in a new age year. It's no longer about the machines, it's about infrastructure as code. So once ObjectScale is generally available which I think is soon, I think it's this year, What should customers do, what's their next step? >> Absolutely, yeah, it's coming out November 2nd. Reach out to your Dell representatives, right? Get an in-depth demo on ObjectScale. Better yet, you get a POC, right? Get a proof of concept, have it set up in your data center and play with it. You can also download the free full featured community edition. We're going to have a community edition that's free up to 30 terabytes of usage, it's full featured. Download that, play with it. If you like it, you can upgrade that free community edition, will license paid version. >> And you said that's full featured. You're not neutering the community edition? >> Exactly, absolutely, it's full featured. >> Nice, that's a great strategy. >> We're confident, we're confident in what we're delivering, and we want you guys to play with it without having your money tied up. >> Nice, I mean, that's the model today. Gone are the days where you got to get new customers in a headlock to get them to, they want to try before they buy. So that's a great little feature. Anahad, thanks so much for joining us on theCUBE. Sounds like it's been a very busy year and it's going to continue to be so. Look forward to see what's coming out with ECS and ObjectScale and seeing those two worlds come together, thank you. >> Yeah, absolutely, it was a pleasure. Thank you so much. >> All right, and thank you for watching this CUBE Conversation. This is Dave Vellante, we'll see you next time. (upbeat music)

(bright upbeat music) >> Welcome to theCUBE, our coverage of Dell Technologies World, the Digital Experience continues. I have a long-time guest coming back, joining me in the next segment here. Jon Siegal is back, the Vice President of Product Marketing at Dell Technologies. Jon, it's good to see you, welcome back to the program. >> Thanks Lisa, always great to be on. >> We last spoke about six months ago and here we are still at home. >> I know. >> But there has been no slowdown whatsoever in the last year. We were talking to you a lot about Edge last time but we're going to talk about PowerStore today. It's just coming up on its one year anniversary. You launched it right when the pandemic happened. >> That's right. >> Talk to me about what's happened in the last year with respect to PowerStore. Adoption, momentum, what's going on? >> Yeah, great, listen, what a year it's been, right? But certainly for PowerStore especially, I mean, customers and partners around the world have really embraced PowerStore, specifically really it's modern architecture. What many people may not know is this is actually the fastest ramping new architecture we've had in all of Dell's history, which is quite a history of course. And we saw 4 X quarter over quarter growth in the most recent quarter. And you know, in terms of shipments, we've shipped well over 400 petabytes of PowerStore, you know, so special thanks to lots of our customers around the world and industries like education, gaming, transportation, retail. More than 60 countries, I think 62 countries now. They include customers like Columbia Southern University, Habib Bank, Real Page, the University of Pisa and Ultra Leap, just to name a few. And to give you a sense of how truly game changing it's been in the market is that approximately 20% of the customers with PowerStore are new to Dell, new to Dell Technologies. And we've tripled the number of wins against some of our key competitors in just the last quarter as well. So look, it's been quite a year, like you said and we're not stopping there. >> Yeah, you must have to wear a neck brace from that whiplash of moving so quickly. (both laughing) But that's actually a good problem to have. >> It is. >> And curious about, is it 20% of the PowerStore customers are net new to Dell? >> Yeah. >> Interesting that you've captured that much in a very turbulent year. Any industries in particular that you see as really being transformed by the technology? >> Yeah, it's a great question. I think just like we're bringing a disruptive technology to market, there's a lot of industries out there that are disrupting themselves as well, right, and how they transform, particularly with, you know, in this new era during the pandemic. I think, I can give you a great example. One of the new capabilities of PowerStore is AppsON just for those that aren't familiar. AppsON is the ability for PowerStore to run apps directly on the appliance, good name, right? And it's thanks to a built-in VMware ESXi hypervisor. And where we've seen really good traction with AppsON, is in storage intensive applications at the edge. And that brings me to my example. And this one's in retail. And you know, of course just like every industry I think it's been up-ended in the past year. There's a large supermarket chain in northern China that is new to Dell. During the pandemic they needed to fast-track the development of a smart autonomous retail system in all their stores, so that their customers could make their purchases via smartphone app. And again, just limiting the essentially the person to person interaction during the pandemic and this required a significant increase in transaction processing to get to the store locations that they didn't have equipment for before, as well as support for big data analytics applications to understand the customer behavior that's going on in real-time. So the net result is they chose PowerStore. They were new to Dell and they deployed it in their stores and delivered a seamless shopping experience via smartphone apps. The whole shopping experience was completely revolutionized. And I think this is really a great example of again, how the innovations that are in PowerStore are enabling our customers to really rethink how they're transacting business. >> Well, enabling the supermarkets to be the edge but also in China where everything started, so much, the market dynamics are still going on, but how quickly were they able to get PowerStore up and running and facilitate that seamless smartphone shopping experience? >> It was only weeks, only weeks, weeks from beginning to getting them up to speed. I mean, we've had great coverage, great support. And again, they embraced, I mean, they happened to leverage the AppsON capabilities, so they were able to run some of their applications directly on the appliance and they were able to get that up and running very quickly. And they were already a VMware customer as well. So they were already familiar with some of the tools and the integration of the VMware. And again, that's also been a sweetspot for this particular offer. >> Okay, got it. So a lot in it's first year. You said 4 X growth, over 60 countries, 400 petabytes plus shipped, a lot of new net new customers. What is new? What are you announcing that's new and that's going to take that up even a higher level? >> That's right. We're always going to up the ante, right? We're always going to, we can't rest on our laurels for too long. Look, we're very excited to share what's new for PowerStore. And that is one of the reasons we're here of course. I can break it down into two key highlights. First is a major software update that brings more enterprise innovation, more speed, more automation in particular to both new and existing customers. And we're also excited to announce a new lower cost entry model for the PowerStore family called the PowerStore 500. And this offers an incredible amount of enterprise class storage capabilities, much of which I have talked about and will talk more about today, for the price. And the price itself is what's going to surprise some folks. It starts as low as 28,000 US street price which is pretty significant, you know, in terms of a game changer, we think, in this industry. >> So let's talk about the software update first. You've got PowerStore 2.0, happy birthday to your customers who are going to take advantage of this. >> That's right. >> Kind of talk me through what some of the technological advancements are that your customers are going to be able to leverage? >> That's a great point. Yeah, so from a software perspective I like how you said that, happy birthday, yeah so all of our, just to be clear from a software update perspective, all of our existing customers are going to get this as a simple free non-disruptive update. And this is a commitment we've had to our customers for some time. And really it's the mantra if you will, of PowerStore, which is all about ensuring that our customers can encounter our very flexible platform that will keep giving them the latest and greatest. So really a couple of things I want to highlight from PowerStore that are brand new. One is we're giving a speed boost to the entire PowerStore lineup. Customers now, existing customers, you get up to 25% faster, mixed workload performance which is incredible, right off the bat. Secondly, we're enabling our customers to take full advantage of NVME now across the data center with the option of running NVME over fiber channel. And this again requires just a simple software update and no additional hardware if they already have 32 gig capable switches and HBAs on-prem. We've also made our unique AppsON feature, which I just talked about in the China example, we've made that more powerful and with scale out. This means more aggregate power, more aggregate capacity and it makes it even more ideal now for storage intensive apps to run at the edge with PowerStore. Another capability that's been very popular with our customers is our data reduction specifically our intelligent Dido which is always on and automated. And now what it does is it enables customers to boost performance while still guaranteeing the four to one data reduction that we have, at the same time. So just to give a quick example, when the system is under extreme IO, duress if you will, it automatically prioritize that IO versus the DDUP itself and provides a 20% turbo boost if you will, of performance boost for the applications running. All this is done automatically, zero management effort, zero impact to the data reduction guarantee of four to one that we already have in place. And then the last highlight I'd like to bring up is, last but not least, is one we're really proud of is the ability for our customers to now take more cost advantage, if you will, cost effective advantage of SCM or storage class memory. PowerStore now differentiates between SCM drives and NVME drives within the same chassis. So they can use SCM as a high-performance layer, if you will with as few as one drive, right? So they don't have to populate the whole chassis, they can use just one SCM drive for cost-effectiveness, for embedded data access. And this actually helps reduce the workload latency by up to 15%. So, another great example on top of NVME that I already mentioned, of how PowerStore is leading the practical adoption of next generation technologies. >> Are you seeing with the lower cost PowerStore 500, is that an opportunity for Dell to expand into the midsize market and an opportunity for those smaller customers to be able to take advantage of this technology? >> Absolutely, yeah. So the PowerStore finder, which we're really excited about introducing does exactly what you just said, Lisa. It is going to allow us to bring PowerStore and the experience of PowerStore to a broad range of businesses, a much broader range of edge use cases as well. And we're really excited about that. It's an incredible amount of enterprise storage class performance, as I mentioned, and functionality for the price that is again, 28,000 starting. And this includes all of the enterprise software capabilities I've been talking about. The ability to cluster, four to one data reduction guarantee, anytime upgrades. And to put this in context, a single 2U appliance, the PowerStore 500 supports up to 2.4 million SQL transactions per minute. I mean, this thing packs a punch, like no other, right? And it's a great fit for stand-alone or edge deployments in virtually every industry, we've mentioned retail already also healthcare, manufacturing, education and more. It's an offering that's really ideal for any solution that requires an optimization of price/performance, small footprint and effortless automation. And I can tell you, it's not just customers that are excited about this, as you can imagine our channel partners, they can't wait to get their hands on this either. >> Was just going to ask you about the channel. >> It is going to help them reach new sets of customers that they never had before. You mentioned midsize, but also in addition to that, it's just going to open it up to all new sets of use cases as well. So I'm really excited to see the creativity from our channel partners and customers and how they adopt and use the PowerStore 500 going forward. >> Tell me about some of those new use cases that it's going to open up. We've seen so many new things in the last year and such acceleration. What are some of the new use cases that this is going to help unlock value for? >> Yeah, again, I think it's going to come down a lot to the edge in particular, as well as mid-size, it can run, again, this can run storage, intensive applications. So it's really about coming down to a price point that I think the biggest example will be mid-sized businesses that now, it's now affordable to. That they weren't able to get this enterprise class capabilities in the past more than anything else. Cause it's all the same capabilities that I've mentioned but it allows them to run all types of things. It could be, they could run, new next-generation intensive data, intensive databases. They can run VDI, they can run SQL, it does, essentially more than anything else makes existing use cases more accessible to mid-sized businesses. >> Got it, okay. So, so much momentum going on in the first year. A lot of that you're souping it up with this your new software, we talked about the new mid-size enterprise version PowerStore 500. What else can we expect from PowerStore, the rest of calendar 2021? >> Yeah, I think lots of things. So first of all we're so pleased at the amount of commitment to innovation that we've had over the past year. We're going to continue to work very closely with VMware to drive more and more innovation and enhancements with capabilities like AppsON that I talked about, and VM-ware or (indistinct) which is a key enabler for that. We're also committed to continuing to lead the industry in the adoption of modern technologies. I gave some good examples today of NVME and AppsON and SCM, storage class memory, and customers can expect that continued commitment. Look, we've designed PowerStore from the ground up to be very flexible so that it can be enhanced and improved non-disruptively. And I think we did that with this release. We proved that and no one can predict the future, clearly, it's been a crazy year. And so businesses need storage that's going to be flexible with them and grow with them and evolve with them. And customers can expect that from PowerStore. And we plan on doing just that. >> So customers can, that are interested can go direct to Dell. They can also go through your huge channel, you said, in terms of those customers that are thinking about it maybe adding to the percentage of new customers. What's your advice on them in terms of next steps? >> Yeah, next steps is, you know, I got to say this, we've done, it's crazy, we've done over 20,000 demos of PowerStore in one year, no joke. And you know, it's a new world. And so the next step is to reach out to Dell. We'd love to showcase this through a demo, give them whether it's a remote experience that way or remote proof of concept but yeah, reach out to Dell, your local rep or local channel partner and we'd love to show you what's possible more than anything else and look, we're really proud of what we've accomplished here. Just as impressive as these updates, I must say, is that in many instances, the team that brought this to market, the engineering team, they did this just like we're doing today, right? Over Zoom, remotely, while balancing life and work. So I just also want to thank the team for their commitment to delivering innovation to our customers. It hasn't wavered at all and I want to thank our top notch team. >> Right, an amazing amount of work done. You've had a very busy year and glad that you're well and healthy and been as successful with PowerStore. We can't wait to see in the next year those numbers that you shared even go up even more. Jon, thank you for joining us >> Looking forward to it. and sharing what's new with PowerStore. We appreciate your time. >> Always a pleasure, Lisa. >> Likewise >> Look forward to talking to you soon. >> Yeah >> Take care. >> For Jon Siegal, I'm Lisa Martin, you're watching theCUBE's coverage of Dell Technologies World, a Digital Experience. (slow upbeat music)

>> From around the globe, it's theCUBE, with digital coverage of VMworld 2020, brought to you by the VMworld and its ecosystem partners. >> I'm Stu Miniman, and welcome back to theCUBES coverage of VMworld 2020, our 11th year doing this show, of course, the global virtual event. And what do we love talking about on theCUBE? We love talking to customers. It is a user conference, of course, so really happy to welcome to the program. From the University of Pisa, the Chief Technology Officer Maurizio Davini and joining him is Thierry Pellegrini, one of our theCUBE alumni. He's the vice president of worldwide, I'm sorry, Workload Solutions and HPC with Dell Technologies. Thierry, thank you so much for joining us. >> Thanks too. >> Thanks to you. >> Alright, so let, let's start. The University of Pisa, obviously, you know, everyone knows Pisa, one of the, you know, famous city iconic out there. I know, you know, we all know things in Europe are a little bit longer when you talk about, you know, some of the venerable institutions here in the United States, yeah. It's a, you know, it's a couple of hundred years, you know, how they're using technology and everything. I have to imagine the University of Pisa has a long storied history. So just, if you could start before we dig into all the tech, give us our audience a little bit, you know, if they were looking up on Wikipedia, what's the history of the university? >> So University of Pisa is one of the oldest in the world because there has been founded in 1343 by a pope. We were authorized to do a university teaching by a pope during the latest Middle Ages. So it's really one of the, is not the oldest of course, but the one of the oldest in the world. It has a long history, but as never stopped innovating. So anything in Pisa has always been good for innovating. So either for the teaching or now for the technology applied to a remote teaching or a calculation or scientific computing, So never stop innovating, never try to leverage new technologies and new kind of approach to science and teaching. >> You know, one of your historical teachers Galileo, you know, taught at the university. So, you know, phenomenal history help us understand, you know, you're the CTO there. What does that encompass? How, you know, how many students, you know, are there certain areas of research that are done today before we kind of get into the, you know, the specific use case today? >> So consider that the University of Pisa is a campus in the sense that the university faculties are spread all over the town. Medieval like Pisa poses a lot of problems from the infrastructural point of view. So, we have bought a lot in the past to try to adapt the Medieval town to the latest technologies advancement. Now, we have 50,000 students and consider that Pisa is a general partners university. So, we cover science, like we cover letters in engineering, medicine, and so on. So, during the, the latest 20 years, the university has done a lot of effort to build an infrastructure that was able to develop and deploy the latest technologies for the students. So for example, we have a private fiber network covering all the town, 65 kilometers of a dark fiber that belongs to the university, four data centers, one big and three little center connected today at 200 gigabit ethernet. We have a big data center, big for an Italian University, of course, and not Poland and U.S. university, where is, but also hold infrastructure for the enterprise services and the scientific computing. >> Yep, Maurizio, it's great that you've had that technology foundation. I have to imagine the global pandemic COVID-19 had an impact. What's it been? You know, how's the university dealing with things like work from home and then, you know, Thierry would love your commentary too. >> You know, we, of course we were not ready. So we were eaten by the pandemic and we have to adapt our service software to transform from imperson to remote services. So we did a lot of work, but we are able, thanks to the technology that we have chosen to serve almost a 100% of our curriculum studies program. We did a lot of work in the past to move to virtualization, to enable our users to work for remote, either for a workstation or DC or remote laboratories or remote calculation. So virtualization has designed in the past our services. And of course when we were eaten by the pandemic, we were almost ready to transform our service from in person to remote. >> Yeah, I think it's, it's true, like Maurizio said, nobody really was preparing for this pandemic. And even for, for Dell Technologies, it was an interesting transition. And as you can probably realize a lot of the way that we connect with customers is in person. And we've had to transition over to modes or digitally connecting with customers. We've also spent a lot of our energy trying to help the community HPC and AI community fight the COVID pandemic. We've made some of our own clusters that we use in our HPC and AI innovation center here in Austin available to genomic research or other companies that are fighting the the virus. And it's been an interesting transition. I can't believe that it's already been over six months now, but we've found a new normal. >> Detailed, let's get in specifically to how you're partnering with Dell. You've got a strong background in the HPC space, working with supercomputers. What is it that you're turning to Dell in their ecosystem to help the university with? >> So we are, we have a long history in HPC. Of course, like you can imagine not to the biggest HPC like is done in the U.S. so in the biggest supercomputer center in Europe. We have several system for doing HPC. Traditionally, HPC that are based on a Dell Technologies offer. We typically host all kind of technology's best, but now it's available, of course not in a big scale but in a small, medium scale that we are offering to our researcher, student. We have a strong relationship with Dell Technologies developing together solution to leverage the latest technologies, to the scientific computing, and this has a lot during the research that has been done during this pandemic. >> Yeah, and it's true. I mean, Maurizio is humble, but every time we have new technologies that are to be evaluated, of course we spend time evaluating in our labs, but we make it a point to share that technology with Maurizio and the team at the University of Pisa, That's how we find some of the better usage models for customers, help tuning some configurations, whether it's on the processor side, the GPU side, the storage and the interconnect. And then the topic of today, of course, with our partners at VMware, we've had some really great advancements Maurizio and the team are what we call a center of excellence. We have a few of them across the world where we have a unique relationship sharing technology and collaborating on advancement. And recently Maurizio and the team have even become one of the VMware certified centers. So it's a great marriage for this new world where virtual is becoming the norm. >> But well, Thierry, you and I had a conversation to talk earlier in the year when VMware was really geering their full kind of GPU suite and, you know, big topic in the keynote, you know, Jensen, the CEO of Nvidia was up on stage. VMware was talking a lot about AI solutions and how this is going to help. So help us bring us in you work with a lot of the customers theory. What is it that this enables for them and how to, you know, Dell and VMware bring, bring those solutions to bear? >> Yes, absolutely. It's one statistic I'll start with. Can you believe that only on average, 15 to 20% of GPU are fully utilized? So, when you think about the amount of technology that's are at our fingertips and especially in a world today where we need that technology to advance research and scientistic discoveries. Wouldn't it be fantastic to utilize those GPU's to the best of our ability? And it's not just GPU's , I think the industry has in the IT world, leverage virtualization to get to the maximum recycles for CPU's and storage and networking. Now you're bringing the GPU in the fold and you have a perfect utilization and also flexibility across all those resources. So what we've seen is that convergence between the IT world that was highly virtualized, and then this highly optimized world of HPC and AI because of the resources out there and researchers, but also data scientists and company want to be able to run their day to day activities on that infrastructure. But then when they have a big surge need for research or a data science use that same environment and then seamlessly move things around workload wise. >> Yeah, okay I do believe your stat. You know, the joke we always have is, you know, anybody from a networking background, there's no such thing as eliminating a bottleneck, you just move it. And if you talk about utilization, we've been playing the shell game for my entire career of, let's try to optimize one thing and then, oh, there's something else that we're not doing. So,you know, so important. Retail, I want to hear from your standpoint, you know, virtualization and HPC, you know, AI type of uses there. What value does this bring to you and, you know, and key learnings you've had in your organization? >> So, we as a university are a big users of the VMware technologies starting from the traditional enterprise workload and VPI. We started from there in the sense that we have an installation quite significant. But also almost all the services that the university gives to our internal users, either personnel or staff or students. At a certain point that we decided to try to understand the, if a VMware virtualization would be good also for scientific computing. Why? Because at the end of the day, their request that we have from our internal users is flexibility. Flexibility in the sense of be fast in deploying, be fast to reconfiguring, try to have the latest beats on the software side, especially on the AI research. At the end of the day we designed a VMware solution like you, I can say like a whiteboard. We have a whiteboard, and we are able to design a new solution of this whiteboard and to deploy as fast as possible. Okay, what we face as IT is not a request of the maximum performance. Our researchers ask us for flexibility then, and want to be able to have the maximum possible flexibility in configuring the systems. How can I say I, we can deploy as more test cluster on the visual infrastructure in minutes or we can use GPU inside the infrastructure tests, of test of new algorithm for deep learning. And we can use faster storage inside the virtualization to see how certain algorithm would vary with our internal developer can leverage the latest, the beat in storage like NVME, MVMS or so. And this is why at the certain point, we decided to try visualization as a base for HPC and scientific computing, and we are happy. >> Yeah, I think Maurizio described it it's flexibility. And of course, if you think optimal performance, you're looking at the bare medal, but in this day and age, as I stated at the beginning, there's so much technology, so much infrastructure available that flexibility at times trump the raw performance. So, when you have two different research departments, two different portions, two different parts of the company looking for an environment. No two environments are going to be exactly the same. So you have to be flexible in how you aggregate the different components of the infrastructure. And then think about today it's actually fantastic. Maurizio was sharing with me earlier this year, that at some point, as we all know, there was a lot down. You could really get into a data center and move different cables around or reconfigure servers to have the right ratio of memory, to CPU, to storage, to accelerators, and having been at the forefront of this enablement has really benefited University of Pisa and given them that flexibility that they really need. >> Wonderful, well, Maurizio my understanding, I believe you're giving a presentation as part of the activities this week. Give us a final glimpses to, you know, what you want your peers to be taking away from what you've done? >> What we have done that is something that is very simple in the sense that we adapt some open source software to our infrastructure in order to enable our system managers and users to deploy HPC and AI solution fastly and in an easy way to our VMware infrastructure. We started doing a sort of POC. We designed the test infrastructure early this year and then we go fastly to production because we had about the results. And so this is what we present in the sense that you can have a lot of way to deploy Vitola HPC, Barto. We went for a simple and open source solution. Also, thanks to our friends of Dell Technologies in some parts that enabled us to do the works and now to go in production. And that's theory told before you talked to has a lot during the pandemic due to the effect that stay at home >> Wonderful, Thierry, I'll let you have the final word. What things are you drawing customers to, to really dig in? Obviously there's a cost savings, or are there any other things that this unlocks for them? >> Yeah, I mean, cost savings. We talked about flexibility. We talked about utilization. You don't want to have a lot of infrastructure sitting there and just waiting for a job to come in once every two months. And then there's also the world we live in, and we all live our life here through a video conference, or at times through the interface of our phone and being able to have this web based interaction with a lot of infrastructure. And at times the best infrastructure in the world, makes things simpler, easier, and hopefully bring science at the finger tip of data scientists without having to worry about knowing every single detail on how to build up that infrastructure. And with the help of the University of Pisa, one of our centers of excellence in Europe, we've been innovating and everything that's been accomplished for, you know at Pisa can be accomplished by our customers and our partners around the world. >> Thierry, Maurizio, thank you much for so much for sharing and congratulations on all I know you've done building up that COE. >> Thanks to you. >> Thank you. >> Stay with us, lots more covered from VMworld 2020. I'm Stu Miniman as always. Thank you for watching the theCUBE. 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>> Narrator: From around the globe, it's theCUBE. With digital coverage of VMworld 2020 brought to you by VMware and its ecosystem partners. >> Welcome back, I'm Stuart Miniman and this is theCUBES's coverage of VMworld 2020. Our 11th year doing the show and happy to welcome back to the program one of our CUBE's alums. Somebody that's is going to VMworld longer than we have been doing it for theCUBE. So Vaughn Stewart he is the Vice President of Technology Alliances with Pure Storage Vaughn, nice to see you. How you doing? >> Hey, Stu. CUBE thanks for having me back. I miss you guys I wish we were doing this in person. >> Yeah, we all wish we were in person but as we've been saying all this year, we get to be together even while we're apart. So we look to you on little screens and things like that rather than bumping into each other at some of the after parties or the coffee shops all around San Francisco. So Vaughn, obviously you know Pure Storage long, long, long partnership with VMware. I think back the first time that I probably met with the Pure team, in person, it probably was around Moscone, having a breakfast having a lunch, having a briefing or the likes. So just give us the high level. I know we've got a lot of things to dig into. Pure and VMware, how's the partnership going these days? >> Partnership is growing fantastic Pure invests a lot of engineering resources in programs with VMware. Particularly the VMware design partner programs for vVols, Container-Native Storage et cetera. The relationship is healthy the business is growing strong. I'm very excited about the investments that VMware is making around VMware Cloud Foundation as a replatforming of what's going on MPREM to help better enable hybrid cloud and to support Tanzu and Kubernetes platforms. So a lot going on at the infrastructure level that ultimately helps customers of all to adopt cloud native workloads and applications. >> Wonderful. Well a lot of pieces to unpack that. Of course Tanzu big piece of what they're talking about. But let's start. You mentioned VCF. You know what is it on the infrastructure side, that is kind of driving your customer adoption these days, and the some of the latest integrations that you're doing? >> Yeah you know VCF has really caught the attention of our mid to large or mid to enterprise size customers. The focus around, as I use the phrase replatform is planning out with VMworld phrase. But the focus on simplifying the lifecycle management, giving you a greater means to connect to the public cloud. I don't know if you're aware, but all VMware public cloud offerings have the VCF framework in terms of architectural framework. So now bringing that back on-prem, allowing customers on a per workload domain basis to extend to a hybrid cloud capability. It's a really big advancement from kind of the base vSphere infrastructure, which architecturally hasn't had a significant advancement in a number of years. What's really big around VCF besides the hybrid connectivity, is the couple of new tools SDDC Manager and vSphere Lifecycle Manager. These tools can actually manage the infrastructure from bare metal up to workload domains and then from workload domains you're now handing off to considered like delegated vCenter Servers right? So that the owner of a workload if you will and then that person can go ahead and provision virtual machines or containers, based on whatever is required to run their workloads. So for us the big gain of this is the advancement in the VMware management. They are bringing their strength in providing simplicity, and end-to-end hardwared application management to disaggregated architectures. Where the focus of that capability has been with HCI over say the past five or six years. And so this really helps close that last gap, if you will, and completes a 360 degree view of providing simplified management across dissimilar architecture and it's consistent and it's standardized by VMware. So HCI, disaggregated architecture, public cloud, it all operates the same. >> So Vaughn, you made a comment about not a lot of changes. If I remember our friends at VMware they made a statement vSphere 7 was the biggest architectural change in over a decade. Of course bringing in Kubernetes it's a major piece of the Tanzu discussion. Pure. Your team's been pretty busy in the Kubernetes space too. Recent acquisition of Portwox to help accelerate that. Maybe let's talk a little bit about you know cloud native. What you're hearing from your customers. (chuckles) And yeah, like we've Dave Vellante had a nice interview with, Pure and Portwox CEOs. Give the VMworld audience a little bit of an update as you know where you all fit in the Kubernetes space. >> Yeah and actually, there was a lot that you shared there kind of in connecting the VCF piece through to vSphere 7 and a lot of changes there in driving into Tanzu and containers. So maybe we're going to jump around here a bit but look we're really excited. We've been working with VMware, but in addition to all of our application partners, you are seeing nearly every traditional enterprise application being replatformed to support containers. I'd love to share with you more details, but there's a lot of NDAs I'd be breaking in that. But the way for enterprise adoption of containers is right upon us. And so the timing for VMware Tanzu is ideal. Our focus has always been around providing a rich set of data services. One that provides faster provisioning, simplified fleet management, and the ability to move that container and those data services between different clouds and different cloud platforms, Be it on-prem, or in the public cloud space. We've had a lot of success doing that with the Pure Service Orchestrator Version 6.0 enables CSI compliant persistent storage capabilities. And it does support Tanzu today. The addition or I should say the acquisition of Portworx is really interesting. Because now we're bringing on an enhanced set of data services that not only run on a Pure Storage storage products, but runs universally regardless of the storage platform, or the Cloud architecture. The capabilities within Portworx are above and beyond what we had in PSO. So this is a great expansion of our capabilities. And ultimately we want to help customers. Whether they want to do containers solely on Tanzu, or if they're going to mix Tanzu with say Amazon EKS, or they've got some department that does development on OpenShift. Whatever it might be. You know that the focus of storage vendors is obviously to help customers make that data available on these platforms through a consistent control plane. >> Yeah. Vaughn it's a great acquisition. Think a nice fit. Anybody that's been talking to Pure the last year or so you've been. How do we take the storage make it more cloud native if you will. So you've got code. Obviously, you've got a great partnership with VMware, but as you said, in Amazon and some of the other hyper clouds those clouds, those storage services, no matter where a customer is, so that that core value, of course we know, is this the software underneath it. And that's what Portworx is. So you know not only Pure's, but other hardware, other clouds and the likes. So a really interesting space You know Vaughn, you and I've been covering this, since the early days of VMware. Hey this software is kind of a big deal and you know (chuckles) cloud in many ways is an extension of what we're doing. I know we used to joke how many years was it that VMworld was storage world? You know. >> Ooh yeah. >> There was talk about like big architectural changes, you know vVols When that finally came out, it was years of hard work by many of the big companies, including your previous and current you know employer. What's the latest? My understanding is that there are some updates there when it comes to the underlying vVols. What are the storage people need to know? >> Yeah. So great question and VMware is always been infrastructure world really Right? Like it is a showcase for storage. But it's also been a showcase for the compute vendors and every Intel partner. From a storage perspective, a lot is going on this year that should really excite both VMware admins and those who are storage centric in their day-to-day jobs. Let's start with the recent news. vVols has been promoted within VCF to being principal storage. For those of you who maybe are unfamiliar with this term 'principal storage' VMware Cloud Foundation supports any form of storage that's supported by vSphere. But SDDC manager tool that I was sharing with you earlier that really excites large scale organizations around it's end-to-end simplicity and management. It had a smaller, less robust support list when it comes to provisioning external storage. And so it had two tiers. Principal and secondary. Principal meant SDDC manager could provision and deprovision sub-tenants. So the recent news brings vVols both on Fiber Channel and iSCSI up to that principal tier. Pure Storage is a VMware design partner around vVols. We are one of the most adopted vVols storage platforms, and we are really leaning in on VCF. So we are very happy to see that come to fruition for our customers. Part of why VMware partners with Pure Storage around VCF, is they want VCF enabled on any Fabric. And you know some vendors only offer ethernet only forms of connectivity. But with Pure Storage, we don't care what your Fabric is right. We just want to provide the data services be it ethernet, fiber channel or next generation NVMe over Fabric. That last point segments into another recent announcement from from VMware. Which is the support for NVMe over Fabric within vSphere 7. This is key because NVMe over Fabric allows the IO path to move away from SCSI based form of communication one to a memory based form of communication. And this unleashes a new level of performance, a way to better support those business and mission critical applications. Or a way to drive greater density into a smaller form factor and footprint within your data center. Obviously Fabric upgrades tend to not happen in conjunction with hypervisor upgrades, but the ability to provide customers a roadmap and a means to be able to continually evolve their infrastructure non disruptively, is our key there. It would be remiss of me to not point out one kind of orthogonal element, which is the new vMotion capabilities that are in vSphere 7. Customers have been tried for a number of years, probably from vSphere 4 through six to virtualize more performance centric and resource intense applications. And they've had some challenges around scale, particularly with the non-disruptive. The ability to non disruptively move a workload. VMware rewrote vMotion for vSphere 7 so it can tackle these larger more performance centric workloads. And when you combine that along with the addition of like NVMe over Fabric support, I think you're truly at a time where you can say, almost every workload can run on a VMware platform, right? From your traditional two two consolidation where you started to looking at performance centric AI, in machine learning workloads. >> Yeah. A lot of pieces you just walked through Vaughn, I'm glad especially the NVMe over Fabric piece. Just want to drill down one level there. As you said, there's a lot of pieces to make sure that this is fully worked. The standards are done, the software is there, the hardware, the various interconnects there and then okay, when's does the customer actually ready to upgrade that? How much of that is just you know okay hitting the update button. How much of that is do I need to do a refresh? And we understand that the testing and purchasing cycles there. So how many customers are you talking to that are like, "Okay I've got all the pieces, "we're ready to roll, "we're implementing in 2020." And you know, what's that roadmap look like for kind of the typical enterprise, which I know is a bit of an oxymoron? (laughs) >> So we've got a handful. I think that's a fair way to give you a size without giving you an exact number. We had a handful of customers who have NVMe over Fabric deployments today. The deployments tend to be application or workload centric versus ubiquitous across the data center. Which I think does bear an opportunity for VMware adoption to be a little bit earlier than across the entire data center. Because most VMware architectures today are based on top of rack switching. Whether that switching is fiber channel or ethernet base, I think the ability to then upgrade that switch. Either you've got modern hardware and it just needs a firmware update, or you've got to replace that hardware and implement NVMe over Fabric. I think that's very attractive. Particularly that you can do so in a non disruptive manner with a flash array or with flash deck. We expect to see the adoption really start to take take hold in 2021. But you probably won't see large market gains until 2022 or 23. >> Well that's super helpful Vaughn especially Pure Storage you've got customers that have some of the most demanding performance environments out there. So they are some of the early adopters that you would expect go into adopting this new technology. All right. I guess last piece, listening to the keynote looking at all the announcements that they have you know, VMware obviously has a big push into the cloud native space they've made a whole lot of acquisitions. We touched on a little bit before but what's your take as to what you are hearing from your customers, where they are with adoption into really modernizing and accelerating their businesses today? >> I think for the majority of our customers and again I would consider more of a commercial or mid market centric up through enterprise. They've particularity enterprise, they've adapted cloud native technologies particularity in developing their own internal or customer facing applications. So I don't think the technology is new. I think where it's newer is this re platforming of enterprise applications and I think that what's driving the timeline for VMware. We have a number of Pivotal deployments that run up here. Very large scale Pivotal deployments that run on Pure. And hopefully as you audience knows Pivotal is what VMware Tanzu has been rebranded as. So we've had success there. We've have had success in the test and development and in the web facing application space. But now this is a broader initiative from VMware supporting enterprise apps along with you know the cloud native disaggregated applications that have been built over the last say five to 10 years. But to provide it though a single management plane. So I'm bullish, I'm really bullish I think they are in a unique position compared to the rest of our technology partners you know they own the enterprise virtualization real estate and as so their ability to successfully add cloud native application to that, I think it's a powerful mix . For us the opportunity is great. I want to thank you for focusing on the fact that we've been able to deliver performance. But performances found on any flash product. And it's not to demote our performance by any means, but when you look at our customers and what they purchase us in terms of the repeat purchases, it's around simplicity, it's around the native integration with VMware and the extending of that value prop through our capabilities whether it's through the end-to-end infrastructure management, through data protection extending in the hybrid cloud. That's where Pure Storage customers fall in love with Pure Storage. And so it's a combination of performance, simplicity and ultimately, you know, economics. As we know economics drive most technical decisions not the actual technology itself. >> Well, Vaughn Stewart thank you so much for the update, congratulation on all the new things that are being brought out in the partnership >> Thank you Stu appreciate being on theCUBE, big shout out to VMware congratulations on VMworld 2020, look forward to seeing everybody soon >> All right, stay tuned for more coverage VMworld 2020 I'm Stu Miniman and that you for watching theCUBE. (bright upbeat music)

>> Announcer: From around the globe, it's theCUBE. With digital coverage of VMworld 2020, brought to you by VMware and its ecosystem partners. >> Welcome back, I'm Stu Miniman. This is theCUBE's coverage of VMworld 2020 of course, happening virtually. And there are certain people that we talk to every year at theCUBE, and this guest, I believe, has been on theCUBE at VMworld more than any others. It's actually not Pat Gelsinger, Eric Herzog. He is the chief marketing officer and vice president of global storage channels at IBM. Eric, Mr. Zoginstor, welcome back to theCUBE, nice to see you. >> Thank you very much, Stu. IBM always enjoys hanging with you, John, and Dave. And again, glad to be here, although not in person this time at VMworld 2020 virtual. Thanks again for having IBM. >> Alright, so, you know, some things are the same, others, very different. Of course, Eric, IBM, a long, long partner of VMware's. Why don't you set up for us a little bit, you know, 2020, the major engagements, what's new with IBM and VMware? >> So, a couple of things, first of all, we have made our Spectrum Virtualize software, software defined block storage work in virtual machines, both in AWS and IBM Cloud. So we started with IBM Cloud and then earlier this year with AWS. So now we have two different cloud platforms where our Spectrum Virtualize software sits in a VM at the cloud provider. The other thing we've done, of course, is V7 support. In fact, I've done several VMUGs. And in fact, my session at VMworld is going to talk about both our support for V7 but also what we're doing with containers, CSI, Kubernetes overall, and how we can support that in a virtual VMware environment, and also we're doing with traditional ESX and VMware configurations as well. And of course, out to the cloud, as I just talked about. >> Yeah, that discussion of hybrid cloud, Eric, is one that we've been hearing from IBM for a long time. And VMware has had that message, but their cloud solutions have really matured. They've got a whole group going deep on cloud native. The Amazon solutions have been something that they've been partnering, making sure that, you know, data protection, it can span between, you know, the traditional data center environment where VMware is so dominant, and the public clouds. You're giving a session on some of those hybrid cloud solutions, so share with us a little bit, you know, where do the visions completely agree? What's some of the differences between what IBM is doing and maybe what people are hearing from VMware? >> Well, first of all, our solutions don't always require VMware to be installed. So for example, if you're doing it in a container environment, for example, with Red Hat OpenShift, that works slightly different. Not that you can't run Red Hat products inside of a virtual machine, which you can, but in this case, I'm talking Red Hat native. We also of course do VMware native and support what VMware has announced with their Kubernetes based solutions that they've been talking about since VMworld last year, obviously when Pat made some big announcements onstage about what they were doing in the container space. So we've been following that along as well. So from that perspective, we have agreement on a virtual machine perspective and of course, what VMware is doing with the container space. But then also a slightly different one when we're doing Red Hat OpenShift as a native configuration, without having a virtual machine involved in that configuration. So those are both the commonalities and the differences that we're doing with VMware in a hybrid cloud configuration. >> Yeah. Eric, you and I both have some of those scars from making sure that storage works in a virtual environment. It took us about a decade to get things to really work at the VM level. Containers, it's been about five years, it feels like we've made faster progress to make sure that we can have stateful environments, we can tie up with storage, but give us a little bit of a look back as to what we've learned and how we've made sure that containerized, Kubernetes environments, you know, work well with storage for customers today. >> Well, I think there's a couple of things. First of all, I think all the storage vendors learn from VMware. And then the expansion of virtual environments beyond VMware to other virtual environments as well. So I think all the storage vendors, including IBM learned through that process, okay, when the next thing comes, which of course in this case happens to be containers, both in a VMware environment, but in an open environment with the Kubernetes management framework, that you need to be able to support it. So for example, we have done several different things. We support persistent volumes in file block and object store. And we started with that almost three years ago on the block side, then we added the file side and now the object storage side. We also can back up data that's in those containers, which is an important feature, right? I am sitting there and I've got data now and persistent volume, but I got to back it up as well. So we've announced support for container based backup either with Red Hat OpenShift or in a generic Kubernetes environment, because we're realistic at IBM. We know that you have to exist in the software infrastructure milieu, and that includes VMware and competitors of VMware. It includes Red Hat OpenShift, but also competitors to Red Hat. And we've made sure that we support whatever the end user needs. So if they're going with Red Hat, great. If they're going with a generic container environment, great. If they're going to use VMware's container solutions, great. And on the virtualization engines, the same thing. We started with VMware, but also have added other virtualization engines. So you think the storage community as a whole and IBM in particular has learned, we need to be ready day one. And like I said, three years ago, we already had persistent volume support for block store. It's still the dominant storage and we had that three years ago. So for us, that would be really, I guess, two years from what you've talked about when containers started to take off. And within two years we had something going that was working at the end user level. Our sales team could sell our business partners. As you know, many of the business partners are really rallying around containers, whether it be Red Hat or in what I'll call a more generic environment as well. They're seeing the forest through the trees. I do think when you look at it from an end user perspective, though, you're going to see all three. So, particularly in the Global Fortune 1000, you're going to see Red Hat environments, generic Kubernetes environments, VMware environments, just like you often see in some instances, heterogeneous virtualization environments, and you're still going to see bare metal. So I think it's going to vary by application workload and use case. And I think all, I'd say midsize enterprise up, let's say, $5 billion company and up, probably will have at least two, if not all three of those environments, container, virtual machine, and bare metal. So we need to make sure that at IBM we support all those environments to keep those customers happy. >> Yeah, well, Eric, I think anybody, everybody in the industry knows, IBM can span those environments, you know, support through generations. And very much knows that everything in IT tends to be additive. You mentioned customers, Eric, you talk to a lot of customers. So bring us inside, give us a couple examples if you would, how are they dealing with this transition? For years we've been talking about, you know, enabling developers, having them be tied more tightly with what the enterprise is doing. So what are you seeing from some of your customers today? >> Well, I think the key thing is they'd like to use data reuse. So, in this case, think of a backup, a snap or replica dataset, which is real world data, and being able to use that and reuse that. And now the storage guys want to make sure they know who's, if you will, checked it out. We do that with our Spectrum Copy Data Management. You also have, of course, integration with the Ansible framework, which IBM supports, in fact, we'll be announcing some additional support for more features in Ansible coming at the end of October. We'll be doing a large launch, very heavily on containers. Containers and primary storage, containers in hybrid cloud environments, containers in big data and AI environments, and containers in the modern data protection and cyber resiliency space as well. So we'll be talking about some additional support in this case about Ansible as well. So you want to make sure, one of the key things, I think, if you're a storage guy, if I'm the VP of infrastructure, or I'm the CIO, even if I'm not a storage person, in fact, if you think about it, I'm almost 70 now. I have never, ever, ever, ever met a CIO who used to be a storage guy, ever. Whether I, I've been with big companies, I was at EMC, I was at Seagate Maxtor, I've been at IBM actually twice. I've also done seven startups, as you guys know at theCUBE. I have never, ever met a CIO who used to be a storage person. Ever, in all those years. So, what appeals to them is, how do I let the dev guys and the test guys use that storage? At the same time, they're smart enough to know that the software guys and the test guys could actually screw up the storage, lose the data, or if they don't lose the data, cost them hundreds of thousands to millions of dollars because they did something wrong and they have to reconfigure all the storage solutions. So you want to make sure that the CIO is comfortable, that the dev and the test teams can use that storage properly. It's a part of what Ansible's about. You want to make sure that you've got tight integration. So for example, we announced a container native version of our Spectrum Discover software, which gives you comprehensive metadata, cataloging and indexing. Not only for IBM's scale-out file, Spectrum Scale, not only for IBM object storage, IBM cloud object storage, but also for Amazon S3 and also for NetApp filers and also for EMC Isilon. And it's a container native. So you want to make sure in that case, we have an API. So the AI software guys, or the big data software guys could interface with that API to Spectrum Discover, let them do all the work. And we're talking about a piece of software that can traverse billions of objects in two seconds, billions of them. And is ideal to use in solutions that are hundreds of petabytes, up into multiple exabytes. So it's a great way that by having that API where the CIO is confident that the software guys can use the API, not mess up the storage because you know, the storage guys and the data scientists can configure Spectrum Discover and then save it as templates and run an AI workload every Monday, and then run a big data workload every Tuesday, and then Wednesday run a different AI workload and Thursday run a different big data. And so once they've set that up, everything is automated. And CIOs love automation, and they really are sensitive. Although they're all software guys, they are sensitive to software guys messing up the storage 'cause it could cost them money, right? So that's their concern. We make it easy. >> Absolutely, Eric, you know, it'd be lovely to say that storage is just invisible, I don't need to think about it, but when something goes wrong, you need those experts to be able to dig in. You spent some time talking about automation, so critically important. How about the management layer? You know, you think back, for years it was, vCenter would be the place that everything can plug in. You could have more generalists using it. The HCI waves were people kind of getting away from being storage specialists. Today VMware has, of course vCenter's their main estate, but they have Tanzu. On the IBM and Red Hat side, you know, this year you announced the Advanced Cluster Management. What's that management landscape look like? How does the storage get away from managing some of the bits and bytes and, you know, just embrace more of that automation that you talked about? >> So in the case of IBM, we make sure we can support both. We need to appeal to the storage nerd, the storage geek if you will. The same time to a more generalist environment, whether it be an infrastructure manager, whether it be some of the software guys. So for example, we support, obviously vCenter. We're going to be supporting all of the elements that are going to happen in a container environment that VMware is doing. We have hot integration and big time integration with Red Hat's management framework, both with Ansible, but also in the container space as well. We're announcing some things that are coming again at the end of October in the container space about how we interface with the Red Hat management schema. And so you don't always have to have the storage expert manage the storage. You can have the Red Hat administrator, or in some cases, the DevOps guys do it. So we're making sure that we can cover both sides of the fence. Some companies, this just my personal belief, that as containers become commonplace while the software guys are going to want to still control it, there eventually will be a Red Hat/container admin, just like all the big companies today have VMware admins. They all do. Or virtualization admins that cover VMware and VMware's competitors such as Hyper-V. They have specialized admins to run that. And you would argue, VMware is very easy to use, why aren't the software guys playing with it? 'Cause guess what? Those VMs are sitting on servers containing both apps and data. And if the software guy comes in to do something, messes it up, so what have of the big entities done? They've created basically a virtualization admin layer. I think that over time, either the virtualization admins become virtualization/container admins, or if it's a big enough for both estates, there'll be container admins at the Global Fortune 500, and they'll also be virtualization admins. And then the software guys, the devOps guys will interface with that. There will always be a level of management framework. Which is why we integrate, for example, with vCenter, what we're doing with Red Hat, what we do with generic Kubernetes, to make sure that we can integrate there. So we'll make sure that we cover all areas because a number of our customers are very large, but some of our customers are very small. In fact, we have a company that's in the software development space for autonomous driving. They have over a hundred petabytes of IBM Spectrum Scale in a container environment. So that's a small company that's gone all containers, at the same time, we have a bunch of course, Global Fortune 1000s where IBM plays exceedingly well that have our products. And they've got some stuff sitting in VMware, some such sitting in generic Kubernetes, some stuff sitting in Red Hat OpenShift and some stuff still in bare metal. And in some cases they don't want their software people to touch it, in other cases, these big accounts, they want their software people empowered. So we're going to make sure we could support both and both management frameworks. Traditional storage management framework with each one of our products and also management frameworks for virtualization, which we've already been doing. And now management frame first with container. We'll make sure we can cover all three of those bases 'cause that's what the big entities will want. And then in the smaller names, you'll have to see who wins out. I mean, they may still use three in a small company, you really don't know, so you want to make sure you've got everything covered. And it's very easy for us to do this integration because of things we've already historically done, particularly with the virtualization environment. So yes, the interstices of the integration are different, but we know here's kind of the process to do the interconnectivity between a storage management framework and a generic management framework, in, originally of course, vCenter, and now doing it for the container world as well. So at least we've learned best practices and now we're just tweaking those best practices in the difference between a container world and a virtualization world. >> Eric, VMworld is one of the biggest times of the year, where we all get together. I know how busy you are going to the show, meeting with customers, meeting with partners, you know, walking the hallways. You're one of the people that traveled more than I did pre-COVID. You know, you're always at the partner shows and meeting with people. Give us a little insight as to how you're making sure that, partners and customers, those conversations are still happening. We understand everything over video can be a little bit challenging, but, what are you seeing here in 2020? How's everybody doing? >> Well, so, a couple of things. First of all, I already did two partner meetings today. (laughs) And I have an end user meeting, two end user meetings tomorrow. So what we've done at IBM is make sure we do a couple things. One, short and to the point, okay? We have automated tools to actually show, drawing, just like the infamous walk up to the whiteboard in a face to face meeting, we've got that. We've also now tried to make sure everybody is being overly inundated with WebEx. And by the way, there's already a lot of WebEx anyway. I can think of meeting I had with a telco, one of the Fortune 300, and this was actually right before Thanksgiving. I was in their office in San Jose, but they had guys in Texas and guys in the East Coast all on. So we're still over WebEx, but it also was a two and a half hour meeting, actually almost a three hour meeting. And both myself and our Flash CTO went up to the whiteboard, which you could then see over WebEx 'cause they had a camera showing up onto the whiteboard. So now you have to take that and use integrated tools. One, but since people are now, I would argue, over WebEx. There is a different feel to doing the WebEx than when you're doing it face to face. We have to fly somewhere, or they have to fly somewhere. We have to even drive somewhere, so in between meetings, if you're going to do four customer calls, Stu, as you know, I travel all over the world. So I was in Sweden actually right before COVID. And in one day, the day after we had a launch, we launched our new Flash System products in February on the 11th, on February 12th, I was still in Stockholm and I had two partner meetings and two end user meetings. But the sales guy was driving me around. So in between the meetings, you'd be in the car for 20 minutes or half an hour. So it connects different when you can do WebEx after WebEx after WebEx with basically no break. So you have to be sensitive to that when you're talking to your partners, sensitive of that when you're talking to the customers sensitive when you're talking to the analysts, such as you guys, sensitive when you're talking to the press and all your various constituents. So we've been doing that at IBM, really, since the COVID thing got started, is coming up with some best practices so we don't overtax the end users and overtax our channel partners. >> Yeah, Eric, the joke I had on that is we're all following the Bill Belichick model now, no days off, just meeting, meeting, meeting every day, you can stack them up, right? You used to enjoy those downtimes in between where you could catch up on a call, do some things. I had to carve out some time to make sure that stack of books that normally I would read in the airports or on flights, everything, you know. I do enjoy reading a book every now and again, so. Final thing, I guess, Eric. Here at VMworld 2020, you know, give us final takeaways that you want your customers to have when it comes to IBM and VMware. >> So a couple of things, A, we were tightly integrated and have been tightly integrated for what they've been doing in their traditional virtualization environment. As they move to containers we'll be tightly integrated with them as well, as well as other container platforms, not just from IBM with Red Hat, but again, generic Kubernetes environments with open source container configurations that don't use IBM Red Hat and don't use VMware. So we want to make sure that we span that. In traditional VMware environments, like with Version 7 that came out, we make sure we support it. In fact, VMware just announced support for NVMe over Fibre Channel. Well, we've been shipping NVMe over Fibre Channel for just under two years now. It'll be almost two years, well, it will be two years in October. So we're sitting here in September, it's almost been two years since we've been shipping that. But they haven't supported it, so now of course we actually, as part of our launch, I pre say something, as part of our launch, the last week of October at IBM's TechU it'll be on October 27th, you can join for free. You don't need to attend TechU, we'll have a free registration page. So just follow Zoginstor or look at my LinkedIns 'cause I'll be posting shortly when we have the link, but we'll be talking about things that we're doing around V7, with support for VMware's announcement of NVMe over Fibre Channel, even though we've had it for two years coming next month. But they're announcing support, so we're doing that as well. So all of those sort of checkbox items, we'll continue to do as they push forward into the container world. IBM will be there right with them as well because we know it's a very large world and we need to support everybody. We support VMware. We supported their competitors in the virtualization space 'cause some customers have, in fact, some customers have both. They've got VMware and maybe one other of the virtualization elements. Usually VMware is the dominant of course, but if they've got even a little bit of it, we need to make sure our storage works with it. We're going to do the same thing in the container world. So we will continue to push forward with VMware. It's a tight relationship, not just with IBM Storage, but with the server group, clearly with the cloud team. So we need to make sure that IBM as a company stays very close to VMware, as well as, obviously, what we're doing with Red Hat. And IBM Storage makes sure we will do both. I like to say that IBM Storage is a Switzerland of the storage industry. We work with everyone. We work with all these infrastructure players from the software world. And even with our competitors, our Spectrum Virtualized software that comes on our Flash Systems Array supports over 550 different storage arrays that are not IBM's. Delivering enterprise-class data services, such as snapshot, replication data, at rest encryption, migration, all those features, but you can buy the software and use it with our competitors' storage array. So at IBM we've made a practice of making sure that we're very inclusive with our software business across the whole company and in storage in particular with things like Spectrum Virtualize, with what we've done with our backup products, of course we backup everybody's stuff, not just ours. We're making sure we do the same thing in the virtualization environment. Particularly with VMware and where they're going into the container world and what we're doing with our own, obviously sister division, Red Hat, but even in a generic Kubernetes environment. Everyone's not going to buy Red Hat or VMware. There are people going to do Kubernetes industry standard, they're going to use that, if you will, open source container environment with Kubernetes on top and not use VMware and not use Red Hat. We're going to make sure if they do it, what I'll call generically, if they use Red Hat, if they use VMware or some combo, we will support all of it and that's very important for us at VMworld to make sure everyone is aware that while we may own Red Hat, we have a very strong, powerful connection to VMware and going to continue to do that in the future as well. >> Eric Herzog, thanks so much for joining us. Always a pleasure catching up with you. >> Thank you very much. We love being with theCUBE, you guys do great work at every show and one of these days I'll see you again and we'll have a beer. In person. >> Absolutely. So, definitely, Dave Vellante and John Furrier send their best, I'm Stu Miniman, and thank you as always for watching theCUBE. (relaxed electronic music)

>> Announcer: From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a Cube conversation. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We are in our Palo Alto studios, COVID is still going on, so all of the interviews continue to be remote, but we're excited to have a Cube alumni, he hasn't been on for a long time, and this guy has been in the weeds of the storage industry for a very very long time and we're happy to have him on and get an update because there continues to be a lot of exciting developments. He's Phil Bullinger, he is the SVP and general manager, data center business unit from Western Digital joining us, I think for Colorado, so Phil, great to see you, how's the weather in Colorado today? >> Hi Jeff, it's great to be here. Well, it's a hot, dry summer here, I'm sure like a lot of places. But yeah, enjoying the summer through these unusual times. >> It is unusual times, but fortunately there's great things like the internet and heavy duty compute and store out there so we can get together this way. So let's jump into it. You've been in the he business a long time, you've been at Western Digital, you were at EMC, you worked on Isilon, and you were at storage companies before that. And you've seen kind of this never-ending up and to the right slope that we see kind of ad nauseum in terms of the amount of storage demands. It's not going anywhere but up, and please increase complexity in terms of unstructure data, sources of data, speed of data, you know the kind of classic big V's of big data. So I wonder, before we jump into specifics, if you can kind of share your perspective 'cause you've been kind of sitting in the Catford seat, and Western Digital's a really unique company; you not only have solutions, but you also have media that feeds other people solutions. So you guys are really seeing and ultimately all this compute's got to put this data somewhere, and a whole lot of it's sitting on Western Digital. >> Yeah, it's a great intro there. Yeah, it's been interesting, through my career, I've seen a lot of advances in storage technology. Speeds and feeds like we often say, but the advancement through mechanical innovation, electrical innovation, chemistry, physics, just the relentless growth of data has been driven in many ways by the relentless acceleration and innovation of our ability to store that data, and that's been a very virtuous cycle through what, for me, has been 30 years in enterprise storage. There are some really interesting changes going on though I think. If you think about it, in a relatively short amount of time, data has gone from this artifact of our digital lives to the very engine that's driving the global economy. Our jobs, our relationships, our health, our security, they all kind of depend on data now, and for most companies, kind of irrespective of size, how you use data, how you store it, how you monetize it, how you use it to make better decisions to improve products and services, it becomes not just a matter of whether your company's going to thrive or not, but in many industries, it's almost an existential question; is your company going to be around in the future, and it depends on how well you're using data. So this drive to capitalize on the value of data is pretty significant. >> It's a really interesting topic, we've had a number of conversations around trying to get a book value of data, if you will, and I think there's a lot of conversations, whether it's accounting kind of way, or finance, or kind of good will of how do you value this data? But I think we see it intrinsically in a lot of the big companies that are really data based, like the Facebooks and the Amazons and the Netflixes and the Googles, and those types of companies where it's really easy to see, and if you see the valuation that they have, compared to their book value of assets, it's really baked into there. So it's fundamental to going forward, and then we have this thing called COVID hit, which I'm sure you've seen all the memes on social media. What drove your digital transformation, the CEO, the CMO, the board, or COVID-19? And it became this light switch moment where your opportunities to think about it are no more; you've got to jump in with both feet, and it's really interesting to your point that it's the ability to store this and think about it now differently as an asset driving business value versus a cost that IT has to accommodate to put this stuff somewhere, so it's a really different kind of a mind shift and really changes the investment equation for companies like Western Digital about how people should invest in higher performance and higher capacity and more unified and kind of democratizing the accessibility that data, to a much greater set of people with tools that can now start making much more business line and in-line decisions than just the data scientist kind of on Mahogany Row. >> Yeah, as you mentioned, Jeff, here at Western Digital, we have such a unique kind of perch in the industry to see all the dynamics in the OEM space and the hyperscale space and the channel, really across all the global economies about this growth of data. I have worked at several companies and have been familiar with what I would have called big data projects and fleets in the past. But at Western Digital, you have to move the decimal point quite a few digits to the right to get the perspective that we have on just the volume of data that the world has just relentless insatiably consuming. Just a couple examples, for our drive projects we're working on now, our capacity enterprise drive projects, you know, we used to do business case analysis and look at their lifecycle capacities and we measured them in exabytes, and not anymore, now we're talking about zettabyte, we're actually measuring capacity enterprise drive families in terms of how many zettabyte they're going to ship in their lifecycle. If we look at just the consumption of this data, the last 12 months of industry TAM for capacity enterprise compared to the 12 months prior to that, that annual growth rate was north of 60%. And so it's rare to see industries that are growing at that pace. And so the world is just consuming immense amounts of data, and as you mentioned, the COVID dynamics have been both an accelerant in some areas, as well as headwinds in others, but it's certainly accelerated digital transformation. I think a lot of companies we're talking about, digital transformation and hybrid models and COVID has really accelerated that, and it's certainly driving, continues to drive just this relentless need to store and access and take advantage of data. >> Yeah, well Phil, in advance of this interview, I pulled up the old chart with all the different bytes, kilobytes, megabytes, gigabytes, terabytes, petabytes, exabytes, and zettabytes, and just per the Wikipedia page, what is a zettabyte? It's as much information as there are grains of sand in all the world's beaches. For one zettabyte. You're talking about thinking in terms of those units, I mean, that is just mind boggling to think that that is the scale in which we're operating. >> It's really hard to get your head wrapped around a zettabyte of storage, and I think a lot of the industry thinks when we say zettabyte scale era, that it's just a buzz word, but I'm here to say it's a real thing. We're measuring projects in terms of zettabytes now. >> That's amazing. Well, let's jump into some of the technology. So I've been fortunate enough here at theCUBE to be there at a couple of major announcements along the way. We talked before we turned the cameras on, the helium announcement and having the hard drive sit in the fish bowl to get all types of interesting benefits from this less dense air that is helium versus oxygen. I was down at the Mammer and Hammer announcement, which was pretty interesting; big heavy technology moves there, to again, increase the capacity of the hard drive's base systems. You guys are doing a lot of stuff on RISC-V I know is an Open source project, so you guys have a lot of things happening, but now there's this new thing, this new thing called zonedd storage. So first off, before we get into it, why do we need zoned storage, and really what does it now bring to the table in terms of a capability? >> Yeah, great question, Jeff. So why now, right? Because I mentioned storage, I've been in storage for quite some time. In the last, let's just say in the last decade, we've seen the advent of the hyperscale model and certainly a whole nother explosion level of data and just the veracity with which they hyperscalers can create and consume and process and monetize data. And of course with that, has also come a lot of innovation, frankly, in the compute space around how to process that data and moving from what was just a general purpose CPU model to GPU's and DPU's and so we've seen a lot of innovation on that side, but frankly, in the storage side, we haven't seen much change at all in terms of how operating systems, applications, file systems, how they actually use the storage or communicate with the storage. And sure, we've seen advances in storage capacities; hard drives have gone from two to four, to eight, to 10 to 14, 16, and now our leading 18 and 20 terabyte hard drives. And similarly, on the SSD side, now we're dealing with the capacities of seven, and 15, and 30 terabytes. So things have gotten larger, as you expect. And some interfaces have improved, I think NVME, which we'll talk about, has been a nice advance in the industry; it's really now brought a very modern scalable low latency multi-threaded interface to a NAM flash to take advantage of the inherent performance of transistor based persistent storage. But really when you think about it, it hasn't changed a lot. But what has changed is workloads. One thing that definitely has evolved in the space of the last decade or so is this, the thing that's driving a lot of this explosion of data in the industry is around workloads that I would characterize as sequential in nature, they're serial, you can capture it in written. They also have a very consistent life cycle, so you would write them in a big chunk, you would read them maybe in smaller pieces, but the lifecycle of that data, we can treat more as a chunk of data, but the problem is applications, operating systems, vial systems continue to interface with storage using paradigms that are many decades old. The old 512 byte or even Forte, Sector size constructs were developed in the hard drive industry just as convenient paradigms to structure what is an unstructured sea of magnetic grains into something structured that can be used to store and access data. But the reality is when we talk about SSDs, structure really matters, and so what has changed in the industry is the workloads are driving very very fresh looks at how more intelligence can be applied to that application OS storage device interface to drive much greater efficiency. >> Right, so there's two things going on here that I want to drill down on. On one hand, you talked about kind of the introduction of NAND and flash, and treating it like you did, generically you did a regular hard drive. But you could get away and you could do some things because the interface wasn't taking full advantage of the speed that was capable in the NAND. But NVME has changed that, and now forced kind of getting rid of some of those inefficient processes that you could live with, so it's just kind of classic next level step up and capabilities. One is you get the better media, you just kind of plug it into the old way. Now actually you're starting to put in processes that take full advantage of the speed that that flash has. And I think obviously prices have come down dramatically since the first introduction, where before it was always kind of a clustered off or super high end, super low latency, super high value apps, it just continues to spread and proliferate throughout the data center. So what did NVME force you to think about in terms of maximizing the return on the NAND and flash? >> Yeah, NVME, which we've been involved in the standardization, I think it's been a very successful effort, but we have to remember NVME is about a decade old, or even more when the original work started around defining this interface, but it's been very successful. The NVME standard's body is very productive cross company effort, it's really driven a significant change, and what we see now is the rapid adoption of NVME in all of data center architectures, whether it's very large hyperscale to classic on prem enterprise to even smaller applications, it's just a very efficient interface mechanism for connecting SSDs into a server. So we continue to see evolution at NVME, which is great, and we'll talk about ZNS today as one of those evolutions. We're also very keenly interested in NVME protocol over fabrics, and so one of the things that Western Digital has been talking about a lot lately is incorporating NVME over fabrics as a mechanism for now connecting shared storage into multiple post architectures. We think this is a very attractive way to build shared storage architectures of the future that are scalable, that are composable, that really have a lot more agility with respect to rack level infrastructure and applying that infrastructure to applications. >> Right, now one thing that might strike some people as kind of counterintuitive is within the zoned storage in zoning off parts of the media, to think of the data also kind of in these big chunks, is it feels contrary to kind of atomization that we're seeing in the rest of the data center, right? So smaller units of compute, smaller units of store, so that you can assemble and disassemble them in different quantities as needed. So what was the special attribute that you had to think about and actually come back and provide a benefit in actually kind of re-chunking, if you will, in these zones versus trying to get as atomic as possible? >> Yeah, it's a great question, Jeff, and I think it's maybe not intuitive in terms of why zoned storage actually creates a more efficient storage paradigm when you're storing stuff essentially in larger blocks of data, but this is really where the intersection of structure and workload and sort of the nature of the data all come together. If you turn back the clock maybe four or five years when SMR hard drives host managers SMR hard drives first emerged on the scene. This was really taking advantage of the fact that the right head on a hard disk drive is larger than the read head, or the read head can be much smaller, and so the notion of overlapping or shingling the data on the drive, giving the read head a smaller target to read, but the writer a larger write pad to write the data could actually, what we found was it increases aerial density significantly. And so that was really the emergence of this notion of sequentially written larger blocks of data being actually much more efficiently stored when you think about physically how it's being stored. What's very new now and really gaining a lot of traction is the SSD corollary to SMR on the hard drive, on the SSD side, we had the ZNS specification, which is, very similarly where you'd divide up the name space of an SSD into fixed size zones, and those zones are written sequentially, but now those zones are intimately tied to the underlying physical architecture of the NAND itself; the dyes, the planes, the read pages, the erase pages. So that, in treating data as a block, you're actually eliminating a lot of the complexity and the work that an SSD has to do to emulate a legacy hard drive, and in doing so, you're increasing performance and endurance and the predictable performance of the device. >> I just love the way that you kind of twist the lens on the problem, and on one hand, by rule, just looking at my notes here, the zoned storage device is the ZSD's introduce a number of restrictions and limitations and rules that are outside the full capabilities of what you might do. But in doing so, an aggregate, the efficiency, and the performance of the system in the whole is much much better, even though when you first look at it, you think it's more of a limiter, but it's actually opens up. I wonder if there's any kind of performance stats you can share or any kind of empirical data just to give people kind of a feel for what that comes out as. >> So if you think about the potential of zoned storage in general and again, when I talk about zoned storage, there's two components; there's an HDD component of zoned storage that we refer to as SMR, and there's an SSD version of that that we call ZNS. So we think about SMR, the value proposition there is additional capacity. So effectively in the same drive architecture, with roughly the same bill of material used to build the drive, we can overlap or shingle the data on the drive. And generally for the customer, additional capacity. Today with our 18, 20 terabyte offerings that's on the order of just over 10%, but that delta is going to increase significantly going forward to 20% or more. And when you think about a hyperscale customer that has not hundreds or thousands of racks, but tens of thousands of racks. A 10 or 20% improvement in effective capacity is a tremendous TCO benefit, and the reason we do that is obvious. I mean, the economic paradigm that drives large at-scale data centers is total custom ownership, both acquisition costs and operating costs. And if you can put more storage in a square tile of data center space, you're going to generally use less power, you're going to run it more efficiently, you're actually, from an acquisition cost, you're getting a more efficient purchase of that capacity. And in doing that, our innovation, we benefit from it and our customers benefit from it. So the value proposition for zoned storage in capacity enterprise HDV is very clear, it's additional capacity. The exciting thing is, in the SSD side of things, or ZNS, it actually opens up even more value proposition for the customer. Because SSDs have had to emulate hard drives, there's been a lot of inefficiency and complexity inside an enterprise SSD dealing with things like garbage collection and right amplification reducing the endurance of the device. You have to over-provision, you have to insert as much as 20, 25, even 28% additional man bits inside the device just to allow for that extra space, that working space to deal with delete of data that are smaller than the block erase that the device supports. So you have to do a lot of reading and writing of data and cleaning up. It creates for a very complex environment. ZNS by mapping the zoned size with the physical structure of the SSD essentially eliminates garbage collection, it reduces over-provisioning by as much as 10x. And so if you were over provisioning by 20 or 25% on an enterprise SSD, and a ZNS SSD, that can be one or two percent. The other thing I have to keep in mind is enterprise SSD is typically incorporate D RAM and that D RAM is used to help manage all those dynamics that I just mentioned, but with a much simpler structure where the pointers to the data can be managed without all the D RAM. We can actually reduce the amount of D RAM in an enterprise SSD by as much as eight X. And if you think about the MILA material of an enterprise SSD, D RAM is number two on the list in terms of the most expensive bomb components. So ZNS and SSDs actually have a significant customer total cost of ownership impact. It's an exciting standard, and now that we have the standard ratified through the NVME working group, it can really accelerate the development of the software ecosystem around. >> Right, so let's shift gears and talk a little bit about less about the tech and more about the customers and the implementation of this. So you talked kind of generally, but are there certain types of workloads that you're seeing in the marketplace where this is a better fit or is it just really the big heavy lifts where they just need more and this is better? And then secondly, within these hyperscale companies, as well as just regular enterprises that are also seeing their data demands grow dramatically, are you seeing that this is a solution that they want to bring in for kind of the marginal kind of next data center, extension of their data center, or their next cloud region? Or are they doing lift and shift and ripping stuff out? Or do they enough data growth organically that there's plenty of new stuff that they can put in these new systems? >> Yeah, I love that. The large customers don't rip and shift; they ride their assets for a long lifecycle, 'cause with the relentless growth of data, you're primarily investing to handle what's coming in over the transom. But we're seeing solid adoption. And in SMRS you know we've been working on that for a number of years. We've got significant interest and investment, co-investment, our engineering, and our customer's engineering adapting the application environment's to take advantage of SMR. The great thing is now that we've got the NVME, the ZNS standard gratified now in the NVME working group, we've got a very similar, and all approved now, situation where we've got SMR standards that have been approved for some time, and the SATA and SCSI standards. Now we've got the same thing in the NVME standard, and the great thing is once a company goes through the lift, so to speak, to adapt an application, file system, operating system, ecosystem, to zoned storage, it pretty much works seamlessly between HDD and SSD, and so it's not an incremental investment when you're switching technologies. Obviously the early adopters of these technologies are going to be the large companies who design their own infrastructure, who have mega fleets of racks of infrastructure where these efficiencies really really make a difference in terms of how they can monetize that data, how they compete against the landscape of competitors they have. For companies that are totally reliant on kind of off the shelf standard applications, that adoption curve is going to be longer, of course, because there are some software changes that you need to adapt to enable zoned storage. One of the things Western Digital has done and taken the lead on is creating a landing page for the industry with zoned storage.io. It's a webpage that's actually an area where many companies can contribute Open source tools, code, validation environments, technical documentation. It's not a marketeering website, it's really a website built to land actual Open source content that companies can use and leverage and contribute to to accelerate the engineering work to adapt software stacks to zoned storage devices, and to share those things. >> Let me just follow up on that 'cause, again, you've been around for a while, and get your perspective on the power of Open source. And it used to be the best secrets, the best IP were closely guarded and held inside, and now really we're in an age where it's not necessarily. And the brilliant minds and use cases and people out there, just by definition, it's more groups of engineers, more engineers outside your building than inside your building, and how that's really changed kind of a strategy in terms of development when you can leverage Open source. >> Yeah, Open source clearly has accelerated innovation across the industry in so many ways, and it's the paradigm around which companies have built business models and innovated on top of it, I think it's always important as a company to understand what value ad you're bringing, and what value ad the customers want to pay for. What unmet needs in your customers are you trying to solve for, and what's the best mechanism to do that? And do you want to spend your RND recreating things, or leveraging what's available and innovating on top of it? It's all about ecosystem. I mean, the days where a single company could vertically integrate top to bottom a complete end solution, you know, those are fewer and far between. I think it's about collaboration and building ecosystems and operating within those. >> Yeah, it's such an interesting change, and one more thing, again, to get your perspective, you run the data center group, but there's this little thing happening out there that we see growing, IOT, in the industrial internet of things, and edge computing as we try to move more compute and store and power kind of outside the pristine world of the data center and out towards where this data is being collected and processed when you've got latency issues and all kinds of reasons to start to shift the balance of where the compute is and where the store and relies on the network. So when you look back from the storage perspective in your history in this industry and you start to see basically everything is now going to be connected, generating data, and a lot of it is even Opensource. I talked to somebody the other day doing kind of Opensource computer vision on surveillance video. So the amount of stuff coming off of these machines is growing in crazy ways. At the same time, it can't all be processed at the data center, it can't all be kind of shipped back and then have a decision and then ship that information back out to. So when you sit back and look at Edge from your kind of historical perspective, what goes through your mind, what gets you excited, what are some opportunities that you see that maybe the laymen is not paying close enough attention to? >> Yeah, it's really an exciting time in storage. I get asked that question from time to time, having been in storage for more than 30 years, you know, what was the most interesting time? And there's been a lot of them, but I wouldn't trade today's environment for any other in terms of just the velocity with which data is evolving and how it's being used and where it's being used. A TCO equation may describe what a data center looks like, but data locality will determine where it's located, and we're excited about the Edge opportunity. We see that as a pretty significant, meaningful part of the TAM as we look three to five years. Certainly 5G is driving much of that, I think just any time you speed up the speed of the connected fabric, you're going to increase storage and increase the processing the data. So the Edge opportunity is very interesting to us. We think a lot of it is driven by low latency work loads, so the concept of NVME is very appropriate for that, we think, in general SSDs deployed and Edge data centers defined as anywhere from a meter to a few kilometers from the source of the data. We think that's going to be a very strong paradigm. The workloads you mentioned, especially IOT, just machine-generated data in general, now I believe, has eclipsed human generated data, in terms of just the amount of data stored, and so we think that curve is just going to keep going in terms of machine generated data. Much of that data is so well suited for zoned storage because it's sequential, it's sequentially written, it's captured, and it has a very consistent and homogenous lifecycle associated with it. So we think what's going on with zoned storage in general and ZNS and SMR specifically are well suited for where a lot of the data growth is happening. And certainly we're going to see a lot of that at the Edge. >> Well, Phil, it's always great to talk to somebody who's been in the same industry for 30 years and is excited about today and the future. And as excited as they have been throughout their whole careers. So that really bodes well for you, bodes well for Western Digital, and we'll just keep hoping the smart people that you guys have over there, keep working on the software and the physics, and the mechanical engineering and keep moving this stuff along. It's really just amazing and just relentless. >> Yeah, it is relentless. What's exciting to me in particular, Jeff, is we've driven storage advancements largely through, as I said, a number of engineering disciplines, and those are still going to be important going forward, the chemistry, the physics, the electrical, the hardware capabilities. But I think as widely recognized in the industry, it's a diminishing curve. I mean, the amount of energy, the amount of engineering effort, investment, that cost and complexity of these products to get to that next capacity step is getting more difficult, not less. And so things like zoned storage, where we now bring intelligent data placement to this paradigm, is what I think makes this current juncture that we're at very exciting. >> Right, right, well, it's applied AI, right? Ultimately you're going to have more and more compute power driving the storage process and how that stuff is managed. As more cycles become available and they're cheaper, and ultimately compute gets cheaper and cheaper, as you said, you guys just keep finding new ways to move the curve in. And we didn't even get into the totally new material science, which is also coming down the pike at some point in time. >> Yeah, very exciting times. >> It's been great to catch up with you, I really enjoy the Western Digital story; I've been fortunate to sit in on a couple chapters, so again, congrats to you and we'll continue to watch and look forward to our next update. Hopefully it won't be another four years. >> Okay, thanks Jeff, I really appreciate the time. >> All right, thanks a lot. All right, he's Phil, I'm Jeff, you're watching theCUBE. Thanks for watching, we'll see you next time.

>> Narrator: From the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is a CUBE conversation. >> Hi, and welcome to this CUBE conversation, I'm Stu Min and I'm coming to you from our Boston area studio, we've been digging in with the Pensando team, understand how they're fitting into the cloud, multi-cloud, edge discussion, really thrilled to welcome to the program, first time guest, Silvano Gai, he's a fellow with Pensando. Silvano, really nice to see you again, thanks so much for joining us on theCUBE. >> Stuart, it's so nice to see you, we used to work together many years ago and that was really good and is really nice to come to you from Oregon, from Bend, Oregon. A beautiful town in the high desert of Oregon. >> I do love the Pacific North West, I miss the planes and the hotels, I should say, I don't miss the planes and the hotels, but going to see some of the beautiful places is something I do miss and getting to see people in the industry I do like. As you mentioned, you and I crossed paths back through some of the spin-ins, back when I was working for a very large storage company, you were working for SISCO, you were known for writing the book, you were a professor in Italy, many of the people that worked on some of those technologies were your students. But Silvano, my understanding is you retired so, maybe share for our audience, what brought you out of that retirement and into working once again with some of your former colleagues and on the Pensando opportunity. >> I did retire for a while, I retired in 2011 from Cisco if I remember correctly. But at the end of 2016, beginning of 2017, some old friend that you may remember and know called me to discuss some interesting idea, which was basically the seed idea that is behind the Pensando product and their idea were interesting, what we built, of course, is not exactly the original idea because you know product evolve over time, but I think we have something interesting that is adequate and probably superb for the new way to design the data center network, both for enterprise and cloud. >> All right, and Silvano, I mentioned that you've written a number of books, really the authoritative look on when some new products had been released before. So, you've got a new book, "Building a Future-Proof Cloud Infrastructure," and look at you, you've got the physical copy, I've only gotten the soft version. The title, really interesting. Help us understand how Pensando's platform is meeting that future-proof cloud infrastructure that you discuss. >> Well, network have evolved dramatically in the data center and in the cloud. You know, now the speed of classical server in enterprise is probably 25 gigabits, in the cloud we are talking of 100 gigabit of speed for a server, going to 200 gigabit. Now, the backbone are ridiculously fast. We no longer use Spanning Tree and all the stuff, we no longer use access code aggregation. We switched to closed network, and with closed network, we have huge enormous amount of bandwidth and that is good but it also imply that is not easy to do services in a centralized fashion. If you want to do a service in a centralized fashion, what you end up doing is creating a giant bottleneck. You basically, there is this word that is being used, that is trombone or tromboning. You try to funnel all this traffic through the bottleneck and this is not really going to work. The only place that you can really do services is at the edge, and this is not an invention, I mean, even all the principles of cloud is move everything to the edge and maintain the network as simple as possible. So, we approach services with the same general philosophy. We try to move services to the edge, as close as possible to the server and basically at the border between the sever and the network. And when I mean services I mean three main categories of services. The networking services of course, there is the basic layer, two-layer, three stuff, plus the bonding, you know VAMlog and what is needed to connect a server to a network. But then there is the overlay, overlay like the xLAN or Geneva, very very important, basically to build a cloud infrastructure, and that are basically the network service. We can have others but that, sort of is the core of a network service. Some people want to run BGP layers, some people don't want to run BGP. There may be a VPN or kind of things like that but that is the core of a network service. Then of course, and we go back to the time we worked together, there are storage services. At that time, we were discussing mostly about fiber tunnel, now the BUS world is clearly NVMe, but it's not just the BUS world, it's really a new way of doing storage, and is very very interesting. So, NVMe kind of service are very important and NVMe as a version that is called NVMeOF, over fiber. Which is basically, sort of remote version of NVMe. And then the third, least but not last, most important category probably, is security. And when I say that security is very very important, you know, the fact that security is very important is clear to everybody in our day, and I think security has two main branches in terms of services. There is the classical firewall and micro-segmentation, in which you basically try to enforce the fact that only who is allowed to access something can access something. But you don't, at that point, care too much about the privacy of the data. Then there is the other branch that encryption, in which you are not trying to enforce to decide who can access or not access the resource, but you are basically caring about the privacy of the data, encrypting the data so that if it is hijacked, snooped or whatever, it cannot be decoded. >> Eccellent, so Silvano, absolutely the edge is a huge opportunity. When someone looks at the overall solution and say you're putting something in the edge, you know, they could just say, "This really looks like a NIC." You talked about some of the previous engagement we'd worked on, host bus adapters, smart NICs and the like. There were some things we could build in but there were limits that we had, so, what differentiates the Pensando solution from what we would traditionally think of as an adapter card in the past? >> Well, the Pensando solution has two main, multiple pieces but in term of hardware, has two main pieces, there is an ASIC that we call copper internally. That ASIC is not strictly related to be used only in an adapter form, you can deploy it also in other form factors in another part of the network in other embodiment, et cetera. And then there is a card, the card has a PCI-E interface and sit in a PCI-E slot. So yes, in that sense, somebody can can call it a NIC and since it's a pretty good NIC, somebody can call it a smart NIC. We don't really like that two terms, we prefer to call it DSC, domain specific card, but the real term that I like to use is domain specific hardware, and I like to use domain specific hardware because it's the same term that Hennessy and Patterson use in a beautiful piece of literature that is the Turing Award lecture. It's on the internet, it's public, I really ask everybody to go and try to find it and listen to that beautiful piece of literature, modern literature on computer architecture. The Turing Award lecture of Hennessy and Patterson. And they have introduced the concept of domain specific hardware, and they explain also the justification for why now is important to look at domain specific hardware. And the justification is basically in a nutshell and we can go more deep if you're interested, but in a nutshell is that the specing, that is the single tried performer's measurement of a CPU, is not growing fast at all, is only growing nowadays like a few point percent a year, maybe 4% per year. And with this slow grow, over specing performance of a core, you know the core need to be really used for user application, for customer application, and all what is known as Sentian can be moved to some domain specific hardware that can do that in a much better fashion, and by no mean I imply that the DSC is the best example of domain specific hardware. The best example of domain specific hardware is in front of all of us, and are GPUs. And not GPUs for graphic processing which are also important, but GPU used basically for artificial intelligence, machine learning inference. You know, that is a piece of hardware that has shown that something can be done with performance that the purpose processor can do. >> Yeah, it's interesting right. If you term back the clock 10 or 15 years ago, I used to be in arguments, and you say, "Do you build an offload, "or do you let it happen is software." And I was always like, "Oh, well Moore's law with mean that, "you know, the software solution will always win, "because if you bake it in hardware, it's too slow." It's a very different world today, you talk about how fast things speed up. From your customer standpoint though, often some of those architectural things are something that I've looked for my suppliers to take care of that. Speak to the use case, what does this all mean from a customer stand point, what are some of those early use cases that you're looking at? >> Well, as always, you get a bit surprised by the use cases, in the sense that you start to design a product thinking that some of the most cool thing will be the dominant use cases, and then you discover that something that you have never really fought have the most interesting use case. One that we have fought about since day one, but it's really becoming super interesting is telemetry. Basically, measuring everything in the network, and understanding what is happening in the network. I was speaking with a friend the other day, and the friend was asking me, "Oh, but we have SNMP for many many years, "which is the difference between SNMP and telemetry?" And the difference is to me, the real difference is in SNMP or in many of these management protocol, you involve a management plan, you involve a control plan, and then you go to read something that is in the data plan. But the process is so inefficient that you cannot really get a huge volume of data, and you cannot get it practically enough, with enough performance. Doing telemetry means thinking a data path, building a data path that is capable of not only measuring everything realtime, but also sending out that measurement without involving anything else, without involving the control path and the management path so that the measurement becomes really very efficient and the data that you stream out becomes really usable data, actionable data in realtime. So telemetry is clearly the first one, is important. One that you honestly, we had built but we weren't thinking this was going to have so much success is what we call Bidirectional ERSPAN. And basically, is just the capability of copying data. And sending data that the card see to a station. And that is very very useful for replacing what are called TAP network, Which is just network, but many customer put in parallel to the real network just to observe the real network and to be able to troubleshoot and diagnose problem in the real network. So, this two feature telemetry and ERSPAN that are basically troubleshooting feature are the two features that are beginning are getting more traction. >> You're talking about realtime things like telemetry. You know, the applications and the integrations that you need to deal with are so important, back in some of the previous start-ups that you done was getting ready for, say how do we optimize for virtualization, today you talk cloud-native architectures, streaming, very popular, very modular, often container based solutions and things change constantly. You look at some of these architectures, it's not a single thing that goes on for a long period of time, but it's lots of things that happen over shorter periods of time. So, what integrations do you need to do, and what architecturally, how do you build things to make them as you talk, future-proof for these kind of cloud architectures? >> Yeah, what I mentioned were just the two low hanging fruit, if you want the first two low hanging fruit of this architecture. But basically, the two that come immediately after and where there is a huge amount of radio are distributor's state for firewall, with micro-segmentation support. That is a huge topic in itself. So important nowadays that is absolutely fundamental to be able to build a cloud. That is very important, and the second one is wire rate encryption. There is so much demand for privacy, and so much demand to encrypt the data. Not only between data center but now also inside the data center. And when you look at a large bank for example. A large bank is no longer a single organization. A large bank is multiple organizations that are compartmentalized by law. That need to keep things separate by law, by regulation, by FCC regulation. And if you don't have encryption, and if you don't have distributed firewall, is really very difficult to achieve that. And then you know, there are other applications, we mentioned storage NVME, and is a very nice application, and then we have even more, if you go to look at load balance in between server, doing compression for storage and other possible applications. But I sort of lost your real question. >> So, just part of the pieces, when you look at integrations that Pensando needs to do, for maybe some of the applications that you would tie in to any of those that come to mind? >> Yeah, well for sure. It depends, I see two main branches again. One is the cloud provider, and one are the enterprise. In the cloud provider, basically this cloud provider have a huge management infrastructure that is already built and they want just the card to adapt to this, to be controllable by this huge management infrastructure. They already know which rule they want to send to the card, they already know which feature they want to enable on the card. They already have all that, they just want the card to provide the data plan performers for that particular feature. So they're going to build something particular that is specific for that particular cloud provider that adapt to that cloud provider architecture. We want the flexibility of having an API on the card that is like a rest API or a gRPC which they can easily program, monitor and control that card. When you look at the enterprise, the situation is different. Enterprise is looking to at two things. Two or three things. The first thing is a complete solution. They don't want to, they don't have the management infrastructure that they have built like a cloud provider. They want a complete solution that has the card and the management station and there's all what is required to make from day one, a working solution, which is absolutely correct in an enterprise environment. They also want integration, and integration is the tool that they already have. If you look at main enterprise, one of a dominant presence is clearly VMware virtualization in terms of ESX and vSphere and NSX. And so most of the customer are asking us to integrate with VMware, which is a very reasonable demand. And then of course, there are other player, not so much in the virtualization's space, but for example, in the data collections space, and the data analysis space, and for sure Pensando doesn't want to reinvent the wheel there, doesn't want to build a data collector or data analysis engine and whatever, there is a lot of work, and there are a lot out there, so integration with things like Splunk for example are kind of natural for Pensando. >> Eccellent, so wait, you talked about some of the places where Pensando doesn't need to reinvent the wheel, you talk through a lot of the different technology pieces. If I had to have you pull out one, what would you say is the biggest innovation that Pensando has built into the platform. >> Well, the biggest innovation is this P4 architecture. And the P4 architecture was a sort of gift that was given us in the sense that it was not invented for what we use it. P4 was basically invented to have programmable switches. The first big P4 company was clearly Barefoot that then was acquired by Intel and Barefoot built a programmable switch. But if you look at the reality of today, the network, most of the people want the network to be super easy. They don't want to program anything into the network. They want to program everything at the edge, they want to put all the intelligence and the programmability of the edge, so we borrowed the P4 architecture, which is fantastic programmable architecture and we implemented that yet. It's also easier because the bandwidth is clearly more limited at the edge compared to being in the core of a network. And that P4 architecture give us a huge advantage. If you, tomorrow come up with the Stuart Encapsulation Super Duper Technology, I can implement in the copper The Stuart, whatever it was called, Super Duper Encapsulation Technology, even when I design the ASIC I didn't know that encapsulation exists. Is the data plan programmability, is the capability to program the data plan and programming the data plan while maintaining wire-speed performance, which I think is the biggest benefit of Pensando. >> All right, well Silvano, thank you so much for sharing, your journey with Pensando so far, really interesting to dig into it and absolutely look forward to following progress as it goes. >> Stuart, it's been really a pleasure to talk with you, I hope to talk with you again in the near future. Thank you so much. >> All right, and thank you for watching theCUBE, I'm Stu Miniman, thanks for watching. (upbeat music)

hi everybody thank you for joining us today for the virtual Vertica BBC 2020 today's breakout session is entitled Vertica and en mode at the trade desk my name is su LeClair director of marketing at Vertica and I'll be your host for this webinar joining me is Ron Cormier senior Vertica database engineer at the trade desk before we begin I encourage you to submit questions or comments during the virtual session you don't have to wait just type your question or comment in the question box below the slides and click submit there will be a Q&A session at the end of the presentation we'll answer as many questions as we're able to during that time any questions that we don't address we'll do our best to answer them offline alternatively you can visit vertical forums to post your questions there after the session our engineering team is planning to join the forums to keep the conversation going also a quick reminder that you can maximize your screen by clicking the double arrow button in the lower right corner of the slide and yes this virtual session is being recorded and will be available to view on demand this week we'll send you a notification as soon as it's ready so let's get started over to you run thanks - before I get started I'll just mention that my slide template was created before social distancing was a thing so hopefully some of the images will harken us back to a time when we could actually all be in the same room but with that I want to get started uh the date before I get started in thinking about the technology I just wanted to cover my background real quick because I think it's peach to where we're coming from with vertically on at the trade desk and I'll start out just by pointing out that prior to my time in the trade desk I was a tech consultant at HP HP America and so I traveled the world working with Vertica customers helping them configure install tune set up their verdict and databases and get them working properly so I've seen the biggest and the smallest implementations and everything in between and and so now I'm actually principal database engineer straight desk and and the reason I mentioned this is to let you know that I'm a practitioner I'm working with with the product every day or most days this is a marketing material so hopefully the the technical details in this presentation are are helpful I work with Vertica of course and that is most relative or relevant to our ETL and reporting stack and so what we're doing is we're taking about the data in the Vertica and running reports for our customers and we're an ad tech so I did want to just briefly describe what what that means and how it affects our implementation so I'm not going to cover the all the details of this slide but basically I want to point out that the trade desk is a DSP it's a demand-side provider and so we place ads on behalf of our customers or agencies and ad agencies and their customers that are advertised as brands themselves and the ads get placed on to websites and mobile applications and anywhere anywhere digital advertising happens so publishers are what we think ocean like we see here espn.com msn.com and so on and so every time a user goes to one of these sites or one of these digital places and an auction takes place and what people are bidding on is the privilege of showing and add one or more ads to users and so this is this is really important because it helps fund the internet ads can be annoying sometimes but they actually help help are incredibly helpful in how we get much much of our content and this is happening in real time at very high volumes so on the open Internet there is anywhere from seven to thirteen million auctions happening every second of those seven to thirteen million auctions happening every second the trade desk bids on hundreds of thousands per second um so that gives it and anytime we did we have an event that ends up in Vertica that's that's one of the main drivers of our data volume and certainly other events make their way into Vertica as well but that wanted to give you a sense of the scale of the data and sort of how it's impacting or how it is impacted by sort of real real people in the world so um the uh let's let's take a little bit more into the workload and and we have the three B's in spades late like many many people listening to a massive volume velocity and variety in terms of the data sizes I've got some information here some stats on on the raw data sizes that we deal with on a daily basis per day so we ingest 85 terabytes of raw data per day and then once we get it into Vertica we do some transformations we do matching which is like joins basically and we do some aggregation group buys to reduce the data and make it clean it up make it so it's more efficient to consume buy our reporting layer so that matching in aggregation produces about ten new terabytes of raw data per day it all comes from the it all comes from the data that was ingested but it's new data and so that's so it is reduced quite a bit but it's still pretty pretty high high volume and so we have this aggregated data that we then run reports on on behalf of our customers so we have about 40,000 reports per day oh that's probably that's actually a little bit old and older number it's probably closer to 50 or 55,000 reports per day at this point so it's I think probably a pretty common use case for for Vertica customers it's maybe a little different in the sense that most of the reports themselves are >> reports so they're not it's not a user sitting at a keyboard waiting for the result basically we have we we have a workflow where we do the ingest we do this transform and then and then once once all the data is available for a day we run reports on behalf of our customer to let me have our customers on that that daily data and then we send the reports out you via email or we drop them in a shared location and then they they look at the reports at some later point of time so it's up until yawn we did all this work on on enterprise Vertica at our peak we had four production enterprise clusters each which held two petabytes of raw data and I'll give you some details on on how those enterprise clusters were configured in the hardware but before I do that I want to talk about the reporting workload specifically so the the reporting workload is particularly lumpy and what I mean by that is there's a bunch of work that becomes available bunch of queries that we need to run in a short period of time after after the days just an aggregation is completed and then the clusters are relatively quiet for the remaining portion of the day that's not to say they are they're not doing anything as far as read workload but they certainly are but it's much less reactivity after that big spike so what I'm showing here is our reporting queue and the spike is is when all those reports become a bit sort of ailable to be processed we can't we can't process we can't run the report until we've done the full ingest and matching and aggregation for the day and so right around 1:00 or 2:00 a.m. UTC time every day that's when we get this spike and the spike we affectionately called the UTC hump but basically it's a huge number of queries that need to be processed sort of as soon as possible and we have service levels that dictate what as soon as possible means but I think the spike illustrates our use case pretty pretty accurately and um it really as we'll see it's really well suited for pervert icky on and we'll see what that means so we've got our we had our enterprise clusters that I mentioned earlier and just to give you some details on what they look like there they were independent and mirrored and so what that means is all four clusters held the same data and we did this intentionally because we wanted to be able to run our report anywhere we so so we've got this big queue over port is big a number of reports that need to be run and we've got these we started we started with one cluster and then we got we found that it couldn't keep up so we added a second and we found the number of reports went up that we needed to run that short period of time and and so on so we eventually ended up with four Enterprise clusters basically with this with the and we'd say they were mirrored they all had the same data they weren't however synchronized they were independent and so basically we would run the the tailpipe line so to speak we would run ingest and the matching and the aggregation on all the clusters in parallel so they it wasn't as if each cluster proceeded to the next step in sync with which dump the other clusters they were run independently so it was sort of like each each cluster would eventually get get consistent and so this this worked pretty well for for us but it created some imbalances and there was some cost concerns that will dig into but just to tell you about each of these each of these clusters they each had 50 nodes they had 72 logical CPU cores a half half a terabyte of RAM a bunch of raid rated disk drives and 2 petabytes of raw data as I stated before so pretty big beefy nodes that are physical physical nodes that we held we had in our data centers we actually reached these nodes so so it was on our data center providers data centers and the these were these these were what we built our business on basically but there was a number of challenges that we ran into as we as we continue to build our business and add data and add workload and and the first one is is some in ceremony can relate to his capacity planning so we had to prove think about the future and try to predict the amount of work that was going to need to be done and how much hardware we were going to need to satisfy that work to meet that demand and that's that's just generally a hard thing to do it's very difficult to verdict the future as we can probably all attest to and how much the world has changed and even in the last month so it's a it's a very difficult thing to do to look six twelve eighteen eighteen months into the future and sort of get it right and and and what people what we tended to do is we reach or we tried to our art plans our estimates were very conservative so we overbought in a lot of cases and not only that we had to plan for the peak so we're planning for that that that point in time that those number of hours in the early morning when we had to we had all those reports to run and so that so so we ended up buying a lot of hardware and we actually sort of overbought at times and then and then as the hardware were days it would kind of come into it would come into maturity and we have our our our workload would sort of come approach matching the demand so that was one of the big challenges the next challenge is that we were running on disk you can we wanted to add data in sort of two dimensions the only dimensions that everybody can think about we wanted to add more columns to our big aggregates and we wanted to keep our big aggregates for for longer periods of time so both horizontally and vertically we wanted to expand the datasets but we basically were running out of disk there was no more disk in and it's hard to add a disc to Vertica in enterprise mode not not impossible but certainly hard and and one cannot add discs without adding compute because enterprise mode the disk is all local to each of the nodes for most most people you can do not exchange with sands and other external rays but that's there are a number of other challenges with that so um adding in order to add disk we had to add compute and that basically meant kept us out of balance we're adding more compute than we needed for the amount of disk so that was the problem certainly physical nodes getting them the order delivered racked cables even before we even start such Vertica there's lead times there and and so it's also long commitment since we like I mentioned me Lisa hardware so we were committing to these nodes these physical servers for two or three years at a time and I mentioned that can be a hard thing to do but we wanted to least to keep our capex down so we wanted to keep our aggregates for a long period of time we could have done crazy things or more exotic things to to help us with this if we had to in enterprise mode we could have started to like daisy chain clusters together and that would have been sort of a non-trivial engineering effort because we would need to then figure out how to migrate data source first to recharge the data across all the clusters and we had to migrate data from one cluster to another cluster hesitation and we would have to think about how to aggregate run queries across clusters so if you assured data set spans two clusters it would have had to sort of aggregated within each cluster maybe and then build something on top the aggregated the data from each of those clusters so not impossible things but certainly not easy things and luckily for us we started talking about two Vertica about separation of compute and storage and I know other customers were talking to Vertica as we were people had had these problems and so Vertica inyeon mode came to the rescue and what I want to do is just talk about nyan mode really briefly for for those in the audience who aren't familiar but it's basically Vertigo's answered to the separation of computing storage it allows one to scale compute and or storage separately and and this there's a number of advantages to doing that whereas in the old enterprise days when you add a compute you added stores and vice-versa now we can now we can add one or the other or both according to how we want to and so really briefly how this works this slide this figure was taken directly from the verdict and documentation and so just just to talk really briefly about how it works the taking advantage of the cloud and so in this case Amazon Web Services the elasticity in the cloud and basically we've got you seen two instances so elastic cloud compute servers that access data that's in an s3 bucket and so three three ec2 nodes and in a bucket or the the blue objects in this diagram and the difference is a couple of a couple of big differences one the data no longer the persistent storage of the data the data where the data lives is no longer on each of the notes the persistent stores of the data is in s3 bucket and so what that does is it basically solves one of our first big problems which is we were running out of disk the s3 has for all intensive purposes infinite storage so we can keep much more data there and that mostly solved one of our big problems so the persistent data lives on s3 now what happens is when a query runs it runs on one of the three nodes that you see here and assuming we'll talk about depo in a second but what happens in a brand new cluster where it's just just spun up the hardware is the query will will run on those ec2 nodes but there will be no data so those nodes will reach out to s3 and run the query on remote storage so that so the query that the nodes are literally reaching out to the communal storage for the data and processing it entirely without using any data on on the nodes themselves and so that that that works pretty well it's not as fast as if the data was local to the nodes but um what Vertica did is they built a caching layer on on each of the node and that's what the depot represents so the depot is some amount of disk that is relatively local to the ec2 node and so when the query runs on remote stores on the on the s3 data it then queues up the data for download to the nodes and so the data will get will reside in the Depot so that the next query or the subsequent subsequent queries can run on local storage instead of remote stores and that speeds things up quite a bit so that that's that's what the role of the Depot is the depot is basically a caching layer and we'll talk about the details of how we can see your in our Depot the other thing that I want to point out is that since this is the cloud another problem that helps us solve is the concurrency problem so you can imagine that these three nodes are one sort of cluster and what we can do is we can spit up another three nodes and have it point to the same s3 communal storage bucket so now we've got six nodes pointing to the same data but we've you isolated each of the three nodes so that they act as if they are their own cluster and so vertical calls them sub-clusters so we've got two sub clusters each of which has three nodes and what this has essentially done it is it doubled the concurrency doubled the number of queries that can run at any given time because we've now got this new place which new this new chunk of compute which which can answer queries and so that has given us the ability to add concurrency much faster and I'll point out that for since it's cloud and and there are on-demand pricing models we can have significant savings because when a sub cluster is not needed we can stop it and we pay almost nothing for it so that's that's really really important really helpful especially for our workload which I pointed out before was so lumpy so those hours of the day when it's relatively quiet I can go and stop a bunch of sub clusters and and I will pay for them so that that yields nice cost savings let's be on in a nutshell obviously engineers and the documentation can use a lot more information and I'm happy to field questions later on as well but I want to talk about how how we implemented beyond at the trade desk and so I'll start on the left hand side at the top the the what we're representing here is some clusters so there's some cluster 0 r e t l sub cluster and it is a our primary sub cluster so when you get into the world of eon there's primary Club questions and secondary sub classes and it has to do with quorum so primary sub clusters are the sub clusters that we always expect to be up and running and they they contribute to quorum they decide whether there's enough instances number a number of enough nodes to have the database start up and so these this is where we run our ETL workload which is the ingest the match in the aggregate part of the work that I talked about earlier so these nodes are always up and running because our ETL pipeline is always on we're internet ad tech company like I mentioned and so we're constantly getting costly running ad and there's always data flowing into the system and the matching is happening in the aggregation so that part happens 24/7 and we wanted so that those nodes will always be up and running and we need this we need that those process needs to be super efficient and so what that is reflected in our instance type so each of our sub clusters is sixty four nodes we'll talk about how we came at that number but the infant type for the ETL sub cluster the primary subclusters is I 3x large so that is one of the instance types that has quite a bit of nvme stores attached and we'll talk about that but on 32 cores 240 four gigs of ram on each node and and that what that allows us to do I should have put the amount of nvme but I think it's seven terabytes for anything me storage what that allows us to do is to basically ensure that our ETL everything that this sub cluster does is always in Depot and so that that makes sure that it's always fast now when we get to the secondary subclusters these are as mentioned secondary so they can stop and start and it won't affect the cluster going up or down so they're they're sort of independent and we've got four what we call Rhian subclusters and and they're not read by definition or technically they're not read only any any sub cluster can ingest and create your data within the database and that'll all get that'll all get pushed to the s3 bucket but logically for us they're read only like these we just most of these the work that they happen to do is read only which it is which is nice because if it's read only it doesn't need to worry about commits and we let we let the primary subclusters or ETL so close to worry about committing data and we don't have to we don't have to have the all nodes in the database participating in transaction commits so we've got a for read subclusters and we've got one EP also cluster so a total of five sub clusters each so plus they're running sixty-four nodes so that gives us a 320 node database all things counted and not all those nodes are up at the same time as I mentioned but often often for big chunks of the days most of the read nodes are down but they do all spin up during our during our busy time so for the reading so clusters we've got I three for Excel so again the I three incidents family type which has nvme stores these notes have I think three and a half terabytes of nvme per node we just rate it to nvme drives we raid zero them together and 16 cores 122 gigs of ram so these are smaller you'll notice but it works out well for us because the the read workload is is typically dealing with much smaller data sets than then the ingest or the aggregation workbook so we can we can run these workloads on on smaller instances and leave a little bit of money and get more granularity with how many sub clusters are stopped and started at any given time the nvme doesn't persist the data on it isn't persisted remember you stop and start this is an important detail but it's okay because the depot does a pretty good job in that in that algorithm where it pulls data in that's recently used and the that gets pushed out a victim is the data that's least reasons use so it was used a long time ago so it's probably not going to be used to get so we've got um five sub-clusters and we have actually got to two of those so we've got a 320 node cluster in u.s. East and a 320 node cluster in u.s. West so we've got a high availability region diversity so and their peers like I talked about before they're they're independent but but yours they are each run 128 shards and and so with that what that which shards are is basically the it's similar to segmentation when you take those dataset you divide it into chunks and though and each sub cluster can concede want the data set in its entirety and so each sub cluster is dealing with 128 shards it shows 128 because it'll give us even distribution of the data on 64 node subclusters 60 120 might evenly by 64 and so there's so there's no data skew and and we chose 128 because the sort of ginger proof in case we wanted to double the size of any of the questions we can double the number of notes and we still have no excuse the data would be distributed evenly the disk what we've done is so we've got a couple of raid arrays we've got an EBS based array that they're catalog uses so the catalog storage location and I think we take for for EBS volumes and raid 0 them together and come up with 128 gigabyte Drive and we wanted an EPS for the catalog because it we can stop and start nodes and that data will persist it will come back when the node comes up so we don't have to run a bunch of configuration when the node starts up basically the node starts it automatically joins the cluster and and very strongly there after it starts processing work let's catalog and EBS now the nvme is another raid zero as I mess with this data and is ephemeral so let me stop and start it goes away but basically we take 512 gigabytes of the nvme and we give it to the data temp storage location and then we take whatever is remaining and give it to the depot and since the ETL and the reading clusters are different instance types they the depot is is side differently but otherwise it's the same across small clusters also it all adds up what what we have is now we we stopped the purging data for some of our big a grits we added bunch more columns and what basically we at this point we have 8 petabytes of raw data in each Jian cluster and it is obviously about 4 times what we can hold in our enterprise classes and we can continue to add to this maybe we need to add compute maybe we don't but the the amount of data that can can be held there against can obviously grow much more we've also built in auto scaling tool or service that basically monitors the queue that I showed you earlier monitors for those spikes I want to see as low spikes it then goes and starts up instances one sub-collector any of the sub clusters so that's that's how that's how we we have compute match the capacity match that's the demand also point out that we actually have one sub cluster is a specialized nodes it doesn't actually it's not strictly a customer reports sub clusters so we had this this tool called planner which basically optimizes ad campaigns for for our customers and we built it it runs on Vertica uses data and Vertica runs vertical queries and it was it was wildly successful um so we wanted to have some dedicated compute and beyond witty on it made it really easy to basically spin up one of these sub clusters or new sub cluster and say here you go planner team do what you want you can you can completely maximize the resources on these nodes and it won't affect any of the other operations that were doing the ingest the matching the aggregation or the reports up so it gave us a great deal of flexibility and agility which is super helpful so the question is has it been worth it and without a doubt the answer is yes we're doing things that we never could have done before sort of with reasonable cost we have lots more data specialized nodes and more agility but how do you quantify that because I don't want to try to quantify it for you guys but it's difficult because each eon we still have some enterprise nodes by the way cost as you have two of them but we also have these Eon clusters and so they're there they're running different workloads the aggregation is different the ingest is running more on eon does the number of nodes is different the hardware is different so there are significant differences between enterprise and and beyond and when we combine them together to do the entire workload but eon is definitely doing the majority of the workload it has most of the data it has data that goes is much older so it handles the the heavy heavy lifting now the query performance is more anecdotal still but basically when the data is in the Depot the query performance is very similar to enterprise quite close when the data is not in Depot and it needs to run our remote storage the the query performance is is is not as good it can be multiples it's not an order not orders of magnitude worse but certainly multiple the amount of time that it takes to run on enterprise but the good news is after the data downloads those young clusters quickly catch up as the cache populates there of cost I'd love to be able to tell you that we're running to X the number of reports or things are finishing 8x faster but it's not that simple as you Iran is that you it is me I seem to have gotten to thank you you hear me okay I can hear you now yeah we're still recording but that's fine we can edit this so if I'm just talking to the person the support person he will extend our recording time so if you want to maybe pick back up from the beginning of the slide and then we'll just edit out this this quiet period that we have sir okay great I'm going to go back on mute and why don't you just go back to the previous slide and then come into this one again and I'll make sure that I tell the person who yep perfect and then we'll continue from there is that okay yeah sound good all right all right I'm going back on yet so the question is has it been worth it and for us the answer has been a resounding yes we're doing things that we never could have done at reasonable cost before and we got more data we've got this Y note this law has nodes and in work we're much more agile so how to quantify that um well it's not quite as simple and straightforward as you might hope I mean we still have enterprise clusters we've got to update the the four that we had at peak so we've still got two of those around and we got our two yawn clusters but they're running different workloads and they're comprised of entirely different hardware the dependence has I've covered the number of nodes is different for sub-clusters so 64 versus 50 is going to have different performance the the workload itself the aggregation is aggregating more columns on yon because that's where we have disk available the queries themselves are different they're running more more queries on more intensive data intensive queries on yon because that's where the data is available so in a sense it is Jian is doing the heavy lifting for the cluster for our workload in terms of query performance still a little anecdotal but like when the queries that run on the enterprise cluster the performance matches that of the enterprise cluster quite closely when the data is in the Depot when the data is not in a Depot and Vertica has to go out to the f32 to get the data performance degrades as you might expect it can but it depends on the curious all things like counts counts are is really fast but if you need lots of the data from the material others to realize lots of columns that can run slower I'm not orders of magnitude slower but certainly multiple of the amount of time in terms of costs anecdotal will give a little bit more quantifying here so what I try to do is I try to figure out multiply it out if I wanted to run the entire workload on enterprise and I wanted to run the entire workload on e on with all the data we have today all the queries everything and to try to get it to the Apple tab so for enterprise the the and estimate that we do need approximately 18,000 cores CPU cores all together and that's a big number but that's doesn't even cover all the non-trivial engineering work that would need to be required that I kind of referenced earlier things like starting the data among multiple clusters migrating the data from one culture to another the daisy chain type stuff so that's that's the data point now for eon is to run the entire workload estimate we need about twenty thousand four hundred and eighty CPU cores so more CPU cores uh then then enterprise however about half of those and partly ten thousand of both CPU cores would only run for about six hours per day and so with the on demand and elasticity of the cloud that that is a huge advantage and so we are definitely moving as fast as we can to being on all Aeon we have we have time left on our contract with the enterprise clusters or not we're not able to get rid of them quite yet but Eon is certainly the way of the future for us I also want to point out that uh I mean yawn is we found to be the most efficient MPP database on the market and what that refers to is for a given dollar of spend of cost we get the most from that zone we get the most out of Vertica for that dollar compared to other cloud and MPP database platforms so our business is really happy with what we've been able to deliver with Yan Yan has also given us the ability to begin a new use case which is probably this case is probably pretty familiar to folks on the call where it's UI based so we'll have a website that our customers can log into and on that website they'll be able to run reports on queries through the website and have that run directly on a separate row to get beyond cluster and so much more latent latency sensitive and concurrency sensitive so the workflow that I've described up until this point has been pretty steady throughout the day and then we get our spike and then and then it goes back to normal for the rest of the day this workload it will be potentially more variable we don't know exactly when our engineers are going to deliver some huge feature that is going to make a 1-1 make a lot of people want to log into the website and check how their campaigns are doing so we but Yohn really helps us with this because we can add a capacity so easily we cannot compute and we can add so we can scale that up and down as needed and it allows us to match the concurrency so beyond the concurrency is much more variable we don't need a big long lead time so we're really excited about about this so last slide here I just want to leave you with some things to think about if you're about to embark or getting started on your journey with vertically on one of the things that you'll have to think about is the no account in the shard count so they're kind of tightly coupled the node count we determined by figuring like spinning up some instances in a single sub cluster and getting performance smaller to finding an acceptable performance considering current workload future workload for the queries that we had when we started and so we went with 64 we wanted to you want to certainly want to increase over 50 but we didn't want to have them be too big because of course it costs money and so what you like to do things in power to so 64 nodes and then the shard count for the shards again is like the data segmentation is a new type of segmentation on the data and the start out we went with 128 it began the reason is so that we could have no skew but you know could process the same same amount of data and we wanted to future-proof it so that's probably it's probably a nice general recommendation doubleness account for the nodes the instance type and and how much people space those are certainly things you're going to consider like I was talking about we went for they I three for Excel I 3/8 Excel because they offer good good Depot stores which gives us a really consistent good performance and it is all in Depot the pretty good mud presentation and some information on on I think we're going to use our r5 or the are for instance types for for our UI cluster so much less the data smaller so much less enter this on Depot so we don't need on that nvm you stores the reader we're going to want to have a reserved a mix of reserved and on-demand instances if you're if you're 24/7 shop like we are like so our ETL subclusters those are reserved instances because we know we're going to run those 24 hours a day 365 days a year so there's no advantage of having them be on-demand on demand cost more than reserve so we get cost savings on on figuring out what we're going to run and have keep running and it's the read subclusters that are for the most part on on demand we have one of our each sub Buster's is actually on 24/7 because we keep it up for ad-hoc queries your analyst queries that we don't know when exactly they're going to hit and they want to be able to continue working whenever they want to in terms of the initial data load the initial data ingest what we had to do and now how it works till today is you've got to basically load all your data from scratch there isn't a great tooling just yet for data populate or moving from enterprise to Aeon so what we did is we exported all the data in our enterprise cluster into park' files and put those out on s3 and then we ingested them into into our first Eon cluster so it's kind of a pain we script it out a bunch of stuff obviously but they worked and the good news is that once you do that like the second yon cluster is just a bucket copy in it and so there's tools missions that can help help with that you're going to want to manage your fetches and addiction so this is the data that's in the cache is what I'm referring to here the data that's in the default and so like I talked about we have our ETL cluster which has the most recent data that's just an injected and the most difficult data that's been aggregated so this really recent data so we wouldn't want anybody logging into that ETL cluster and running queries on big aggregates to go back one three years because that would invalidate the cache the depot would start pulling in that historical data and it was our assessing that historical data and evicting the recent data which would slow things out flow down that ETL pipelines so we didn't want that so we need to make sure that users whether their service accounts or human users are connecting to the right phone cluster and I mean we just created the adventure users with IPS and target groups to palm those pretty-pretty it was definitely something to think about lastly if you're like us and you're going to want to stop and start nodes you're going to have to have a service that does that for you we're where we built this very simple tool that basically monitors the queue and stops and starts subclusters accordingly we're hoping that that we can work with Vertica to have it be a little bit more driven by the cloud configuration itself so for us all amazon and we love it if we could have it have a scale with the with the with the eight of us can take through points do things to watch out for when when you're working with Eon is the first is system table queries on storage layer or metadata and the thing to be careful of is that the storage layer metadata is replicated it's caught as a copy for each of the sub clusters that are out there so we have the ETL sub cluster and our resources so for each of the five sub clusters there is a copy of all the data in storage containers system table all the data and partitions system table so when you want to use this new system tables for analyzing how much data you have or any other analysis make sure that you filter your query with a node name and so for us the node name is less than or equal to 64 because each of our sub clusters at 64 so we limit we limit the nodes to the to the 64 et 64 node ETL collector otherwise if we didn't have this filter we would get 5x the values for counts and some sort of stuff and lastly there is a problem that we're kind of working on and thinking about is a DC table data for sub clusters that are our stops when when the instances stopped literally the operating system is down and there's no way to access it so it takes the DC table DC table data with it and so I cannot after after my so close to scale up in the morning and then they scale down I can't run DC table queries on how what performed well and where and that sort of stuff because it's local to those nodes so we're working on something so something to be aware of and we're working on a solution or an implementation to try to suck that data out of all the notes you can those read only knows that stop and start all the time and bring it in to some other kind of repository perhaps another vertical cluster so that we can run analysis and monitoring even you want those those are down that's it um thanks for taking the time to look into my presentation really do it thank you Ron that was a tremendous amount of information thank you for sharing that with everyone um we have some questions come in that I would like to present to you Ron if you have a couple min it your first let's jump right in the first one a loading 85 terabytes per day of data is pretty significant amount what format does that data come in and what does that load process look like yeah a great question so the format is a tab separated files that are Jesus compressed and the reason for that could basically historical we don't have much tabs in our data and this is how how the data gets compressed and moved off of our our bidders the things that generate most of this data so it's a PSD gzip compressed and how you kind of we kind of have how we load it I would say we have actually kind of a Cadillac loader in a couple of different perspectives one is um we've got this autist raishin layer that's homegrown managing the logs is the data that gets loaded into Vertica and so we accumulate data and then we take we take some some files and we push them to redistribute them along the ETL nodes in the cluster and so we're literally pushing the file to through the nodes and we then run a copy statement to to ingest data in the database and then we remove the file from from the nodes themselves and so it's a little bit extra data movement which you may think about changing in the future assisting we move more and more to be on well the really nice thing about this especially for for the enterprise clusters is that the copy' statements are really fast and so we the coffee statements use memory but let's pick any other query but the performance of the cautery statement is really sensitive to the amount of available memory and so since the data is local to the nodes literally in the data directory that I referenced earlier it can access that data from the nvme stores and the kabhi statement runs very fast and then that memory is available to do something else and so we pay a little bit of cost in terms of latency and in terms of downloading the data to the nose we might as we move more and more PC on we might start ingesting it directly from s3 not copying the nodes first we'll see about that what's there that's how that's how we read the data interesting works great thanks Ron um another question what was the biggest challenge you found when migrating from on-prem to AWS uh yeah so um a couple of things that come to mind the first was the baculum the data load it was kind of a pain I mean like I referenced in that last slide only because I mean we didn't have tools built to do this so I mean we had to script some stuff out and it wasn't overly complex but yes it's just a lot of data to move I mean even with starting with with two petabytes so making sure that there there is no missed data no gaps making and moving it from the enterprise cluster so what we did is we exported it to the local disk on the enterprise buses and we then we push this history and then we ingested it in ze on again Allspark X oh so it's a lot of days to move around and I mean we have to you have to take an outage at some point stop loading data while we do that final kiss-up phase and so that was that was a challenge a sort of a one-time challenge the other saying that I mean we've been dealing with a week not that we're dealing with but with his challenge was is I mean it's relatively you can still throw totally new product for vertical and so we are big advantages of beyond is allow us to stop and start nodes and recently Vertica has gotten quite good at stopping in part starting nodes for a while there it was it was it took a really long time to start to Noah back up and it could be invasive but we worked with with the engineering team with Yan Zi and others to really really reduce that and now it's not really an issue that we think that we think too much about hey thanks towards the end of the presentation you had said that you've got 128 shards but you have your some clusters are usually around 64 nodes and you had talked about a ratio of two to one why is that and if you were to do it again would you use 128 shards ah good question so that is a reference the reason why is because we wanted to future professionals so basically we wanted to make sure that the number of stars was evenly divisible by the number of nodes and you could I could have done that was 64 I could have done that with 128 or any other multiple entities for but we went with 128 is to try to protect ourselves in the future so that if we wanted to double the number of nodes in the ECL phone cluster specifically we could have done that so that was double from 64 to 128 and then each node would have happened just one chart that it had would have to deal with so so no skew um the second part of question if I had to do it if I had to do it over again I think I would have done I think I would have stuck with 128 we still have I mean so we either running this cluster for more than 18 months now I think especially in USC and we haven't needed to increase the number of nodes so in that sense like it's been a little bit extra overhead having more shards but it gives us the peace of mind that we can easily double that and not have to worry about it so I think I think everyone is a nice place to start and you may even consider a three to one or four to one if if you're if you're expecting really rapid growth that you were just getting started with you on and your business and your gates that's a small now but what you expect to have them grow up significantly less powerful green thank you Ron that's with all the questions that we have out there for today if you do have others please feel free to send them in and we will get back to you and we'll respond directly via email and again our engineers will be available on the vertical forums where you can continue the discussion with them there I want to thank Ron for the great presentation and also the audience for your participation in questions please note that a replay of today's event and a copy of the slides will be available on demand shortly and of course we invite you to share this information with your colleagues as well again thank you and this concludes this webinar and have a great day you

(upbeat music) >> Welcome back to theCUBE everybody. This is Dave Vellante. We've been covering the transformation of Oracle Consulting and really its rebirth. And I'm here with Chris Fox, who's the Group Vice President for Enterprise Cloud Architects and Chief Technologist for the North America Tech Cloud at Oracle. Chris, thanks so much for coming on theCUBE. >> Thanks Dave, glad to be here. >> So I love this title. I mean years ago there was no such thing as a Cloud Architect, certainly there were Chief Technologists but so you are really-- Those are your peeps, is that right? >> That's right. That's right. That's really, my team and I, that's all we do. So our focus is really helping our customers take this journey from when they were on premise to really transforming with cloud. And when we think about cloud, really for us, it's a combination. It's our hybrid cloud which happens to be on premise and then of course the true public cloud like most people are familiar with. So, very exciting journey and frankly I've seen just a lot of success for our customers. >> interesting that you hear conversations like, "Oh every company is a software company" which by the way we believe. Everybody's got a some kind of SaaS offering, but it really used to be the application, heads within organizations that had a lot of the power, still do, but of course you have cloud native developers etc. And now you have this new role of Cloud Architects, they've got to align, essentially have to provide infrastructure and capabilities so that you can be agile from a development standpoint. I wonder if you can talk about that dynamic of how the roles have evolved in the last several years. >> Yeah, you know it's very interesting now because as Oracle we spend a lot of our time with those applications owners. As a leader in SaaS right now, SaaS ERP, HCM. You just start walking through the list, they're transforming their organizations. They're trying to make their lives, much more efficient, better for their employees or customers etc. On the other side of the spectrum, we have the cloud native development teams and they're looking at better ways to deploy, develop applications, roll out new features at scale, roll out new pipelines. But Dave, what I think we're seeing at Oracle though, because we're so connected with SaaS and then we're also connected with the traditional applications that have run the business for years, the legacy applications that have been servicing us for 20 years and then the cloud native developers. So what my team and I are constantly focused on now is things like digital transformation and really wiring up all three of these across. So if we think of like a customer outcome, like I want to have a package delivered to me from a retailer, that actual process flow could touch a brand new cloud native site from e-commerce. It could touch essentially, maybe a traditional application that used to be on prem that's now on the cloud and then it might even use some new SaaS application maybe for maybe a procurement process or delivery vehicle and scheduling. So what my team does, we actually connect all three. So, what I always mention to my team and all of our customers, we have to be able to service all three of those constituents and really think about process flows. So I take the cloud native developer, we help them become efficient. We take the person who's been running that traditional application and we help them become more efficient. And then we have the SaaS applications which are now rolling out new features on a quarterly basis and the whole new delivery model. But the real key is connecting all three of these into a business process flow that makes the customer's life much more efficient. >> So what you're saying is that these Cloud Architects and the sort of modern day Chief Technologists, they're multi tool players. It's not just about cloud, it's about connecting that cloud to, whether the system's on prem or other clouds. Is that right? >> It is. You know and one thing that we're seeing too Dave, is that we know it's multi cloud. So it could be Oracle's cloud, hopefully it's always Oracle's cloud, but we don't expect that. So as architects, we certainly have to take a look at what is it that we're trying to optimize? What's the outcome we're looking for? And then be able to work across these teams, and I think what makes it probably most fun and exciting, on one day in one morning, let's say, you could be talking to the cloud native developer team. Talking about Kubernetes, CI/CD pipelines, all the great technologies that help us roll out applications and features faster. Then you'll go to a traditional, maybe Oracle E-Business suite job. This is something that's been running on prem maybe for 20 years, and it's really still servicing the business. And then you have another team that maybe is rolling out a SaaS application from Oracle. And literally all three teams are connected by a process flow. So the question is, how do we optimize all three on behalf of either the customer, the employee, the supplier? And that's really the job for the Oracle Cloud Architect. Which I think, really good, that's different than the other cloud because for the most part, we actually do offer SaaS, we offer platform, we offer infrastructure and we offer the hybrid cloud on prem. So it's a common conversation. How do we optimize all these? >> So I want to get into this cloud conversation a little bit. You guys are used to this term last mover advantage. I got to ask you about it. How is being last an advantage? But let me start there. >> Yeah, that's a great question. I mean, so frankly speaking I think that-- So Oracle has been developing, what's interesting is our SaaS applications for many, many, many years, and where we began this journey is looking at SaaS. And then we started with platform. Right after that we started saying how do we augment SaaS? This OCI for us or Oracle Cloud Infrastructure Gen 2 could be considered a last mover advantage. What does that mean? We join this cloud journey later than the others but because of our heritage, of the workloads we've been running, right? We've been running enterprise scale workloads for years, the cloud itself has been phenomenal, right? It's easier to use, pay for what you use, elastic etc. These are all phenomenal features, fell. And based on our enterprise heritage it wasn't delivering resilience at scale, even for like the traditional applications we've known on prem forever. People always say, "Chris we want to get out of the data center. "We're going zero data center." And I always say, "Well, how are you going to handle that back office stuff?" Right? The stuff that's really big, it's cranky, doesn't handle just, instances dying or things going away too easily. It needs predictable performance. It needs scale. It absolutely needs security and ultimately a lot of these applications truly have relied on an Oracle database. The Oracle database has it's own specific characteristics that it needs to run really well. So we actually looked at the cloud and we said, let's take the first generation clouds, which are doing great, but let's add the features that specifically, a lot of times, the Oracle workload needed in order to run very well and in a cost effective manner. So that's what we mean when we say, last mover advantage. We said, let's take the best of the clouds that are out there today. Let's look at the workloads that, frankly Oracle runs and has been running for years, what our customers needed and then let's build those features right into this next version of the cloud, we can service the enterprise. So our goal, honestly what's interesting is, even that first discussion we had about cloud native, and legacy applications, and also the new SaaS applications, we built a cloud that handles all three use cases, at scale resiliently in a very secure manner, and I don't know of any other cloud that's handling those three use cases, all in, we'll call it the same tendency for us at Oracle. >> Let's unpack that a little bit and get into, sort of, trying to understand the strategy and I want to frame it. So you were the last really to enter the cloud market, let's sort of agree on that. >> Chris: Yup. >> And you kind of built it from the ground up. And it's just too expensive now. The CapEx required to get into cloud is just astronomical. Now, even for a SaaS company, there's no sense. If you're a new SaaS company, you're going to run it in the cloud. Somebody else's cloud. There are some SaaS companies that of course run their own data centers but they're fewer and further between. But so, and I've also said that your advantage relative to the hyper scalers is that you've got this big SaaS estate and it somewhat insulates you, actually more than somewhat. Largely insulates you from the race to the bottom. On compute and storage, cost per bit kind of thing. But my question is, why was it was it important for Oracle, and is it important for Oracle and it's customers, that it had to participate in IaaS and PaaS and SaaS? Why not just the last two layers of that? What does that give you from a strategic advantage standpoint and what does that do for your customer? >> Yeah, great question. So the number one reason why we needed to have all three was that we have so many customers to today that are in a data center. They're running a lot of our workloads on premise and they absolutely are trying to find a better way to deliver a lower cost services to their customers. And, so, we couldn't just say let's just-- everyone needs to just become net new. Everyone just needs to ditch the old and go just to brand new alone. Too hard, too expensive at times. So we said, let's give us customers the ultimate amount of choice. So, let's even go back again to that developer conversation in SaaS. If you didn't have IaaS, we couldn't help customers achieve a zero data center strategy with their traditional application. We'll call it Peoplesoft, or JD Edwards or E-Business suite or even-- there's some massive applications that are running on the Oracle cloud right now that are custom applications built on the Oracle database. What they want is they said, "Give me the lowest ASP to get predictable performance IaaS" I'll run my app's tier on this. Number two, give me a platform service for database 'cause frankly, I don't really want to run your database, like, with all the manual effort, I want someone to automate, patching, scale up and down, and all these types of features like the pilot should have given us. And then number three, I do want SaaS over time. So we spend a lot of time with our customers, really saying, "how do I take this traditional application, run it on IaaS and PaaS?" And then number two, "let's modernize it at scale." Maybe I want to start peeling off functionality and running them as cloud native services right alongside, right? That's something again, that we're doing at scale, and other people are having a hard time running these traditional workloads on prem in the cloud. The second part is they say, "You know, I've got this legacy traditional ERP. Been servicing we well or maybe a supply chain system. Ultimately I want to get out of this. How do I get to SaaS?" And we say, "Okay, here's the way to do this. First, bring into the cloud, run it on IaaS and PaaS. And then selectively, I call it cloud slicing. Take a piece of functionality and put it into SaaS." For ERP, it might be something like start with GL, a new chart of accounts in ERP SaaS. And then slowly over a number of your journey as needed, adopt the next module. So this way, I mean, I'll just say this is the fun part of as an architect, our jobs, we're helping customers move to the cloud at scale, we're helping them do it at their rate, with whatever level of change they want. And when they're ready for SaaS, we're ready for them. And I would just say the other IaaS providers, here's the challenge we're seeing Dave, is that they're getting to the cloud, they're doing a little bit of modernization, but they want PaaS, they also want to ultimately get to SaaS, and frankly, those other clouds don't offer them. So they're kind of in this we're stuck on this lift and shift. But then we want to really move and modernize and go to SaaS. And I would say that's what Oracle is doing right now for enterprises. We're really helping them move these traditional workloads to the cloud IaaS and PaaS. And then number two, they're moving to SaaS when they're ready. And even when you get to SaaS, everyone says, "You know what, leave it as as vanilla as possible, but I want to make myself differentiated." In that case, again, IaaS and PaaS, coupled alongside a SaaS environment, you can build your specific differentiation. And then you leave the ERP pristine, so it can be upgraded constantly with no impact to your specific sidebar applications. So, I would say that the best clouds in the world, I mean, I think you're going to see a lot of the others are trying to, either SaaS providers trying to grow a PaaS, or maybe some of the IaaS players are trying to add SaaS. So, I think you're going to see this blending more and more because customers are asking for the flexibility For either or all three. But I will say that-- >> How can I get PaaS and SaaS-minus. >> Absolutely, I mean, what are you doing there? You're offering choice. There's not a question in my mind that Cisco is a huge customer of ours, they have a product that is one of their SaaS applications running Tetration on the Oracle Cloud. It actually doesn't run any Oracle. It's all cloud native applications. Natively built with a number of open source components. They run just IaaS. That's it, the Tetration product, and it runs fast. The Gen 2 cloud has a great architecture underneath it, flattened fast network. By far, for us, we feel like we really gotten into the guts of IaaS and made it run more efficiently. Other customers say, "I've got a huge Oracle footprint in the data center, help me get it out." So up to the cloud that they go, and they say I don't want just IaaS because that means I'm writing all the automation, like I have to manage all the patching. And this is where for us platform services really help because we give them the automation at scale, which allows their people to do other things, that may be more impactful for the business. >> I want to ask you about, the automation piece. And you guys have made the statement that your Gen 2 cloud is fundamentally different than how other clouds work, Gen 1 clouds. And the Gen 1 clouds which are evolving, the hyper scalars are evolving, but how is Oracle's Gen 2 cloud fundamentally different? >> Yeah. I think that one of the most basic elements of the cloud itself was that for us, we had to start with the security and the network. So if you imagine that those two components really, A, could dictate speed and performance, plus doing it in a secure fashion. The two things that you'll see an awful lot about for us, is that we've embedded not only security at every level. But we've even separated off what we call, every cloud, you have a number of compute instances and then you have storage, right? In the middle, you have a network. However, to become a cloud, and to offer the elastic scale and the multiple sharing of resources, you have to have something called a control plane. What we've done is we've actually extracted the control plane out into its own separate instance of a running machine. Other clouds actually have the control plane inside of there running compute cores. Now, what does that do? Well, the fact of the matter is, we assume that the control plane and the network should be completely separate from what you run on your cloud. So if you run a virtual machine, or if you run a bare metal instance, there's no Oracle software running on it. We actually don't trust customers, and we actually tell the customers don't trust us, either. So by separating out the control plane, and all the code that runs that environment off of the running machine, you get more cores meaning like you have-- There's no Oracle tax for running this environment. It's a separate conmputer for each one, the control plane. Number two, it's more secure. We actually don't have any running code on that machine, if you had a bare metal instance. So therefore, there's no way for one machine in the cloud to infect another machine if the control plane was compromised. The second part of the network, the guys who have been building this cloud, Don Johnson, a lot of the guys came from other clouds before and they said, "yYou know the one thing we have to do is make a we call it Flattened Fast Clause Network that really is never oversubscribed." So you'll constantly see and people always ask me same question, "Dave, why is the performance faster if its the same VM shape? "Like I don't understand why it's going faster, like high performance computing." And the reason again a lot of times is the network itself is that it's just not oversubscribed. It's constantly flowing all the data, there's no such thing as congestion on the network, which can happen. The last part, we actually added 52 terabytes of local storage to every one of those compute nodes. So therefore, there's a possibility you don't even have to traverse the network to do some really serious work on the local machine. So you add these together, the idea is make the network incredibly fast, separate out the control plane and run the software and security layer separate from the entire node where all the customers work is being done. Number three, give the customers more compute, by obviously having us offload it to a separate machine. And the last thing is put local storage and everything is what's called NVMe storage. Whether it's local or remote, everything's NVMe, though the IOPS we get are really off the charts. And again, it shows up in our benchmarks. >> Yeah, so you're getting, atomic access to memory. But in your control plane, you describe that control plane that's running. Sorry to geek out everybody. But I'm kind of curious, you know. You got me started, Chris. So that's control-- >> Yeah, that's good. >> the Oracle cloud or runs. Where's it live? >> It's essentially separated from the compute node. We actually have it in between, there's a compute node that all the work is done from the customer, could be on like a Kubernetes container or VM, whatever it might be. The control plane literally is separate. And it lives right next to the actual compute node the customer is using. So it's actually embedded on a SmartNIC, it's a completely different cores. It's a different chipset, different memory structure, everything. And it does two things. It helps us control what happens up in the customers compute nodes in VMs. And it also helps us virtualize the network down as well. So it literally, the control plane is separate and distinct. It's essentially a couple SmartNICS. >> And then how does Autonomous fit into this whole architecture? I'm speaking by the way for that description, I mean, it's nuanced, but it's important. I'm sure you having this conversation with a lot of cloud architects and chief technologists, they want to know this stuff, and they want to know how it works. And then, obviously, we'll talk about what the business impact is. But talk about Autonomous and where that fit. >> Yeah, so as Larry says that there are two products that really dictate the future of Oracle and our success with our customers. Number one is ERP-SaaS. The second one is Autonomous Database. So the Autonomous Database, what we've done is really taken a look at all the runtime operations of an Oracle database. So tuning, patching, securing all these different features, and what we've done is taken the best of the Oracle database, the best of something called Exadata which we run on the cloud, which really helps a lot of our customers. And then we've wrapped it with a set of automation and security tools to help it really manage itself, tune itself, patch itself, scale up and down, independent between compute and storage. So, why that's important though, is that really our goal is to help people run the Oracle database as they have for years but with far less effort, and then even not only far less effort, hopefully, a machine plus man, out of the equation we always talk about is man plus machine is greater than man alone. So being assisted by artificial intelligence and machine learning to perform those database operations, we should provide a better service to our customers with far less costs. >> Yeah, the greatest chess player in the world is a combination of man and machine, you know that? >> You know what? It makes sense. It makes sense because, there's a number of things that we can do as humans that are just too difficult to program. And then there are other things where machines are just phenomenal, right? I mean, there's no-- Think of Google Maps, you ask it wherever you want to go. And it'll tell you in a fraction of a second, not only the best route, but based on traffic from maybe the last couple of years. right now, we don't have autonomous cars, right, that are allowed to at least drive fully autonomous yet, it's coming. But in the meantime, a human could really work through a lot of different scenarios it was hard to find a way to do that in autonomous driving. So I do believe that it's going to be a great combination. Our hope and goal is that the people who have been running Oracle databases, how can we help them do it with far less effort and maybe spend more time on what the data can do for the organization, right? Improve customer experience, etc. Versus maybe like, how do I spin up a table? One of our customers is a huge consumer. They said, "our goal is how do we reduce the time to first table?" Meaning someone in the business just came up with an idea? How do I reduce the time to first table. For some of our customers, it can take months. I mean, if you were going to put in a new server, find a place in the data center, stand up a database, make the security controls, right and etc. With the autonomous database, I could spin one up right here, for us and, and we could start using it and it would be secure, which is utmost and paramount. It would scale up and down, meaning like just based on workload, as I load data into it, it would tune itself, it would help us with the idea of running more efficiently, which means less cores, which means also less cost. And then the constant security patches that may come up because of different threats or new features. It would do that potentially on its own if you allow it. Obviously some people want to watch you know what exactly it's going to do first. Do regression testing. But it's an exciting product because I've been working with the Oracle database for about 20 years now. And to see it run in this manner, it's just phenomenal. And I think that's the thing, a lot of the database teams have seen. Pretty amazing work. >> So I love this conversation. It's hardcore computer science, architecture, engineering. But now let's end with by up leveling this. We've been talking, a lot about Oracle Consulting. So let's talk about the business impact. So you go into customers, you talk to the cloud architects, the chief technologist, you pass that test. Now you got to deliver the business impact. Where does Oracle consulting fit with regard to that, and maybe you could talk about sort of where you guys want to take this thing. >> Yeah, absolutely. I mean, so, the cloud is great set of technologies, but where Oracle consulting is really helping us deliver is in the outcome. One of the things I think that's been fantastic working with the Oracle consulting team is that cloud is new. For a lot of customers who've been running these environments for a number of years, there's always some fear and a little bit of trepidation saying, "How do I learn this new cloud?" I mean, the workloads, we're talking about deeper, like tier zero, tier one, tier two, and all the way up to Dev and Test and DR, Oracle Consulting does really, a couple of things in particular, number one, they start with the end in mind. And number two, that they start to do is they really help implement these systems. And, there's a lot of different assurances that we have that we're going to get it done on time, and better be under budget, 'cause ultimately, again, that's something that's really paramount for us. And then the third part of it a lot of it a lot of times is run books, right? We actually don't want to just live at our customers environments. We want to help them understand how to run this new system. So training and change management. A lot of times Oracle Consulting is helping with run books. We usually will, after doing it the first time, we'll sit back and let the customer do it the next few times, and essentially help them through the process. And our goal at that point is to leave, only if the customer wants us to but ultimately, our goal is to implement it, get it to go live on time, and then help the customer learn this journey to the cloud. And without them, frankly, I think these systems are sometimes too complex and difficult to do on your own, maybe the first time especially because like I say, they're closing the books, they might be running your entire supply chain. They run your entire HR system or whatever they might be. Too important to leave to chance. So they really help us with helping the customer become live and become very competent and skilled, because they can do it themselves. >> But Chris, we've covered the gamut. We're talking about, architecture, went to NVMe. We're talking about the business impact, all of your automation, run books, loved it. Loved the conversation, but to leave it right there but thanks so much for coming on theCUBE and sharing your insights, great stuff. >> Absolutely, thanks Dave, and thank you for having me on. >> All right, you're welcome. And thank you for watching everybody. This is Dave Vellante for theCUBE. We are covering the Oracle North America Consulting transformation and its rebirth in this digital event. Keep it right there. We'll be right back. (upbeat music)

(upbeat funk jazz music) >> Hello, and welcome to theCUBE Studios in Palo Alto, California for another CUBE Conversation, where we go in depth with thought leaders driving innovation across tech industry. I'm your host, Peter Burris. What does every CIO want to do? They want to support the business as it evolves and transforms, using data as that catalyst for better customer experience, improved operations, and more profitable options. But to do that we have to come up with a way of improving the underlying infrastructure that makes all this possible. We can't have a situation where we introduce more complex applications in response to richer business needs and have that translated into non-scalable underlying technology. CIOs in 2020 and beyond have to increasingly push their suppliers to make things simpler. And that's true in all domains, but perhaps especially storage, where the explosion of data is driving so many of these changes. So what does it mean to say that storage can be made more simple? Well to have that conversation we're going to be speaking with Eric Herzog, CMO and VP of Global Channels at IBM Storage, about, quite frankly, an announcement that IBM's doing to specifically address that question, making storage simpler. Eric, thanks very much for coming back to theCUBE. >> Great, thank you. We love to be here. >> All right, I know you got an announcement to talk about, but give us the update. What's going on with IBM Storage? >> Well, I think the big thing is, clients have told us, storage is too complex. We have a multitude of different platforms, an entry product, a mid-range product, a high-end product, then we have to traverse to the cloud. Why can't we get a simple, easy to use, but very robust feature set? So at IBM Storage with this FlashSystem announcement, we have a family that traverses entry, mid-range, enterprise and automatically can go out to a hybrid multicloud environment, all driven across a common platform, common API, common software, our award-winning Spectrum Virtualize, and innovative technologies around, whether it be cyber-resiliency, performance, incredible performance, ease of use, easier and easier to use. For example, we can do AI-based automated tiering from one flash array to another, or from storage class memory to flash. Innovation, at the same time driving better value out of the storage but not charging a lot of extra money for these features. In fact, our FlashSystems announcement, the platforms, depending on the configuration, can be as much as 50% lower than our previous generation. Now that's delivering value, but at the same time we added enhanced features, for example, the capability of even better container support than we already had in our older platform. Or our new FlashCore Modules that can deliver performance in a cluster of up to 17.2 million IOPS, up from our previous performance of 15. Yet, as I said before, delivering that enterprise value and those enterprise data services, in this case I think you said, depending on the config, up to as much as 50% less expensive than some of our previous generation products. >> So let me unpack that a little bit. So, historically, when you look at, or even today, when you look at how storage product lines are set up, they're typically set up for one footprint for the low end, one or more footprints in the mid-range, and then one or more footprints at the high-end. And those are differentiated by the characteristics of the technologies being employed, the function and services that are being offered, and the prices and financial arrangements that are part of it. Are you talking about, essentially, a common product line that is differentiated only by the configuration needs of the volume and workloads? >> Exactly. The FlashSystem traverses entry, mid-range, enterprise, and can automatically get you out to a hybrid multicloud environment, same APIs, same software, same management infrastructure. Our Storage Insights product, which is a could-based storage manager and predictive analytics, works on the entry product, at no charge, mid-range product at no charge, the enterprise product at no charge, and we've even added, in that solution, support for non-IBM platforms, again. So, delivering more value across a standard platform with a common API, a common software. Remember, today's storage is growing exponentially. Are the enterprise customers getting exponentially more storage admins? No. In fact, many of the big enterprises, after the downturn of '08 and '09 had to cut back on storage resources. They haven't hired back to how many storage resources they had in 2007 or '8. They've gotten back to full IT, but a lot of those guys are DevOps people or other functions, so, the storage admins and the IT infrastructure admins have to manage extra petabytes, extra exabytes depending on the type of company. So one platform that can do that and traverse out to the cloud automatically, gives you that innovation and that value. In fact, two of our competitors, just as example, do the same thing, have four platforms. Two other have three. We can do it with one. Simple platform, common API, common storage management, common interface, incredible performance, cyber-resiliency, but all built in something that's a common data management infrastructure with common data software, yet continuing to innovate as we've done with this release of the FlashSystem family. >> OK, so talk about the things that, common API, common software, also, I presume, common, the core module, that FlashCore Module that you have, common across the family as well? >> Almost all the family. At the very entry space we still do use interstandard SSDs but we can get as low as a street price for all-flash config of $16,000 for an all-flash array. Two, three years ago that would've been unheard of. And, by the way, it had six lines of availability, same software interface and API as a system that could go up to millions of dollars at the way high end, right? And anything in between. So common ease of use, common management, simple to manage, simple to deploy, simple to use, but not simple in the value proposition. Reduce the TCO, reduce the ROI, reduce the operational manpower, they're overtaxed as it is. So by making this across the portfolio with the FlashSystem and go out to the hybrid multicloud but bringing in all this high technology such as our FlashCore Modules and, as I said, at a reduced price to the previous generation. What more could you ask for? >> OK, so you've got some promises that you made in 2019 that you're also actually realizing. One of my favorite ones, something I think is pretty important, is storage class memory. Talk about how some of those 2019 promises are being realized in this announcement. >> So what we did is, when we announced our first FlashSystem family in 2018 using our new NVMe FlashCore Modules, we had an older FlashSystem family for several years that used, you know, the standard SaaS interface. But our first NVMe product was announced in the summer of 2018. At that time we said, all the way back then, that in early '20 we would be start shipping storage class memory. Now, by the way, those FlashSystems NVMe products that we announced back then, actually can still use storage class memory, so, we're protecting the investment of our installed base. Again, innovation with value on the installed base. >> A very IBM thing to do. >> Yes, we want to take care of the installed base, we also want to have new modern technologies, like storage class memory, like improved performance and capacity in our FlashCore Modules where we take off the shelf Flash and create our own modules. Seven year media warranty, up to 17.2 million IOPS, 17 mites of latency, which is 30% better than our next nearest competitor. By the way, we can create a 17 million IOP config in only eight rack U. One of our competitors gets close, 15 million, but it takes them 40 rack U. Again, operational manpower, 40 rack U's harder to manage, simplicity of deployment, it's harder to deploy all that in 40 rack U, we can do it in eight. >> And pricing. >> Yes. And we've even brought out now, a preconfigured rack. So what we call the FlashSystem 9200R built into the rack with a switching infrastructure, with the storage you need, IBM services will deploy it for you, that's part of the deal, and you can create big solutions that can scale dramatically. >> Now R stands for hybrid? >> Rack. >> Rack. Well talk to me about some of the hybrid packaging that you're bringing out for hybrid cloud. >> Sure, so, from a hybrid cloud perspective, our Spectrum Virtualize software, which sits on-prem, entry, mid-range and at the upper end, can traverse to a cloud called Spectrum Virtualize for Cloud. Now, one of the keys things of Spectrum Virtualize, both on-prem and our cloud version, is it supports not only IBM arrays, but through a storage virtualisation technology, over 450 arrays from multi-vendors, and in short our competition. So we can take our arrays, and automatically go out to the cloud. We can do a lot of things. Cloud air gapping, to help with malware and ransonware protection, DR, snapshots and replicas. Not only can the new FlashSystem family do that, to Spectrum Virtualize on-prem and then out, but Spectrum Virtualize coming on our FlashSystem portfolio can actually virtualize non-IBM arrays and give them the same enterprise functionality and in this case, hybrid cloud technology, not only for us, but for our competitors products as well. One user interface. Now talk about simple. Our own products, again one family, entry, mid-range and enterprise traversing the cloud. And by the way, for those of you who are heterogeneous, we can deliver those enterprise class services, including going out to a hybrid multi-cloud configuration, for our competitors products as well. One user interface, one throat to choke, one support infrastructure with our Storage Insights platform, so it's a great way to make things easier, cut the CAPEX and OPEX, but not cut the innovation. We believe in value and innovation, but in an easy deploy methodology, so that you're not overly complex. And that is killing people, the complexity of their solutions. >> All right. So there's a couple of things about cloud, as we move forward, that are going to be especially interesting. One of them is going to be containers. Everybody's talking about, and IBM's been talking about, you've been talking about this, we've talked about this a number of times, about how containers and storage and data are going to come together. How do you see this announcement supporting those emerging and evolving need for container-based applications in the enterprise. >> So, first of all, it's often tied to hybrid multi-cloudness. Many of the hybrid cloud configurations are configured on a container based environment. We support Red Hat OpenShift. We support Kubernetes environments. We can provide on these systems at no charge, persistent storage for those configurations. We also, although it does require a backup package, Spectrum Protect, the capability of backing up that persistent storage in an OpenShift or Kubernetes environment. So really it's critical. Part of our simplicity is this FlashSystem platform with this technology, can support bare metal workloads, virtualised workloads, VMware, HyperV, KVM, OVM, and now container workloads. And we do see, for the next coming years, think about bare metal. Bare metal is as old as I am. That's pretty old. Well we got tons of customers still got bare metal applications, but everyone's also gone virtualized. So it's not, are we going to have one? It's you're going to have all three. So with the FlashSystems family, and what we have with Spectrum Virtualized software, what we have with our container support, we need with bare metal support, incredible performance, whatever you need, VMware integration, HyperV integration, everything you need for a virtualized environment, and for a container environment, we have everything too. And we do think the, especially the mid to big accounts, are going to try run all three, at least for the next couple of years. This gives you a platform that can do that, at the entry point, up to the high end, and then out to a hybrid multi-cloud environment. >> With that common software and APIs across. Now, every year that you and I have talked, you've been especially passionate about the need for turning the crank, and evolving and improving the nature of automation, which is another one of the absolute necessities, as we start thinking about cloud. How is this announcement helping to take that next step, turn the crank in automation? >> So a couple of things. One is our support now for Ansible, so offering that Ansible support, integrates into the container management frameworks. Second thing is, we have a ton of AI-type specific based technology built into the FlashSystem platform. First is our cloud based storage and management predictive analytics package, Storage Insights. The base version comes for free across our whole portfolio, whether it be entry, mid-range or high-end, across the whole FlashSystems family. It gives you predictive analytics. If you really do have a support problem, it eases the support issues. For example, instead of me saying, "Peter send me those log files." Guess what? We can see the log files. And we can do it right there while you're on the phone. You've got a problem? Let's make it easier for you to get it solved. So Storage Insights across AI based, predictive analytics, performance, configuration issues, all predicatively done, so AI based. Secondly, we've integrated AI in to our Spectrum Virtualize product. So as exemplar, easier to your technology, can allow you to tier data from storage class memory to Flash, as an example, and guess what it does? It automatically knows based on usage patterns, where the data should go. Should it be on the storage class memory? Should it be on Flash core modules? And in fact, we can create a configuration, we have Flash core modules and introduce standard SSDs, which are both Flash, but our Flash core modules are substantially faster, much better latency, like I said, 30% better than the next nearest competition, up to 17.2 million IOPS. The next closest is 15. And in fact, it's interesting, one of our competitors has used storage class memory as a read cache. It dramatically helps them. But they go from 250 publicly stated mites of latency, to 125. With this product, the FlashSystem, anything that uses our Flash core modules, our FlashSystems semi 200, our FlashSystem 9200 product, and the 9200-R product. We can do 70 mites of latency, so almost twice as fast, without using storage class memory. So think what that storage class memory will offer. So we can create hybrid configurations, with StorageClass and Flash, you could have our Flash core modules, and introduce standard SSDs if you want, but it's all AI based. So we have AI based in our Storage Insights, predictive analytics, management and support infrastructure. And we have predictive analytics in things like our Easy Tier. So not only do we think storage is a critical foundation for the AI application workload and use case, which it is, but you need to imbue your storage, which we've done across FlashSystems, including what we've done with our cloud edition, because Spectrum Virtualize has a cloud edition, and an on-prem edition, seamless transparency, but AI in across that entire platform, using Spectrum Virtualize. >> All right, so let me summarize. We've got an absolute requirement from enterprise, to make storage simpler, which requires simple product families with more commonality, where that commonality delivers great value, and at the same time the option to innovate, where that innovation's going to create value. We have a lot simpler set of interfaces and technologies, as you said they're common, but they are more focused on the hybrid cloud, the multi-cloud world, that we're working in right now, that brings more automation and more high-quality storage services to bear wherever you are in the enterprise. So I've got to ask you one more question. I'm a storage administrator, or a person who is administering data, inside the infrastructure. I used to think of doing things this way, what is the one or two things that I'm going to do differently as a consequence of this kind of an announcement? >> So I think the first one, it's going to reduce your operational expenses and your operational man power, because you have a common API, a common software platform, a common foundation for data management and data movement, it's not going to be as complex for you to pull your storage configurations. Second thing, you don't have to make as many choices between high-end workloads, mid-range workloads, and entry workloads. Six lines across the board. Enterprise class data services across the board. So when you think simple, don't think simple as simplistic, low-end. This is a simple to use, simple deploy, simple to manage product, with extensive innovation and a price that's- >> So simple to secure? >> And simple to secure. Data rest encryption across the portfolio. And in fact those that use our FlashCore Modules, no performance hit on encryption, and no performance hit on data compression. So it can help you shrink the actual amount you need to buy from us, which sounds sort of crazy, that a storage company would do that, but with our data reduction technologies, compression being one of them, there's no performance hits, you can compress compressable workloads, and now, anything with a FlashCore Module, which by the way, happens to be FIPS 140-2 certified, there's no excuse not to encrypt, because encryption, as you know, has had a performance hit in the past. Now, our 7200, our 5100 FlashSystem, and our FlashSystem 9200 and 9200R, there's no performance on encrypting, so it gives you that extra resiliency, that you need in a storage world, and you don't get a non-compression, which helps you shrink how much you end up buying from IBM. So that's the type of innovation we deliver, in a simple to use, easy to deploy, easy to manage but incredible innovative value, brought into a very innovative solution, across the board, not just let's innovate at the high end or you know what I mean? Trying to make that innovation spread, which, by the way, makes it easier for the storage guy. >> Well, look, in a world, even inside a single enterprise, you're going to have branch offices, you're going to have local this, the edge, you can't let the bad guys in on a lesser platform that then can hit data on a higher end platform. So the days of presuming that there's this great differentiation in the tier are slowly coming to an end as everything becomes increasingly integrated. >> Well as you've pointed out many times, data is the asset. Not the most valuable one. It is the asset of today's digital enterprise and it doesn't matter whether you're a global Fortune 500, or you're a (mumble). Everybody is a digital enterprise these days, big, medium or small. So cyber resiliency is important, cutting costs is important, being able to modernize and optimize your infrastructure, simply and easily. The small guys don't have a storage guy, and a network guy and a server guy, they have the IT guy. And even the big guys, who used to have hundreds of storage admins in some cases, don't have hundreds any more. They've got a lot of IT people, but they cut back so these storage admins and infrastructure admins in these global enterprise, they're managing 10, 20 times the amount of storage they managed even two or three years ago. So, simple, across the board, and of course hyper multicloud is critical to these configurations. >> Eric, it's a great annoucement, congratulations to IBM to actually delivering on what your promises are. Once again, great to have you on theCUBE. >> Great, thank you very much Peter. >> And thanks to you, again, for participating in this CUBE conversation, I'm Peter Burris, see you next time. (upbeat, jazz music)