>> Announcer: From around the globe it's theCUBE. Presenting the Convergence of File and Object brought to you by Pure Storage. >> Okay now we're going to get the customer perspective on object and we'll talk about the convergence of file and object, but really focusing on the object pieces this is a content program that's being made possible by Pure Storage and it's co-created with theCUBE. Christopher CB Bohn is here. He's a lead architect for MicroFocus the enterprise data warehouse and principal data engineer at MicroFocus. CB welcome good to see you. >> Thanks Dave good to be here. >> So tell us more about your role at Microfocus it's a pan Microfocus role because we know the company is a multi-national software firm it acquired the software assets of HP of course including Vertica tell us where you fit. >> Yeah so Microfocus is you know, it's like I can says it's wide, worldwide company that it sells a lot of software products all over the place to governments and so forth. And it also grows often by acquiring other companies. So there is there the problem of integrating new companies and their data. And so what's happened over the years is that they've had a number of different discreet data systems so you've got this data spread all over the place and they've never been able to get a full complete introspection on the entire business because of that. So my role was come in, design a central data repository and an enterprise data warehouse, that all reporting could be generated against. And so that's what we're doing and we selected Vertica as the EDW system and Pure Storage FlashBlade as the communal repository. >> Okay so you obviously had experience with with Vertica in your previous role, so it's not like you were starting from scratch, but paint a picture of what life was like before you embarked on this sort of consolidated approach to your data warehouse. Was it just dispared data all over the place? A lot of M and A going on, where did the data live? >> CB: So >> Right so again the data is all over the place including under people's desks and just dedicated you know their own private SQL servers, It, a lot of data in a Microfocus is one on SQL server, which has pros and cons. Cause that's a great transactional database but it's not really good for analytics in my opinion. So but a lot of stuff was running on that, they had one Vertica instance that was doing some select reporting. Wasn't a very powerful system and it was what they call Vertica enterprise mode where it had dedicated nodes which had the compute and storage in the same locus on each server okay. So Vertica Eon mode is a whole new world because it separates compute from storage. Okay and at first was implemented in AWS so that you could spin up you know different numbers of compute nodes and they all share the same communal storage. But there has been a demand for that kind of capability, but in an on-prem situation. Okay so Pure storage was the first vendor to come along and have an S3 emulation that was actually workable. And so Vertica worked with Pure Storage to make that all happen and that's what we're using. >> Yeah I know back when back from where we used to do face-to-face, we would be at you know Pure Accelerate, Vertica was always there it stopped by the booth, see what they're doing so tight integration there. And you mentioned Eon mode and the ability to scale, storage and compute independently. And so and I think Vertica is the only one I know they were the first, I'm not sure anybody else does that both for cloud and on-prem, but so how are you using Eon mode, are you both in AWS and on-prem are you exclusively cloud? Maybe you could describe that a little bit. >> Right so there's a number of internal rules at Microfocus that you know there's, it's not AWS is not approved for their business processes. At least not all of them, they really wanted to be on-prem and all the transactional systems are on-prem. And so we wanted to have the analytics OLAP stuff close to the OLTP stuff right? So that's why they called there, co-located very close to each other. And so we could, what's nice about this situation is that these S3 objects, it's an S3 object store on the Pure Flash Blade. We could copy those over if we needed it to AWS and we could spin up a version of Vertica there, and keep going. It's like a tertiary GR strategy cause we actually have a, we're setting up a second, Flash Blade Vertica system geo located elsewhere for backup and we can get into it if you want to talk about how the latest version of the Pure software for the Flash Blade allows synchronization across network boundaries of those Flash Blade which is really nice because if, you know there's a giant sinkhole opens up under our Koll of facility and we lose that thing then we just have to switch to DNS. And we were back in business of the DR. And then the third one was to go, we could copy those objects over to AWS and be up and running there. So we're feeling pretty confident about being able to weather whatever comes along. >> Yeah I'm actually very interested in that conversation but before we go there. you mentioned you want, you're going to have the old lab close to the OLTP, was that for latency reasons, data movement reasons, security, all of the above. >> Yeah it's really all of the above because you know we are operating under the same sub-net. So to gain access to that data, you know you'd have to be within that VPN environment. We didn't want to going out over the public internet. Okay so and just for latency reasons also, you know we have a lot of data and we're continually doing ETL processes into Vertica from our production data, transactional databases. >> Right so they got to be approximate. So I'm interested in so you're using the Pure Flash Blade as an object store, most people think, oh object simple but slow. Not the case for you is that right? >> Not the case at all >> Why is that. >> This thing had hoop It's ripping, well you have to understand about Vertica and the way it stores data. It stores data in what they call storage containers. And those are immutable, okay on disc whether it's on AWS or if you had a enterprise mode Vertica, if you do an update or delete it actually has to go and retrieve that object container from disc and it destroys it and rebuilds it, okay which is why you don't, you want to avoid updates and deletes with vertica because the way it gets its speed is by sorting and ordering and encoding the data on disk. So it can read it really fast. But if you do an operation where you're deleting or updating a record in the middle of that, then you've got to rebuild that entire thing. So that actually matches up really well with S3 object storage because it's kind of the same way, it gets destroyed and rebuilt too okay. So that matches up very well with Vertica and we were able to design the system so that it's a panda only. Now we have some reports that we're running in SQL server. Okay which we're taking seven days. So we moved that to Vertica from SQL server and we rewrote the queries, which were had, which had been written in TC SQL with a bunch of loops and so forth and we were to get, this is amazing it went from seven days to two seconds, to generate this report. Which has tremendous value to the company because it would have to have this long cycle of seven days to get a new introspection in what they call the knowledge base. And now all of a sudden it's almost on demand two seconds to generate it. That's great and that's because of the way the data is stored. And the S3 you asked about, oh you know it, it's slow, well not in that context. Because what happens really with Vertica Eon mode is that it can, they have, when you set up your compute nodes, they have local storage also which is called the depot. It's kind of a cache okay. So the data will be drawn from the Flash Blade and cached locally. And that was, it was thought when they designed that, oh you know it's that'll cut down on the latency. Okay but it turns out that if you have your compute nodes close meaning minimal hops to the Flash Blade that you can actually tell Vertica, you know don't even bother caching that stuff just read it directly on the fly from the from the Flash Blade and the performance is still really good. It depends on your situation. But I know for example a major telecom company that uses the same topologies we're talking about here they did the same thing. They just dropped the cache cause the Flash Blade was able to deliver the data fast enough. >> So that's, you're talking about that's speed of light issues and just the overhead of switching infrastructure is that, it's eliminated and so as a result you can go directly to the storage array? >> That's correct yeah, it's like, it's fast enough that it's almost as if it's local to the compute node. But every situation is different depending on your needs. If you've got like a few tables that are heavily used, then yeah put them in the cache because that'll be probably a little bit faster. But if you're have a lot of ad hoc queries that are going on, you know you may exceed the storage of the local cache and then you're better off having it just read directly from the, from the Flash Blade. >> Got it so it's >> Okay. >> It's an append only approach. So you're not >> Right >> Overwriting on a record, so but then what you have automatically re index and that's the intelligence of the system. how does that work? >> Oh this is where we did a little bit of magic. There's not really anything like magic but I'll tell you what it is I mean. ( Dave laughing) Vertica does not have indexes. They don't exist. Instead I told you earlier that it gets a speed by sorting and encoding the data on disk and ordering it right. So when you've got an append-only situation, the natural question is well if I have a unique record, with let's say ID one, two, three, what happens if I append a new version of that, what happens? Well the way Vertica operates is that there's a thing called a projection which is actually like a materialized columnar data store. And you can have a, what they call a top-K projection, which says only put in this projection the records that meet a certain condition. So there's a field that we like to call a discriminator field which is like okay usually it's the latest update timestamp. So let's say we have record one, two, three and it had yesterday's date and that's the latest version. Now a new version comes in. When the data at load time vertical looks at that and then it looks in the projection and says does this exist already? If it doesn't then it adds it. If it does then that one now goes into that projection okay. And so what you end up having is a projection that is the latest snapshot of the data, which would be like, oh that's the reality of what the table is today okay. But inherent in that is that you now have a table that has all the change history of those records, which is awesome. >> Yeah. >> Because, you often want to go back and revisit, you know what it will happen to you. >> But that materialized view is the most current and the system knows that at least can (murmuring). >> Right so we then create views that draw off from that projection so that our users don't have to worry about any of that. They just get oh and say select from this view and they're getting the latest greatest snapshot of what the reality of the data is right now. But if they want to go back and say, well how did this data look two days ago? That's an easy query for them to do also. So they get the best of both worlds. >> So could you just plug any flash array into your system and achieve the same results or is there anything really unique about Pure? >> Yeah well they're the only ones that have got I think really dialed in the S3 object form because I don't think AWS actually publishes every last detail of that S3 spec. Okay so it had, there's a certain amount of reverse engineering they had to do I think. But they got it right. When we've, a couple maybe a year and a half ago or so there they were like at 99%, but now they worked with Vertica people to make sure that that object format was true to what it should be. So that it works just as if Vertica doesn't care, if it is on AWS or if it's on Pure Flash Blade because Pure did a really good job of dialing in that format and so Vertica doesn't care. It just knows S3, doesn't know what it doesn't care where it's going it just works. >> So the essentially vendor R and D abstracted that complexity so you didn't have to rewrite the application is that right? >> Right, so you know when Vertica ships it's software, you don't get a specific version for Pure or AWS, it's all in one package, and then when you configure it, it knows oh okay well, I'm just pointed at the, you know this port, on the Pure storage Flash Blade, and it just works. >> CB what's your data team look like? How is it evolving? You know a lot of customers I talked to they complain that they struggled to get value out of the data and they don't have the expertise, what does your team look like? How is it, is it changing or did the pandemic change things at all? I wonder if you could bring us up to date on that? >> Yeah but in some ways Microfocus has an advantage in that it's such a widely dispersed across the world company you know it's headquartered in the UK, but I deal with people I'm in the Bay Area, we have people in Mexico, Romania, India. >> Okay enough >> All over the place yeah all over the place. So when this started, it was actually a bigger project it got scaled back, it was almost to the point where it was going to be cut. Okay, but then we said, well let's try to do almost a skunkworks type of thing with reduced staff. And so we're just like a hand. You could count the number of key people on this on one hand. But we got it all together, and it's been a traumatic transformation for the company. Now there's, it's one approval and admiration from the highest echelons of this company that, hey this is really providing value. And the company is starting to get views into their business that they didn't have before. >> That's awesome, I mean, I've watched Microfocus for years. So to me they've always had a, their part of their DNA is private equity I mean they're sharp investors, they do great M and A >> CB: Yeah >> They know how to drive value and they're doing modern M and A, you know, we've seen what they what wait, what they did with SUSE, obviously driving value out of Vertica, they've got a really, some sharp financial people there. So that's they must have loved the the Skunkworks, fast ROI you know, small denominator, big numerator. (laughing) >> Well I think that in this case, smaller is better when you're doing development. You know it's a two-minute cooks type of thing and if you've got people who know what they're doing, you know I've got a lot of experience with Vertica, I've been on the advisory board for Vertica for a long time. >> Right And you know I was able to learn from people who had already, we're like the second or third company to do a Pure Flash Blade Vertica installation, but some of the best companies after they've already done it we are members of the advisory board also. So I learned from the best, and we were able to get this thing up and running quickly and we've got you know, a lot of other, you know handful of other key people who know how to write SQL and so forth to get this up and running quickly. >> Yeah so I mean, look it Pure is a fit I mean I sound like a fan boy, but Pure is all about simplicity, so is object. So that means you don't have to ra, you know worry about wrangling storage and worrying about LANs and all that other nonsense and file names but >> I have burned by hardware in the past you know, where oh okay they built into a price and so they cheap out on stuff like fans or other things in these components fail and the whole thing goes down, but this hardware is super good quality. And so I'm happy with the quality of that we're getting. >> So CB last question. What's next for you? Where do you want to take this initiative? >> Well we are in the process now of, we're when, so I designed a system to combine the best of the Kimball approach to data warehousing and the inland approach okay. And what we do is we bring over all the data we've got and we put it into a pristine staging layer. Okay like I said it's a, because it's append-only, it's essentially a log of all the transactions that are happening in this company, just as they appear okay. And then from the Kimball side of things we're designing the data marts now. So that's what the end users actually interact with. So we're taking the, we're examining the transactional systems to say, how are these business objects created? What's the logic there and we're recreating those logical models in Vertica. So we've done a handful of them so far, and it's working out really well. So going forward we've got a lot of work to do, to create just about every object that the company needs. >> CB you're an awesome guest really always a pleasure talking to you and >> Thank you. >> congratulations and good luck going forward stay safe. >> Thank you, you too Dave. >> All right thank you. And thank you for watching the Convergence of File and Object. This is Dave Vellante for theCUBE. (soft music)

>>Welcome to the convergence of file and object, a special program made possible by pure storage and co-created with the cube we're running. What I would call a little mini series and we're exploring the conversions of file and object storage. What are the key trends? Why would you want to converge file and object? What are the use cases and architectural considerations and importantly, what are the business drivers of U F F O so-called unified fast file and object in this program, you'll hear from Matt Burr, who was the GM of pure flash blade business. And then we'll bring in the perspectives of a solutions architect, Garrett who's from CDW, and then the analyst angle with Scott St. Claire of the enterprise strategy group ESG. And then we'll wrap with a really interesting technical conversation with Chris and bond CB bond, who is a lead data architect at Microfocus. And he's got a really cool use case to share with us. So sit back and enjoy the pros.

we're running what i would call a little mini series and we're exploring the convergence of file and object storage what are the key trends why would you want to converge file an object what are the use cases and architectural considerations and importantly what are the business drivers of uffo so-called unified fast file and object in this program you'll hear from matt burr who is the gm of pure's flashblade business and then we'll bring in the perspectives of a solutions architect garrett belsner who's from cdw and then the analyst angle with scott sinclair of the enterprise strategy group esg he'll share some cool data on our power panel and then we'll wrap with a really interesting technical conversation with chris bond cb bond who is a lead data architect at microfocus and he's got a really cool use case to share with us so sit back and enjoy the program from around the globe it's thecube presenting the convergence of file and object brought to you by pure storage we're back with the convergence of file and object a special program made possible by pure storage and co-created with the cube so in this series we're exploring that convergence between file and object storage we're digging into the trends the architectures and some of the use cases for unified fast file and object storage uffo with me is matt burr who's the vice president and general manager of flashblade at pure storage hello matt how you doing i'm doing great morning dave how are you good thank you hey let's start with a little 101 you know kind of the basics what is unified fast file and object yeah so look i mean i think you got to start with first principles talking about the rise of unstructured data so um when we think about unstructured data you sort of think about the projections 80 of data by 2025 is going to be unstructured data whether that's machine generated data or um you know ai and ml type workloads uh you start to sort of see this um i don't want to say it's a boom uh but it's sort of a renaissance for unstructured data if you will we move away from you know what we've traditionally thought of as general purpose nas and and file shares to you know really things that focus on uh fast object taking advantage of s3 cloud native applications that need to integrate with applications on site um you know ai workloads ml workloads tend to look to share data across you know multiple data sets and you really need to have a platform that can deliver both highly performant and scalable fast file and object from one system so talk a little bit more about some of the drivers that you know bring forth that need to unify file an object yeah i mean look you know there's a there's there's a real challenge um in managing you know bespoke uh bespoke infrastructure or architectures around general purpose nas and daz etc so um if you think about how a an architect sort of looks at an application they might say well okay i need to have um you know fast daz storage proximal to the application um but that's going to require a tremendous amount of dams which is a tremendous amount of drives right hard drives are you know historically pretty pretty pretty unwieldy to manage because you're replacing them relatively consistently at multi-petabyte scale um so you start to look at things like the complexity of daz you start to look at the complexity of general purpose nas and you start to just look at quite frankly something that a lot of people don't really want to talk about anymore but actual data center space right like consolidation matters the ability to take you know something that's the size of a microwave like a modern flash blade or a modern um you know uffo device uh replaces something that might be you know the size of three or four or five refrigerators so matt what why is is now the right time for this i mean for years nobody really paid much attention to object s3 already obviously changed you know that course most of the world's data is still stored in file formats and you get there with nfs or smb why is now the time to think about unifying object and file well because we're moving to things like a contactless society um you know the the things that we're going to do are going to just require a tremendous amount more compute power network um and quite frankly storage throughput and you know i can give you two sort of real primary examples here right you know warehouses are being you know taken over by robots if you will um it's not a war it's a it's a it's sort of a friendly advancement in you know how do i how do i store a box in a warehouse and you know we have we have a customer who focuses on large sort of big box distribution warehousing and you know a box that carried a an object two weeks ago might have a different box size two weeks later well that robot needs to know where the space is in the data center in order to put it but also needs to be able to process hey i don't want to put the thing that i'm going to access the most in the back of the warehouse i'm going to put that thing in the front of the warehouse all of those types of data you know sort of real time you can think of the robot as almost an edge device is processing in real time unstructured data in its object right so it's sort of the emergence of these new types of workloads and i give you the opposite example the other end of the spectrum is ransomware right you know today you know we'll talk to customers and they'll say quite commonly hey if you know anybody can sell me a backup device i need something that can restore quickly um if you had the ability to restore something in 270 terabytes an hour or 250 terabytes an hour uh that's much faster when you're dealing with a ransomware attack you want to get your data back quickly you know so i want to add i was going to ask you about that later but since you brought it up what is the right i guess call it architecture for for for ransomware i mean how and explain like how unified object and file which appointment i get the fast recovery but how how would you recommend a customer uh go about architecting a ransomware proof you know system yeah well you know with with flashblade and and with flasharray there's an actual feature called called safe mode and that safe mode actually protects uh the snapshots and and the data from uh sort of being a part of the of the ransomware event and so if you're in a type of ransomware situation like this you're able to leverage safe mode and you say okay what happens in a ransomware attack is you can't get access to your data and so you know the bad guy the perpetrator is basically saying hey i'm not going to give you access to your data until you pay me you know x in bitcoin or whatever it might be right um with with safe mode those snapshots are actually protected outside of the ransomware blast zone and you can bring back those snapshots because what's your alternative if you're not doing something like that your alternative is either to pay and unlock your data or you have to start retouring restoring excuse me from tape or slow disk that could take you days or weeks to get your data back so leveraging safe mode um you know in either the flash for the flash blade product uh is a great way to go about architecting against ransomware i got to put my my i'm thinking like a customer now so safe mode so that's an immutable mode right can't change the data um is it can can an administrator go in and change that mode can you turn it off do i still need an air gap for example what would you recommend there yeah so there there are still um uh you know sort of our back or roll back role-based access control policies uh around who can access that safe mode and who can right okay so uh anyway subject for a different day i want to i want to actually bring up uh if you don't object a topic that i think used to be really front and center and it now be is becoming front and center again i mean wikibon just produced a research note forecasting the future of flash and hard drives and those of you who follow us know we've done this for quite some time and you can if you could bring up the chart here you you could and we see this happening again it was originally we forecast the the the death of of quote-unquote high spin speed disc drives which is kind of an oxymoron but you can see on here on this chart this hard disk had a magnificent journey but they peaked in volume in manufacturing volume in 2010 and the reason why that is is so important is that volumes now are steadily dropping you can see that and we use wright's law to explain why this is a problem and wright's law essentially says that as you your cumulative manufacturing volume doubles your cost to manufacture decline by a constant percentage now i won't go too much detail on that but suffice it to say that flash volumes are growing very rapidly hdd volumes aren't and so flash because of consumer volumes can take advantage of wright's law and that constant reduction and that's what's really important for the next generation which is always more expensive to build uh and so this kind of marks the beginning of the end matt what do you think what what's the future hold for spinning disc in your view uh well i can give you the answer on two levels on a personal level uh it's why i come to work every day uh you know the the eradication or or extinction of an inefficient thing um you know i like to say that uh inefficiency is the bane of my existence uh and i think hard drives are largely inefficient and i'm willing to accept the sort of long-standing argument that um you know we've seen this transition in block right and we're starting to see it repeat itself in in unstructured data and i'm going to accept the argument that cost is a vector here and it most certainly is right hdds have been considerably cheaper uh than than than flash storage um you know even to this day uh you know up up to this point right but we're starting to approach the point where you sort of reach a a 3x sort of um you know differentiator between the cost of an hdd and an std and you know that really is that point in time when uh you begin to pick up a lot of volume and velocity and so you know that tends to map directly to you know what you're seeing here which is you know a a slow decline uh which i think is going to become even more rapid kind of probably starting around next year um where you start to see sds excuse me ssds uh you know really replacing hdds uh at a much more rapid clip particularly on the unstructured data side and it's largely around cost the the workloads that we talked about robots and warehouses or you know other types of advanced machine learning and artificial intelligence type applications and workflows you know they require a degree of performance that a hard drive just can't deliver we are we are seeing sort of the um creative innovative uh disruption of an entire industry right before our eyes it's a fun thing to live through yeah and and we would agree i mean it doesn't the premise there is that it doesn't have to be less expensive we think it will be by you know the second half or early second half of this decade but even if it's a we think around a 3x delta the value of of ssd relative to spinning disk is going to overwhelm just like with your laptop you know it got to the point where you said why would i ever have a spinning disc in my laptop we see the same thing happening here um and and so and we're talking about you know raw capacity you know put in compression and d-dupe and everything else that you really can't do with spinning discs because of the performance issues you can do with flash okay let's come back to uffo can we dig into the challenges specifically that that this solves for customers give me give us some examples yeah so you know i mean if we if we think about the examples um you know the the robotic one um i think is is is the one that i think is the marker for you know kind of of of the the modern side of of of what we see here um but what we're you know what we're what we're seeing from a trend perspective which you know not everybody's deploying robots right um you know there's there's many companies that are you know that aren't going to be in either the robotic business uh or or even thinking about you know sort of future type oriented type things but what they are doing is green field applications are being built on object um generally not on not on file and and not on block and so you know the rise of of object as sort of the the sort of let's call it the the next great protocol for um you know for uh for for modern workloads right this is this is that that modern application coming to the forefront and that could be anything from you know financial institutions you know right down through um you we've even see it and seen it in oil and gas uh we're also seeing it across across healthcare uh so you know as as as companies take the opportunity as industries to take this opportunity to modernize you know they're modernizing not on things that are are leveraging you know um you know sort of archaic disk technology they're they're they're really focusing on on object but they still have file workflows that they need to that they need to be able to support and so having the ability to be able to deliver those things from one device in a capacity orientation or a performance orientation uh while at the same time dramatically simplifying uh the overall administration of your environment both physically and non-physically is a key driver so the great thing about object is it's simple it's a kind of a get put metaphor um it's it scales out you know because it's got metadata associated with the data uh and and it's cheap uh the drawback is you don't necessarily associate it with high performance and and and as well most applications don't you know speak in that language they speak in the language of file you know or as you mentioned block so i i see real opportunities here if i have some some data that's not necessarily frequently accessed you know every day but yet i want to then whether end of quarter or whatever it is i want to i want to or machine learning i want to apply some ai to that data i want to bring it in and then apply a file format uh because for performance reasons is that right maybe you could unpack that a little bit yeah so um you know we see i mean i think you described it well right um but i don't think object necessarily has to be slow um and nor does it have to be um you know because when you think about you brought up a good point with metadata right being able to scale to a billions of objects being able to scale to billions of objects excuse me is of value right um and i think people do traditionally associate object with slow but it's not necessarily slow anymore right we we did a sort of unofficial survey of of of our of our customers and our employee base and when people described object they thought of it as like law firms and storing a word doc if you will um and that that's just you know i think that there's a lack of understanding or a misnomer around what modern what modern object has become and perform an object particularly at scale when we're talking about billions of objects you know that's the next frontier right um is it at pace performance wise with you know the other protocols no uh but it's making leaps and grounds so you talked a little bit more about some of the verticals that you see i mean i think when i think of financial services i think transaction processing but of course they have a lot of tons of unstructured data are there any patterns you're seeing by by vertical market um we're you know we're not that's the interesting thing um and you know um as a as a as a as a company with a with a block heritage or a block dna those patterns were pretty easy to spot right there were a certain number of databases that you really needed to support oracle sql some postgres work et cetera then kind of the modern databases around cassandra and things like that you knew that there were going to be vmware environments you know you could you could sort of see the trends and where things were going unstructured data is such a broader horizontal thing right so you know inside of oil and gas for example you have you know um you have specific applications and bespoke infrastructures for those applications um you know inside of media entertainment you know the same thing the the trend that we're seeing the commonality that we're seeing is the modernization of you know object as a starting point for all the all the net new workloads within within those industry verticals right that's the most common request we see is what's your object roadmap what's your you know what's your what's your object strategy you know where do you think where do you think object is going so um there isn't any um you know sort of uh there's no there's no path uh it's really just kind of a wide open field in front of us with common requests across all industries so the amazing thing about pure just as a kind of a little you know quasi you know armchair historian the industry is pure was really the only company in many many years to be able to achieve escape velocity break through a billion dollars i mean three part couldn't do it isilon couldn't do it compellent couldn't do it i could go on but pure was able to achieve that as an independent company and so you become a leader you look at the gartner magic quadrant you're a leader in there i mean if you've made it this far you've got to have some chops and so of course it's very competitive there are a number of other storage suppliers that have announced products that unify object and file so i'm interested in how pure differentiates why pure um it's a great question um and it's one that uh you know having been a long time puritan uh you know i take pride in answering um and it's actually a really simple answer um it's it's business model innovation and technology right the the technology that goes behind how we do what we do right and i don't mean the product right innovation is product but having a better support model for example um or having on the business model side you know evergreen storage right where we sort of look at your relationship to us as a subscription right um you know we're going to sort of take the thing that that you've had and we're going to modernize that thing in place over time such that you're not rebuying that same you know terabyte or you know petabyte of storage that you've that you that you've paid for over time so um you know sort of three legs of the stool uh that that have made you know pure clearly differentiated i think the market has has recognized that um you're right it's it's hard to break through to a billion dollars um but i look forward to the day that you know we we have two billion dollar products and i think with uh you know that rise in in unstructured data growing to 80 by 2025 and you know the massive transition that you know you guys have noted in in in your hdd slide i think it's a huge opportunity for us on you know the other unstructured data side of the house you know the other thing i'd add matt i've talked to cause about this is is it's simplicity first i've asked them why don't you do this why don't you do it and the answer is always the same is that adds complexity and we we put simplicity for the customer ahead of everything else and i think that served you very very well what about the economics of of unified file an object i mean if you bring in additional value presumably there's a there there's a cost to that but there's got to be also a business case behind it what kind of impact have you seen uh with customers yeah i mean look i'll i'll i'll go back to something i mentioned earlier which is just the reclamation of floor space and power and cooling right um you know there's a you know there's people people people want to search for kind of the the sexier element if you will when it comes to looking at how we how you derive value from something but the reality is if you're reducing your power consumption by you know by by a material percentage power bills matter in big in big data centers um you know customers typically are are facing you know a paradigm of well i i want to go to the cloud but you know the clouds are not being more expensive than i thought it was going to be or you know i figured out what i can use in the cloud i thought it was going to be everything but it's not going to be everything so hybrid's where we're landing but i want to be out of the data center business and i don't want to have a team of 20 storage people to match you know to administer my storage um you know so there's sort of this this very tangible value around you know hey if i could manage um you know multiple petabytes with one full-time engineer uh because the system uh to yoran kaz's point was radically simpler to administer didn't require someone to be running around swapping drives all the time would that be a value the answer is yes 100 of the time right and then you start to look at okay all right well on the uffo side from a product perspective hey if i have to manage a you know bespoke environment for this application if i have to manage a bespoke environment for this application and a bespoke environment for this application and this book environment for this application i'm managing four different things and can i actually share data across those four different things there's ways to share data but most customers it just gets too complex how do you even know what your what your gold.master copy is of data if you have it in four different places or you try to have it in four different places and it's four different siloed infrastructures so when you get to the sort of the side of you know how do we how do you measure value in uffo it's actually being able to have all of that data concentrated in one place so that you can share it from application to application got it i'm interested we use a couple minutes left i'm interested in the the update on flashblade you know generally but also i have a specific question i mean look getting file right is hard enough uh you just announced smb support for flashblade i'm interested in you know how that fits in i think it's kind of obvious with file and object converging but give us the update on on flashblade and maybe you could address that specific question yeah so um look i mean we're we're um you know tremendously excited about the growth of flashblade uh you know we we we found workloads we never expected to find um you know the rapid restore workload was one that was actually brought to us from from from a customer actually and has become you know one of our one of our top two three four you know workloads so um you know we're really happy with the trend we've seen in it um and you know mapping back to you know thinking about hdds and ssds you know we're well on a path to building a billion dollar business here so you know we're very excited about that um but to your point you know you don't just snap your fingers and get there right um you know we've learned that doing file and object uh is is harder than block um because there's more things that you have to go do for one you're basically focused on three protocols s b nfs and s3 not necessarily in that order um but to your point about smb uh you know we we are uh on the path through to releasing um you know smb uh full full native smb support in in the system that will allow us to uh service customers we have a limitation with some customers today where they'll have an s b portion of their nfs workflow um and we do great on the nfs side um but you know we didn't we didn't have the ability to plug into the s p component of their workflow so that's going to open up a lot of opportunity for us um on on that front um and you know we continue to you know invest significantly across the board in in areas like security which is you know become more than just a hot button you know today security's always been there but it feels like it's blazing hot today um and so you know going through the next couple years we'll be looking at uh you know developing some some um you know pretty material security elements of the product as well so uh well on a path to a billion dollars is the net on that and uh you know we're we're fortunate to have have smb here and we're looking forward to introducing that to to those customers that have you know nfs workloads today with an s p component yeah nice tailwind good tam expansion strategy matt thanks so much really appreciate you coming on the program we appreciate you having us and uh thanks much dave good to see you [Music] okay we're back with the convergence of file and object in a power panel this is a special content program made possible by pure storage and co-created with the cube now in this series what we're doing is we're exploring the coming together of file and object storage trying to understand the trends that are driving this convergence the architectural considerations that users should be aware of and which use cases make the most sense for so-called unified fast file in object storage and with me are three great guests to unpack these issues garrett belsner is the data center solutions architect he's with cdw scott sinclair is a senior analyst at enterprise strategy group he's got deep experience on enterprise storage and brings that independent analyst perspective and matt burr is back with us gentlemen welcome to the program thank you hey scott let me let me start with you uh and get your perspective on what's going on the market with with object the cloud a huge amount of unstructured data out there that lives in files give us your independent view of the trends that you're seeing out there well dave you know where to start i mean surprise surprise date is growing um but one of the big things that we've seen is we've been talking about data growth for what decades now but what's really fascinating is or changed is because of the digital economy digital business digital transformation whatever you call it now people are not just storing data they actually have to use it and so we see this in trends like analytics and artificial intelligence and what that does is it's just increasing the demand for not only consolidation of massive amounts of storage that we've seen for a while but also the demand for incredibly low latency access to that storage and i think that's one of the things that we're seeing that's driving this need for convergence as you put it of having multiple protocols consolidated onto one platform but also the need for high performance access to that data thank you for that a great setup i got like i wrote down three topics that we're going to unpack as a result of that so garrett let me let me go to you maybe you can give us the perspective of what you see with customers is is this is this like a push where customers are saying hey listen i need to converge my file and object or is it more a story where they're saying garrett i have this problem and then you see unified file and object as a solution yeah i think i think for us it's you know taking that consultative approach with our customers and really kind of hearing pain around some of the pipelines the way that they're going to market with data today and kind of what are the problems that they're seeing we're also seeing a lot of the change driven by the software vendors as well so really being able to support a disaggregated design where you're not having to upgrade and maintain everything as a single block has really been a place where we've seen a lot of customers pivot to where they have more flexibility as they need to maintain larger volumes of data and higher performance data having the ability to do that separate from compute and cache and those other layers are is really critical so matt i wonder if if you could you know follow up on that so so gary was talking about this disaggregated design so i like it you know distributed cloud etc but then we're talking about bringing things together in in one place right so square that circle how does this fit in with this hyper-distributed cloud edge that's getting built out yeah you know i mean i i could give you the easy answer on that but i could also pass it back to garrett in the sense that you know garrett maybe it's important to talk about um elastic and splunk and some of the things that you're seeing in in that world and and how that i think the answer to dave's question i think you can give you can give a pretty qualified answer relative what your customers are seeing oh that'd be great please yeah absolutely no no problem at all so you know i think with um splunk kind of moving from its traditional design and classic design whatever you want you want to call it up into smart store um that was kind of one of the first that we saw kind of make that move towards kind of separating object out and i think you know a lot of that comes from their own move to the cloud and updating their code to basically take advantage of object object in the cloud uh but we're starting to see you know with like vertica eon for example um elastic other folks taking that same type of approach where in the past we were building out many 2u servers we were jamming them full of uh you know ssds and nvme drives that was great but it doesn't really scale and it kind of gets into that same problem that we see with you know hyper convergence a little bit where it's you know you're all you're always adding something maybe that you didn't want to add um so i think it you know again being driven by software is really kind of where we're seeing the world open up there but that whole idea of just having that as a hub and a central place where you can then leverage that out to other applications whether that's out to the edge for machine learning or ai applications to take advantage of it i think that's where that convergence really comes back in but i think like scott mentioned earlier it's really folks are now doing things with the data where before i think they were really storing it trying to figure out what are we going to actually do with it when we need to do something with it so this is making it possible yeah and dave if i could just sort of tack on to the end of garrett's answer there you know in particular vertica with neon mode the ability to leverage sharded subclusters give you um you know sort of an advantage in terms of being able to isolate performance hot spots you an advantage to that is being able to do that on a flashblade for example so um sharded subclusters allow you to sort of say i'm you know i'm going to give prioritization to you know this particular element of my application and my data set but i can still share those share that data across those across those subclusters so um you know as you see you know vertica advance with eon mode or you see splunk advance with with smart store you know these are all sort of advancements that are you know it's a chicken in the egg thing um they need faster storage they need you know sort of a consolidated data storage data set um and and that's what sort of allows these things to drive forward yeah so vertica eon mode for those who don't know it's the ability to separate compute and storage and scale independently i think i think vertica if they're if they're not the only one they're one of the only ones i think they might even be the only one that does that in the cloud and on-prem and that sort of plays into this distributed you know nature of this hyper-distributed cloud i sometimes call it and and i'm interested in the in the data pipeline and i wonder scott if we could talk a little bit about that maybe we're unified object and file i mean i'm envisioning this this distributed mesh and then you know uffo is sort of a node on that that i i can tap when i need it but but scott what are you seeing as the state of infrastructure as it relates to the data pipeline and the trends there yeah absolutely dave so when i think data pipeline i immediately gravitate to analytics or or machine learning initiatives right and so one of the big things we see and this is it's an interesting trend it seems you know we continue to see increased investment in ai increased interest and people think and as companies get started they think okay well what does that mean well i got to go hire a data scientist okay well that data scientist probably needs some infrastructure and what they end what often happens in these environments is where it ends up being a bespoke environment or a one-off environment and then over time organizations run into challenges and one of the big challenges is the data science team or people whose jobs are outside of it spend way too much time trying to get the infrastructure to to keep up with their demands and predominantly around data performance so one of the one of the ways organizations that especially have artificial intelligence workloads in production and we found this in our research have started mitigating that is by deploying flash all across the data pipeline we have we have data on this sorry interrupt but yeah if you could bring up that that chart that would be great um so take us through this uh uh scott and share with us what we're looking at here yeah absolutely so so dave i'm glad you brought this up so we did this study um i want to say late last year uh one of the things we looked at was across artificial intelligence environments now one thing that you're not seeing on this slide is we went through and we asked all around the data pipeline and we saw flash everywhere but i thought this was really telling because this is around data lakes and when when or many people think about the idea of a data lake they think about it as a repository it's a place where you keep maybe cold data and what we see here is especially within production environments a pervasive use of flash storage so i think that 69 of organizations are saying their data lake is mostly flash or all flash and i think we have zero percent that don't have any flash in that environment so organizations are finding out that they that flash is an essential technology to allow them to harness the value of their data so garrett and then matt i wonder if you could chime in as well we talk about digital transformation and i sometimes call it you know the coveted forced march to digital transformation and and i'm curious as to your perspective on things like machine learning and the adoption and scott you may have a perspective on this as well you know we had to pivot we had to get laptops we had to secure the end points you know and vdi those became super high priorities what happened to you know injecting ai into my applications and and machine learning did that go in the back burner was that accelerated along with the need to digitally transform garrett i wonder if you could share with us what you saw with with customers last year yeah i mean i think we definitely saw an acceleration um i think folks are in in my market are still kind of figuring out how they inject that into more of a widely distributed business use case but again this data hub and allowing folks to now take advantage of this data that they've had in these data lakes for a long time i agree with scott i mean many of the data lakes that we have were somewhat flash accelerated but they were typically really made up of you know large capacity slower spinning near-line drive accelerated with some flash but i'm really starting to see folks now look at some of those older hadoop implementations and really leveraging new ways to look at how they consume data and many of those redesigned customers are coming to us wanting to look at all flash solutions so we're definitely seeing it we're seeing an acceleration towards folks trying to figure out how to actually use it in more of a business sense now or before i feel it goes a little bit more skunk works kind of people dealing with uh you know in a much smaller situation maybe in the executive offices trying to do some testing and things scott you're nodding away anything you can add in here yeah so first off it's great to get that confirmation that the stuff we're seeing in our research garrett's seeing you know out in the field and in the real world um but you know as it relates to really the past year it's been really fascinating so one of the things we study at esg is i.t buying intentions what are things what are initiatives that companies plan to invest in and at the beginning of 2020 we saw a heavy interest in machine learning initiatives then you transition to the middle of 2020 in the midst of covid some organizations continued on that path but a lot of them had the pivot right how do we get laptops to everyone how do we continue business in this new world well now as we enter into 2021 and hopefully we're coming out of this uh you know the pandemic era um we're getting into a world where organizations are pivoting back towards these strategic investments around how do i maximize the usage of data and actually accelerating those because they've seen the importance of of digital business initiatives over the past year yeah matt i mean when we exited 2019 we saw a narrowing of experimentation and our premise was you know that that organizations are going to start now operationalizing all their digital transformation experiments and and then we had a you know 10 month petri dish on on digital so what do you what are you seeing in this regard a 10 month petri dish is an interesting way to interesting way to describe it um you know we saw another there's another there's another candidate for pivot in there around ransomware as well right um you know security entered into the mix which took people's attention away from some of this as well i mean look i'd like to bring this up just a level or two um because what we're actually talking about here is progress right and and progress isn't is an inevitability um you know whether it's whether whether you believe that it's by 2025 or you or you think it's 2035 or 2050 it doesn't matter we're on a forced march to the eradication of disk and that is happening in many ways uh you know in many ways um due to some of the things that garrett was referring to and what scott was referring to in terms of what are customers demands for how they're going to actually leverage the data that they have and that brings me to kind of my final point on this which is we see customers in three phases there's the first phase where they say hey i have this large data store and i know there's value in there i don't know how to get to it or i have this large data store and i've started a project to get value out of it and we failed those could be customers that um you know marched down the hadoop path early on and they they got some value out of it um but they realized that you know hdfs wasn't going to be a modern protocol going forward for any number of reasons you know the first being hey if i have gold.master how do i know that i have gold.4 is consistent with my gold.master so data consistency matters and then you have the sort of third group that says i have these large data sets i know how to extract value from them and i'm already on to the verticas the elastics you know the splunks etc um i think those folks are the folks that that ladder group are the folks that kept their their their projects going because they were already extracting value from them the first two groups we we're seeing sort of saying the second half of this year is when we're going to begin really being picking up on these on these types of initiatives again well thank you matt by the way for for hitting the escape key because i think value from data really is what this is all about and there are some real blockers there that i kind of want to talk about you mentioned hdfs i mean we were very excited of course in the early days of hadoop many of the concepts were profound but at the end of the day it was too complicated we've got these hyper-specialized roles that are that are you know serving the business but it still takes too long it's it's too hard to get value from data and one of the blockers is infrastructure that the complexity of that infrastructure really needs to be abstracted taking up a level we're starting to see this in in cloud where you're seeing some of those abstraction layers being built from some of the cloud vendors but more importantly a lot of the vendors like pew are saying hey we can do that heavy lifting for you uh and we you know we have expertise in engineering to do cloud native so i'm wondering what you guys see uh maybe garrett you could start us off and other students as some of the blockers uh to getting value from data and and how we're going to address those in the coming decade yeah i mean i i think part of it we're solving here obviously with with pure bringing uh you know flash to a market that traditionally was utilizing uh much slower media um you know the other thing that i that i see that's very nice with flashblade for example is the ability to kind of do things you know once you get it set up a blade at a time i mean a lot of the things that we see from just kind of more of a you know simplistic approach to this like a lot of these teams don't have big budgets and being able to kind of break them down into almost a blade type chunk i think has really kind of allowed folks to get more projects and and things off the ground because they don't have to buy a full expensive system to run these projects so that's helped a lot i think the wider use cases have helped a lot so matt mentioned ransomware you know using safe mode as a place to help with ransomware has been a really big growth spot for us we've got a lot of customers very interested and excited about that and the other thing that i would say is bringing devops into data is another thing that we're seeing so kind of that push towards data ops and really kind of using automation and infrastructure as code as a way to now kind of drive things through the system the way that we've seen with automation through devops is really an area we're seeing a ton of growth with from a services perspective guys any other thoughts on that i mean we're i'll tee it up there we are seeing some bleeding edge which is somewhat counterintuitive especially from a cost standpoint organizational changes at some some companies uh think of some of the the the internet companies that do uh music uh for instance and adding podcasts etc and those are different data products we're seeing them actually reorganize their data architectures to make them more distributed uh and actually put the domain heads the business heads in charge of the the data and the data pipeline and that is maybe less efficient but but it's again some of these bleeding edge what else are you guys seeing out there that might be yes some harbingers of the next decade uh i'll go first um you know i think specific to um the the construct that you threw out dave one of the things that we're seeing is um you know the the application owner maybe it's the devops person but it's you know maybe it's it's it's the application owner through the devops person they're they're becoming more technical in their understanding of how infrastructure um interfaces with their with their application i think um you know what what we're seeing on the flashblade side is we're having a lot more conversations with application people than um just i.t people it doesn't mean that the it people aren't there the it people are still there for sure they have to deliver the service etc um but you know the days of of i.t you know building up a catalog of services and a business owner subscribing to one of those services you know picking you know whatever sort of fits their need um i don't think that constru i think that's the construct that changes going forward the application owner is becoming much more prescriptive about what they want the infrastructure to fit how they want the infrastructure to fit into their application and that's a big change and and for for um you know certainly folks like like garrett and cdw um you know they do a good job with this being able to sort of get to the application owner and bring those two sides together there's a tremendous amount of value there for us it's been a little bit of a retooling we've traditionally sold to the i.t side of the house and um you know we've had to teach ourselves how to go talk the language of of applications so um you know i think you pointed out a good a good a good construct there and and you know that that application owner taking playing a much bigger role in what they're expecting uh from the performance of it infrastructure i think is is is a key is a key change interesting i mean that definitely is a trend that's put you guys closer to the business where the the infrastructure team is is serving the business as opposed to sometimes i talk to data experts and they're frustrated uh especially data owners or or data product builders who are frustrated that they feel like they have to beg beg the the data pipeline team to get you know new data sources or get data out how about the edge um you know maybe scott you can kick us off i mean we're seeing you know the emergence of edge use cases ai inferencing at the edge a lot of data at the edge what are you seeing there and and how does this unified object i'll bring us back to that and file fit wow dave how much time do we have um two minutes first of all scott why don't you why don't you just tell everybody what the edge is yeah you got it figured out all right how much time do you have matt at the end of the day and that that's that's a great question right is if you take a step back and i think it comes back today of something you mentioned it's about extracting value from data and what that means is when you extract value from data what it does is as matt pointed out the the influencers or the users of data the application owners they have more power because they're driving revenue now and so what that means is from an i.t standpoint it's not just hey here are the services you get use them or lose them or you know don't throw a fit it is no i have to i have to adapt i have to follow what my application owners mean now when you bring that back to the edge what it means is is that data is not localized to the data center i mean we just went through a nearly 12-month period where the entire workforce for most of the companies in this country had went distributed and business continued so if business is distributed data is distributed and that means that means in the data center that means at the edge that means that the cloud that means in all other places in tons of places and what it also means is you have to be able to extract and utilize data anywhere it may be and i think that's something that we're going to continue to and continue to see and i think it comes back to you know if you think about key characteristics we've talked about things like performance and scale for years but we need to start rethinking it because on one hand we need to get performance everywhere but also in terms of scale and this ties back to some of the other initiatives and getting value from data it's something i call that the massive success problem one of the things we see especially with with workloads like machine learning is businesses find success with them and as soon as they do they say well i need about 20 of these projects now all of a sudden that overburdens it organizations especially across across core and edge and cloud environments and so when you look at environments ability to meet performance and scale demands wherever it needs to be is something that's really important you know so dave i'd like to um just sort of tie together sort of two things that um i think that i heard from scott and garrett that i think are important and it's around this concept of scale um you know some of us are old enough to remember the day when kind of a 10 terabyte blast radius was too big of a blast radius for people to take on or a terabyte of storage was considered to be um you know an exemplary budget environment right um now we sort of think as terabytes kind of like we used to think of as gigabytes in some ways um petabyte like you don't have to explain anybody what a petabyte is anymore um and you know what's on the horizon and it's not far are our exabyte type data set workloads um and you start to think about what could be in that exabyte of data we've talked about how you extract that value we've talked about sort of um how you start but if the scale is big not everybody's going to start at a petabyte or an exabyte to garrett's point the ability to start small and grow into these products or excuse me these projects i think a is a really um fundamental concept here because you're not going to just go by i'm going to kick off a five petabyte project whether you do that on disk or flash it's going to be expensive right but if you could start at a couple hundred terabytes not just as a proof of concept but as something that you know you could get predictable value out of that then you could say hey this either scales linearly or non-linearly in a way that i can then go map my investments to how i can go dig deeper into this that's how all of these things are gonna that's how these successful projects are going to start because the people that are starting with these very large you know sort of um expansive you know greenfield projects at multi-petabyte scale it's gonna be hard to realize near-term value excellent we gotta wrap but but garrett i wonder if you could close when you look forward you talk to customers do you see this unification of of file and object is it is this an evolutionary trend is it something that is that that is that is that is going to be a lever that customers use how do you see it evolving over the next two three years and beyond yeah i mean i think from our perspective i mean just from what we're seeing from the numbers within the market the amount of growth that's happening with unstructured data is really just starting to finally really kind of hit this data deluge or whatever you want to call it that we've been talking about for so many years it really does seem to now be becoming true as we start to see things scale out and really folks settle into okay i'm going to use the cloud to to start and maybe train my models but now i'm going to get it back on prem because of latency or security or whatever the the um decision points are there this is something that is not going to slow down and i think you know folks like pure having the ability to have the tools that they give us um to use and bring to market with our customers are really key and critical for us so i see it as a huge growth area and a big focus for us moving forward guys great job unpacking a topic that you know it's covered a little bit but i think we we covered some ground that is uh that is new and so thank you so much for those insights and that data really appreciate your time thanks steve thanks yeah thanks dave okay and thank you for watching the convergence of file and object keep it right there right back after this short break innovation impact influence welcome to the cube disruptors developers and practitioners learn from the voices of leaders who share their personal insights from the hottest digital events around the globe enjoy the best this community has to offer on the cube your global leader in high-tech digital coverage [Music] okay now we're going to get the customer perspective on object and we'll talk about the convergence of file and object but really focusing on the object piece this is a content program that's being made possible by pure storage and it's co-created with the cube christopher cb bond is here he's a lead architect for microfocus the enterprise data warehouse and principal data engineer at microfocus cb welcome good to see you thanks dave good to be here so tell us more about your role at microfocus it's a pan microfocus role of course we know the company is a multinational software firm and acquired the software assets of hp of course including vertica tell us where you fit yeah so microfocus is uh you know it's like i said wide worldwide uh company that uh sells a lot of software products all over the place to governments and so forth and um it also grows often by acquiring other companies so there is the problem of of integrating new companies and their data and so what's happened over the years is that they've had a a number of different discrete data systems so you've got this data spread all over the place and they've never been able to get a full complete introspection on the entire business because of that so my role was come in design a central data repository an enterprise data warehouse that all reporting could be generated against and so that's what we're doing and we selected vertica as the edw system and pure storage flashblade as the communal repository okay so you obviously had experience with with vertica in your in your previous role so it's not like you were starting from scratch but but paint a picture of what life was like before you embarked on this sort of consolidated a approach to your your data warehouse what was it just disparate data all over the place a lot of m a going on where did the data live right so again the data was all over the place including under people's desks in just dedicated you know their their own private uh sql servers it a lot of data in in um microfocus is run on sql server which has pros and cons because that's a great uh transactional database but it's not really good for analytics in my opinion so uh but a lot of stuff was running on that they had one vertica instance that was doing some select uh reporting wasn't a very uh powerful system and it was what they call vertica enterprise mode where had dedicated nodes which um had the compute and storage um in the same locus on each uh server okay so vertica eon mode is a whole new world because it separates compute from storage you mentioned eon mode uh and the ability to to to scale storage and compute independently we wanted to have the uh analytics olap stuff close to the oltp stuff right so that's why they're co-located very close to each other and so uh we could what's nice about this situation is that these s3 objects it's an s3 object store on the pure flash plate we could copy those over if we needed to uh aws and we could spin up um a version of vertica there and keep going it's it's like a tertiary dr strategy because we actually have a we're setting up a second flashblade vertica system geo-located elsewhere for backup and we can get into it if you want to talk about how the latest version of the pure software for the flashblade allows synchronization across network boundaries of those flash plays which is really nice because if uh you know there's a giant sinkhole opens up under our colo facility and we lose that thing then we just have to switch the dns and we were back in business off the dr and then if that one was to go we could copy those objects over to aws and be up and running there so we're feeling pretty confident about being able to weather whatever comes along so you're using the the pure flash blade as an object store um most people think oh object simple but slow uh not the case for you is that right not the case at all it's ripping um well you have to understand about vertica and the way it stores data it stores data in what they call storage containers and those are immutable okay on disk whether it's on aws or if you had a enterprise mode vertica if you do an update or delete it actually has to go and retrieve that object container from disk and it destroys it and rebuilds it okay which is why you don't you want to avoid updates and deletes with vertica because the way it gets its speed is by sorting and ordering and encoding the data on disk so it can read it really fast but if you do an operation where you're deleting or updating a record in the middle of that then you've got to rebuild that entire thing so that actually matches up really well with s3 object storage because it's kind of the same way uh it gets destroyed and rebuilt too okay so that matches up very well with vertica and we were able to design this system so that it's append only now we had some reports that were running in sql server okay uh which were taking seven days so we moved that to uh to vertica from sql server and uh we rewrote the queries which were which had been written in t sql with a bunch of loops and so forth and we were to get this is amazing it went from seven days to two seconds to generate this report which has tremendous value uh to the company because it would have to have this long cycle of seven days to get a new introspection in what they call their knowledge base and now all of a sudden it's almost on demand two seconds to generate it that's great and that's because of the way the data is stored and uh the s3 you asked about oh you know is it slow well not in that context because what happens really with vertica eon mode is that it can they have um when you set up your compute nodes they have local storage also which is called the depot it's kind of a cache okay so the data will be drawn from the flash and cached locally uh and that was it was thought when they designed that oh you know it's that'll cut down on the latency okay but it turns out that if you have your compute nodes close meaning minimal hops to the flashblade that you can actually uh tell vertica you know don't even bother caching that stuff just read it directly on the fly from the from the flashblade and the performance is still really good it depends on your situation but i know for example a major telecom company that uh uses the same topology as we're talking about here they did the same thing they just they just dropped the cache because the flash player was able to to deliver the the data fast enough so that's you're talking about that that's speed of light issues and just the overhead of of of switching infrastructure is that that gets eliminated and so as a result you can go directly to the storage array that's correct yeah it's it's like it's fast enough that it's it's almost as if it's local to the compute node uh but every situation is different depending on your uh your knees if you've got like a few tables that are heavily used uh then yeah put them um put them in the cash because that'll be probably a little bit faster but if you have a lot of ad hoc queries that are going on you know you may exceed the storage of the local cache and then you're better off having it uh just read directly from the uh from the flash blade got it look it pure's a fit i mean i sound like a fanboy but pure is all about simplicity so is object so that means you don't have to you know worry about wrangling storage and worrying about luns and all that other you know nonsense and and file i've been burned by hardware in the past you know where oh okay they're building to a price and so they cheap out on stuff like fans or other things and these these components fail and the whole thing goes down but this hardware is super super good quality and uh so i'm i'm happy with the quality that we're getting so cb last question what's next for you where do you want to take this uh this this initiative well we are in the process now of we um when so i i designed this system to combine the best of the kimball approach to data warehousing and the inland approach okay and what we do is we bring over all the data we've got and we put it into a pristine staging layer okay like i said it's uh because it's append only it's essentially a log of all the transactions that are happening in this company just they appear okay and then from the the kimball side of things we're designing the data marts now so that that's what the end users actually interact with and so we're we're taking uh the we're examining the transactional systems to say how are these business objects created what's what's the logic there and we're recreating those logical models in uh in vertica so we've done a handful of them so far and it's working out really well so going forward we've got a lot of work to do to uh create just about every object that that the company needs cb you're an awesome guest to really always a pleasure talking to you and uh thank you congratulations and and good luck going forward stay safe thank you [Music] okay let's summarize the convergence of file and object first i want to thank our guests matt burr scott sinclair garrett belsener and c.b bohn i'm your host dave vellante and please allow me to briefly share some of the key takeaways from today's program so first as scott sinclair of esg stated surprise surprise data's growing and matt burr he helped us understand the growth of unstructured data i mean estimates indicate that the vast majority of data will be considered unstructured by mid-decade 80 or so and obviously unstructured data is growing very very rapidly now of course your definition of unstructured data and that may vary across across a wide spectrum i mean there's video there's audio there's documents there's spreadsheets there's chat i mean these are generally considered unstructured data but of course they all have some type of structure to them you know perhaps it's not as strict as a relational database but there's certainly metadata and certain structure to these types of use cases that i just mentioned now the key to what pure is promoting is this idea of unified fast file and object uffo look object is great it's inexpensive it's simple but historically it's been less performant so good for archiving or cheap and deep types of examples organizations often use file for higher performance workloads and let's face it most of the world's data lives in file formats what pure is doing is bringing together file and object by for example supporting multiple protocols ie nfs smb and s3 s3 of course has really given new life to object over the past decade now the key here is to essentially enable customers to have the best of both worlds not having to trade off performance for object simplicity and a key discussion point that we've had on the program has been the impact of flash on the long slow death of spinning disk look hard disk drives they had a great run but hdd volumes they peaked in 2010 and flash as you well know has seen tremendous volume growth thanks to the consumption of flash in mobile devices and then of course its application into the enterprise and that's volume is just going to keep growing and growing and growing the price declines of flash are coming down faster than those of hdd so it's the writing's on the wall it's just a matter of time so flash is riding down that cost curve very very aggressively and hdd has essentially become you know a managed decline business now by bringing flash to object as part of the flashblade portfolio and allowing for multiple protocols pure hopes to eliminate the dissonance between file and object and simplify the choice in other words let the workload decide if you have data in a file format no problem pure can still bring the benefits of simplicity of object at scale to the table so again let the workload inform what the right strategy is not the technical infrastructure now pure course is not alone there are others supporting this multi-protocol strategy and so we asked matt burr why pure or what's so special about you and not surprisingly in addition to the product innovation he went right to pure's business model advantages i mean for example with its evergreen support model which was very disruptive in the marketplace you know frankly pure's entire business disrupted the traditional disk array model which was fundamentally was flawed pure forced the industry to respond and when it achieved escape velocity velocity and pure went public the entire industry had to react and a big part of the pure value prop in addition to this business model innovation that we just discussed is simplicity pure's keep its simple approach coincided perfectly with the ascendancy of cloud where technology organizations needed cloud-like simplicity for certain workloads that were never going to move into the cloud they're going to stay on-prem now i'm going to come back to this but allow me to bring in another concept that garrett and cb really highlighted and that is the complexity of the data pipeline and what do you mean what do i mean by that and why is this important so scott sinclair articulated he implied that the big challenge is organizations their data full but insights are scarce scarce a lot of data not as much insights it takes time too much time to get to those insights so we heard from our guests that the complexity of the data pipeline was a barrier to getting to faster insights now cb bonds shared how he streamlined his data architecture using vertica's eon mode which allowed him to scale compute independently of storage so that brought critical flexibility and improved economics at scale and flashblade of course was the back-end storage for his data warehouse efforts now the reason i think this is so important is that organizations are struggling to get insights from data and the complexity associated with the data pipeline and data life cycles let's face it it's overwhelming organizations and there the answer to this problem is a much longer and different discussion than unifying object and file that's you know i can spend all day talking about that but let's focus narrowly on the part of the issue that is related to file and object so the situation here is that technology has not been serving the business the way it should rather the formula is twisted in the world of data and big data and data architectures the data team is mired in complex technical issues that impact the time to insights now part of the answer is to abstract the underlying infrastructure complexity and create a layer with which the business can interact that accelerates instead of impedes innovation and unifying file and object is a simple example of this where the business team is not blocked by infrastructure nuance like does this data reside in a file or object format can i get to it quickly and inexpensively in a logical way or is the infrastructure in a stovepipe and blocking me so if you think about the prevailing sentiment of how the cloud is evolving to incorporate on premises workloads that are hybrid and configurations that are working across clouds and now out to the edge this idea of an abstraction layer that essentially hides the underlying infrastructure is a trend we're going to see evolve this decade now is uffo the be all end-all answer to solving all of our data pipeline challenges no no of course not but by bringing the simplicity and economics of object together with the ubiquity and performance of file uffo makes it a lot easier it simplifies life organizations that are evolving into digital businesses which by the way is every business so we see this as an evolutionary trend that further simplifies the underlying technology infrastructure and does a better job supporting the data flows for organizations so they don't have to spend so much time worrying about the technology details that add a little value to the business okay so thanks for watching the convergence of file and object and thanks to pure storage for making this program possible this is dave vellante for the cube we'll see you next time [Music] you

>>From around the globe presenting the convergence of file and object brought to you by pure storage. Okay. >>We're back with the convergence of file and object and a power panel. This is a special content program made possible by pure storage. And co-created with the cube. Now in this series, what we're doing is we're exploring the coming together of file and object storage, trying to understand the trends that are driving this convergence, the architectural considerations that users should be aware of and which use cases make the most sense for so-called unified fast file in object storage. And with me are three great guests to unpack these issues. Garrett bell center is the data center solutions architect he's with CDW. Scott Sinclair is a senior analyst at enterprise strategy group. He's got deep experience on enterprise storage and brings that independent analyst perspective. And Matt Burr is back with us, gentlemen, welcome to the program. >>Thank you. >>Hey Scott, let me, let me start with you, uh, and get your perspective on what's going on in the market with, with object to cloud huge amount of unstructured data out there. It lives in files. Give us your independent view of the trends that you're seeing out there. >>Well, Dave, you know where to start, I mean, surprise, surprise data's growing. Um, but one of the big things that we've seen is that we've been talking about data growth for what decades now, but what's really fascinating is or changed is because of the digital economy, digital business, digital transformation, whatever you call it. Now, people are not just storing data. They actually have to use it. And so we see this in trends like analytics and artificial intelligence. And what that does is it's just increasing the demand for not only consolidation of massive amounts of storage that we've seen for awhile, but also the demand for incredibly low latency access to that storage. And I think that's one of the things that we're seeing, that's driving this need for convergence, as you put it of having multiple protocols can Solidated onto one platform, but also the need for high performance access to that data. >>Thank you for that. A great setup. I got, like I wrote down three topics that we're going to unpack as a result of that. So Garrett, let me, let me go to you. Maybe you can give us the perspective of what you see with customers is, is this, is this like a push where customers are saying, Hey, listen, I need to converge my file and object. Or is it more a story where they're saying, Garrett, I have this problem. And then you see unified file and object as a solution. >>Yeah, I think, I think for us, it's, you know, taking that consultative approach with our customers and really kind of hearing pain around some of the pipelines, the way that they're going to market with data today and kind of what are the problems that they're seeing. We're also seeing a lot of the change driven by the software vendors as well. So really being able to support a dis-aggregated design where you're not having to upgrade and maintain everything as a single block has been a place where we've seen a lot of customers pivot to where they have more flexibility as they need to maintain larger volumes of data and higher performance data, having the ability to do that separate from compute and cash. And some of those other layers are, is really critical. >>So, Matt, I wonder if you could follow up on that. So, so Gary was talking about this dis-aggregated design, so I like it, you know, distributed cloud, et cetera, but then we're talking about bringing things together in one place, right? So square that circle. How does this fit in with this hyper distributed cloud edge that's getting built out? >>Yeah. You know, I mean, I could give you the easy answer on that, but I can also pass it back to Garrett in the sense that, you know, Garrett, maybe it's important to talk about, um, elastic and Splunk and some of the things that you're seeing in, in that world and, and how that, I think the answer today, the question I think you can give, you can give a pretty qualified answer relative to what your customers are seeing. >>Oh, that'd be great, please. >>Yeah, absolutely. No, no problem at all. So, you know, I think with, um, Splunk kind of moving from its traditional design and classic design, whatever you want to, you want to call it up into smart store? Um, that was kind of one of the first that we saw kind of make that move towards kind of separating object out. And I think, you know, a lot of that comes from their own move to the cloud and updating their code to basically take advantage of object object in the cloud. Um, but we're starting to see, you know, with like Vertica Ian, for example, um, elastic other folks taking that same type of approach where in the past we were building out many to use servers. We were jamming them full of, uh, you know, SSDs and then DME drives. Um, that was great, but it doesn't really scale. >>And it kind of gets into that same problem that we see with hyperconvergence a little bit where it's, you know, you're all, you're always adding something maybe that you didn't want to add. Um, so I think it, you know, again, being driven by software is really kind of where we're seeing the world open up there. Um, but that whole idea of just having that as a hub and a central place where you can then leverage that out to other applications, whether that's out to the edge for machine learning or AI applications to take advantage of it. I think that's where that convergence really comes back in. Um, but I think like Scott mentioned earlier, it's really folks are now doing things with the data where before I think they were really storing and trying to figure out what are we going to actually do with it when we need to do something with it? So this is making it possible. >>Yeah. And Dave, if I could just sort of tack onto the end of the Garrett's answer there, you know, in particular verdict with beyond mode, the ability to leverage sharted sub clusters, give you, um, you know, sort of an advantage in terms of being able to isolate performance, hotspots you an advantage to that as being able to do that on a flash blade, for example. So, um, sharted, sub clusters allow you to sort of say, I am, you know, I am going to give prioritization to, you know, this particular element of my application in my dataset, but I can still share those, share that data across those, across those sub clusters. So, um, you know, as you see, you know, Vertica with the non-motor, >>You see Splunk advanced with, with smart store, um, you know, these are all sort of advancements that are, you know, it's a chicken and the egg thing. Um, they need faster storage, they need, you know, sort of a consolidated data storage data set. Um, and, and that's what sort of allows these things to drive forward. Yes, >>The verdict eon mode, there was a no, no, it's the ability to separate compute and storage and scale independently. I think, I think Vertica, if they're, if they're not the only one, they're one of the only ones I think they might even be the only one that does that in the cloud and on prem and that sort of plays into this distributed nature of this hyper distributed cloud. I sometimes call it and I'm interested in the, in the data pipeline. And I wonder Scott, if we can talk a little bit about that maybe where unified object and file fund. I mean, I'm envisioning this, this distributed mesh and then, you know, UFO is sort of a note on that, that I can tap when I need it. But, but Scott, what are you seeing as the state of infrastructure as it relates to the data pipeline and the trends there? >>Yeah, absolutely. Dave, so w when I think data pipeline, I immediately gravitate to analytics or, or machine learning initiatives. Right. And so one of the big things we see, and this is, it's an interesting trend. It seems, you know, we continue to see increased investment in AI, increase interest and people think, and as companies get started, they think, okay, well, what does that mean? Well, I gotta go hire a data scientist. Okay. Well that data scientist probably needs some infrastructure. And what they end, what often happens in these environments is where it ends up being a bespoke environment or a one-off environment. And then over time organizations run into challenges. And one of the big challenges is the data science team or people whose jobs are outside of it, spend way too much time trying to get the infrastructure, um, to, to keep up with their demands and predominantly around data performance. So one of the, one of the ways organizations that especially have artificial intelligence workloads in production, and we found this in our research have started mitigating that is by deploying flash all across the data pipe. We have. Yeah, >>We have data on this. Sorry to interrupt, but Pat, if you could bring up that, that chart, that would be great. Um, so take us through this, uh, Scott and, and share with us what we're looking at here. >>Yeah, absolutely. So, so Dave, I'm glad you brought this up. So we did this study. Um, I want to say late last year, uh, one of the things we looked at was across artificial intelligence environments. Now, one thing that you're not seeing on this slide is we went through and we asked all around the data pipeline and we saw flash everywhere. But I thought this was really telling because this is around data lakes. And when many people think about the idea of a data Lake, they think about it as a repository. It's a place where you keep maybe cold data. And what we see here is especially within production environments, a pervasive use of flash stores. So I think that 69% of organizations are saying their data Lake is mostly flash or all flash. And I think we had 0% that don't have any flash in that environment. So organizations are out that thing that flashes in essential technology to allow them to harness the value of their data. >>So Garrett, and then Matt, I wonder if you could chime in as well. We talk about digital transformation and I, I sometimes call it, you know, the COVID forced March to digital transformation. And, and I'm curious as to your perspective on things like machine learning and the adoption, um, and Scott, you may have a perspective on this as well. You know, we had to pivot, he had to get laptops. We had to secure the end points, you know, VDI, those became super high priorities. What happened to, you know, injecting AI into my applications and, and machine learning. Did that go in the back burner? Was that accelerated along with the need to digitally transform, uh, Garrett, I wonder if you could share with us what you saw with, with customers last year? >>Yeah. I mean, I think we definitely saw an acceleration. Um, I think folks are in, in my market are, are still kind of figuring out how they inject that into more of a widely distributed business use case. Um, but again, this data hub and allowing folks to now take advantage of this data that they've had in these data lakes for a long time. I agree with Scott. I mean, many of the data lakes that we have were somewhat flashing, accelerated, but they were typically really made up of large capacity, uh, slower spinning nearline drives, um, accelerated with some flash, but I'm really starting to see folks now look at some of those older Hadoop implementations and really leveraging new ways to look at how they consume data. And many of those redesigned customers are coming to us, wanting to look at all flash solutions. So we're definitely seeing it. And we're seeing an acceleration towards folks trying to figure out how to actually use it in more of a business sense now, or before I feel it goes a little bit more skunkworks kind of people dealing with, uh, you know, in a much smaller situation, maybe in the executive offices trying to do some testing and things. >>Scott you're nodding away. Anything you can add in here. >>Yeah. So, well, first off, it's great to get that confirmation that the stuff we're seeing in our research, Garrett seeing, you know, out in the field and in the real world, um, but you know, as it relates to really the past year, it's been really fascinating. So one of the things we, we studied at ESG is it buying intentions. What are things, what are initiatives that companies plan to invest in? And at the beginning of 2020, we saw heavy interest in machine learning initiatives. Then you transition to the middle of 2020 in the midst of COVID. Uh, some organizations continued on that path, but a lot of them had the pivot, right? How do we get laptops, everyone? How do we continue business in this new world? Well, now as we enter into 2021, and hopefully we're coming out of this, uh, you know, the, the pandemic era, um, we're getting into a world where organizations are pivoting back towards these strategic investments around how do I maximize the usage of data and actually accelerating those because they've seen the importance of, of digital business initiatives over the past >>Year. >>Yeah, Matt, I mean, when we exited 2019, we saw a narrowing of experimentation in our premise was, you know, that that organizations are going to start now operationalizing all their digital transformation experiments. And, and then we had a 10 month Petri dish on, on digital. So what are you, what are you seeing in this regard? >>It's 10 months, Petri dish is an interesting way to interesting way to describe it. Um, you know, we, we saw another, there's another, there's another candidate for pivot in there around ransomware as well. Right. Um, you know, security entered into the mix, uh, which took people's attention away from some of this as well. I mean, look, I I'd like to bring this up just a level or two, um, because what we're actually talking about here is progress, right? And, and progress is an, is an inevitability. Um, you know, whether it's whether, whether you believe that it's by 20, 25 or you, or you think it's 20, 35 or 2050, it doesn't matter. We're on a forced March to the eradication of desk. And that is happening in many ways. Uh, you know, in many ways, um, due to some of the things that Garrett was referring to and what Scott was referring to in terms of what our customer's demands for, how they're going to actually leverage the data that they have. >>And that brings me to kind of my final point on this, which is we see customers in three phases. There's the first phase where they say, Hey, I have this large data store, and I know there's value in there. I don't know how to get to it. Or I have this large data store and I've started a project to get value out of it. And we failed. Those could be customers that, um, you know, marched down the dupe, the Hadoop path early on. And they, they, they got some value out of it. Um, but they realized that, you know, HDFS, wasn't going to be a modern protocol going forward for any number of reasons. You know, the first being, Hey, if I have gold dot master, how do I know that I have gold dot four is consistent with my gold dot master? So data consistency matters. >>And then you have the sort of third group that says, I have these large datasets. I know how to extract value from them. And I'm already on to the Vertica is the elastics, you know, the Splunks et cetera. Um, I think those folks are the folks that, that latter group are the folks that kept their, their, their projects going because they were already extracting value from them. The first two groups we were seeing, sort of saying the second half of this year is when we're going to begin really being picking up on these, on these types of initiatives again. >>Well, thank you, Matt, by the way, for, for hitting the escape key, because I think value from data really is what this is all about. And there are some real blockers there that I kind of want to talk about. You've mentioned HDFS. I mean, we were very excited, of course, in the early days of a dupes, many of the concepts were profound, but at the end of the day, it was too complicated. We've got these hyper specialized roles that are, that are serving the business, but it still takes too long. It's, it's too hard to get value from data. And one of the blockers is infrastructure that the complexity of that infrastructure really needs to be abstracted taken up a level. We're starting to see this in, in cloud where you're seeing some of those abstraction layers being built from some of the cloud vendors, but more importantly, a lot of the vendors like pure, Hey, we can do that heavy lifting for you. Uh, and we, you know, we have expertise in engineering to do cloud native. So I'm wondering what you guys see. Maybe Garrett, you could start us off and the other salmon as some of the blockers, uh, to getting value from data and how we're going to address those in the coming decade. >>Yeah. I mean, I think part of it we're solving here obviously with, with pure bringing, uh, you know, flash to a market that traditionally was utilizing a much slower media. Um, you know, the other thing that I, that I see that's very nice with flash blade for example, is the ability to kind of do things, you know, once you get it set up a blade at a time. I mean, a lot of the things that we see from just kind of more of a simplistic approach to this, like a lot of these teams don't have big budgets and being able to kind of break them down into almost a blade type chunk, I think has really kind of allowed folks to get more projects and, and things off the ground because they don't have to buy a full expensive system to run these projects. Um, so that's helped a lot. >>I think the wider use cases have helped a lot. So, um, Matt mentioned ransomware, um, you know, using safe mode as a, as a place to help with ransomware has been a really big growth spot for us. We've got a lot of customers, very interested and excited about that. Um, and the other thing that I would say is bringing dev ops into data is another thing that we're seeing. So kind of that push towards data ops and really kind of using automation and infrastructure as code as a way to now kind of drive things through the system. The way that we've seen with automation through dev ops is, is really an area we're seeing a ton of growth with from a services perspective, >>Guys, any other thoughts on that? I mean, we're, I I'll, I'll tee it up there. I, we are seeing some bleeding edge, which is somewhat counterintuitive, especially from a cost standpoint, organizational changes at some, some companies, uh, think of some of the, the, the, the internet companies that do, uh, music, uh, for instance, and adding podcasts, et cetera. And those are different data products. We're seeing them actually reorganize their data architectures to make them more distributed, uh, and actually put the domain heads, the business heads in charge of the data and the data pipeline. And that is maybe less efficient, but, but it's, again, some of these bleeding edge. What else are you guys seeing out there that might be some harbinger of the next decade? >>Uh, I'll go first. Um, you know, I think specific to, um, the, the construct that you threw out, Dave, one of the things that we're seeing is, um, you know, the, the, the application owner, maybe it's the dev ops person, but it's, you know, maybe it's, it's, it's, it's the application owner through the dev ops person. They're, they're becoming more technical in their understanding of how infrastructure, um, interfaces with their, with their application. I think, um, you know, what, what we're seeing on the flash blade side is we're having a lot more conversations with application people than, um, just it people. It doesn't mean that the, it people aren't there, the it, people are still there for sure if they have to deliver the service, et cetera. Um, but you know, the days of, of it, you know, building up a catalog of services and a business owner subscribing to one of those services, you know, picking, you know, whatever sort of fits their need. >>Um, I don't think that constant, I think that's the construct that changes going forward. The application owner is becoming much more prescriptive about what they want the infrastructure to fit, how they want the infrastructure to fit into their application. Um, and that's a big change. And for, for, um, you know, certainly folks like, like Garrett and CDW, um, you know, they do a good job with this being able to sort of get to the application owner and bring those two sides together. There's a tremendous amount of value there, uh, for us to spend a little bit of a, of a retooling we've traditionally sold to the it side of the house. And, um, you know, we've had to teach ourselves how to go talk the language of, of applications. So, um, you know, I think you pointed out a good, a good, a good construct there, and you know, that that application owner tank playing a much bigger role in what they're expecting from the performance of it, infrastructure I think is, is, is a key, is a key change. >>Interesting. I mean, that definitely is a trend. That's puts you guys closer to the business where the infrastructure team is serving the business, as opposed to sometimes I talked to data experts and they're frustrated, uh, especially data owners or data, product builders who are frustrated that they feel like they have to beg, beg the, the data pipeline team to get, you know, new data sources or get data out. How about the edge? Um, you know, maybe Scott, you can kick us off. I mean, we're seeing, you know, the emergence of, of edge use cases, AI inferencing at the edge, lot of data at the edge. W what are you seeing there and how does this unified object I'll bring us back to that in file fit. >>Wow. Dave, how much time do we have, um, tell me, first of all, Scott, why don't you, why don't you just tell everybody what the edge is? Yeah. You got it all figured out. How much time do you have end of the day. And that's, that's a great question, right? Is if you take a step back and I think it comes back to Dave, something you mentioned it's about extracting value from data. And what that means is when you extract value from data, what it does is as Matt pointed out the, the influencers or the users of data, the application owners, they have more power because they're driving revenue now. And so what that means is from an it standpoint, it's not just, Hey, here are the services you get, use them or lose them, or, you know, don't throw a fit. It is no, I have to, I have to adapt. I have to follow what my application owners me. Now, when you bring that back to the edge, what it means is, is that data is not localized to the data center. I mean, we just went through a nearly 12 month period where >>The entire workforce for most of the companies in this country had went distributed and business continued. So if business is distributed, data is distributed. And that means, that means in the data center, that means at the edge, that means that the cloud, and that means in all other places and tons of places. And what it also means is you have to be able to extract and utilize data anywhere it may be. And I think that's something that we're going to continue to and continue to see. And I think it comes back to, you know, if you think about key characteristics, we've talked about, um, things like performance and scale for years, but we need to start rethinking it because on one hand, we need to get performance everywhere. But also in terms of scale, and this ties back to some of the other initiatives and getting value from data, it's something I call the, the massive success problem. One of the things we see, especially with, with workloads like machine learning is businesses find success with them. And as soon as they do they say, well, I need about 20 of these projects now will all of a sudden that overburdens it organizations, especially across, across core and edge and cloud environments. And so when you look at environments ability to meet performance and scale demands, wherever it needs to be is something that's really important. You know, >>Dave, I'd like to, um, just sort of tie together sort of two things that, um, I think that I heard from Scott and Garrett that I think are important and it's around this concept of scale. Um, you know, some of us are old enough to remember the day when kind of a 10 terabyte blast radius was too big of a blast radius for people to take on, or a terabyte of storage was considered to be, um, you know, uh, uh, an exemplary budget environment. Right. Um, now we sort of think as terabytes, kind of like we used to think of as gigabytes in some ways, um, petabyte, like you don't have to explain to anybody what a petabyte is anymore. Um, and you know, what's on the horizon and it's not far are our exabyte type dataset workloads. Um, and you start to think about what could be in that exabyte of data. >>We've talked about how you extract that value. And we've talked about sort of, um, how you start, but if the scale is big, not everybody's going to start at a petabyte or an exabyte to Garrett's point, the ability to start small and grow into these products, or excuse me, these projects, I think is a, is a really, um, fundamental concept here because you're not going to just go buy five. I'm going to go kick off a five petabyte project, whether you do that on disk or flash, it's going to be expensive, right. But if you could start at a couple of hundred terabytes, not just as a proof of concept, but as something that, you know, you could get predictable value out of that, then you could say, Hey, this either scales linearly, or non-linearly in a way that I can then go map my investments to how I can go dig deeper into this. That's how all of these things are going to, that's how these successful projects are going to start, because the people that are starting with these very large, you know, sort of, um, expansive, you know, Greenfield projects at multi petabyte scale, it's gonna be hard to realize near-term value. Excellent. Uh, >>We we're, we gotta wrap, but, but Garrett, I wonder if you could close it, when you look forward, you talk to customers, do you see this unification of file and object? Is it, is this an evolutionary trend? Is it something that is, that is, that is, that is going to be a lever that customers use. How do you see it evolving over the next two, three years and beyond? >>Yeah, I mean, I think from our perspective, I mean, just from what we're seeing from the numbers within the market, the amount of growth that's happening with unstructured data is really just starting to finally really kind of hit this data delusion or whatever you want to call it that we've been talking about for so many years. Um, it really does seem to now be becoming true, um, as we start to see things scale out and really folks settle into, okay, I'm going to use the cloud to start and maybe train my models, but now I'm going to get it back on prem because of latency or security or whatever the, the, the, um, decision points are there. Um, this is something that is not going to slow down. And I think, you know, folks like pure having the ability to have the tools that they give us, um, do use and bring to market with our customers are, are really key and critical for us. So I see it as a huge growth area and a big focus for us moving forward, >>Guys, great job unpacking a topic that, you know, it's covered a little bit, but I think we, we covered some ground. That is a, that is new. And so thank you so much for those insights and that data really appreciate your time. >>Thanks, Dave. Thanks. Yeah. Thanks, Dave. >>Okay. And thank you for watching the convergence of file and object. Keep it right there. Bright, bright back after the short break.

from around the globe it's thecube presenting the convergence of file and object brought to you by pure storage we're back with the convergence of file and object a special program made possible by pure storage and co-created with the cube so in this series we're exploring that convergence between file and object storage we're digging into the trends the architectures and some of the use cases for unified fast file and object storage uffo with me is matt burr who's the vice president general manager of flashblade at pure storage hello matt how you doing i'm doing great morning dave how are you good thank you hey let's start with a little 101 you know kind of the basics what is unified fast file and object yeah so look i mean i think you got to start with first principles talking about the rise of unstructured data so when we think about unstructured data you sort of think about the projections 80 of data by 2025 is going to be unstructured data whether that's machine generated data or you know ai and ml type workloads you start to sort of see this i don't want to say it's a boom uh but it's sort of a renaissance for unstructured data if you will where we move away from you know what we've traditionally thought of as general purpose nas and and file shares to you know really things that focus on uh fast object taking advantage of s3 cloud native applications that need to integrate with applications on site um you know ai workloads ml workloads tend to look to share data across uh you know multiple data sets and you really need to have a platform that can deliver both highly performant and scalable fast file and object from one system so talk a little bit more about some of the drivers that you know bring forth that need to unify file an object yeah i mean look you know there's a there's there's a real challenge um in managing you know bespoke uh bespoke infrastructure or architectures around general purpose nas and daz etc so um if you think about how a an architect sort of looks at an application they might say well okay i need to have um you know fast daz storage proximal to the application um but that's gonna require a tremendous amount of dabs which is a tremendous amount of drives right hard drives are you know historically pretty pretty pretty unwieldy to manage because you're replacing them relatively consistently at multi-petabyte scale so you start to look at things like the complexity of das you start to look at the complexity of general purpose nas and you start to just look at quite frankly something that a lot of people don't really want to talk about anymore but actual data center space right like consolidation matters the ability to take you know something that's the size of a microwave like a modern flash blade or a modern um you know uffo device replaces something that might be you know the size of three or four or five refrigerators so matt why is is now the right time for this i mean for years nobody really paid much attention to object s3 already obviously changed you know that course most of the world's data is still stored in file formats and you get there with nfs or smb why is now the time to think about unifying object and and file well because we're moving to things like a contactless society um you know the the things that we're going to do are going to just require a tremendous amount more compute power network and quite frankly storage throughput and you know i can give you two sort of real primary examples here right um you know warehouses are being you know taken over by robots if you will um it's not a war it's a it's a it's sort of a friendly advancement in you know how do i how do i store a box in a warehouse and you know we have we have a customer who focuses on large sort of big box distribution warehousing and you know a box that carried a an object uh two weeks ago might have a different box size two weeks later well that robot needs to know where the space is in the data center in order to put it but also needs to be able to process hey i don't want to put the thing that i'm going to access the most in the back of the warehouse i'm going to put that thing in the front of the warehouse all of those types of data you know sort of real time you can think of the robot as almost an edge device uh is processing in real time unstructured data and its object right so it's sort of the emergence of these new types of workloads and i give you the opposite example the other end of the spectrum is ransomware right you know today you know we'll talk to customers and they'll say quite commonly hey if you know anybody can sell me a backup device i need something that can restore quickly if you had the ability to restore something in 270 terabytes an hour or 250 terabytes an hour that's much faster when you're dealing with a ransomware attack you want to get your data back quickly you know so i want to actually i was going to ask you about that later but since you brought it up what is the right i guess call it architecture for for for ransomware i mean how and explain like how unified object and file would support me i get the fast recovery but how would you recommend a customer uh go about architecting a ransomware proof you know system yeah well you know with with flashblade and and with flasharray there's an actual feature called called safe mode and that safe mode actually protects uh the snapshots and and the data from uh sort of being is a part of the of the ransomware event and so if you're in a type of ransomware situation like this you're able to leverage safe mode and you say okay what happens in a ransomware attack is you can't get access to your data and so you know the bad guy the perpetrator is basically saying hey i'm not going to give you access to your data until you pay me you know x in bitcoin or whatever it might be right um with with safe mode those snapshots are actually protected outside of the ransomware blast zone and you can bring back those snapshots because what's your alternative if you're not doing something like that your alternative is either to pay and unlock your data or you have to start retouring restoring excuse me from tape or slow disk that could take you days or weeks to get your data back so leveraging safe mode um you know in either the flash for the flash blade product is a great way to go about uh architecting against ransomware i got to put my i'm thinking like a customer now so safe mode so that's an immutable mode right can't change the data um is it can can an administrator go in and change that mode can he turn it off do i still need an air gap for example what would you recommend there yeah so there there are still um uh you know sort of our back or rollback role-based access control policies uh around who can access that safe mode and who can right okay so uh anyway subject for a different day i want to i want to actually bring up uh if you don't object a topic that i think used to be really front and center and it now be is becoming front and center again i mean wikibon just produced a research note forecasting the future of flash and hard drives and those of you who follow us know we've done this for quite some time and you can if you could bring up the chart here you you could see and we see this happening again it was originally we forecast the the death of of quote unquote high spin speed disk drives which is kind of an oxymoron but you can see on here on this chart this hard disk had a magnificent journey but they peaked in volume in manufacturing volume in 2010 and the reason why that is is so important is that volumes now are steadily dropping you can see that and we use wright's law to explain why this is a problem and wright's law essentially says that as you your cumulative manufacturing volume doubles your cost to manufacture decline by a constant percentage now i won't go too much detail on that but suffice it to say that flash volumes are growing very rapidly hdd volumes aren't and so flash because of consumer volumes can take advantage of wright's law and that constant reduction and that's what's really important for the next generation which is always more expensive to build and so this kind of marks the beginning of the end matt what do you think what what's the future hold for spinning disc in your view uh well i can give you the answer on two levels on a personal level uh it's why i come to work every day uh you know the the eradication or or extinction of an inefficient thing um you know i like to say that inefficiency is the bane of my existence uh and i think hard drives are largely inefficient and i'm willing to accept the sort of long-standing argument that um you know we've seen this transition in block right and we're starting to see it repeat itself in in unstructured data um and i'm willing to accept the argument that cost is a vector here and it most certainly is right hdds have been considerably cheaper uh than than than flash storage um you know even to this day uh you know up to this point right but we're starting to approach the point where you sort of reach a 3x sort of you know differentiator between the cost of an hdd and an sdd and you know that really is that point in time when uh you begin to pick up a lot of volume and velocity and so you know that tends to map directly to you know what you're seeing here which is you know a slow decline uh which i think is going to become even more rapid kind of probably starting around next year where you start to see sds excuse me ssds uh you know really replacing hdds uh at a much more rapid clip particularly on the unstructured data side and it's largely around cost the the workloads that we talked about robots and warehouses or you know other types of advanced machine learning and artificial intelligence type applications and workflows you know they require a degree of performance that a hard drive just can't deliver we are we are seeing sort of the um creative innovative uh disruption of an entire industry right before our eyes it's a fun thing to live through yeah and and we would agree i mean it doesn't the premise there is it doesn't have to be less expensive we think it will be by you know the second half or early second half of this decade but even if it's a we think around a 3x delta the value of of ssd relative to spinning disk is going to overwhelm just like with your laptop you know it got to the point where you said why would i ever have a spinning disc in my laptop we see the same thing happening here um and and so and we're talking about you know raw capacity you know put in compression and dedupe and everything else that you really can't do with spinning discs because of the performance issues you can do with flash okay let's come back to uffo can we dig into the challenges specifically that that this solves for customers give me give us some examples yeah so you know i mean if we if we think about the examples um you know the the robotic one um i think is is is the one that i think is the marker for you know kind of of of the the modern side of of of what we see here um but what we're you know what we're what we're seeing from a trend perspective which you know not everybody's deploying robots right um you know there's there's many companies that are you know that aren't going to be in either the robotic business uh or or even thinking about you know sort of future type oriented type things but what they are doing is greenfield applications are being built on object um generally not on not on file and and not on block and so you know the rise of of object as sort of the the sort of let's call it the the next great protocol for um you know for uh for for modern workloads right this is this is that that modern application coming to the forefront and that could be anything from you know financial institutions you know right down through um you know we've even see it and seen it in oil and gas uh we're also seeing it across across healthcare uh so you know as as as companies take the opportunity as industries to take this opportunity to modernize you know they're modernizing not on things that are are leveraging you know um you know sort of archaic disk technology they're they're they're really focusing on on object but they still have file workflows that they need to that they need to be able to support and so having the ability to be able to deliver those things from one device in a capacity orientation or a performance orientation while at the same time dramatically simplifying the overall administration of your environment both physically and non-physically is a key driver so the great thing about object is it's simple it's a kind of a get put metaphor um it's it scales out you know because it's got metadata associated with the data uh and and it's cheap the drawback is you don't necessarily associate it with high performance and and as well most applications don't you know speak in that language they speak in the language of file you know or as you mentioned block so i i see real opportunities here if i have some some data that's not necessarily frequently accessed you know every day but yet i want to then whether end of quarter or whatever it is i want to i want to or machine learning i want to apply some ai to that data i want to bring it in and then apply a file format uh because for performance reasons is that right maybe you could unpack that a little bit yeah so um you know we see i mean i think you described it well right um but i don't think object necessarily has to be slow um and nor does it have to be um you know because when you think about you brought up a good point with metadata right being able to scale to a billions of objects being able to scale to billions of objects excuse me is of value right um and i think people do traditionally associate object with slow but it's not necessarily slow anymore right we we did a sort of unofficial survey of of of our of our customers and our employee base and when people described object they thought of it as like law firms and storing a word doc if you will um and that that's just you know i think that there's a lack of understanding or a misnomer around what modern what modern object has become and perform an object particularly at scale when we're talking about billions of objects you know that's the next frontier right um is it at pace performance wise with you know the other protocols no but it's making leaps and grounds so you talked a little bit more about some of the verticals that you see i mean i think when i think of financial services i think transaction processing but of course they have a lot of tons of unstructured data are there any patterns you're seeing by by vertical market um we're you know we're not that's the interesting thing um and you know um as a as a as a as a company with a with a block heritage or a block dna those patterns were pretty easy to spot right there were a certain number of databases that you really needed to support oracle sql some postgres work etc then kind of the modern databases around cassandra and things like that you knew that there were going to be vmware environments you know you could you could sort of see the trends and where things were going unstructured data is such a broader horizontal um thing right so you know inside of oil and gas for example you have you know um you have specific applications and bespoke infrastructures for those applications um you know inside of media entertainment you know the same thing the the trend that we're seeing the commonality that we're seeing is the modernization of you know object as a starting point for all the all of the net new workloads within within those industry verticals right that's the most common request we see is what's your object roadmap what's your you know what's your what's your object strategy you know where do you think where do you think object is going so um there isn't any um you know sort of uh there's no there's no path uh it's really just kind of a wide open field in front of us with common requests across all industries so the amazing thing about pure just as a kind of a little you know quasi you know armchair historian the industry is pure was really the only company in many many years to be able to achieve escape velocity break through a billion dollars i mean three part couldn't do it isilon couldn't do it compellent couldn't do it i could go on but pure was able to achieve that as an independent company uh and so you become a leader you look at the gartner magic quadrant you're a leader in there i mean if you've made it this far you've got to have some chops and so of course it's very competitive there are a number of other storage suppliers that have announced products that unify object and file so i'm interested in how pure differentiates why pure um it's a great question um and it's one that uh you know having been a long time puritan uh you know i take pride in answering um and it's actually a really simple answer um it's it's business model innovation and technology right the the technology that goes behind how we do what we do right and i don't mean the product right innovation is product but having a better support model for example um or having on the business model side you know evergreen storage right where we sort of look at your relationship to us as a subscription right um you know we're gonna sort of take the thing that that you've had and we're gonna modernize that thing in place over time such that you're not rebuying that same you know terabyte or you know petabyte of storage that you've that you that you've paid for over time so um you know sort of three legs of the stool uh that that have made you know pure clearly differentiated i think the market has has recognized that um you're right it's it's hard to break through to a billion dollars um but i look forward to the day that you know we we have two billion dollar products and i think with uh you know that rise in in unstructured data growing to 80 by 2025 and you know the massive transition that you know you guys have noted in in in your hdd slide i think it's a huge opportunity for us on you know the other unstructured data side of the house you know the other thing i'd add matt and i've talked to cause about this is is it's simplicity first i've asked them why don't you do this why don't you do it and the answer is always the same is that adds complexity and we we put simplicity for the customer ahead of everything else and i think that served you very very well what about the economics of of unified file and object i mean if you bringing additional value presumably there's a there there's a cost to that but there's got to be also a business case behind it what kind of impact have you seen with customers yeah i mean look i'll i'll go back to something i mentioned earlier which is just the reclamation of floor space and power and cooling right um you know there's a you know there's people people people want to search for kind of the the sexier element if you will when it comes to looking at how we how you derive value from something but the reality is if you're reducing your power consumption by you know by by a material percentage um power bills matter in big in big data centers you know customers typically are are facing you know a paradigm of well i i want to go to the cloud but you know the clouds are not being more expensive than i thought it was going to be or you know i've figured out what i can use in the cloud i thought it was going to be everything but it's not going to be everything so hybrid's where we're landing but i want to be out of the data center business and i don't want to have a team of 20 storage people to match you know to administer my storage um you know so there's sort of this this very tangible value around you know hey if i could manage um you know multiple petabytes with one full-time engineer uh because the system uh to your and kaza's point was radically simpler to administer didn't require someone to be running around swapping drives all the time would that be a value the answer is yes 100 of the time right and then you start to look at okay all right well on the uffo side from a product perspective hey if i have to manage a you know bespoke environment for this application if i have to manage a bespoke environment for this application and a spoke environment for this application and this focus environment for this application i'm managing four different things and can i actually share data across those four different things there's ways to share data but most customers it just gets too complex how do you even know what your what your gold.master copy is of data if you have it in four different places or you try to have it in four different places and it's four different siloed infrastructures so when you get to the sort of the side of you know how do we how do you measure value in uffo it's actually being able to have all of that data concentrated in one place so that you can share it from application to application got it i'm interested we use a couple minutes left i'm interested in the the update on flashblade you know generally but also i have a specific question i mean look getting file right is hard enough uh you just announced smb support for flashblade i'm interested in you know how that fits in i think it's kind of obvious with file and object converging but give us the update on on flashblade and maybe you could address that specific question yeah so um look i mean we're we're um you know tremendously excited about the growth of flashblade uh you know we we we found workloads we never expected to find um you know the rapid restore workload was one that was actually brought to us from from a customer actually um and has become you know one of our one of our top two three four you know workloads so um you know we're really happy with the trend we've seen in it um and you know mapping back to you know thinking about hdds and ssds you know we're well on a path to building a billion dollar business here so you know we're very excited about that but to your point you know you don't just snap your fingers and get there right um you know we've learned that doing file and object uh is is harder than block um because there's more things that you have to go do for one you're basically focused on three protocols s b nfs and s3 not necessarily in that order um but to your point about s b uh you know we we are on the path through to releasing um you know smb full full native smb support in in the system that will allow us to uh service customers we have a limitation with some customers today where they'll have an smb portion of their nfs workflow um and we do great on the nfs side um but you know we didn't we didn't have the ability to plug into the s p component of their workflow so that's going to open up a lot of opportunity for us um on on that front um and you know we continue to you know invest significantly across the board in in areas like security which is you know become more than just a hot button you know today security's always been there but it feels like it's blazing hot today and so you know going through the next couple years we'll be looking at uh you know developing some some uh you know pretty material security elements of the product as well so uh well on a path to a billion dollars is the net on that and uh you know we're we're fortunate to have have smb here and we're looking forward to introducing that to to those customers that have you know nfs workloads today with an s b component yeah nice tailwind good tam expansion strategy matt thanks so much we're out of time but really appreciate you coming on the program we appreciate you having us and uh thanks much dave good to see you all right good to see you and you're watching the convergence of file and object keep it right there we'll be back with more right after this short break [Music]

>> We continue with cube on cloud. We here with Mai-Lan Tomsen Bukovec who's the vice president of block and object storage at AWS which comprises elastic block storage, AWS S3 and Amazon glacier. Mai-Lan Great to see you again. Thanks so much for coming on the program. >> Nice to be here. Thanks for having me, Dave. >> You're very welcome. So here we're unpacking the future of cloud and we'd love to get your perspectives on how customers should think about the future of infrastructure things like applying machine intelligence to their data but just to set the stage, when we look back at the history of storage and the cloud has obviously started with S3 and then a couple of years later AWS introduced EBS for block storage and those are the most well-known services in the portfolio but there's more of this cold storage and new capabilities that you announced recently at reinvent around, you know, super-duper block storage and in tiering is another example. But it looks like AWS is really starting to accelerate and pick up the pace of customer options in storage. So my first question is how should we think about this expanding portfolio? >> Well, I think you have to go all the way back to what customers are trying to do with their data Dave. The path to innovation is paved by data. If you don't have data, you don't have machine learning. You don't have the next generation of analytics applications that helps you chart a path forward into a world that seems to be changing every week. And so in order to have that insight in order to have that predictive forecasting that every company needs, regardless of what industry that you're in today, it all starts from data. And I think the key shift that I've seen is how customers are thinking about that data, about being instantly usable. Whereas in the past, it might've been a backup. Now it's part of a data lake. And if you can bring that data into a data lake you can have not just analytics or machine learning or auditing applications, it's really what does your application do for your business and how can it take advantage of that vast amount of shared data set in your business? >> Awesome, so thank you. So I want to make sure we're hitting on the big trends that you're seeing in the market that kind of are informing your strategy around the portfolio, and what you're seeing with customers. Instant usability, you know, you bring in machine learning into the equation. I think people have really started to understand the benefits of cloud storage as a service and the pay by the drink. and that whole model. Obviously COVID has accelerated that, you know, cloud migration is accelerated. Anything else we're missing there? What are the other big trends that you see? If any. >> Well, Dave, you did a good job of capturing a lot of the drivers. The one thing I would say that just sits underneath all of it is the massive growth of digital data year over year. IDC says digital data is growing at a rate of 40% year over year. And that has been true for a while and it's not going to stop. It's going to keep on growing because the sources of that data acquisition keeps on expanding and whether it's IOT devices whether it is a content created by users, that data is going to grow and everything you're talking about depends on the ability to not just capture it and store it. But as you say, use it. >> Well, you know, and we talk about data growth a lot and sometimes it can, it becomes bromide. But I think the interesting thing that I've observed over the last couple of decades really is that the growth is non-linear and it's really the curve is starting to shape exponentially. You guys always talk about that flywheel effect it's really hard to believe, you know people say trees don't grow to the moon. It seems like data does. >> It does and what's interesting about working in a world of AWS storage Dave is that it's counter-intuitive but our goal with a data growth is to make it cost effective. And so year over year how can we make it cheaper and cheaper? It is have customers store more and more data so they can use it. But it's also to think about the definition of usage and what kind of data is being tapped by businesses for their insights and make that easier than it's ever been before. >> Let me ask you a follow up question on that Mai-Lan. Cause I get asked this a lot, or I hear comments a lot that yes AWS continuously and rigorously reduces pricing but it's just kind of following the natural curve of Moore's law or whatever. How do you respond to that? Are there other factors involved? Obviously labor is another, you know, cost reducing factor, but what's the trend line say? >> Well, cost efficiency is in our DNA, Dave we come to work every day in AWS across all of our services and we ask ourselves, how can we lower our costs and be able to pass that along to customers. As you say, there are many different aspects to costs. There's a cost to the storage itself There's a cost to the data center. And that's really what we've seen impact a lot of customers that were slower or just getting started with a move to the cloud, is they entered 2020 and then they found out exactly how expensive that data center was to maintain because they had to put in safety equipment and they had to do all the things that you have to do in a pandemic, in a data center. And so sometimes that cost is a little bit hidden or it won't show up until you really don't need to have it land. But the costs of managing that explosive growth of data is very real. And when we're thinking about costs, we're thinking about costs in terms of how can I lower it on a per gigabyte per month basis, but we're also building into the product itself, adaptive discounts. Like we have a storage class in S3 that's called intelligent tiering. And in intelligent tiering we have built-in monitoring where if particular objects aren't frequently accessed in a given month, a customer will automatically get a discounted price for that storage or a customer can, you know, as of late last year say that they want to automatically move storage in the storage class that has been stored for example longer than 180 days and saves 95% by moving it into deep archive storage. And so it's not just, you know relentlessly going after and lowering the cost of storage. It's also building into the products these new ways where we can adaptively discount storage based on what a customer's storage is actually doing. >> Right, and I would add to already is the other thing Gatos has done is it's really forced transparency almost the same way that Amazon has done on retail. And now Mai-Lan when we talked last I mentioned that S3 was an object store. And of course that's technically correct but your comment to me was Dave, it's more than that. And you started to talk about SageMaker and AI and bringing in machine learning. And I wonder if you could talk a little bit about the future of how storage is going to be leveraged in the cloud. That's maybe different than what we've been used to in the early days of S3. And how your customers should be thinking about infrastructure, not as bespoke services, but as a suite of capabilities and maybe some of those adjacent services that you see as most leverageable for customers and why? >> Well, to tell this story, Dave, we're going to have to go a little bit back in time, all the way back to the 1990s or before then. When all you had was a set of hardware appliance vendors that sold you appliances that you put in your data center and inherently created a data silo because those hardware appliances were hardwired to your application. And so an individual application that was dealing with auditing as an example wouldn't really be able to access the storage for another application, because you know, the architecture of that legacy world is tied to a data silo and S3 came out launched in 2006 and introduced very low cost storage. That is an object. And I'll tell you, Dave, you know, over the last 10 plus years we have seen all kinds of data coming to S3. Whereas before it might've been backups or it might've been images and videos. Now a pretty substantial data set is our parquet files and work files. These files are there for business analytics for more real-time type of processing. And that has really been the trend of the future, is taking these different files putting them in a shared file layer, so any application today or in the future can tap into that data. And so this idea of the shared file layer is a major trend that has been taking off for the last I would say five or six years. And I expect that to not only keep on going but to really open up the type of services that you can then do on that shared file layer. And whether that's Sage maker or some of the machine learning introduced by our connect service, it's bringing together the data as a starting point and then the applications can evolve very rapidly on top of that. >> I want to ask your opinion about big data architectures. One of our guests Chamakh Tigani, she's amazing data architect. And she's put forth this notion of a distributed global mesh. And picking up on some of the comments, Andy Jassy made it at re-invent how essentially, "Hey we're bringing AWS to the edge. "We see the data center is just another edge node." So you're seeing this massive distributed system evolving. You guys have talked about that for a while and data by its very nature is distributed but we've had this tendency to put it into a monolithic data Lake or a data warehouse and it's sort of antithetical to that distributed nature. So how do you see that playing out? What do you see customers in the future doing in terms of their big data architectures and what does that mean for storage? >> It comes down to the nature of the data and again the usage and Dave that's where I see the biggest difference in these modern data architectures from the legacy of 20 years ago, is the idea that the data need drives the data storage. So let's take an example of the type of data that you always want to have on the edge. We have customers today that need to have storage in the field and whether the field of scientific research or oftentimes it's content creation in the film industry, or if it's for military operations there's a lot of data that needs to be captured and analyzed in the field. And for us, what that means is that, you know we have a suite of products called snow ball and whether it's snow ball or snow cone, take your pick. That whole portfolio of AWS services is targeted at customers that need to do work with storage at the edge. And so, you know, if you think about the need for multiple applications acting on the same data set that's when you keep it in an AWS region. And what we've done in AWS storage is we've recognized that depending on the need of usage where you put your data and how you interact with it may vary. But we've built a whole set of services like data transfer to help make sure that we can connect data from, for example that new snow cone into a region automatically. And so our goal Dave is to make sure that when customers are operating at the edge or they're operating in the region they have the same quality of storage service and they have easy ways to go between them. You shouldn't have to pick, you should be able to do it all. >> So in the spirit of do it all there's this sort of age old dynamic in the tech business where you've got the friction between the best of breed and the integrated suite. And my question is around what you're optimizing for customers. And can you have your cake and eat it too? In other words, why AWS storage? What makes it compelling? Is it because it's kind of a best of breed storage service or is it because it's integrated with AWS? Would you ever sub optimize one in order to get an advantage to the other? Or can you actually, you know have your cake and eat it too? >> The way that we build storage is to focus on being both the breadth of capabilities and the depth of capabilities. And so where we identify a particular need where we think that it takes a whole new service to deliver we'll go build that service. And an example for that as FTP our AWS SFTP service, which, you know, there's a lot of SFTP usage out there and there will be for a while because of the, you know, the legacy B2B type of architectures that still live in the business world today. And so we looked at that problem. We said, how are we going to build that in the best depth way, in the best focus? And we launched a separate service for that. And so our goal is to take the individual building blocks of EBS and glacier and S3 and make the best of class and the most comprehensive in the capabilities of what we can do and where we identify a very specific need. We'll go build a service for it. But Dave, you know as an example for that idea of both depth and breadth, S3 Storage Lens is a great example of that. S3 Storage Lens is a new capability that we launched late last year. And what it does is it lets you look across all your regions and all your accounts and get a summary view of all your S3 storage and whether that's buckets or the most active prefixes that you have and be able to drill down from that. And that is built in to the S3 service and available for any customer that wants to turn it on in the AWS management console. >> Right, and we saw just recently made, I called it super-duper block storage but you can make some improvements in really addressing the highest performance. I want to ask you, so we've all learned about an experience that benefits of cloud over the last several years and especially in the last 10 months during the pandemic but one of the challenges and it's particularly acute with IO is of course latency and moving data around and accessing data remotely. It's a challenge for customers, you know, due to speed of light, et cetera. So my question is how was AWS thinking about all that data that's still resides on premises? I think we heard at reinvent, that's still on 90% of the opportunity is, or the the workloads are still on prem that live inside a customer's data centers. So how do you tap into those and help customers innovate with on-prem data, particularly from a storage angle? >> Well, we always want to provide the best of class solution for those little latency workloads. And that's why we launched Block Express just late last year at reinvent. And Block Express has a new capability in preview on top of our IO to provisioned IOPS volume type. And what's really interesting about block express Dave is that the way that we're able to deliver the performance of Block Express, which is sound performance with cloud elasticity is that we went all the way down to the network layer and we customize the hardware software. And at the network layer we built Block Express on something called SRD which stands for a scalable reliable diagrams. And basically what it's letting us do is offload all of our EBS operations for Block Express on the nitrile card on hardware. And so that type of innovation where we're able to, you know, take advantage of modern cop commodity, multi-tenant data center networks, where we're sending in this new network protocol across a large number of network paths. And that type of innovation all the way down to that protocol level helps us innovate in a way that's hard. In fact, I would say impossible for other sound providers to kind of really catch up and keep up. And so we feel that the amount of innovation that we have for delivering those low latency workloads in our AWS cloud storage is unlimited really because of that ability to customize software hardware and network protocols as we go along without requiring upgrades from a customer it just gets better. And the customer benefits. Now, if you want to stay in your data center that's why we build outposts. And for outposts, we have UVS and we have S3 for outposts and our goal there is that some customers will have workloads where they want to keep them resident in the data center. And for those customers we want to give them that AWS storage opportunities as well. >> So thank you for coming back to Block Express. So you call it, you know, sand in the cloud. So is that essentially it comprises a custom built essentially storage network. Is that right? What you just described SRD? I think you called it. >> Yeah, it's a SRD is used by other AWS services as well but it is a custom network protocol that we designed to deliver the lowest latency experience and we're taking advantage of it with Block Express. >> So sticking with traditional data centers for a moment I'm interested in your thoughts on the importance of the cloud pricing approach, I.e the consumption model to pay by the drink. Obviously it's one of the most attractive features, and I asked that because we're seeing what Andy Jassy refers to as the old guard Institute, flexible pricing models two of the biggest storage companies, HP with GreenLake and Dell has this thing called apex. They've announced such models for on-prem and presumably cross cloud. How do you think this is going to impact your customers leverage of AWS cloud storage? Is it something that you have an opinion on? >> Yeah, I think it all comes down to, again that usage of the storage, and this is where I think there's an inherent advantage for our cloud storage. So there might be an attempt by the old guard to lower prices or add flexibility but at the end of the day it comes down to what the customer actually needs to tune. And if you think about gp3 which is the new EBS volume. The idea with gp3 is we're going to pass a long savings to the customer by making the storage 20% cheaper than gp2. And we're going to make the product better by giving a great, reliable baseline performance. But we're also going to let customers who want to run workloads like Cassandra on EBS tune their throughput separately, for example from their capacity. So if you're running Cassandra sometimes you don't need to change your capacity. Your storage capacity works just fine. But what happens with, for example Cassandra workload is that you may need more throughput. And if you're buying hardware appliance you just have to buy for your peak. You have to buy for the max of what you think your throughput and the max of what your storage is. And this inherent flexibility that we have for AWS storage and being able to tune throughput separate from up separate from capacity like you do for gp3 that is really where the future is for customers having control over costs and control over customer experience without compromising or trading off either one. >> Awesome, thank you for that. So in the time we have remaining Mai-Lan, I want to talk about the topic of diversity social impact, and as a woman leader, women executive, and I really want to get your perspectives on this. And I've shared with the audience previously, one of my breaking analysis segments, your boxing video which is awesome. And so, you've got a lot of unique non-traditional aspects to your life and I love it, but I want to ask you this. So it's obviously, you know, certainly politically and socially correct to talk about diversity, the importance of diversity, there's data that suggests that diversity is good both economically, not just socially, and of course it's the right thing to do. But there are those, you know, Peter teal is probably the most prominent but there are others that say, "You know what? "Forget that, just hire people, just like you'll be able "to go faster, ramp up more quickly, hit escape "velocity it's natural." And that's what you should do. Why is that not the right approach? Why is diversity both, of course, socially, you know responsible, but also, you know, good for business >> For Amazon we think about diversity as something that is essential to how we think about innovation. And so, Dave, as you know, from listening to some of the announcements at reinvent, we launch a lot of new ideas, like new concepts and new services in AWS. And just bringing that lens down to storage. Astri has been reinventing itself every year since we launched in 2006. EBS introduced the first sun on the cloud late last year, and continues to reinvent how customers think about block storage. We would not be able to look at a product in a different way and think to ourselves, not just what is the legacy system do in a data center today but how do we want to build this new distributed system in a way that helps customers achieve not just what they're doing today, but what they want to do in five and 10 years. You can't get that innovative mindset without bringing different perspectives to the table. And so we strongly believe in hiring people who are from under represented groups and whether that's gender or it's related to racial equality or if it's geographic diversity and bringing them in to have the conversation because those diverse viewpoints inform how we can innovate at all levels in AWS. >> Right, and so I really appreciate their perspectives on that. And we've had, as you probably know the cube has been, you know a very big advocate of diversity, you know, generally but women in tech specifically, we participated a lot. And I often ask this question is, you know, as a smaller company, I, and some of my other colleagues in small business, sometimes we struggle. And so my question is how do you go beyond what's your advice for going beyond, you know the good old boys network? I think it's large companies like AWS and, you know, the big players, you've got responsibility too that you can put somebody in charge and make it their full-time job. How should smaller companies that are largely white male dominated, how should they become more diverse? What should they do to increase that diversity? >> I think the place to start is voice. A lot of what we try to do is make sure that the under represented voice is heard. And so Dave, any small business owner of any industry can encourage voice for your under represented or your unheard populations. And honestly, it is as simple as being in a meeting and looking around that table or on your screen, as it were and asking yourself, who hasn't talked? Who hasn't weighed in? Particularly if the debate is contentious or even animated. And you will see, particularly if you note this over time you will see that there may be somebody and whether it's an under represented group or it's a woman who's early career, or it's not it's just a member of your team who happens to be a white male too, who's not being heard. And you can ask that person for their perspective. And that is a step that every one of us can and should do which is ask to have everyone's voice at the table to listen and to weigh in on it. So I think that is something everyone should do. I think if you are a member of an under represented group as for example, I'm Vietnamese American and I'm a female in tech, I think, it's something to think about how you can make sure that you're always taking that bold step forward. And it's one of the topics that we covered at re-invent. We had a great discussion with a group of women CEOs and a lot of it we talked about is being bold taking the challenge of being bold in tough situations. And that is an important thing, I think for anybody to keep in mind, but especially for members of under represented groups, because sometimes Dave that bold step that you kind of think of as like, "Oh I don't know if I should ask for that promotion." or "I don't know if I should volunteer for that project." It's not a big ask, but it's big in your head. And so if you can internalize as a member of some, you know, a group that maybe isn't heard as or seen as much how you can take those bold challenges and step forward and learn, maybe fail also cause that's how you learn. Then that is a way to also have people learn and develop and become leaders in whatever industry it is. >> That's great advice. It reminds me of, I think most of us can relate to that Mai-Lan, because when we started in the industry, we may be timid. You didn't want to necessarily speak up. And I think it's incumbent upon those in a position of power. And by the way power might just be running a meeting agenda to maybe call on those folks that are, maybe it's not diversity of gender or, you know, or race. Maybe it's just the under represented. Maybe that's a good way to start building muscle memory. So that's unique advice that I hadn't heard before. So thank you very much for that. I appreciate it. And Hey, listen. Thanks so much for coming on the Cube On Cloud. We're out of time and really always appreciate your perspectives and you're doing a great job. And thank you. >> Great, thank you Dave. Thanks for having me and have a great day. >> All right, and Keep it right there buddy. You're watching the Cube On Cloud. Right back. (gentle upbeat music)

(electronic music) >> Hi everybody, welcome back to Supercloud 2. I'm Dave Vellante with my co-host John Furrier. We're here at our tricked out Palo Alto studio. We're going live wall to wall all day. We're inserting a number of pre-recorded interviews, folks like Walmart. We just heard from Nir Zuk of Palo Alto Networks, and I'm really pleased to welcome in David Flynn. David Flynn, you may know as one of the people behind Fusion-io, completely changed the way in which people think about storing data, accessing data. David Flynn now the founder and CEO of a company called Hammerspace. David, good to see you, thanks for coming on. >> David: Good to see you too. >> And Dr. Nelu Mihai is the CEO and founder of Cloud of Clouds. He's actually built a Supercloud. We're going to get into that. Nelu, thanks for coming on. >> Thank you, Happy New Year. >> Yeah, Happy New Year. So I'm going to start right off with a little debate that's going on in the community if you guys would bring out this slide. So Bob Muglia early today, he gave a definition of Supercloud. He felt like we had to tighten ours up a little bit. He said a Supercloud is a platform, underscoring platform, that provides programmatically consistent services hosted on heterogeneous cloud providers. Now, Nelu, we have this shared doc, and you've been in there. You responded, you said, well, hold on. Supercloud really needs to be an architecture, or else we're going to have this stove pipe of stove pipes, really. And then you went on with more detail, what's the information model? What's the execution model? How are users going to interact with Supercloud? So I start with you, why architecture? The inference is that a platform, the platform provider's responsible for the architecture? Why does that not work in your view? >> No, the, it's a very interesting question. So whenever I think about platform, what's the connotation, you think about monolithic system? Yeah, I mean, I don't know whether it's true or or not, but there is this connotation of of monolithic. On the other hand, if you look at what's a problem right now with HyperClouds, from the customer perspective, they're very complex. There is a heterogeneous world where actually every single one of this HyperClouds has their own architecture. You need rocket scientists to build a cloud applications. Always there is this contradiction between cost and performance. They fight each other. And I'm quoting here a former friend of mine from Bell Labs who work at AWS who used to say "Cloud is cheap as long as you don't use it too much." (group chuckles) So clearly we need something that kind of plays from the principle point of view the role of an operating system, that seats on top of this heterogeneous HyperCloud, and there's nothing wrong by having these proprietary HyperClouds, think about processors, think about operating system and so on, so forth. But in order to build a system that is simple enough, I think we need to go deeper and understand. >> So the argument, the counterargument to that, David, is you'll never get there. You need a proprietary system to get to market sooner, to solve today's problem. Now I don't know where you stand on this platform versus architecture. I haven't asked you, but. >> I think there are aspects of both for sure. I mean it needs to be an architecture in the sense that it's broad based and open and so forth. But you know, platform, you could say as long as people can instantiate it themselves, on their own infrastructure, as long as it's something that can be deployed as, you know, software defined, you don't want the concept of platform being the monolith, you know, combined hardware and software. So it really depends on what you're focused on when you're saying platform, you know, I'd say as long as they software defined thing, to where it can literally run anywhere. I mean, because I really think what we're talking about here is the original concept of cloud computing. The ability to run anything anywhere, without having to care about the physical infrastructure. And what we have today is not that, the cloud today is a big mainframe in the sky, that just happens to be large enough that once you select which region, generally you have enough resources. But, you know, nowadays you don't even necessarily have enough resources in one region. and then you're kind of stuck. So we haven't really gotten to that utility model of computing. And you're also asked to rewrite your application, you know, to abandon the conveniences of high performance file access. You got to rewrite it to use object storage stuff. We have to get away from that. >> Okay, I want to just drill on that, 'cause I think I like that point about, there's not enough availability, but on the developer cloud, the original AWS premise was targeting developers, 'cause at that time, you have to provision a Sun box get a Cisco DSU/CSU, now you get on the cloud. But I think you're giving up the scale question, 'cause I think right now, scale is huge, enterprise grade versus cloud for developers. >> That's Right. >> Because I mean look at, Amazon, Azure, they got compute, they got storage, they got queuing, and some stuff. If you're doing a startup, you throw your app up there, localhost to cloud, no big deal. It's the scale thing that gets me- >> And you can tell by the fact that, in regions that are under high demand, right, like in London or LA, at least with the clients we work with in the median entertainment space, it costs twice as much for the exact same cloud instances that do the exact same amount of work, as somewhere out in rural Canada. So why is it you have such a cost differential, it has to do with that supply and demand, and the fact that the clouds aren't really the ability to run anything anywhere. Even within the same cloud vendor, you're stuck in a specific region. >> And that was never the original promise, right? I mean it was, we turned it into that. But the original promise was get rid of the heavy lifting of IT. >> Not have to run your own, yeah, exactly. >> And then it became, wow, okay I can run anywhere. And then you know, it's like web 2.0. You know people say why Supercloud, you and I talked about this, why do you need a name for Supercloud? It's like web 2.0. >> It's what Cloud was supposed to be. >> It's what cloud was supposed to be, (group laughing and talking) exactly, right. >> Cloud was supposed to be run anything anywhere, or at least that's what we took it as. But you're right, originally it was just, oh don't have to run your own infrastructure, and you can choose somebody else's infrastructure. >> And you did that >> But you're still bound to that. >> Dave: And People said I want more, right? >> But how do we go from here? >> That's, that's actually, that's a very good point, because indeed when the first HyperClouds were designed, were designed really focus on customers. I think Supercloud is an opportunity to design in the right way. Also having in mind the computer science rigor. And we should take advantage of that, because in fact actually, if cloud would've been designed properly from the beginning, probably wouldn't have needed Supercloud. >> David: You wouldn't have to have been asked to rewrite your application. >> That's correct. (group laughs) >> To use REST interfaces to your storage. >> Revisist history is always a good one. But look, cloud is great. I mean your point is cloud is a good thing. Don't hold it back. >> It is a very good thing. >> Let it continue. >> Let it go as as it is. >> Yeah, let that thing continue to grow. Don't impose restrictions on the cloud. Just refactor what you need to for scale or enterprise grade or availability. >> And you would agree with that, is that true or is it problem you're solving? >> Well yeah, I mean it, what the cloud is doing is absolutely necessary. What the public cloud vendors are doing is absolutely necessary. But what's been missing is how to provide a consistent interface, especially to persistent data. And have it be available across different regions, and across different clouds. 'cause data is a highly localized thing in current architecture. It only exists as rendered by the storage system that you put it in. Whether that's a legacy thing like a NetApp or an Isilon or even a cloud data service. It's localized to a specific region of the cloud in which you put that. We have to delocalize data, and provide a consistent interface to it across all sites. That's high performance, local access, but to global data. >> And so Walmart earlier today described their, what we call Supercloud, they call it the Walmart cloud native platform. And they use this triplet model. They have AWS and Azure, no, oh sorry, no AWS. They have Azure and GCP and then on-prem, where all the VMs live. When you, you know, probe, it turns out that it's only stateless in the cloud. (John laughs) So, the state stuff- >> Well let's just admit it, there is no such thing as stateless, because even the application binaries and libraries are state. >> Well I'm happy that I'm hearing that. >> Yeah, okay. >> Because actually I have a lot of debate (indistinct). If you think about no software running on a (indistinct) machine is stateless. >> David: Exactly. >> This is something that was- >> David: And that's data that needs to be distributed and provided consistently >> (indistinct) >> Across all the clouds, >> And actually, it's a nonsense, but- >> Dave: So it's an illusion, okay. (group talks over each other) >> (indistinct) you guys talk about stateless. >> Well, see, people make the confusion between state and persistent state, okay. Persistent state it's a different thing. State is a different thing. So, but anyway, I want to go back to your point, because there's a lot of debate here. People are talking about data, some people are talking about logic, some people are talking about networking. In my opinion is this triplet, which is data logic and connectivity, that has equal importance. And actually depending on the application, can have the center of gravity moving towards data, moving towards what I call execution units or workloads. And connectivity is actually the most important part of it. >> David: (indistinct). >> Some people are saying move the logic towards the data, some other people, and you are saying actually, that no, you have to build a distributed data mesh. What I'm saying is actually, you have to consider all these three variables, all these vector in order to decide, based on application, what's the most important. Because sometimes- >> John: So the application chooses >> That's correct. >> Well it it's what operating systems were in the past, was principally the thing that runs and manages the jobs, the job scheduler, and the thing that provides your persistent data (indistinct). >> Okay. So we finally got operating system into the equation, thank you. (group laughs) >> Nelu: I actually have a PhD in operating system. >> Cause what we're talking about is an operating system. So forget platform or architecture, it's an operating environment. Let's use it as a general term. >> All right. I think that's about it for me. >> All right, let's take (indistinct). Nelu, I want ask you quick, 'cause I want to give a, 'cause I believe it's an operating system. I think it's going to be a reset, refactored. You wrote to me, "The model of Supercloud has to be open theoretical, has to satisfy the rigors of computer science, and customer requirements." So unique to today, if the OS is going to be refactored, it's not going to be, may or may not be Red Hat or somebody else. This new OS, obviously requirements are for customers too but is what's the computer science that is needed? Where are we, what's the missing? Where's the science in this shift? It's not your standard OS it's not like an- (group talks over each other) >> I would beg to differ. >> (indistinct) truly an operation environment. But the, if you think about, and make analogies, what you need when you design a distributed system, well you need an information model, yeah. You need to figure out how the data is located and distributed. You need a model for the execution units, and you need a way to describe the interactions between all these objects. And it is my opinion that we need to go deeper and formalize these operations in order to make a step forward. And when we design Supercloud, and design something that is better than the current HyperClouds. And actually that is when we design something better, you make a system more efficient and it's going to be better from the cost point of view, from the performance point of view. But we need to add some math into all this customer focus centering and I really admire AWS and their executive team focusing on the customer. But now it's time to go back and see, if we apply some computer science, if you try to formalize to build a theoretical model of cloud, can we build a system that is better than existing ones? >> So David, how do you- >> this is what I'm saying. >> That's a good question >> How do You see the operating system of a, or operating environment of a decentralized cloud? >> Well I think it's layered. I mean we have operating systems that can run systems quite efficiently. Linux has sort of one in the data center, but we're talking about a layer on top of that. And I think we're seeing the emergence of that. For example, on the job scheduling side of things, Kubernetes makes a really good example. You know, you break the workload into the most granular units of compute, the containerized microservice, and then you use a declarative model to state what is needed and give the system the degrees of freedom that it can choose how to instantiate it. Because the thing about these distributed systems, is that the complexity explodes, right? Running a piece of hardware, running a single server is not a problem, even with all the many cores and everything like that. It's when you start adding in the networking, and making it so that you have many of them. And then when it's going across whole different data centers, you know, so, at that level the way you solve this is not manually (group laughs) and not procedurally. You have to change the language so it's intent based, it's a declarative model, and what you're stating is what is intended, and you're leaving it to more advanced techniques, like machine learning to decide how to instantiate that service across the cluster, which is what Kubernetes does, or how to instantiate the data across the diverse storage infrastructure. And that's what we do. >> So that's a very good point because actually what has been neglected with HyperClouds is really optimization and automation. But in order to be able to do both of these things, you need, I'm going back and I'm stubborn, you need to have a mathematical model, a theoretical model because what does automation mean? It means that we have to put machines to do the work instead of us, and machines work with what? Formula, with algorithms, they don't work with services. So I think Supercloud is an opportunity to underscore the importance of optimization and automation- >> Totally agree. >> In HyperCloud, and actually by doing that, we can also have an interesting connotation. We are also contributing to save our planet, because if you think right now. we're consuming a lot of energy on this HyperClouds and also all this AI applications, and I think we can do better and build the same kind of application using less energy. >> So yeah, great point, love that call out, the- you know, Dave and I always joke about the old, 'cause we're old, we talk about, you know, (Nelu Laughs) old history, OS/2 versus DOS, okay, OS's, OS/2 is silly better, first threaded OS, DOS never went away. So how does legacy play into this conversation? Because I buy the theoretical, I love the conversation. Okay, I think it's an OS, totally see it that way myself. What's the blocker? Is there a legacy that drags it back? Is the anchor dragging from legacy? Is there a DOS OS/2 moment? Is there an opportunity to flip the script? This is- >> I think that's a perfect example of why we need to support the existing interfaces, Operating Systems, real operating systems like Linux, understands how to present data, it's called a file system, block devices, things that that plumb in there. And by, you know, going to a REST interface and S3 and telling people they have to rewrite their applications, you can't even consume your application binaries that way, the OS doesn't know how to pull that sort of thing. So we, to get to cloud, to get to the ability to host massive numbers of tenants within a centralized infrastructure, you know, we abandoned these lower level interfaces to the OS and we have to go back to that. It's the reason why DOS ultimately won, is it had the momentum of the install base. We're seeing the same thing here. Whatever it is, it has to be a real file system and not a come down file system >> Nelu, what's your reaction, 'cause you're in the theoretical bandwagon. Let's get your reaction. >> No, I think it's a good, I'll give, you made a good analogy between OS/2 and DOS, but I'll go even farther saying, if you think about the evolution operating system didn't stop the evolution of underlying microprocessors, hardware, and so on and so forth. On the contrary, it was a catalyst for that. So because everybody could develop their own hardware, without worrying that the applications on top of operating system are going to modify. The same thing is going to happen with Supercloud. You're going to have the AWSs, you're going to have the Azure and the the GCP continue to evolve in their own way proprietary. But if we create on top of it the right interface >> The open, this is why open is important. >> That's correct, because actually you're going to see sometime ago, everybody was saying, remember venture capitals were saying, "AWS killed the world, nobody's going to come." Now you see what Oracle is doing, and then you're going to see other players. >> It's funny, Amazon's trying to be more like Microsoft. Microsoft's trying to be more like Amazon and Google- Oracle's just trying to say they have cloud. >> That's, that's correct, (group laughs) so, my point is, you're going to see a multiplication of this HyperClouds and cloud technology. So, the system has to be open in order to accommodate what it is and what is going to come. Okay, so it's open. >> So the the legacy- so legacy is an opportunity, not a blocker in your mind. And you see- >> That's correct, I think we should allow them to continue to to to be their own actually. But maybe you're going to find a way to connect with it. >> Amazon's the processor, and they're on the 80 80 80 right? >> That's correct. >> You're saying you love people trying to get put to work. >> That's a good analogy. >> But, performance levels you say good luck, right? >> Well yeah, we have to be able to take traditional applications, high performance applications, those that consume file system and persistent data. Those things have to be able to run anywhere. You need to be able to put, put them onto, you know, more elastic infrastructure. So, we have to actually get cloud to where it lives up to its billing. >> And that's what you're solving for, with Hammerspace, >> That's what we're solving for, making it possible- >> Give me the bumper sticker. >> Solving for how do you have massive quantities of unstructured file data? At the end of the day, all data ultimately is unstructured data. Have that persistent data available, across any data center, within any cloud, within any region on-prem, at the edge. And have not just the same APIs, but have the exact same data sets, and not sucked over a straw remote, but at extreme high performance, local access. So how do you have local access to globally shared distributed data? And that's what we're doing. We are orchestrating data globally across all different forms of storage infrastructure, so you have a consistent access at the highest performance levels, at the lowest level innate built into the OS, how to consume it as (indistinct) >> So are you going into the- all the clouds and natively building in there, or are you off cloud? >> So This is software that can run on cloud instances and provide high performance file within the cloud. It can take file data that's on-prem. Again, it's software, it can run in virtual or on physical servers. And it abstracts the data from the existing storage infrastructure, and makes the data visible and consumable and orchestratable across any of it. >> And what's the elevator pitch for Cloud of Cloud, give that too. >> Well, Cloud of Clouds creates a theoretical model of cloud, and it describes every single object in the cloud. Where is data, execution units, and connectivity, with one single class of very simple object. And I can, I can give you (indistinct) >> And the problem that solves is what? >> The problem that solves is, it creates this mathematical model that is necessary in order to do other interesting things, such as optimization, using sata engines, using automation, applying ML for instance. Or deep learning to automate all this clouds, if you think about in the industrial field, we know how to manage and automate huge plants. Why wouldn't it do the same thing in cloud? It's the same thing you- >> That's what you mean by theoretical model. >> Nelu: That's correct. >> Lay out the architecture, almost the bones of skeleton or something, or, and then- >> That's correct, and then on top of it you can actually build a platform, You can create your services, >> when you say math, you mean you put numbers to it, you kind of index it. >> You quantify this thing and you apply mathematical- It's really about, I can disclose this thing. It's really about describing the cloud as a knowledge graph for every single object in the graph for node, an edge is a vector. And then once you have this model, then you can apply the field theory, and linear algebra to do operation with these vectors. And it's, this creates a very interesting opportunity to let the math do this thing for us. >> Okay, so what happens with hyperscale, or it's like AWS in your model. >> So in, in my model actually, >> Are they happy with this, or they >> I'm very happy with that. >> Will they be happy with you? >> We create an interface to every single HyperCloud. We actually, we don't need to interface with the thousands of APIs, but you know, if we have the 80 20 rule, and we map these APIs into this graph, and then every single operation that is done in this graph is done from the beginning, in an optimized manner and also automation ready. >> That's going to be great. David, I want us to go back to you before we close real quick. You've had a lot of experience, multiple ventures on the front end. You talked to a lot of customers who've been innovating. Where are the classic (indistinct)? Cause you, you used to sell and invent product around the old school enterprises with storage, you know that that trajectory storage is still critical to store the data. Where's the classic enterprise grade mindset right now? Those customers that were buying, that are buying storage, they're in the cloud, they're lifting and shifting. They not yet put the throttle on DevOps. When they look at this Supercloud thing, Are they like a deer in the headlights, or are they like getting it? What's the, what's the classic enterprise look like? >> You're seeing people at different stages of adoption. Some folks are trying to get to the cloud, some folks are trying to repatriate from the cloud, because they've realized it's better to own than to rent when you use a lot of it. And so people are at very different stages of the journey. But the one thing that's constant is that there's always change. And the change here has to do with being able to change the location where you're doing your computing. So being able to support traditional workloads in the cloud, being able to run things at the edge, and being able to rationalize where the data ought to exist, and with a declarative model, intent-based, business objective-based, be able to swipe a mouse and have the data get redistributed and positioned across different vendors, across different clouds, that, we're seeing that as really top of mind right now, because everybody's at some point on this journey, trying to go somewhere, and it involves taking their data with them. (John laughs) >> Guys, great conversation. Thanks so much for coming on, for John, Dave. Stay tuned, we got a great analyst power panel coming right up. More from Palo Alto, Supercloud 2. Be right back. (bouncy music)

>>Hello everyone. Welcome to the Super Cloud Event preview. I'm John Forry, host of the Cube, and with Dave Valante, host of the popular Super cloud events. This is Super Cloud two preview. I'm joined by industry leader and Cube alumni, Victoria Vigo, vice president of klos Cross Cloud Services at VMware. Vittorio. Great to see you. We're here for the preview of Super Cloud two on January 17th, virtual event, live stage performance, but streamed out to the audience virtually. We're gonna do a preview. Thanks for coming in. >>My pleasure. Always glad to be here. >>It's holiday time. We had the first super cloud on in August prior to VMware, explore North America prior to VMware, explore Europe prior to reinvent. We've been through that, but right now, super Cloud has got momentum. Super Cloud two has got some success. Before we dig into it, let's take a step back and set the table. What is Super Cloud and why is important? Why are people buzzing about it? Why is it a thing? >>Look, we have been in the cloud now for like 10, 15 years and the cloud is going strong and I, I would say that going cloud first was deliberate and strategic in most cases. In some cases the, the developer was going for the path of risk resistance, but in any sizable company, this caused the companies to end up in a multi-cloud world where 85% of the companies out there use two or multiple clouds. And with that comes what we call cloud chaos, because each cloud brings their own management tools, development tools, security. And so that increase the complexity and cost. And so we believe that it's time to usher a new era in cloud computing, which we, you call the super cloud. We call it cross cloud services, which allows our customers to have a single way to build, manage, secure, and access any application across any cloud. Lowering the cost and simplifying the environment. Since >>Dave Ante and I introduced and rift on the concept of Supercloud, as we talked about at reinvent last year, a lot has happened. Supercloud one, it was in August, but prior to that, great momentum in the industry. Great conversation. People are loving it, they're hating it, which means it's got some traction. Berkeley has come on board as with a position paper. They're kind of endorsing it. They call it something different. You call it cross cloud services, whatever it is. It's kind of the same theme we're seeing. And so the industry has recognized something is happening that's different than what Cloud one was or the first generation of cloud. Now we have something different. This Super Cloud two in January. This event has traction with practitioners, customers, big name brands, Sachs, fifth Avenue, Warner, media Financial, mercury Financial, other big names are here. They're leaning in. They're excited. Why the traction in the customer's industry converts over to, to the customer traction. Why is it happening? You, you get a lot of data. >>Well, in, in Super Cloud one, it was a vendor fest, right? But these vendors are smart people that get their vision from where, from the customers. This, this stuff doesn't happen in a vacuum. We all talk to customers and we tend to lean on the early adopters and the early adopters of the cloud are the ones that are telling us, we now are in a place where the complexity is too much. The cost is ballooning. We're going towards slow down potentially in the economy. We need to get better economics out of, of our cloud. And so every single customers I talked to today, or any sizable company as this problem, the developers have gone off, built all these applications, and now the business is coming to the operators and asking, where are my applications? Are they performing? What is the security posture? And how do we do compliance? And so now they're realizing we need to do something about this or it is gonna be unmanageable. >>I wanna go to a clip I pulled out from the, our video data lake and the cube. If we can go to that clip, it's Chuck Whitten Dell at a keynote. He was talking about what he calls multi-cloud by default, not by design. This is a state of the, of the industry. If we're gonna roll that clip, and I wanna get your reaction to that. >>Well, look, customers have woken up with multiple clouds, you know, multiple public clouds. On-premise clouds increasingly as the edge becomes much more a reality for customers clouds at the edge. And so that's what we mean by multi-cloud by default. It's not yet been designed strategically. I think our argument yesterday was it can be, and it should be, it is a very logical place for architecture to land because ultimately customers want the innovation across all of the hyperscale public clouds. They will see workloads and use cases where they wanna maintain an on-premise cloud. On-premise clouds are not going away. I mentioned edge Cloud, so it should be strategic. It's just not today. It doesn't work particularly well today. So when we say multi-cloud, by default we mean that's the state of the world. Today, our goal is to bring multi-cloud by design, as you heard. Yeah, I >>Mean, I, okay, Vittorio, that's, that's the head of Dell Technologies president. He obvious he runs it. Michael Dell's still around, but you know, he's the leader. This is a interesting observation. You know, he's not a customer. We have some customer equips we'll go to as well, but by default it kind of happened not by design. So we're now kind of in a zoom out issue where, okay, I got this environment just landed on me. What, what is the, what's your reaction to that clip of how multi-cloud has become present in, in everyone's on everyone's plate right now to deal with? Yeah, >>I it is, it is multi-cloud by default, I would call it by accident. We, we really got there by accident. I think now it's time to make it a strategic asset because look, we're using multiple cloud for a reason, because all these hyperscaler bring tremendous innovation that we want to leverage. But I strongly believe that in it, especially history repeat itself, right? And so if you look at the history of it, as was always when a new level of obstruction that simplify things, that we got the next level of innovation at the lower cost, you know, from going from c plus plus to Visual basic, going from integrating application at the bits of by layer to SOA and then web services. It's, it's only when we simplify the environment that we can go faster and lower cost. And the multi-cloud is ready for that level of obstruction today. >>You know, you've made some good points. You know, developers went crazy building great apps. Now they got, they gotta roll it out and operationalize it globally. A lot of compliance issues going on. The costs are going up. We got an economic challenge, but also agility with the cloud. So using cloud and or hybrid, you can get better agility. And also moving to the cloud, it's kind of still slow. Okay, so I get that at reinvent this year and at VMware explorer we were observing and we reported that you're seeing a transition to a new kind of ecosystem partner. Ones that aren't just ISVs anymore. You have ISVs, independent software vendors, but you got the emergence of bigger players that just, they got platforms, they have their own ecosystems. So you're seeing ecosystems on top of ecosystems where, you know, MongoDB CEO and the Databricks CEO both told me, we're not an isv, we're a platform built on a cloud. So this new kind of super cloudlike thing is going on. Why should someone pay attention to the super cloud movement? We're on two, we're gonna continue to do these out in the open. Anyone can participate. Why should people pay attention to this? Why should they come to the event? Why is this important? Is this truly an inflection point? And if they do pay attention, what should they pay attention to? >>I would pay attention to two things. If you are customers that are now starting to realize that you have a multi-cloud problem and the costs are getting outta control, look at what the leading vendors are saying, connect the dots with the early adopters and some of the customers that we are gonna have at Super Cloud two, and use those learning to not fall into the same trap. So I, I'll give you an example. I was talking to a Fortune 50 in Europe in my latest trip, and this is an a CIO that is telling me >>We build all these applications and now for compliance reason, the business is coming to me, I don't even know where they are, right? And so what I was telling him, so look, there are other customers that are already there. What did they do? They built a platform engineering team. What is the platform? Engineering team is a, is an operation team that understands how developers build modern applications and lays down the foundation across multiple clouds. So the developers can be developers and do their thing, which is writing code. But now you as a cio, as a, as a, as a governing body, as a security team can have the guardrail. So do you know that these applications are performing at a lower cost and are secure and compliant? >>Patura, you know, it's really encouraging and, and love to get your thoughts on this is one is the general consensus of industry leaders. I talked to like yourself in the round is the old way was soft complexity with more complexity. The cloud demand simplicity, you mentioned abstraction layer. This is our next inflection point. It's gotta be simpler and it's gotta be easy and it's gotta be performant. That's the table stakes of the cloud. What's your thoughts on this next wave of simplicity versus complexity? Because again, abstraction layers take away complexity, they should make it simpler. What's your thoughts? >>Yeah, so I'll give you few examples. One, on the development side and runtime. You, you one would think that Kubernetes will solve all the problems you have Kubernetes everywhere, just look at, but every cloud has a different distribution of Kubernetes, right? So for example, at VMware with tansu, we create a single place that allows you to deploy that any Kubernetes environment. But now you have one place to set your policies. We take care of the differences between this, this system. The second area is management, right? So once you have all everything deployed, how do you get a single object model that tells you where your stuff is and how it's performing, and then apply policies to it as well. So these are two areas and security and so on and so forth. So the idea is that figure out what you can abstract and make common across cloud. Make that simple and put it in one place while always allowing the developers to go underneath and use the differentiated features for innovation. >>Yeah, one of the areas I'm excited, I want to get your thoughts of too is, we haven't talked about this in the past, but it, I'll throw it out there. I think the, the new AI coming out chat, G P T and other things like lens, you see it and see new kinds of AI coming that's gonna be right in the heavy lifting opportunity to make things easier with AI and automation. I think AI will be a big factor in super cloud and, and cross cloud. What's your thoughts? >>Well, the one way to look at AI is, is one of the main, main services that you would want out of a multi-cloud, right? You want eventually, right now Google seems to have an edge, but you know, the competition creates, you know, innovation. So later on you wanna use something from Azure or from or from Oracle or something that, so you want at some point that is gonna be prone every single service in in the cloud is gonna be prone to obstruction and simplification. And I, I'm just excited about to see >>What book, I can't wait for the chat services to write code automatically for us. Well, >>They >>Do, they do. They're doing it now. They do. >>Oh, the other day, somebody, you know that I do this song par this for. So for fun sometimes. And somebody the other day said, ask the AI to write a parody song for multi-cloud. And so I have the lyrics stay >>Tuned. I should do that from my blog post. Hey, write a blog post on this January 17th, Victoria, thanks for coming in, sharing the preview bottom line. Why should people come? Why is it important? What's your final kind of takeaway? Billboard message >>History is repeat itself. It goes to three major inflection points, right? We had the inflection point with the cloud and the people that got left behind, they were not as competitive as the people that got on top o of this wave. The new wave is the super cloud, what we call cross cloud services. So if you are a customer that is experiencing this problem today, tune in to to hear from other customers in, in your same space. If you are behind, tune in to avoid the, the, the, the mistakes and the, the shortfalls of this new wave. And so that you can use multi-cloud to accelerate your business and kick butt in the future. >>All right. Kicking kick your names and kicking butt. Okay, we're here on J January 17th. Super Cloud two. Momentum continues. We'll be super cloud three. There'll be super cloud floor. More and more open conversations. Join the community, join the conversation. It's open. We want more voices. We want more, more industry. We want more customers. It's happening. A lot of momentum. Victoria, thank you for your time. Thank you. Okay. I'm John Farer, host of the Cube. Thanks for watching.

>>Good afternoon and welcome back to the Classiest Show in Technology. This is the Cube we are at AWS Reinvent 2022 in Fabulous Sin City. That's why I've got my sequence on. We love a little Vegas, don't we? I'm joined by John Farer, another, another Vegas >>Fan. I don't have my sequence, I left it in my room. We're >>Gonna have to figure out how to get us 20 as soon as possible. What's been your biggest shock for you at the show so far? >>Well, I think the data story and security is so awesome. I love how that's front and center. If you look at the minutes of the keynote of Adamski, the CEO on day one, it's all bulked into data and security. All worked hand in hand. That's on top of already the innovation of their infrastructure. So I think you're gonna see a lot of interplay going on in this next segment. It's gonna tell a lot of that innovation story that's coming next. It's pretty awesome. >>It is pretty awesome, and I'm super excited. It's not only what we do here on the Cube, it's also in my show notes. We are gonna be geeking out for the next segment. Please welcome Paul and Puja. Wonderful to have you both here. Paul from Amazon, s3, glacier, and Pujan, CEO of kuo. I wanna turn to you Pujan, to start us off, just in case the audience isn't familiar, give us the Kuo pitch. >>Yeah, so basically Kuo is a, a backup as a service offering, right? Built in AWS four aws, right? And effectively going after, you know, any service that a customer uses on top of aws, right? And so a lot of the data sitting on s3, right? So that's been like our, our big use case going and basically building backup and air gap protection for, for s3. But we basically go to every other service, e c two, ebs, dynamo, you know, you name it, right? So basically do the whole thing >>And the relationship with aws. Can you guys share, I mean, you got you here together. You guys are a great partnership. Born in the cloud, operation in the cloud. Absolutely. I think talk about the partnership with aws. >>Absolutely. I think the last five years of building on AWS has been phenomenal, right? And I love the platform. It's, it's a very pure platform for us. You know, the APIs and, and the access you get and access you get to the service teams like Paul sitting here and the other teams you have gotten access to, I think has been phenomenal. But we also have, I would say, pushed the envelope in terms of how innovative we have been and how aggressive we have been in utilizing all the innovation that AWS has built in over the last few years. But it would not have happened without the fantastic partnership with the service teams. >>Paul, talk about the, AM the S3 part of this. What's the story there? >>Well, it's been great working with the CUO team over the course of the last few years. We were just upstairs diving deep into the, to the features that they're taking advantage of. They really push us hard on behalf of customers, and it's been a, it's just been a great relationship over the last years. >>That's awesome. And the ecosystem at such a, we're gonna hear tomorrow, the keynote on the, from Aruba who's gonna tend over the ecosystem. You guys are working together. There's a lot of strategic partnerships, so much collaboration between you guys that makes it very, this is the next gen cloud of cloud environment we're seeing. And you heard the, the economies around the corner. It's still gonna be challenging, but still there's more growth in the cloud. This is not stopping. This is impacts the customers. What are the customers saying to you guys when you work backwards from their needs? They want it faster, easier, cheaper. They want it more integrated. What are some of the things, all those you guys hearing from customers? >>So for us, you know, if you think about it, like, you know, as people are moving to the cloud, especially like take a use case like s3, right? So much of critical data sitting on top of S3 today. And so what folks have realized that as they're, you know, putting all of those, you know, what, over two 50 trillion objects, you know, sitting on s3, a lot of them need backup and data protection because there could be accidental deletions, there could be software bugs, there could be a ransomware type event due to which you need a second copy of the data that is outside of your security domain, right? But again, that needs to get be done at the, at the right price point, right? And that's where like a technology like Columbia comes in because since we've been built on the cloud, we've optimized it correctly. So especially for folks who are very cost conscious, given the macroeconomic conditions, we are heading into a technology that's built correctly so that, you know, you get the right architecture and the right solution at the right price point and the scale, right? Talking about trillions of objects, billions of objects within a single customer, within a single bucket sometimes. And that's where Columbia comes in. Cause we basically do that at scale without, again, impacting the, the customer's wallet more than it needs to. >>The porridge has to be the right temperature and the right size bowl. With the right spoon. You've got a lot of complexity when it comes to solving those customer challenges. You have a couple customer story examples you're allowed to share with us. Correct? Paul, do you want to kick one off? Go ahead. Oh, puja. All right. >>No, absolutely. I think there's a ton of them. I, I'll talk about, you know, want to begin with like Cox Automotive, right? A phenomenal customer that we, all of us have worked together with them. And again, looking for a solution to backup S3 to essentially go air gap protection outside of their account, right? They looked at doing it themselves, right? They thought they'll go and basically do it themselves. And then they fortunately bumped into Columbia, they looked at our architecture, looked at what it would really go and take to build it. And guess what, sitting in 2022, getting 23 right now, nobody wants to go and build this themselves. They actually want a turnkey solution that just does it, right? And so, again, we are a phenomenal joint customer of ours doing this at a pretty massive scale, right? And there are many more like that. There's Warner Brothers that are essentially going into the cloud from on premises, right? And they're going really fast accelerating the usage on aws again, looking at, you know, backup and data protection and using clum because of our extreme simplicity that we provide. >>Yeah, I think it's, you've got a, a lot of different people solving different problems that you're working with all the time. Millions of customers. Well, how do you prioritize? >>Well, for us, it really all comes down to fundamentals, right? So Amazon, s3 s unique distributed architecture delivers industry leading durability, availability, performance and security at virtually unlimited scale, right? And it's really been delivering on the fundamentals that has earned the trust of so many customers of all sizes and industries over the course of over 16 years. Now, in terms of how we prioritize on behalf of those customers, we always say that 90% of our roadmap comes directly from what customers are telling us is important. And a large number of our customers now are using S3 through lumino, which is why the relationship is so important. We're here talking about customer use cases here at the show, and we do that regularly throughout the year as well. And that's, that's how we land on a road. >>And what are the, what are the top stories from customers? What, what are they telling you? What's the number one top three things you're hearing? >>I tell you, like, again, it just comes down to the fundamentals, right? Of security, availability, durability and performance at virtually unlimited scale. Like that is the first customer first discussions that we have with customers talking about durable storage, for >>Sure. What I find interesting in, you mentioned scale, right? That comes up a lot scale with data. Yeah. That we heard data. The big theme here, security, what's in my S3 bucket? Can you find out what's in there? Is it backed up properly? How do I get it back? Where's the ransomware? Why not just target the ransomware? So how do you navigate the, the security challenges, the, the need to store all that scale data? What's the secret sauce? >>Yeah, so I think the, the big thing is we'll start with the, you know, how we have architected the product, right? If you think about it, this, you're dealing with a lot of scale, right? You get to a hundred million, a billion and billions very fast on S3 few, especially on a cloud native application. So it starts with the visibility, right? It's basically about, like we have things where you do, where you create a subset of your buckets called protection groups that you can essentially, you know, do it based on prefixes. So now you can essentially figure out what prefix you want to back up and what you don't want to back up. Maybe there's log data that you don't care about, so you don't back that up, right? And it all starts with that visibility that you give. And the prefix level data protection then comes the scale, which is where I was telling you, right? We have basically built an orchestration engine, right? It's like we call the ES for Lambdas, right? So we have a internal orchestration engine and essentially what what we have done is we have our own language internally that spawns off these lambdas, right? And they go after these S3 partitions do the right things and then you basically reel them back. So things like that that we do that are not possible if you're not built on the >>Clock. Well also, I mean, just mind blowing and go back 10 years. Yeah. I mean you got Lambda. What you're talking about here is the gift of the cloud innovation. Yeah. So the benefit of S3 is now accelerated. This is the story this year. Yeah. I mean they're highlighting it at scale, not just in the data, but like what we knew when Lambda came out and what S3 could do. But now mainstream solutions are coming in. Does that change your backup plans? Because we're gonna see a lot more end to end, lot more solutions. We heard that on the keynote. Some are saying it's more complexity. Of course it might, but you can abstract another way with the cloud that's the best part of the cloud. So these abstraction leads. So what's your view on that? But I wanna get your thoughts because you guys are perfectly positioned for this scale, but there's more coming. Yes. Yes. Exactly. What, how are you looking at that? >>So again, I think the, you know, obviously the, the S3 teams and every team in AWS is basically pushing the envelope in terms of innovation. But the key for a partner like us is to go and take that innovation. A lot of complex architectures behind the scene. But what you deliver to the customer is simple. I'll give you one more example. One of the things we launched that, you know, Paul and others are very excited about, is this ability to do instant access on the backup, right? So you could have billions of objects that you backed up. Maybe you need just 10,000 of them for a DR test. And we can basically create like an instant virtual bucket on top of that backup that you can instantly restore >>Spinning up a sandbox of temporary data to go check it >>Out. Exactly. Offer an inte application. >>Think we're geeking out right now. >>Yeah, I know. Brought that part of the segment, John. Don't worry, we're safely there. But, >>But that's the thing, right? That all that is possible because of all the, the scale and innovation and all the APIs and everything that, you know, Paul and the team gives us that we go and build on top of >>Paul, geek out on with us on this. We >>Are super excited for instant restore >>For store. I mean, automation programmability. >>It is, I mean it's the logical next step for backup in the cloud. Exactly. Yeah. But it's a super hard engineering problem to go solve for customers. I mean, the RTO benefits alone are super compelling, but then there's a cost element as well of not having to bring back all that stuff for a test restore, for example. And so it's, it's been really great to, to work with the team on that. We have some ideas on how we may help solve it from our side, and we're looking forward to collaborating on it. >>This is a great illustration of what I was writing about this week around the classic cloud, which is great. And as Adam said, and used like to use the word and, and you got this new functionality we're seeing emerge from the growth. Yes. From the companies that are built on Amazon web services that are growing. You're a partner, they have a lot of other partners and people are taking over restaurant here off action. I mean, there's real growth and new functionality on top of aws. You guys are no different. What's, are you prepared for that? Are you ready to go? >>Yeah, no, absolutely. And I think if you think about, if you think about it, right, I think it's also about doing this without impacting the primary application. Like if the customer is running a primary application at scale on s3, a backup application like ours can't come in and really mess with that. So I think being able to do things where, and this is where you solve really hard computer science problems, right? Where you're bottling yourself. If you are essentially seeing any kind of, you know, interfering with the primary, you're going to cut yourself down. You're gonna go after a different partition. So there are a lot of things you need to do behind the scenes, which is again, all the complexity, all of that, but deliver the, to the customer a very, very simple thing. >>You know, Paul, I wanna get your thoughts and I want you to chime in. Yeah. In 2014, I interviewed Steven Schmidt, my first interview with the, he was the CISO then, and now he's a CSO and, and former ciso, he's back at that time, the word was the cloud's not secure. Now we're talking about security. Just in the complexity of how you're partitioning and managing your sub portions, how you explained it, it's harder for the attackers. The cloud in its in its architecture has become a more secure environment. Yeah. Well, and getting more secure as you have laying out this, this is a new dynamic. This is good. Can you explain the, >>I mean, I, I can just tell you that at AWS security is job zero and that it will always be our number one priority, right? We have a, an infrastructure with under AWS that is vetted and approved to run even top secret workloads, which benefits all customers in all regions. >>And your, your security posture is embedded on top of that. And you got your own stuff. >>Yeah. And if you think of it as a shared responsibility model, so security of the cloud is the responsibility of the cloud provider, but then security of the data on top of it. Like you, you go and delete stuff, your software goes and does something that resiliency, the integrity of the data is your responsibility as a customer. And that's where, you know, we come in. Who >>Shared responsibility has been such a hot topic all week. Yeah. >>I gotta ask him one more question. Cause this is fascinating. And we are talking about on the cube all day today after we saw the announcement and Adam's comment on the cube, Adams LE's comment on the keynote. I mean, he said, if you're gonna tighten your belt, meaning economic cost recovery, re right sizing. If you want to tighten your belt, come to the cloud. So I have to ask you guys, Puja, if you can comment, that'd be great. There's a lot of other competitors out there that aren't born on aws. What is the customer gonna do when they tighten the build? What does that mean? They're gonna go to, to the individual contracts. They're gonna work in the marketplace. I mean this, there's a new dynamic in town. It's called AWS 2022. They weren't really around much in the recession of 2008. They were just starting to grow. Now they're an economic force. People like yourselves have embedded in there. There's a lot of competition. What's gonna happen? >>I think people are gonna just go to a place like, you know, AWS marketplace. You're going to essentially look for solutions and essentially like, and, and the right solutions built in are going to be self-service like aws. It's a very self-service thing. A hundred percent. So you go and do self-service, you figure out what's working, what's not working. Also, the model has to be consumption oriented. No longer can you expect the customer to go and pay a bunch of money for shelfware, right? It's like, like how we charge how AWS charges, which is you pay for what you consume. That and all has to be front and center, >>Right? I think that's a really, I think that's a really important >>Point. It's time >>And I think it's time. So we have a new challenge on the cube. We give you 30 seconds roughly to give us your extraordinarily hot take your shining thought leadership moment and, and highlight what you think is the most important takeaway from the show. The biggest soundbite, the juiciest announcement. Paul, I'll >>Start with an Instagram. Real basically. Yeah. Okay. >>Yeah. Hi. Go. I would just say from an S3 perspective, over the course of the last several years, we've really seen workloads shift from just backup and recovery and static images on websites to data lake analytics applications. And you continue to see that here. And I can tell you that some of these scaled applications are running at enormous mind blowing scale, right? And so, so every year we come here, we talk to customers, and it's just every year it sort of blows me away. And I've been in the storage industry for a long time and it's just is, it blows me away. Just the scale at customers are running in >>And >>Blowing scale. And when it comes to backup, let me just say that it's easy to back up and recover a single object, but doing an easy thing, a billion or 10 billion times over, that's actually quite hard. >>And just to, just to bold that a little bit, just pull out my highlighter. S3 now has over 280 trillion objects. That's a lot. >>That's a lot of objects. >>Yeah. You are not, you are not kidding. When you talk about scale, I mean, this is the most scalable. >>That's not solution's not there. Yeah. That, that's right. And we wake up every, we have a culture of durability and we wake up every single day to raise the bar on the fundamentals and make sure that every single one of those objects is protected and safe. >>Okay. You, I, >>I can't imagine worrying about two, two 80 trillion different things. >>Let's go. You're Instagram real >>For me again, you know, between S3 and us, we are two players out there that are really, you know, processing the data at the end of the day, right? And so I'm very excited about, you know, what we are going to do more and more with the instant restore capability where we can integrate third party services on top of it that can do more things with the data that is not, not passively sitting, but now becomes active data that you can analyze and do things with. So that's something where we take this to the next level is something that I'm super excited about. >>There's a lot to be excited about and, and we're excited to have you. We're excited to hear what happens next. Excited to see more collaboration like this. Paul Pon, thank you so much for joining us here on the show. Thank all of you from for tuning into our continuous wall to wall super thrilling live coverage of AWS reinvent here in fabulous Las Vegas, Nevada, with John Furrier. I'm Savannah Peterson. We're the cube, the leading source for high tech coverage.

from the cube studios in Palo Alto in Boston bringing you data-driven insights from the cube and ETR this is breaking analysis with Dave vellante over the past decade cloudflare has built a Global Network that has the potential to become the fourth us-based hyperscale class cloud in our view the company is building a durable Revenue model with hooks into many important markets these include the more mature DDOS protection space to other growth sectors such as zero trust a serverless platform for application development and an increasing number of services such as database and object storage and other network services in essence cloudflare could be thought of as a giant distributed supercomputer that can connect multiple clouds and act as a highly efficient scheduling engine at scale its disruptive DNA is increasingly attracting novel startups and established Global firms alike looking for Reliable secure high performance low latency and more cost-effective alternatives to AWS and Legacy infrastructure Solutions hello and welcome to this week's wikibon Cube insights powered by ETR in this breaking analysis we initiate our deeper coverage of cloudflare we'll briefly explain our take on the company and its unique business model we'll then share some peer comparisons with both the financial snapshot and some fresh ETR survey data finally we'll share some examples of how we think cloudflare could be a disruptive force with a super cloud-like offering that in many respects is what multi-cloud should have been cloudflare has been on our peripheral radar Ben Thompson and many others have written about their disruptive business model and recently a breaking analysis follower who will remain anonymous emailed with some excellent insights on cloudflare that prompted us to initiate more detailed coverage let's first take a look at how cloudflare seize the world in terms of its view of a modern stack this is a graphic from cloudflare that shows a simple three-layer Stack comprising Storage and compute the lower level and application layer and the network and their key message is basically that the big four hyperscalers have replaced the on-prem leaders apps have been satisfied and that mess of network that you see and Security in the upper left can now be handled all by cloudflare and the stack can be rented via Opex versus requiring heavy capex investment so okay somewhat of a simplified view is those companies on the the left are you know not standing still and we're going to come back to that but cloudflare has done something quite amazing I mean it's been a while since we've invoked Russ hanneman of Silicon Valley Fame on breaking analysis but remember when he was in a meeting one of his first meetings if not the first with Richard Hendricks it was the whiz kid on the show Silicon Valley and hanneman said something like if you had a blank check and you could build anything in the world what would it be and Richard's answer was basically a new internet and that led to Pied Piper this peer-to-peer Network powered by decentralized devices and and iPhones and this amazing compression algorithm that enabled high-speed data movement and low latency uh up to no low latency access across the network well in a way that's what cloudflare has built its founding premise reimagined how the internet should be built with a consistent set of server infrastructure where each server had lots of cores lots of dram lots of cash fast ssds and plenty of network connectivity and bandwidth and well this picture makes it look like a bunch of dots and points of presence on a map which of course it is there's a software layer that enables cloudflare to efficiently allocate resources across this Global Network the company claims that it's Network utilization is in the 70 percent range and it has used its build out to enter the technology space from the bottoms up offering for example free tiers of services to users with multiple entry points on different services and selling then more services over time to a customer which of course drives up its average contract value and its lifetime value at the same time the company continues to innovate and add new services at a very rapid cloud-like Pace you can think of cloudflare's initial Market entry as like a lightweight Cisco as a service the company's CFO actually he uses that term he calls it that which really must tick off Cisco who of course has a massive portfolio and a dominant Market position now because it owns the network cloudflare is a marginal cost of adding new Services is very small and goes towards zero so it's able to get software like economics at scale despite all this infrastructure that's building out so it doesn't have to constantly face the increasing infrastructure tax snowflake for example doesn't own its own network infrastructure as it grows it relies on AWS or Azure gcp and and while it gives the company obvious advantages it doesn't have to build out its own network it also requires them to constantly pay the tax and negotiate with hyperscalers for better rental rates now as previously mentioned Cloud Fair cloudflare claims that its utilization is very high probably higher than the hyperscalers who can spin up servers that they can charge for underutilized customer capacity cloudflare also has excellent Network traffic data that it can use to its Advantage with its Analytics the company has been rapidly innovating Beyond its original Core Business adding as I said before serverless zero trust offerings it has announced a database it calls its database D1 that's pretty creative and it's announced an object store called R2 that is S3 minus one both from the alphabet and the numeric I.E minus the egress cost saying no egress cost that's their big claim to fame and they've made a lot of marketing noise around about that and of course they've promised in our a D2 database which of course is R2D2 RR they've launched a developer platform cloudflare can be thought of kind of like first of all a modern CDN they've got a simpler security model that's how they compete for example with z-scaler that brings uh they also bring VPN sd-wan and DDOS protection services that are that are part of the network and they're less expensive than AWS that's kind of their sort of go to market and messaging and value proposition and they're positioning themselves as a neutral Network that can connect across multiple clouds now to be clear unlike AWS in particular cloudflare is not well suited to lift and shift your traditional apps like for instance sap Hana you're not going to run that in on cloudflare's platform rather the company started by making websites more secure and faster and it flew under the radar and much in the same way that clay Christensen described the disruption in the steel industry if you've seen that where new entrants picked off the low margin rebar business then moved up the stack we've used that analogy in the semiconductor business with arm and and even China cloudflare is running a similar playbook in the cloud and in the network so in the early part of the last decade as aws's ascendancy was becoming more clear many of us started thinking about how and where firms could compete and add value as AWS is becoming so dominant so for instance take an industry Focus you could do things like data sharing with snowflake eventually you know uh popularized you could build on top of clouds again snowflake is doing that as are others you could build private clouds and of course connect to hybrid clouds but not many had the wherewithal and or the hutzpah to build out a Global Network that could serve as a connecting platform for cloud services cloudflare has traction in the market as it adds new services like zero trust and object store or database its Tam continues to grow here's a quick snapshot of cloudflare's financials relative to Z scalar which is both a competitor and a customer fastly which is a smaller CDN and Akamai a more mature CDN slash Edge platform cloudflare and fastly both reported earnings this past week Cloud Fair Cloud flare surpassed a billion dollar Revenue run rate but they gave tepid guidance and the stock got absolutely crushed today which is Friday but the company's business model is sound it's growing close to 50 annually it has sas-like gross margins in the mid to high 70s and it's it it's got a very strong balance sheet and a 13x revenue run rate multiple in fact it's Financial snapshot is quite close to that of z-scaler which is kind of interesting which zinc sailor of course doesn't own its own network that's a pure play software company fastly is much smaller and growing more slowly than cloudflare hence its lower multiple well Akamai as you can see is a more mature company but it's got a nice business now on its earnings call this week cloudflare announced that its head of sales was stepping down and the company has brought in a new leader to take the firm to five billion dollars in sales I think actually its current sales leader felt like hey you know my work is done here bring on somebody else to take it to the next level the company is promising to be free cash flow positive by the end of the year and is working hard toward its long-term financial model or so working towards sorry it's a long-term financial model with gross margin Targets in the mid 70s it's targeting 20 non-gaap operating margins so so solid you know very solid not like completely off the charts but you know very good and to our knowledge it has not committed to a long-term growth rate but at that sort of operating profit level you would like to see growth be consistently at least in the 20 range so they could at least be a rule of 40 company or perhaps even even five even higher if they're going to continue to command a premium valuation okay let's take a look at the ETR data ETR is very positive on cloudflare and has recently published a report on the company like many companies cloudflare is seeing an across the board slowdown in spending velocity we've reported on this quite extensively using the ETR data to quantify the degree to that Slowdown and on the data set with ETR we see that many customers they're shifting their spend to Flat spend you know plus or minus let's say you know single digits you know two three percent or even zero or in the market we're seeing a shift from paid to free tiers remember cloudflare offers a lot of free services as you're seeing customers maybe turn off the pay for a while and going with the freebie but we're also seeing some larger customers in the data and the fortune 1000 specifically they're actually spending more which was confirmed on cloudflare's earnings call they did say everything across the board was softer but they did also indicate that some of their larger customers are actually growing faster than their smaller customers and their churn is very very low here's a two-dimensional graphic we'd like to share this view a lot it's got Net score or spending momentum on the vertical axis and overlap or pervasiveness in the survey on the horizontal axis and this cut isolates three segments in the etrs taxonomy that cloudflare plays in Cloud security and networking now the table inserted in that upper left there shows the raw data which informs the position of each company in the dots with Net score in the ends listed in that rightmost column the red dotted line indicates a highly elevated Net score and finally we posted the breakdown those colors in the bottom right of cloudflare's Net score the lime green that's new adoptions the forest green is we're spending more six percent or more the gray is flat plus or minus uh five percent and you can see that the majority of customers you can see that's the majority of the customers that gray area the pink is we're spending Less in other words down six percent or worse and the bright red is churn which is minimal one percent very good indicator for for cloudflare what you do to get etr's proprietary Net score and they've done this for many many quarters so we have that time series data you subtract the Reds from the greens and that's Net score cloudflare is at 39 just under that magic red line now note that cloudflare and zscaler are right on top of each other Cisco has a dominant position on the x-axis that cloudflare and others are eyeing AWS is also dominant but note that its Net score is well above the red dotted line it's incredible Palo Alto networks is also very impressive it's got both a strong presence on the horizontal axis and it's got a Net score that's pretty comparable to cloudflare and z-scaler to much smaller companies Akamai is actually well positioned for a reasonably mature company and you can see fastly ATT Juniper and F5 have far less spending momentum on their platforms than does cloudflare but at least they are in positive Net score territory so what's going to be really interesting to see is whether cloudflare can continue to hold this momentum or even accelerate it as we've seen with some other clouds as it scales its Network and keeps adding more and more services cloudflare has a couple of potential strategic vectors that we want to talk about and it'll be going to be interesting to see how that plays out Now One path is to compete more directly as a Cloud Player offering secure access Edge services like firewall as a service and zero Trust Services like data loss prevention email security from its area one acquisition and other zero trust offerings as well as Network Services like routing and network connectivity this is The Sweet Spot of the company load balancing many others and then add in things like Object Store and database Services more Edge services in the future it might be telecom like services such as Network switching for offices so that's one route and cloudflare is clearly on that path more services more cohorts at innovating and and growing the company and bringing in more Revenue increasing acvs and and increasing long-term value and keeping retention high now the other Vector is what we're just going to refer to as super cloud as an enabler of cross-cloud infrastructure this is new value uh relative to the former Vector that we were just talking about now the title of this episode is what multi-cloud should have been meaning cloudflare could be the control plane providing a consistent experience across clouds one that is fast and secure at global scale now to give you Insight on this let's take a look at some of the comments made by Matthew Prince the CEO and co-founder of cloudflare cloudflare put its R2 Object Store into public beta this past May and I believe it's storing around a petabyte of data today I think that's what they said in their call here's what Prince said about that quote we are talking to very large companies about moving more and more of their stored objects to where we can store that with R2 and one of the benefits is not only can we help them save money on the egress fees but it allows them to then use those object stores or objects across any of the different Cloud platforms they're that they're using so by being that neutral third party we can let people adopt a little bit of Amazon a little bit of Microsoft a little bit of Google a little bit of SAS vendors and share that data across all those different places so what's interesting about this in the super cloud context is it suggests that customers could take the best of each Cloud to power their digital businesses I might like AWS for in redshift for my analytic database or I love Google's machine learning Microsoft's collaboration and I'd like a consistent way to connect those resources but of course he's strongly hinting and has made many public statements that aws's egress fees are a blocker to that vision now at a recent investor event Matthew Prince added some color to this concept when he talked about one metric of success being how much R2 capacity was consumed and how much they sold but perhaps a more interesting Benchmark is highlighted by the following statement that he made he said a completely different measure of success for R2 is Andy jassy says I'm sick and tired of these guys meaning cloudflare taking our objects away we're dropping our egress fees to zero I would be so excited because we've then unlocked the ability to be the network that interconnects the cloud together now of course it would be Adam solipski who would be saying that or maybe Andy Jesse you know still watching over AWS and I think it's highly unlikely that that's going to happen anytime soon and that of course but but in theory gets us closer to the super cloud value proposition and to further drive that point home and we're paraphrasing a little bit his comments here he said something the effect of quote customers need one consistent control plane across clouds and we are the neutral Network that can be consistent no matter which Cloud you're using interesting right that Prince sees the world that's similar to if not nearly identical to the concepts that the cube Community has been putting forth around supercloud now this vision is a ways off let's be real Prince even suggested that his initial vision of an application running across multiple clouds you know that's like super cloud Nirvana isn't what customers are doing today that's that's really hard to do and perhaps you know it's never going to happen but there's a little doubt that cloudflare could be and is positioning itself as that cross-cloud control plane it has the network economics and the business model levers to pull it's got an edge up on the competition at the edge pun intended cloudflare is the definition of Edge and it's distributed platform it's decentralized platform is much better suited for Edge workloads than these giant data centers that are you know set up to to try and handle that today the the hyperscalers are building out you know their Edge networks things like outposts you know going out to the edge and other local zones Etc now cloudflare is increasingly competitive to the hyperscalers and those traditional Stacks that it depositioned on an earlier slide that we showed but you know the likes of AWS and Dell and hpe and Cisco and those others they're not sitting in their hands they have a huge huge customer install bases and they are definitely a moving Target they're investing and they're building out their own Super clouds with really robust stacks as well let's face it it's going to take a decade or more for Enterprises to adopt a developer platform or a new database Cloud plus cloudflare's capabilities when compared to incumbent stacks and the hyperscalers is much less robust in these areas and even in storage you know despite all the great conversation that R2 generated and the buzz you take a specialist like Wasabi they're more mature they're more functional and they're way cheaper even than cloudflare so you know it's not a fake a complete that cloudflare is going to win in those markets but we love the disruption and if cloudflare wants to be the fourth us-based hyperscaler or join the the big four as the as the fifth if we put Alibaba in the mix it's got a lot of work to do in the ecosystem by its own admission as much to learn and is part of the value by the way that it sees in its area one acquisition it's email security company that it bought but even in that case much of the emphasis has been on reseller channels compare that to the AWS ecosystem which is not only a channel play but is as much an innovation flywheel filling gaps where companies like snowflake Thrive side by side with aws's data stores as well all the on-prem stacks are building hybrid connections to AWS and other clouds as a means of providing consistent experiences across clouds indeed many of them see what they call cross-cloud services or what we call super cloud hyper cloud or whatever you know Mega Cloud you want to call it we use super cloud they are really eyeing that opportunity so very few companies frankly are not going after that space but we're going to close with this cloudflare is one of those companies that's in a position to wake up each morning and ask who can we disrupt today and very few companies are in a position to disrupt the hyperscalers to the degree that cloudflare is and that my friends is going to be fascinating to watch unfold all right let's call it a wrap I want to thank Alex Meyerson who's on production and manages the podcast as well as Ken schiffman who's our newest addition to the Boston Studio Kristen Martin and Cheryl Knight help us get the word out on social media and in our newsletters and Rob Hof is our editor-in-chief over at silicon angle thank you to all remember all these episodes are available as podcasts wherever you listen all you're going to do is search breaking analysis podcasts I publish each week on wikibon.com and siliconangle.com you can email me at david.velante at siliconangle.com or DM me at divalante if you comment on my LinkedIn posts and please do check out etr.ai they got the best survey data in the Enterprise Tech business this is Dave vellante for the cube insights powered by ETR thank you very much for watching and we'll see you next time on breaking analysis

>> The rapid rise of ransomware attacks has added yet another challenge that business technology executives have to worry about these days, cloud storage, immutability, and air gaps have become a must have arrows in the quiver of organization's data protection strategies. But the important reality that practitioners have embraced is data protection, it can't be an afterthought or a bolt on it, has to be designed into the operational workflow of technology systems. The problem is, oftentimes, data protection is complicated with a variety of different products, services, software components, and storage formats, this is why object storage is moving to the forefront of data protection use cases because it's simpler and less expensive. The put data get data syntax has always been alluring, but object storage, historically, was seen as this low-cost niche solution that couldn't offer the performance required for demanding workloads, forcing customers to make hard tradeoffs between cost and performance. That has changed, the ascendancy of cloud storage generally in the S3 format specifically has catapulted object storage to become a first class citizen in a mainstream technology. Moreover, innovative companies have invested to bring object storage performance to parity with other storage formats, but cloud costs are often a barrier for many companies as the monthly cloud bill and egress fees in particular steadily climb. Welcome to Secure Storage Hot Takes, my name is Dave Vellante, and I'll be your host of the program today, where we introduce our community to Wasabi, a company that is purpose-built to solve this specific problem with what it claims to be the most cost effective and secure solution on the market. We have three segments today to dig into these issues, first up is David Friend, the well known entrepreneur who co-founded Carbonite and now Wasabi will then dig into the product with Drew Schlussel of Wasabi, and then we'll bring in the customer perspective with Kevin Warenda of the Hotchkiss School, let's get right into it. We're here with David Friend, the President and CEO and Co-founder of Wasabi, the hot storage company, David, welcome to theCUBE. >> Thanks Dave, nice to be here. >> Great to have you, so look, you hit a home run with Carbonite back when building a unicorn was a lot more rare than it has been in the last few years, why did you start Wasabi? >> Well, when I was still CEO of Wasabi, my genius co-founder Jeff Flowers and our chief architect came to me and said, you know, when we started this company, a state of the art disk drive was probably 500 gigabytes and now we're looking at eight terabyte, 16 terabyte, 20 terabyte, even 100 terabyte drives coming down the road and, you know, sooner or later the old architectures that were designed around these much smaller disk drives is going to run out of steam because, even though the capacities are getting bigger and bigger, the speed with which you can get data on and off of a hard drive isn't really changing all that much. And Jeff foresaw a day when the architectures sort of legacy storage like Amazon S3 and so forth was going to become very inefficient and slow. And so he came up with a new, highly parallelized architecture, and he said, I want to go off and see if I can make this work. So I said, you know, good luck go to it and they went off and spent about a year and a half in the lab, designing and testing this new storage architecture and when they got it working, I looked at the economics of this and I said, holy cow, we can sell cloud storage for a fraction of the price of Amazon, still make very good gross margins and it will be faster. So this is a whole new generation of object storage that you guys have invented. So I recruited a new CEO for Carbonite and left to found Wasabi because the market for cloud storage is almost infinite. You know, when you look at all the world's data, you know, IDC has these crazy numbers, 120 zetabytes or something like that and if you look at that as you know, the potential market size during that data, we're talking trillions of dollars, not billions and so I said, look, this is a great opportunity, if you look back 10 years, all the world's data was on-prem, if you look forward 10 years, most people agree that most of the world's data is going to live in the cloud, we're at the beginning of this migration, we've got an opportunity here to build an enormous company. >> That's very exciting. I mean, you've always been a trend spotter, and I want to get your perspectives on data protection and how it's changed. It's obviously on people's minds with all the ransomware attacks and security breaches, but thinking about your experiences and past observations, what's changed in data protection and what's driving the current very high interest in the topic? >> Well, I think, you know, from a data protection standpoint, immutability, the equivalent of the old worm tapes, but applied to cloud storage is, you know, become core to the backup strategies and disaster recovery strategies for most companies. And if you look at our partners who make backup software like Veeam, Convo, Veritas, Arcserve, and so forth, most of them are really taking advantage of mutable cloud storage as a way to protect customer data, customers backups from ransomware. So the ransomware guys are pretty clever and they, you know, they discovered early on that if someone could do a full restore from their backups, they're never going to pay a ransom. So, once they penetrate your system, they get pretty good at sort of watching how you do your backups and before they encrypt your primary data, they figure out some way to destroy or encrypt your backups as well, so that you can't do a full restore from your backups. And that's where immutability comes in. You know, in the old days you, you wrote what was called a worm tape, you know, write once read many, and those could not be overwritten or modified once they were written. And so we said, let's come up with an equivalent of that for the cloud, and it's very tricky software, you know, it involves all kinds of encryption algorithms and blockchain and this kind of stuff but, you know, the net result is if you store your backups in immutable buckets, in a product like Wasabi, you can't alter it or delete it for some period of time, so you could put a timer on it, say a year or six months or something like that, once that data is written, you know, there's no way you can go in and change it, modify it, or anything like that, including even Wasabi's engineers. >> So, David, I want to ask you about data sovereignty. It's obviously a big deal, I mean, especially for companies with the presence overseas, but what's really is any digital business these days, how should companies think about approaching data sovereignty? Is it just large firms that should be worried about this? Or should everybody be concerned? What's your point of view? >> Well, all around the world countries are imposing data sovereignty laws and if you're in the storage business, like we are, if you don't have physical data storage in-country, you're probably not going to get most of the business. You know, since Christmas we've built data centers in Toronto, London, Frankfurt, Paris, Sydney, Singapore, and I've probably forgotten one or two, but the reason we do that is twofold; one is, you know, if you're closer to the customer, you're going to get better response time, lower latency, and that's just a speed of light issue. But the bigger issue is, if you've got financial data, if you have healthcare data, if you have data relating to security, like surveillance videos, and things of that sort, most countries are saying that data has to be stored in-country, so, you can't send it across borders to some other place. And if your business operates in multiple countries, you know, dealing with data sovereignty is going to become an increasingly important problem. >> So in May of 2018, that's when the fines associated with violating GDPR went into effect and GDPR was like this main spring of privacy and data protection laws and we've seen it spawn other public policy things like the CCPA and think it continues to evolve, we see judgments in Europe against big tech and this tech lash that's in the news in the U.S. and the elimination of third party cookies, what does this all mean for data protection in the 2020s? >> Well, you know, every region and every country, you know, has their own idea about privacy, about security, about the use of even the use of metadata surrounding, you know, customer data and things of this sort. So, you know, it's getting to be increasingly complicated because GDPR, for example, imposes different standards from the kind of privacy standards that we have here in the U.S., Canada has a somewhat different set of data sovereignty issues and privacy issues so it's getting to be an increasingly complex, you know, mosaic of rules and regulations around the world and this makes it even more difficult for enterprises to run their own, you know, infrastructure because companies like Wasabi, where we have physical data centers in all kinds of different markets around the world and we've already dealt with the business of how to meet the requirements of GDPR and how to meet the requirements of some of the countries in Asia and so forth, you know, rather than an enterprise doing that just for themselves, if you running your applications or keeping your data in the cloud, you know, now a company like Wasabi with, you know, 34,000 customers, we can go to all the trouble of meeting these local requirements on behalf of our entire customer base and that's a lot more efficient and a lot more cost effective than if each individual country has to go deal with the local regulatory authorities. >> Yeah, it's compliance by design, not by chance. Okay, let's zoom out for the final question, David, thinking about the discussion that we've had around ransomware and data protection and regulations, what does it mean for a business's operational strategy and how do you think organizations will need to adapt in the coming years? >> Well, you know, I think there are a lot of forces driving companies to the cloud and, you know, and I do believe that if you come back five or 10 years from now, you're going to see majority of the world's data is going to be living in the cloud and I think storage, data storage is going to be a commodity much like electricity or bandwidth, and it's going to be done right, it will comply with the local regulations, it'll be fast, it'll be local, and there will be no strategic advantage that I can think of for somebody to stand up and run their own storage, especially considering the cost differential, you know, the most analysts think that the full, all in costs of running your own storage is in the 20 to 40 terabytes per month range, whereas, you know, if you migrate your data to the cloud, like Wasabi, you're talking probably $6 a month and so I think people are learning how to deal with the idea of an architecture that involves storing your data in the cloud, as opposed to, you know, storing your data locally. >> Wow, that's like a six X more expensive in the clouds, more than six X, all right, thank you, David,-- >> In addition to which, you know, just finding the people to babysit this kind of equipment has become nearly impossible today. >> Well, and with a focus on digital business, you don't want to be wasting your time with that kind of heavy lifting. David, thanks so much for coming in theCUBE, a great Boston entrepreneur, we've followed your career for a long time and looking forward to the future. >> Thank you. >> Okay, in a moment, Drew Schlussel will join me and we're going to dig more into product, you're watching theCUBE, the leader in enterprise and emerging tech coverage, keep it right there. ♪ Whoa ♪ ♪ Brenda in sales got an email ♪ ♪ Click here for a trip to Bombay ♪ ♪ It's not even called Bombay anymore ♪ ♪ But you clicked it anyway ♪ ♪ And now our data's been held hostage ♪ ♪ And now we're on sinking ship ♪ ♪ And a hacker's in our system ♪ ♪ Just 'cause Brenda wanted a trip ♪ ♪ She clicked on something stupid ♪ ♪ And our data's out of our control ♪ ♪ Into the hands of a hacker's ♪ ♪ And he's a giant asshole. ♪ ♪ He encrypted it in his basement ♪ ♪ He wants a million bucks for the key ♪ ♪ And I'm pretty sure he's 15 ♪ ♪ And still going through puberty ♪ ♪ I know you didn't mean to do us wrong ♪ ♪ But now I'm dealing with this all week long ♪ ♪ To make you all aware ♪ ♪ Of all this ransomware ♪ ♪ That is why I'm singing you this song ♪ ♪ C'mon ♪ ♪ Take it from me ♪ ♪ The director of IT ♪ ♪ Don't click on that email from a prince Nairobi ♪ ♪ 'Cuz he's not really a prince ♪ ♪ Now our data's locked up on our screen ♪ ♪ Controlled by a kid who's just fifteen ♪ ♪ And he's using our money to buy a Ferrari ♪ (gentle music) >> Joining me now is Drew Schlussel, who is the Senior Director of Product Marketing at Wasabi, hey Drew, good to see you again, thanks for coming back in theCUBE. >> Dave, great to be here, great to see you. >> All right, let's get into it. You know, Drew, prior to the pandemic, Zero Trust, just like kind of like digital transformation was sort of a buzzword and now it's become a real thing, almost a mandate, what's Wasabi's take on Zero Trust. >> So, absolutely right, it's been around a while and now people are paying attention, Wasabi's take is Zero Trust is a good thing. You know, there are too many places, right, where the bad guys are getting in. And, you know, I think of Zero Trust as kind of smashing laziness, right? It takes a little work, it takes some planning, but you know, done properly and using the right technologies, using the right vendors, the rewards are, of course tremendous, right? You can put to rest the fears of ransomware and having your systems compromised. >> Well, and we're going to talk about this, but there's a lot of process and thinking involved and, you know, design and your Zero Trust and you don't want to be wasting time messing with infrastructure, so we're going to talk about that, there's a lot of discussion in the industry, Drew, about immutability and air gaps, I'd like you to share Wasabi's point of view on these topics, how do you approach it and what makes Wasabi different? >> So, in terms of air gap and immutability, right, the beautiful thing about object storage, which is what we do all the time is that it makes it that much easier, right, to have a secure immutable copy of your data someplace that's easy to access and doesn't cost you an arm and a leg to get your data back. You know, we're working with some of the best, you know, partners in the industry, you know, we're working with folks like, you know, Veeam, Commvault, Arc, Marquee, MSP360, all folks who understand that you need to have multiple copies of your data, you need to have a copy stored offsite, and that copy needs to be immutable and we can talk a little bit about what immutability is and what it really means. >> You know, I wonder if you could talk a little bit more about Wasabi's solution because, sometimes people don't understand, you actually are a cloud, you're not building on other people's public clouds and this storage is the one use case where it actually makes sense to do that, tell us a little bit more about Wasabi's approach and your solution. >> Yeah, I appreciate that, so there's definitely some misconception, we are our own cloud storage service, we don't run on top of anybody else, right, it's our systems, it's our software deployed globally and we interoperate because we adhere to the S3 standard, we interoperate with practically hundreds of applications, primarily in this case, right, we're talking about backup and recovery applications and it's such a simple process, right? I mean, just about everybody who's anybody in this business protecting data has the ability now to access cloud storage and so we've made it really simple, in many cases, you'll see Wasabi as you know, listed in the primary set of available vendors and, you know, put in your private keys, make sure that your account is locked down properly using, let's say multifactor authentication, and you've got a great place to store copies of your data securely. >> I mean, we just heard from David Friend, if I did my math right, he was talking about, you know, 1/6 the cost per terabyte per month, maybe even a little better than that, how are you able to achieve such attractive economics? >> Yeah, so, you know, I can't remember how to translate my fractions into percentages, but I think we talk a lot about being 80%, right, less expensive than the hyperscalers. And you know, we talked about this at Vermont, right? There's some secret sauce there and you know, we take a different approach to how we utilize the raw capacity to the effective capacity and the fact is we're also not having to run, you know, a few hundred other services, right? We do storage, plain and simple, all day, all the time, so we don't have to worry about overhead to support, you know, up and coming other services that are perhaps, you know, going to be a loss leader, right? Customers love it, right, they see the fact that their data is growing 40, 80% year over year, they know they need to have some place to keep it secure, and, you know, folks are flocking to us in droves, in fact, we're seeing a tremendous amount of migration actually right now, multiple petabytes being brought to Wasabi because folks have figured out that they can't afford to keep going with their current hyperscaler vendor. >> And immutability is a feature of your product, right? What the feature called? Can you double-click on that a little bit? >> Yeah, absolutely. So, the term in S3 is Object Lock and what that means is your application will write an object to cloud storage, and it will define a retention period, let's say a week. And for that period, that object is immutable, untouchable, cannot be altered in any way, shape, or form, the application can't change it, the system administration can't change it, Wasabi can't change it, okay, it is truly carved in stone. And this is something that it's been around for a while, but you're seeing a huge uptick, right, in adoption and support for that feature by all the major vendors and I named off a few earlier and the best part is that with immutability comes some sense of, well, it comes with not just a sense of security, it is security. Right, when you have data that cannot be altered by anybody, even if the bad guys compromise your account, they steal your credentials, right, they can't take away the data and that's a beautiful thing, a beautiful, beautiful thing. >> And you look like an S3 bucket, is that right? >> Yeah, I mean, we're fully compatible with the S3 API, so if you're using S3 API based applications today, it's a very simple matter of just kind of redirecting where you want to store your data, beautiful thing about backup and recovery, right, that's probably the simplest application, simple being a relative term, as far as lift and shift, right? Because that just means for your next full, right, point that at Wasabi, retain your other fulls, you know, for whatever 30, 60, 90 days, and then once you've kind of made that transition from vine to vine, you know, you're often running with Wasabi. >> I talked to my open about the allure of object storage historically, you know, the simplicity of the get put syntax, but what about performance? Are you able to deliver performance that's comparable to other storage formats? >> Oh yeah, absolutely, and we've got the performance numbers on the site to back that up, but I forgot to answer something earlier, right, you said that immutability is a feature and I want to make it very clear that it is a feature but it's an API request. Okay, so when you're talking about gets and puts and so forth, you know, the comment you made earlier about being 80% more cost effective or 80% less expensive, you know, that API call, right, is typically something that the other folks charge for, right, and I think we used the metaphor earlier about the refrigerator, but I'll use a different metaphor today, right? You can think of cloud storage as a magical coffee cup, right? It gets as big as you want to store as much coffee as you want and the coffee's always warm, right? And when you want to take a sip, there's no charge, you want to, you know, pop the lid and see how much coffee is in there, no charge, and that's an important thing, because when you're talking about millions or billions of objects, and you want to get a list of those objects, or you want to get the status of the immutable settings for those objects, anywhere else it's going to cost you money to look at your data, with Wasabi, no additional charge and that's part of the thing that sets us apart. >> Excellent, so thank you for that. So, you mentioned some partners before, how do partners fit into the Wasabi story? Where do you stop? Where do they pick up? You know, what do they bring? Can you give us maybe, a paint a picture for us example, or two? >> Sure, so, again, we just do storage, right, that is our sole purpose in life is to, you know, to safely and securely store our customer's data. And so they're working with their application vendors, whether it's, you know, active archive, backup and recovery, IOT, surveillance, media and entertainment workflows, right, those systems already know how to manage the data, manage the metadata, they just need some place to keep the data that is being worked on, being stored and so forth. Right, so just like, you know, plugging in a flash drive on your laptop, right, you literally can plug in Wasabi as long as your applications support the API, getting started is incredibly easy, right, we offer a 30-day trial, one terabyte, and most folks find that within, you know, probably a few hours of their POC, right, it's giving them everything they need in terms of performance, in terms of accessibility, in terms of sovereignty, I'm guessing you talked to, you know, Dave Friend earlier about data sovereignty, right? We're global company, right, so there's got to be probably, you know, wherever you are in the world some place that will satisfy your sovereignty requirements, as well as your compliance requirements. >> Yeah, we did talk about sovereignty, Drew, this is really, what's interesting to me, I'm a bit of a industry historian, when I look back to the early days of cloud, I remember the large storage companies, you know, their CEOs would say, we're going to have an answer for the cloud and they would go out, and for instance, I know one bought competitor of Carbonite, and then couldn't figure out what to do with it, they couldn't figure out how to compete with the cloud in part, because they were afraid it was going to cannibalize their existing business, I think another part is because they just didn't have that imagination to develop an architecture that in a business model that could scale to see that you guys have done that is I love it because it brings competition, it brings innovation and it helps lower clients cost and solve really nagging problems. Like, you know, ransomware, of mutability and recovery, I'll give you the last word, Drew. >> Yeah, you're absolutely right. You know, the on-prem vendors, they're not going to go away anytime soon, right, there's always going to be a need for, you know, incredibly low latency, high bandwidth, you know, but, you know, not all data's hot all the time and by hot, I mean, you know, extremely hot, you know, let's take, you know, real time analytics for, maybe facial recognition, right, that requires sub-millisecond type of processing. But once you've done that work, right, you want to store that data for a long, long time, and you're going to want to also tap back into it later, so, you know, other folks are telling you that, you know, you can go to these like, you know, cold glacial type of tiered storage, yeah, don't believe the hype, you're still going to pay way more for that than you would with just a Wasabi-like hot cloud storage system. And, you know, we don't compete with our partners, right? We compliment, you know, what they're bringing to market in terms of the software vendors, in terms of the hardware vendors, right, we're a beautiful component for that hybrid cloud architecture. And I think folks are gravitating towards that, I think the cloud is kind of hitting a new gear if you will, in terms of adoption and recognition for the security that they can achieve with it. >> All right, Drew, thank you for that, definitely we see the momentum, in a moment, Drew and I will be back to get the customer perspective with Kevin Warenda, who's the Director of Information technology services at The Hotchkiss School, keep it right there. >> Hey, I'm Nate, and we wrote this song about ransomware to educate people, people like Brenda. >> Oh, God, I'm so sorry. We know you are, but Brenda, you're not alone, this hasn't just happened to you. >> No! ♪ Colonial Oil Pipeline had a guy ♪ ♪ who didn't change his password ♪ ♪ That sucks ♪ ♪ His password leaked, the data was breached ♪ ♪ And it cost his company 4 million bucks ♪ ♪ A fake update was sent to people ♪ ♪ Working for the meat company JBS ♪ ♪ That's pretty clever ♪ ♪ Instead of getting new features, they got hacked ♪ ♪ And had to pay the largest crypto ransom ever ♪ ♪ And 20 billion dollars, billion with a b ♪ ♪ Have been paid by companies in healthcare ♪ ♪ If you wonder buy your premium keeps going ♪ ♪ Up, up, up, up, up ♪ ♪ Now you're aware ♪ ♪ And now the hackers they are gettin' cocky ♪ ♪ When they lock your data ♪ ♪ You know, it has gotten so bad ♪ ♪ That they demand all of your money and it gets worse ♪ ♪ They go and the trouble with the Facebook ad ♪ ♪ Next time, something seems too good to be true ♪ ♪ Like a free trip to Asia! ♪ ♪ Just check first and I'll help before you ♪ ♪ Think before you click ♪ ♪ Don't get fooled by this ♪ ♪ Who isn't old enough to drive to school ♪ ♪ Take it from me, the director of IT ♪ ♪ Don't click on that email from a prince in Nairobi ♪ ♪ Because he's not really a prince ♪ ♪ Now our data's locked up on our screen ♪ ♪ Controlled by a kid who's just fifteen ♪ ♪ And he's using our money to buy a Ferrari ♪ >> It's a pretty sweet car. ♪ A kid without facial hair, who lives with his mom ♪ ♪ To learn more about this go to wasabi.com ♪ >> Hey, don't do that. ♪ Cause if we had Wasabi's immutability ♪ >> You going to ruin this for me! ♪ This fifteen-year-old wouldn't have on me ♪ (gentle music) >> Drew and I are pleased to welcome Kevin Warenda, who's the Director of Information Technology Services at The Hotchkiss School, a very prestigious and well respected boarding school in the beautiful Northwest corner of Connecticut, hello, Kevin. >> Hello, it's nice to be here, thanks for having me. >> Yeah, you bet. Hey, tell us a little bit more about The Hotchkiss School and your role. >> Sure, The Hotchkiss School is an independent boarding school, grades nine through 12, as you said, very prestigious and in an absolutely beautiful location on the deepest freshwater lake in Connecticut, we have 500 acre main campus and a 200 acre farm down the street. My role as the Director of Information Technology Services, essentially to oversee all of the technology that supports the school operations, academics, sports, everything we do on campus. >> Yeah, and you've had a very strong history in the educational field, you know, from that lens, what's the unique, you know, or if not unique, but the pressing security challenge that's top of mind for you? >> I think that it's clear that educational institutions are a target these days, especially for ransomware. We have a lot of data that can be used by threat actors and schools are often underfunded in the area of IT security, IT in general sometimes, so, I think threat actors often see us as easy targets or at least worthwhile to try to get into. >> Because specifically you are potentially spread thin, underfunded, you got students, you got teachers, so there really are some, are there any specific data privacy concerns as well around student privacy or regulations that you can speak to? >> Certainly, because of the fact that we're an independent boarding school, we operate things like even a health center, so, data privacy regulations across the board in terms of just student data rights and FERPA, some of our students are under 18, so, data privacy laws such as COPPA apply, HIPAA can apply, we have PCI regulations with many of our financial transactions, whether it be fundraising through alumni development, or even just accepting the revenue for tuition so, it's a unique place to be, again, we operate very much like a college would, right, we have all the trappings of a private college in terms of all the operations we do and that's what I love most about working in education is that it's all the industries combined in many ways. >> Very cool. So let's talk about some of the defense strategies from a practitioner point of view, then I want to bring in Drew to the conversation so what are the best practice and the right strategies from your standpoint of defending your data? >> Well, we take a defense in-depth approach, so we layer multiple technologies on top of each other to make sure that no single failure is a key to getting beyond those defenses, we also keep it simple, you know, I think there's some core things that all organizations need to do these days in including, you know, vulnerability scanning, patching , using multifactor authentication, and having really excellent backups in case something does happen. >> Drew, are you seeing any similar patterns across other industries or customers? I mean, I know we're talking about some uniqueness in the education market, but what can we learn from other adjacent industries? >> Yeah, you know, Kevin is spot on and I love hearing what he's doing, going back to our prior conversation about Zero Trust, right, that defense in-depth approach is beautifully aligned, right, with the Zero Trust approach, especially things like multifactor authentication, always shocked at how few folks are applying that very, very simple technology and across the board, right? I mean, Kevin is referring to, you know, financial industry, healthcare industry, even, you know, the security and police, right, they need to make sure that the data that they're keeping, evidence, right, is secure and immutable, right, because that's evidence. >> Well, Kevin, paint a picture for us, if you would. So, you were primarily on-prem looking at potentially, you know, using more cloud, you were a VMware shop, but tell us, paint a picture of your environment, kind of the applications that you support and the kind of, I want to get to the before and the after Wasabi, but start with kind of where you came from. >> Sure, well, I came to The Hotchkiss School about seven years ago and I had come most recently from public K12 and municipal, so again, not a lot of funding for IT in general, security, or infrastructure in general, so Nutanix was actually a hyperconverged solution that I implemented at my previous position. So when I came to Hotchkiss and found mostly on-prem workloads, everything from the student information system to the card access system that students would use, financial systems, they were almost all on premise, but there were some new SaaS solutions coming in play, we had also taken some time to do some business continuity, planning, you know, in the event of some kind of issue, I don't think we were thinking about the pandemic at the time, but certainly it helped prepare us for that, so, as different workloads were moved off to hosted or cloud-based, we didn't really need as much of the on-premise compute and storage as we had, and it was time to retire that cluster. And so I brought the experience I had with Nutanix with me, and we consolidated all that into a hyper-converged platform, running Nutanix AHV, which allowed us to get rid of all the cost of the VMware licensing as well and it is an easier platform to manage, especially for small IT shops like ours. >> Yeah, AHV is the Acropolis hypervisor and so you migrated off of VMware avoiding the VTax avoidance, that's a common theme among Nutanix customers and now, did you consider moving into AWS? You know, what was the catalyst to consider Wasabi as part of your defense strategy? >> We were looking at cloud storage options and they were just all so expensive, especially in egress fees to get data back out, Wasabi became across our desks and it was such a low barrier to entry to sign up for a trial and get, you know, terabyte for a month and then it was, you know, $6 a month for terabyte. After that, I said, we can try this out in a very low stakes way to see how this works for us. And there was a couple things we were trying to solve at the time, it wasn't just a place to put backup, but we also needed a place to have some files that might serve to some degree as a content delivery network, you know, some of our software applications that are deployed through our mobile device management needed a place that was accessible on the internet that they could be stored as well. So we were testing it for a couple different scenarios and it worked great, you know, performance wise, fast, security wise, it has all the features of S3 compliance that works with Nutanix and anyone who's familiar with S3 permissions can apply them very easily and then there was no egress fees, we can pull data down, put data up at will, and it's not costing as any extra, which is excellent because especially in education, we need fixed costs, we need to know what we're going to spend over a year before we spend it and not be hit with, you know, bills for egress or because our workload or our data storage footprint grew tremendously, we need that, we can't have the variability that the cloud providers would give us. >> So Kevin, you explained you're hypersensitive about security and privacy for obvious reasons that we discussed, were you concerned about doing business with a company with a funny name? Was it the trial that got you through that knothole? How did you address those concerns as an IT practitioner? >> Yeah, anytime we adopt anything, we go through a risk review. So we did our homework and we checked the funny name really means nothing, there's lots of companies with funny names, I think we don't go based on the name necessarily, but we did go based on the history, understanding, you know, who started the company, where it came from, and really looking into the technology and understanding that the value proposition, the ability to provide that lower cost is based specifically on the technology in which it lays down data. So, having a legitimate, reasonable, you know, excuse as to why it's cheap, we weren't thinking, well, you know, you get what you pay for, it may be less expensive than alternatives, but it's not cheap, you know, it's reliable, and that was really our concern. So we did our homework for sure before even starting the trial, but then the trial certainly confirmed everything that we had learned. >> Yeah, thank you for that. Drew, explain the whole egress charge, we hear a lot about that, what do people need to know? >> First of all, it's not a funny name, it's a memorable name, Dave, just like theCUBE, let's be very clear about that, second of all, egress charges, so, you know, other storage providers charge you for every API call, right? Every get, every put, every list, everything, okay, it's part of their process, it's part of how they make money, it's part of how they cover the cost of all their other services, we don't do that. And I think, you know, as Kevin has pointed out, right, that's a huge differentiator because you're talking about a significant amount of money above and beyond what is the list price. In fact, I would tell you that most of the other storage providers, hyperscalers, you know, their list price, first of all, is, you know, far exceeding anything else in the industry, especially what we offer and then, right, their additional cost, the egress costs, the API requests can be two, three, 400% more on top of what you're paying per terabyte. >> So, you used a little coffee analogy earlier in our conversation, so here's what I'm imagining, like I have a lot of stuff, right? And I had to clear up my bar and I put some stuff in storage, you know, right down the street and I pay them monthly, I can't imagine having to pay them to go get my stuff, that's kind of the same thing here. >> Oh, that's a great metaphor, right? That storage locker, right? You know, can you imagine every time you want to open the door to that storage locker and look inside having to pay a fee? >> No, that would be annoying. >> Or, every time you pull into the yard and you want to put something in that storage locker, you have to pay an access fee to get to the yard, you have to pay a door opening fee, right, and then if you want to look and get an inventory of everything in there, you have to pay, and it's ridiculous, it's your data, it's your storage, it's your locker, you've already paid the annual fee, probably, 'cause they gave you a discount on that, so why shouldn't you have unfettered access to your data? That's what Wasabi does and I think as Kevin pointed out, right, that's what sets us completely apart from everybody else. >> Okay, good, that's helpful, it helps us understand how Wasabi's different. Kevin, I'm always interested when I talk to practitioners like yourself in learning what you do, you know, outside of the technology, what are you doing in terms of educating your community and making them more cyber aware? Do you have training for students and faculty to learn about security and ransomware protection, for example? >> Yes, cyber security awareness training is definitely one of the required things everyone should be doing in their organizations. And we do have a program that we use and we try to make it fun and engaging too, right, this is often the checking the box kind of activity, insurance companies require it, but we want to make it something that people want to do and want to engage with so, even last year, I think we did one around the holidays and kind of pointed out the kinds of scams they may expect in their personal life about, you know, shipping of orders and time for the holidays and things like that, so it wasn't just about protecting our school data, it's about the fact that, you know, protecting their information is something do in all aspects of your life, especially now that the folks are working hybrid often working from home with equipment from the school, the stakes are much higher and people have a lot of our data at home and so knowing how to protect that is important, so we definitely run those programs in a way that we want to be engaging and fun and memorable so that when they do encounter those things, especially email threats, they know how to handle them. >> So when you say fun, it's like you come up with an example that we can laugh at until, of course, we click on that bad link, but I'm sure you can come up with a lot of interesting and engaging examples, is that what you're talking about, about having fun? >> Yeah, I mean, sometimes they are kind of choose your own adventure type stories, you know, they stop as they run, so they're telling a story and they stop and you have to answer questions along the way to keep going, so, you're not just watching a video, you're engaged with the story of the topic, yeah, and that's what I think is memorable about it, but it's also, that's what makes it fun, you're not just watching some talking head saying, you know, to avoid shortened URLs or to check, to make sure you know the sender of the email, no, you're engaged in a real life scenario story that you're kind of following and making choices along the way and finding out was that the right choice to make or maybe not? So, that's where I think the learning comes in. >> Excellent. Okay, gentlemen, thanks so much, appreciate your time, Kevin, Drew, awesome having you in theCUBE. >> My pleasure, thank you. >> Yeah, great to be here, thanks. >> Okay, in a moment, I'll give you some closing thoughts on the changing world of data protection and the evolution of cloud object storage, you're watching theCUBE, the leader in high tech enterprise coverage. >> Announcer: Some things just don't make sense, like showing up a little too early for the big game. >> How early are we? >> Couple months. Popcorn? >> Announcer: On and off season, the Red Sox cover their bases with affordable, best in class cloud storage. >> These are pretty good seats. >> Hey, have you guys seen the line from the bathroom? >> Announcer: Wasabi Hot Cloud Storage, it just makes sense. >> You don't think they make these in left hand, do you? >> We learned today how a serial entrepreneur, along with his co-founder saw the opportunity to tap into the virtually limitless scale of the cloud and dramatically reduce the cost of storing data while at the same time, protecting against ransomware attacks and other data exposures with simple, fast storage, immutability, air gaps, and solid operational processes, let's not forget about that, okay? People and processes are critical and if you can point your people at more strategic initiatives and tasks rather than wrestling with infrastructure, you can accelerate your process redesign and support of digital transformations. Now, if you want to learn more about immutability and Object Block, click on the Wasabi resource button on this page, or go to wasabi.com/objectblock. Thanks for watching Secure Storage Hot Takes made possible by Wasabi. This is Dave Vellante for theCUBE, the leader in enterprise and emerging tech coverage, well, see you next time. (gentle upbeat music)

>>Hi, buddy. Welcome back to the keeps coverage of AWS 2021. Re-invent you're watching the cube and I'm really excited. We're going to go outside the storage box. I like to say with my lawn Thompson Bukovac, who's the vice-president of block and object storage and Wayne Duso was a VP of storage edge and data governance guys. Great to see you again, we saw you at storage day, the 15 year anniversary of AWS, of course, the first product service ever. So awesome to be here. Isn't it. Wow. >>So much energy in the room. It's so great to see customers learning from each other, learning from AWS, learning from the things that you're observing as well. >>A lot of companies decided not to do physical events. I think you guys are on the right side of history. We're going to show you, you weren't exactly positive. How many people are going to show up. Everybody showed. I mean, it's packed house here, so >>Number 10. Yeah. >>All right. So let's get right into it. Uh, news of the week. >>So much to say, when you want to kick this off, >>We had a, we had a great set of announcements that Milan, uh, talked about yesterday, uh, in her talk and, and a couple of them in the file space, specifically a new, uh, member of the FSX family. And if you remember that the FSA, Amazon FSX is, uh, for customers who want to run fully managed versions of third party and open source file systems on AWS. And so yesterday we announced a new member it's FSX for open ZFS. >>Okay, cool. And there's more, >>Well, there's more, I mean, one of the great things about the new match file service world and CFS is it's powered by gravity. >>It is taught by Gravatar and all of the capabilities that AWS brings in terms of networking, storage, and compute, uh, to our customers. >>So this is really important. I want the audience to understand this. So I I've talked on the cube about how a large proportion let's call it. 30% of the CPU cycles are kind of wasted really on things like offloads, and we could be much more efficient, so graviton much more efficient, lower power and better price performance, lower cost. Amazon is now on a new curve, uh, cycles are faster for processors, and you can take advantage of that in storage it's storage users, compute >>That's right? In fact, you have that big launch as well for luster, with gravity. >>We did in fact, uh, so with, with, uh, Yasmin of open CFS, we also announced the next gen Lustre offering. And both of these offerings, uh, provide a five X improvement in performance. For example, now with luster, uh, customers can drive up to one terabyte per second of throughput, which is simply amazing. And with open CFS, right out of, right out of the box at GA a million IOPS at sub-millisecond latencies taking advantage of gravitas, taking advantage of our storage and networking capabilities. >>Well, I guess it's for HPC workloads, but what's the difference between these days HPC, big data, data intensive, a lot of AI stuff, >>All right. You to just, there's a lot of intersection between all of those different types of workloads they have, as you said, and you know, it all, it all depends on it all matters. And this is the reason why having the suite of capabilities that the, if you would, the members of the family is so important to our guests. >>We've talked a lot about, it's really can't think about traditional storage as a traditional storage anymore. And certainly your world's not a box. It's really a data platform, but maybe you could give us your point of view on that. >>Yeah, I think, you know, if, if we look, if we take a step back and we think about how does AWS do storage? Uh, we think along multiple dimensions, we have the dimension that Wayne's talking about, where you bring together the power of compute and storage for these managed file services that are so popular. You and I talked about, um, NetApp ONTAP. Uh, we went into some detail on that with you as well, and that's been enormously popular. And so that whole dimension of these managed file services is all about where is the customer today and how can we help them get to the cloud? But then you think about the other things that we're also imagining, and we're, re-imagining how customers want to grow those applications and scale them. And so a great example here at reinvent is let's just take the concept of archive. >>So many people, when they think about archive, they think about taking that piece of data and putting it away on tape, putting it away in a closet somewhere, never pulling it out. We don't think about archive like that archive just happens to be data that you just aren't using at the moment, but when you need it, you need it right away. And that's why we built a new storage class that we launched just yesterday, Dave, and it's called glacier instead of retrieval, it has retrieval and milliseconds, just like an Esri storage class has the same pricing of four tenths of a cent as glacier archive. >>So what's interesting at the analyst event today, Adam got a question about, and somebody was poking at him, you know, analysts can be snarky sometimes about, you know, price, declines and so forth. And he said, you know, one of the, one of the things that's not always shown up and we don't always get credit for lowering prices, but we might lower costs. And there's the archive and deep archive is an example of that. Maybe you could explain that point of view. >>Yeah. The way we look at it is that our customers, when they talk to us about the cost of storage, they talked to us about the total cost of the storage, and it's not just storing the data, it's retrieving it and using it. And so we have done an amazing amount across all the portfolio around reducing costs. We have glacier answer retrieval, which is 68% cheaper than standard infrequent access. That's a big cost reduction. We have EBS snapshots archive, which we introduced yesterday, 75% cheaper to archive a snapshot. And these are the types of that just transform the total cost. And in some cases we just eliminate costs. And so the glacier storage class, all bulk retrievals of data from the glacier storage class five to 12 hours, it's now free of charge. If you don't even have to think about, we didn't even reduce it. We just eliminated the cost of that data retrieval >>And additive to what Milan said around, uh, archiving. If you look at what we've done throughout the entire year, you know, a interesting statistic that was brought up yesterday is over the course of 2021, between our respective teams, we've launched over 105 capabilities for our customers throughout this year. And in some of them, for instance, on the file side for EFS, we launched one zone which reduced, uh, customer costs by 47%. Uh, you can now achieve on EFS, uh, cost of roughly 4.30 cents per gigabyte month on, uh, FSX, we've reduced costs up to 92%, uh, on Lustre and FSX for windows and with the introduction of ONTAP and open CFS, we continue those forward, including customers ability to compress and Dedoose against those costs. So they ended up seeing a considerable savings, even over what our standard low prices are. >>100 plus, what can I call them releases? And how can you categorize those? Are they features of eight? Do they fall into, >>Because they range for major services, like what we've launched with open ZFS to major features and really 95 of those were launched before re-invent. And so really what you have between the different teams that work in storage is you have this relentless drive to improve all the storage platforms. And we do it all across the course of the year, all across the course of the year. And in some cases, the benefit shows up at no cost at all to a customer. >>Uh, how, how did this, it seems like you're on an accelerated pace, a S3 EBS, and then like hundreds of services. I guess the question is how come it took so long and how is it accelerating now? Is it just like, there was so much focus on compute before you had to get that in place, or, but now it's just rapidly accessing, >>I I'll tell you, Dave, we took the time to count this year. And so we came to you with this number of 106, uh, that acceleration has been in place for many years. We just didn't take the time to couch. Correct. So this has been happening for years and years. Wayne and I have been with AWS for, for a long time now for 10 plus years. And really that velocity that we're talking about right now that has been happening every single year, which is where you have storage today. And I got to tell you, innovation is in our DNA and we are not going to stop now >>So 10 years. Okay. So it was really, the first five years was kind of slow. And then >>I think that's true at all. I don't think that try, you know, if you, if you look at, uh, the services that we have, we have the most complete portfolio of any cloud provider when it comes to storage and data. And so over the years, we've added to the foundation, which is S3 and the foundation, which is EBS. We've come out with a number of storage services in the, in the file space. Now you have an entire suite of persistent data stores within AWS and the teams behind those that are able to accelerate that pace. Just to give you an example, when I joined 10 years ago, AWS launched within that year, roughly a hundred and twenty, a hundred and twenty eight services or features our teams together this year have launched almost that many, just in those in, just in this space. So AWS continues to accelerate the storage teams continue to accelerate. And as my line said, we just started counting >>The thing. And if you think about those first five years, that was laying the baseline to launch us three, to launch EBS, to get that foundation in place, get lifecycle policies in place. But really, I think you're just going to see an even faster acceleration that number's going up. >>No, I that's what I'm saying. It does appear that way. And you had to build a team and put teams in place. And so that's, you know, part of the equation. But again, I come back to, it's not even, I don't even think of it as storage anymore. It's it's data. People are data lake is here to stay. You might not like the term. We always use the joke about a data ocean, but data lake is here to say 200,000 data lakes. Now we heard Adam talk about, uh, this morning. I think it was Adam. No, it was Swami. Do you want a thousand data lakes in your customer base now? And people are adding value to that data in new ways, injecting machine intelligence, you know, SageMaker is a big piece of that. Tying it in. I know a lot of customers are using glue as catalogs and which I'm like, wow, is glue a catalog or, I mean, it's just so flexible. So what are you seeing customers do with that base of data now and driving new business value? Because I've said last decade plus has been about it transformation. And now we're seeing business transformation. Maybe you could talk about that a little bit. >>Well, the base of every data lake is going to be as three yesterday has over 200 trillion objects. Now, Dave, and if you think about that, if you took every person on the planet, each of those people would have 26,000 S3 objects. It's gotten that big. And you know, if you think about the base of data with 200 trillion plus objects, really the opportunity for innovation is limitless. And you know, a great example for that is it's not just business value. It's really the new customer experiences that our customers are inventing the NFL. Uh, they, you know, they have that application called digital athlete where, you know, they started off with 10,000 labeled images or up to 20,000 labeled images now. And they're all using it to drive machine learning models that help predict and support the players on the field when they start to see things unfold that might cause injury. That is a brand new experience. And it's only possible with vast amounts of data >>Additive to when my line said, we're, we're in you talk about business transformation. We are in the age of data and we represent storage services. But what we really represent is what our customers hold one of their most valuable assets, which is their data. And that set of data is only growing. And the ability to use that data, to leverage that data for value, whether it's ML training, whether it's analytics, that's only accelerated, this is the feedback we get from our customers. This is where these features and new capabilities come from. So that's, what's really accelerating our pace >>Guys. I wish we had more time. I'd have to have you back because we're on a tight clock here, but, um, so great to see you both especially live. I hope we get to do more of this in 2022. I'm an optimist. Okay. And keep it right there, everybody. This is Dave Volante for the cube you're leader in live tech coverage, right back.

>>mhm mhm >>Hey guys, welcome back to Los Angeles lisa martin. Coming to you live from cuba con and cloud native Con north America 2021. Very excited to be here. This is our third day of back to back coverage on the cube and we've got a couple of guests cube alumni joining me remotely. Please welcome parse our karate senior consultant, product marketing, Dell Technologies and David Noi VP product management at Dell Technologies. Gentlemen welcome back to the program. >>Thanks johnny >>so far so let's go ahead and start with you. Let's talk about what Dell EMC is offering to developers today in terms of unstructured data. >>Absolutely, it's great to be here. So let me start with the container storage interface. This is Q khan and a couple of years ago the container storage interface was still in beta and the storage vendors, we're very enthusiastically kind of building the plug in city of the different storage portfolio to offer enterprise grade features to developers are building applications of the Cuban this platform. And today if you look at the deli in storage portfolio, big block volumes. Nash shares s three object A P I S beyond their virtual volumes. However you're consuming storage, you have the plug ins that are required to run your applications with these enterprise Great feature speech right about snap sharks data replication, all available in the Cuban this layer and just this week at coupon we announced the container storage modules which is kind of the next step of productivity for developers beat you know uh in terms of observe ability of the storage metrics using tools like Prometheus visualizing it ravana authorization capabilities so that you know too bad moments can have better resource management of the storage that is being consumed um that so there are these multiple models were released. And if you look at unstructured data, this term may be a bit new for our kind of not very family for developers but basically the storage. Well there is a distinction that is being made you know, between primary storage and unstructured storage or unstructured data solutions And by unstructured we mean file and object storage. If you look at the cube contact nickel sessions, I was very glad to see that there is an entire stream for um machine learning and data so that speaks to how popular communities deployment models are getting when it comes to machine learning and artificial intelligence. Um even applications like genomics and media and entertainment and with the container storage interface uh and the container storage modules with the object storage portfolio that bill has, we offer the comprehensive unstructured data solutions for developers beat object or file. And the advantage the developers are getting is these you know, if you look at platforms like power scale and these areas, these are like the industry workhorses with the highest performance. And if you think of scale, you know, think of 250 nasnotes, you know with a single name space with NVIDIA gpu direct capabilities. All these capabilities developers can use um for you know, applications like machine learning or any competition intensive for data intensive applications that requires these nass uh scale of mass platforms. So so um that's that's what is new in terms of uh what we are offering, you have the storage heaters >>got a parcel. Thank you. David, let's bring you into the conversation now you've launched objects scale at VM World. Talk to us about that, what some of the key features and capabilities are and some of those big business benefits that customers are going to be able to achieve. >>Sure thing. So I really want to focus on three of the biggest benefits. This would be the fact that the product is actually based on kubernetes country, the scale of the product and then its ability to do global replication. So let me just touch on those in order. Mhm You said that the product is based on kubernetes and here we are cube concept. The perfect time to be talking about that. This product really caters to those who are looking for a flexible way to deploy object storage in containerized fashion, appeals to the devops folks and folks who like to automate things and call the communities a P I. S to make uh the actual deployment of the product. Very simple in turnkey and that's really what people turn to kubernetes for is the ability to spin things up when they need them and spend them down as they don't and make that all on commodity hardware and commodity, you know, the quantity pricing and the idea there is that I'm making it as simple and easy as possible. You're not going to get as much shadow I. T. You won't have people going off and putting things off into a public cloud. And so where security of an organization or control of the data that flows with an organization is important. Having something that's easy for developers to use in the same paradigm that they're used to is critical. Now I talked about scale and you know, if you have come to me two years ago I would have told you, you know, kubernetes, yeah, containers people are kicking it around and they're doing some interesting science experiments, I would say in the last year I started to see a lot of requests from customers um in the dozens, even 200 petabyte range as it relates to capacity for committees and specifically looking for C. S. I and cozy with this. This this is the the object storage implementation of the container storage interfaces. Uh So skin was definitely there and the idea of this product is to provide easy scalability from the terabytes range into the multi petabyte range and again it's that ease of use, ease of deployment because it is kubernetes basically because it's a KPI driven that makes that possible. So we're talking about going from a three night minimum to thousands of nodes. and this allows people to deploy the product either at the edge or in the data center um in the edge because you can get very small deployments in the data center to massive scale. So we want to provide something that covers the gamut. The last thing I talked about was replication. So let me just touch upon what I mean by that uh when people go and build these deployments, if you're building a deployment at the edge of an object scale product, you're probably taking in sensor data or some kind of information that you want to then send back to a data center for processing. So you make it simple to do bucket based replication. An object, sorry object storage based replication to move things to another location. And uh that can be used either for bringing data back for analytics from the edge, it can be used for availability. So making sure that you have data available across multiple data centers in the case that you have an outage. It could be even used for sharing data between developers in one site and another site. So we provide that level of flexibility overall. Um this is the next generation object store leveraging. Dell technologies number one position in object storage. So I'm pretty excited about >>and how David is object scale integrated with VM ware software. Stop give us that slice and dice. >>Yeah, and that's a good question. And so, you know, we're talking about this being a Kubernetes based product, you can deploy it on open shift or we integrate directly with VM ware cloud foundation and with Tansy, which is VM ware's container orchestration and management platform. I've seen the demo of the product myself from my team and they've showed it to be did all of the management of the product was actually done within the V sphere Ui, which is great. So easy to go and just enter the V sphere. You I installed the product very simply have it up and running and then go and do all of your management through that user interface or to automate it using the same api is that you used to through VM ware and the 10 Zoo uh platform. >>Thank you, paris are back to you. Security is a big theme here in kubernetes. It's also been a big theme here. We've been talking about it the last three days here at cop con. How does Dell EMC's unstructured portfolio offer that necessary cyber protection that developers need to have and bake that into what they're doing. So >>surely, you know, they talk about cybersecurity, you know, there are different layers of security right from, you know, smarter firewalls to you know how to manage privileged account access and so on. And what we are trying to do is to provide a layer of cyber defense, right at the asset that you're trying to protect, which is the data and this is where the ransom their defender solution is basically detecting any patterns of the compromise that might have happened and alerting the I. T. Um administration about this um possible um intrusions into their into the data by looking at the data access parents in real time. So that's a pretty big deal. Then we're actually putting all this, you know, observance on the primary data and that's what the power scale platform cybersecurity protection features offers. Now we've also extended this kind of detection mechanism for the object data framework on pcs platforms as well. So this is like an additional layer of security at the um layer of uh you know where the data is actually being read and written. Do that's the area, you know, in case of object here we're looking at the S. Three traffic and trying to find his parents in case of a file data atmosphere, looking at the file's access parents and so on. So and in relation to this we're also providing uh data isolation mechanism that is very critical in many cyber recovery processes with the smart absolution as well. So this is something that the developers are getting for like without having to worry about it because that is something implemented at the infrastructure layer itself. So they don't have to worry about you know trying to court it or develop their application to integrate these kinds of things because it's an it's embedded in the infrastructure at the one of the FBI level at the E C. S A P I level. So that's pretty um pretty differentiating in the industry in the country storage solutions. I'll get. >>Uh huh. Yeah. I mean look if you look at what a lot of the object storage players are doing as it relates to cyber security. They're they're playing off the fact that they've implemented object lock and basically using that to lockdown data. And that's that's good. I mean I'm glad that they're doing that and if the case that you were able to lock something down and someone wasn't able to bypass that in some way, that's fantastic. Or if they didn't already encrypted before I got locked down what parts are is referring to is a little bit more than that. It's actually the ability to look at user behavior and determined that something bad is happening. So this is about actually being able to do, you know, predictive analytics being able to go and figure out that you're under attack. There's anomalous behavior um and we're able to go and actually infer from that that something bad is happening and where we think it's happening and lock it down even even more securely than for example just saying hey we provide object like capabilities which is one of the responses that I've seen out there from object storage vendors >>can you share with us. Parts are a customer example like walk us through how this is actually being used and deployed and what some of those business outcomes are. >>Yes lisa. So in terms of container realization itself, they have a media and entertainment kind of customer story here. Um Swiss TXT um they have a platform as a service where they serve their customer base with a range of uh you know, media production and broadcasting solutions and they have containers this platform and part of this computerization is part of their services is they offer infrastructure as a service to you know, media producers who need a high performance storage, high performance computing and power skill And Iceland have been their local solutions to offer this And now that they have containerized their core platform. Well you see a sign interface for power skills, they are able to continue to deliver the infrastructure, high performance infrastructure and storage services to their customers through the A. P I. And it's great to see how fast they could, you know, re factor their application but yet continue to offer the high performance and degrees enterprise grade uh features of the power scale platform. So Swiss Txt and would love to share more. Keep it on the story. Yeah. Hyperlink. >>And where can folks go to learn more about objects scale and what you guys are announcing? Yes, particular. You are a website that you want to direct folks too. >>I would say that technologies dot com. And uh that's the best place to start. >>Yeah, I would go to the Delta product pages around objects should be publicly built. >>Excellent guys, thank you for joining me on the program today. Walking through what how Dell EMC is helping developers with respect to unstructured data, Talking to us about objects skill that you launched VM world, some of those big customer benefits and of course showing us the validation, the proof in the pudding with that customer story. We appreciate your insights. >>Thank you. Thank you lisa >>For my guests. I'm Lisa Martin. You're watching the Cube live from Los Angeles. We're coming to you from our coverage of coupon and cloud native on North America 21. Coming back. Stick around. Rather I should say we'll be back after a short break with our next guest.

(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)