Thomas Been, DataStax | AWS re:Invent 2022
(intro music) >> Good afternoon guys and gals. Welcome back to The Strip, Las Vegas. It's "theCUBE" live day four of our coverage of "AWS re:Invent". Lisa Martin, Dave Vellante. Dave, we've had some awesome conversations the last four days. I can't believe how many people are still here. The AWS ecosystem seems stronger than ever. >> Yeah, last year we really noted the ecosystem, you know, coming out of the isolation economy 'cause everybody had this old pent up demand to get together and the ecosystem, even last year, we were like, "Wow." This year's like 10x wow. >> It really is 10x wow, it feels that way. We're going to have a 10x wow conversation next. We're bringing back DataStax to "theCUBE". Please welcome Thomas Bean, it's CMO. Thomas welcome to "theCUBE". >> Thanks, thanks a lot, thanks for having me. >> Great to have you, talk to us about what's going on at DataStax, it's been a little while since we talked to you guys. >> Indeed, so DataStax, we are the realtime data company and we've always been involved in technology such as "Apache Cassandra". We actually created to support and take this, this great technology to the market. And now we're taking it, combining it with other technologies such as "Apache Pulse" for streaming to provide a realtime data cloud. Which helps our users, our customers build applications faster and help them scale without limits. So it's all about mobilizing all of this information that is going to drive the application going to create the awesome experience, when you have a customer waiting behind their mobile phone, when you need a decision to take place immediately to, that's the kind of data that we, that we provide in the cloud on any cloud, but especially with, with AWS and providing the performance that technologies like "Apache Cassandra" are known for but also with market leading unit economics. So really empowering customers to operate at speed and scale. >> Speaking of customers, nobody wants less data slower. And one of the things I think we learned in the in the pan, during the pandemic was that access to realtime data isn't nice to have anymore for any business. It is table stakes, it's competitive advantage. There's somebody right behind in the rear view mirror ready to take over. How has the business model of DataStax maybe evolved in the last couple of years with the fact that realtime data is so critical? >> Realtime data has been around for some time but it used to be really niches. You needed a lot of, a lot of people a lot of funding actually to, to implement these, these applications. So we've adapted to really democratize it, made super easy to access. Not only to start developing but also scaling. So this is why we've taken these great technologies made them serverless cloud native on the cloud so that developers could really start easily and scale. So that be on project products could be taken to the, to the market. And in terms of customers, the patterns is we've seen enterprise customers, you were talking about the pandemic, the Home Depot as an example was able to deliver curbside pickup delivery in 30 days because they were already using DataStax and could adapt their business model with a real time application that combines you were just driving by and you would get the delivery of what exactly you ordered without having to go into the the store. So they shifted their whole business model. But we also see a real strong trend about customer experiences and increasingly a lot of tech companies coming because scale means success to them and building on, on our, on our stack to, to build our applications. >> So Lisa, it's interesting. DataStax and "theCUBE" were started the same year, 2010, and that's when it was the beginning of the ascendancy of the big data era. But of course back then there was, I mean very little cloud. I mean most of it was on-prem. And so data stacks had, you know, had obviously you mentioned a number of things that you had to do to become cloud friendly. >> Thomas: Yes. >> You know, a lot of companies didn't make it, make it through. You guys just raised a bunch of dough as well last summer. And so that's been quite a transformation both architecturally, you know, bringing the customers through. I presume part of that was because you had such a great open source community, but also you have a unique value problem. Maybe you could sort of describe that a little. >> Absolutely, so the, I'll start with the open source community where we see a lot of traction at the, at the moment. We were always very involved with, with the "Apache Cassandra". But what we're seeing right now with "Apache Cassandra" is, is a lot of traction, gaining momentum. We actually, we, the open source community just won an award, did an AMA, had a, a vote from their readers about the top open source projects and "Apache Cassandra" and "Apache Pulse" are part of the top three, which is, which is great. We also run a, in collaboration with the Apache Project, the, a series of events around the, around the globe called "Cassandra Days" where we had tremendous attendance. We, some of them, we had to change venue twice because there were more people coming. A lot of students, a lot of the big users of Cassandra like Apple, Netflix who spoke at these, at these events. So we see this momentum actually picking up and that's why we're also super excited that the Linux Foundation is running the Cassandra Summit in in March in San Jose. Super happy to bring that even back with the rest of the, of the community and we have big announcements to come. "Apache Cassandra" will, will see its next version with major advances such as the support of asset transactions, which is going to make it even more suitable to more use cases. So we're bringing that scale to more applications. So a lot of momentum in terms of, in terms of the, the open source projects. And to your point about the value proposition we take this great momentum to which we contribute a lot. It's not only about taking, it's about giving as well. >> Dave: Big committers, I mean... >> Exactly big contributors. And we also have a lot of expertise, we worked with all of the members of the community, many of them being our customers. So going to the cloud, indeed there was architectural work making Cassandra cloud native putting it on Kubernetes, having the right APIs for developers to, to easily develop on top of it. But also becoming a cloud company, building customer success, our own platform engineering. We, it's interesting because actually we became like our partners in a community. We now operate Cassandra in the cloud so that all of our customers can benefit from all the power of Cassandra but really efficiently, super rapidly, and also with a, the leading unit economies as I mentioned. >> How will the, the asset compliance affect your, you know, new markets, new use cases, you know, expand your TAM, can you explain that? >> I think it will, more applications will be able to tap into the power of, of "NoSQL". Today we see a lot on the customer experience as IOT, gaming platform, a lot of SaaS companies. But now with the ability to have transactions at the database level, we can, beyond providing information, we can go even deeper into the logic of the, of the application. So it makes Cassandra and therefore Astra which is our cloud service an even more suitable database we can address, address more even in terms of the transaction that the application itself will, will support. >> What are some of the business benefits that Cassandra delivers to customers in terms of business outcomes helping businesses really transform? >> So Cassandra brings skill when you have millions of customers, when you have million of data points to go through to serve each of the customers. One of my favorite example is Priceline, who runs entirely on our cloud service. You may see one offer, but it's actually everything they know about you and everything they have to offer matched while you are refreshing your page. This is the kind of power that Cassandra provide. But the thing to say about "Apache Cassandra", it used to be also a database that was a bit hard to manage and hard to develop with. This is why as part of the cloud, we wanted to change these aspects, provide developers the API they like and need and what the application need. Making it super simple to operate and, and, and super affordable, also cost effective to, to run. So the the value to your point, it's time to market. You go faster, you don't have to worry when you choose the right database you're not going to, going to have to change horse in the middle of the river, like sixth month down the line. And you know, you have the guarantee that you're going to get the performance and also the best, the best TCO which matters a lot. I think your previous person talking was addressing it. That's also important especially in the, in a current context. >> As a managed service, you're saying, that's the enabler there, right? >> Thomas: Exactly. >> Dave: That is the model today. I mean, you have to really provide that for customers. They don't want to mess with, you know, all the plumbing, right? I mean... >> Absolutely, I don't think people want to manage databases anymore, we do that very well. We take SLAs and such and even at the developer level what they want is an API so they get all the power. All of of this powered by Cassandra, but now they get it as a, and it's as simple as using as, as an API. >> How about the ecosystem? You mentioned the show in in San Jose in March and the Linux Foundation is, is hosting that, is that correct? >> Yes, absolutely. >> And what is it, Cassandra? >> Cassandra Summit. >> Dave: Cassandra Summit >> Yep. >> What's the ecosystem like today in Cassandra, can you just sort of describe that? >> Around Cassandra, you have actually the big hyperscalers. You have also a few other companies that are supporting Cassandra like technologies. And what's interesting, and that's been a, a something we've worked on but also the "Apache Project" has worked on. Working on a lot of the adjacent technologies, the data pipelines, all of the DevOps solutions to make sure that you can actually put Cassandra as part of your way to build these products and, and build these, these applications. So the, the ecosystem keeps on, keeps on growing and actually the, the Cassandra community keeps on opening the database so that it's, it's really easy to have it connect to the rest of the, the rest environment. And we benefit from all of this in our Astra cloud service. >> So things like machine learning, governance tools that's what you would expect in the ecosystem forming around it, right? So we'll see that in March. >> Machine learning is especially a very interesting use case. We see more and more of it. We recently did a, a nice video with one of our customers called Unifour who does exactly this using also our abstract cloud service. What they provide is they analyze videos of sales calls and they help actually the sellers telling them, "Okay here's what happened here was the customer sentiment". Because they have proof that the better the sentiment is, the shorter the sell cycle is going to be. So they teach the, the sellers on how to say the right things, how to control the thing. This is machine learning applied on video. Cassandra provides I think 200 data points per second that feeds this machine learning. And we see more and more of these use cases, realtime use cases. It happens on the fly when you are on your phone, when you have a, a fraud maybe to detect and to prevent. So it is going to be more and more and we see more and more of these integration at the open source level with technologies like even "Feast" project like "Apache Feast". But also in the, in, in the partners that we're working with integrating our Cassandra and our cloud service with. >> Where are customer conversations these days, given that every company has to be a data company. They have to be able to, to democratize data, allow access to it deep into the, into the organizations. Not just IT or the data organization anymore. But are you finding that the conversations are rising up the, up the stack? Is this, is this a a C-suite priority? Is this a board level conversation? >> So that's an excellent question. We actually ran a survey this summer called "The State of the Database" where we, we asked these tech leaders, okay what's top of mind for you? And real time actually was, was really one of the top priorities. And they explained for the one that who call themselves digital leaders that for 71% of them they could correlate directly the use of realtime data, the quality of their experience or their decision making with revenue. And that's really where the discussion is. And I think it's something we can relate to as users. We don't want the, I mean if the Starbucks apps take seconds to to respond there will be a riot over there. So that's, that's something we can feel. But it really, now it's tangible in, in business terms and now then they take a look at their data strategy, are we equipped? Very often they will see, yeah, we have pockets of realtime data, but we're not really able to leverage it. >> Lisa: Yeah. >> For ML use cases, et cetera. So that's a big trend that we're seeing on one end. On the other end, what we're seeing, and it's one of the things we discussed a lot at the event is that yeah cost is important. Growth at all, at all cost does not exist. So we see a lot of push on moving a lot of the workloads to the cloud to make them scale but at the best the best cost. And we also see some organizations where like, okay let's not let a good crisis go to waste and let's accelerate our innovation not at all costs. So that we see also a lot of new projects being being pushed but reasonable, starting small and, and growing and all of this fueled by, by realtime data, so interesting. >> The other big topic amongst the, the customer community is security. >> Yep. >> I presume it's coming up a lot. What's the conversation like with DataStax? >> That's a topic we've been working on intensely since the creation of Astra less than two years ago. And we keep on reinforcing as any, any cloud provider not only our own abilities in terms of making sure that customers can manage their own keys, et cetera. But also integrating to the rest of the, of the ecosystem when some, a lot of our customers are running on AWS, how do we integrate with PrivateLink and such? We fit exactly into their security environment on AWS and they use exactly the same management tool. Because this is also what used to cost a lot in the cloud services. How much do you have to do to wire them and, and manage. And there are indeed compliance and governance challenges. So that's why making sure that it's fully connected that they have full transparency on what's happening is, is a big part of the evolution. It's always, security is always something you're working on but it's, it's a major topic for us. >> Yep, we talk about that on pretty much every event. Security, which we could dive into, but we're out of time. Last question for you. >> Thomas: Yes. >> We're talking before we went live, we're both big Formula One fans. Say DataStax has the opportunity to sponsor a team and you get the whole side pod to, to put like a phrase about DataStax on the side pod of this F1 car. (laughter) Like a billboard, what does it say? >> Billboard, because an F1 car goes pretty fast, it will be hard to, be hard to read but, "Twice the performance at half the cost, try Astra a cloud service." >> Drop the mike. Awesome, Thomas, thanks so much for joining us. >> Thank for having me. >> Pleasure having you guys on the program. For our guest, Thomas Bean and Dave Vellante, I'm Lisa Martin and you're watching "theCUBE" live from day four of our coverage. "theCUBE", the leader in live tech coverage. (outro music)
SUMMARY :
the last four days. really noted the ecosystem, We're going to have a 10x Thanks, thanks a lot, we talked to you guys. in the cloud on any cloud, in the pan, during the pandemic was And in terms of customers, the patterns is of the ascendancy of the big data era. bringing the customers through. A lot of students, a lot of the big users members of the community, of the application. But the thing to say Dave: That is the model today. even at the developer level of the DevOps solutions the ecosystem forming around it, right? the shorter the sell cycle is going to be. into the organizations. "The State of the Database" where we, of the things we discussed the customer community is security. What's the conversation of the ecosystem when some, Yep, we talk about that Say DataStax has the opportunity to "Twice the performance at half the cost, Drop the mike. guys on the program.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Lisa Martin | PERSON | 0.99+ |
Thomas | PERSON | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
Lisa | PERSON | 0.99+ |
Cassandra | PERSON | 0.99+ |
March | DATE | 0.99+ |
San Jose | LOCATION | 0.99+ |
Dave | PERSON | 0.99+ |
Apple | ORGANIZATION | 0.99+ |
Thomas Bean | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
DataStax | ORGANIZATION | 0.99+ |
Netflix | ORGANIZATION | 0.99+ |
Linux Foundation | ORGANIZATION | 0.99+ |
71% | QUANTITY | 0.99+ |
Thomas Been | PERSON | 0.99+ |
One | QUANTITY | 0.99+ |
theCUBE | TITLE | 0.99+ |
last year | DATE | 0.99+ |
sixth month | QUANTITY | 0.99+ |
Thomas Bean | PERSON | 0.99+ |
Unifour | ORGANIZATION | 0.99+ |
30 days | QUANTITY | 0.99+ |
Home Depot | ORGANIZATION | 0.99+ |
one | QUANTITY | 0.99+ |
Priceline | ORGANIZATION | 0.99+ |
Twice | QUANTITY | 0.99+ |
each | QUANTITY | 0.99+ |
Starbucks | ORGANIZATION | 0.99+ |
twice | QUANTITY | 0.99+ |
2010 | DATE | 0.98+ |
10x | QUANTITY | 0.98+ |
Today | DATE | 0.98+ |
Cassandra Summit | EVENT | 0.97+ |
millions of customers | QUANTITY | 0.97+ |
last summer | DATE | 0.97+ |
theCUBE | ORGANIZATION | 0.96+ |
this summer | DATE | 0.96+ |
both | QUANTITY | 0.96+ |
pandemic | EVENT | 0.95+ |
TAM | ORGANIZATION | 0.95+ |
today | DATE | 0.95+ |
Cassandra | TITLE | 0.95+ |
one end | QUANTITY | 0.95+ |
This year | DATE | 0.94+ |
DataStax | TITLE | 0.94+ |
day four | QUANTITY | 0.94+ |
half | QUANTITY | 0.93+ |
Apache Cassandra | ORGANIZATION | 0.93+ |
top three | QUANTITY | 0.93+ |
Cassandra Days | EVENT | 0.92+ |
Apache | ORGANIZATION | 0.91+ |
NoSQL | TITLE | 0.89+ |
200 data points per second | QUANTITY | 0.89+ |
Apache Project | ORGANIZATION | 0.88+ |
Billboard | ORGANIZATION | 0.88+ |
less than | DATE | 0.88+ |
The Strip, Las Vegas | LOCATION | 0.87+ |
one offer | QUANTITY | 0.85+ |
Cassandra | ORGANIZATION | 0.85+ |
SiliconANGLE Report: Reporters Notebook with Adrian Cockcroft | AWS re:Invent 2022
(soft techno upbeat music) >> Hi there. Welcome back to Las Vegas. This is Dave Villante with Paul Gillon. Reinvent day one and a half. We started last night, Monday, theCUBE after dark. Now we're going wall to wall. Today. Today was of course the big keynote, Adam Selipsky, kind of the baton now handing, you know, last year when he did his keynote, he was very new. He was sort of still getting his feet wet and finding his guru swing. Settling in a little bit more this year, learning a lot more, getting deeper into the tech, but of course, sharing the love with other leaders like Peter DeSantis. Tomorrow's going to be Swamy in the keynote. Adrian Cockcroft is here. Former AWS, former network Netflix CTO, currently an analyst. You got your own firm now. You're out there. Great to see you again. Thanks for coming on theCUBE. >> Yeah, thanks. >> We heard you on at Super Cloud, you gave some really good insights there back in August. So now as an outsider, you come in obviously, you got to be impressed with the size and the ecosystem and the energy. Of course. What were your thoughts on, you know what you've seen so far, today's keynotes, last night Peter DeSantis, what stood out to you? >> Yeah, I think it's great to be back at Reinvent again. We're kind of pretty much back to where we were before the pandemic sort of shut it down. This is a little, it's almost as big as the, the largest one that we had before. And everyone's turned up. It just feels like we're back. So that's really good to see. And it's a slightly different style. I think there were was more sort of video production things happening. I think in this keynote, more storytelling. I'm not sure it really all stitched together very well. Right. Some of the stories like, how does that follow that? So there were a few things there and some of there were spelling mistakes on the slides, you know that ELT instead of ETL and they spelled ZFS wrong and something. So it just seemed like there was, I'm not quite sure just maybe a few things were sort of rushed at the last minute. >> Not really AWS like, was it? It's kind of remind the Patriots Paul, you know Bill Belichick's teams are fumbling all over the place. >> That's right. That's right. >> Part of it may be, I mean the sort of the market. They have a leader in marketing right now but they're going to have a CMO. So that's sort of maybe as lack of a single threaded leader for this thing. Everything's being shared around a bit more. So maybe, I mean, it's all fixable and it's mine. This is minor stuff. I'm just sort of looking at it and going there's a few things that looked like they were not quite as good as they could have been in the way it was put together. Right? >> But I mean, you're taking a, you know a year of not doing Reinvent. Yeah. Being isolated. You know, we've certainly seen it with theCUBE. It's like, okay, it's not like riding a bike. You know, things that, you know you got to kind of relearn the muscle memories. It's more like golf than is bicycle riding. >> Well I've done AWS keynotes myself. And they are pretty much scrambled. It looks nice, but there's a lot of scrambling leading up to when it actually goes. Right? And sometimes you can, you sometimes see a little kind of the edges of that, and sometimes it's much more polished. But you know, overall it's pretty good. I think Peter DeSantis keynote yesterday was a lot of really good meat there. There was some nice presentations, and some great announcements there. And today I was, I thought I was a little disappointed with some of the, I thought they could have been more. I think the way Andy Jesse did it, he crammed more announcements into his keynote, and Adam seems to be taking sort of a bit more of a measured approach. There were a few things he picked up on and then I'm expecting more to be spread throughout the rest of the day. >> This was more poetic. Right? He took the universe as the analogy for data, the ocean for security. Right? The Antarctic was sort of. >> Yeah. It looked pretty, >> yeah. >> But I'm not sure that was like, we're not here really to watch nature videos >> As analysts and journalists, You're like, come on. >> Yeah, >> Give it the meat >> That was kind the thing, yeah, >> It has always been the AWS has always been Reinvent has always been a shock at our approach. 100, 150 announcements. And they're really, that kind of pressure seems to be off them now. Their position at the top of the market seems to be unshakeable. There's no clear competition that's creeping up behind them. So how does that affect the messaging you think that AWS brings to market when it doesn't really have to prove that it's a leader anymore? It can go after maybe more of the niche markets or fix the stuff that's a little broken more fine tuning than grandiose statements. >> I think so AWS for a long time was so far out that they basically said, "We don't think about the competition, we are listen to the customers." And that was always the statement that works as long as you're always in the lead, right? Because you are introducing the new idea to the customer. Nobody else got there first. So that was the case. But in a few areas they aren't leading. Right? You could argue in machine learning, not necessarily leading in sustainability. They're not leading and they don't want to talk about some of these areas and-- >> Database. I mean arguably, >> They're pretty strong there, but the areas when you are behind, it's like they kind of know how to play offense. But when you're playing defense, it's a different set of game. You're playing a different game and it's hard to be good at both. I think and I'm not sure that they're really used to following somebody into a market and making a success of that. So there's something, it's a little harder. Do you see what I mean? >> I get opinion on this. So when I say database, David Foyer was two years ago, predicted AWS is going to have to converge somehow. They have no choice. And they sort of touched on that today, right? Eliminating ETL, that's one thing. But Aurora to Redshift. >> Yeah. >> You know, end to end. I'm not sure it's totally, they're fully end to end >> That's a really good, that is an excellent piece of work, because there's a lot of work that it eliminates. There's are clear pain points, but then you've got sort of the competing thing, is like the MongoDB and it's like, it's just a way with one database keeps it simple. >> Snowflake, >> Or you've got on Snowflake maybe you've got all these 20 different things you're trying to integrate at AWS, but it's kind of like you have a bag of Lego bricks. It's my favorite analogy, right? You want a toy for Christmas, you want a toy formula one racing car since that seems to be the theme, right? >> Okay. Do you want the fully built model that you can play with right now? Or do you want the Lego version that you have to spend three days building. Right? And AWS is the Lego technique thing. You have to spend some time building it, but once you've built it, you can evolve it, and you'll still be playing those are still good bricks years later. Whereas that prebuilt to probably broken gathering dust, right? So there's something about having an vulnerable architecture which is harder to get into, but more durable in the long term. And so AWS tends to play the long game in many ways. And that's one of the elements that they do that and that's good, but it makes it hard to consume for enterprise buyers that are used to getting it with a bow on top. And here's the solution. You know? >> And Paul, that was always Andy Chassy's answer to when we would ask him, you know, all these primitives you're going to make it simpler. You see the primitives give us the advantage to turn on a dime in the marketplace. And that's true. >> Yeah. So you're saying, you know, you take all these things together and you wrap it up, and you put a snowflake on top, and now you've got a simple thing or a Mongo or Mongo atlas or whatever. So you've got these layered platforms now which are making it simpler to consume, but now you're kind of, you know, you're all stuck in that ecosystem, you know, so it's like what layer of abstractions do you want to tie yourself to, right? >> The data bricks coming at it from more of an open source approach. But it's similar. >> We're seeing Amazon direct more into vertical markets. They spotlighted what Goldman Sachs is doing on their platform. They've got a variety of platforms that are supposedly targeted custom built for vertical markets. How do successful do you see that play being? Is this something that the customers you think are looking for, a fully integrated Amazon solution? >> I think so. There's usually if you look at, you know the MongoDB or data stacks, or the other sort of or elastic, you know, they've got the specific solution with the people that really are developing the core technology, there's open source equivalent version. The AWS is running, and it's usually maybe they've got a price advantage or it's, you know there's some data integration in there or it's somehow easier to integrate but it's not stopping those companies from growing. And what it's doing is it's endorsing that platform. So if you look at the collection of databases that have been around over the last few years, now you've got basically Elastic Mongo and Cassandra, you know the data stacks as being endorsed by the cloud vendors. These are winners. They're going to be around for a very long time. You can build yourself on that architecture. But what happened to Couch base and you know, a few of the other ones, you know, they don't really fit. Like how you going to bait? If you are now becoming an also ran, because you didn't get cloned by the cloud vendor. So the customers are going is that a safe place to be, right? >> But isn't it, don't they want to encourage those partners though in the name of building the marketplace ecosystem? >> Yeah. >> This is huge. >> But certainly the platform, yeah, the platform encourages people to do more. And there's always room around the edge. But the mainstream customers like that really like spending the good money, are looking for something that's got a long term life to it. Right? They're looking for a long commitment to that technology and that it's going to be invested in and grow. And the fact that the cloud providers are adopting and particularly AWS is adopting some of these technologies means that is a very long term commitment. You can base, you know, you can bet your future architecture on that for a decade probably. >> So they have to pick winners. >> Yeah. So it's sort of picking winners. And then if you're the open source company that's now got AWS turning up, you have to then leverage it and use that as a way to grow the market. And I think Mongo have done an excellent job of that. I mean, they're top level sponsors of Reinvent, and they're out there messaging that and doing a good job of showing people how to layer on top of AWS and make it a win-win both sides. >> So ever since we've been in the business, you hear the narrative hardware's going to die. It's just, you know, it's commodity and there's some truth to that. But hardware's actually driving good gross margins for the Cisco's of the world. Storage companies have always made good margins. Servers maybe not so much, 'cause Intel sucked all the margin out of it. But let's face it, AWS makes most of its money. We know on compute, it's got 25 plus percent operating margins depending on the seasonality there. What do you think happens long term to the infrastructure layer discussion? Okay, commodity cloud, you know, we talk about super cloud. Do you think that AWS, and the other cloud vendors that infrastructure, IS gets commoditized and they have to go up market or you see that continuing I mean history would say that still good margins in hardware. What are your thoughts on that? >> It's not commoditizing, it's becoming more specific. We've got all these accelerators and custom chips now, and this is something, this almost goes back. I mean, I was with some micro systems 20,30 years ago and we developed our own chips and HP developed their own chips and SGI mips, right? We were like, the architectures were all squabbling of who had the best processor chips and it took years to get chips that worked. Now if you make a chip and it doesn't work immediately, you screwed up somewhere right? It's become the technology of building these immensely complicated powerful chips that has become commoditized. So the cost of building a custom chip, is now getting to the point where Apple and Amazon, your Apple laptop has got full custom chips your phone, your iPhone, whatever and you're getting Google making custom chips and we've got Nvidia now getting into CPUs as well as GPUs. So we're seeing that the ability to build a custom chip, is becoming something that everyone is leveraging. And the cost of doing that is coming down to startups are doing it. So we're going to see many, many more, much more innovation I think, and this is like Intel and AMD are, you know they've got the compatibility legacy, but of the most powerful, most interesting new things I think are going to be custom. And we're seeing that with Graviton three particular in the three E that was announced last night with like 30, 40% whatever it was, more performance for HPC workloads. And that's, you know, the HPC market is going to have to deal with cloud. I mean they are starting to, and I was at Supercomputing a few weeks ago and they are tiptoeing around the edge of cloud, but those supercomputers are water cold. They are monsters. I mean you go around supercomputing, there are plumbing vendors on the booth. >> Of course. Yeah. >> Right? And they're highly concentrated systems, and that's really the only difference, is like, is it water cooler or echo? The rest of the technology stack is pretty much off the shelf stuff with a few tweets software. >> You point about, you know, the chips and what AWS is doing. The Annapurna acquisition. >> Yeah. >> They're on a dramatically different curve now. I think it comes down to, again, David Floyd's premise, really comes down to volume. The arm wafer volumes are 10 x those of X 86, volume always wins. And the economics of semis. >> That kind of got us there. But now there's also a risk five coming along if you, in terms of licensing is becoming one of the bottlenecks. Like if the cost of building a chip is really low, then it comes down to licensing costs and do you want to pay the arm license And the risk five is an open source chip set which some people are starting to use for things. So your dis controller may have a risk five in it, for example, nowadays, those kinds of things. So I think that's kind of the the dynamic that's playing out. There's a lot of innovation in hardware to come in the next few years. There's a thing called CXL compute express link which is going to be really interesting. I think that's probably two years out, before we start seeing it for real. But it lets you put glue together entire rack in a very flexible way. So just, and that's the entire industry coming together around a single standard, the whole industry except for Amazon, in fact just about. >> Well, but maybe I think eventually they'll get there. Don't use system on a chip CXL. >> I have no idea whether I have no knowledge about whether going to do anything CXL. >> Presuming I'm not trying to tap anything confidential. It just makes sense that they would do a system on chip. It makes sense that they would do something like CXL. Why not adopt the standard, if it's going to be as the cost. >> Yeah. And so that was one of the things out of zip computing. The other thing is the low latency networking with the elastic fabric adapter EFA and the extensions to that that were announced last night. They doubled the throughput. So you get twice the capacity on the nitro chip. And then the other thing was this, this is a bit technical, but this scalable datagram protocol that they've got which basically says, if I want to send a message, a packet from one machine to another machine, instead of sending it over one wire, I consider it over 16 wires in parallel. And I will just flood the network with all the packets and they can arrive in any order. This is why it isn't done normally. TCP is in order, the packets come in order they're supposed to, but this is fully flooding them around with its own fast retry and then they get reassembled at the other end. So they're not just using this now for HPC workloads. They've turned it on for TCP for just without any change to your application. If you are trying to move a large piece of data between two machines, and you're just pushing it down a network, a single connection, it takes it from five gigabits per second to 25 gigabits per second. A five x speed up, with a protocol tweak that's run by the Nitro, this is super interesting. >> Probably want to get all that AIML that stuff is going on. >> Well, the AIML stuff is leveraging it underneath, but this is for everybody. Like you're just copying data around, right? And you're limited, "Hey this is going to get there five times faster, pushing a big enough chunk of data around." So this is turning on gradually as the nitro five comes out, and you have to enable it at the instance level. But it's a super interesting announcement from last night. >> So the bottom line bumper sticker on commoditization is what? >> I don't think so. I mean what's the APIs? Your arm compatible, your Intel X 86 compatible or your maybe risk five one day compatible in the cloud. And those are the APIs, right? That's the commodity level. And the software is now, the software ecosystem is super portable across those as we're seeing with Apple moving from Intel to it's really not an issue, right? The software and the tooling is all there to do that. But underneath that, we're going to see an arms race between the top providers as they all try and develop faster chips for doing more specific things. We've got cranium for training, that instance has they announced it last year with 800 gigabits going out of a single instance, 800 gigabits or no, but this year they doubled it. Yeah. So 1.6 terabytes out of a single machine, right? That's insane, right? But what you're doing is you're putting together hundreds or thousands of those to solve the big machine learning training problems. These super, these enormous clusters that they're being formed for doing these massive problems. And there is a market now, for these incredibly large supercomputer clusters built for doing AI. That's all bandwidth limited. >> And you think about the timeframe from design to tape out. >> Yeah. >> Is just getting compressed It's relative. >> It is. >> Six is going the other way >> The tooling is all there. Yeah. >> Fantastic. Adrian, always a pleasure to have you on. Thanks so much. >> Yeah. >> Really appreciate it. >> Yeah, thank you. >> Thank you Paul. >> Cheers. All right. Keep it right there everybody. Don't forget, go to thecube.net, you'll see all these videos. Go to siliconangle.com, We've got features with Adam Selipsky, we got my breaking analysis, we have another feature with MongoDB's, Dev Ittycheria, Ali Ghodsi, as well Frank Sluman tomorrow. So check that out. Keep it right there. You're watching theCUBE, the leader in enterprise and emerging tech, right back. (soft techno upbeat music)
SUMMARY :
Great to see you again. and the ecosystem and the energy. Some of the stories like, It's kind of remind the That's right. I mean the sort of the market. the muscle memories. kind of the edges of that, the analogy for data, As analysts and journalists, So how does that affect the messaging always in the lead, right? I mean arguably, and it's hard to be good at both. But Aurora to Redshift. You know, end to end. of the competing thing, but it's kind of like you And AWS is the Lego technique thing. to when we would ask him, you know, and you put a snowflake on top, from more of an open source approach. the customers you think a few of the other ones, you know, and that it's going to and doing a good job of showing people and the other cloud vendors the HPC market is going to Yeah. and that's really the only difference, the chips and what AWS is doing. And the economics of semis. So just, and that's the entire industry Well, but maybe I think I have no idea whether if it's going to be as the cost. and the extensions to that AIML that stuff is going on. and you have to enable And the software is now, And you think about the timeframe Is just getting compressed Yeah. Adrian, always a pleasure to have you on. the leader in enterprise
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Adam Selipsky | PERSON | 0.99+ |
David Floyd | PERSON | 0.99+ |
Peter DeSantis | PERSON | 0.99+ |
Paul | PERSON | 0.99+ |
Ali Ghodsi | PERSON | 0.99+ |
Adrian Cockcroft | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Frank Sluman | PERSON | 0.99+ |
Paul Gillon | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Apple | ORGANIZATION | 0.99+ |
Andy Chassy | PERSON | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
Adam | PERSON | 0.99+ |
Dev Ittycheria | PERSON | 0.99+ |
Andy Jesse | PERSON | 0.99+ |
Dave Villante | PERSON | 0.99+ |
August | DATE | 0.99+ |
two machines | QUANTITY | 0.99+ |
Bill Belichick | PERSON | 0.99+ |
10 | QUANTITY | 0.99+ |
Cisco | ORGANIZATION | 0.99+ |
today | DATE | 0.99+ |
last year | DATE | 0.99+ |
1.6 terabytes | QUANTITY | 0.99+ |
AMD | ORGANIZATION | 0.99+ |
Goldman Sachs | ORGANIZATION | 0.99+ |
hundreds | QUANTITY | 0.99+ |
one machine | QUANTITY | 0.99+ |
three days | QUANTITY | 0.99+ |
Adrian | PERSON | 0.99+ |
800 gigabits | QUANTITY | 0.99+ |
Today | DATE | 0.99+ |
iPhone | COMMERCIAL_ITEM | 0.99+ |
David Foyer | PERSON | 0.99+ |
two years | QUANTITY | 0.99+ |
ORGANIZATION | 0.99+ | |
yesterday | DATE | 0.99+ |
this year | DATE | 0.99+ |
Snowflake | TITLE | 0.99+ |
Nvidia | ORGANIZATION | 0.99+ |
five times | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
Netflix | ORGANIZATION | 0.99+ |
thecube.net | OTHER | 0.99+ |
Intel | ORGANIZATION | 0.99+ |
five | QUANTITY | 0.99+ |
both sides | QUANTITY | 0.99+ |
Mongo | ORGANIZATION | 0.99+ |
Christmas | EVENT | 0.99+ |
last night | DATE | 0.99+ |
HP | ORGANIZATION | 0.98+ |
25 plus percent | QUANTITY | 0.98+ |
thousands | QUANTITY | 0.98+ |
20,30 years ago | DATE | 0.98+ |
pandemic | EVENT | 0.98+ |
both | QUANTITY | 0.98+ |
two years ago | DATE | 0.98+ |
twice | QUANTITY | 0.98+ |
tomorrow | DATE | 0.98+ |
X 86 | COMMERCIAL_ITEM | 0.98+ |
Antarctic | LOCATION | 0.98+ |
Patriots | ORGANIZATION | 0.98+ |
siliconangle.com | OTHER | 0.97+ |
Stephen Chin, JFrog | KubeCon + CloudNativeCon NA 2022
>>Good afternoon, brilliant humans, and welcome back to the Cube. We're live in Detroit, Michigan at Cub Con, and I'm joined by John Furrier. John three exciting days buzzing. How you doing? >>That's great. I mean, we're coming down to the third day. We're keeping the energy going, but this segment's gonna be awesome. The CD foundation's doing amazing work. Developers are gonna be running businesses and workflows are changing. Productivity's the top conversation, and you're gonna start to see a coalescing of the communities who are continuous delivery, and it's gonna be awesome. >>And, and our next guess is an outstanding person to talk about this. We are joined by Stephen Chin, the chair of the CD Foundation. Steven, thanks so much for being here. >>No, no, my pleasure. I mean, this has been an amazing week quote that CubeCon with all of the announcements, all of the people who came out here to Detroit and, you know, fantastic. Like just walking around, you bump into all the right people here. Plus we held a CD summit zero day events, and had a lot of really exciting announcements this week. >>Gotta love the shirt. I gotta say, it's one of my favorites. Love the logos. Love the love the branding. That project got traction. What's the news in the CD foundation? I tried to sneak in the back. I got a little laid into your co-located event. It was packed. Everyone's engaged. It was really looked, look really cool. Give us the update. >>What's the news? Yeah, I know. So we, we had a really, really powerful event. All the key practitioners, the open source leads and folks were there. And one of, one of the things which I think we've done a really good job in the past six months with the CD foundation is getting back to the roots and focusing on technical innovation, right? This is what drives foundations, having strong projects, having people who are building innovation, and also bringing in a new innovation. So one of the projects which we added to the CD foundation this week is called Persia. So it's a, it's a decentralized package repository for getting open source libraries. And it solves a lot of the problems which you get when you have centralized infrastructure. You don't have the right security certificates, you don't have the right verification libraries. And these, these are all things which large companies provision and build out inside of their infrastructure. But the open source communities don't have the benefit of the same sort of really, really strong architecture. A lot of, a lot of the systems we depend upon. It's >>A good point, yeah. >>Yeah. I mean, if you think about the systems that developers depend upon, we depend upon, you know, npm, ruby Gems, Mayn Central, and these systems been around for a while. Like they serve the community well, right? They're, they're well supported by the companies and it's, it's, it's really a great contribution that they give us. But every time there's an outage or there's a security issue, guess, guess how many security issues that our, our research team found at npm? Just ballpark. >>74. >>So there're >>It's gotta be thousands. I mean, it's gotta be a lot of tons >>Of Yeah, >>They, they're currently up to 60,000 >>Whoa. >>Vulnerable, malicious packages in NPM and >>Oh my gosh. So that's a super, that's a jar number even. I know it was gonna be huge, but Holy mo. >>Yeah. So that's a software supply chain in actually right there. So that's, that's open source. Everything's out there. What's, how do, how does, how do you guys fix that? >>Yeah, so per peria kind of shifts the whole model. So when, when you think about a system that can be sustained, it has to be something which, which is not just one company. It has to be a, a, a set of companies, be vendor neutral and be decentralized. So that's why we donated it to the Continuous Delivery Foundation. So that can be that governance body, which, which makes sure it's not a single company, it is to use modern technologies. So you, you, you just need something which is immutable, so it can't be changed. So you can rely on it. It has to have a strong transaction ledger so you can see all of the history of it. You can build up your software, build materials off of it, and it, it has to have a strong peer-to-peer architecture, so it can be sustained long term. >>Steven, you mentioned something I want to just get back to. You mentioned outages and disruption. I, you didn't, you didn't say just the outages, but this whole disruption angle is interesting if something happens. Talk about the impact of the developer. They stalled, inefficiencies create basically disruption. >>No, I mean, if, if, so, so if you think about most DevOps teams in big companies, they support hundreds or thousands of teams and an hour of outage. All those developers, they, they can't program, they can't work. And that's, that's a huge loss of productivity for the company. Now, if you, if you take that up a level when MPM goes down for an hour, how many millions of man hours are wasted by not being able to get your builds working by not being able to get your codes to compile. Like it's, it's >>Like, yeah, I mean, it's almost hard to fathom. I mean, everyone's, It's stopped. Exactly. It's literally like having the plug pulled >>Exactly on whenever you're working on, That's, that's the fundamental problem we're trying to solve. Is it, it needs to be on a, like a well supported, well architected peer to peer network with some strong backing from big companies. So the company is working on Persia, include J Frog, which who I work for, Docker, Oracle. We have Deploy hub, Huawei, a whole bunch of other folks who are also helping out. And when you look at all of those folks, they all have different interests, but it's designed in a way where no single party has control over the network. So really it's, it's a system system. You, you're not relying upon one company or one logo. You're relying upon a well-architected open source implementation that everyone can rely >>On. That's shared software, but it's kind of a fault tolerant feature too. It's like, okay, if something happens here, you have a distributed piece of it, decentralized, you're not gonna go down. You can remediate. All right, so where's this go next? I mean, cuz we've been talking about the role of developer. This needs to be a modern, I won't say modern upgrade, but like a modern workflow or value chain. What's your vision? How do you see that? Cuz you're the center of the CD foundation coming together. People are gonna be coalescing multiple groups. Yeah. >>What's the, No, I think this is a good point. So there, there's a, a lot of different continuous delivery, continuous integration technologies. We're actually, from a Linux Foundation standpoint, we're coalescing all the continued delivery events into one big conference >>Next. You just made an announcement about this earlier this week. Tell us about CD events. What's going on, what's in, what's in the cooker? >>Yeah, and I think one of the big announcements we had was the 0.1 release of CD events. And CD events allows you to take all these systems and connect them in an event scalable, event oriented architecture. The first integration is between Tecton and Capin. So now you can get CD events flowing cleanly between your, your continuous delivery and your observability. And this extends through your entire DevOps pipeline. We all, we all need a standards based framework Yep. For how we get all the disparate continuous integration, continuous delivery, observability systems to, to work together. That's also high performance. It scales with our needs and it, it kind of gives you a future architecture to build on top of. So a lot of the companies I was talking with at the CD summit Yeah. They were very excited about not only using this with the projects we announced, but using this internally as an architecture to build their own DevOps pipelines on. >>I bet that feels good to hear. >>Yeah, absolutely. Yeah. >>Yeah. You mentioned Teton, they just graduated. I saw how many projects have graduated? >>So we have two graduated projects right now. We have Jenkins, which is the first graduated project. Now Tecton is also graduated. And I think this shows that for Tecton it was, it was time, the very mature project, great support, getting a lot of users and having them join the set of graduated projects. And the continuous delivery foundation is a really strong portfolio. And we have a bunch of other projects which also are on their way towards graduation. >>Feels like a moment of social proof I bet. >>For you all. Yeah, yeah. Yeah. No, it's really good. Yeah. >>How long has the CD Foundation been around? >>The CD foundation has been around for, i, I won't wanna say the exact number of years, a few years now. >>Okay. >>But I, I think that it, it was formed because what we wanted is we wanted a foundation which was purpose built. So CNCF is a great foundation. It has a very large umbrella of projects and it takes kind of that big umbrella approach where a lot of different efforts are joining it, a lot of things are happening and you can get good traction, but it produces its own bottlenecks in process. Having a foundation which is just about continuous delivery caters to more of a DevOps, professional DevOps audience. I think this, this gives a good platform for best practices. We're working on a new CDF best practices Yeah. Guide. We're working when use cases with all the member companies. And it, it gives that thought leadership platform for continuous delivery, which you need to be an expert in that area >>And the best practices too. And to identify the issues. Because at the end of the day, with the big thing that's coming out of this is velocity and more developers coming on board. I mean, this is the big thing. More people doing more. Yeah. Well yeah, I mean you take this open source continuous thunder away, you have more developers coming in, they be more productive and then people are gonna even either on the DevOps side or on the straight AP upside. And this is gonna be a huge issue. And the other thing that comes out that I wanna get your thoughts on is the supply chain issue you talked about is hot verifications and certifications of code is such big issue. Can you share your thoughts on that? Because Yeah, this is become, I won't say a business model for some companies, but it's also becoming critical for security that codes verified. >>Yeah. Okay. So I, I think one of, one of the things which we're specifically doing with the Peria project, which is unique, is rather than distributing, for example, libraries that you developed on your laptop and compiled there, or maybe they were built on, you know, a runner somewhere like Travis CI or GitHub actions, all the libraries being distributed on Persia are built by the authorized nodes in the network. And then they're, they're verified across all of the authorized nodes. So you nice, you have a, a gar, the basic guarantee we're giving you is when you download something from the Peria network, you'll get exactly the same binary as if you built it yourself from source. >>So there's a lot of trust >>And, and transparency. Yeah, exactly. And if you remember back to like kind of the seminal project, which kicked off this whole supply chain security like, like whirlwind it was SolarWinds. Yeah. Yeah. And the exact problem they hit was the build ran, it produced a result, they modified the code of the bill of the resulting binary and then they signed it. So if you built with the same source and then you went through that same process a second time, you would've gotten a different result, which was a malicious pre right. Yeah. And it's very hard to risk take, to take a binary file Yep. And determine if there's malicious code in it. Cuz it's not like source code. You can't inspect it, you can't do a code audit. It's totally different. So I think we're solving a key part of this with Persia, where you're freeing open source projects from the possibility of having their binaries, their packages, their end reduces, tampered with. And also upstream from this, you do want to have verification of prs, people doing code reviews, making sure that they're looking at the source code. And I think there's a lot of good efforts going on in the open source security foundation. So I'm also on the governing board of Open ssf >>To Do you sleep? You have three jobs you've said on camera? No, I can't even imagine. Yeah. Didn't >>You just spin that out from this open source security? Is that the new one they >>Spun out? Yeah, So the Open Source Security foundation is one of the new Linux Foundation projects. They, they have been around for a couple years, but they did a big reboot last year around this time. And I think what they really did a good job of now is bringing all the industry players to the table, having dialogue with government agencies, figuring out like, what do we need to do to support open source projects? Is it more investment in memory, safe languages? Do we need to have more investment in, in code audits or like security reviews of opensource projects. Lot of things. And all of those things require money investments. And that's what all the companies, including Jay Frogger doing to advance open source supply chain security. I >>Mean, it's, it's really kind of interesting to watch some different demographics of the developers and the vendors and the customers. On one hand, if you're a hardware person company, you have, you talk zero trust your software, your top trust, so your trusted code, and you got zero trust. It's interesting, depending on where you're coming from, they're all trying to achieve the same thing. It means zero trust. Makes sense. But then also I got code, I I want trust. Trust and verified. So security is in everything now. So code. So how do you see that traversing over? Is it just semantics or what's your view on that? >>The, the right way of looking at security is from the standpoint of the hacker, because they're always looking for >>Well said, very well said, New >>Loop, hope, new loopholes, new exploits. And they're, they're very, very smart people. And I think when you, when you look some >>Of the smartest >>Yeah, yeah, yeah. I, I, I work with, well former hackers now, security researchers, >>They converted, they're >>Recruited. But when you look at them, there's like two main classes of like, like types of exploits. So some, some attacker groups. What they're looking for is they're looking for pulse zero days, CVEs, like existing vulnerabilities that they can exploit to break into systems. But there's an increasing number of attackers who are now on the opposite end of the spectrum. And what they're doing is they're creating their own exploits. So, oh, they're for example, putting malicious code into open source projects. Little >>Trojan horse status. Yeah. >>They're they're getting their little Trojan horses in. Yeah. Or they're finding supply chain attacks by maybe uploading a malicious library to NPM or to pii. And by creating these attacks, especially ones that start at the top of the supply chain, you have such a large reach. >>I was just gonna say, it could be a whole, almost gives me chills as we're talking about it, the systemic, So this is this >>Gnarly nation state attackers, like people who wanted serious >>Damages. Engineered hack just said they're high, highly funded. Highly skilled. Exactly. Highly agile, highly focused. >>Yes. >>Teams, team. Not in the teams. >>Yeah. And so, so one, one example of this, which actually netted quite a lot of money for the, for the hacker who exposed it was, you guys probably heard about this, but it was a, an attack where they uploaded a malicious library to npm with the same exact namespace as a corporate library and clever, >>Creepy. >>It's called a dependency injection attack. And what happens is if you, if you don't have the right sort of security package management guidelines inside your company, and it's just looking for the latest version of merging multiple repositories as like a, like a single view. A lot of companies were accidentally picking up the latest version, which was out in npm uploaded by Alex Spearson was the one who did the, the attack. And he simultaneously reported bug bounties on like a dozen different companies and netted 130 k. Wow. So like these sort of attacks that they're real Yep. They're exploitable. And the, the hackers >>Complex >>Are finding these sort of attacks now in our supply chain are the ones who really are the most dangerous. That's the biggest threat to us. >>Yeah. And we have stacker ones out there. You got a bunch of other services, the white hat hackers get the bounties. That's really important. All right. What's next? What's your vision of this show as we end Coan? What's the most important story coming outta Coan in your opinion? And what are you guys doing next? >>Well, I, I actually think this is, this is probably not what most hooks would say is the most exciting story to con, but I find this personally the best is >>I can't wait for this now. >>So, on, on Sunday, the CNCF ran the first kids' day. >>Oh. >>And so they had a, a free kids workshop for, you know, underprivileged kids for >>About, That's >>Detroit area. It was, it was taught by some of the folks from the CNCF community. So Arro, Eric hen my, my older daughter, Cassandra's also an instructor. So she also was teaching a raspberry pie workshop. >>Amazing. And she's >>Here and Yeah, Yeah. She's also here at the show. And when you think about it, you know, there's always, there's, there's, you know, hundreds of announcements this week, A lot of exciting technologies, some of which we've talked about. Yeah. But it's, it's really what matters is the community. >>It this is a community first event >>And the people, and like, if we're giving back to the community and helping Detroit's kids to get better at technology, to get educated, I think that it's a worthwhile for all of us to be here. >>What a beautiful way to close it. That is such, I'm so glad you brought that up and brought that to our attention. I wasn't aware of that. Did you know that was >>Happening, John? No, I know about that. Yeah. No, that was, And that's next generation too. And what we need, we need to get down into the elementary schools. We gotta get to the kids. They're all doing robotics club anyway in high school. Computer science is now, now a >>Sport, in my opinion. Well, I think that if you're in a privileged community, though, I don't think that every school's doing robotics. And >>That's why Well, Cal Poly, Cal Poly and the universities are stepping up and I think CNCF leadership is amazing here. And we need more of it. I mean, I'm, I'm bullish on this. I love it. And I think that's a really great story. No, >>I, I am. Absolutely. And, and it just goes to show how committed CNF is to community, Putting community first and Detroit. There has been such a celebration of Detroit this whole week. Stephen, thank you so much for joining us on the show. Best Wishes with the CD Foundation. John, thanks for the banter as always. And thank you for tuning in to us here live on the cube in Detroit, Michigan. I'm Savannah Peterson and we are having the best day. I hope you are too.
SUMMARY :
How you doing? We're keeping the energy going, but this segment's gonna be awesome. the chair of the CD Foundation. of the announcements, all of the people who came out here to Detroit and, you know, What's the news in the CD foundation? You don't have the right security certificates, you don't have the right verification libraries. you know, npm, ruby Gems, Mayn Central, I mean, it's gotta be a lot of tons So that's a super, that's a jar number even. What's, how do, how does, how do you guys fix that? It has to have a strong transaction ledger so you can see all of the history of it. Talk about the impact of the developer. No, I mean, if, if, so, so if you think about most DevOps teams It's literally like having the plug pulled And when you look at all of those folks, they all have different interests, you have a distributed piece of it, decentralized, you're not gonna go down. What's the, No, I think this is a good point. What's going on, what's in, what's in the cooker? And CD events allows you to take all these systems and connect them Yeah. I saw how many projects have graduated? And the continuous delivery foundation is a really strong portfolio. For you all. The CD foundation has been around for, i, I won't wanna say the exact number of years, it gives that thought leadership platform for continuous delivery, which you need to be an expert in And the other thing that comes out that I wanna get your thoughts on is So you nice, you have a, a gar, the basic guarantee And the exact problem they hit was the build ran, To Do you sleep? And I think what they really did a good job of now is bringing all the industry players to So how do you see that traversing over? And I think when you, when you look some Yeah, yeah, yeah. But when you look at them, there's like two main classes of like, like types Yeah. the supply chain, you have such a large reach. Engineered hack just said they're high, highly funded. Not in the teams. the same exact namespace as a corporate library the latest version, which was out in npm uploaded by Alex Spearson That's the biggest threat to us. And what are you guys doing next? the CNCF community. And she's And when you think about it, And the people, and like, if we're giving back to the community and helping Detroit's kids to get better That is such, I'm so glad you brought that up and brought that to our attention. into the elementary schools. And And I think that's a really great story. And thank you for tuning in to us here live
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Steven | PERSON | 0.99+ |
Stephen Chin | PERSON | 0.99+ |
Alex Spearson | PERSON | 0.99+ |
Stephen | PERSON | 0.99+ |
Continuous Delivery Foundation | ORGANIZATION | 0.99+ |
Cal Poly | ORGANIZATION | 0.99+ |
Detroit | LOCATION | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
John | PERSON | 0.99+ |
Cassandra | PERSON | 0.99+ |
Huawei | ORGANIZATION | 0.99+ |
130 k. | QUANTITY | 0.99+ |
Savannah Peterson | PERSON | 0.99+ |
hundreds | QUANTITY | 0.99+ |
John Furrier | PERSON | 0.99+ |
one | QUANTITY | 0.99+ |
Jay Frogger | PERSON | 0.99+ |
Mayn Central | ORGANIZATION | 0.99+ |
CNCF | ORGANIZATION | 0.99+ |
Tecton | ORGANIZATION | 0.99+ |
CD Foundation | ORGANIZATION | 0.99+ |
last year | DATE | 0.99+ |
Sunday | DATE | 0.99+ |
Docker | ORGANIZATION | 0.99+ |
Detroit, Michigan | LOCATION | 0.99+ |
Detroit, Michigan | LOCATION | 0.99+ |
thousands | QUANTITY | 0.99+ |
third day | QUANTITY | 0.99+ |
first event | QUANTITY | 0.99+ |
Linux Foundation | ORGANIZATION | 0.99+ |
Open Source Security | ORGANIZATION | 0.99+ |
one company | QUANTITY | 0.99+ |
KubeCon | EVENT | 0.99+ |
this week | DATE | 0.98+ |
CD foundation | ORGANIZATION | 0.98+ |
CNF | ORGANIZATION | 0.98+ |
one logo | QUANTITY | 0.98+ |
millions | QUANTITY | 0.98+ |
earlier this week | DATE | 0.98+ |
JFrog | PERSON | 0.98+ |
second time | QUANTITY | 0.98+ |
Teton | ORGANIZATION | 0.98+ |
J Frog | ORGANIZATION | 0.97+ |
Arro | PERSON | 0.97+ |
CloudNativeCon | EVENT | 0.97+ |
npm | ORGANIZATION | 0.97+ |
first integration | QUANTITY | 0.97+ |
GitHub | ORGANIZATION | 0.96+ |
an hour | QUANTITY | 0.96+ |
two main classes | QUANTITY | 0.96+ |
Persia | ORGANIZATION | 0.95+ |
up to 60,000 | QUANTITY | 0.95+ |
Capin | ORGANIZATION | 0.95+ |
hundreds of announcements | QUANTITY | 0.94+ |
zero days | QUANTITY | 0.94+ |
zero trust | QUANTITY | 0.94+ |
three jobs | QUANTITY | 0.93+ |
single company | QUANTITY | 0.92+ |
Cube | ORGANIZATION | 0.91+ |
single view | QUANTITY | 0.91+ |
Deploy hub | ORGANIZATION | 0.9+ |
past six months | DATE | 0.9+ |
CD | ORGANIZATION | 0.9+ |
ruby Gems | ORGANIZATION | 0.89+ |
NA 2022 | EVENT | 0.89+ |
Eric hen | PERSON | 0.87+ |
zero day | QUANTITY | 0.86+ |
single party | QUANTITY | 0.86+ |
Matt LeBlanc & Tom Leyden, Kasten by Veeam | VMware Explore 2022
(upbeat music) >> Hey everyone and welcome back to The Cube. We are covering VMware Explore live in San Francisco. This is our third day of wall to wall coverage. And John Furrier is here with me, Lisa Martin. We are excited to welcome two guests from Kasten by Veeam, please welcome Tom Laden, VP of marketing and Matt LeBlanc, not Joey from friends, Matt LeBlanc, the systems engineer from North America at Kasten by Veeam. Welcome guys, great to have you. >> Thank you. >> Thank you for having us. >> Tom-- >> Great, go ahead. >> Oh, I was going to say, Tom, talk to us about some of the key challenges customers are coming to you with. >> Key challenges that they have at this point is getting up to speed with Kubernetes. So everybody has it on their list. We want to do Kubernetes, but where are they going to start? Back when VMware came on the market, I was switching from Windows to Mac and I needed to run a Windows application on my Mac and someone told me, "Run a VM." Went to the internet, I downloaded it. And in a half hour I was done. That's not how it works with Kubernetes. So that's a bit of a challenge. >> I mean, Kubernetes, Lisa, remember the early days of The Cube Open Stack was kind of transitioning, Cloud was booming and then Kubernetes was the paper that became the thing that pulled everybody together. It's now de facto in my mind. So that's clear, but there's a lot of different versions of it and you hear VMware, they call it the dial tone. Usually, remember, Pat Gelter, it's a dial tone. Turns out that came from Kit Colbert or no, I think AJ kind of coined the term here, but it's since been there, it's been adopted by everyone. There's different versions. It's open source. AWS is involved. How do you guys look at the relationship with Kubernetes here and VMware Explore with Kubernetes and the customers because they have choices. They can go do it on their own. They can add a little bit with Lambda, Serverless. They can do more here. It's not easy. It's not as easy as people think it is. And then this is a skill gaps problem too. We're seeing a lot of these problems out there. What's your take? >> I'll let Matt talk to that. But what I want to say first is this is also the power of the cloud native ecosystem. The days are gone where companies were selecting one enterprise application and they were building their stack with that. Today they're building applications using dozens, if not hundreds of different components from different vendors or open source platforms. And that is really what creates opportunities for those cloud native developers. So maybe you want to... >> Yeah, we're seeing a lot of hybrid solutions out there. So it's not just choosing one vendor, AKS, EKS, or Tanzu. We're seeing all the above. I had a call this morning with a large healthcare provider and they have a hundred clusters and that's spread across AKS, EKS and GKE. So it is covering everything. Plus the need to have a on-prem solution manage it all. >> I got a stat, I got to share that I want to get your reactions and you can laugh or comment, whatever you want to say. Talk to big CSO, CXO, executive, big company, I won't say the name. We got a thousand developers, a hundred of them have heard of Kubernetes, okay. 10 have touched it and used it and one's good at it. And so his point is that there's a lot of Kubernetes need that people are getting aware. So it shows that there's more and more adoption around. You see a lot of managed services out there. So it's clear it's happening and I'm over exaggerating the ratio probably. But the point is the numbers kind of make sense as a thousand developers. You start to see people getting adoption to it. They're aware of the value, but being good at it is what we're hearing is one of those things. Can you guys share your reaction to that? Is that, I mean, it's hyperbole at some level, but it does point to the fact of adoption trends. You got to get good at it, you got to know how to use it. >> It's very accurate, actually. It's what we're seeing in the market. We've been doing some research of our own, and we have some interesting numbers that we're going to be sharing soon. Analysts don't have a whole lot of numbers these days. So where we're trying to run our own surveys to get a grasp of the market. One simple survey or research element that I've done myself is I used Google trends. And in Google trends, if you go back to 2004 and you compare VMware against Kubernetes, you get a very interesting graph. What you're going to see is that VMware, the adoption curve is practically complete and Kubernetes is clearly taking off. And the volume of searches for Kubernetes today is almost as big as VMware. So that's a big sign that this is starting to happen. But in this process, we have to get those companies to have all of their engineers to be up to speed on Kubernetes. And that's one of the community efforts that we're helping with. We built a website called learning.kasten.io We're going to rebrand it soon at CubeCon, so stay tuned, but we're offering hands on labs there for people to actually come learn Kubernetes with us. Because for us, the faster the adoption goes, the better for our business. >> I was just going to ask you about the learning. So there's a big focus here on educating customers to help dial down the complexity and really get them, these numbers up as John was mentioning. >> And we're really breaking it down to the very beginning. So at this point we have almost 10 labs as we call them up and they start really from install a Kubernetes Cluster and people really hands on are going to install a Kubernetes Cluster. They learn to build an application. They learn obviously to back up the application in the safest way. And then there is how to tune storage, how to implement security, and we're really building it up so that people can step by step in a hands on way learn Kubernetes. >> It's interesting, this VMware Explore, their first new name change, but VMWorld prior, big community, a lot of customers, loyal customers, but they're classic and they're foundational in enterprises and let's face it. Some of 'em aren't going to rip out VMware anytime soon because the workloads are running on it. So in Broadcom we'll have some good action to maybe increase prices or whatnot. So we'll see how that goes. But the personas here are definitely going cloud native. They did with Tanzu, was a great thing. Some stuff was coming off, the fruit's coming off the tree now, you're starting to see it. CNCF has been on this for a long, long time, CubeCon's coming up in Detroit. And so that's just always been great, 'cause you had the day zero event and you got all kinds of community activity, tons of developer action. So here they're talking, let's connect to the developer. There the developers are at CubeCon. So the personas are kind of connecting or overlapping. I'd love to get your thoughts, Matt on? >> So from the personnel that we're talking to, there really is a split between the traditional IT ops and a lot of the people that are here today at VMWare Explore, but we're also talking with the SREs and the dev ops folks. What really needs to happen is we need to get a little bit more experience, some more training and we need to get these two groups to really start to coordinate and work together 'cause you're basically moving from that traditional on-prem environment to a lot of these traditional workloads and the only way to get that experience is to get your hands dirty. >> Right. >> So how would you describe the persona specifically here versus say CubeCon? IT ops? >> Very, very different, well-- >> They still go ahead. Explain. >> Well, I mean, from this perspective, this is all about VMware and everything that they have to offer. So we're dealing with a lot of administrators from that regard. On the Kubernetes side, we have site reliability engineers and their goal is exactly as their title describes. They want to architect arch applications that are very resilient and reliable and it is a different way of working. >> I was on a Twitter spaces about SREs and dev ops and there was people saying their title's called dev ops. Like, no, no, you do dev ops, you don't really, you're not the dev ops person-- >> Right, right. >> But they become the dev ops person because you're the developer running operations. So it's been weird how dev ops been co-opted as a position. >> And that is really interesting. One person told me earlier when I started Kasten, we have this new persona. It's the dev ops person. That is the person that we're going after. But then talking to a few other people who were like, "They're not falling from space." It's people who used to do other jobs who now have a more dev ops approach to what they're doing. It's not a new-- >> And then the SRE conversation was in site, reliable engineer comes from Google, from one person managing multiple clusters to how that's evolved into being the dev ops. So it's been interesting and this is really the growth of scale, the 10X developer going to more of the cloud native, which is okay, you got to run ops and make the developer go faster. If you look at the stuff we've been covering on The Cube, the trends have been cloud native developers, which I call dev ops like developers. They want to go faster. They want self-service and they don't want to slow down. They don't want to deal with BS, which is go checking security code, wait for the ops team to do something. So data and security seem to be the new ops. Not so much IT ops 'cause that's now cloud. So how do you guys see that in, because Kubernetes is rationalizing this, certainly on the compute side, not so much on storage yet but it seems to be making things better in that grinding area between dev and these complicated ops areas like security data, where it's constantly changing. What do you think about that? >> Well there are still a lot of specialty folks in that area in regards to security operations. The whole idea is be able to script and automate as much as possible and not have to create a ticket to request a VM to be billed or an operating system or an application deployed. They're really empowered to automatically deploy those applications and keep them up. >> And that was the old dev ops role or person. That was what dev ops was called. So again, that is standard. I think at CubeCon, that is something that's expected. >> Yes. >> You would agree with that. >> Yeah. >> Okay. So now translating VM World, VMware Explore to CubeCon, what do you guys see as happening between now and then? Obviously got re:Invent right at the end in that first week of December coming. So that's going to be two major shows coming in now back to back that're going to be super interesting for this ecosystem. >> Quite frankly, if you compare the persona, maybe you have to step away from comparing the personas, but really compare the conversations that we're having. The conversations that you're having at a CubeCon are really deep dives. We will have people coming into our booth and taking 45 minutes, one hour of the time of the people who are supposed to do 10 minute demos because they're asking more and more questions 'cause they want to know every little detail, how things work. The conversations here are more like, why should I learn Kubernetes? Why should I start using Kubernetes? So it's really early day. Now, I'm not saying that in a bad way. This is really exciting 'cause when you hear CNCF say that 97% of enterprises are using Kubernetes, that's obviously that small part of their world. Those are their members. We now want to see that grow to the entire ecosystem, the larger ecosystem. >> Well, it's actually a great thing, actually. It's not a bad thing, but I will counter that by saying I am hearing the conversation here, you guys'll like this on the Veeam side, the other side of the Veeam, there's deep dives on ransomware and air gap and configuration errors on backup and recovery and it's all about Veeam on the other side. Those are the guys here talking deep dive on, making sure that they don't get screwed up on ransomware, not Kubernete, but they're going to Kub, but they're now leaning into Kubernetes. They're crossing into the new era because that's the apps'll end up writing the code for that. >> So the funny part is all of those concepts, ransomware and recovery, they're all, there are similar concepts in the world of Kubernetes and both on the Veeam side as well as the Kasten side, we are supporting a lot of those air gap solutions and providing a ransomware recovery solution and from a air gap perspective, there are a many use cases where you do need to live. It's not just the government entity, but we have customers that are cruise lines in Europe, for example, and they're disconnected. So they need to live in that disconnected world or military as well. >> Well, let's talk about the adoption of customers. I mean this is the customer side. What's accelerating their, what's the conversation with the customer at base, not just here but in the industry with Kubernetes, how would you guys categorize that? And how does that get accelerated? What's the customer situation? >> A big drive to Kubernetes is really about the automation, self-service and reliability. We're seeing the drive to and reduction of resources, being able to do more with less, right? This is ongoing the way it's always been. But I was talking to a large university in Western Canada and they're a huge Veeam customer worth 7000 VMs and three months ago, they said, "Over the next few years, we plan on moving all those workloads to Kubernetes." And the reason for it is really to reduce their workload, both from administration side, cost perspective as well as on-prem resources as well. So there's a lot of good business reasons to do that in addition to the technical reliability concerns. >> So what is those specific reasons? This is where now you start to see the rubber hit the road on acceleration. >> So I would say scale and flexibility that ecosystem, that opportunity to choose any application from that or any tool from that cloud native ecosystem is a big driver. I wanted to add to the adoption. Another area where I see a lot of interest is everything AI, machine learning. One example is also a customer coming from Veeam. We're seeing a lot of that and that's a great thing. It's an AI company that is doing software for automated driving. They decided that VMs alone were not going to be good enough for all of their workloads. And then for select workloads, the more scalable one where scalability was more of a topic, would move to Kubernetes. I think at this point they have like 20% of their workloads on Kubernetes and they're not planning to do away with VMs. VMs are always going to be there just like mainframes still exist. >> Yeah, oh yeah. They're accelerating actually. >> We're projecting over the next few years that we're going to go to a 50/50 and eventually lean towards more Kubernetes than VMs, but it was going to be a mix. >> Do you have a favorite customer example, Tom, that you think really articulates the value of what Kubernetes can deliver to customers where you guys are really coming in and help to demystify it? >> I would think SuperStereo is a really great example and you know the details about it. >> I love the SuperStereo story. They were a AWS customer and they're running OpenShift version three and they need to move to OpenShift version four. There is no upgrade in place. You have to migrate all your apps. Now SuperStereo is a large French IT firm. They have over 700 developers in their environment and it was by their estimation that this was going to take a few months to get that migration done. We're able to go in there and help them with the automation of that migration and Kasten was able to help them architect that migration and we did it in the course of a weekend with two people. >> A weekend? >> A weekend. >> That's a hackathon. I mean, that's not real come on. >> Compared to thousands of man hours and a few months not to mention since they were able to retire that old OpenShift cluster, the OpenShift three, they were able to stop paying Jeff Bezos for a couple of those months, which is tens of thousands of dollars per month. >> Don't tell anyone, keep that down low. You're going to get shot when you leave this place. No, seriously. This is why I think the multi-cloud hybrid is interesting because these kinds of examples are going to be more than less coming down the road. You're going to see, you're going to hear more of these stories than not hear them because what containerization now Kubernetes doing, what Dockers doing now and the role of containers not being such a land grab is allowing Kubernetes to be more versatile in its approach. So I got to ask you, you can almost apply that concept to agility, to other scenarios like spanning data across clouds. >> Yes, and that is what we're seeing. So the call I had this morning with a large insurance provider, you may have that insurance provider, healthcare provider, they're across three of the major hyperscalers clouds and they do that for reliability. Last year, AWS went down, I think three times in Q4 and to have a plan of being able to recover somewhere else, you can actually plan your, it's DR, it's a planned migration. You can do that in a few hours. >> It's interesting, just the sidebar here for a second. We had a couple chats earlier today. We had the influences on and all the super cloud conversations and trying to get more data to share with the audience across multiple areas. One of them was Amazon and that super, the hyper clouds like Amazon, as your Google and the rest are out there, Oracle, IBM and everyone else. There's almost a consensus that maybe there's time for some peace amongst the cloud vendors. Like, "Hey, you've already won." (Tom laughs) Everyone's won, now let's just like, we know where everyone is. Let's go peace time and everyone, then 'cause the relationship's not going to change between public cloud and the new world. So there's a consensus, like what does peace look like? I mean, first of all, the pie's getting bigger. You're seeing ecosystems forming around all the big new areas and that's good thing. That's the tides rise and the pie's getting bigger, there's bigger market out there now so people can share and share. >> I've never worked for any of these big players. So I would have to agree with you, but peace would not drive innovation. And in my heart is with tech innovation. I love it when vendors come up with new solutions that will make things better for customers and if that means that we're moving from on-prem to cloud and back to on-prem, I'm fine with that. >> What excites me is really having the flexibility of being able to choose any provider you want because you do have open standards, being cloud native in the world of Kubernetes. I've recently discovered that the Canadian federal government had mandated to their financial institutions that, "Yes, you may have started all of your on cloud presence in Azure, you need to have an option to be elsewhere." So it's not like-- >> Well, the sovereign cloud is one of those big initiatives, but also going back to Java, we heard another guest earlier, we were thinking about Java, right once ran anywhere, right? So you can't do that today in a cloud, but now with containers-- >> You can. >> Again, this is, again, this is the point that's happening. Explain. >> So when you have, Kubernetes is a strict standard and all of the applications are written to that. So whether you are deploying MongoDB or Postgres or Cassandra or any of the other cloud native apps, you can deploy them pretty much the same, whether they're in AKS, EKS or on Tanzu and it makes it much easier. The world became just a lot less for proprietary. >> So that's the story that everybody wants to hear. How does that happen in a way that is, doesn't stall the innovation and the developer growth 'cause the developers are driving a lot of change. I mean, for all the talk in the industry, the developers are doing pretty good right now. They've got a lot of open source, plentiful, open source growing like crazy. You got shifting left in the CICD pipeline. You got tools coming out with Kubernetes. Infrastructure has code is almost a 100% reality right now. So there's a lot of good things going on for developers. That's not an issue. The issue is just underneath. >> It's a skillset and that is really one of the biggest challenges I see in our deployments is a lack of experience. And it's not everyone. There are some folks that have been playing around for the last couple of years with it and they do have that experience, but there are many people that are still young at this. >> Okay, let's do, as we wrap up, let's do a lead into CubeCon, it's coming up and obviously re:Invent's right behind it. Lisa, we're going to have a lot of pre CubeCon interviews. We'll interview all the committee chairs, program chairs. We'll get the scoop on that, we do that every year. But while we got you guys here, let's do a little pre-pre-preview of CubeCon. What can we expect? What do you guys think is going to happen this year? What does CubeCon look? You guys our big sponsor of CubeCon. You guys do a great job there. Thanks for doing that. The community really recognizes that. But as Kubernetes comes in now for this year, you're looking at probably the what third year now that I would say Kubernetes has been on the front burner, where do you see it on the hockey stick growth? Have we kicked the curve yet? What's going to be the level of intensity for Kubernetes this year? How's that going to impact CubeCon in a way that people may or may not think it will? >> So I think first of all, CubeCon is going to be back at the level where it was before the pandemic, because the show, as many other shows, has been suffering from, I mean, virtual events are not like the in-person events. CubeCon LA was super exciting for all the vendors last year, but the attendees were not really there yet. Valencia was a huge bump already and I think Detroit, it's a very exciting city I heard. So it's going to be a blast and it's going to be a huge attendance, that's what I'm expecting. Second I can, so this is going to be my third personally, in-person CubeCon, comparing how vendors evolved between the previous two. There's going to be a lot of interesting stories from vendors, a lot of new innovation coming onto the market. And I think the conversations that we're going to be having will yet, again, be much more about live applications and people using Kubernetes in production rather than those at the first in-person CubeCon for me in LA where it was a lot about learning still, we're going to continue to help people learn 'cause it's really important for us but the exciting part about CubeCon is you're talking to people who are using Kubernetes in production and that's really cool. >> And users contributing projects too. >> Also. >> I mean Lyft is a poster child there and you've got a lot more. Of course you got the stealth recruiting going on there, Apple, all the big guys are there. They have a booth and no one's attending you like, "Oh come on." Matt, what's your take on CubeCon? Going in, what do you see? And obviously a lot of dynamic new projects. >> I'm going to see much, much deeper tech conversations. As experience increases, the more you learn, the more you realize you have to learn more. >> And the sharing's going to increase too. >> And the sharing, yeah. So I see a lot of deep conversations. It's no longer the, "Why do I need Kubernetes?" It's more, "How do I architect this for my solution or for my environment?" And yeah, I think there's a lot more depth involved and the size of CubeCon is going to be much larger than we've seen in the past. >> And to finish off what I think from the vendor's point of view, what we're going to see is a lot of applications that will be a lot more enterprise-ready because that is the part that was missing so far. It was a lot about the what's new and enabling Kubernetes. But now that adoption is going up, a lot of features for different components still need to be added to have them enterprise-ready. >> And what can the audience expect from you guys at CubeCon? Any teasers you can give us from a marketing perspective? >> Yes. We have a rebranding sitting ready for learning website. It's going to be bigger and better. So we're not no longer going to call it, learning.kasten.io but I'll be happy to come back with you guys and present a new name at CubeCon. >> All right. >> All right. That sounds like a deal. Guys, thank you so much for joining John and me breaking down all things Kubernetes, talking about customer adoption, the challenges, but also what you're doing to demystify it. We appreciate your insights and your time. >> Thank you so much. >> Thank you very much. >> Our pleasure. >> Thanks Matt. >> For our guests and John Furrier, I'm Lisa Martin. You've been watching The Cube's live coverage of VMware Explore 2022. Thanks for joining us. Stay safe. (gentle music)
SUMMARY :
We are excited to welcome two customers are coming to you with. and I needed to run a and you hear VMware, they the cloud native ecosystem. Plus the need to have a They're aware of the value, And that's one of the community efforts to help dial down the And then there is how to tune storage, So the personas are kind of and a lot of the people They still go ahead. and everything that they have to offer. the dev ops person-- So it's been weird how dev ops That is the person that we're going after. the 10X developer going to and not have to create a ticket So again, that is standard. So that's going to be two of the people who are but they're going to Kub, and both on the Veeam side not just here but in the We're seeing the drive to to see the rubber hit the road that opportunity to choose any application They're accelerating actually. over the next few years and you know the details about it. and they need to move to I mean, that's not real come on. and a few months not to mention since and the role of containers and to have a plan of being and that super, the and back to on-prem, I'm fine with that. that the Canadian federal government this is the point that's happening. and all of the applications and the developer growth and that is really one of How's that going to impact and it's going to be a huge attendance, and no one's attending you like, the more you learn, And the sharing's and the size of CubeCon because that is the part It's going to be bigger and better. adoption, the challenges, of VMware Explore 2022.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Matt LeBlanc | PERSON | 0.99+ |
Lisa Martin | PERSON | 0.99+ |
Europe | LOCATION | 0.99+ |
John | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Pat Gelter | PERSON | 0.99+ |
Tom Leyden | PERSON | 0.99+ |
Matt | PERSON | 0.99+ |
John Furrier | PERSON | 0.99+ |
Tom Laden | PERSON | 0.99+ |
Lisa | PERSON | 0.99+ |
Tom | PERSON | 0.99+ |
Veeam | ORGANIZATION | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
one hour | QUANTITY | 0.99+ |
San Francisco | LOCATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
LA | LOCATION | 0.99+ |
Detroit | LOCATION | 0.99+ |
Joey | PERSON | 0.99+ |
Apple | ORGANIZATION | 0.99+ |
10 minute | QUANTITY | 0.99+ |
two people | QUANTITY | 0.99+ |
Last year | DATE | 0.99+ |
Jeff Bezos | PERSON | 0.99+ |
45 minutes | QUANTITY | 0.99+ |
John Furrier | PERSON | 0.99+ |
2004 | DATE | 0.99+ |
two guests | QUANTITY | 0.99+ |
Western Canada | LOCATION | 0.99+ |
ORGANIZATION | 0.99+ | |
7000 VMs | QUANTITY | 0.99+ |
Java | TITLE | 0.99+ |
97% | QUANTITY | 0.99+ |
hundreds | QUANTITY | 0.99+ |
last year | DATE | 0.99+ |
third | QUANTITY | 0.99+ |
Kit Colbert | PERSON | 0.99+ |
Second | QUANTITY | 0.99+ |
today | DATE | 0.99+ |
20% | QUANTITY | 0.99+ |
CNCF | ORGANIZATION | 0.99+ |
two groups | QUANTITY | 0.99+ |
first | QUANTITY | 0.99+ |
Tanzu | ORGANIZATION | 0.99+ |
Windows | TITLE | 0.99+ |
third day | QUANTITY | 0.99+ |
North America | LOCATION | 0.99+ |
dozens | QUANTITY | 0.99+ |
One | QUANTITY | 0.99+ |
over 700 developers | QUANTITY | 0.99+ |
learning.kasten.io | OTHER | 0.98+ |
AKS | ORGANIZATION | 0.98+ |
one | QUANTITY | 0.98+ |
Veeam | PERSON | 0.98+ |
VMware Explore 2022 | TITLE | 0.98+ |
VMWare Explore | ORGANIZATION | 0.98+ |
CubeCon | EVENT | 0.98+ |
One example | QUANTITY | 0.98+ |
Kubernetes | TITLE | 0.98+ |
three months ago | DATE | 0.98+ |
both | QUANTITY | 0.98+ |
EKS | ORGANIZATION | 0.97+ |
Lyft | ORGANIZATION | 0.97+ |
Today | DATE | 0.97+ |
Kasten | ORGANIZATION | 0.97+ |
this year | DATE | 0.97+ |
three times | QUANTITY | 0.97+ |
SuperStereo | TITLE | 0.97+ |
third year | QUANTITY | 0.96+ |
Vaughn Stewart, Pure Storage | VMware Explore 2022
>>Hey everyone. It's the cube live at VMware Explorer, 2022. We're at Mascone center and lovely, beautiful San Francisco. Dave Volante is with me, Lisa Martin. Beautiful weather here today. >>It is beautiful. I couldn't have missed this one because you know, the orange and the pure and VA right. Are history together. I had a, I had a switch sets. You >>Did. You were gonna have FOMO without a guest. Who's back. One of our longtime alumni V Stewart, VP of global technology alliances partners at pure storage one. It's great to have you back on the program, seeing you in 3d >>It's. It's so great to be here and we get a guest interviewer. So this >>Is >>Fantastic. Fly by. Fantastic. >>So talk to us, what's going on at pure. It's been a while since we had a chance to talk, >>Right. Well, well, besides the fact that it's great to see in person and to be back at a conference and see all of our customers, partners and prospects, you know, pure storage has just been on a tear just for your audience. Many, those who don't follow pure, right? We finished our last year with our Q4 being 41% year over year growth. And in the year, just under 2.2 billion, and then we come outta the gates this year, close our Q1 at 50% year over year, quarter quarterly growth. Have you ever seen a storage company or an infrastructure partner at 2 billion grow at that rate? >>Well, the thing was, was striking was that the acceleration of growth, because, you know, I mean, COVID, there were supply chain issues and you know, you saw that. And then, and we've seen this before at cloud companies, we see actually AWS as accelerated growth. So this is my premise here is you guys are actually becoming a cloud-like company building on top of, of infrastructure going from on-prem to cloud. But we're gonna talk about that. >>This is very much that super cloud premise. Well, >>It is. And, and, but I think it's it's one of the characteristics is you can actually, it, you know, we used to see companies, they go, they'd come out of escape velocity, and then they'd they'd growth would slow. I used to be at IDC. We'd see it. We'd see it. Okay. Down then it'd be single digits. You guys are seeing the opposite. >>It's it's not just our bookings. And by the way, I would be remiss if I didn't remind your audience that our second quarter earnings call is tomorrow. So we'll see how this philosophy and momentum keeps going. See, right. But besides the growth, right? All the external metrics around our business are increasing as well. So our net promoter score increased right at 85.2. We are the gold standard, not just in storage in infrastructure period. Like there's no one close to us, >>85. I mean, that's like, that's a, like apple, >>It's higher than apple than apple. It's apple higher than Tesla. It's higher than AWS shopping. And if you look in like our review of our products, flash rate is the leader in the gardener magic quadrant for, for storage array. It's been there for eight years. Port works is the leader in the GIGO OME radar for native Kubernetes storage three years in a row. Like just, it's great to be at a company that's hitting on all cylinders. You know, particularly at a time that's just got so much change going on in our >>Industry. Yeah. Tremendous amount of change. Talk about the, the VMware partnership from a momentum of velocity perspective what's going on there. And some of the things that you're accelerating. >>Absolutely. So VMware is, is the, the oldest or the longest tenured technology partner that we've had. I'm about to start my 10th year at pure storage. It feels like it was yesterday. When I joined, they were a, an Alliance partner before I joined. And so not to make that about me, but that's just like we built some of the key aspects around our first product, the flash array with VMware workloads in mind. And so we are a, a co-development partner. We've worked with them on a number of projects over years of, of late things that are top of mind is like the evolution of vials, the NV support for NVMe over fabric storage, more recently SRM support for automating Dr. With Viv a deployments, you know, and, and, and then our work around VMware ex extends to not just with VMware, they're really the catalyst for a lot of three way partnerships. So partnerships into our investments in data protection partners. Well, you gotta support V ADP for backing up the VMware space, our partnership within Nvidia, well, you gotta support NVA. I, so they can accelerate bringing those technologies into the enterprise. And so it's it, it's not just a, a, a, you know, unilateral partnership. It's a bidirectional piece because for a lot of customers, VMware's kind of like a touchpoint for managing the infrastructure. >>So how is that changing? Because you you've mentioned, you know, all the, the, the previous days, it was like, okay, let's get, make storage work. Let's do the integration. Let's do the hard work. It was kind of a race for the engineering teams to get there. All the storage companies would compete. And it was actually really good for the industry. Yeah, yeah. Right. Because it, it went from, you know, really complex, to much, much simpler. And now with the port works acquisition, it brings you closer to the whole DevOps scene. And you're seeing now VMware it's with its multi-cloud initiatives, really focusing on, you know, the applications and that, and that layer. So how does that dynamic evolve in terms of the partnership and, and where the focus is? >>So there's always in the last decade or so, right. There's always been some amount of overlap or competing with your partnerships, right. Something in their portfolios they're expanding maybe, or you expand you encroach on them. I think, I think two parts to how I would want to answer your question. The retrospective look V VMware is our number one ISV from a, a partner that we, we turn transactions with. The booking's growth that I shared with you, you could almost say is a direct reflection of how we're growing within that, that VMware marketplace. We are bringing a platform that I think customers feel services their workloads well today and gives them the flexibility of what might come in their cloud tomorrow. So you look at programs like our evergreen one subscription model, where you can deploy a consumption based subscription model. So very cloud-like only pay for what you use on-prem and turn that dial as you need to dial it into a, a cloud or, or multiple clouds. >>That's just one example. Looking forward, look, port works is probably the platform that VMware should have bought because when you look at today's story, right, when kit Culbert shared a, a cross cloud services, right, it was, it was the modern version of what VMware used to say, which was, here's a software defined data center. We're gonna standardize all your dissimilar hardware, another saying software defined management to standardize all your dissimilar clouds. We do that for Kubernetes. We talk about accelerating customers' adoption of Kubernetes by, by allowing developers, just to turn on an enable features, be its security, backup high availability, but we don't do it mono in a, you know, in a, in a homogeneous environment, we allow customers to do it heterogeneously so I can deploy VMware Tansu and connect it to Amazon EKS. I can switch one of those over to red head OpenShift, non disruptively, if I need to. >>Right? So as customers are going on this journey, particularly the enterprise customers, and they're not sure where they're going, we're giving them a platform that standardizes where they want to go. On-prem in the cloud and anywhere in between. And what's really interesting is our latest feature within the port works portfolio is called port works data services, and allows customers to deploy databases on demand. Like, install it, download the binaries. You have a cus there, you got a database, you got a database. You want Cassandra, you want Mongo, right? Yeah. You know, and, and for a lot of enterprise customers, who've kind of not, not know where to don't know where to start with port works. We found that to be a great place where they're like, I have this need side of my infrastructure. You can help me reduce cost time. Right. And deliver databases to teams. And that's how they kick off their Tansu journey. For example. >>It's interesting. So port works was the enabler you mentioned maybe VMware should above. Of course they had to get the value out of, out of pivotal. >>Understood. >>So, okay. Okay. So that, so how subsequent to the port works acquisition, how has it changed the way that you guys think about storage and how your customers are actually deploying and managing storage? >>Sure. So you touched base earlier on what was really great about the cloud and VMware was this evolution of simplifying storage technologies, usually operational functions, right? Making things simpler, more API driven, right. So they could be automated. I think what we're seeing customers do to today is first off, there's a tremendous rise in everyone wanting to do every customer, not every customer, a large portion of the customer bases, wanting to acquire technology on as OPEX. And it, I think it's really driven by like eliminate technical debt. I sign a short term agreement, our short, our shortest commitment's nine months. If we don't deliver around what we say, you walk away from us in nine months. Like you, you couldn't do that historically. Furthermore, I think customers are looking for the flexibility for our subscriptions, you know, more from between on-prem and cloud, as I shared earlier, is, is been a, a, a big driver in that space. >>And, and lastly, I would, would probably touch on our environmental and sustainability efforts. You saw this morning, Ragu in the keynote touch on what was it? Zero carbon consumption initiative, or ZCI my apologies to the veer folks. If I missed VO, you know, we've had, we've had sustainability into our products since day one. I don't know if you saw our inaugural ESG report that came out about 60 days ago, but the bottom line is, is, is our portfolio reduces the, the power directly consumed by storage race by up to 80%. And another aspect to look at is that 97% of all of the products that we sold in the last six years are still in the market today. They're not being put into, you know, into, to recycle bins and whatnot, pure storage's goal by the end of this decade is to further drive the efficiency of our platforms by another 66%. And so, you know, it's an ambitious goal, but we believe it's >>Important. Yeah. I was at HQ earlier this month, so I actually did see it. So, >>Yeah. And where is sustainability from a differentiation perspective, but also from a customer requirements perspective, I'm talking to a lot of customers that are putting that requirement when they're doing RFPs and whatnot on the vendors. >>I think we would like to all, and this is a free form VO comment here. So my apologies, but I think we'd all like to, to believe that we can reduce the energy consumption in the planet through these efforts. And in some ways maybe we can, what I fear in the technology space that I think we've all and, and many of your viewers have seen is there's always more tomorrow, right? There's more apps, more vendors, more offerings, more, more, more data to store. And so I think it's really just an imperative is you've gotta continue to be able to provide more services or store more data in this in yesterday's footprint tomorrow. A and part of the way they get to is through a sustainability effort, whether it's in chip design, you know, storage technologies, et cetera. And, and unfortunately it's, it's, it's something that organizations need to adopt today. And, and we've had a number of wins where customers have said, I thought I had to evacuate this data center. Your technology comes in and now it buys me more years of time in this in infrastructure. And so it can be very strategic to a lot of vendors who think their only option is like data center evacuation. >>So I don't want to, I, I don't wanna set you up, but I do want to have the super cloud conversation. And so let's go, and you, can you, you been around a long time, your, your technical, or you're more technical than I am, so we can at least sort of try to figure it out together when I first saw you guys. I think Lisa, so you and I were at, was it, when did you announce a block storage for AWS? The, was that 2019 >>Cloud block store? I believe block four years >>Ago. Okay. So 20 18, 20 18, 20 18. Okay. So we were there at, at accelerate at accelerate and I said, oh, that's interesting. So basically if I, if I go back there, it was, it was a hybrid model. You, you connecting your on-prem, you were, you were using, I think, priority E C two, you know, infrastructure to get high performance and connecting the two. And it was a singular experience yeah. Between on-prem and AWS in a pure customer saw pure. Right. Okay. So that was the first time I started to think about Supercloud. I mean, I think thought about it in different forms years ago, but that was the first actual instantiation. So my, my I'm interested in how that's evolved, how it's evolving, how it's going across clouds. Can you talk just conceptually about how that architecture is, is morphing? >>Sure. I just to set the expectations appropriately, right? We've got, we've got a lot of engineering work that that's going on right now. There's a bunch of stuff that I would love to share with you that I feel is right around the corner. And so hopefully we'll get across the line where we're at today, where we're at today. So the connective DNA of, of flash array, OnPrem cloud block store in the cloud, we can set up for, for, you know, what we call active. Dr. So, so again, customers are looking at these arrays is a, is a, is a pair that allows workloads to be put into the, put into the cloud or, or transferred between the cloud. That's kind of like your basic building, you know, blocking tackling 1 0 1. Like what do I do for Dr. Example, right? Or, or gimme an easy button to, to evacuate a data center where we've seen a, a lot of growth is around cloud block store and cloud block store really was released as like a software version of our hardware, Ray on-prem and it's been, and, and it hasn't been making the news, but it's been continually evolving. >>And so today the way you would look at cloud block store is, is really bringing enterprise data services to like EBS for, for AWS customers or to like, you know, is Azure premium disc for Azure users. And what do I mean by enterprise data services? It's, it's the, the, the way that large scale applications are managed, on-prem not just their performance and their avail availability considerations. How do I stage the, the development team, the sandbox team before they patch? You know, what's my cyber protection, not just data protection, how, how am I protected from a cyber hack? We bring all those capabilities to those storage platforms. And the, the best result is because of our data reduction technologies, which was critical in reducing the cost of flash 10 years ago, reduces the cost of the cloud by 50% or more and pays for the, for pays more than pays for our software of cloud block store to enable these enterprise data services, to give all these rapid capabilities like instant database, clones, instant, you know, recovery from cyber tech, things of that nature. >>Do customers. We heard today that cloud chaos are, are customers saying so, okay, you can run an Azure, you can run an AWS fine. Are customers saying, Hey, we want to connect those islands. Are you hearing that from customers or is it still sort of still too early? >>I think it's still too early. It doesn't mean we don't have customers who are very much in let's buy, let me buy some software that will monitor the price of my cloud. And I might move stuff around, but there's also a cost to moving, right? The, the egress charges can add up, particularly if you're at scale. So I don't know how much I seen. And even through the cloud days, how much I saw the, the notion of workloads moving, like kind of in the early days, like VMO, we thought there might be like a, is there gonna be a fall of the moon computing, you know, surge here, like, you know, have your workload run where power costs are lower. We didn't really see that coming to fruition. So I think there is a, is a desire for customers to have standardization because they gain the benefits of that from an operational perspective. Right. Whether they put that in motion to move workloads back and forth. I think >>So let's say, let's say to be determined, let let's say they let's say they don't move them because your point you knows too expensive, but, but, but, but you just, I think touched on it is they do want some kind of standard in terms of the workflow. Yep. You you're saying you're, you're starting to see demand >>Standard operating practices. Okay. >>Yeah. SOPs. And if they're, if they're big into pure, why wouldn't they want that? If assuming they have, you know, multiple clouds, which a lot of customers do. >>I, I, I I'll assure with you one thing that the going back to like basic primitives and I touched it touched on it a minute ago with data reduction. You have customers look at their, their storage bills in the cloud and say, we're gonna reduce that by half or more. You have a conversation >>Because they can bring your stack yeah. Into the cloud. And it's got more maturity than what you'd find from a cloud company, cloud >>Vendor. Yeah. Just data. Reduction's not part of block storage today in the cloud. So we've got an advantage there that we, we bring to bear. Yeah. >>So here we are at, at VMware Explorer, the first one of this name, and I love the theme, the center of the multi-cloud universe. Doesn't that sound like a Marvel movie. I feel like there should be superheroes walking around here. At some point >>We got Mr. Fantastic. Right here. We do >>Gone for, I dunno it >>Is. But a lot of, a lot of news this morning in the keynote, you were in the keynote, what are some of the things that you're hearing from VMware and what excites you about this continued evolution of the partnership with pure >>Yeah. Great point. So I, I think I touched on the, the two things that really caught my attention. Obviously, you know, we've got a lot of investment in V realize it was now kind of rebranded as ay, that, you know, I think we're really eager to see if we can help drive that consumption a bit higher, cuz we believe that plays into our favor as a vendor. We've we've we have over a hundred templates for the area platform right now to, you know, automation templates, whether it's, you know, levels set your platform, you know, automatically move workloads, deploy on demand. Like just so, so again, I think the focus there is very exciting for us, obviously when they've got a new release, like vSphere eight, that's gonna drive a lot of channel behaviors. So we've gotta get our, you know, we're a hundred percent channel company. And so we've gotta go get our channel ready because with about half of the updates of vSphere is, is hardware refresh. And so, you know, we've gotta be, be prepared for that. So, you know, some of the excitements about just being how to find more points in the market to do more business together. >>All right. Exciting cover the grounds. Right. I mean, so, okay. You guys announce earnings tomorrow, so we can't obviously quiet period, but of course you're not gonna divulge that anyway. So we'll be looking for that. What other catalysts are out there that we should be paying attention to? You know, we got, we got reinvent coming up in yep. In November, you guys are obviously gonna be there in, in a big way. Accelerate was back this year. How was accelerate >>Accelerate in was in Los Angeles this year? Mm. We had great weather. It was a phenomenal venue, great event, great partner event to kick it off. We happened to, to share the facility with the president and a bunch of international delegates. So that did make for a little bit of some logistic securities. >>It was like the summit of the Americas. I, I believe I'm recalling that correctly, but it was fantastic. Right. You, you get, you get to bring the customers out. You get to put a bunch of the engineers on display for the products that we're building. You know, one of the high, you know, two of the highlights there were, we, we announced our new flash blade S so, you know, higher, more performant, more scalable version of our, our scale and object and file platform with that. We also announced the, the next generation of our a I R I, which is our AI ready, AI ready infrastructure within video. So think of it like converged infrastructure for AI workloads. We're seeing tremendous growth in that unstructured space. And so, you know, we obviously pure was funded around block storage, a lot around virtual machines. The data growth is in unstructured, right? >>We're just seeing, we're seeing, you know, just tons of machine learning, you know, opportunities, a lot of opportunities, whether we're looking at health, life sciences, genome sequencing, medical imaging, we're seeing a lot of, of velocity in the federal space. You know, things, I can't talk about a lot of velocity in the automotive space. And so just, you know, from a completeness of platform, you know, flat flash blade is, is really addressing a need really kind of changing the market from NAS as like tier two storage or object is tier three to like both as a tier one performance candidate. And now you see applications that are supporting running on top of object, right? All your analytics platforms are on an object today, Absolut. So it's a, it's a whole new world. >>Awesome. And Pierce also what I see on the website, a tech Fest going on, you guys are gonna be in Seoul, Mexico city in Singapore in the next week alone. So customers get the chance to be able to in person talk with those execs once again. >>Yeah. We've been doing the accelerate tech tech fests, sorry about that around the globe. And if one of those align with your schedule, or you can free your schedule to join us, I would encourage you. The whole list of events dates are on pure storage.com. >>I'm looking at it right now. Vaon thank you so much for joining Dave and me. I got to sit between two dapper dudes, great conversation about what's going on at pure pure with VMware better together and the, and the CATA, the cat catalysis that's going on on both sides. I think that's an actual word I should. Now I have a degree biology for Vaughn Stewart and Dave Valante I'm Lisa Martin. You're watching the cube live from VMware Explorer, 22. We'll be right back with our next guest. So keep it here.
SUMMARY :
It's the cube live at VMware Explorer, 2022. I couldn't have missed this one because you know, the orange and the pure and VA right. It's great to have you back on the program, So this Fantastic. So talk to us, what's going on at pure. partners and prospects, you know, pure storage has just been on a So this is my premise here is you guys are actually becoming a cloud-like company This is very much that super cloud premise. it, you know, we used to see companies, they go, they'd come out of escape velocity, and then they'd they'd growth And by the way, I would be remiss if I didn't remind your audience that our And if you look in like our review of our products, flash rate is the leader in And some of the things that you're accelerating. And so it's it, it's not just a, a, a, you know, unilateral partnership. And now with the port works acquisition, it brings you closer to the whole DevOps scene. So very cloud-like only pay for what you use on-prem and turn availability, but we don't do it mono in a, you know, in a, in a homogeneous environment, You have a cus there, you got a database, you got a database. So port works was the enabler you mentioned maybe VMware should above. works acquisition, how has it changed the way that you guys think about storage and how flexibility for our subscriptions, you know, more from between on-prem and cloud, as I shared earlier, is, And so, you know, it's an ambitious goal, but we believe it's So, perspective, I'm talking to a lot of customers that are putting that requirement when they're doing RFPs and to is through a sustainability effort, whether it's in chip design, you know, storage technologies, I think Lisa, so you and I were at, was it, when did you announce a block You, you connecting your on-prem, you were, to share with you that I feel is right around the corner. for, for AWS customers or to like, you know, is Azure premium disc for Azure users. okay, you can run an Azure, you can run an AWS fine. of in the early days, like VMO, we thought there might be like a, is there gonna be a fall of the moon computing, you know, So let's say, let's say to be determined, let let's say they let's say they don't move them because your point you knows too expensive, Okay. you know, multiple clouds, which a lot of customers do. I, I, I I'll assure with you one thing that the going back to like basic primitives and I touched it touched And it's got more maturity than what you'd So we've got an advantage there So here we are at, at VMware Explorer, the first one of this name, and I love the theme, the center of the We do Is. But a lot of, a lot of news this morning in the keynote, you were in the keynote, So we've gotta get our, you know, we're a hundred percent channel company. In November, you guys are obviously gonna be there in, So that did make for a little bit of some logistic securities. You know, one of the high, you know, two of the highlights there were, we, we announced our new flash blade S so, And so just, you know, from a completeness of platform, So customers get the chance to be And if one of those align with your schedule, or you can free your schedule to join us, Vaon thank you so much for joining Dave and me.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Lisa Martin | PERSON | 0.99+ |
Dave Valante | PERSON | 0.99+ |
Dave Volante | PERSON | 0.99+ |
Tesla | ORGANIZATION | 0.99+ |
VMware | ORGANIZATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
apple | ORGANIZATION | 0.99+ |
Nvidia | ORGANIZATION | 0.99+ |
10th year | QUANTITY | 0.99+ |
San Francisco | LOCATION | 0.99+ |
2019 | DATE | 0.99+ |
Vaughn Stewart | PERSON | 0.99+ |
2 billion | QUANTITY | 0.99+ |
three years | QUANTITY | 0.99+ |
50% | QUANTITY | 0.99+ |
nine months | QUANTITY | 0.99+ |
November | DATE | 0.99+ |
Los Angeles | LOCATION | 0.99+ |
41% | QUANTITY | 0.99+ |
97% | QUANTITY | 0.99+ |
Lisa | PERSON | 0.99+ |
eight years | QUANTITY | 0.99+ |
Ragu | PERSON | 0.99+ |
tomorrow | DATE | 0.99+ |
first | QUANTITY | 0.99+ |
today | DATE | 0.99+ |
two | QUANTITY | 0.99+ |
this year | DATE | 0.99+ |
first product | QUANTITY | 0.99+ |
two things | QUANTITY | 0.99+ |
one example | QUANTITY | 0.99+ |
yesterday | DATE | 0.99+ |
66% | QUANTITY | 0.99+ |
both | QUANTITY | 0.99+ |
both sides | QUANTITY | 0.99+ |
last year | DATE | 0.99+ |
10 years ago | DATE | 0.99+ |
Singapore | LOCATION | 0.99+ |
two parts | QUANTITY | 0.99+ |
next week | DATE | 0.99+ |
four years | QUANTITY | 0.98+ |
EBS | ORGANIZATION | 0.97+ |
V Stewart | PERSON | 0.97+ |
Cassandra | PERSON | 0.97+ |
half | QUANTITY | 0.97+ |
vSphere eight | TITLE | 0.96+ |
vSphere | TITLE | 0.96+ |
Seoul, Mexico | LOCATION | 0.96+ |
Vaon | PERSON | 0.96+ |
OPEX | ORGANIZATION | 0.95+ |
up to 80% | QUANTITY | 0.95+ |
first time | QUANTITY | 0.95+ |
a minute ago | DATE | 0.95+ |
OnPrem | ORGANIZATION | 0.95+ |
one | QUANTITY | 0.95+ |
first one | QUANTITY | 0.95+ |
Azure | TITLE | 0.94+ |
85 | QUANTITY | 0.94+ |
OpenShift | TITLE | 0.93+ |
2022 | DATE | 0.93+ |
this morning | DATE | 0.92+ |
earlier this month | DATE | 0.92+ |
Eric Herzog, Infinidat | VeeamON 2022
(light music playing) >> Welcome back to VEEAMON 2022 in Las Vegas. We're at the Aria. This is theCUBE and we're covering two days of VEEAMON. We've done a number of VEEAMONs before, we did Miami, we did New Orleans, we did Chicago and we're, we're happy to be back live after two years of virtual VEEAMONs. I'm Dave Vellante. My co-host is David Nicholson. Eric Herzog is here. You think he's, Eric's been on theCUBE, I think more than any other guest, including Pat Gelsinger, who at one point was the number one guest. Eric Herzog, CMO of INFINIDAT great to see you again. >> Great, Dave, thank you. Love to be on theCUBE. And of course notice my Hawaiian shirt, except I now am supporting an INFINIDAT badge on it. (Dave laughs) Look at that. >> Is that part of the shirt or is that a clip-on? >> Ah, you know, one of those clip-ons but you know, it looks good. Looks good. >> Hey man, what are you doing at VEEAMON? I mean, you guys started this journey into data protection several years ago. I remember we were actually at one of their competitors' events when you first released it, but tell us what's going on with Veeam. >> So we do a ton of stuff with Veeam. We do custom integration. We got some integration on the snapshotting side, but we do everything and we have a purpose built backup appliance known as InfiniGuard. It works with Veeam. We also actually have some customers who use our regular primary storage device as a backup target. The InfiniGuard product will do the data reduction, the dedupe compression, et cetera. The standard product does not, it's just a standard high performance array. We will compress the data, but we have customers that do it either way. We have a couple customers that started with the InfiniBox and then transitioned to the InfiniGuard, realizing that why would you put it on regular storage? Why not go to something that's customized for it? So we do that. We do stuff in the field with them. We've been at all the VEEAMONs since the, since like, I think the second one was the first one we came to. We're doing the virtual one as well as the live one. So we've got a little booth inside, but we're also doing the virtual one today as well. So really strong work with Veeam, particularly at the field level with the sales guys and in the channel. >> So when INFINIDAT does something, you guys go hardcore, high end, fast recovery, you just, you know, reliable, that's kind of your brand. Do you see this movement into data protection as kind of an adjacency to your existing markets? Is it a land and expand strategy? Can you kind of explain the strategy there. >> Ah, so it's actually for us a little bit of a hybrid. So we have several accounts that started with InfiniBox and now have gone with the InfiniGuard. So they start with primary storage and go with secondary storage/modern data protection. But we also have, in fact, we just got a large PO from a Fortune 50, who was buying the InfiniGuard first and now is buying our InfiniBox. >> Both ways. Okay. >> All flash array. And, but they started with backup first and then moved to, so we've got them moving both directions. And of course, now that we have a full portfolio, our original product, the InfiniBox, which was a hybrid array, outperformed probably 80 to 85% of the all flash arrays, 'cause the way we use DRAM. And what's so known as our mural cash technology. So we could do very well, but there is about, you know, 15, 20% of the workloads we could not outperform the competition. So then we had an all flash array and purpose built backup. So we can do, you know, what I'll say is standard enterprise storage, high performance enterprise storage. And then of course, modern data protection with our partnerships such as what we do with Veeam and we've incorporated across the entire portfolio, intense cyber resilience technology. >> Why does the world, Eric, need another purpose built backup appliance? What do you guys bring that is filling a gap in the marketplace? >> Well, the first thing we brought was much higher performance. So when you look at the other purpose built backup appliances, it's been about our ability to have incredibly high performance. The second area has been CapEx and OpEx reduction. So for example, we have a cloud service provider who happens to be in South Africa. They had 14 purpose built backup appliances from someone else, seven in one data center and seven in another. Now they have two InfiniGuards, one in each data center handling all of their backup. You know, they're selling backup as a service. They happen to be using Veeam as well as one other backup company. So if you're the cloud provider from their perspective, they just dramatically reduce their CapEx and OpEx. And of course they've made it easier for them. So that's been a good story for us, that ability to consolidation, whether it be on primary storage or secondary storage. We have a very strong play with cloud providers, particularly those meeting them in small that have to compete with the hyperscalers right. They don't have the engineering of Amazon or Google, right? They can't compete with what the Azure guys have got, but because the way both the InfiniGuard and the InfiniBox work, they could dramatically consolidate workloads. We probably got 30 or 40 midsize and actually several members of the top 10 telcos use us. And when they do their clouds, both their internal cloud, but actually the clouds that are actually running the transmissions and the traffic, it actually runs on InfiniBox. One of them has close to 200 petabytes of InfiniBox and InfiniBox, all flash technology running one of the largest telcos on the planet in a cloud configuration. So all that's been very powerful for us in driving revenue. >> So phrases of the week have been air gap, logical air gap, immutable. Where does InfiniGuard fit into that universe? And what's the profile of the customer that's going to choose InfiniGuard as the target where they're immutable, Write Once Read Many, data is going to live. >> So we did, we announced our InfiniSafe technology first on the InfiniGuard, which actually earlier this year. So we have what I call the four legs of the stool of cyber resilience. One is immutable snapshots, but that's only part of it. Second is logical air gapping, and we can do both local and remote and we can provide and combine local with remote. So for example, what that air gap does is separate the management plane from the actual data plane. Okay. So in this case, the Veeam data backup sets. So the management cannot touch that immutable, can't change it, can't delete it. can't edit it. So management is separated once you start and say, I want to do an immutable snap of two petabytes of Veeam backup dataset. Then we just do that. And the air gap does it, but then you could take the local air gap because as you know, from inception to the end of an attack can be close to 300 days, which means there could be a fire. There could be a tornado, there could be a hurricane, there could be an earthquake. And in the primary data center, So you might as well have that air gap just as you would do- do a remote for disaster recovery and business continuity. Then we have the ability to create a fenced forensic environment to evaluate those backup data sets. And we can do that actually on the same device. That is the purpose built backup appliance. So when you look at the architectural, these are public from our competitors, including the guys that are in sort of Hopkinton/Austin, Texas. You can see that they show a minimum of two physical devices. And in many cases, a third, we can do that with one. So not only do we get the fence forensic environment, just like they do, but we do it with reduction, both CapEx and OpEx. Purpose built backup is very high performance. And then the last thing is our ability to recover. So some people talk about rapid recovery, I would say, they dunno what they're talking about. So when we launched the InfiniGuard with InfiniSafe, we did a live demo, 1.5 petabytes, a Veeam backup dataset. We recovered it in 12 minutes. So once you've identified and that's on the InfiniGuard. On the InfiniBox, once you've identified a good copy of data to do the recovery where you're free of malware ransomware, we can do the recovery in three to five seconds. >> Okay. >> So really, really quick. Actually want to double click on something because people talk about immutable copies, immutable snapshots in particular, what have the actual advances been? I mean, is this simply a setting that maybe we didn't set for retention at some time in the past, or if you had to engineer something net new into a system so to provide that logical air gap. >> So what's net new is the air gapping part. Immutable snapshots have been around, you know, before we were on screen, you talked about WORM, Write Once Read Many. Well, since I'm almost 70 years old, I actually know what that means. When you're 30 or 40 or 50, you probably don't even know what a WORM is. Okay. And the real use of immutable snapshots, it was to replace WORM which was an optical technology. And what was the primary usage? Regulatory and compliance, healthcare, finance and publicly traded companies that were worried about. The SEC or the EU or the Japanese finance ministry coming down on them because they're out of compliance and regulatory. That was the original use of immutable snap. Then people were, well, wait a second. Malware ransomware could attack me. And if I got something that's not changeable, that makes it tougher. So the real magic of immutability was now creating the air gap part. Immutability has been around, I'd say 25 years. I mean, WORMs sort of died back when I was at Mac store the first time. So that was 1990-ish is when WORMs sort of fell away. And there have been immutable snapshots from most of the major storage vendors, as well as a lot of the small vendors ever since they came out, it's kind of like a checkbox item because again, regulatory and compliance, you're going to sell to healthcare, finance, public trade. If you don't have the immutable snapshot, then they don't have their compliance and regulatory for SEC or tax purposes, right? With they ever end up in an audit, you got to produce data. And no one's using a WORM drive anymore to my knowledge. >> I remember the first storage conference I ever went to was in Monterey. It had me in the early 1980s, 84 maybe. And it was a optical disc drive conference. The Jim Porter of optical. >> Yep. (laughs) >> I forget what the guy's name was. And I remember somebody coming up to me, I think it was like Bob Payton rest his soul, super smart strategy guy said, this is never going to happen because of the cost and that's what it was. And now you've got that capability on flash, you know, hard disk, et cetera. >> Right. >> So the four pillars, immutability, the air gap, both local and remote, the fence forensics and the recovery speed. Right? >> Right. Pick up is one thing. Recovery is everything. Those are the four pillars, right? >> Those are the four things. >> And your contention is that those four things together differentiate you from the competition. You mentioned, you know, the big competition, but how unique is this in the marketplace, those capabilities and how difficult is it to replicate? >> So first of all, if someone really puts their engineering hat to it, it's not that hard to replicate. It takes a while. Particularly if you're doing an enterprise, for example, our solutions all have a hundred percent availability guarantee. That's hard to do. Most guys have seven nines. >> That's hard. >> We really will guarantee a hundred percent availability. We offer an SLA that's included when you buy. We don't charge extra for it. It's like if you want it, like you just get it. Second thing is really making sure on the recovery side is the hardest part, particularly on a purpose built backup appliance. So when you look at other people and you delve into their public material, press releases, white paper, support documentation. No one's talking about. Yeah, we can take a 1.5 petabyte Veeam backup data set and make it available in 12 minutes and 12 seconds, which was the exact time that we did on our live demo when we launched the product in February of 2022. No one's talking that. On primary storage, you're hearing some of the vendors such as my old employer that also who, also starts with an "I", talk about a recovery time of two to three hours once you have a known good copy. On primary storage, once we have a known good copy, we're talking three to five seconds for that copy to be available. So that's just sort of the power of the snapshot technology, how we manage our metadata and what we've done, which previous to cyber resiliency, we were known for our replication capability and our snapshot capability from an enterprise class data store. That's what people said. INFINIDAT really knows how to do the replication snapshot. I remember our founder was one of the technical founders of EMC for a product known as the Symmetric, which then became the DMAX, the VMAX and is now is the PowerMax. That was invented by the guy who founded INFINIDAT. So that team has the real chops at enterprise high-end storage to the global fortune 2000. And what are the key feature checkbox items they need that's in both the InfiniBox and also in the InfiniGuard. >> So the business case for cyber resiliency is changing. As Dave said, we've had a big dose last several months, you know, couple years actually, of the importance of cyber resiliency, given all the ransomware tax, et cetera. But it sounds like the business case is shifting really focused on avoiding that risk, avoiding that downtime time versus the cost. The cost is always important. I mean, you got a consolidation play here, right? >> Yeah, yeah. >> Dedupe, does dedupe come into play? >> So on the InfiniGuard we do both dedupe and compression. On the InfiniBox we only do compression. So we do have data reduction. It depends on which product you're using from a Veeam perspective. Most of that now is with the InfiniGuard. So you get the block level dedupe and you get compression. And if you can do both, depending on the data set, we do both. >> How does that affect recovery time? >> Yeah, good question. >> So it doesn't affect recovery times. >> Explain why. >> So first of all, when you're doing a backup data set, the final final recovery, you recovered the backup data set, whether it's Veeam or one of their competitors, you actually make it available to the backup administrator to do a full restore of a backup data set. Okay. So in that case, we get it ready and expose it to the Veeam admin or some other backup admin. And then they launch the Veeam software or the other software and do a restore. Okay. So it's really a two step process on the secondary storage model and actually three. First identifying a known good backup copy. Second then we recover, which is again 12, 13 minutes. And then the backup admin's got to do a, you know, a restore of the backup 'cause it's backup data set in the format of backup, which is different from every backup vendor. So we support that. We get it ready to go. And then whether it's a Veeam backup administrator and quite honestly, from our perspective, most of our customers in the global fortune 2000, 25% of the fortune 50 use INIFINIDAT products. 25% and we're a tiny company. So we must have some magic fairy dust that appeals to the biggest companies on the planet. But most of our customers in that area and actually say probably in the fortune 500 actually use two to three different backup packages. So we can support all those on a single InfiniGuard or multiples depending on how big their backup data sets. Our biggest InfiniGuard is 50 petabytes counting the data reduction technology. So we get that ready. On the InfiniBox, the recovery really is, you know, a couple of seconds and in that case, it's primary data in block format. So we just make that available. So on the InfiniBox, the recovery is once, well two. Identifying a known good copy, first step, then just doing recovery and it's available 'cause it's blocked data. >> And that recovery doesn't include movement of a whole bunch of data. It's essentially realignment of pointers to where the good data is. >> Right. >> Now in the InfiniBox as well as in InfiniGuard. >> No, it would be, So in the case of that, in the case of the InfiniGuard, it's a full recovery of a backup data set. >> Okay. >> So the backup software just launches and it sees, >> Okay. >> your backup one of Veeam and just starts doing a restore with the Veeam restoration technology. Okay? >> Okay. >> In the case of the block, as long as the physical InfiniBox, if that was the primary storage and then filter box is not damaged when you make it available, it's available right away to the apps. Now, if you had an issue with the app side or the physical server side, and now you're pointing new apps and you had to reload stuff on that side, you have to point it at that InfiniBox which has the data. And then you got to wait for the servers and the SAP or Oracle or Mongo, Cassandra to recognize, oh, this is my primary storage. So it depends on the physical configuration on the server side and the application perspective, how bad were the apps damaged? So let's take malware. Malware is even worse because you either destroying data or messing, playing with the app so that the app is now corrupted as well as the data is corrupted. So then it's going to take longer the block data's ready, the SAP workload. And if the SAP somehow was compromised, which is a malware thing, not a ransomware thing, they got to reload a good copy of SAP before it can see the data 'cause the malware attacked the application as well as the data. Ransomware doesn't do that. It just holds it for ransom and it encrypts. >> So this is exactly what we're talking about. When we talk about operational recovery and automation, Eric is addressing the reality that it doesn't just end at the line above some arbitrary storage box, you know, reaching up real recovery, reaches up into the application space and it's complicated. >> That's when you're actually recovered. >> Right. >> When the application- >> Well, think of it like a disaster. >> Okay. >> Yes, right. >> I'll knock on woods since I was born and still live in California. Dave too. Let's assume there's a massive earthquake in the bay area in LA. >> Let's not. >> Okay. Let's yes, but hypothetically and the data center's cat five. It doesn't matter what they're, they're all toast. Okay. Couple weeks later it's modern. You know, people figure out what to do and certain buildings don't fall down 'cause of the way earthquake standards are in California now. So there's data available. They move into temporary space. Okay. Data's sitting there in the Colorado data center and they could do a restore. Well, they can't do a restore. How many service did they need? Had they reloaded all of the application software to do a restoration. What happened to the people? If no one got injured, like in the 1989 earthquake in California, very few people got injured yet cost billions of dollars. But everyone was watching this San Francisco giants played in Oakland, >> I remember >> so no one was on the road. >> Al Michael's. >> Epic moment. >> Imagine it's in the middle of commute time in LA and San Francisco, hundreds of thousands of people. What if it's your data center team? Right? So there's a whole bunch around disaster recovery and business country that have nothing to do with the storage, the people, what your process. So I would argue that malware ransomware is a disaster and it's exactly the same thing. You know, you got the known good copy. You've got okay. You're sure that the SAP and Oracle, especially on the malware side, weren't compromised. On the ransomware side, you don't have to worry about that. And those things, you got to take a look at just as if it, I would argue malware and ransomware is a disaster and you need to have a process just like you would. If there was an earthquake, a fire or a flood in the data center, you need a similar process. That's slightly different, but the same thing, servers, people, software, the data itself. And when you have that all mapped out, that's how you do successful malware ransomeware recovery. It's a different type of disaster. >> It's absolutely a disaster. It comes down to business continuity and be able to transact business with as little disruption as possible. We heard today from the keynotes and then Jason Buffington came on about the preponderance of ransomware. Okay. We know that. But then the interesting stat was the percentage of customers that paid the ransom about a third weren't able to recover. And so 'cause you kind of had this feeling of all right, well, you know, see it on, you know, CNBC, should you pay the ransom or not? You know, pay the ransom. Okay. You'll get back. But no, it's not the case. You won't necessarily get back. So, you know, Veeam stated, Hey, our goal is to sort of eliminate that problem. Are you- You feel like you guys in a partnership can actually achieve that. >> Yes. >> So, and you have customers that have actually avoided, you know, been hit and were able to- >> We have people who won't publicly say they've been hit, but the way they talk about what they did, like in a meeting, they were hit and they were very thankful. >> (laughs) Yeah. >> And so that's been very good. I- >> So we got proof. >> Yes, we absolutely have proof. And quite honestly, with the recent legislation in the United States, malware and ransomware actually now is also regulatory and compliance. >> Yeah. >> Because the new law states mid-March that whether it's Herzog's bar and grill to bank of America or any large foreign company doing business in the US, you have to report to the United States federal government, any attack, same with the county school district with any local government, any agency, the federal government, as well as every company from the tiniest to the largest in the world that does, they're supposed to report it 'cause the government is trying to figure out how to fight it. Just the way if you don't report burglary, how they catch the burglars. >> Does your solution simplify testing in any way or reduce the risk of testing? >> Well, because the recovery is so rapid, we recommend that people do this on a regular basis. So for example, because the recovery is so quick, you can recover in 12 minutes while we do not practice, let's say once a month or once every couple weeks. And guess what? It also allows you to build a repository of known good copies. Remember when you get ransomeware, no one's going to come say, Hey, I'm Mr. Rans. I'm going to steal your stuff. It's all done surreptitiously. They're all James Bond on the sly who doesn't say "By the way, I'm James Bond". They are truly underneath the radar. And they're very slowly encrypting that data set. So guess what? Your primary data and your backup data that you don't want to be attacked can be attacked. So it's really about finding a known good copy. So if you're doing this on a regular basis, you can get an index of known good copies. >> Right. >> And then, you know, oh, I can go back to last Tuesday and you know that that's good. Otherwise you're literally testing Wednesday, Thursday, Friday, Saturday to try to find a known good copy, which delays the recovery process 'cause you really do have to test. They make sure it's good. >> If you increase that frequency, You're going to protect yourself. That's why I got to go. Thanks so much for coming on theCUBEs. Great to see you. >> Great. Thank you very much. I'll be wearing a different Hawaiian shirt next to. >> All right. That sounds good. >> All right, Eric Herzog, Eric Herzog on theCUBE, Dave Vallante for David Nicholson. We'll be right back at VEEAMON 2022. Right after this short break. (light music playing)
SUMMARY :
We're at the Aria. And of course notice my Hawaiian shirt, those clip-ons but you know, I mean, you guys started this journey the first one we came to. the strategy there. So we have several accounts Okay. So we can do, you know, the first thing we brought So phrases of the So the management cannot or if you had to engineer So the real magic of immutability was now I remember the first storage conference happen because of the cost So the four pillars, Those are the four pillars, right? the big competition, it's not that hard to So that team has the real So the business case for So on the InfiniGuard we do So on the InfiniBox, the And that recovery Now in the InfiniBox So in the case of that, in and just starts doing a restore So it depends on the Eric is addressing the reality in the bay area in LA. 'cause of the way earthquake standards are On the ransomware side, you of customers that paid the ransom but the way they talk about what they did, And so that's been very good. in the United States, Just the way if you don't report burglary, They're all James Bond on the sly And then, you know, oh, If you increase that frequency, Thank you very much. That sounds good. Eric Herzog on theCUBE,
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave | PERSON | 0.99+ |
David Nicholson | PERSON | 0.99+ |
Eric Herzog | PERSON | 0.99+ |
Pat Gelsinger | PERSON | 0.99+ |
Jason Buffington | PERSON | 0.99+ |
Dave Vallante | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
California | LOCATION | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
US | LOCATION | 0.99+ |
Eric | PERSON | 0.99+ |
ORGANIZATION | 0.99+ | |
Veeam | PERSON | 0.99+ |
SEC | ORGANIZATION | 0.99+ |
12 | QUANTITY | 0.99+ |
February of 2022 | DATE | 0.99+ |
CNBC | ORGANIZATION | 0.99+ |
LA | LOCATION | 0.99+ |
two | QUANTITY | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
Bob Payton | PERSON | 0.99+ |
Colorado | LOCATION | 0.99+ |
South Africa | LOCATION | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
EMC | ORGANIZATION | 0.99+ |
EU | ORGANIZATION | 0.99+ |
25 years | QUANTITY | 0.99+ |
40 | QUANTITY | 0.99+ |
15 | QUANTITY | 0.99+ |
Monterey | LOCATION | 0.99+ |
30 | QUANTITY | 0.99+ |
12 minutes | QUANTITY | 0.99+ |
Jim Porter | PERSON | 0.99+ |
80 | QUANTITY | 0.99+ |
seven | QUANTITY | 0.99+ |
five seconds | QUANTITY | 0.99+ |
Oakland | LOCATION | 0.99+ |
today | DATE | 0.99+ |
25% | QUANTITY | 0.99+ |
Second | QUANTITY | 0.99+ |
Veeam | ORGANIZATION | 0.99+ |
San Francisco | LOCATION | 0.99+ |
hundred percent | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
Mongo | ORGANIZATION | 0.99+ |
billions of dollars | QUANTITY | 0.99+ |
three | QUANTITY | 0.99+ |
three hours | QUANTITY | 0.99+ |
New Orleans | LOCATION | 0.99+ |
SAP | ORGANIZATION | 0.99+ |
both | QUANTITY | 0.99+ |
VEEAMON | ORGANIZATION | 0.99+ |
two step | QUANTITY | 0.99+ |
James Bond | PERSON | 0.99+ |
two petabytes | QUANTITY | 0.99+ |
1.5 petabytes | QUANTITY | 0.99+ |
50 petabytes | QUANTITY | 0.99+ |
One | QUANTITY | 0.99+ |
1990 | DATE | 0.99+ |
second area | QUANTITY | 0.99+ |
Both ways | QUANTITY | 0.99+ |
United States | LOCATION | 0.99+ |
Japanese finance ministry | ORGANIZATION | 0.99+ |
12 seconds | QUANTITY | 0.99+ |
First | QUANTITY | 0.99+ |
mid-March | DATE | 0.98+ |
85% | QUANTITY | 0.98+ |
JJ Davis, Dell Technologies | Dell Technologies World 2022
>> The Cube presents Dell Technologies World brought to you by Dell. (crowd murmuring) >> Welcome back to Las Vegas. It's The Cube live at Dell Technologies World 2022. This is day two of our coverage Lisa Martin, with Dave Vellante. We've had a lot of great conversations all day today half a day yesterday. We've got another great conversation coming up about ESG environmental, social and governance. Please welcome JJ Davis, the Chief Corporate Affairs Officer at Dell Technologies. Welcome to the program. >> Hi, thanks for having me. >> Hey, hey. >> It's great to be here. >> ESG is a very popular topic. >> Yes. >> It's one thing to talk about another thing to actually have a plan, have a strategy, have those 20, 30 moonshot goals and implement. Talk to us about what ESG means for Dell Technologies and some of these great things, that you have going on. >> Absolutely. So you said it, I mean it can be acronym soup. When you think about, is it social impact? Is it corporate social responsibility? Is it ESG and the beauty of having an environmental social governance strategy is we now are bringing ESG much closer to the corporate strategy and how we meet the needs of all of our stakeholders. So I'd love to just back it up for a minute and think about the purpose of Dell Technologies is to create technologies that advance human potential. Our vision is to be the most essential technology company for the data era. The way we do that is we're growing and modernizing our core businesses like PC servers and storage while we're building the technology ecosystem of the future. Well guess what? ESG is embedded in all of that because the future is more sustainable, built by people that represent our customer base with a workforce that is more diverse and a workplace that is more inclusive. We put human rights and the needs of people at the center of what we do as well as the needs of the planet. And when I get to put together purpose planet and profit and bring that strategy together in partnership with so many leaders of across the company and meeting the demands of our customers. ESG is just a part of the way we do business now >> It's part of the DNA. >> Yeah. >> Talk to us about some of the key priorities from a climate perspective, for example. >> Sure. >> What are some of Dell's key focus areas where that's concerned? >> So when we think about our ESG priorities as a whole there are four climate, circular, economy, diverse workplace and digital inclusion. And so within our sustainability pillar of our strategy or the E, we are committed to being net zero across scopes 1, 2 and 3 emissions by 2050. We are revamping our product energy goal right now to relaunch that. When we think about our customers 95% of our big customer RFPs ask about sustainability and our commitment and what we'll be doing to help them because they're going to be reliant on technology to meet their own sustainability and climate goals, whether it's green IT or IT for green and they're going to really be looking to us to help them. >> You know, I love this purpose planet profit. >> Yeah. >> You and I have talked about this a little bit. It's actually good business. Explain why ESG is good business? >> Well, I mean, used to social impact kind of sat off to the side. We might have been called do gooders or people that are passionate about things that maybe don't align to the corporate strategy. And now when you think about business round table and Michael Dell as a member and they came out with their purpose of a company statement it'll be three years in August to really redefine the purpose of a company to meet the needs of all stakeholders from employees, to customers, to shareholders as well. And so we know that new hires and new buyers demand more of their employer and of the companies they buy from. They want their own personal values to align with that of the company they work for or buy from. And so now we need to the needs of our business commitments, but also if companies don't take a leadership role, we're screwed, we're not going to be able to reverse the negative impacts. So climate change and technology plays a big role. >> Yeah. "The earth gets the last at bat," as they say. >> Yeah. >> From an accountability perspective that you mentioned 95% of RFPs are coming in and customers are looking for- >> Yes. >> Dell Technologies's commitment to ESG. Talk about the accountability to your customers to all customers where ESG is concerned and how is it measured? >> Sure. So we've been spending a lot of time over the last year, year and a half on the G of ESG the governance. And so we have been doing this for a couple decades really moving the needle on social impact. Michael talked about it in his key note, that this is in our DNA like you said. But now we have to be able to really measure. You can't manage what you can't measure. We have put a lot of governance around, what do we disclose and why Michael Dell is an active participant in the world economic forum, common metrics project because, you know, there's too many metrics and frameworks to know what companies need to be measuring and how we hold ourselves accountable and what we ultimately report to our shareholders. And so there's a lot of work to get more clarity there. You're seeing the SEC put out new rules around climate and human rights. And so when you start to get regulated that changes the game in terms of how transparent you need to be. And then what are the third party assurances that you need to have to validate the data that you're reporting on? We do have an annual ESG report that comes out every June where we report across several moonshot goals across sustainability, inclusive culture, transforming lives and ethics and privacy. Then we have sub goals. There's probably about 25 in total. And we're going to tell you our stakeholders every year how we're doing against our 20, 30 commitment. And I think it's that level of transparency and measurement that we have to hold ourselves accountable to and our customers do as well. >> Can you share a little bit about where you are on the 2030 moonshot that was announced about a couple years ago at the beginning of 20, yeah, towards the beginning of 2020. Where is Dell on the that, what's your moonscape look like? >> Yeah, sure. So we are announcing our update from calendar year 21 in June. So I'm not going to get the numbers exactly right. But if you take sustainability so one of our moonshot goals is around 100% of our packaging by 2030 will be made of recycled or renewable content. We're over 90% now. So we're going to probably restate that goal and evolve it or meet it early and set a new one. In terms of product contents. We have a goal that is 50% of our product contents will be from recycled over renewable materials. That's a little harder, plastic is easy, steel is hard. And so we're still working through how across the main components that go into our machines. How does that become more renewed and sustainable? If you think about 50% women in our workforce 25% African American or Hispanic in our US workforce we're making really good progress. And we have scaled programs that are helping us deliver on those commitments. >> Yeah. I think I'm quoting JJ Davis, correct me if I'm wrong but, "ESG marries who we are with what we do." What do you mean by that? >> So when you think about what we do, we build technology that delivers or advances human progress. We help our customers solve their biggest problems but really who we are. We are a founder-led company and Michael Dell was a purpose led driven CEO before that was even a term. And so he always wanted to have an ethical company that just did business above and beyond what the law required. And we'd been recycling PC for more than 20 years. And so we are an inclusive culture where we can bring our full selves to work and we are entrepreneurial. And, you know, if we have an idea and you raise that idea or a problem, you see then oftentimes the management will say, "Okay you go fix that." And so I think just what we do, we build technology. Who we are, is we're problem solvers for our customers. And that is good for business and good for the environment and what it is society really expects of us. And we're empowered to make a difference. Feels good. >> One of, I'm curious to get your perspective on , you know, the events of the last two years. One of the things that's happened is the great resignation. I think we all all know multiple people who have decided they're moving forward, lots of opportunity but where is Dell's ESG strategy as a differentiator for people going, I get it, I support that, that's the kind of company I want to work for? >> Our Chief Human Resources Officer Jen Saavedra calls it, "The great reshuffle." I think that's maybe a more positive way to look at it. And, you know, I've had people actually join my team because they are really positive on our mission and not just our proactive strategy around ESG but how we have handled our response to social issues. >> Yeah. >> I mean, who knew that company CEOs would be expected to speak out on voter access or LGBTQ rights and, you know. So a lot of people are coming to work for us because we are very measured in where we weigh in and what we stand for, how we speak out. But they're also really buying into our ESG strategy. I would also say our flexible work commitment. It's a big part of our DNI strategy as well and helps us attract and retain diverse talent. You can live and work wherever you want to proximity the headquarters is no longer criteria for advancement. And that's going to be a really big differentiator companies that get this right will win the talent war. And that means they'll better serve their customers. >> When you took over this role, I'm guessing you kind of did a scan to see who else was out there, what others were doing, not just in Tech. >> Sure. >> Not just in North America, but globally. What did you find? Where do you get your inspiration? Are there any organizations out there that are really models that you get inspiration from? Or is it so new? You are the model. Can you just talk about that? >> Well I mean, I think we're doing a really good job and we're pretty advanced, but nobody has this figured out and frankly, we need to do it together. This is a space where you don't actually want to compete. >> Right. >> You want to partner. And so we have our own sustainability advisory aboard and companies like Boeing or on that. I serve on a sustain the advisory board from McLaren and Unilever's chief sustainability officers there. That is a company that is really inspirational to us. And so partners like Intel, they're very involved in 50. So the next 50% that needs to get connected to the internet and participate in the digital economy. We're big partner, as you know we're their largest customer. And so there's a lot going on across our competition our customers and our partners. And we're all inspiring each other and figuring it out together. Cause it's evolving so fast. Nobody has all the answers. >> But that's a great point. The evolution is happening so quickly and every day you turn on the news and there's something else that needs to be responded to. >> Yeah. >> I mean, think that from a strategic perspective from that overall vision perspective, it sounds like what and there's been some announcements this week. >> Yeah. >> That respect to issue. What's been some of the feedback from the part of ecosystem, from customers, from investors on this laser focused vision that Dell has with respect to sustainability and ESG? >> So Cassandra Garber, our head of ESG just finished out of cycle road show with investors and had really good conversations. They're asking a lot of questions about our strategy. They're asking questions about executive compensation tied to ESG as an example. Our customers are very positive and responding. They're looking for technology solutions. As I mentioned to meet their own climate commitments. And from our channel partners they really want to partner on our initiatives and really go do good and make an impact together. And we're getting really good feedback. >> So carrot or stick, it's probably not 100% that the channel partners or even suppliers, you know, some just don't have the resource possibly or maybe they don't share your values. >> Right. >> So how do you approach that? Is it through inspiration? Is it through a little tap in the head or a little headlock? How do you deal with that? >> It's both. I mean, our suppliers have to adhere to the contract and the RSA code of conduct that they have to sign on to uphold. And so we very much hold them accountable just like we do our ourselves. And so that is more compliance driven but we do have partners like Western's Green in our supply chain who we're really involved with us in some early work around recycled gold and partners that are involved with us in setting up the ocean plastic supply chain. And so we have great partnership but there are things they have to do from a human rights perspective or commitment to the environment that are required. From a channel partner perspective, you know, we want to incent them. We want to make money together. We are for profit businesses after all. And ESG can be a part of that. And if you don't have the resources to drive your own take back initiative, then we can do that in partnership through our asset recovery services which partners can sell and then use our infrastructure to take back and recycle old equipment. >> I mean, I feel like a lot of my questions are two-way but you feel as though you're in influencing public policy or a public policy is influencing you? >> Both. I mean, early on when the SEC was looking at the climate rules that they just put out, there was, I think we submitted a six page response to their, you know, ask for inquiry and response. And so that's good. We're able to talk to each other and have conversations and shape things, but ultimately we'll be regulated in these areas and that's fine. We just got to make sure that we're ready. >> Great. >> It's always good to have that push and pull it's like with the pandemic all the silver linings that have come out of the acceleration, we talk about that all the time on this show. The acceleration of digital transformation, we were talking about the acceleration of retail in the intelligence store. >> Right. >> And as consumers, we expect that, but that push and pull sometimes those forcing functions are necessary to be able to drive forward. >> For sure. >> Yeah. >> Yeah. >> My last question for you is Dell just came off it's most successful year. >> Yes. >> First time hitting north of 100 billion. >> Yes. >> In the company's history. What are some of the things that we think is the moonshot goals, we're only in 2020. >> I know. >> But as time is going by so quickly, what are some of the things that you are personally looking forward to from a corporate affairs ESG perspective say the next like three to five years? >> Well, I'm really excited about some of the groundwork we've laid in digital inclusion. We just made some new hires there. We're connecting the dots, you know, and we have a lot of initiatives that can really if we can scale them, make a big impact. So we have student tech crew, it's where high school students serve as the technical support in their local high school and get certified. So they are job ready the minute they graduate. If they don't want to go to community college or university they can go right into the workforce. How do we marry that up with other skill building initiatives that we have? And if you add 1 plus 1 it equals 3. And I think this year will be a really big accelerator for us in the area of digital inclusion and how we bring connectivity, community services and support and digital skills together. Because that's what, you know, those that aren't participating in the digital economy we need to partner and really deliver on the promise of what it means to be in technology and at least have the skills to compete >> Right. Start eliminating that digital divide. JJ, thank you for joining David and me today talking about ESG- >> Thank you. >> corporate affairs, such an interesting focused efforts that Dell is really wrapped around. And it sounds like there's that push pull from the customers, from policy, but ultimately going in a great direction that can be measured. Thank you for your insights and your time. >> Thank you. >> For JJ and Dave Vellante I'm Lisa Martin. You've been watching The Cube live from Las Vegas. This is the end of day 2 of our coverage of Dell Technologies World. We thank you for watching. You can find all of our content on replay on theCUBE.net. And of course, we will be here tomorrow with John Farrier and Dave Nicholson as well. Have a great night. We'll see you tomorrow. (upbeat music)
SUMMARY :
brought to you by Dell. Welcome to the program. Talk to us about what ESG and the needs of people of the key priorities or the E, we are committed You know, I love this You and I have talked And so we know that new last at bat," as they say. and how is it measured? and measurement that we Where is Dell on the that, And we have scaled programs What do you mean by that? and good for the environment One of the things that's happened and not just our proactive And that's going to be a to see who else was out there, You are the model. and frankly, we need to do it together. So the next 50% that needs to that needs to be responded to. from that overall vision What's been some of the feedback As I mentioned to meet their that the channel partners that they have to sign on to uphold. to their, you know, ask of the acceleration, we talk about that And as consumers, we expect My last question for you is Dell north of 100 billion. that we think is the moonshot and at least have the skills to compete JJ, thank you for joining from the customers, from policy, And of course, we will be here tomorrow
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave | PERSON | 0.99+ |
David | PERSON | 0.99+ |
Michael | PERSON | 0.99+ |
Paul | PERSON | 0.99+ |
David Brown | PERSON | 0.99+ |
Marc Lemire | PERSON | 0.99+ |
Chris O'Brien | PERSON | 0.99+ |
Verizon | ORGANIZATION | 0.99+ |
Chris | PERSON | 0.99+ |
Dennis Donohue | PERSON | 0.99+ |
Hilary | PERSON | 0.99+ |
Mark | PERSON | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
Michelle Lin | PERSON | 0.99+ |
Ildiko Vancsa | PERSON | 0.99+ |
Rebecca Knight | PERSON | 0.99+ |
John | PERSON | 0.99+ |
Jeff Frick | PERSON | 0.99+ |
Alan Cohen | PERSON | 0.99+ |
Lisa Martin | PERSON | 0.99+ |
John Troyer | PERSON | 0.99+ |
Rajiv | PERSON | 0.99+ |
Indianapolis | LOCATION | 0.99+ |
Europe | LOCATION | 0.99+ |
Stefan Renner | PERSON | 0.99+ |
Herain Oberoi | PERSON | 0.99+ |
Chris Wright | PERSON | 0.99+ |
Ildiko | PERSON | 0.99+ |
Jeff | PERSON | 0.99+ |
Rebecca | PERSON | 0.99+ |
Mark Lohmeyer | PERSON | 0.99+ |
JJ Davis | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Paul Noglows | PERSON | 0.99+ |
John Fourier | PERSON | 0.99+ |
Beth | PERSON | 0.99+ |
Jon Bakke | PERSON | 0.99+ |
Bruce | PERSON | 0.99+ |
John Farrier | PERSON | 0.99+ |
Boeing | ORGANIZATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Manoj Agarwal | PERSON | 0.99+ |
Dave Nicholson | PERSON | 0.99+ |
Cassandra Garber | PERSON | 0.99+ |
Peter McKay | PERSON | 0.99+ |
ORGANIZATION | 0.99+ | |
Cisco | ORGANIZATION | 0.99+ |
Dave Brown | PERSON | 0.99+ |
Andy | PERSON | 0.99+ |
2013 | DATE | 0.99+ |
Beth Cohen | PERSON | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
Eric Herzog, Infinidat | CUBE Conversation April 2022
(upbeat music) >> Lately Infinidat has been on a bit of a Super cycle of product announcements. Adding features, capabilities, and innovations to its core platform that are applied across its growing install base. CEO, Phil Bollinger has brought in new management and really emphasized a strong and consistent cadence of product releases, a hallmark of successful storage companies. And one of those new executives is a CMO with a proven product chops, who seems to bring an energy and an acceleration of product output, wherever he lands. Eric Herzog joins us on "theCUBE". Hey, man. Great to see you. Awesome to have you again. >> Dave. Thank you. And of course, for "theCUBE", of course, I had to put on a Hawaiian shirt as always. >> They're back. All right, I love it.(laughs) Watch out for those Hawaiian shirt police, Eric. (both laughing) All right. I want to have you start by. Maybe you can make some comments on the portfolio over the past year. You heard my intro, InfiniBox is the core, the InfiniBox SSA, which announced last year. InfiniGuard you made some substantial updates in February of this year. Real focus on cyber resilience, which we're going to talk about with Infinidat. Give us the overview. >> Sure. Well, what we've got is it started really 11 years ago with the InfiniBox. High end enterprise solution, hybrid oriented really incredible magic fairy dust around the software and all the software technology. So for example, the Neural Cache technology, which has multiple patents on it, allowed the original InfiniBox to outperform probably 85% of the All-Flash Arrays in the industry. And it still does that today. We also of course, had our real, incredible ease-of-use the whole point of the way it was configured and set up from the beginning, which we continued to make sure we do is if you will a set it and forget it model. For example, When you install, you don't create lungs and raid groups and volumes it automatically and autonomously configures. And when you add new solutions, AKA additional applications or additional servers and point it at the InfiniBox. It automatically, again in autonomously, adjust to those new applications learning what it needs to configure everything. So you're not setting cash size and Q depth, or Stripes size, anything you would performance to you don't have to do any of that. So that entire set of software is on the InfiniBox. The InfiniBox SSA II, which we're of course launching today and then inside of the InfiniGuard platform, there's a actually an InfiniBox. So the commonality of snapshots replication, ease of use. All of that is identical across the platform of all-flash array, hybrid array and purpose-built backup secondary storage and no other vendor has that breadth of product that has the same exact software. Some make a similar GUI, but we're talking literally the same exact software. So once you learn it, all three platforms, even if you don't have them, you could easily buy one of the other platforms that you don't have yet. And once you've got it, you already know how to use it. 'Cause you've had one platform to start as an example. So really easy to use from a customer perspective. >> So ever since I've been following the storage business, which has been a long time now, three things that customers want. They want something that is rock solid, dirt cheap and super fast. So performance is something that you guys have always emphasized. I've had some really interesting discussions over the years with Infinidat folks. How do you get performance? If you're using this kind of architecture, it's been quite amazing. But how does this launch extend or affect performance? Why the focus on performance from your standpoint? >> Well, we've done a number of different things to bolster the performance. We've already been industry-leading performance again. The regular InfiniBox outperforms 80, 85% of the All-Flash Arrays. Then, when the announcement of the InfiniBox SSA our first all-flash a year ago, we took that now to the highest demanding workloads and applications in the industry. So what did it add to the super high end Oracle app or SAP or some custom app that someone's created with Mongo or Cassandra. We can absolutely meet the performance between either the InfiniBox or the InfiniBox all-flash with the InfiniBox SSA. However, we've decided to extend the performance even farther. So we added a whole bunch of new CPU cores into our tri part configuration. So we don't have two array controllers like many companies do. We actually have three everything's in threes, which gives us the capability of having our 100% availability guarantee. So we've extended that now we've optimized. We put a additional InfiniBand interconnects between the controllers, we've added the CPU core, we've taken if you will the InfiniBox operating system, Neural Cache and everything else we've had. And what we have done is we have optimized that to take advantage of all those additional cores. This has led us to increase performance in all aspects, IOPS bandwidth and in fact in latency. In latency we now are at 35 mikes of latency. Real world, not a hero number, but real-world on an array. And when you look end to end, if I Mr. Oracle, or SAP sitting in the server and I'll look across that bridge, of course the sand and over to the other building the storage building that entire traversing can be as fast as a 100 microseconds of latency across the entire configuration, not just the storage. >> Yeah. I think that's best in class for an external array. Well, so what's the spectrum you can now hit with the performance ranges. Can you hit all the aspects of the market with the two InfiniBoxes, your original, and then the SSA? >> Yes, even with the original SSA. In fact, we've had one of our end users, who's been first InfiniBox customer, then InfiniBox SSA actually has been running for the last two months. A better version of the SSA II. So they've had a better version and this customer's running high end Oracle rack configurations. So they decided, you know what? We're not going to run storage benchmarks. We're going to run only Oracle benchmarks. And in every benchmark IOPS, latency and bandwidth oriented, we outperformed the next nearest competition. So for example, 57% faster in IOPS, 58% faster in bandwidth and on the latency side using real-world Oracle apps, we were three times better performance on the latency aspect, which of course for a high end high performance workload, that's heavily transactional. Latency is the most important, but when you look across all three of those aspects dramatically outperform. And by the way, that was a beta unit that didn't of course have final code on it yet. So incredible performance angle with the InfiniBox SSA II. >> So I mean you earlier, you were talking about the ease of use. You don't have to provision lungs and all that sort of nonsense, and you've always emphasized ease-of-use. Can you double click on that a little bit? How do you think about that capability? And I'm really interested in why you think it's different from other vendors? >> Well, we make sure that, for example, when you install you don't have to do anything, you have to rack and stack, yes and cable. And of course, point the servers at the storage, but the storage just basically comes up. In fact, we have a customer and it's a public reference that bought a couple units many years ago and they said they were up and going in about two hours. So how many high-end enterprise storage array can be up and going in two hours? Almost I mean, basically nobody about us. So we wanted to make sure that we maintain that when we have customers, one of our big plays, particularly helping with CapEx and OpEx is because we are so performant. We can consolidate, we have a large customer in Europe that took 57 arrays from one of our competitors and consolidate it to five of the original InfiniBox. 57 to 5. They saved about $25 million in capital expense and they're saving about a million and a half a year in operational expense. But the whole point was as they kept adding more and more servers that were connected to those competitive arrays and pointing them at the InfiniBox, there's no performance tuning. Again, that's all ease-of-use, not only saving on operational expense, but obviously as we know, the headcount for storage admins is way down from its peak, which was probably in 2007. Yet every admin is managing what 25 to 50 times the amount of storage between 2007 and 2022. So the reality is the easier it is to use. Not only does of course the CIO love it because both the two of us together probably been storage, doing storage now for close to 80 years would be my guess I've been doing it for 40. You're a little younger. So maybe we're at 75 to 78. Have you ever met a CIO used to be a storage admin ever? >> No. >> And I can't think of one either so guess what? The easier it is to use the CIOs know that they need storage. They don't like it. They're all these days are all software guys. There used to be some mainframe guys in the old days, but they're long gone too. It's all about software. So when you say, not only can we help reduce your CapEx at OpEx, but the operational manpower to run the storage, we can dramatically reduce that because of our ease-of-use that they get and ease-of-use has been a theme on the software side ever since the Mac came out. I mean, Windows used to be a dog. Now it's easy to use and you know, every time the Linux distribution come out, someone's got something that's easier and easier to use. So, the fact that the storage is easy to use, you can turn that directly into, we can help you save on operational manpower and OPEX and CIOs. Again, none of which ever met are storage guys. They love that message. Of course the admins do too 'cause they're managing 25 to 50 times more storage than they had to manage back in 2007. So the easier it is for them at the tactical level, the storage admin, the storage manager, it's a huge deal. And we've made sure we've maintained that as you've added the SSA, as we brought up the InfiniGuard, as we've continue to push new feature function. We always make it easy to use. >> Yeah. Kind of a follow up on that. Just focus on software. I mean, I would think every storage company today, every modern storage company is going to have more software engineers than hardware engineers. And I think Infinidat obviously is no different. You got a strong set of software, it's across the portfolio. It's all included kind of thing. I wonder if you could talk about your software approach and how that is different from your competitors? >> Sure, so we started out 11 years ago when in Infinidat first got started. That was all about commodity hardware. So while some people will use custom this and custom that, yeah and I having worked at two of the biggest storage companies in the world before I came here. Yes, I know it's heavily software, but our percentage of hardware engines, softwares is even less hardware engineering than our competitors have. So we've had that model, which is why this whole what we call the set it and forget it mantra of ease-of-use is critical. We make sure that we've expanded that. For example, we're announcing today, our InfiniOps focus and Infini Ops all software allows us to do AIOps both inside of our storage system with our InfiniVerse and InfiniMetrics packages. They're easy to use. They come pre-installed and they manage capacity performance. We also now have heavy integration with AI, what I'll call data center, AIOps vendors, Vetana ServiceNow, VMware and others. And in that case, we make sure that we expose all of our information out to those AIOps data center apps so that they can report on the storage level. So we've made sure we do that. We have incredible support for the Ansible framework again, which is not only a software statement, but an ease-of-use statement as well. So for the Ansible framework, which is trying to allow an even simpler methodology for infrastructure deployment in companies. We support that extensively and we added some new features. Some more, if you will, what I'll say are more scripts, but they're not really scripts that Ansible hides all that. And we added more of that, whether that be configuration installations, that a DevOps guy, which of course just had all the storage guys listening to this video, have a heart attack, but the DevOps guy could actually configure storage. And I guess for my storage buddies, they can do it without messing up your storage. And that's what Ansible delivers. So between our AIOps focus and what we're doing with InfiniOps, that extends of course this ease-of-use model that we've had and includes that. And all this again, including we already talked about a little bit cyber resilience Dave, within InfiniSafe. All this is included when you buy it. So we don't piecemeal, which is you get this and then we try to upcharge you for that. We have the incredible pricing that delivers this CapEx and an OpEx. Not just for the array, but for the associated software that goes with it, whether that be Neural Cache, the ease-of-use, the InfiniOps, InfiniSafes. You get all of that package together in the way we deploy from a business now perspective, ease of doing business. You don't cut POS for all kinds of pieces. You cut APO and you just get all the pieces on the one PO when we deliver it. >> I was talking yesterday to a VC and we were chatting about AI And of course, everybody's chasing AI. It's a lot of investments go in there, but the reality is, AI is like containers. It's just getting absorbed into virtually every thing. And of course, last year you guys made a pretty robust splash into AIOps. And then with this launch, you're extending that pretty substantially. Tell us a little bit more about the InfiniOps announcement news. >> So the InfiniOps includes our existing in the box framework InfiniVerse and what we do there, by the way, InfiniVerse has the capability with the telemetry feed. That's how we could able to demo at our demo today and also at our demo for our channel partner pre-briefing. Again a hundred mics of latency across the entire configuration, not just to a hundred mics of latency on storage, which by the way, several of our competitors talk about a hundred mics of latency as their quote hero number. We're talking about a hundred mics of latency from the application through the server, through the SAN and out to the storage. Now that is incredible. But the monitoring for that is part of the InfiniOps packaging, okay. We support again with DevOps with all the integration that we do, make it easy for the DevOps team, such as with Ansible. Making sure for the data center people with our integration, with things like VMware and ServiceNow. The data center people who are obviously often not the storage centric person can also be managing the entire data center. And whether that is conversing with the storage admin on, we need this or that, or whether they're doing it themselves again, all that is part of our InfiniOps framework and we include things like the Ansible support as part of that. So InfiniOps is sort of an overarching theme and then overarching thing extends to AIops inside of the storage system. AIops across the data center and even integration with I'll say something that's not even considered an infrastructure play, but something like Ansible, which is clearly a red hat, software oriented framework that incorporates storage systems and servers or networks in the capability of having DevOps people manage them. And quite honestly have the DevOps people manage them without screwing them up or losing data or losing configuration, which of course the server guys, the network guys and the storage guys hate when the DevOps guys play with it. But that integration with Ansible is part of our InfiniOps strategy. >> Now our shift gears a little bit talk about cyber crime and I mean, it's a topic that we've been on for a long time. I've personally been writing about it now for the last few years. Periodically with my colleagues from ETR, we hit that pretty hard. It's top of mind, and now the house just approved what's called the Better Cybercrime Metrics Act. It was a bipartisan push. I mean, the vote was like 377 to 48 and the Senate approved this bill last year. Once president Biden signs it, it's going to be the law's going to be put into effect and you and many others have been active in this space Infinidat. You announced cyber resilience on your purpose bill backup appliance and secondary storage solution, InfiniGuard with the launch of InfiniSafe. What are you doing for primary storage from InfiniBox around cyber resilience? >> So the goal between the InfiniGuard and secondary storage and the InfiniBox and the InfiniBox SSA II, we're launching it now, but the InfiniSafe for InfiniBox will work on the original InfiniBox. It's a software only thing. So there's no extra hardware needed. So it's a software only play. So if you have an InfiniBox today, when you upgrade to the latest software, you can have the InfiniSafe reference architecture available to you. And the idea is to support the four key legs of the cybersecurity table from a storage perspective. When you look at it from a storage perspective, there's really four key things that the CISO and the CIO look for first is a mutable snapshot technology. An article can't be deleted, right? You can schedule it. You can do all kinds of different things, but the point is you can't get rid of it. Second thing of course, is an air gap. And there's two types of air gap, logical air gap, which is what we provide and physical the main physical air gaping would be either to tape or to course what's left of the optical storage market. But we've got a nice logical air gap and we can even do that logical air gaping remotely. Since most customers often buy for disaster recovery purposes, multiple arrays. We can then put that air gap, not just locally, but we can put the air gap of course remotely, which is a critical differentiator for the InfiniBox a remote logical air gap. Many other players have logical, we're logical local, but we're going remote. And then of course the third aspect is a fenced forensic environment. That fence forensic environment needs to be easily set up. So you can determine a known good copy to a restoration after you've had a cyber incident. And then lastly is rapid recovery. And we really pride ourself on this. When you go to our most recent launch in February of the InfiniGuard within InfiniSafe, we were able to demo live a recovery taking 12 minutes and 12 seconds of 1.5 petabytes of backup data from Veeam. Now that could have been any backup data. Convolt IBM spectrum tech Veritas. We happen to show with Veeam, but in 12 minutes and 12 seconds. Now on the primary storage side, depending on whether you're going to try to recover locally or do it from a remote, but if it's local, we're looking at something that's going to be 1 to 2 minutes recovery, because the way we do our snapshot technology, how we just need to rebuild the metadata tree and boom, you can recover. So that's a real differentiator, but those are four things that a CISO and a CIO look for from a storage vendor is this imutable snapshot capability, the air gaping capability, the fenced environment capability. And of course this near instantaneous recovery, which we have proven out well with the InfiniGuard. And now with the InfiniBox SSA II and our InfiniBox platform, we can make that recovery on primary storage, even faster than what we have been able to show customers with the InfiniGuard on the secondary data sets and backup data sets. >> Yeah. I love the four layer cake. I just want to clarify something on the air gap if I could so you got. You got a local air gap. You can do a remote air gap with your physical storage. And then you're saying there's I think, I'm not sure I directly heard that, but then the next layer is going to be tape with the CTA, the Chevy truck access method, right? >> Well, so while we don't actively support tape and go to that there's basically two air gap solutions out there that people talk about either physical, which goes to tape or optical or logical. We do logical air gaping. We don't do air gaping to tape 'cause we don't sell tape. So we make sure that it's a remote logical air gap going to a secondary DR Site. Now, obviously in today's world, no one has a true DR data center anymore, right. All data centers are both active and DR for another site. And because we're so heavily concentrated in the global Fortune 2000, almost all the InfiniBoxes in the field already are set up as in a disaster recovery configuration. So using a remote logical air gap would be is easy for us to do with our InfiniBox SSA II and the whole InfiniBox family. >> And, I get, you guys don't do tape, but when you say remote, so you've got a local air gap, right? But then you also you call a remote logical, but you've got a physical air gap, right? >> Yeah, they would be physically separated, but when you're not going to tape because it's fully removable or optical, then the security analysts consider that type of air gap, a logical air gap, even though it's physically at a remote. >> I understand, you spent a lot of time with the channel as well. I know, and they must be all over this. They must really be climbing on to the whole cyber resiliency. What do you say, do they set up? Like a lot of the guys, doing managed services as well? I'm just curious. Are there separate processes for the air gap piece than there are for the mainstream production environment or is it sort of blended together? How are they approaching that? >> So on the InfiniGuard product line, it's blended together, okay. On the InfiniBox with our InfiniSafe reference architecture, you do need to have an extra server where you create an scuzzy private VLAN and with that private VLAN, you set up your fenced forensic environment. So it's a slightly more complicated. The InfiniGuard is a 100% automated. On the InfiniBox we will be pushing that in the future and we will continue to have releases on InfiniSafe and making more and more automated. But the air gaping and the fence reference now are as a reference architecture configuration. Not with click on a gooey in the InfiniGuard case are original InfiniSafe. All you do is click on some windows and it just goes does. And we're not there yet, but we will be there in the future. But it's such a top of mind topic, as you probably see. Last year, Fortune did a survey of the Fortune 500 CEOs and the number one cited threat at 66% by the way was cybersecurity. So one of the key things store storage vendors do not just us, but all storage vendors is need to convince the CISO that storage is a critical component of a comprehensive cybersecurity strategy. And by having these four things, the rapid recovery, the fenced forensic environment, the air gaping technology and the immutable snapshots. You've got all of the checkbox items that a CISO needs to see to make sure. That said many CISOs still even today stood on real to a comprehensive cybersecurity strategy and that's something that the storage industry in general needs to work on with the security community from a partner perspective. The value is they can sell a full package, so they can go to their end user and say, look, here's what we have for edge protection. Here's what we've got to track the bad guide down once something's happened or to alert you that something's happened by having tools like IBM's, Q Radar and competitive tools to that product line. That can traverse the servers and the software infrastructure, and try to locate malware, ransomware akin to the way all of us have Norton or something like Norton on our laptop that is trolling constantly for viruses. So that's sort of software and then of course storage. And those are the elements that you really need to have an overall cybersecurity strategy. Right now many companies have not realized that storage is critical. When you think about it. When you talk to people in security industry, and I know you do from original insertion intrusion to solution is 287 days. Well guess what if the data sets thereafter, whether it be secondary InfiniGuard or primary within InfiniBox, if they're going to trap those things and they're going to take it. They might have trapped those few data sets at day 50, even though you don't even launch the attack until day 200. So it's a big deal of why storage is so critical and why CISOs and CIOs need to make sure they include it day one. >> It's where the data lives, okay. Eric. Wow.. A lot of topics we discovered. I love the agile sort of cadence. I presume you're not done for the year. Look forward to having you back and thanks so much for coming on today. >> Great. Thanks you, Dave. We of course love being on "theCUBE". Thanks again. And thanks for all the nice things about Infinidat. You've been saying thank you. >> Okay. Yeah, thank you for watching this cube conversation. This is Dave Vellante and we'll see you next time. (upbeat music)
SUMMARY :
to have you again. And of course, for "theCUBE", of course, on the portfolio over the past year. of product that has the following the storage business, and applications in the industry. spectrum you can now hit and on the latency side and all that sort of nonsense, So the reality is the easier it is to use. So the easier it is for it's across the portfolio. and then we try to upcharge you for that. but the reality is, AI is like containers. and servers or networks in the capability and the Senate approved And the idea is to on the air gap if I could so you got. and the whole InfiniBox family. consider that type of air gap, Like a lot of the guys, and the software infrastructure, I love the agile sort of cadence. And thanks for all the nice we'll see you next time.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Steve | PERSON | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
Steve Manly | PERSON | 0.99+ |
Sanjay | PERSON | 0.99+ |
Rick | PERSON | 0.99+ |
Lisa Martin | PERSON | 0.99+ |
Verizon | ORGANIZATION | 0.99+ |
David | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Fernando Castillo | PERSON | 0.99+ |
John | PERSON | 0.99+ |
Dave Balanta | PERSON | 0.99+ |
Erin | PERSON | 0.99+ |
Aaron Kelly | PERSON | 0.99+ |
Jim | PERSON | 0.99+ |
Fernando | PERSON | 0.99+ |
Phil Bollinger | PERSON | 0.99+ |
Doug Young | PERSON | 0.99+ |
1983 | DATE | 0.99+ |
Eric Herzog | PERSON | 0.99+ |
Lisa | PERSON | 0.99+ |
Deloitte | ORGANIZATION | 0.99+ |
Yahoo | ORGANIZATION | 0.99+ |
Spain | LOCATION | 0.99+ |
25 | QUANTITY | 0.99+ |
Pat Gelsing | PERSON | 0.99+ |
Data Torrent | ORGANIZATION | 0.99+ |
EMC | ORGANIZATION | 0.99+ |
Aaron | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Pat | PERSON | 0.99+ |
AWS Partner Network | ORGANIZATION | 0.99+ |
Maurizio Carli | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Drew Clark | PERSON | 0.99+ |
March | DATE | 0.99+ |
John Troyer | PERSON | 0.99+ |
Rich Steeves | PERSON | 0.99+ |
Europe | LOCATION | 0.99+ |
BMW | ORGANIZATION | 0.99+ |
VMware | ORGANIZATION | 0.99+ |
three years | QUANTITY | 0.99+ |
85% | QUANTITY | 0.99+ |
Phu Hoang | PERSON | 0.99+ |
Volkswagen | ORGANIZATION | 0.99+ |
1 | QUANTITY | 0.99+ |
Cook Industries | ORGANIZATION | 0.99+ |
100% | QUANTITY | 0.99+ |
Dave Valata | PERSON | 0.99+ |
Red Hat | ORGANIZATION | 0.99+ |
Peter Burris | PERSON | 0.99+ |
Boston | LOCATION | 0.99+ |
Stephen Jones | PERSON | 0.99+ |
UK | LOCATION | 0.99+ |
Barcelona | LOCATION | 0.99+ |
Better Cybercrime Metrics Act | TITLE | 0.99+ |
2007 | DATE | 0.99+ |
John Furrier | PERSON | 0.99+ |
Pete Lilley and Ben Bromhead, Instaclustr | CUBE Conversation
(upbeat music) >> Hello, and welcome to this "CUBE" conversation. I'm John Furrier, host of "theCUBE", Here in Palo Alto, California, beginning in 2022, kicking off the new year with a great conversation. We're with folks from down under, two co-founders of Instaclustr. Peter Lilley, CEO, Ben Bromhead, the CTO, Intaclustr success. 'Cause he's been on "theCUBE" before, 2018 at Amazon re:Invent. Gentlemen, thanks for coming on "theCUBE". Thanks for piping in from Down Under into Palo Alto. >> Thanks, John, it's really good to be here, I'm looking forward to the conversation. >> So, I love the name, Instaclustr. It conjures up cloud, cloud scale, modern application, server list. It just gives me a feel of things coming together. Spin me up a cluster of these kinds of feelings. The cloud is here, open sources is growing, that's what you guys are in the middle of. Take a minute to explain what you guys do real quick and this open source cloud intersection that's just going supernova right now. >> Yeah, yeah, yeah. So, Instaclustr is on a mission to really enable the world's ambitions to use open source technology. And we do that specifically at the data layer. And we primarily do that through what we call our platform offering. And think of it as the way to make it super easy, super scalable, super reliable way to adopt open source technologies at the data layer, to build cutting edge applications in the cloud. Today used by customers all over the world. We started the business in Australia but we've very quickly become a global business. But we are the business that sits behind some of the most successful brands that are building massively scalable cloud based applications. And you did right. We sit at a real intersection of kind of four things. One is open source adoption which is an incredibly powerful journey and wave that's driving the future direction of IT. You've got managed services or managed operations and moving those onto a platform like Instaclustr. You've got the adoption of cloud and cloud as a wave, like open source is a wave. And then you've got the growth of data, everything is data-driven these days. And data is just excellent for businesses and our customers. And in a lot of cases when we work with our customers on Instaclustr today, the application and the data, the data is the business. >> Ben, I want to get your thoughts as a CTO because open source, and technology, and cloud, has been a real game changer. If you go back prior to cloud, open source is very awesome, still great, freedom, we've got code, it's just the scale of open source. And then cloud came along, changed the game, so, open source. And then new business models became, so commercial open source software is now an industry. It's not just open source, "Hey, free software." And then maybe a red hat's out there, or someone like a red hat, have some premium support. There's been innovation on the business model side. So, matching technology innovation with the business model has been a big change in the past, many, many years. And this past year in particular that's been key. And open source, open core, these are the things that people are talking about. License changes, this is a big discussion. Because you could be on the wrong side of history if you make the wrong decision here. >> Yeah, yeah, definitely. I think it's also worth, I guess, taking a step back and understanding a little bit about why have people gravitated towards open source and the cloud? Beyond kind of the hippie freedoms of, I can see the code and I have ownership, and everything's free and great. And I think the reason why it's really taken off in a commercial setting, in an enterprise setting is velocity. How much easier is it to go reach and grab a open-source tool? That you can download, you can grab, you can compile yourself, you can make it work the way you want it to do to solve a problem here and now. Versus the old school way of doing it which is with I have to go download a trial version. Oh no, some of the features are locked. I've got to go talk to a procurement or a salesperson to kind of go and solve the problem that I have. And then I've got to get that approved by my own purchasing department. And do we have budget? And all of a sudden it's way, way, way harder to solve the problem in front of you as an engineer. Whereas with open source I just go grab it and I move on. I've achieved something for the day. >> Basically all that friction that comes, you got a problem to solve, oh, open-source, I'm going to just get a hammer and hammer that nail. Wait, whoa, whoa. I got to stand in line, I got to jump over hoops, I got to do all these things. This is the hassle and friction. >> Exactly, and this is why it's often called one of the most impressive things about that. And I think on the cloud side it's the same thing, but for hardware, and capability, and compute, and memory. Previously, if you wanted to compute, oh, you're going to lodge a ticket. You've got to ask someone to rack a server in a data center. You've got to deal with three different departments. Oh my goodness. How painful is that just to get a server up to go run and do something? That's just pulling your hair out. Whereas with the cloud, that's an API call or clicking a few buttons on a console and off you go. You'd have to combine those two things. And I would say that software engineers are probably the most productive they've ever been in the last 20 years. I know sometimes it doesn't look like that but their ability to solve problems in front of them, especially using external stuff is way way, way better. >> Peter: I think when you put those two things together you get an- >> The fact of the matter is they are productive. They're putting security into the code right in the CICD pipeline. So, this is highly agile right now. So, coders are highly productive and efficient in changing the way people are rolling out applications. So, the game is over, open source has won, open core is winning. And this is where the people are confused. This is why I got you guys here? What's the difference between open source and open core? What's the big deal? Why is it so important? >> Yeah, no, great question. So, really the difference between open source and open core, it comes down to, really it's a business model. So, open core contains open-source software, that's a hundred percent true. So, usually what will happen is a company will take a project that is open source, that has an existing community around it, or they've built it, or they've contributed it, or however that genesis has happened. And then what they'll do is they'll look at all the edges around that open-source project. And I think what are some enterprise features that don't exist in the open-source project that we can build ourselves? And then sprinkle those around the edges and sell that as a proprietary offering. So, what you get is you get the core functionality is powered by an open-source project. And quite often the code is identical. But there's all these kinds of little features around the outside that might make it a little bit easier to use in an enterprise environment. Or might make it a bit easier to do some operations side of things. And they'll charge you a license for that. So, you end up in a situation where you might have adopted the open source project, but then now if you want a feature X, Y, or Z, you then need to go and fork over some money and go into that whole licensing kind of contract. So, that's the core difference between open core and open-source, right? Open core, it's got all these little proprietary bits kind of sprinkled around the outside. >> So, how would you describe your platform for your customers? Obviously, you guys are succeeding, your growth is great, we're going to get that second. But as you guys have been steadily expanding the platform of open source data technologies, what is the main solution that you guys are offering customers? Managing open source technologies? What's the main value that you guys bring to the customer? >> Yeah, definitely. So, really the main value that we bring to the customer is we allow them to, I guess, successfully adopt open source databases or database technologies without having to go down that open core path. Open core can be quite attractive, but what it does is you end up with all these many Oracles drivers. Still having to pay the toll in terms of license fees. What we do, however, is we take those open-source projects and we deliver that as a database, as a service on our managed platform. So, we take care of all the operations, the pain, the care, the feeding, patch management, backups. Everything that you need to do, whether you're running it yourself or getting someone else to run it, we'll take care of that for you. But we do it with the pure upstream open source version. So, that means you get full flexibility, full portability. And more importantly you're not paying those expensive license fees. Plus it's easy and it just works. You get that full cloud native experience and you get your database right now when you need it. >> And basically you guys solve the problem of one, I got this legacy or existing licensed technology I've got to pay for. And it may not be enabling modern applications, and they don't have a team to go do all the work (laughing). Or some companies have like a whole army of people just embedded in open-source, that's very rare. So, it sounds like you guys do both. Did I get that right, is that right? >> Yeah, definitely. So, we definitely enable it if you don't have that capability yourself. We are the outsourced option to that. It's obviously a lot more than that but it's one of those pressures that companies nowadays face. And if we take it back to that concept of developer velocity, you really want them working on your core business problems. You don't want them having to fight database infrastructure. So, you've also got the opportunity cost of having your existing engineers working on running this stuff themselves. Or running a proprietary or an open call solution themselves, when really you should be outsourcing preferably to Instaclustr. But hey, let's be honest, you should be outsourcing it to anyone so that your engineers can be focusing on your core business problems. And really letting them work on the things that make you money. >> That's very smart. You guys have a great business model. Because one of the things we've been reporting on "theCUBE" on SiliconANGLE as well, is that the database market is becoming so diverse for the right reasons. Databases are everywhere now and code is becoming horizontally scalable for the cloud but vertically specialized with machine learning. So, you're seeing applications and new databases, no one database rules the world anymore. It's not about Oracle anymore, or anything else. So, open source fits nicely into this kind of platform view. How do you guys decide which technologies go in to the platform that you support? >> Yeah, great question. So, we certainly live in a world of, I call it polyglot persistence. But a simple way of referring to that is the right tool for the right job. And so, we really live in this world where engineers will reach for a database that solves a specific problem and solves it well. As you mentioned, companies, they're no longer Oracle shops, or they're no longer MySQL shops. You'll quite often see services or applications of teams using two or three different databases to solve different challenges. And so, what we do at Instaclustr is we really look at what are the technologies that our existing customers are using, and using side-by-side with, say, some of the existing Instaclustr offerings. We take great lead from that. We also look at what are the different projects out there that are solving use cases that we don't address at the moment. So, it's very use case driven. Whether it's, "Hey, we need something that's better at," say, "Time series." Or we need something that's a little bit better at translatable workloads. Or something a bit of a better fit for a case, right? And we work with those. And I think importantly, we also have this view that in a world of polyglot persistence, you've also got data integration challenges. So, how do you keep data safe between these two different database types? So, we're also looking at how do we integrate those better and support our users on that particular journey. So, it really comes down to one, listening to your customers, seeing what's out there and what's the right use case for a given technology and then we look to adopt that. >> That's great, Ben, machine learning is completely on fire right now. People love it, they want more of it. AI everything, everyone's putting AI on every label. If it does any automation, it's magic, it's AI. So, really, we know what that's happening, it's just really database work and machine learning under the covers. Pete, the business model here has completely changed too, because now with open source as a platform you have more scale, you have differentiation opportunities. I'm sure business is doing great. Give us an update on the business side of Instaclustr. What's clicking for you guys, what's working? What's the success trajectory look like? >> Yeah, it's been an amazing journey for us. When you think about it we were founded it in 2013, so, we're eight years into our journey. When we started the business we were focused entirely on Cassandra. But as Ben talked about, we've gone in diversified those technologies onto the platform, that common experience that we offer customers. So, you can adopt any one to a number of open source technologies in a highly integrated way and really, really grow off the back of that. It's driving some phenomenal growth in our business and we've really enjoyed growth rates that have been 70, 80, 100 year on year since we've started the business. And that's led to an enormous scale and opportunities for us to invest further in the platform, invest further in additional technologies in a really highly opinionated way. I think Ben talked about that integrations, then that becomes incredibly complex as you have many, many kinds of offerings on the platform. So, Instaclustr is much more targeted in terms of how we want to take our business forward and the growth opportunity before us. We think about being deeply expert and deeply capable in a smaller subset of technologies. But those which actually integrate and inter operate for customers so they can build solutions for their applications. But do that on Instaclustr using its platform with a common experience. And, so we've grown to 270 people now around the world. We started in Australia, we've got a strong presence in the US. We recently acquired a business called credativ in Europe, which was a PostgreSQL specialist organization. And that was because, as Ben said before, talking about those technologies we bring onto our platform. PostgreSQL, huge market, disrupting Oracle, exactly the right place that we want to be as Instaclustr with pure open source offerings. We brought them into the Instaclustr family in March this year and we did that to accelerate it on our platform. And so, we think about that. We think about future technologies on their platform, what we can do, and introduced to even provide an even greater and richer experience. Cadence is new to our platform. Super exciting for us because not only is it something that provides workflow as code, as an open source experience, but as a glue technology to build a complex business technology for applications. It actually drives workloads across Cassandra, PostgreSQL and Kafka, which are kind of core technologies on our platform. Super exciting for us, a big market. Interesting kind of group of adopters. You've got Uber kind of leading the charge there with that and us partnering with them now. We see that as a massive growth opportunity for our business. And as we introduce analytics capabilities, exploration, visibility features into the platform all built on open source. So, you can build a complete top to bottom data services layer using open source technology for your platform. We think that's an incredibly exciting part of the business and a great opportunity for us. >> Opportunities to raise money, more acquisitions on the horizon? >> Well, I think acquisitions where it makes sense. I talked about credativ, where we looked at credativ, we knew that PostgreSQL was new to our market, and we were coming into that market reasonably late. So, the way we thought about that from a strategy perspective was we wanted to accelerate the richness of the capability on our platform that we introduced and became GA late last year. So, we think about when we're selecting that kind of technology, that's the perfect opportunity to consider an acquisition for us. So, as we look at what we're going to introduce in the platform over the next sort of two, three, four years, that sort of decision that will, or that sort of thinking, or frames our thinking on what we would do from an acquisition perspective. I think the other way we think about acquisitions is new markets. So, thinking about globally entering, say into the Japanese market. does that make sense because of any language requirements to be able to support customers? 'Cause one of the things that's really, really important to us is the platform is fantastic for scaling, growing, deploying, running, operating this very powerful open source technology. But so too is the importance of having deep operational open source expertise backing and being there to call on if a customer's having an application issue. And that kind of drives the need for us to have in country kind of market support. And so, when we think about those sort of opportunities, I think we think about acquisition there, isn't it like another string to the bow in terms of getting presence in a particular or an emerging market that we're interested in. >> Awesome, Ben, final question to you is, on the technology front what do you see this year emerging? A lot of changes in 2021. We've got another year of pandemic situation going on. Hopefully it goes by fast. Hopefully it won't be three years, but again, who knows? But you're seeing the cloud open source actually taking as a tailwind from the pandemic. New opportunities, companies are refreshing, they have to, they're forced. There's going to be a lot more changes. What do you see from a tech perspective in open-source, open core, and in general for large companies as opensource continues to power the innovation? >> So, definitely the pandemic has a tailwind, particularly for those companies adopting the cloud. I think it's forced a lot of their hands as well. Their five-year plans have certainly become two or three year plans around moving to the cloud. And certainly, that contest for talent means that you really want to be keeping your engineers focused on core things. So, definitely I think we're going to see a continuation of that. We're going to say the continuation of open source dominating when it comes to a database and the database market, the same with cloud. I think we're going to see the gradual march towards different adoption models within the cloud. So, server lists, right? I think we're going to see that kind of slowly mature. I think it's still a little bit early in the hype cycle there, but we're going to start to see that mature. On the ML, AI side of things as well, people have been talking about it for the last three or four years. And I'm sure to people in the industry, they're like, "Oh, we're over that." But I think on the broader industry we're still quite early in that particular cycle as people figure out, how do they use the data that they've got? How do they use that? How do they train models on that? How do they serve inference on that? And how do they unlock other things with lower down on their data stack as well when it comes to ML and AI, right? We're seeing great research papers come out from AI powered indexes, right? So, the AI is actually speeding up queries, let alone actually solving business problems. So, I think we're going to say more and more of that kind of come out. I think we're going to see more and more process capabilities and organizational responses to this explosion of data. I'm super excited to say people talking about concepts and organizational concepts like data mesh. I think that's going to be fundamental as we move forward and have to manage the complexities of dealing with this. So, it's an old industry, data, when you think about it. As soon as you had computers you had data, and it's an old industry from that perspective. But I feel like we're only just getting started and it's just heating up. So, we're super excited to see what 2022 holds for us. >> Every company will be an source AI company. It has to be no matter what. (Ben laughing) Well, thanks for sharing the data Pete and Ben, the co-founders of Instaclustr. We'll get our "CUBE" AI working on this data we got today from you guys. Thanks for sharing, great stuff. Thanks for sharing the open core perspective. We really appreciate it and congratulations on your success. Companies do need more Instaclustrs out there, and you guys are doing a great job. Thanks for coming on, I appreciate it. >> Thanks John, cheers mate. >> Thanks John. >> It's "theCUBE" Conversation here at Palo Alto. I'm John Furrier, thanks for watching. (bright music)
SUMMARY :
kicking off the new year I'm looking forward to the conversation. So, I love the name, Instaclustr. applications in the cloud. it's just the scale of open source. and the cloud? This is the hassle and friction. in the last 20 years. So, the game is over, So, that's the core difference What's the main value that you So, that means you get full So, it sounds like you guys do both. on the things that make you money. is that the database market is the right tool for the right job. So, really, we know what that's happening, and the growth opportunity before us. And that kind of drives the need for us Awesome, Ben, final question to you and the database market, and you guys are doing a great job. I'm John Furrier, thanks for watching.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Peter Lilley | PERSON | 0.99+ |
Australia | LOCATION | 0.99+ |
2013 | DATE | 0.99+ |
Ben | PERSON | 0.99+ |
John | PERSON | 0.99+ |
70 | QUANTITY | 0.99+ |
Ben Bromhead | PERSON | 0.99+ |
two | QUANTITY | 0.99+ |
John Furrier | PERSON | 0.99+ |
five-year | QUANTITY | 0.99+ |
Peter | PERSON | 0.99+ |
Europe | LOCATION | 0.99+ |
Pete | PERSON | 0.99+ |
Palo Alto | LOCATION | 0.99+ |
2021 | DATE | 0.99+ |
Pete Lilley | PERSON | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
US | LOCATION | 0.99+ |
three | QUANTITY | 0.99+ |
Uber | ORGANIZATION | 0.99+ |
eight years | QUANTITY | 0.99+ |
two things | QUANTITY | 0.99+ |
2022 | DATE | 0.99+ |
PostgreSQL | ORGANIZATION | 0.99+ |
three year | QUANTITY | 0.99+ |
four years | QUANTITY | 0.99+ |
270 people | QUANTITY | 0.99+ |
Instaclustr | ORGANIZATION | 0.99+ |
Today | DATE | 0.99+ |
Palo Alto, California | LOCATION | 0.99+ |
2018 | DATE | 0.98+ |
three years | QUANTITY | 0.98+ |
today | DATE | 0.98+ |
both | QUANTITY | 0.98+ |
80 | QUANTITY | 0.98+ |
Oracles | ORGANIZATION | 0.98+ |
One | QUANTITY | 0.97+ |
one | QUANTITY | 0.97+ |
100 year | QUANTITY | 0.97+ |
Cassandra | TITLE | 0.97+ |
March this year | DATE | 0.96+ |
Kafka | TITLE | 0.96+ |
MySQL | TITLE | 0.96+ |
second | QUANTITY | 0.95+ |
Intaclustr | ORGANIZATION | 0.95+ |
PostgreSQL | TITLE | 0.94+ |
hundred percent | QUANTITY | 0.93+ |
pandemic | EVENT | 0.93+ |
two co-founders | QUANTITY | 0.92+ |
past year | DATE | 0.91+ |
SiliconANGLE | ORGANIZATION | 0.9+ |
late last year | DATE | 0.9+ |
theCUBE | ORGANIZATION | 0.9+ |
credativ | ORGANIZATION | 0.88+ |
Amazon | ORGANIZATION | 0.86+ |
three different databases | QUANTITY | 0.86+ |
last 20 years | DATE | 0.84+ |
this year | DATE | 0.83+ |
Instaclustr | TITLE | 0.74+ |
Eric Herzog, Infinidat | CUBEconversations
(upbeat music) >> Despite its 70 to $80 billion total available market, computer storage is like a small town, everybody knows everybody else. We say in the storage world, there are a hundred people, and 99 seats. Infinidat is a company that was founded in 2011 by storage legend, Moshe Yanai. The company is known for building products with rock solid availability, simplicity, and a passion for white glove service, and client satisfaction. Company went through a leadership change recently, in early this year, appointed industry vet, Phil Bullinger, as CEO. It's making more moves, bringing on longtime storage sales exec, Richard Bradbury, to run EMEA, and APJ Go-To-Market. And just recently appointed marketing maven, Eric Hertzog to be CMO. Hertzog has worked at numerous companies, ranging from startups that were acquired, two stints at IBM, and is SVP of product marketing and management at Storage Powerhouse, EMC, among others. Hertzog has been named CMO of the year as an OnCon Icon, and top 100 influencer in big data, AI, and also hybrid cloud, along with yours truly, if I may say so. Joining me today, is the newly minted CMO of Infinidat, Mr.Eric Hertzog. Good to see you, Eric, thanks for coming on. >> Dave, thank you very much. You know, we love being on theCUBE, and I am of course sporting my Infinidat logo wear already, even though I've only been on the job for two weeks. >> Dude, no Hawaiian shirt, okay. That's a pretty buttoned up company. >> Well, next time, I'll have a Hawaiian shirt, don't worry. >> Okay, so give us the backstory, how did this all come about? you know Phil, my 99 seat joke, but, how did it come about? Tell us that story. >> So, I have known Phil since the late 90s, when he was a VP at LSA of Engineering, and he had... I was working at a company called Milax, which was acquired by IBM. And we were doing a product for HP, and he was providing the subsystem, and we were providing the fiber to fiber, and fiber to SCSI array controllers back in the day. So I met him then, we kept in touch for years. And then when I was a senior VP at EMC, he started originally as VP of engineering for the EMC Isilon team. And then he became the general manager. So, while I didn't work for him, I worked with him, A, at LSA, and then again at EMC. So I just happened to congratulate him about some award he won, and he said "Hey Herzog, "we should talk, I have a CMO opening". So literally happened over LinkedIn discussion, where I reached out to him, and congratulate him, he said "Hey, I need a CMO, let's talk". So, the whole thing took about three weeks in all honesty. And that included interviewing with other members of his exec staff. >> That's awesome, that's right, he was running the Isilon division for awhile at the EMC. >> Right. >> You guys were there, and of course, you talk about Milax, LSA, there was a period of time where, you guys were making subsystems for everybody. So, you sort of saw the whole landscape. So, you got some serious storage history and chops. So, I want to ask you what attracted you to Infinidat. I mean, obviously they're a leader in the magic quadrant. We know about InfiniBox, and the petabyte scale, and the low latency, what are the... When you look at the market, you obviously you see it, you talk to everybody. What were the trends that were driving your decision to join Infinidat? >> Well, a couple of things. First of all, as you know, and you guys have talked about it on theCUBE, most CIOs don't know anything about storage, other than they know a guy got to spend money on it. So the Infinidat message of optimizing applications, workloads, and use cases with 100% guaranteed availability, unmatched reliability, the set and forget ease of use, which obviously AIOps is driving that, and overall IT operations management was very attractive. And then on top of that, the reality is, when you do that consolidation, which Infinidat can do, because of the performance that it has, you can dramatically free up rack, stack, power, floor, and operational manpower by literally getting rid of, tons and tons of arrays. There's one customer that they have, you actually... I found out when I got here, they took out a hundred arrays from EMC Hitachi. And that company now has 20 InfiniBoxes, and InfiniBox SSAs running the exact same workloads that used to be, well over a hundred subsystems from the other players. So, that's got a performance angle, a CapEx and OPEX angle, and then even a clean energy angle because reducing Watson slots. So, lots of different advantages there. And then I think from just a pure marketing perspective, as someone has said, they're the best kept secret to the storage industry. And so you need to, if you will, amp up the message, get it out. They've expanded the portfolio with the InfiniBox SSA, the InfiniGuard product, which is really optimized, not only as the PBA for backup perspective, and it works with all the backup vendors, but also, has an incredible play on data and cyber resilience with their capability of local logical air gapping, remote logical air gapping, and creating a clean room, if you will, a vault, so that you can then recover their review for malware ransomware before you do a full recovery. So it's got the right solutions, just that most people didn't know who they were. So, between the relationship with Phil, and the real opportunity that this company could skyrocket. In fact, we have 35 job openings right now, right now. >> Wow, okay, so yeah, I think it was Duplessy called them the best kept secret, he's not the only one. And so that brings us to you, and your mission because it's true, it is the best kept secret. You're a leader in the Gartner magic quadrant, but I mean, if you're not a leader in a Gartner magic quadrant, you're kind of nobody in storage. And so, but you got chops and block storage. You talked about the consolidation story, and I've talked to many folks in Infinidat about that. Ken Steinhardt rest his soul, Dr. Rico, good business friend, about, you know... So, that play and how you handle the whole blast radius. And that's always a great discussion, and Infinidat has proven that it can operate at very very high performance, low latency, petabyte scale. So how do you get the word out? What's your mission? >> Well, so we're going to do a couple of things. We're going to be very, very tied to the channel as you know, EMC, Dell EMC, and these are articles that have been in CRN, and other channel publications is pulling back from the channel, letting go of channel managers, and there's been a lot of conflict. So, we're going to embrace the channel. We already do well over 90% of our business within general globally. So, we're doing that. In fact, I am meeting, personally, next week with five different CEOs of channel partners. Of which, only one of them is doing business with Infinidat now. So, we want to expand our channel, and leverage the channel, take advantage of these changes in the channel. We are going to be increasing our presence in the public relations area. The work we do with all the industry analysts, not just in North America, but in Europe as well, and Asia. We're going to amp up, of course, our social media effort, both of us, of course, having been named some of the best social media guys in the world the last couple of years. So, we're going to open that up. And then, obviously, increase our demand generation activities as well. So, we're going to make sure that we leverage what we do, and deliver that message to the world. Deliver it to the partner base, so the partners can take advantage, and make good margin and revenue, but delivering products that really meet the needs of the customers while saving them dramatically on CapEx and OPEX. So, the partner wins, and the end user wins. And that's the best scenario you can do when you're leveraging the channel to help you grow your business. >> So you're not only just the marketing guy, I mean, you know product, you ran product management at very senior levels. So, you could... You're like a walking spec sheet, John Farrier says you could just rattle it off. Already impressed that how much you know about Infinidat, but when you joined EMC, it was almost like, there was too many products, right? When you joined IBM, even though it had a big portfolio, it's like it didn't have enough relevant products. And you had to sort of deal with that. How do you feel about the product portfolio at Infinidat? >> Well, for us, it's right in the perfect niche. Enterprise class, AI based software defined storage technologies that happens run on a hybrid array, an all flash array, has a variant that's really tuned towards modern data protection, including data and cyber resilience. So, with those three elements of the portfolio, which by the way, all have a common architecture. So while there are three different solutions, all common architecture. So if you know how to use the InfiniBox, you can easily use an InfiniGuard. You got an InfiniGuard, you can easily use an InfiniBox SSA. So the capability of doing that, helps reduce operational manpower and hence, of course, OPEX. So the story is strong technically, the story has a strong business tie in. So part of the thing you have to do in marketing these days. Yeah, we both been around. So you could just talk about IOPS, and latency, and bandwidth. And if the people didn't... If the CIO didn't know what that meant, so what? But the world has changed on the expenditure of infrastructure. If you don't have seamless integration with hybrid cloud, virtual environments and containers, which Infinidat can do all that, then you're not relevant from a CIO perspective. And obviously with many workloads moving to the cloud, you've got to have this infrastructure that supports core edge and cloud, the virtualization layer, and of course, the container layer across a hybrid environment. And we can do that with all three of these solutions. Yet, with a common underlying software defined storage architecture. So it makes the technical story very powerful. Then you turn that into business benefit, CapEX, OPEX, the operational manpower, unmatched availability, which is obviously a big deal these days, unmatched performance, everybody wants their SAP workload or their Oracle or Mongo Cassandra to be, instantaneous from the app perspective. Excuse me. And we can do that. And that's the kind of thing that... My job is to translate that from that technical value into the business value, that can be appreciated by the CIO, by the CSO, by the VP of software development, who then says to VP of industry, that Infinidat stuff, we actually need that for our SAP workload, or wow, for our overall corporate cybersecurity strategy, the CSO says, the key element of the storage part of that overall corporate cybersecurity strategy are those Infinidat guys with their great cyber and data resilience. And that's the kind of thing that my job, and my team's job to work on to get the market to understand and appreciate that business value that the underlying technology delivers. >> So the other thing, the interesting thing about Infinidat. This was always a source of spirited discussions over the years with business friends from Infinidat was the company figured out a way, it was formed in 2011, and at the time the strategy perfectly reasonable to say, okay, let's build a better box. And the way they approached that from a cost standpoint was you were able to get the most out of spinning disk. Everybody else was moving to flash, of course, floyers work a big flash, all flash data center, etc, etc. But Infinidat with its memory cache and its architecture, and its algorithms was able to figure out how to magically get equivalent or better performance in an all flash array out of a system that had a lot of spinning disks, which is I think unique. I mean, I know it's unique, very rare anyway. And so that was kind of interesting, but at the time it made sense, to go after a big market with a better mouse trap. Now, if I were starting a company today, I might take a different approach, I might try to build, a storage cloud or something like that. Or if I had a huge install base that I was trying to protect, and maybe go into that. But so what's the strategy? You still got huge share gain potentials for on-prem is that the vector? You mentioned hybrid cloud, what's the cloud strategy? Maybe you could summarize your thoughts on that? >> Sure, so the cloud strategy, is first of all, seamless integration to hybrid cloud environments. For example, we support Outpost as an example. Second thing, you'd be surprised at the number of cloud providers that actually use us as their backend, either for their primary storage, or for their secondary storage. So, we've got some of the largest hyperscalers in the world. For example, one of the Telcos has 150 Infiniboxes, InfiniBox SSAS and InfiniGuards. 150 running one of the largest Telcos on the planet. And a huge percentage of that is their corporate cloud effort where they're going in and saying, don't use Amazon or Azure, why don't you use us the giant Telco? So we've got that angle. We've got a ton of mid-sized cloud providers all over the world that their backup is our servers, or their primary storage that they offer is built on top of Infiniboxes or InfiniBox SSA. So, the cloud strategy is one to arm the hyperscalers, both big, medium, and small with what they need to provide the right end user services with the right outside SLAs. And the second thing is to have that hybrid cloud integration capability. For example, when I talked about InfiniGuard, we can do air gapping locally to give almost instantaneous recovery, but at the same time, if there's an earthquake in California or a tornado in Kansas City, or a tsunami in Singapore, you've got to have that remote air gapping capability, which InfiniGuard can do. Which of course, is essentially that logical air gap remote is basically a cloud strategy. So, we can do all of that. That's why it has a cloud strategy play. And again we have a number of public references in the cloud, US signal and others, where they talk about why they use the InfiniBox, and our technologies to offer their storage cloud services based on our platform. >> Okay, so I got to ask you, so you've mentioned earthquakes, a lot of earthquakes in California, dangerous place to live, US headquarters is in Waltham, we're going to pry you out of the Golden State? >> Let's see, I was born at Stanford hospital where my parents met when they were going there. I've never lived anywhere, but here. And of course, remember when I was working for EMC, I flew out every week, and I sort of lived at that Milford Courtyard Marriott. So I'll be out a lot, but I will not be moving, I'm a Silicon Valley guy, just like that old book, the Silicon Valley Guy from the old days, that's me. >> Yeah, the hotels in Waltham are a little better, but... So, what's your priority? Last question. What's the priority first 100 days? Where's your focus? >> Number one priority is team assessment and integration of the team across the other teams. One of the things I noticed about Infinidat, which is a little unusual, is there sometimes are silos and having done seven other small companies and startups, in a startup or a small company, you usually don't see that silo-ness, So we have to break down those walls. And by the way, we've been incredibly successful, even with the silos, imagine if everybody realized that business is a team sport. And so, we're going to do that, and do heavy levels of integration. We've already started to do an incredible outreach program to the press and to partners. We won a couple awards recently, we're up for two more awards in Europe, the SDC Awards, and one of the channel publications is going to give us an award next week. So yeah, we're amping up that sort of thing that we can leverage and extend. Both in the short term, but also, of course, across a longer term strategy. So, those are the things we're going to do first, and yeah, we're going to be rolling into, of course, 2022. So we've got a lot of work we're doing, as I mentioned, I'm meeting, five partners, CEOs, and only one of them is doing business with us now. So we want to get those partners to kick off January with us presenting at their sales kickoff, going "We are going with Infinidat "as one of our strong storage providers". So, we're doing all that upfront work in the first 100 days, so we can kick off Q1 with a real bang. >> Love the channel story, and you're a good guy to do that. And you mentioned the silos, correct me if I'm wrong, but Infinidat does a lot of business in overseas. A lot of business in Europe, obviously the affinity to the engineering, a lot of the engineering work that's going on in Israel, but that's by its very nature, stovepipe. Most startups start in the US, big market NFL cities, and then sort of go overseas. It's almost like Infinidat sort of simultaneously grew it's overseas business, and it's US business. >> Well, and we've got customers everywhere. We've got them in South Africa, all over Europe, Middle East. We have six very large customers in India, and a number of large customers in Japan. So we have a sales team all over the world. As you mentioned, our white glove service includes not only our field systems engineers, but we have a professional services group. We've actually written custom software for several customers. In fact, I was on the forecast meeting earlier today, and one of the comments that was made for someone who's going to give us a PO. So, the sales guy was saying, part of the reason we're getting the PO is we did some professional services work last quarter, and the CIO called and said, I can't believe it. And what CIO calls up a storage company these days, but the CIO called him and said "I can't believe the work you did. We're going to buy some more stuff this quarter". So that white glove service, our technical account managers to go along with the field sales SEs and this professional service is pretty unusual in a small company to have that level of, as you mentioned yourself, white glove service, when the company is so small. And that's been a real hidden gem for this company, and will continue to be so. >> Well, Eric, congratulations on the appointment, the new role, excited to see what you do, and how you craft the story, the strategy. And we've been following Infinidat since, sort of day zero and I really wish you the best. >> Great, well, thank you very much. Always appreciate theCUBE. And trust me, Dave, next time I will have my famous Hawaiian shirt. >> Ah, I can't wait. All right, thanks to Eric, and thank you for watching everybody. This is Dave Vellante for theCUBE, and we'll see you next time. (bright upbeat music)
SUMMARY :
Hertzog has been named CMO of the year on the job for two weeks. That's a pretty buttoned up company. a Hawaiian shirt, don't worry. you know Phil, my 99 seat joke, So, the whole thing took about division for awhile at the EMC. and the low latency, what are the... the reality is, when you You're a leader in the And that's the best scenario you can do just the marketing guy, and of course, the container layer and at the time the strategy And the second thing the Silicon Valley Guy from Yeah, the hotels in Waltham and integration of the team a lot of the engineering work and one of the comments that was made the new role, excited to see what you do, Great, well, thank you very much. and thank you for watching everybody.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
IBM | ORGANIZATION | 0.99+ |
Phil Bullinger | PERSON | 0.99+ |
Eric | PERSON | 0.99+ |
Europe | LOCATION | 0.99+ |
2011 | DATE | 0.99+ |
India | LOCATION | 0.99+ |
Phil | PERSON | 0.99+ |
Telco | ORGANIZATION | 0.99+ |
EMC | ORGANIZATION | 0.99+ |
Ken Steinhardt | PERSON | 0.99+ |
California | LOCATION | 0.99+ |
Japan | LOCATION | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
HP | ORGANIZATION | 0.99+ |
Israel | LOCATION | 0.99+ |
Eric Hertzog | PERSON | 0.99+ |
Telcos | ORGANIZATION | 0.99+ |
Infinidat | ORGANIZATION | 0.99+ |
100% | QUANTITY | 0.99+ |
South Africa | LOCATION | 0.99+ |
US | LOCATION | 0.99+ |
Isilon | ORGANIZATION | 0.99+ |
70 | QUANTITY | 0.99+ |
John Farrier | PERSON | 0.99+ |
Eric Herzog | PERSON | 0.99+ |
Hertzog | PERSON | 0.99+ |
two weeks | QUANTITY | 0.99+ |
99 seats | QUANTITY | 0.99+ |
Asia | LOCATION | 0.99+ |
Herzog | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Golden State | LOCATION | 0.99+ |
Waltham | LOCATION | 0.99+ |
Richard Bradbury | PERSON | 0.99+ |
Rico | PERSON | 0.99+ |
next week | DATE | 0.99+ |
one | QUANTITY | 0.99+ |
North America | LOCATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
January | DATE | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
both | QUANTITY | 0.99+ |
five partners | QUANTITY | 0.99+ |
LSA | ORGANIZATION | 0.99+ |
Kansas City | LOCATION | 0.99+ |
2022 | DATE | 0.99+ |
Milax | ORGANIZATION | 0.99+ |
Duplessy | PERSON | 0.99+ |
Middle East | LOCATION | 0.99+ |
EMEA | ORGANIZATION | 0.99+ |
CapEx | ORGANIZATION | 0.99+ |
seven | QUANTITY | 0.99+ |
Both | QUANTITY | 0.99+ |
OPEX | ORGANIZATION | 0.99+ |
last quarter | DATE | 0.99+ |
One | QUANTITY | 0.99+ |
one customer | QUANTITY | 0.99+ |
first | QUANTITY | 0.98+ |
Singapore | LOCATION | 0.98+ |
EMC Hitachi | ORGANIZATION | 0.98+ |
Storage Powerhouse | ORGANIZATION | 0.98+ |
Rob Lee, Pure Storage Pure Launch
>>the cloud is evolving, you know, it's no longer just a set of remote services access through a public cloud Rather it's expanding to on premises to multiple premises across clouds and eventually out to the edge. The challenge for customers is how to treat these locations as one the opportunity for technology companies is to make that as simple as possible from an operational perspective. Welcome to this cube program. We're featuring pure storage and its latest innovations and bringing infrastructure and applications more closely together, fusing them if you will. And today we have a two part program. First we're gonna hear from rob leaves the CTO of pure storage and then my colleague john Walls is gonna talk to scott. Sinclair of Enterprise Strategy Group Scott will provide his expert analysis on infrastructure modernization and what to expect in today's changing world. So joining me right now is rob lee CTO pure storage. Welcome rob. Good to see you. >>Good to see you again to dave >>Okay, so take us through the announcements from today at a high level what's most exciting about what you're delivering? Yeah, >>absolutely. So as you know, many announcements today, many things to discuss. But overall, uh you know, I think what's most exciting is it's the expansion of our ability to help customers along the modern data journey. Right. We've always thought of the journey to modern data is being formed by by three pillars if you will. Certainly modernizing infrastructure modernizing operations uh and applications, uh today's announcements are really uh in that in that kind of middle category if like you said, bringing infrastructures and applications a lot more closely together. Right. We've been modernizing infrastructure since day one. Probably people best know us for that. Today's announcements are really about uh tackling that operations, peace bring infrastructure and code and applications more closely together. So when we think about pure fusion, for example, um you know that that's really a huge step forward in how we're enabling our customers to manage large fleets of infrastructure, uh products and components to deliver those services in a more automated, more tightly integrated, seamlessly transparently delivered way to the application actions that they serve. Whether these services are being delivered by many different arrays in one location, many different arrays in different data center locations or between the premise on premise environment, in the cloud environment. Um likewise, uh the application front, um you know, when we think about today's announcements uh in port works data services, that's really all about how do we make the run and operate uh steps of a lot of the application building blocks that cloud native developers are using and relying on the database applications that are most popular and open source CAssandra Mongo so on and so forth. How do we make the run and operate pieces of those applications, a lot more intuitive, a lot more easily deployed, scaled, managed monitored for those app developers and so a ton of a ton of momentum is a big step forward on that front. And then right in the middle, when we think about today's announcements in pure one, um that's really all about how do we create more visibility, connecting the monitoring and management of the infrastructure, running the apps and bring those closer together. So when we think about um, you know, the visibility, we're now able to deliver for port works to apologies, allowing developers and devops teams to look at the entire uh tech stack, if you will of a container environment from the application to the containers to the kubernetes cluster, to the compute nodes all the way down to the storage and be able to see everything that's going on root cause any sort of problems that come up again, that's all in service of bringing infrastructure and applications a lot more closely together. Um so that's really how I view it, uh and and like I said, it's really the next step in our journey of of helping customers modernize between infrastructure operations and and their applications. >>Okay, So, so you've got the control plane piece, which is all about the operating model. You've got pure one, you mentioned that which is for monitoring, you've got the port works piece, which brings sort of development and deployment together and both infrastructure as a code is code and better understanding that full stack of like you say, from applications through the clusters, the containers all the way down. So the story says, I feel like it's not even storage anymore. I mean it's cloud, >>It is and you know, I talk a little bit because, you know, at the end of the day we deliver storage, but what customers are looking for is in what they value and what they care about is their data. Now, obviously the storage is in service of the data. Um what we're, what we're doing with today's announcements is again just making it extending, extending our reach, helping customers work over their data. Uh you know, a couple more steps down the road beyond just serving the bits and bytes of the storage. But now getting into how do we connect the data that's sitting on our storage more quickly? Get it, you know, in the hands of developers and the applications more seamlessly and more fluidly across these different environments. How >>does this news fit into pure evolution as a company? I mean I don't see it as a pivot because of pivots like, okay, we're gonna go from here and now we're >>doing this right? So >>it's it's more like a reinvention or progression of the vision and the strategy. Can you talk to that? >>Absolutely. Um you know, I think between those two words, I would say it's a progression, it's the next step in the journey as opposed to a reinvention. Right? You know, and again, I go back to um you know, I go back to the difference between storage and data and how customers are using data. We've been on a long, long term hath long term journey to continue to help customers modernize how they work with data, the results they're able to drive from the data we got our starting infrastructure um and and just uh you know, if you want to do, if you want to do bleeding edge things with data, you're not gonna do it on decades old infrastructure. So let's fix that component first. That's how we got our start. Um you know, today's announcements are really the next couple of steps along that journey. Um how do we make, how do we make the core infrastructure more easily delivered, more flexible to operate more automated in the hands of not just the devops teams, the I. T. Teams but the application developers, how do we, how do we deliver infrastructure more seamlessly as code? Well, why why is that important? Um It's important because what customers are looking for out of their data is both speeds and feeds the traditional kind of measures bandwidth i obsolete and see that sort of thing. But they're looking for a speed of agility. Right? You look at the modern application space around how data is being processed. It's a very, very fast moving application space. Uh you know, the databases that are being used today may be different than the ones using being used three months from now or six months from now And so um developers, application teams are looking for, you know, a ton more flexibility, ton more agility than they were 35, 10, 15 years ago. Um The other aspect is simplicity and reliability, right? As you know, um that's a core component of uh you know of everything. We do our core products uh you know, uh you know, our arrays are storage appliances, um you know, we're very well known for the simplicity and reliability. We drive at the individual product level. Well as we scale and look at um you know, larger environments as we look at uh customers expectations for what they expect from a cloud like service. There is the next level of scale and how we deliver that simplicity and reliability. Right. And what do I mean by that? Well, a large enterprise customer who wants to operate like a cloud wants to be able to manage large fleets of uh infrastructure resources, be able to package them up, deliver uh infrastructure services to their internal customers, want they want to be able to do it in a self service, policy driven, easy to control, easy to manage way. Um and that's the next level of fleet level simplicity and that's really what what pure fusion is about, right, is allowing operators that control plane to specify those um those attributes and how that service should be delivered. Um Same thing with poor works, right. If we think about simplicity and reliability, uh containers, collaborative applications, microservices, a lot of benefits. They're very fast moving space, you can mix and match components put them together very easily. Um, but what goes hand in hand with that is now a need for a greater degree of simplicity because you have more moving parts and a greater need for reliability because well now you're not just serving one application, but You know, 30 or 40 working in unison and that's really what we're after with port works and port works data services in the evolution of that family. So getting back to your original question um, I really look at today's announcements as not a pivot, not a reinvention, but the next logical steps in our long-term journey to help customers modernize everything they do around data. >>Right. Thanks for that rob. Hey, I want to switch topics. Virtually every infrastructure player now has an as a service offering and there are lots of claims out there about who was first, who is the best etcetera. What's up yours position on this topic? You claim you're ahead of the pack and delivering subscription and, and as a service offerings in the storage industry? You certainly refers to with Evergreen. That was sort of a real change in how folks delivered. What about as a service and Pure as a service. What gives you confidence that you have the right approach and you're leading the industry in this regard? >>Yeah, absolutely. I mean, I think first and foremost we think of everything we do, uh, you know, pure as a service and whether that's delivering products and helping customers to run and operate uh in an average service model internally or whether it's pure taking on more of that run and operate uh as a service ourselves with pure as a service. Um and so, you know, the second part of your question, which is uh you know, what is it that that sets us apart, What are we doing differently? What gives us confidence that um you know, this is the right path? Well, you know, fundamentally, I think the difference is obviously this is a uh you know, a hotter topic in the industry um you know, of late, but I think the difference is between us and the competitive set is we really look at this as a product and technology led philosophy and strategy and we have since day one. Right. And I think that's different than a lot of others in the industry. Um you know, who look at it as a little bit more of a, you know, a packaging exercise between financial services, professional services, wrap it up in T and CS and call it a service. Um what do I mean by that? Right. So, you know, if you look internally a pure everything we do, we think of as a service, we have a business unit organized around it, we have an engineering team, significant resources dedicated to it uh in building out service offerings. Um, you know, when we think about why this is technology led, uh you know, I think of a service for something to be thought of as a service. Right. It's got to be flexible, it's got to be adaptable. I've got to be able to grow as a customer and evolve as I need uh whether that's, you know, changing needs in terms of performance and capacity, I've got to be able to do that without being locked into day one rigid kind of static swim lanes of Having the capacity plan or plan out what my use is gonna look like 18 months from now. Right. Um I've got to be able to move and evolve and grow without disruption. Right? Uh you know, it's it's not it's not a service if you're gonna make me do a data migration or take a downtown. Uh and so when I net all that out Right, what are the things that you need? The attributes you need to be able to deliver a service? Well, you need a product that that is going to be able to be highly malleable, highly flexible, highly evolved able. Um you need something that's going to be able to cover the entire gamut of, of needs, whether it's price performance, uh tears, uh you know, high performance capacity, lower cost price points. Um you need something that's got a rich set of capabilities, whether it's access protocols, file block object, whether it's data protection properties, you know, replication snapshots, uh ransomware protection, so you need that full suite of capabilities um but in order to deliver this to service and enable me as a customer to seamlessly grow and change, you know, that's got to be delivered in a very tight set of technology that can be repurposed and and configured in different ways. You can't do this on 17 different products uh and expect me to change and and move every every single time I have a a service to need change. And so when I net that out that puts us in a absolutely differentiated position to be able to deliver this because again, everything we do is based on to core product families, port works adds a third. We're able to deliver all of the major storage protocols, all of the data protection capabilities across all of the price, performance and service tiers. And we're able to do this on a very tight code base and and as you know, uh everything we do is completely not disruptive. So all of the elements really add up in our favor. And like I said, this is a huge area of strategic focus for us. >>So these offerings are all part of the services. Service driven component of your portfolio, is that correct? >>Absolutely great. >>Um you talk all the time about modern data experiences, modern applications, modern data changing the way customers think about infrastructure, what exactly does that mean? And how are you driving that? >>Well, I think um I think it means a couple different things, but if I had to let it out, it's it's a greater demand for agility, a greater demand for flexibility and optionality. Um and if we look at why that is uh you know, when I talk to customers As they think about infrastructure largely they think about their existing application demands and needs, what they're spending 90% of their time and budget dealing with today and then the new stuff that they're getting more and more pressured to go off and build and support, which is often times the more strategic initiatives that they have to serve. So they're kind of balancing both worlds um and in the new world of modern applications, it's much more dynamic meaning, you know, the application sets that are being deployed are changing all the time. Um the environments and what the infrastructure needs to deliver uh has to change more quickly in terms of scaling up down, growing has to be a lot more elastic um and has much higher variance. Right? And what I mean by that is um you know, you look at a modern cloud, native microservices architecture type application, it's really, you know, 2030 40 different applications, all working in concert with one another under the hood, This is a very different infrastructure demand than your more traditional application set right back in the day, um you know, you have an oracle application, you go design in an environment for that, right? It's a big exercise, but once you put it in place, it has its own life cycle. Um these days with modern applications, uh you know, it's not just one application, it's 20 or 30, you've got to support all of them, uh you know, working in unison, you don't want to build separate infrastructures for each piece. Um and that set of 20 or 30 applications is changing very rapidly as open source ecosystem moves forward as the application space moves forward. And so when customers think about the changing events and infrastructure, this is kind of what they're thinking about and having to juggle and so that at the end of the day drives them to demand much more flexibility in their infrastructure, being able to use it for many different purposes, um much more agility, being able to adapt very, very quickly. Uh and much more variants are dynamic range, right? The ability to support many different needs on the same set of infrastructure and this is where we see very, very strong demand indicators and we're very invested in meeting these needs because they fit very well with our core product principles. >>Great, thank you for that. I really liked that answer because it's not just a bunch of, you know, slide wear mumbo jumbo, you actually put some substance on rob, we're gonna have to leave it there. Thanks so much for joining us today. >>Thank you and >>look forward to having you back soon. Now in a moment, scott Sinclair, who's a senior analyst at enterprise Strategy Group, speaks with the cubes john walls to give you the independent analysts take you're watching the cube, your global leader in high tech coverage. >>Mhm.
SUMMARY :
the cloud is evolving, you know, it's no longer just a set of remote services access through uh the application front, um you know, when we think about today's announcements uh and better understanding that full stack of like you say, from applications through the clusters, It is and you know, I talk a little bit because, you know, at the end of the day we deliver storage, Can you talk to that? You know, and again, I go back to um you know, I go back to you have the right approach and you're leading the industry in this regard? Um and so, you know, the second part of your question, which is uh you know, So these offerings are all part of the services. Um and if we look at why that is uh you know, when I talk to customers I really liked that answer because it's not just a bunch of, you know, slide wear mumbo jumbo, to give you the independent analysts take you're watching the cube, your global leader in
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
90% | QUANTITY | 0.99+ |
john Walls | PERSON | 0.99+ |
scott Sinclair | PERSON | 0.99+ |
20 | QUANTITY | 0.99+ |
two words | QUANTITY | 0.99+ |
Sinclair | PERSON | 0.99+ |
Rob Lee | PERSON | 0.99+ |
today | DATE | 0.99+ |
Evergreen | ORGANIZATION | 0.99+ |
30 | QUANTITY | 0.99+ |
40 | QUANTITY | 0.99+ |
first | QUANTITY | 0.99+ |
Today | DATE | 0.99+ |
each piece | QUANTITY | 0.98+ |
17 different products | QUANTITY | 0.98+ |
both | QUANTITY | 0.98+ |
First | QUANTITY | 0.98+ |
john walls | PERSON | 0.98+ |
one application | QUANTITY | 0.97+ |
one location | QUANTITY | 0.97+ |
rob | PERSON | 0.97+ |
40 different applications | QUANTITY | 0.97+ |
three months | QUANTITY | 0.96+ |
dave | PERSON | 0.96+ |
2030 | DATE | 0.96+ |
Enterprise Strategy Group | ORGANIZATION | 0.95+ |
one | QUANTITY | 0.94+ |
second part | QUANTITY | 0.93+ |
Strategy Group | ORGANIZATION | 0.93+ |
three pillars | QUANTITY | 0.93+ |
Scott | PERSON | 0.93+ |
30 applications | QUANTITY | 0.92+ |
15 years | DATE | 0.92+ |
six months | QUANTITY | 0.91+ |
third | QUANTITY | 0.91+ |
both worlds | QUANTITY | 0.89+ |
scott | PERSON | 0.87+ |
10 | DATE | 0.87+ |
two part program | QUANTITY | 0.81+ |
18 months | QUANTITY | 0.81+ |
single | QUANTITY | 0.8+ |
couple | QUANTITY | 0.77+ |
35 | DATE | 0.77+ |
day one | QUANTITY | 0.71+ |
CAssandra Mongo | TITLE | 0.63+ |
ton | QUANTITY | 0.62+ |
day | QUANTITY | 0.59+ |
decades | QUANTITY | 0.55+ |
uh | ORGANIZATION | 0.5+ |
Pure//Launch | Pure Storage
(electronic music) >> The cloud is evolving. You know, it's no longer just a set of remote services accessed through a public cloud. Rather, it's expanding to on-premises, to multiple premises, across clouds, and eventually out to the edge. The challenge for customers is how to treat these locations as one. The opportunity for technology companies is to make that as simple as possible from an operational perspective. Welcome to this CUBE program where we're featuring Pure Storage in its latest innovations in bringing infrastructure and applications more closely together, fusing them, if you will. And today, we have a two-part program. First, we're going to hear from Rob Lee who's the CTO of Pure Storage and then my colleague John Walls is going to talk to Scott Sinclair of Enterprise Strategy Group. Scott will provide his expert analysis on infrastructure modernization and what to expect in today's changing world. So joining me right now is Rob Lee, CTO of Pure Storage. Welcome, Rob, good to see you. >> Good to see you again too, Dave. >> So take us through the announcements from today at a high level. What's most exciting about what you're delivering? >> Yeah, absolutely. So as you know, many announcement today, many things to discuss. But overall, I think what's most exciting is it's the expansion of our ability to help customers along the modern data journey. We've always thought of the journey to modern data as being formed by three pillars, if you will, certainly, modernizing infrastructure, modernizing operations and applications. And today's announcements are really in that kind of middle category of, like you said, bringing infrastructures and applications a lot more closely together. We've been modernizing infrastructure since day one, probably, people best know us for that and today's announcements are really about tackling that operations piece, bringing infrastructure and code and applications more closely together. So when we think about Pure Fusion, for example, that's really a huge step forward in how we're enabling our customers to manage large fleets of infrastructure, products, and components to deliver those services in a more automated, more tightly-integrated, seamlessly transparently delivered way to the applications that they serve, whether these services are being delivered by many different arrays in one location, many different arrays in different data center locations, or between the premise, on-premise environment and the cloud environment. Likewise, on the application front, when we think about today's announcements in Portworx Data Services, that's really all about how do we make the run and operate steps of a lot of the application building blocks that cloud-native developers are using and relying on, the database applications that are most poplar in open source, Cassandra, Mongo, so on and so forth, how dow we make the run and operate pieces of those applications a lot more intuitive, a lot more easily deployed, scaled, managed, monitored for those app developers? And so a ton of momentum. It's a big step forward on that front. And then right in the middle, when we think about today's announcements in Pure One, that's really all about how do we create more visibility, connecting the monitoring and management of the infrastructure running the apps and bring those closer together? So when we think about the visibility, we're now able to deliver for Portworx topologies allowing developers and DevOps teams to look at the entire tech stack, if you will, of a container environment from the application to the containers, to the Kubernetes cluster, to the compute nodes, all the way down to the storage, and be able to see everything that's going on, the root cause of any sort of problems that come up, that again, that's all in service of bringing infrastructure and applications a lot more closely together. So that's really how I view it and like I said, that's really the next step in our journey of helping customers modernize between infrastructure, operations, and their applications. >> Okay, so you got the control plane piece which is all about the operating model, you've got Pure One, you mentioned that which is for monitoring, you've got the Portworx piece which brings sort of development and deployment together in both infrastructure as code and better understanding of that full stack of, like you say, from applications through the clusters, the containers, all the way down to the storage. So I feel like it's not even the storage anymore. I mean, it's cloud. (chuckling) >> It is and you know, I chuckle a little bit because at the end of the day, we deliver storage but what customers are looking for is, and what they value and what they care about is their data. Now obviously, the storage is in service of the data and what we're doing with today's announcements is, again, just making it, extending our reach, helping customers work with their data a couple more steps down the road beyond just serving the bits and bytes of the storage but now getting into how do we connect the data that's sitting on our storage more quickly, get it, you know, in the hands of developers and the applications more seamlessly and more fluidly across these different environments. >> How does this news fit into Pure's evolution as a company? I mean, I don't see it as a pivot because a pivot's like, okay, we're going to go from here and now we're doin' this? >> Rob: Yeah, we were doing this, now we're doing that, right. >> And so it's more like a reinvention or a progression of the vision and the strategy. Can you talk to that? >> Absolutely. You know what, I think between those two words, I would say it's a progression, it's a next step in the journey as opposed to a reinvention. And again, I go back to, you know, I go back to the difference between storage and data and how customers are using data. We've been on a long-term path, long-term journey to continue to help customers modernize how they work with data, the results they're able to drive from the data. We got our start in infrastructure and just, you know, if you want to do bleeding edge things with data, you're not going to do it on decades-old infrastructure. So let's fix that component first, that's how we got our start. Today's announcement are really the next couple of steps along that journey. How do we make the core infrastructure more easily delivered, more flexible to operate, more automated in the hands of not just the DevOps teams, the IT teams, but the application developers? How do we deliver infrastructure more seamlessly as code? Well, why is that important? It's important because what customers are looking for out of their data is both speeds and feeds, the traditional kind of measures, bandwidth, iOps, latency, that sort of thing, but they're looking for speed of agility. You look at the modern application space around how data's being processed, it's a very, very fast-moving application space. The databases that are being used today may be different than the ones being used three months from now or six months from now. And so developers, application teams are looking for a ton more flexibility, a ton more agility than they were three, five, 10, 15 years ago. The other aspect is simplicity and reliability. As you know, that's a core component of everything we do. Our core products, you know, our arrays, our storage appliances, we're very well-known for the simplicity and reliability we drive at the individual product level. Well, as we scale and look at larger environments, as we look at customers' expectations for what they expect from a cloud-like service, there's the next level of scale and how we deliver that simplicity and reliability. And what do I mean by that? Well, a large enterprise customer who wants to operate like a cloud, wants to be able to manage large fleets of infrastructure resources, be able to package them up, deliver infrastructure services to their internal customers, they want to be able to do it in a self-service, policy-driven, easy to control, easy to manage way and that's the next level of fleet level simplicity and that's really what Pure Fusion is about is allowing operators that control plane to specify those attributes and how that service should be delivered. Same thing with Portworx, if we think about simplicity and reliability, containers, cloud-native applications, micro services, a lot of benefits there. A very fast-moving space, you can mix and match components, put them together very easily, but what goes hand in hand with that is now a need for a greater degree of simplicity 'cause you have more moving parts, and a greater need for reliability because, well now, you're not just serving one application but 30 or 40 working in unison. And that's really what we're after with Portworx and Portworx Data Services and the evolution of that family. So getting back to your original question, I really look at today's announcements as not a pivot, not a reinvention, but the next logical steps in our long-term journey to help customers modernize everything they do around data. >> Right, thanks for that, Rob. Hey, I want to switch topics. So virtually every infrastructure player now has an as-a-service offering and there're lots of claims out there about who was first, who's the best, et cetera. What's Pure's position on this topic? You claim you're ahead of the pack in delivering subscription and as-a-service offerings in the storage industry. You certainly were first with Evergreen. That was sort of a real change in how folks delivered. What about as-a-service and Pure as-a-service? What gives you confidence that you have the right approach and you're lead in the industry in this regard? >> Yeah, absolutely. I mean, I think of, first and foremost, we think of everything we do at Pure as a service and whether that's delivering products and helping customers to run and operate in an as-a-service model internally, or whether it's Pure taking on more of that run and operate as-a-service, ourselves, with Pure as a service. And so the second part of your question which is what is it that sets us apart, what are we doing differently, what gives us confidence that this is the right path, well, fundamentally, I think the difference is obviously this is a, you know, a hotter topic in the industry of late, but I think the difference is between us and the competitive set is we really look at this as a product and technology-led philosophy and strategy and we have since day one. And I think that's different than a lot of others in the industry who look at it as a little bit more of a packaging exercise between financial services, professional services, wrap it up in T(s) and C(s) and you call it a service. And what do I mean by that? So, you know, if you look internally at Pure, everything we do we think of as a service. We have a business unit organized around it, we have an engineering team, significant resources dedicated to it and building out service offerings. When we think about why this is technology-led, I think of a service. For something to be thought of as a service, it's got to be flexible, it's got to be adaptable. I've got to be able to grow as a customer and evolve as I need, whether that's changing needs in terms of performance and capacity, I've got to be able to do that without being locked into day-one, rigid kind of static some lands of having the capacity planned or plan out what my user's going to look like 18 months from now. I've got to be able to move and evolve and grow without disruption, right? You know, it's not a service if you're going to make me do a data migration or take a down time. And so when I net all that out, what are the things that you need the attributes that you need to be able to deliver a service? Well, you need a product set that is going to be able to be highly malleable, highly flexible, highly evolvable. You need something that's going to be able to cover the entire gamut of needs, whether it's price performance, tiers, you know, high performance capacity, lower cost, price points. You need something that's got a rich set of capabilities whether it's access protocols, file block object, whether it's data protection properties, you know, replications, snapshots, ransomware protection. So you need that full suite of capabilities but in order to deliver it as a service and enable me, as a customer, to seamlessly grow and change, that's got to be delivered on a very tight set of technology that can be repurposed and configured in different ways. You can't do this on 17 different products (chuckling) and expect me to change and move every single time that I have a service need change. And so when I net that out, that puts us in an absolutely differentiated position to be able to deliver this because again, everything we do is based on two core product families, Portworx adds a third. We're able to deliver all of the major storage protocols, all of the data protection capabilities across all of the price performance and service tiers, and we're able to do this on a very tight code base. And as you know, everything we do is completely non-disruptive so all of the elements really add up in our favor. And like I said, this is a huge area of a strategic focus for us. >> So these offerings, they're all part of the service-driven component of your portfolio, is that correct? >> Absolutely, yep. >> Great. You talk all the time about modern data experiences, modern application, the modern data changing the way customers think about infrastructure. What exactly does that mean and how are you driving that? >> Well, I think it means a couple of different things, but if I were to net it out, it's a greater demand for agility, a greater demand for flexibility and optionality. And if we look at why that is, you know, when I talk to customers, as they think about an infrastructure, largely, they think about their existing application demands and needs, what they're spending 90% of their time and budget dealing with today, and then the new stuff that they're getting more and more pressured to go off and build and support which is oftentimes the more strategic initiatives that they have to serve, so they're kind of balancing both worlds. And in the new world of modern applications, it's much more dynamic, meaning the application sets that are being deployed are changing all the time, the environments and what the infrastructure needs to deliver has to change more quickly in terms of scaling up, down, growing, it has to be a lot more elastic, and has much more variance. And what I mean by that is you look at a modern, cloud-native, micro services architecture-type application, it's really, you know, 20, 30, 40 different applications all working in concert with one another under the hood. This is a very different infrastructure demand than your more traditional application set. Back in the day, you have an Oracle application, you go design an environment for that. It's a big exercise, but once you put it in place, it has its own lifecycle. These days with modern applications, it's not just one application, it's 20 or 30, you've got to support all of them working in unison, you don't want to build separate infrastructures for each piece, and that set of 20 or 30 applications is changing very rapidly as open source ecosystem moves forward, as the application space moves forward. And so when customers think about the change in demands and infrastructure, this is kind of what they're thinking about and having to juggle. And so that, at the end of the day, drives them to demand much more flexibility in their infrastructure being able to use it for many different purposes, much more agility being able to adapt very, very quickly, and much more variance or dynamic range, the ability to support many different needs on the same set of infrastructure. And this is where we see very, very strong demand indicators and we're very invested in meeting these needs because they fit very well with our core product principles. >> Great, thank you for that. I really like that answer because it's not just a bunch of slideware mumbo-jumbo. You actually put some substance on it. Rob, we're going to have to leave it there. Thanks so much for joining us today. >> Thank you. >> And look forward to havin' you back soon. Now, in a moment, Scott Sinclair who's a senior analyst at Enterprise Strategy Group speaks with theCUBE's John Walls to give you the independent analyst's take. You're watching theCUBE, your global leader in high tech coverage. (techno music) >> Agility is what all digital organizations strive for, and for almost the entirety of the enterprise storage industry, agility and storage aren't words you'd often hear together. Since the founding of Pure Storage, we've been laser focused on taking what's painful about traditional enterprise storage and making it better. We imagined a world where consumers self-service the provisioning of their storage resources to match the performance and data protection capabilities that their applications require. No endless back and forth between application owners and storage teams, just true on-demand self-service. At the same time, imagine all of the complex storage management operations required to make this possible being automated through software. From the placement of the initial workload to storage adjusting with the unpredictable needs of an application and seamlessly migrating and rebalancing the fleet as needed, all with zero down time and no manual intervention. And finally, imagine almost limitless scale that adjusts to meet your business' data management needs over time. This is what we believe the future of enterprise storage looks like. >> Today, we are announcing Pure Fusion, a leap forward in enterprise storage, marrying the best parts of the public cloud with the storage experience and capabilities you've come to expect from Pure. By bringing the simplicity and scalability of the cloud operating model with on-demand consumption and automated provisioning, organizations can deliver an enterprise-grade managed, self-service storage model that unifies fleets of arrays and optimizes storage pulls on the fly. End users will be able to rapidly consume volumes, file systems, and advanced data services like replication without waiting for backend manual work making storage hardware truly invisible. And organizations will be able to scale seamlessly across block, file, and object workloads, leveraging the power of the entire Pure Storage family, including FlashArray, Pure Cloud Block Store, FlashBlade, and Portworx. (electronic music) >> It is time to take a look at what Pure's up to from a slightly different perspective. To help us do that is Scott Sinclair who's a senior analyst at the Enterprise Strategy Group. And Scott, thanks for joining us here, on theCUBE. Good to see ya today. >> Great to see you. >> All right, so let's jump into this. First, we'll get to the announcement in just a little bit. First off, in terms of Pure's strategy, as you've been watching this company evolve over years now, how has it evolved? And then we'll go to the announcements and how that fits into the strategy. But first off, let's just take them from your point of view where have they been and how are they doin'? >> You know, many people know of Pure or maybe they don't know of their history as an all-Flash array. I think Pure has always been, ever since they entered the IT industry as a pioneer, they're one of the early ones that said look, we're going all in on the all-Flash array business and a focus on Flash technology. Then they were early pioneers in things like Evergreen and things like storage-as-a-service capabilities for on-premises storage. And the entire time, they've had a really almost streamline focus on ease of use which, you know, from the outside, I think everyone talks about ease of use and making things simple for IT, but Pure has really made that almost like core as part of not only their product and their design but also part of their culture. And one of the things, and we'll get into this a little bit as we talk about the announcements, but, you know, if you look at these announcements and where Pure's going, they're trying to expand that culture, that DNA around ease of use or simplicity, and expanding it beyond just storage or IT operations, and really trying to see okay, how do we make the entire digital initiative process or the larger IT operations journey simpler. And I think that's part of where Pure is going is not just storage but focusing more on apps, operations, and data, and making it easier for the entire experience. >> So how do the announcements we're talking about, well, there're three phases here, and again, we'll unpack those separately, but in general, how do the announcements then, you think, fit into that strategy and fit into their view and your view, really, of the market trends? >> I think one of the big trends is, you know, IT in terms for most businesses is, it's not just an enabler anymore. IT's actually in the driver's seat. We see in our research at ESGU, we just did this study and I'm going to glance over my notes as I'm kind of talking, but we see one of the things is more than half of businesses are identifying some portion of their revenue is coming from digital products or digital services. So data is part of the revenue chain for a majority of organizations according to what we're seeing in our research. And so what that does is it puts IT right in that core, you know, that core delivery model of where the faster IT can operate, the faster organizations can realize these revenues opportunities. So what is that doing to IT organizations? Well first off, it makes their life a lot harder, it makes demands continue to increase. But also, this old adage or this old narrative that IT's about availability, it's about resiliency, it's about keeping the lights on and ensuring that the business doesn't go down, well none of that goes away. But now, IT organizations are being measured on their ability to accelerate operations. And in this world where everything's becoming more, you know, more complex, there're more demands, organizations are becoming more distributed, application demands are becoming more diverse and they're growing in breadth. All of this means that more pressure is falling not only on the IT operations but also on the infrastructure providers like Pure Storage to step up and make things even simpler with things like automation and simplification which, you know, we're going to talk about, but to help accelerate those operations. >> Yeah, I mean, if you're DevOps these days, I mean, and you're talkin' about kind of these quandaries that people are in, but what are these specific challenges do you think, on the enterprise level here, that Pure is addressing? >> Well so for example, you talked about developers and driving into that in particular, I want to say let's see, glance at my notes here, about two-thirds of organizations say they're under pressure to accelerate IT initiatives due to pressures specifically from DevOps teams as well as line of business teams. So what does that mean? It means that as organizations build up and try to accelerate either their revenue creation via the creation of software or products, or things of that, that drive, that support a DevOps team, maybe it's improving customer experience for example, as well as other line of business teams such as analytics and trying to provide better insights and better decision making off of data, what that means is this traditional process of IT operations of where you submit a trouble ticket and then it takes, after a few days, something happens and they start doing analysis in terms of basically what ends up being multiple days or multiple weeks, to end up to basically provision storage, it just takes too long. And so in these announcements what we're seeing is Pure delivering solutions that are all about automating the backend services and delivering storage in a way that is designed to be easily and quickly consumed by the new consumers of IT, the developers, the line of business teams via APIs where you can write to a standard API and it goes across basically lots of different technologies and happens very quickly where a lot of the backend processes are automated, and essentially, making the storage invisible to these new consumers. And all of that just delivers value because what these groups are doing is now they can access and get the resources that they need and they don't have to know about what's happening behind the scenes which, candidly, they don't really know much about, right now, and they don't really care. >> Right. (chuckling) That's right. Yeah, what I don't see, what I don't know won't hurt me. And it can, as we know, it can. So let's look at the announcements. Pure Fusion, I think we were hearing about that just a little bit before, earlier in the interview that Dave was conducting, but let's talk about Pure Fusion and your thoughts on that. >> Pure Fusion is what I was talking about a little bit where they're abstracting a lot of the storage capabilities and presenting it as an API, a consistent API that allows developers to provision things very quickly and where a lot of the backend services are automated and, you know, essentially invisible to the developer. And that is, I mean, it addresses where, you know, I kind of talk about this with some of the data that we just, you know, some of our research stats that we just discussed, but it's where a lot of organizations are going. The bottom line is, we used to, in a world where IT services weren't growing as fast and where everything had to be resilient and available, you could put a lot of personnel power or personal hours focused on okay, making sure every box and everything was checked prior to doing a new implementation.and all that was designed to reduce risk and possibly optimize the environment and reduce cost. Now in this world of acceleration what we've seen is organizations need faster responsiveness from the IT organization. Well that's all well and good, but the problem is it's difficult to do all those backend processes and make sure that data's fully being protected or making sure that everything is happening behind the scenes the way it should be. And so this is, again, just mounting more and more pressure. So with things like Pure Fusion what they're doing is they're essentially automating a lot of that on the backend and really simplifying it and making it so storage, or IT administrators can provide access to their line of business, to development teams to leverage infrastructure a lot faster while still ensuring that all those backend services, all those operations still happen. Portworx Data Services also announced and we're hearing it from Dave, for that perspective may be a game-changer in terms of storage. So your take on that and Portworx? >> You know, I really like Portworx. I've been following them ever since prior to the acquisition. One of the things that they were very early on is understanding the impact of micro services on the industry and really, the importance of designing infrastructure around for that environment. I think what they're doing around data services is really intriguing. I think it's really intriguing, first off, for Pure as a company because it elevates their visibility to a new audience and a new persona that may not have been familiar with them. As organizations are looking at, you know, one of the things that they're doing with this data services is essentially delivering a database-as-a-service platform where you can go provision and stand up databases very quickly and again, similar to we talked about fusion, a lot of those backend processes are automated. Really fascinating, again, aligns directly with this acceleration need that we talked about. So, you know, a huge value, but it's really fascinating for Pure because it opens them up to, you know, hey, there's this whole new world of possible consumers that where they're, that they can get experience to really, the ease of use that Pure is known for a lot of the capabilities that Portworx is known for, but also just increase really the value that Pure is able to deliver to some of these modern enterprises. >> And just to add, briefly, on the enhancements that Pure One also being announced today. Your take on those? >> I like that as well. I think one of the things if I kind of go through the list is a lot of insights and intelligence in terms of new app, sizing applications for the environment if I remember correctly, and more, you know, better capabilities to help ensure that your environment is optimized which candidly is a top challenge around IT organizations. We talk about, again, I keep hitting on this need to move faster, faster, faster. One of the big disconnects that we've seen and we saw it very early when organizations were moving to, for example, public cloud services, is this disconnect towards for this individual app, how many resources do I really need and I think that's something that, you know, vendors like Pure need to start integrating more and more intelligence. And that's, my understanding is they're doing with Pure One which is really impressive. >> I hope it's all it takes. Scott, we appreciate the time. Thank you for your insights into what has been a big day for Pure Storage. But thank you again for the time. Scott Sinclair at the Enterprise Strategy Group, senior analyst, there. Let's go back to Dave Vellante now with more on theCUBE. (electronic music) >> Thanks for watching this CUBE program made possible by Pure Storage. I want to say in summary, you know, sometimes it's hard to squint through all the vendor noise on cloud and as-a-service, and all the buzz words, and acronyms in the marketplace. But as I said at the top, the cloud is changing, it's evolving, it's expanding to new locations. The operating model is increasingly defining the cloud. There's so much opportunity to build value on top of the massive infrastructure build-out from the hyperscalers to $100 billion in CapEx last year, alone. This is not just true for technology vendors, but organizations are building their own layer to take advantage of the cloud. Now, of course, technology's critical so when you're evaluating technology solutions, look for the following. First, the ability of the solution to simplify your life. Can it abstract the underlying complexity of a cloud, multiple clouds, connect to on-prem workloads in an experience that is substantially identical, irrespective of location? Does the solution leverage cloud-native technologies and innovations and primitives and APIs or is it just a hosted stack that's really not on the latest technology curve, whether that's processor technology or virtualization, or machine learning, streaming, open source tech, et cetera? Third, how programmable is the infrastructure? Does it make developers more productive? Does it accelerate time to value? Does it minimize rework and increase the quality of your output? And four, what's the business impact? Will customers stand up and talk about the solution and how it contributed to their digital transformation by flexibly supporting emerging data-intensive workloads and evolving as their business rapidly changed? These are some of the important markers that we would suggest you monitor. Pure is obviously driving hard to optimize these and other areas, so watch closely and make your own assessment as to how, what they and others are building will fit into your business. Now as always, this content is available on demand on theCUBE.net, so definitely check that out. This I Dave Vellante for John Walls and the entire CUBE team, thanks for watching, everybody. We'll see ya next time. (soft electronic music)
SUMMARY :
and eventually out to the edge. what you're delivering? and the cloud environment. all the way down to the storage. and bytes of the storage Rob: Yeah, we were doing this, of the vision and the strategy. and that's the next level in the storage industry. and change, that's got to be and how are you driving that? the ability to support have to leave it there. John Walls to give you the and rebalancing the fleet as of the public cloud with at the Enterprise Strategy Group. and how that fits into the strategy. And the entire time, they've had a really and I'm going to glance over my and get the resources that earlier in the interview a lot of that on the backend for a lot of the capabilities And just to add, One of the big disconnects that we've seen Scott Sinclair at the and acronyms in the marketplace.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Scott | PERSON | 0.99+ |
Scott Sinclair | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Rob Lee | PERSON | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
Portworx | ORGANIZATION | 0.99+ |
John Walls | PERSON | 0.99+ |
Rob | PERSON | 0.99+ |
Scott Sinclair | PERSON | 0.99+ |
90% | QUANTITY | 0.99+ |
20 | QUANTITY | 0.99+ |
two words | QUANTITY | 0.99+ |
last year | DATE | 0.99+ |
three | QUANTITY | 0.99+ |
ESGU | ORGANIZATION | 0.99+ |
$100 billion | QUANTITY | 0.99+ |
First | QUANTITY | 0.99+ |
17 different products | QUANTITY | 0.99+ |
five | QUANTITY | 0.99+ |
today | DATE | 0.99+ |
Pure Storage | ORGANIZATION | 0.99+ |
Today | DATE | 0.99+ |
Evergreen | ORGANIZATION | 0.99+ |
each piece | QUANTITY | 0.99+ |
first | QUANTITY | 0.99+ |
three months | QUANTITY | 0.99+ |
four | QUANTITY | 0.99+ |
30 | QUANTITY | 0.99+ |
30 applications | QUANTITY | 0.99+ |
Pure | ORGANIZATION | 0.99+ |
Portworx Data Services | ORGANIZATION | 0.99+ |
one | QUANTITY | 0.99+ |
40 | QUANTITY | 0.98+ |
Third | QUANTITY | 0.98+ |
CUBE | ORGANIZATION | 0.98+ |
One | QUANTITY | 0.98+ |
Enterprise Strategy Group | ORGANIZATION | 0.98+ |
Enterprise Strategy Group | ORGANIZATION | 0.98+ |
both | QUANTITY | 0.98+ |
both worlds | QUANTITY | 0.97+ |
one location | QUANTITY | 0.97+ |
six months | QUANTITY | 0.97+ |
10 | QUANTITY | 0.97+ |
Cassandra | TITLE | 0.96+ |
one application | QUANTITY | 0.96+ |
Unpacking IBM's Summer 2021 Announcement | CUBEconversation
(upbeat music) >> There are many constants in the storage business, relentlessly declining costs per bit. Innovations that perpetually battle the laws of physics, a seemingly endless flow of venture capital, very intense competition. And there's one other constant in the storage industry, Eric Herzog. And he joins us today in this CUBE video exclusive to talk about IBM's recent storage announcements. Eric, welcome back to theCUBE. Great to see you, my friend. >> Great Dave, thank you very much. Of course, IBM always loves to participate with theCUBE and everything you guys do. Thank you very much for inviting us to come today. >> Really our pleasure. So we're going to cover a lot of ground. IBM Storage made a number of announcements this month around data resilience. You've got a new as a service model. You've got performance enhancements. Eric, can you give us, give us the top line summary of the hard news? >> Yeah. Top line. IBM is enhancing data and cyber resiliency across all non mainframe platforms. We already have it on the mainframe of course, and we're changing CapEx to OpEx with our storage as a service. Those are the key takeaways and the hot ticket items from an end user perspective. >> So maybe we could start with sort of the cyber piece. I mean, wow. I mean the last 18 months have been incredible and you're just seeing, you know, new levels of threats. The work from home pivot has created greater exposure. Organizations are kind of rethinking hybrid. You're seeing the ascendancy of some of the sort of hot cyber startups, but, but you're also seeing the, not only of the attack vectors winded, but the, the techniques are different. You know, threat hunting has become much more important. Your responses to threats. You have to be really careful the whole ransomware thing. So what are some of the big trends that you guys are seeing that are kind of informing how you approach the market? >> Well, first of all, it's gotten a lot worse. In fact, Fortune magazine just released the Fortune 500 a couple of weeks ago, and they had a survey that's public of CEOs, and they said, "What's the number one threat to your business? With no list just what's the number one threat?" Cyber security was number one 66% of the Fortune 500 Chief Executive Officers. Not CIOs not CTOs, but literally the CEOs of the biggest companies in the world. However, it's not just big companies. It hits the mid size, the small companies, everyone is open now to cyber threats and cyber attacks. >> Yeah. So for sure. And it's (chuckles) across the board. Let's talk about your solution, the announcement that you made here. Safeguard Copy, I think is what the branding is. >> Yeah. So what we've done is we've got a number of different technologies within our storage portfolio. For example, with our Spectrum Protect product, we can see anomalous pattern detection and backup data sets. Why would that matter? If I am going to hold theCUBE for ransom, if I don't get control of your secondary storage, snaps, replicas, and backups, you can just essentially say, I'm not paying you. You could just do a recovery, right? So we have anomalous protection there. We see encryption, we encrypt at rest with no performance penalty with our FlashSystem's family. We do air gapping. And in case of safeguarded copy, it's a form of air gapping. So we see physical air gapping with tape. logical air gapping, but to a remote location with snaps or replicas to your Cloud provider, and then local logical on-prem, which is what safeguarded copy does. We've had this technology for many years now on the mainframe platform. And we brought it down to the non mainframe environments, Linux, UNIX, and the Windows Server world by putting safeguarded copy on our FlashSystem's portfolio. >> So, okay. So part of the strategy is air gapping. So you're taking a copy, your air gapping it. You probably, you probably take those snaps, you know, at different intervals, you mix that up, et cetera. How do you manage the copies? How do you ensure if I have to do a recovery that you've got kind of a consistent data set? >> Yeah. So a couple things, first of all, we can create on a single FlashSystem array the full array up to 15,000 immutable copies, essentially they're weren't, you can't delete them, you can't change them. On a per volume basis, you can have 255. This is all managed with our storage copy manager, which can automate the entire process. Creation, deletion, frequency, and even recovery mode. So for example, I could have volume one and volume one perhaps I need to make immutable copies every four hours, while at 255 divided by four a day, I can go for many months and still be making those immutable copies. But with our Copy Services Manager, you can set up to be only 30 days, 60 days, you can set the frequency and once you set it up, it's all automated. And you can even integrate with IBM's QRadar, which is a threat detection and breach software from the security division of IBM. And when certain threats hit, it can actually automatically kick off a safeguarded copy. So what we do is make sure you've got that incredibly rapid recovery. And in fact, you can get air gapping, remotely. We have this on the main frame and a number of large global Fortune 500's actually do double air gapping, local logical, right? So they can do recovery in just a couple hours if they have an attack. And then they take that local logical and either go remote logical. Okay. Which gives them a second level of protection, or they'll go out to tape. So you can use this in a myriad of ways. You can have multiple protection. We even, by the way Dave, have three separate different admin levels. So you can have three different types of admins. One admin can't delete, one admin can. So that way you're also safe from what I'll call industrial espionage. So you can never know if someone's going to be stealing stuff from inside with multiple administrative capabilities, it makes it more difficult for someone to steal your data and then sell it to somebody. >> So, okay. Yeah, right. Because immutable is sort of, well, you're saying that you can set it up so that only one admin has control over that, is that right? If you want it... >> There's three, there's three admins with different levels of control. >> Right. >> And the whole point of having a three admins with different levels of control, is you have that extra security from an internal IT perspective versus one person, again, think of the old war movies, you know, nuclear war movies. Thank God it's never happened. Where two guys turn the key. So you've got some protection, we've got multiple admin level to do that as well. So it's a great solution with the air gapping. It's rapid recovery because it's local, but it is fully logically air gapped separated from the host. It's immutable, it's WORM, Write Once, Read Many can't delete can't change. Can't do anything. And you can automate all the management with our Copy Services Manager software that will work with safeguard copy. >> You, you talked about earlier, you could detect anomalous behavior. So, so presumably this can help with, with detecting threats, is that? >> Well, that's what our spectrum protect product does. My key point was we have all levels of data resiliency across the whole portfolio, whether it be encrypting data at rest, with our VTLs, we can encrypt in-flight. We have safeguarded copy on the mainframe, safeguarded copy on FlashSystems, any type of storage, including our competitor storage. You could air gap it to tape, right? With our spectrum virtualized software in our SAN Volume Controller, you could actually air gap out to a Cloud for 500 arrays that aren't even ours. So what we've done is put in a huge set of data and cyber resiliency across the portfolio. One thing that I've noticed, Dave, that's really strange. Storage is intrinsic to every data center, whether you're big, medium, or small. And when most people think about a cybersecurity strategy from a corporate perspective, they usually don't even think about storage. I've been shocked, but I've been in meetings with CEOs and VPs and they said, "oh, you're right, storage is, is a risk." I don't know why they don't think of it. And clearly many of the security channel partners, right? You have channel that are very focused on security and security consultants, they often don't think about the storage gaps. So we're trying to make sure, A, we've got broad coverage, primary storage, secondary storage, backup, you know, all kinds of things that we can do. And we make sure that we're talking to the end users, as well as the channel to realize that if you don't have data resilience storage, you do not have a corporate cybersecurity strategy because you just left out the storage part. >> Right on. Eric, are you seeing any use case patterns emerge in the customer base? >> Well, the main use case is prioritizing workloads. Obviously, as you do the immutable copies, you chew up capacity. Right now there's a good reason to do that. So you've got these immutable copies, but what they're doing is prioritizing workloads. What are the workloads? I absolutely have to have up and going rapidly. What are other workloads that are super important, but I could do maybe remote logical air gapping? What ones can I put out to tape? Where I have a logical, where I have a true physical air gap. But of course tape can take a long recovery time. So they're prioritizing their applications, workloads and use case to figure out what they need to have a safeguarded copy with what they could do. And by the way, they're trying to do that as well. You know, with our FlashSystem products, we could encrypt data at rest with no performance penalty. So if you were getting, you know, 30,000 database records and they were taken, you know, 10 seconds for sake of argument, when you encrypt, normally you slow that down. Well, guess what, when you encrypt with our FlashSystem product. So in fact, you know, it's interesting Dave, we have a comprehensive and free cyber resiliency assessment, no charge to the end-user, no charge to a business partner if they want to engage with us. And we will look at based on the NIST framework, any gaps. So for example, if theCUBE said, these five databases are most critical databases, then part of our cyber resilience assess and say, "ah, well, we noticed that you're not encrypting those. Why are you not encrypting those?" And by the way, that cyber resilience assessment works not only for IBM storage, but any storage estate they've got. So if they're homogenous, we can evaluate that if they're heterogeneous in their storage estate would evaluate that, and it is vendor agnostic and conforms to the NIST framework, which of course is adopted all over the world. And it's a great thing for people to get free, no obligation. You don't have to buy a single thing from IBM. It's just a free assessment of their storage and what cyber security exposure they have in their storage estate. And that's a free thing that we offer that includes safeguarded copy, encryption, air gapping, all the various functionality. And we'll say, "why are you not encrypting? Why are you not air gapping?" That if it's that important, "what, why are you leaving these things exposed?" So that's what our free cyber resilience assessment does. >> Got to love those freebies take advantage of those for sure. A lot of, a lot of organizations will charge big bucks for those. You know, maybe not ridiculously huge bucks, but you're talking tens of thousands. Sometimes you'll get up to hundreds of thousands of dollars for that type of type of assessment. So that's, you've got to take advantage of that if you're a customer out there. You know, I, I wanted to ask you about just kind of shift topics here and get into the, as a service piece of it. So you guys announced your, your as a service for storage, a lot of people have also done that. What do we need to know about the IBM Solution? And what's different from the others, maybe two part question, but what's the first part. What do we need to know? >> A couple of thing is, from an overall strategy perspective, you don't buy storage. It's a full OpEx model. IBM retains legal title. We own it. We'll do the software upgrades as needed. We may even go ahead and swap the physical system out. You buy an SLA, a tier if you will. You buy capacity, performance, we own it. So let's take an easy one. Our tier two, we give you our worst case performance at 2,250 IOPS per terabyte. Our competitors by the way, when you look at their contracts and look what they're putting out there, they will give you their best case number. So if they're two is 2,250, that's the best case. With us it's our worst case, which means if your applications or workloads get 4,000 IOPS per terabyte, it's free. We don't charge you for that. We give you the worst case scenario and our numbers are higher than our competition. So we make sure that we're differentiated true OpEx model. It's not a modified Lease model. So it's truly converts CapEx into operational expense. We have a base as everybody does, but we have a variable. And guess what? There's the base price and the variable price are the same. So if you don't use the variable, we don't charge you. We bill you for 1/4 in arrears, every feature function that's on our FlashSystem technology such as safeguarded copy, which we just talked about. AI based tiering, data at rest encryption with no performance penalty, data in compression with no performance, all those features you get, all of them, all we're doing is giving you an option. We still let you buy CapEx. We will let you lease with IBM Global Financial Services. And guess what? You could do a full OpEx model. The technology though, our flash core modules, our spectrum virtualized software is all the same. So it's all the same feature function. It's not some sort of stripped down model. We even offer Dave, 100% availability option. We give Six Nines of availability as a default, several of the competitor, which is only five minutes and 26 seconds of downtime, several of our competitors, guess what they give? Fournines. If you want five or six, you got to pay for it. We just give you six as a default differentiator, but then we're the only vendor to offer 100% availability guarantee. Now that is an option. It's the one option. But since we're already at Six Nines, when our competitors are at Four or Five Nines, we already have better availability with our storage as a service than the competition does. >> So let me just make this, make sure I'm clear on this. So you got Six Nines as part of the service. That's >> Absolutely >> Fundamental. And I get, I can pay up for 100% availability option. And, >> Yes you can. >> So what does that, what does that mean? Practically? You're putting in redundancies and, >> Right, right. So we have a technology known as HyperSwap. We have several public references by the way, at ibm.com. We've been shipping HyperSwap on both the mainframe, probably eight or nine years now. We brought it to our FlashSystem product probably five years ago. As I mentioned, we've got public references. You don't pay for the software by the way, you do have to have a dual node cluster. And HyperSwap allows you to do that. But you can do that as a service. You can buy it. You can do as CapEx, right? When you need the additional FlashSystem to go with it again, the software is free. So you're not to pay for the software. You just have to pay for the additional system level componentry, but you can do that as a service and have it completely be an OpEx model as well. We even assign a technical account manager to every account. Every account gets a technical account manager. If you will, concierge service comes with every OpEx version of our storage as a service. >> So what does that mean? What does that concierge do? Just paying attention to (indistinct) >> Concierge service will do a quarterly, a quarterly review with you. So let's say theCUBE bought 10,000 other analyst firms in the industry. You're now the behemoth. And you at theCUBE are using IBM storage as a service. You call up your technical account manager to say, "Guess what? We just bought these companies. We're going to convert them all to storage as a service, A, we need a higher tier, you could upgrade the tier B, we have a one-year contract, but you know what we'd like to extend it to two, C, we think we need more capacity." You tell your technical account manager, they'll take care of all of that for you, as well as giving you best practices. For example, if you decide you want to do safeguarded copy, which you can do, because it's built into our spectrum virtualized software, which is part of our storage as a service, we can give you best practices on that he would tell you, or she would tell you about our integration with our security visions, QRadar. So those are various best practices. So the technical account manager makes sure the software is always up to date, right? All the little things that you would have to do yourself if you own it, we take care of, because we legally own it, which is allow you to buy it as a service. So it is a true OpEx model from a financial perspective. >> In the term of the contracts are what? One, two and three years. >> One to five. >> Yeah. Okay. >> If you don't renew and you don't cancel, we'll automatically re up you at the exact tier you're at, at the exact same price. Several of our competitors, by the way, if you do that, they actually charge you a premium until you sign a contract. We do not. So if you have a contract based on tier two, right? We go buy SLA tier one, tier two, tier three. So if I have a tier two contract at theCUBE, and you forgot to get the contract done at the end of two years, but you still want it, you can go for the next 2/4. I mean, well our business partner as I should say, "Dave, don't you want to sign a contract, you said you like it." Obviously you would, but we will let you stay. You just say, now I want to keep it without a contract. And we don't charge your premium. Our competitors if you don't have a contract, they charge your premium. If you keep it installed without putting a contract in place. So little things like that clearly differentiate what we do. We don't charge a premium. If you go above the base. One of the competitors, in fact, when you go into the variable space, okay? And by the way, we provide 50% extra capacity. We over-provision. The other competitors usually do 25%. We do 50%. No charge, is just part of the service. So the other vendors, if you go into the variable space, they raised the price. So if it's $5, you know, for X capacity and you go into the, which is your base, and then you go above that, they charge you $7 and 50 cents. We don't. It's $5 at the base and $5 at the variable. Now obviously your variable can be very big or very small, but whatever the variable is, we charge you. But we do not charge you an a bigger price. Couple of competitors when you go into the variable world, they charge you more. Guess what it gets you to do, raise your base capacity. (Eric laughs) >> Yeah. I mean, that's, that should, the math should be the opposite of that, in my view. If you make a commitment to a vendor, say, okay, I'm going to commit to X. You have a nice chart on this, actually in your, in your deck. If I'm going to commit to X, and then I'm going to add on, I would think the add on price per bit should be at the same or lower. It shouldn't be higher. Right? And I get, I get what you're saying there. They're forcing you to jack up the base, but then you're taking all the risk. That's not a shared risk model. I get... >> And that's why we made sure that we don't do that. In fact, Dave, you can, you know, the fact that we don't charge you a premium if you go beyond your contract period and say, "I still wanted to do it, but I haven't done the contract yet." The other guys charge you a premium, if you go beyond your contract period. We don't do that either. So we try to be end-user friendly, customer friendly, and we've also factored in our business partners can participate in this program. At least one of our competitors came out with a program and guess what? Partners could not participate. It was all direct. And that company by happens to have about 80% of their business through the channel and their partners were basically cut out of the model, which by the way, is what a lot of Cloud providers had done in the past as well. So it was not a channel friendly model, we're channel friendly, we're end user-friendly, it's all about ease of use. In fact, when you need more capacity, it takes about 10 minutes to get the new capacity up and going, that's it? >> How long does it take to set up? How long does it take to set up initially? And how long does it take to get new capacity? >> So, first of all, we deploy either in a Colo facility that you've contracted with, including Equinix, Equinix, is part of our press release, or we install on your site. So the technical account managers is assigned, he would call up theCUBE and say, "When is it okay for us to come install the storage?" We install it. You don't install anything. You just say, here's your space. Go ahead and install. We do the installation. You then of course do the normal rationing of the capacity to this goes to this Oracle, this goes to SAP. This goes to Mongo or Cassandra, right? You do that part, but we install it. We get it up and going. We get it turned on. We hook it up to your switching infrastructure. If you've got switching infrastructure, we do all of that. And then when you need more capacity, we use our storage insights pro which automatically monitors capacity, performance, and potential tech support problems. So we give you 50% extra, right? If you drop that to 25%, so you now don't have 50% extra anymore, you only have 25% extra, we'll, the technical account manager would call you and say, "Dave, do you know that we'd like to come install extra capacity at no charge to get you back up to that 50% margin?" So we always call because it's on your site or in your Colo facility, right? We own the asset, but we set it up and you know, it takes a week or two, whatever it takes to ship to whatever location. Now by the way, our storage as a service for 2021 will be in North America and Europe only, we are really expanding our storage as a service outside into Asia and into Latin America, et cetera, but not until 2022. So we'll start out with North America and Europe first. >> So I presume part of that is figuring out just the compensation models right? And so how, how did you solve that? I mean, you can't, you know, you don't seem to be struggling with that. Like some do. I think there's some people dipping their toes in the water. Was that because, you know, IBM's got experience with like SAS pricing or how were you thinking about that and how did you deal with kind of the internal (indistinct) >> Sure. So, first of all, we've had for several years, our storage utility model. >> Right? >> Our storage utility model has been sort of a hybrid part CapEx and part OpEx. So first of all, we were already halfway there to an OpEx model with our storage utility model that's item, number one. It also gave us the experience of the billing. So for example, we bill you for a full quarter. We don't send you a monthly bill. We send you a quarterly bill. And guess what, we always bill you in arrears. So for example, since theCUBE is going to be a customer this quarter, we will send you a bill for this quarter in October for the October quarter, we'll send you a bill for that quarter in January. Okay. And if it goes up, it goes up. If it goes down, it goes down. And if you don't use any variable, there's no bill. Because what we do is the base you pay for once a year, the variable you pay for by on a quarterly basis. So if you, if you are within the base, we don't send you a bill at all because there's no bill. You didn't go into the variable capacity area at all. >> I love that. >> When you have a variable It can go up and down. >> Is that unique to some, do some competitors try to charge you up front? Like if it's a one-year term. (Dave laughs) >> Everbody charges, everybody builds yearly on the base capacity. Pretty much everyone does that. >> Okay, so upfront you pay for the base? Okay. >> Right. And the variable can be zero. If you really only use the base, then there is no variable. We only bill for it's a pay for what you use model. So if you don't use any of the variable, we never charge you for variable. Now, you know, because you guys have written about it, storage grows exponentially. So the odds of them ending up needing some of the variable is moderately high. The other thing we've done is we didn't just look at what we've done with our storage utility model, but we actually looked at Cloud providers. And in fact, not only IBM storage, but almost every of our competitors does a comparison to Cloud pricing. And when you do apples to apples, Cloud vendors are more expensive than storage as a services, not just from us, but pretty much for a moment. So let's take an example. We're Six Nines by default. Okay. So as you know, most Cloud providers provide three or Fournines as the default. They'll let you get five or Six Nines, but guess what? They charge you extra. So item number one. Second thing, performance, as you know, the performance of Cloud storage is usually very weak, but you can make it faster if you want to. They charge extra for that. We're sitting at 2,250 terabytes per IOPS, excuse me, per terabytes. That's incredible performance If you've got 100 terabytes, okay. And if your applications and workloads and that's the worst case, by the way, which differentiates from our competitors who usually quote the best case, we quote you the worst case and our worst case by the way, is almost always higher than their best cases in each of the tiers. So at their middle tier, our worst case is usually better than their best case. But the point is, if you get 4,000 IOPS per terabyte and you're on a tier two contract, it's a two-tier contract. And in fact, let's say that theCUBE has a five-year deal. And we base this on our FlashSystem technology. And so let's say for tier two, for sake of argument, FlashSystem, 7,200. We come out two years after theCUBE has it installed with the FlashSystem, 7,400. And let's say the FlashSystem, 7,400, won't deliver a 2,250 IOPS per terabyte, but 5,000, if we choose to replace it, 'cause remember it's our physical property. We own it. If we choose to replace that 7,200 with a 7,400, and now you get 5,000 IOPS per terabyte, it's free. You signed a tier two contract for five years. So two years later, if we decide to put a different physical system there and it's faster, or has four more software features, we don't charge you for any of that. You signed an SLA for tier two. >> You haven't Paid for capacity, right? All right. >> You are paying for the capacity (indistinct) performance, you don't pay for that. If we swap it out and the, the array is physically faster, and has got five new software features. You pay nothing, you pay what your original contract was based on the capacity. >> What I'm saying is you're learning from the Cloud providers 'cause you are a Cloud provider. But you know, a lot of the Cloud providers always sort of talk about how they lower prices. They lower prices, but you know, well, you worked at storage companies your whole life and they, they lower prices on a regular basis because they 'cause the cost of the curve. And so. >> Right. The cost of storage to Cloud, I mean, the average price decline in the storage industry is between 15 and 25%, depending on the year, every single year. >> Right. >> As, you know, you used to be with one of those analysts firms that used to track it by the numbers. So you've seen the numbers. >> For sure. Absolutely. >> On average it drops 15 to 25% every year. >> So, what's driving this then? If it's, it's not necessarily, is it the shift from, from CapEx to OPEX? Is it just a more convenient model than on a Cloud like model? How do you see that? >> So what's happened in IT overall is of course it started with people like salesforce.com. Well, over 10 years ago, and of course it's swept the software industry software as a service. So once that happened, then you now see infrastructure as a service, servers, switches, storage, and an IBM with our storage as a service, we're providing that storage capability. So that as a service model, getting off of the traditional licensing in the software world, which still is out there, but it's mostly now is mostly software as a service has now moved into the infrastructure space. From our perspective, we are giving our business partners and our customers, the choice. You still want to buy it. No problem. You want to lease it? No problem. You want a full OpEx model. No problem. So for us, we're able to offer any of the three options. The, as a service model that started in software has moved now into the systems world. So people want to change often that CapEx into OpEx, we can even see Global Fortune 500s where one division is doing something and a different division might do something else, or they might do it different by geography. In a certain geography, they buy our FlashSystem products and other geographies they lease them. And in other geographies it's, as a service. We are delivering the same feature, function, benefit from a performance availability software function. We just give them a different way to procure. Do you want CapEx you want leasing or OpEx you pick what you want, we'll deliver the right solution for you. >> So, you got the optionality. And that's great. You've thought that out, but, but the reason I'm asking Eric, is I'm trying to figure out this is not just for you for everybody. Is this a check-off item or is this going to be the prevailing way in which storage is consumed? So if you had, if you had a guess, let's go far out. So we're not making any near-term forecast, but end of the decade, is this going to be the dominant model or is it going to be, you know, one of the few. >> It will be one of a few, but it'll be a big few. It'll be the big, one of the biggest. So for sake of argument, there we'll still be CapEx, they'll still be OpEx they'll still be, or there will be OpEx and they're still be leasing, but I will bet you, you know, at the end of this decade, it'll be 40 to 50% will be on the OpEx model. And the other two will have the other 50%. I don't think it's going to move to everything 'cause remember, it's a little easier during the software world. In the system world, you've got to put the storage, the servers, or the networking on the prem, right? Otherwise you're not truly, you know, you got to make it a true OpEx model. There's legal restrictions. You have to make it OpEx, if not, then, you know, based on the a country's practice, depending on the country, you're in, they could say, "Well, no, you really bought that. It's not really a service model." So there's legal constraints that the software worldwise easier to get through and easier to get to bypass. Right? So, and remember, now everything is software as a service, but go back when salesforce.com was started, everyone in the enterprise was doing ELAs and all the small companies were buying some sort of contract, right, or buying by the (indistinct) basis. It took a while for that to change. Now, obviously the predominant model is software as a service, but I would argue given when salesforce.com started, which was, you know, 2007 or so, it took a good 10 years for software as a service to become the dominant level. So I think A, it won't take 10 full years because the software world has blazed a trail now for the systems world. But I do think you'll see, right. We're sitting here know halfway through 2021, that you're going to have a huge percentage. Like I said, the dominant percentage will be OpEx, but the other two will still be there as well. >> Right. >> By the way, you know in software, almost, no one's doing ELAs these days, right? A few people still do, but it's very rare, right? It's all software as a service. So we see that over time doing the same thing in the, in the infrastructure side, but we do think it will be slower. And we'll, we'll offer all three as, as long as customers want it. >> I think you're right. I think it's going to be mixed. Like, do I care more about my income statement or my balance sheet and the different companies or individual different divisions are going to have different requirements. Eric, you got to leave it there. Thanks much for your time and taking us through this announcement. Always great to see you. >> Great. Thank you very much. We really appreciate our time with theCUBE. >> All right. Thank you for watching this CUBE conversation. This is Dave Vellante and we'll see you next time. (upbeat music)
SUMMARY :
in the storage business, and everything you guys do. Eric, can you give us, and the hot ticket items how you approach the market? of the Fortune 500 Chief the announcement that you made here. you can just essentially say, So part of the strategy is air gapping. So you can use this in a myriad of ways. If you want it... different levels of control. And you can automate all the management you could detect anomalous behavior. And clearly many of the security are you seeing any use So in fact, you know, So you guys announced your, So if you don't use the So you got Six Nines And I get, And HyperSwap allows you to do that. we can give you best practices on that In the term of the contracts are what? Yeah. So the other vendors, if you If you make a commitment if you go beyond your So we give you 50% extra, right? and how did you deal with kind of the So, first of all, we've the variable you pay for When you have a variable to charge you up front? on the base capacity. Okay, so upfront you pay for the base? So if you don't use any of the variable, You haven't Paid for capacity, right? you pay what your original contract was But you know, decline in the storage industry As, you know, For sure. 15 to 25% every year. Do you want CapEx you want leasing or OpEx So if you had, if not, then, you know, By the way, you know in software, Eric, you got to leave it there. Thank you very much. Thank you for watching
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave | PERSON | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Eric | PERSON | 0.99+ |
One | QUANTITY | 0.99+ |
Equinix | ORGANIZATION | 0.99+ |
Asia | LOCATION | 0.99+ |
$7 | QUANTITY | 0.99+ |
Eric Herzog | PERSON | 0.99+ |
$5 | QUANTITY | 0.99+ |
six | QUANTITY | 0.99+ |
five | QUANTITY | 0.99+ |
IBM Global Financial Services | ORGANIZATION | 0.99+ |
40 | QUANTITY | 0.99+ |
five-year | QUANTITY | 0.99+ |
North America | LOCATION | 0.99+ |
2,250 | QUANTITY | 0.99+ |
60 days | QUANTITY | 0.99+ |
OPEX | ORGANIZATION | 0.99+ |
100% | QUANTITY | 0.99+ |
25% | QUANTITY | 0.99+ |
one-year | QUANTITY | 0.99+ |
Latin America | LOCATION | 0.99+ |
50% | QUANTITY | 0.99+ |
Europe | LOCATION | 0.99+ |
5,000 | QUANTITY | 0.99+ |
two | QUANTITY | 0.99+ |
three | QUANTITY | 0.99+ |
three admins | QUANTITY | 0.99+ |
CapEx | ORGANIZATION | 0.99+ |
10 years | QUANTITY | 0.99+ |
2,250 terabytes | QUANTITY | 0.99+ |
10 seconds | QUANTITY | 0.99+ |
2021 | DATE | 0.99+ |
2007 | DATE | 0.99+ |
October quarter | DATE | 0.99+ |
a week | QUANTITY | 0.99+ |
100 terabytes | QUANTITY | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
15 | QUANTITY | 0.99+ |
255 | QUANTITY | 0.99+ |
7,200 | QUANTITY | 0.99+ |
two guys | QUANTITY | 0.99+ |
26 seconds | QUANTITY | 0.99+ |
North America | LOCATION | 0.99+ |
five years ago | DATE | 0.99+ |
FlashSystem | TITLE | 0.99+ |
first part | QUANTITY | 0.99+ |
eight | QUANTITY | 0.99+ |
five minutes | QUANTITY | 0.99+ |
two-tier | QUANTITY | 0.99+ |
one division | QUANTITY | 0.99+ |
two part | QUANTITY | 0.99+ |
each | QUANTITY | 0.99+ |
five years | QUANTITY | 0.99+ |
nine years | QUANTITY | 0.99+ |
Bryan Kirschner, DataStax | CUBE Conversation, July 2021
>>Welcome to this cube conversation. I'm Lisa Martin. Joining me next is bran Kirschner, the vice president of strategy at DataStax Brian. Welcome to the program. Thank you. Glad to be here. Excited to unpack this survey that DataStax recently did. This is with 500 or so it executives, technology practitioners talking about data strategy. Talk to me, first of all, about the state of the data, racist, the name of the survey. Why did data sect students? What was the impetus behind that? >>Yeah. Great question. Thank you. So, you know, um, we are in a race for our company. Every organization is in a race to find ways to use data in new ways to move the business forward, satisfy your customers and so on. Um, it's okay to have a strategy to be a leader. It's probably okay to have a strategy, to be a fast follower. It might even be okay to say we stayed in touch with best practices and once they're proven we adopt them, but what's not okay, is one to lose track of where you need to be relative to how the market's moving most important than your competitors. But in general, customer expectations, your employee partner expectations are going to be set by companies potentially in different industries. So you need to be at the right spot in your journey. So that's why we do a lot of benchmarking, but as important is as your particular company's context and history and situation and technical architecture, um, kind of comes in contact with a strategy that looks great on paper, you have to understand is something slowing us down that we didn't expect because of our culture or unspoken incentives or, you know, what is our next best step for us? >>So in this, in this dataset, we really look to identify the leaders who are having the most success and then work back from the patterns and practices we saw with them to how different, different types of companies at different stages of their journey can find their next best step to make the right progress. >>So the showed that a lot of companies have a data strategy. The execution piece is a, is a different story. Talk to me about how this survey defines a data leader. What is it, what are some of the key characteristics? Yes, >>There are quite a few. Um, in fact, what we've done over the last year that we fed into the survey was, you know, in the course of my work and my colleagues work, we talked with lots of CEOs, hands-on techno practitioners, CTOs, and so on. And we put all that conversation and qualitative insight together into, uh, about 70 measures. Um, and so that was all in the survey. And once we got the data back, uh, we did a cluster analysis, bringing some data science, the data strategy, if you will. Um, and that's surface these segments. Um, and for example, how much revenue you were generating from data was not part of the, so then we mapped these segments and these practices against that, and we say, oh, the leaders generating the most revenue from data. So that gave us some confidence in using these patterns and practices to bucketize folks. >>And you found that the data, those companies in the data leadership category were able to attribute more than 20% of their data of two gives me 20% of their revenue to data and analytics. Talk to me about that 20% benchmark is that considered where a lot of organizations need to aim to be because there's still a lot of money on the table. Yeah, >>That's right. That's right. So, you know, in common industry parlance as a standard, you know, materiality on the balance sheet is 10%. Um, and we've seen a pretty significant number of companies hit that mark. Um, what we saw, which is interesting in our data was, you know, that's kind of a comfortable benchmark to pick it's an industry standard data's material, Hey, congratulations. Uh, but you're actually drill down further and you look at that 20% mark and you say, well, 10% is probably not aiming nearly high enough because a significant proportion of these leaders have already gotten to that 20% mark. Um, and so it's in part, you know, again about that benchmarking where you are, where's your destination, your destination, probably isn't we're on the board, your destination probably isn't its material. Your destination is probably, you know, it's big and it keeps getting bigger. >>And where are these data leaders with respect to deploying a hybrid data strategy? What is it about how they're organized and structurally what they're doing that is positioning them to actually really drive incremental revenue from data? >>Yes. Yeah. What stands out about the leaders, um, is, and, you know, we see this in our data, you can see this in any number of analysts, firms and other data sources hybrid cloud strategy is, you know, the dominant strategy for large enterprises, right? It's about preserving your flexibility to operate in multiple clouds. And on-prem, so that's pretty well understood. What we saw in this data was overwhelmingly almost a hundred percent of the data leaders also say they're pursuing a hybrid data strategy. So they're already doing that kind of same level of thoughtfulness and planning about how can we get and deploy apps and compute everywhere to how can we store and deploy and redeploy data everywhere. And there's a real steep curve to the extent where the folks who are just starting out, who may have a strategy, but have taken very little action. None of them strongly agree that they have that type of hybrid data strategy. Um, and so the pattern qualitative pattern we see is companies go down this hybrid cloud compute strategy for good reasons, and it pays off, starts to pay off. And then they realize, oh, we should be doing the same thing for data. Um, and that's giving these leaders, you know, a lot of agility control, flexibility, um, and opportunities. >>One of the things I found interesting in the report from a statistics perspective is that those data leaders that you talked about that are able to, or able to attribute more than 20% of their revenue to data and analytics twice as many of those are two. And they're two X likely to be using a robust open source data stack talking about that as it plays into the computing strategy and the ability to convert data into revenue. >>That's right. So they're, they're, they're almost a hundred percent comparable to the hybrid data strategy. Almost a hundred percent are also increasing their use of open source software. And I kind of think about this from, from two dimensions, right? The, the hybrid cloud and hybrid data strategy gives you agility, optionality flexibility for your infrastructure, for your compute, for your storage and so on. Um, then it's about really making sure you're using the best of breed tools for the job of creating value with data. Um, and if you look backwards, um, you know, the track record of open source technologies, Apache Cassandra Kafka spark at some of just like, you know, the applications and experiences that are, you know, have, have, you know, validated the massive impact data can have on a business. Um, the track record of open source is strong and you look at the cycle of innovation and you see, you know, Kafka having emerged and now pulse are emerging as sort of a, a newer, more cloud friendly version of Kafka and flank kind of emerging as potentially a successor to spark that cycle of innovation, arguably is accelerating. >>Um, and so as you think about what's, you know, what's unique to us as a company, um, it's the data you have, right? No one has the customer interactions. You have, nobody has a business processes you have. So what you want to do is take those best of breed tools and have flexibility about the infrastructure services to support them and focus your people on doing great things with the data. So don't try to solve a problem that the open source ecosystem has already solved, right? If you're, if you're writing that code, instead of focusing on what differentiates your business, that's a miss. Um, so when you see the leaders leaning hard into, um, open source, you know, it's because they've got the clarity about, we differentiate by using these best of breed tools on our data, not reinventing the wheel, >>Are these companies, you mentioned culture a minute ago, and that's always something that I find intriguing because it's very hard to change. We've been in the last 16, 18 months in an, in a very fast pace of change, as we know, but are you seeing these data leaders that are companies that are reorienting towards a data culture where data is part of everyone's job? >>Yeah, absolutely. Absolutely. So they, so it's interesting. Um, a majority of all companies said that reacting to the COVID crisis did increase their pace of innovation, but again, it's almost universal among, among those leaders. Um, and one of the patterns that stands out is indeed, when you say making it everyone's job, I'll put finer point on it. It's saying accountability for creating value, generating revenue with data is the line of business is accountability. I'm in conversations. I've literally had CEOs say, it's not my problem anymore. It's my problem to help them execute on the ideas, right? And that can even raise the bar because now they're coming up with bolder, bigger ideas, but it's not about it being the custodians of the data, trying to go to the business and say, Hey, could you use some data it's business, general managers, VPs now accountable for how have you used data to drive revenue? >>How can it change the way you sell or the way you service customers? Um, and so on. And, and that, um, in part, what we heard from some folks was in organizations with progressive CEOs, chief data officers, they have been going to the side to the business side of things and saying, Hey, I think we've got ways to do business better, but there wasn't pressure on the business. They're like our business is going fine. Uh, but once COVID hit, it was okay. We need to take out costs. We need to find new ways to grow. Um, and there's sort of that that drove and organic embrace of, ah, I see, I want to pick up the reins and, you know, work with my technology partners to make it happen, but now I see we should be driving it on the business side. >>And have you seen in the COVID era data strategy become really a board level initiative and, and to your point, one of the things that you've found is, is it's not just the culture of data being core to everyone's job, it's the accountability level at the line of business level. But I imagine that that data strategy is indeed a board level initiative. >>That's right. That's the biggest, when you mentioned culture, the biggest of the segments is a group whose biggest challenge is cultural change about almost a third of, of all organizations. Um, and you see there, there's this big drop, you know, compared to the leaders of whether the data strategy is a board level discussion, right. And you see this big drop in other metrics where, you know, do you have a data strategy, mild agreement like, oh yeah, we talk about data of everybody talks about data. Um, but it's really about getting that top down. This is a true corporate priority, which kind of circles back to our initial conversation, you know, if the goal is 20% or more of your revenue from data, it better be a board level conversation. Right. And, and, you know, if you have an effective board, you want the board to be helping to drive toward that. Um, so it really closes the loop on, you know, again, calibrating, what's our aspiration, um, what's at stake. And if we believe in the data, you know, we shouldn't be hesitating to elevate this to the board level and get their attention on >>It. Right. Give me an example of a, of a customer that's doing that. That's a data leader that's doing this really well. And one that pivoted to be able to, to use data and extract value and revenue from it during the last year and a half, >>I would say it's a little bit less of a pivot and more of an amazing success story. Um, uh, because of you look backwards a few years ago, um, home Depot made a significant board level, you know, top-down, company-wide commitment to a very bold digital and data strategy. And so, you know, by 2019, um, for one example, you know, Forester ranked them as a top retail app, um, uh, for customers, um, and all that work, which is already paying off, right. They're making big investments, but they're getting big payoffs. Um, when COVID hits home, Depot is able to deploy curbside delivery as a service. They did not have a feature they did not have in weeks at scale, um, which drove even more outsized returns during COVID. Um, and so it's, it's a little, uh, you know, it's a less of a pivot, but more about the value of making that commitment. >>Um, because you know, they, weren't planning on deploying curbside delivery to the app in weeks, but when COVID hit, they were able to, because they already had the cultural change, the infrastructure, the metrics, the technologies in place. Um, and so, you know, it's really a message about don't wait, right? If you are going to fast follow, if you are going to be away for proven best practices, you don't want to start off the blocks at zero. When something disruptive happens, you want to have some success stories, some practice at it under your belt. So, you know, even if you're, if you're, if you're fortunate enough not to have been pushed into radical action because of COVID, don't, don't let that stop you from seizing the day and actually starting to move. >>I now I've, I think I'll never have the same opinion of, of home Depot. Again, I will always go on there looking for light bulbs and batteries and flashlights thinking of them as a data company, but as a company, that, to your point, committed to it and push that accountability out into those lines of business. How does, what did the survey show in terms of those data leaders embracing, uh, open source, embracing a hybrid data strategy? How does that facilitate that, driving that accountability into the lines of business so that that revenue that's sitting on the table from data can be unpacked. >>Yeah, it's, it's almost, I think, you know, if I look at it from the technology side, um, imagine, you know, in the past, you're the custodian of data, you know, as a CIO and your job is to kind of make, make, make, you know, data's not lost. We comply with regulations, you know, for the kind of way we run the business yesterday and today doesn't break tomorrow. And so if I think about the shifts to where the lines of business are now accountable for finding new ways to use data, what are the, to come up with? Like, you know, if you think about like, you know, innovating in business, um, taking data under the wing, right? Your job now, as a manager is innovate, innovate your business model, deliver something we never delivered before deliver something. No one in our industry delivers. So on the tech side, you know, it should be exciting, but it also means you may be on the hook for delivering some capability that your company had never thought about. >>Um, so that really gets back to this idea of like, do you have access to, you know, the best infrastructure services through hybrid cloud and data strategy? Are you set up to use best of breed tools, even if, you know, last year we didn't have a scenario that uses best of breed tools. Well, now that the businesses, I think it really hard on how we differentiate with data. They're probably going to come up with some big bold ideas, um, again, which should be exciting, but you gotta be ready to invest in change and something new as opposed to keeping the lights on. >>Right. I think that pace of innovation, I don't know, maybe it's permanently altered because of the scenario was one that nobody ever expected to be in. As we saw so much transformation in the last year and a half, and the pace of innovation change and, and the, you know, the places that are like the home Depot being able to radically change so quickly. And so we saw a lot of other businesses that could not do that. What are some of the market trends that you're seeing as we're now coming around the corner into the second half of 2021? >>I mean, the acceleration is a great point because when you're using data to deliver value to customers or create value for your business, things actually build on them on each other. Right. So, you know, data doesn't get used up until the, the amazing things about digital data. It can be used and reuse and recombined. So if you saw, for example, you know, leaders are well on the way before COVID, do you have real time inventory we'll share. Uh, but then once COVID hit, do you have real time inventory? And can you make a recommendation for somebody that's out of stock became like, wow, we should get that done ASAP. So then as you see folks do some necessary things, um, you start to see, well, if we've got real-time inventory and we can make recommendations, why are we getting a 360 degree view of the customer from that data plus marketing data, right? >>And now the value gets unlocked. Whereas if you said, you know, two years ago, how can we justify creating a 360 degree view of the customer, some organizations might've been like, well, we can, you know, it's hard to do. We can't see the value. Whereas once you're doing a couple of these use cases, it becomes obvious that they'd be better together. Right. And so, um, if you see, you know, the home Depot, I think you're going to see, um, you know, essentially every retailer that wants to stay competitive is going to follow in that path. >>Do you think that those companies that become data leaders or are on the path to become data leaders that have the hybrid data strategy that are embracing OpenStack? Is that mentality in your opinion, going to separate the winners and the losers going forward in the next year plus? >>Yeah, I mean, I think, I think in a sense it has to, uh, because again, as I think, you know, there was a trend already in place for all of us as consumers, right. We love, for example, delightful recommendations, you know, uh, companies and applications that know us and just make our lives better because they're smart, like Netflix and Spotify, right. The classic examples. Um, but now you think about for anything. So Cengage is an education platform company, and they talk about being the Netflix of education. Um, and you know, retailers like home Depot, like target have gotten super smart about things like recommendations. Um, and you know, in the case of home Depot, like connecting me with the data that explains how to do DIY projects and use the tools I'm trying to buy. So, you know, the bar just keeps getting raised to the point where, you know, you look at, you know, you look at a, the e-commerce site of the past, we just sort of a dumb e-commerce site where it's, I can pick things, put them in a cart and buy, you know, that's not acceptable by any stretch of the imagination today, right. >>Are there user reviews? Are there, you know, recommendations? We expect all of this. Um, and I think you'll see it, you know, obviously retail's heavily disrupted by COVID pointing into the sphere, so to speak, but I mean, telehealth is another example where, you know, I think the writing is on the wall. If you can't do telehealth as a health system or a hospital, you know, very soon you're going to have a big problem. >>Yeah. The consumer demand is incredible for, I want whatever it is, if it's I'm shopping on Amazon or if it's going to be, but I want them to know what to recommend to me next, based on what I just thought we have that expectation that the Netflix is and the Spotify is to your point have set. And we also have that expectation in our business life. So when folks are buying it, interacting with software, they want the same thing, right. It's not just limited to healthcare retailers. That's >>Right. And I that's that there's a virtuous cycle, right? If you think about companies, you know, making that cultural change, leaning into using data to make things better, it's not just for customers, it's for your employees, it's for your partners, it's for your business processes. Right. And how are you going to be able to hire people who are super excited about making things better for customers, if you're also not, you know, internally making things better for your employees, right. There's just a real disconnect in terms of, you know, culture and personnel. There. >>That's a great point. Those are in my opinion, inextricably linked, Brian, it's been great to have you on the program. Thank you for sharing with us. The state of the data raised very interesting sort of that you guys have done. Folks can get their hands on that lot of opportunity and a lot of money on the table for organizations in any industry. Thanks so much for joining me today, brand thank you for Brian Kirschner. I'm Lisa Martin. You're watching a cube conversation.
SUMMARY :
Talk to me, first of all, about the state of the data, So, you know, um, we are in a race for our to make the right progress. Talk to me about how this survey defines a data leader. you know, in the course of my work and my colleagues work, we talked with lots of CEOs, And you found that the data, those companies in the data leadership category were you know, again about that benchmarking where you are, where's your destination, Um, and that's giving these leaders, you know, a lot of agility control, flexibility, leaders that you talked about that are able to, or able to attribute more than that are, you know, have, have, you know, validated the massive impact data can have on Um, and so as you think about what's, you know, what's unique to us as a company, as we know, but are you seeing these data leaders that are companies that are reorienting that stands out is indeed, when you say making it everyone's job, How can it change the way you sell or the way you service customers? And have you seen in the COVID era data strategy become really a board Um, so it really closes the loop on, you know, again, calibrating, And one that pivoted to be able to, and so it's, it's a little, uh, you know, it's a less of a pivot, but more about the value of making Um, because you know, they, weren't planning on deploying curbside delivery to the app in of business so that that revenue that's sitting on the table from data can be unpacked. So on the tech side, you know, it should be exciting, Um, so that really gets back to this idea of like, do you have access to, you know, the places that are like the home Depot being able to radically change you know, leaders are well on the way before COVID, do you have real time inventory we'll share. And so, um, if you see, you know, the home Depot, I think you're going to see, Um, and you know, in the case of home Depot, like connecting you know, very soon you're going to have a big problem. if it's I'm shopping on Amazon or if it's going to be, but I want them to know what to recommend to me next, you know, internally making things better for your employees, right. Those are in my opinion, inextricably linked, Brian, it's been great to have you on the program.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Lisa Martin | PERSON | 0.99+ |
Brian Kirschner | PERSON | 0.99+ |
Bryan Kirschner | PERSON | 0.99+ |
20% | QUANTITY | 0.99+ |
DataStax | ORGANIZATION | 0.99+ |
Depot | ORGANIZATION | 0.99+ |
July 2021 | DATE | 0.99+ |
10% | QUANTITY | 0.99+ |
Brian | PERSON | 0.99+ |
two | QUANTITY | 0.99+ |
today | DATE | 0.99+ |
Apache | ORGANIZATION | 0.99+ |
tomorrow | DATE | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
360 degree | QUANTITY | 0.99+ |
Netflix | ORGANIZATION | 0.99+ |
2019 | DATE | 0.99+ |
yesterday | DATE | 0.99+ |
One | QUANTITY | 0.99+ |
bran Kirschner | PERSON | 0.99+ |
more than 20% | QUANTITY | 0.99+ |
two dimensions | QUANTITY | 0.99+ |
last year | DATE | 0.99+ |
home Depot | ORGANIZATION | 0.99+ |
twice | QUANTITY | 0.98+ |
Spotify | ORGANIZATION | 0.98+ |
next year | DATE | 0.98+ |
Cengage | ORGANIZATION | 0.98+ |
one example | QUANTITY | 0.98+ |
more than 20% | QUANTITY | 0.98+ |
last year and a half | DATE | 0.98+ |
Kafka | TITLE | 0.98+ |
Forester | ORGANIZATION | 0.97+ |
500 | QUANTITY | 0.97+ |
two years ago | DATE | 0.97+ |
one | QUANTITY | 0.95+ |
COVID crisis | EVENT | 0.93+ |
about 70 measures | QUANTITY | 0.92+ |
second half of 2021 | DATE | 0.9+ |
a minute ago | DATE | 0.89+ |
few years ago | DATE | 0.89+ |
COVID | OTHER | 0.89+ |
COVID | TITLE | 0.88+ |
first | QUANTITY | 0.82+ |
almost a hundred percent | QUANTITY | 0.74+ |
almost a hundred percent | QUANTITY | 0.74+ |
16 | QUANTITY | 0.74+ |
Almost a hundred percent | QUANTITY | 0.63+ |
zero | QUANTITY | 0.61+ |
vice president | PERSON | 0.59+ |
18 months | QUANTITY | 0.59+ |
OpenStack | ORGANIZATION | 0.58+ |
last | DATE | 0.58+ |
target | ORGANIZATION | 0.55+ |
home | ORGANIZATION | 0.52+ |
Cassandra Kafka | PERSON | 0.47+ |
third | QUANTITY | 0.45+ |
COVID | EVENT | 0.44+ |
Survey Data Shows no Slowdown in AWS & Cloud Momentum
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 despite all the chatter about cloud repatriation and the exorbitant cost of cloud computing customer spending momentum continues to accelerate in the post-isolation economy if the pandemic was good for the cloud it seems that the benefits of cloud migration remain lasting in the late stages of covid and beyond and we believe this stickiness is going to continue for quite some time we expect i asked revenue for the big four hyperscalers to surpass 115 billion dollars in 2021 moreover the strength of aws specifically as well as microsoft azure remain notable such large organizations showing elevated spending momentum as shown in the etr survey results is perhaps unprecedented in the technology sector hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll share some some fresh july survey data that indicates accelerating momentum for the largest cloud computing firms importantly not only is the momentum broad-based but it's also notable in key strategic sectors namely ai and database there seems to be no stopping the cloud momentum there's certainly plenty of buzz about the cloud tax so-called cloud tax but other than wildly assumptive valuation models and some pockets of anecdotal evidence you don't really see the supposed backlash impacting cloud momentum our forecast calls for the big four hyperscalers aws azure alibaba and gcp to surpass 115 billion as we said in is revenue this year the latest etr survey results show that aws lambda has retaken the lead among all major cloud services tracked in the data set as measured in spending momentum this is the service with the most elevated scores azure overall azure functions vmware cloud on aws and aws overall also demonstrate very highly elevated performance all above that of gcp now impressively aws momentum in the all-important fortune 500 where it has always showed strength is also accelerating one concern in the most recent survey data is that the on-prem clouds and so-called hybrid platforms which we had previously reported as showing an upward spending trajectory seem to have cooled off a bit but the data is mixed and it's a little bit too early to draw firm conclusions nonetheless while hyperscalers are holding steady the spending data appears to be somewhat tepid for the on-prem players you know particularly for their cloud we'll study that further after etr drops its full results on july 23rd now turning our attention back to aws the aws cloud is showing strength across its entire portfolio and we're going to show you that shortly in particular we see notable strength relative to others in analytics ai and the all-important database category aurora and redshift are particularly strong but several other aws database services are showing elevated spending velocity which we'll quantify in a moment all that said snowflake continues to lead all database suppliers in spending momentum by a wide margin which again will quantify in this episode but before we dig into the survey let's take a look at our latest projections for the big four hyperscalers in is as you know we track quarterly revenues for the hyperscalers remember aws and alibaba ias data is pretty clean and reported in their respective earnings reports azure and gcp we have to extrapolate and strip out all a lot of the the apps and other certain revenue to make an apples-to-apples comparison with aws and alibaba and as you can see we have the 2021 market exceeding 115 billion dollars worldwide that's a torrid 35 growth rate on top of 41 in 2020 relative to 2019. aggressive yes but the data continues to point us in this direction until we see some clearer headwinds for the cloud players this is the call we're making aws is perhaps losing a sharepoint or so but it's also is so large that its annual incremental revenue is comparable to alibaba's and google's respective cloud business in total is business in total the big three u.s cloud companies all report at the end of july while alibaba is mid mid-august so we'll update these figures at that time okay let's move on and dig into the survey data we don't have the data yet on alibaba and we're limited as to what we can share until etr drops its research update on on the 23rd but here's a look at the net score timeline in the fortune 500 specifically so we filter the fortune 500 for cloud computing you got azure and the yellow aws and the black and gcp in blue so two points here stand out first is that aws and microsoft are converging and remember the customers who respond to the survey they probably include a fair amount of application software spending in their cloud answers so it favors microsoft in that respect and gcp second point is showing notable deceleration relative to the two leaders and the green call out is because this cut is from an aws point of view so in other words gcp declines are a positive for aws so that's how it should be interpreted now let's take a moment to better understand the idea of net score this is one of the fundamental metrics of the etr methodology here's the data for aws so we use that as a as a reference point net score is calculated by asking customers if they're adding a platform new that's the lime green bar that you see here in the current survey they're asking are you spending six percent or more in the second half relative to the first half of the year that's the forest green they're also asking is spending flat that's the gray or are you spending less that's the pink or are you replacing the platform i.e repatriating so not much spending going on in replacements now in fairness one percent of aws is half a billion dollars so i can see where some folks would get excited about that but in the grand scheme of things it's a sliver so again we don't see repatriation in the numbers okay back to net score subtract the reds from the greens and you get net score which in the case of aws is 61 now just for reference my personal subjective elevated net score level is 40 so anything above that is really impressive based on my experience and to have a company of this size be so elevated is meaningful same for microsoft by the way which is consistently well above the 50 mark in net score in the etr surveys so that's you can think about it that's even more impressive perhaps than aws because it's triple the revenue okay let's stay with aws and take a look at the portfolio and the strength across the board this chart shows net score for the past three surveys serverless is on fire by the way not just aws but azure and gcp functions as well but look at the aws portfolio every category is well above the 40 percent elevated red line the only exception is chime and even chime is showing an uptick and chime is meh if you've ever used chime every other category is well above 50 percent next net score very very strong for aws now as we've frequently reported ai is one of the four biggest focus areas from a spending standpoint along with cloud containers and rpa so it stands to reason that the company with the best ai and ml and the greatest momentum in that space has an advantage because ai is being embedded into apps data processes machines everywhere this chart compares the ai players on two dimensions net score on the vertical axis and market share or presence in the data set on the horizontal axis for companies with more than 15 citations in the survey aws has the highest net score and what's notable is the presence on the horizontal axis databricks is a company where high on also shows elevated scores above both google and microsoft who are showing strength in their own right and then you can see data iq data robot anaconda and salesforce with einstein all above that 40 percent mark and then below you can see the position of sap with leonardo ibm watson and oracle which is well below the 40 line all right let's look at at the all-important database category for a moment and we'll first take a look at the aws database portfolio this chart shows the database services in aws's arsenal and breaks down the net score components with the total net score superimposed on top of the bars point one is aurora is highly elevated with a net score above 70 percent that's due to heavy new adoptions redshift is also very strong as are virtually all aws database offerings with the exception of neptune which is the graph database rds dynamodb elastic document db time stream and quantum ledger database all show momentum above that all important 40 line so while a lot of people criticize the fragmentation of the aws data portfolio and their right tool for the right job approach the spending spending metrics tell a story and that that the strategy is working now let's take a look at the microsoft database portfolio there's a story here similar similar to that of aws azure sql and cosmos db microsoft's nosql distributed database are both very highly elevated as are azure database for mysql and mariadb azure cash for redis and azure for cassandra also microsoft is giving look at microsoft's giving customers a lot of options which is kind of interesting you know we've often said that oracle's strategy because we think about oracle they're building the oracle database cloud we've said oracle strategy should be to not just be the cloud for oracle databases but be the cloud for all databases i mean oracle's got a lot of specialty capability there but it looks like microsoft is beating oracle to that punch not that oracle is necessarily going there but we think it should to expand the appeal of its cloud okay last data chart that we'll show and then and then this one looks at database disruption the chart shows how the cloud database companies are doing in ibm oracle teradata in cloudera accounts the bars show the net score granularity as we described earlier and the etr callouts are interesting so first remember this is an aws this is in an aws context so with 47 responses etr rightly indicates that aws is very well positioned in these accounts with the 68 net score but look at snowflake it has an 81 percent net score which is just incredible and you can see google database is also very strong and the high 50 percent range while microsoft even though it's above the 40 percent mark is noticeably lower than the others as is mongodb with presumably atlas which is surprisingly low frankly but back to snowflake so the etr callout stresses that snowflake doesn't have a strong as strong a presence in the legacy database vendor accounts yet now i'm not sure i would put cloudair in the legacy database category but okay whatever cloudera they're positioning cdp is a hybrid platform as are all the on-prem players with their respective products and platforms but it's going to be interesting to see because snowflake has flat out said it's not straddling the cloud and on-prem rather it's all in on cloud but there is a big opportunity to connect on-prem to the cloud and across clouds which snowflake is pursuing that that ladder the cross-cloud the multi-cloud and snowflake is betting on incremental use cases that involve data sharing and federated governance while traditional players they're protecting their turf at the same time trying to compete in cloud native and of course across cloud i think there's room for both but clearly as we've shown cloud has the spending velocity and a tailwind at its back and aws along with microsoft seem to be getting stronger especially in the all-important categories related to machine intelligence ai and database now to be an essential infrastructure technology player in the data era it would seem obvious that you have to have database and or data management intellectual property in your portfolio or you're going to be less valuable to customers and investors okay we're going to leave it there for today remember these episodes they're all available as podcasts wherever you listen all you do is search breaking analysis podcast and please subscribe to the series check out etr's website at etr dot plus plus etr plus we also publish a full report every week on wikibon.com and siliconangle.com you can get in touch with me david.velante at siliconangle.com you can dm me at d vallante or you can hit hit me up on our linkedin post this is dave vellante for the cube insights powered by etr have a great week stay safe be well and we'll see you next time you
SUMMARY :
that the company with the best ai and ml
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
alibaba | ORGANIZATION | 0.99+ |
six percent | QUANTITY | 0.99+ |
81 percent | QUANTITY | 0.99+ |
2020 | DATE | 0.99+ |
2021 | DATE | 0.99+ |
2019 | DATE | 0.99+ |
40 percent | QUANTITY | 0.99+ |
july 23rd | DATE | 0.99+ |
microsoft | ORGANIZATION | 0.99+ |
115 billion | QUANTITY | 0.99+ |
dave vellante | PERSON | 0.99+ |
50 percent | QUANTITY | 0.99+ |
41 | QUANTITY | 0.99+ |
61 | QUANTITY | 0.99+ |
47 responses | QUANTITY | 0.99+ |
boston | LOCATION | 0.99+ |
one percent | QUANTITY | 0.99+ |
second half | QUANTITY | 0.99+ |
aws | ORGANIZATION | 0.99+ |
40 | QUANTITY | 0.99+ |
two leaders | QUANTITY | 0.99+ |
second point | QUANTITY | 0.99+ |
115 billion dollars | QUANTITY | 0.99+ |
first | QUANTITY | 0.99+ |
half a billion dollars | QUANTITY | 0.99+ |
more than 15 citations | QUANTITY | 0.98+ |
mid mid-august | DATE | 0.98+ |
two points | QUANTITY | 0.98+ |
ORGANIZATION | 0.98+ | |
siliconangle.com | OTHER | 0.98+ |
end of july | DATE | 0.98+ |
david.velante | PERSON | 0.97+ |
july | DATE | 0.97+ |
50 | QUANTITY | 0.97+ |
40 percent | QUANTITY | 0.97+ |
this year | DATE | 0.97+ |
both | QUANTITY | 0.96+ |
oracle | ORGANIZATION | 0.95+ |
sql | TITLE | 0.95+ |
mysql | TITLE | 0.95+ |
first half | QUANTITY | 0.95+ |
palo alto | ORGANIZATION | 0.95+ |
pandemic | EVENT | 0.95+ |
35 | QUANTITY | 0.94+ |
this week | DATE | 0.93+ |
etr | ORGANIZATION | 0.93+ |
four biggest focus areas | QUANTITY | 0.91+ |
aws azure | ORGANIZATION | 0.91+ |
azure | ORGANIZATION | 0.91+ |
one | QUANTITY | 0.91+ |
23rd | DATE | 0.9+ |
40 line | QUANTITY | 0.89+ |
Pure Storage Convergence of File and Object FULL SHOW V1
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
SUMMARY :
on the nfs side um but you know we
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
garrett belsner | PERSON | 0.99+ |
matt burr | PERSON | 0.99+ |
2010 | DATE | 0.99+ |
2050 | DATE | 0.99+ |
270 terabytes | QUANTITY | 0.99+ |
seven days | QUANTITY | 0.99+ |
2021 | DATE | 0.99+ |
scott sinclair | PERSON | 0.99+ |
2035 | DATE | 0.99+ |
2019 | DATE | 0.99+ |
four | QUANTITY | 0.99+ |
three | QUANTITY | 0.99+ |
two seconds | QUANTITY | 0.99+ |
2025 | DATE | 0.99+ |
matt burr | PERSON | 0.99+ |
first phase | QUANTITY | 0.99+ |
dave | PERSON | 0.99+ |
dave vellante | PERSON | 0.99+ |
scott sinclair | PERSON | 0.99+ |
five | QUANTITY | 0.99+ |
250 terabytes | QUANTITY | 0.99+ |
10 terabyte | QUANTITY | 0.99+ |
zero percent | QUANTITY | 0.99+ |
100 | QUANTITY | 0.99+ |
steve | PERSON | 0.99+ |
gary | PERSON | 0.99+ |
two billion dollar | QUANTITY | 0.99+ |
garrett | PERSON | 0.99+ |
two minutes | QUANTITY | 0.99+ |
two weeks later | DATE | 0.99+ |
three topics | QUANTITY | 0.99+ |
two sides | QUANTITY | 0.99+ |
two weeks ago | DATE | 0.99+ |
billion dollars | QUANTITY | 0.99+ |
mid-decade 80 | DATE | 0.99+ |
today | DATE | 0.99+ |
cdw | PERSON | 0.98+ |
three phases | QUANTITY | 0.98+ |
80 | QUANTITY | 0.98+ |
billions of objects | QUANTITY | 0.98+ |
10 month | QUANTITY | 0.98+ |
one device | QUANTITY | 0.98+ |
an hour | QUANTITY | 0.98+ |
one platform | QUANTITY | 0.98+ |
scott | ORGANIZATION | 0.97+ |
last year | DATE | 0.97+ |
five petabyte | QUANTITY | 0.97+ |
scott | PERSON | 0.97+ |
cassandra | PERSON | 0.97+ |
one | QUANTITY | 0.97+ |
single block | QUANTITY | 0.97+ |
one system | QUANTITY | 0.97+ |
next decade | DATE | 0.96+ |
tons of places | QUANTITY | 0.96+ |
both worlds | QUANTITY | 0.96+ |
vertica | TITLE | 0.96+ |
matt | PERSON | 0.96+ |
both | QUANTITY | 0.96+ |
69 of organizations | QUANTITY | 0.96+ |
billion dollars | QUANTITY | 0.95+ |
pandemic | EVENT | 0.95+ |
first | QUANTITY | 0.95+ |
three great guests | QUANTITY | 0.95+ |
next year | DATE | 0.95+ |
Matt Burr, General Manager, FlashBlade, Pure Storage | The Convergence of File and Object
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]
SUMMARY :
i need to have um you know fast daz
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
2010 | DATE | 0.99+ |
Matt Burr | PERSON | 0.99+ |
250 terabytes | QUANTITY | 0.99+ |
270 terabytes | QUANTITY | 0.99+ |
2025 | DATE | 0.99+ |
three | QUANTITY | 0.99+ |
four | QUANTITY | 0.99+ |
matt burr | PERSON | 0.99+ |
today | DATE | 0.99+ |
billion dollars | QUANTITY | 0.98+ |
two levels | QUANTITY | 0.98+ |
billions of objects | QUANTITY | 0.98+ |
two weeks later | DATE | 0.98+ |
80 | QUANTITY | 0.98+ |
two weeks ago | DATE | 0.98+ |
one system | QUANTITY | 0.98+ |
an hour | QUANTITY | 0.97+ |
cassandra | PERSON | 0.97+ |
matt | PERSON | 0.97+ |
next year | DATE | 0.96+ |
billions of objects | QUANTITY | 0.96+ |
dave | PERSON | 0.96+ |
one device | QUANTITY | 0.96+ |
both | QUANTITY | 0.96+ |
first principles | QUANTITY | 0.93+ |
second half | QUANTITY | 0.93+ |
billion dollar | QUANTITY | 0.91+ |
petabyte | QUANTITY | 0.9+ |
four different siloed infrastructures | QUANTITY | 0.89+ |
two billion dollar | QUANTITY | 0.89+ |
one place | QUANTITY | 0.89+ |
next couple years | DATE | 0.88+ |
80 of data | QUANTITY | 0.88+ |
early second half of this decade | DATE | 0.87+ |
20 storage people | QUANTITY | 0.86+ |
four different things | QUANTITY | 0.86+ |
five refrigerators | QUANTITY | 0.86+ |
one | QUANTITY | 0.84+ |
oracle sql | TITLE | 0.81+ |
one full-time | QUANTITY | 0.8+ |
wikibon | ORGANIZATION | 0.79+ |
four different places | QUANTITY | 0.79+ |
first | QUANTITY | 0.79+ |
3x | QUANTITY | 0.78+ |
a lot of people | QUANTITY | 0.78+ |
FlashBlade | ORGANIZATION | 0.78+ |
end of quarter | DATE | 0.77+ |
a couple minutes | QUANTITY | 0.77+ |
two sort | QUANTITY | 0.75+ |
isilon | ORGANIZATION | 0.74+ |
s3 | TITLE | 0.74+ |
three part | QUANTITY | 0.72+ |
100 of | QUANTITY | 0.7+ |
terabyte | QUANTITY | 0.7+ |
three legs | QUANTITY | 0.68+ |
two | QUANTITY | 0.68+ |
multiple petabytes | QUANTITY | 0.68+ |
vice president | PERSON | 0.65+ |
many years | QUANTITY | 0.61+ |
flashblade | ORGANIZATION | 0.57+ |
many companies | QUANTITY | 0.56+ |
tons | QUANTITY | 0.55+ |
gartner | ORGANIZATION | 0.53+ |
General Manager | PERSON | 0.53+ |
multi | QUANTITY | 0.51+ |
general manager | PERSON | 0.45+ |
Pure | ORGANIZATION | 0.34+ |
Mai Lan Tomsen Bukovec, AWS | theCUBE on Cloud 2021
>>from around the globe. It's the Cube presenting Cuban cloud brought to you by silicon angle. >>We continue >>with Cuban Cloud. We're here with Milan Thompson Bukovec, who's the vice president? Block and object storage at A W s, which comprise comprises elastic block storage, AWS s three and Amazon Glacier. Milan. Great to see you again. Thanks so much for coming on the program. >>Nice to be here. Thanks for having me, David. >>You're very welcome it So here we are. 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 in the Cloud is obviously started with us three. And then a couple years later was introduced CBS for block storage. And those are the most well known services in the portfolio. But there's there's Mawr, this cold storage and new capabilities that you announced recently. It reinvent around, you know, super duper block storage and in tearing 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 air 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 orderto have that insight in orderto 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 have been a backup. Now it's part of a data lake, and if you could 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 wanna I wanna make sure we're hitting on the big trends that you're seeing in the market. That kind of informing your strategy around the portfolio and what you're seeing with customers Instant usability. You you bring in machine learning into the equation. I think, um, people have really started to understand the benefits of of of cloud storage as a service on the pay paid by the drink and that whole whole model, obviously co vid has accelerated that cloud migration has 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 I. D. C. 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 gonna keep on growing because the sources of that data acquisition keeps on expanding and whether it's coyote devices whether it is 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 becomes bromide. But I think the interesting thing that I've observed over the last a couple of decades really is that the growth is nonlinear on. It's really the curve is starting. Thio used to shape exponentially. You guys always talk about that flywheel. Effect it. 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 the world of AWS storage Dave is that it's counterintuitive. But our goal without data growth is to make it cost effective. And so year over year, how could we make it cheaper and cheaper? Just 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 that? Eyes 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 my life could I get asked this a lot? Or guy here comments a lot that yes, A W s continuously and rigorously reduces pricing. But it's just >>kind of >>following the natural curve of Moore's law or, you know, whatever. How >>do you >>respond to that? And there are other factors involved. Obviously, labor is another cost reducing factor. But what's the trend line say, >>Well, cost efficiencies in our DNA, Dave. We come to work every day and 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 cost. There's the cost of the storage itself is the cost of the data center. And that's really what we've seen impact a lot of customers that were slower or just getting started with removed. 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 won't show up until you really don't need to have it land. But the cost of managing that explosive growth of data is very riel. And when we're thinking about cost, we're thinking about cost 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 S three that's called intelligent hearing. And in intelligence hearing, we have built in monitoring where, if particular objects aren't frequently accessed in a given month, ah, customer will automatically get a discounted price for that storage or a customer Can you know, as of late last year, say that they wanna automatically move storage in the storage class that has been stored, for example, longer than 100 and 80 days and saves 95% by moving it into archive storage, deep archives 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 adaptive Lee discount storage based on what a customer's storage is actually doing >>well. And I would, I would add to our audience, is the other thing that does has done is it's really forced transparency almost the same way that Amazon has done on retail. And now my mom, When we talked last I mentioned that s three was an object store. And of course, that's technically technically correct. But your comment to me was Dave. It's more than that. And you started to talk about sage Maker and AI and bringing in machine learning. And I wonder if you could talk a little bit about the future of how storage is gonna be leveraged in the cloud that's may be different than what we've been, you know, used to in the early days of s three 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 adjacent services that you see as most leverage a ble for customers And why? >>Well, to tell this story, dude, we're gonna have to go a little bit back in time all the way back to the 19 nineties. Or before then, when all you had waas, 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 er of that legacy world is tied to a data silo and s tree came out launched in 2000 and six 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 come into us three, whereas before it might have been backups or it might have been images and videos. Now a pretty substantial data set is our parquet files and orc files. Thes 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 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, Jim Octagon E. She's amazing, uh, data architect, and she's put forth this notion of a distributed global mesh, and I picked him picking up on some of the comments. Andy Jassy made it at reinvent How essentially Hey, we're bringing a W s to the edge. We see the data center is just another edge. Notes. 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 into it monolithic Data Lake or a data warehouse on bits 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 taken example of the type of data that you always wanna have on the edge. We have customers today that need tohave storage in the field and whether the field of scientific research or oftentimes, it's content creation in the 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 Snowball and whether it's snowball 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 it 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 interactive, 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 air 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, this is sort of age old dynamic in the tech business, where you've got the friction between the the best of breed and the integrated suite, and my question is around what you're optimizing for for customers. And can you have your cake and eat it too? In other words, why A W S storage does what makes a compelling? Is it because it's kind of a best of breed storage service? Or is it because it's integrated with a W S? Would you ever sub optimize one in 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 breath of capabilities on the depth of capabilities. And so where we identify ah, particular need where we think that it takes a whole new service to deliver, we'll go build that service and example for that is 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 B two b type of architectures that still live in the business world today. And so we looked at that problem. We said, How are we gonna build that in the best depth way and the best focus? And we launched a separate service for them. And so our goal is to take the individual building blocks of CBS and Glacier and s three and make the best of class and the most comprehensive in the capabilities of what we can dio and where we identify very specific need. We'll go build a service for. But, Dave, you know, as an example for that idea of both depths and breath s three storage lands is a great example of that s three storage lands is a new capability that we launched 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 s three storage and whether that's buckets or, you know, the most active prefixes that you have and be able to drill down from that and that is built in to the S three service and available for any customer that wants to turn it on in the AWS Management Council. >>Right? And we we saw just recently made I called it super duper block storage. But you made some, you know, improvements and really addressing the highest performance. Um, I want to ask you So we've all learned about an experience the 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 bio is, of course, Leighton see and moving data around and accessing data remotely. It's It's a challenge for customers, you know, due to speed of light, etcetera. So my question is, how was a W s thinking about all that data that still resides on premises? I think we heard that reinvent. That's still 90% of the opportunities or or the workloads. They're still on Prem that live inside a customer's data center. 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 Leighton see workloads, and that's why we launched Block Express just late last year. It reinvent and Black expresses a new capability and preview on top of our Iot to provisioned eye ops 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 Lehrer, we built a Block Express on something called SRD, which stands for a scalable, reliable diagrams. And basically, what is letting us to do is offload all of our EBS operations for Block Express on the Nitro card on hardware. And so that type of innovation where we're able Thio, 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 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 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 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 built outposts. And for outpost, we have EBS and we have s three 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 in sand in the cloud eso Is that essentially you've you've comprises a custom built, essentially storage storage network. Is that is that right? What kind of what you just described? SRD? I think you call it. >>Yeah, it's SRT is used by other AWS services as well, but it is a custom network protocol that we designed to deliver the lowest latency experience on We're taking advantage of it with Block Express >>sticking with traditional data centers for a moment, I'm interested in your thoughts on the importance of the cloud you know, pricing approach I e. The consumption model to paid by the drink. Obviously, it's one of the most attractive features But But And I ask that because we're seeing what Andy Jassy first, who is the old Guard Institute? Flexible pricing models. Two of the biggest storage companies HP with Green Lake and Dell has this thing called Apex. They've announced such models for on Prem and 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 ah, opinion on? >>Yeah, I think it all comes down to again that usage of the storage And this is where I think there is an inherent advantage for our cloud storage. So there might be an attempt by the old guard toe lower prices or add flexibility. But the end of the day it comes down to what the customer actually needs to to. And if you think about gp three, which is the new E. B s volume, the idea with GP three is we're gonna pass along savings to the customer by making the storage 20% cheaper than GP two. And we're gonna make the product better by giving a great, reliable baseline performance. But we're also going to let customers who want to run work clothes like Cassandra on TBS 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 were quote 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 in 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 IOP, separate from capacity like you do for GP three. 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 another time we have remaining my line. I want to talk about the topic of diversity. Uh, social impact on Daz. Ah, woman leader, women executive on. I really wanna get your perspectives on this, and I've shared with the audience previously. One of my breaking analysis segments your your boxing video, which is awesome and eso so you've got a lot of unique, non traditional aspects to your to your life, and 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 that that diversity is good both economically, not just socially. And of course, it's the right thing to do. But there are those. Peter Thiel is probably the most prominent, but there are others who say, You know what, >>But >>get that. Just hire people just like you will be able to go faster, ramp up more quickly, hit escape velocity. It's natural. And that's what you should dio. Why is that not the right approach? Why is diversity both course socially responsible, but also good for business? >>For Amazon, we think about diversity as something that is essential toe how we think about innovation. And so, Dave, you know, as you know, from listening to some of the announcements I reinvent, we launched a lot of new ideas, new concepts and new services in AWS and just bringing that lends down to storage U. S. Tree has been reinventing itself every year since we launched in 2000 and six. PBS introduced the first Son on the Cloud late last year and continues to reinvent how customers think about block storage. We would not be able Thio. Look at a product in a different way and think to ourselves Not just what is the legacy system dio 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 underrepresented groups and whether that's gender or it's related racial equality or if its geographic, uh, diversity and bringing them in tow have the conversation. Because those divers viewpoints inform how we can innovate at all levels in a W s >>right. And so I really appreciate the perspectives on that, and we've had a zoo. 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 you know, I often ask this question is, you know, as a smaller company, uh, I and some of my other colleagues in in small business Sometimes we struggle. Um and so my question is, how >>how do >>you go beyond What's your advice for going beyond, you know, the good old boys network? I think its large companies like AWS and the big players you've got a responsibility to that. You can put somebody in charge and make it you know, their full time job. How should smaller companies, um, that are largely white, male dominated? How should they become more diverse? What should they do? Thio increase that diversity? >>Well, I think the place to start his voice. A lot of what we try to dio is make sure that the underrepresented 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 a simple as being in a meeting and looking around that table, we're 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 underrepresented, a group or its ah woman whose early career or it's it's not. It's just a member of your team who happens to be a white male to who's not being hurt. 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 asked toe, have everyone's voice at the table, toe listen and to weigh in on it. So I think that is something everyone should dio. I think if you are a member of an underrepresented groups, as for example, I'm Vietnamese American and I'm the female in Tech. I think it z 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 it at reinvent. We had a great discussion with a group of women CEOs, and a lot of it we talked about is being bolt, 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 underrepresented groups, because sometimes Dave, that bold step that you kind of think of is 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. 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 hasn't heard or seen as much how you can take those bold challenges and step forward and learn, maybe fell also because that's how you learn. Then that is a way toe. Also have people learn and develop and become leaders in whatever industry it ISS. It's >>great advice, and I reminds me of, I mean, I think most of us can relate to that my land, 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 calling those folks that are. Maybe it's not diversity of gender or, you know, our or race. And maybe it's just the underrepresented. 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. Appreciate it. And, uh hey, listen, thanks so much for coming on the Cuban cloud. Uh, we're out of time and 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, everybody. You're watching the cube on cloud right back.
SUMMARY :
cloud brought to you by silicon angle. Great to see you again. Nice to be here. capabilities that you announced recently. So my first question is, how should we think about this expanding portfolio? and if you could bring that data into a data lake, you can have not just analytics or What are the other big trends that you see if any? And it's not going to stop. that I've observed over the last a couple of decades really is that the growth is nonlinear And so year over year, how could we make it cheaper and cheaper? you a follow up question on that my life could I get asked this a lot? following the natural curve of Moore's law or, you know, And there are other factors involved. And so it's not just, you know, relentlessly going after And I wonder if you could talk a little bit about the future of how storage is gonna be leveraged in the cloud that's that you put in your data center and inherently created a data silo because those hardware We see the data center is just another And so it you know, if you think about the need And can you have your cake and eat it too? And what it does is it lets you look across all your regions and all your you know, improvements and really addressing the highest performance. It's It's a challenge for customers, you know, And at the network Lehrer, we built a Block Express on something called SRD, What kind of what you just described? Two of the biggest storage companies HP with Green Lake and Dell has this thing called Apex. But the end of the day it comes down to what the customer actually Thank you for that. And of course, it's the right thing to do. And that's what you should dio. Dave, you know, as you know, from listening to some of the announcements I reinvent, we launched a lot You probably know the Cube has been, you know, a very big advocate of diversity, You can put somebody in charge and make it you know, their full time job. And so if you can internalize as a member And maybe it's just the underrepresented. And keep it right, everybody.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave | PERSON | 0.99+ |
David | PERSON | 0.99+ |
Andy Jassy | PERSON | 0.99+ |
Dell | ORGANIZATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
PBS | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
HP | ORGANIZATION | 0.99+ |
90% | QUANTITY | 0.99+ |
Two | QUANTITY | 0.99+ |
40% | QUANTITY | 0.99+ |
Peter Thiel | PERSON | 0.99+ |
five | QUANTITY | 0.99+ |
20% | QUANTITY | 0.99+ |
six years | QUANTITY | 0.99+ |
2020 | DATE | 0.99+ |
2000 | DATE | 0.99+ |
last year | DATE | 0.99+ |
first question | QUANTITY | 0.99+ |
Green Lake | ORGANIZATION | 0.99+ |
95% | QUANTITY | 0.99+ |
three | QUANTITY | 0.99+ |
80 days | QUANTITY | 0.99+ |
CBS | ORGANIZATION | 0.99+ |
10 years | QUANTITY | 0.99+ |
Apex | ORGANIZATION | 0.99+ |
both | QUANTITY | 0.99+ |
TBS | ORGANIZATION | 0.98+ |
Moore | PERSON | 0.98+ |
Mai Lan Tomsen Bukovec | PERSON | 0.98+ |
one | QUANTITY | 0.98+ |
Guard Institute | ORGANIZATION | 0.98+ |
19 nineties | DATE | 0.98+ |
20 years ago | DATE | 0.97+ |
late last year | DATE | 0.97+ |
longer than 100 | QUANTITY | 0.96+ |
late last year | DATE | 0.95+ |
One | QUANTITY | 0.95+ |
today | DATE | 0.95+ |
Cuban | OTHER | 0.94+ |
Milan Thompson Bukovec | PERSON | 0.94+ |
late last year | DATE | 0.94+ |
pandemic | EVENT | 0.94+ |
AWS Management Council | ORGANIZATION | 0.93+ |
a couple years later | DATE | 0.91+ |
Leighton | ORGANIZATION | 0.91+ |
last 10 months | DATE | 0.91+ |
EBS | ORGANIZATION | 0.9+ |
Jim Octagon E. | PERSON | 0.89+ |
first | QUANTITY | 0.89+ |
gp three | TITLE | 0.87+ |
Block Express | COMMERCIAL_ITEM | 0.87+ |
S. Tree | LOCATION | 0.86+ |
Cloud 2021 | TITLE | 0.85+ |
Mai Lan Tomsen Bukovec, Vice President, Block and Object Storage, AWS
>> 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)
SUMMARY :
Mai-Lan Great to see you again. Nice to be here. and the cloud has And so in order to have that insight in the market that kind of on the ability to not just it's really hard to believe, you know and make that easier than Obviously labor is another, you know, And so it's not just, you know And I wonder if you could talk And I expect that to in the future doing of data that you always And can you have your cake and eat it too? And that is built in to the S3 service and especially in the last is that the way that we're I think you called it. network protocol that we of the most attractive features, by the old guard to lower and of course it's the right thing to do. And so, Dave, as you know, from listening the cube has been, you know And it's one of the topics And by the way Great, thank you Dave. it right there buddy.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave | PERSON | 0.99+ |
Dell | ORGANIZATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
2006 | DATE | 0.99+ |
Andy Jassy | PERSON | 0.99+ |
HP | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
40% | QUANTITY | 0.99+ |
90% | QUANTITY | 0.99+ |
two | QUANTITY | 0.99+ |
EBS | ORGANIZATION | 0.99+ |
GreenLake | ORGANIZATION | 0.99+ |
20% | QUANTITY | 0.99+ |
Chamakh Tigani | PERSON | 0.99+ |
Mai Lan Tomsen Bukovec | PERSON | 0.99+ |
five | QUANTITY | 0.99+ |
first question | QUANTITY | 0.99+ |
95% | QUANTITY | 0.99+ |
IDC | ORGANIZATION | 0.99+ |
one | QUANTITY | 0.99+ |
six years | QUANTITY | 0.99+ |
Moore | PERSON | 0.99+ |
10 years | QUANTITY | 0.99+ |
2020 | DATE | 0.98+ |
1990s | DATE | 0.98+ |
S3 | TITLE | 0.98+ |
both | QUANTITY | 0.98+ |
gp2 | TITLE | 0.98+ |
gp3 | TITLE | 0.98+ |
late last year | DATE | 0.98+ |
20 years ago | DATE | 0.98+ |
longer than 180 days | QUANTITY | 0.97+ |
Mai-Lan Tomsen Bukovec | PERSON | 0.97+ |
pandemic | EVENT | 0.96+ |
today | DATE | 0.95+ |
Gatos | ORGANIZATION | 0.94+ |
block express | TITLE | 0.94+ |
EBS | TITLE | 0.94+ |
Mai-Lan | PERSON | 0.93+ |
Astri | ORGANIZATION | 0.92+ |
Reliance Jio: OpenStack for Mobile Telecom Services
>>Hi, everyone. My name is my uncle. My uncle Poor I worked with Geo reminds you in India. We call ourselves Geo Platforms. Now on. We've been recently in the news. You've raised a lot off funding from one of the largest, most of the largest tech companies in the world. And I'm here to talk about Geos Cloud Journey, Onda Mantis Partnership. I've titled it the story often, Underdog becoming the largest telecom company in India within four years, which is really special. And we're, of course, held by the cloud. So quick disclaimer. Right. The content shared here is only for informational purposes. Um, it's only for this event. And if you want to share it outside, especially on social media platforms, we need permission from Geo Platforms limited. Okay, quick intro about myself. I am a VP of engineering a geo. I lead the Cloud Services and Platforms team with NGO Andi. I mean the geo since the beginning, since it started, and I've seen our cloud footprint grow from a handful of their models to now eight large application data centers across three regions in India. And we'll talk about how we went here. All right, Let's give you an introduction on Geo, right? Giorgio is on how we became the largest telecom campaign, India within four years from 0 to 400 million subscribers. And I think there are There are a lot of events that defined Geo and that will give you an understanding off. How do you things and what you did to overcome massive problems in India. So the slide that I want to talkto is this one and, uh, I The headline I've given is, It's the Geo is the fastest growing tech company in the world, which is not a new understatement. It's eggs, actually, quite literally true, because very few companies in the world have grown from zero to 400 million subscribers within four years paying subscribers. And I consider Geo Geos growth in three phases, which I have shown on top. The first phase we'll talk about is how geo grew in the smartphone market in India, right? And what we did to, um to really disrupt the telecom space in India in that market. Then we'll talk about the feature phone phase in India and how Geo grew there in the future for market in India. and then we'll talk about what we're doing now, which we call the Geo Platforms phase. Right. So Geo is a default four g lt. Network. Right. So there's no to geo three g networks that Joe has, Um it's a state of the art four g lt voiceover lt Network and because it was designed fresh right without any two D and three G um, legacy technologies, there were also a lot of challenges Lawn geo when we were starting up. One of the main challenges waas that all the smart phones being sold in India NGOs launching right in 2000 and 16. They did not have the voice or lt chip set embedded in the smartphone because the chips it's far costlier to embed in smartphones and India is a very price and central market. So none of the manufacturers were embedding the four g will teach upset in the smartphones. But geos are on Lee a volte in network, right for the all the network. So we faced a massive problem where we said, Look there no smartphones that can support geo. So how will we grow Geo? So in order to solve that problem, we launched our own brand of smartphones called the Life um, smartphones. And those phones were really high value devices. So there were $50 and for $50 you get you You At that time, you got a four g B storage space. A nice big display for inch display. Dual cameras, Andi. Most importantly, they had volte chip sets embedded in them. Right? And that got us our initial customers the initial for the launch customers when we launched. But more importantly, what that enabled other oh, EMS. What that forced the audience to do is that they also had to launch similar smartphones competing smartphones with voltage upset embedded in the same price range. Right. So within a few months, 3 to 4 months, um, all the other way EMS, all the other smartphone manufacturers, the Samsung's the Micromax is Micromax in India, they all had volte smartphones out in the market, right? And I think that was one key step We took off, launching our own brand of smartphone life that helped us to overcome this problem that no smartphone had. We'll teach upsets in India and then in order. So when when we were launching there were about 13 telecom companies in India. It was a very crowded space on demand. In order to gain a foothold in that market, we really made a few decisions. Ah, phew. Key product announcement that really disrupted this entire industry. Right? So, um, Geo is a default for GLT network itself. All I p network Internet protocol in everything. All data. It's an all data network and everything from voice to data to Internet traffic. Everything goes over this. I'll goes over Internet protocol, and the cost to carry voice on our smartphone network is very low, right? The bandwidth voice consumes is very low in the entire Lt band. Right? So what we did Waas In order to gain a foothold in the market, we made voice completely free, right? He said you will not pay anything for boys and across India, we will not charge any roaming charges across India. Right? So we made voice free completely and we offer the lowest data rates in the world. We could do that because we had the largest capacity or to carry data in India off all the other telecom operators. And these data rates were unheard off in the world, right? So when we launched, we offered a $2 per month or $3 per month plan with unlimited data, you could consume 10 gigabytes of data all day if you wanted to, and some of our subscriber day. Right? So that's the first phase off the overgrowth and smartphones and that really disorders. We hit 100 million subscribers in 170 days, which was very, very fast. And then after the smartphone faith, we found that India still has 500 million feature phones. And in order to grow in that market, we launched our own phone, the geo phone, and we made it free. Right? So if you take if you took a geo subscription and you carried you stayed with us for three years, we would make this phone tree for your refund. The initial deposit that you paid for this phone and this phone had also had quite a few innovations tailored for the Indian market. It had all of our digital services for free, which I will talk about soon. And for example, you could plug in. You could use a cable right on RCR HDMI cable plug into the geo phone and you could watch TV on your big screen TV from the geophones. You didn't need a separate cable subscription toe watch TV, right? So that really helped us grow. And Geo Phone is now the largest selling feature phone in India on it. 100 million feature phones in India now. So now now we're in what I call the geo platforms phase. We're growing of a geo fiber fiber to the home fiber toe the office, um, space. And we've also launched our new commerce initiatives over e commerce initiatives and were steadily building platforms that other companies can leverage other companies can use in the Jeon o'clock. Right? So this is how a small startup not a small start, but a start of nonetheless least 400 million subscribers within four years the fastest growing tech company in the world. Next, Geo also helped a systemic change in India, and this is massive. A lot of startups are building on this India stack, as people call it, and I consider this India stack has made up off three things, and the acronym I use is jam. Trinity, right. So, um, in India, systemic change happened recently because the Indian government made bank accounts free for all one billion Indians. There were no service charges to store money in bank accounts. This is called the Jonathan. The J. GenDyn Bank accounts. The J out off the jam, then India is one of the few countries in the world toe have a digital biometric identity, which can be used to verify anyone online, which is huge. So you can simply go online and say, I am my ankle poor on duh. I verify that this is indeed me who's doing this transaction. This is the A in the jam and the last M stands for Mobil's, which which were held by Geo Mobile Internet in a plus. It is also it is. It also stands for something called the U. P I. The United Unified Payments Interface. This was launched by the Indian government, where you can carry digital transactions for free. You can transfer money from one person to the to another, essentially for free for no fee, right so I can transfer one group, even Indian rupee to my friend without paying any charges. That is huge, right? So you have a country now, which, with a with a billion people who are bank accounts, money in the bank, who you can verify online, right and who can pay online without any problems through their mobile connections held by G right. So suddenly our market, our Internet market, exploded from a few million users to now 506 106 100 million mobile Internet users. So that that I think, was a massive such a systemic change that happened in India. There are some really large hail, um, numbers for this India stack, right? In one month. There were 1.6 billion nuclear transactions in the last month, which is phenomenal. So next What is the impact of geo in India before you started, we were 155th in the world in terms off mobile in terms of broadband data consumption. Right. But after geo, India went from one 55th to the first in the world in terms of broadband data, largely consumed on mobile devices were a mobile first country, right? We have a habit off skipping technology generation, so we skip fixed line broadband and basically consuming Internet on our mobile phones. On average, Geo subscribers consumed 12 gigabytes of data per month, which is one of the highest rates in the world. So Geo has a huge role to play in making India the number one country in terms off broad banded consumption and geo responsible for quite a few industry first in the telecom space and in fact, in the India space, I would say so before Geo. To get a SIM card, you had to fill a form off the physical paper form. It used to go toe Ah, local distributor. And that local distributor is to check the farm that you feel incorrectly for your SIM card and then that used to go to the head office and everything took about 48 hours or so, um, to get your SIM card. And sometimes there were problems there also with a hard biometric authentication. We enable something, uh, India enable something called E K Y C Elektronik. Know your customer? We took a fingerprint scan at our point of Sale Reliance Digital stores, and within 15 minutes we could verify within a few minutes. Within a few seconds we could verify that person is indeed my hunk, right, buying the same car, Elektronik Lee on we activated the SIM card in 15 minutes. That was a massive deal for our growth. Initially right toe onboard 100 million customers. Within our and 70 days. We couldn't have done it without be K. I see that was a massive deal for us and that is huge for any company starting a business or start up in India. We also made voice free, no roaming charges and the lowest data rates in the world. Plus, we gave a full suite of cloud services for free toe all geo customers. For example, we give goTV essentially for free. We give GOTV it'll law for free, which people, when we have a launching, told us that no one would see no one would use because the Indians like watching TV in the living rooms, um, with the family on a big screen television. But when we actually launched, they found that GOTV is one off our most used app. It's like 70,000,080 million monthly active users, and now we've basically been changing culture in India where culture is on demand. You can watch TV on the goal and you can pause it and you can resume whenever you have some free time. So really changed culture in India, India on we help people liver, digital life online. Right, So that was massive. So >>I'm now I'd like to talk about our cloud >>journey on board Animal Minorities Partnership. We've been partners that since 2014 since the beginning. So Geo has been using open stack since 2014 when we started with 14 note luster. I'll be one production environment One right? And that was I call it the first wave off our cloud where we're just understanding open stack, understanding the capabilities, understanding what it could do. Now we're in our second wave. Where were about 4000 bare metal servers in our open stack cloud multiple regions, Um, on that around 100,000 CPU cores, right. So it's a which is one of the bigger clouds in the world, I would say on almost all teams, with Ngor leveraging the cloud and soon I think we're going to hit about 10,000 Bama tools in our cloud, which is massive and just to give you a scale off our network, our in French, our data center footprint. Our network introduction is about 30 network data centers that carry just network traffic across there are there across India and we're about eight application data centers across three regions. Data Center is like a five story building filled with servers. So we're talking really significant scale in India. And we had to do this because when we were launching, there are the government regulation and try it. They've gotten regulatory authority of India, mandates that any telecom company they have to store customer data inside India and none of the other cloud providers were big enough to host our clothes. Right. So we we made all this intellectual for ourselves, and we're still growing next. I love to show you how we grown with together with Moran says we started in 2014 with the fuel deployment pipelines, right? And then we went on to the NK deployment. Pipelines are cloud started growing. We started understanding the clouds and we picked up M C p, which has really been a game changer for us in automation, right on DNA. Now we are in the latest release, ofem CPM CPI $2019 to on open stack queens, which on we've just upgraded all of our clouds or the last few months. Couple of months, 2 to 3 months. So we've done about nine production clouds and there are about 50 internal, um, teams consuming cloud. We call as our tenants, right. We have open stack clouds and we have communities clusters running on top of open stack. There are several production grade will close that run on this cloud. The Geo phone, for example, runs on our cloud private cloud Geo Cloud, which is a backup service like Google Drive and collaboration service. It runs out of a cloud. Geo adds G o g S t, which is a tax filing system for small and medium enterprises, our retail post service. There are all these production services running on our private clouds. We're also empaneled with the government off India to provide cloud services to the government to any State Department that needs cloud services. So we were empaneled by Maiti right in their ego initiative. And our clouds are also Easter. 20,000 certified 20,000 Colin one certified for software processes on 27,001 and said 27,017 slash 18 certified for security processes. Our clouds are also P our data centers Alsop a 942 be certified. So significant effort and investment have gone toe These data centers next. So this is where I think we've really valued the partnership with Morantes. Morantes has has trained us on using the concepts of get offs and in fries cold, right, an automated deployments and the tool change that come with the M C P Morantes product. Right? So, um, one of the key things that has happened from a couple of years ago to today is that the deployment time to deploy a new 100 north production cloud has decreased for us from about 55 days to do it in 2015 to now, we're down to about five days to deploy a cloud after the bear metals a racked and stacked. And the network is also the physical network is also configured, right? So after that, our automated pipelines can deploy 100 0 clock in five days flight, which is a massive deal for someone for a company that there's adding bear metals to their infrastructure so fast, right? It helps us utilize our investment, our assets really well. By the time it takes to deploy a cloud control plane for us is about 19 hours. It takes us two hours to deploy a compu track and it takes us three hours to deploy a storage rack. Right? And we really leverage the re class model off M C. P. We've configured re class model to suit almost every type of cloud that we have, right, and we've kept it fairly generous. It can be, um, Taylor to deploy any type of cloud, any type of story, nor any type of compute north. Andi. It just helps us automate our deployments by putting every configuration everything that we have in to get into using infra introduction at school, right plus M. C. P also comes with pipelines that help us run automated tests, automated validation pipelines on our cloud. We also have tempest pipelines running every few hours every three hours. If I recall correctly which run integration test on our clouds to make sure the clouds are running properly right, that that is also automated. The re class model and the pipelines helpers automate day to operations and changes as well. There are very few seventh now, compared toa a few years ago. It very rare. It's actually the exception and that may be because off mainly some user letter as opposed to a cloud problem. We also have contributed auto healing, Prometheus and Manager, and we integrate parameters and manager with our even driven automation framework. Currently, we're using Stack Storm, but you could use anyone or any event driven automation framework out there so that it indicates really well. So it helps us step away from constantly monitoring our cloud control control planes and clothes. So this has been very fruitful for us and it has actually apps killed our engineers also to use these best in class practices like get off like in France cord. So just to give you a flavor on what stacks our internal teams are running on these clouds, Um, we have a multi data center open stack cloud, and on >>top of that, >>teams use automation tools like terra form to create the environments. They also create their own Cuba these clusters and you'll see you'll see in the next slide also that we have our own community that the service platform that we built on top of open stack to give developers development teams NGO um, easy to create an easy to destroy Cuban. It is environment and sometimes leverage the Murano application catalog to deploy using heats templates to deploy their own stacks. Geo is largely a micro services driven, Um um company. So all of our applications are micro services, multiple micro services talking to each other, and the leverage develops. Two sets, like danceable Prometheus, Stack stone from for Otto Healing and driven, not commission. Big Data's tax are already there Kafka, Patches, Park Cassandra and other other tools as well. We're also now using service meshes. Almost everything now uses service mesh, sometimes use link. Erred sometimes are experimenting. This is Theo. So So this is where we are and we have multiple clients with NGO, so our products and services are available on Android IOS, our own Geo phone, Windows Macs, Web, Mobile Web based off them. So any client you can use our services and there's no lock in. It's always often with geo, so our sources have to be really good to compete in the open Internet. And last but not least, I think I love toe talk to you about our container journey. So a couple of years ago, almost every team started experimenting with containers and communities and they were demand for as a platform team. They were demanding community that the service from us a manage service. Right? So we built for us, it was much more comfortable, much more easier toe build on top of open stack with cloud FBI s as opposed to doing this on bare metal. So we built a fully managed community that a service which was, ah, self service portal, where you could click a button and get a community cluster deployed in your own tenant on Do the >>things that we did are quite interesting. We also handle some geo specific use cases. So we have because it was a >>manage service. We deployed the city notes in our own management tenant, right? We didn't give access to the customer to the city. Notes. We deployed the master control plane notes in the tenant's tenant and our customers tenant, but we didn't give them access to the Masters. We didn't give them the ssh key the workers that the our customers had full access to. And because people in Genova learning and experimenting, we gave them full admin rights to communities customers as well. So that way that really helped on board communities with NGO. And now we have, like 15 different teams running multiple communities clusters on top, off our open stack clouds. We even handle the fact that there are non profiting. I people separate non profiting I peoples and separate production 49 p pools NGO. So you could create these clusters in whatever environment that non prod environment with more open access or a prod environment with more limited access. So we had to handle these geo specific cases as well in this communities as a service. So on the whole, I think open stack because of the isolation it provides. I think it made a lot of sense for us to do communities our service on top off open stack. We even did it on bare metal, but that not many people use the Cuban, indeed a service environmental, because it is just so much easier to work with. Cloud FBI STO provision much of machines and covering these clusters. That's it from me. I think I've said a mouthful, and now I love for you toe. I'd love to have your questions. If you want to reach out to me. My email is mine dot capulet r l dot com. I'm also you can also message me on Twitter at my uncouple. So thank you. And it was a pleasure talking to you, Andre. Let let me hear your questions.
SUMMARY :
So in order to solve that problem, we launched our own brand of smartphones called the So just to give you a flavor on what stacks our internal It is environment and sometimes leverage the Murano application catalog to deploy So we have because it was a So on the whole, I think open stack because of the isolation
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
2015 | DATE | 0.99+ |
India | LOCATION | 0.99+ |
2014 | DATE | 0.99+ |
two hours | QUANTITY | 0.99+ |
$50 | QUANTITY | 0.99+ |
3 | QUANTITY | 0.99+ |
12 gigabytes | QUANTITY | 0.99+ |
three years | QUANTITY | 0.99+ |
Morantes | ORGANIZATION | 0.99+ |
70,000,080 million | QUANTITY | 0.99+ |
Andre | PERSON | 0.99+ |
three hours | QUANTITY | 0.99+ |
Samsung | ORGANIZATION | 0.99+ |
2000 | DATE | 0.99+ |
70 days | QUANTITY | 0.99+ |
Genova | LOCATION | 0.99+ |
five days | QUANTITY | 0.99+ |
2 | QUANTITY | 0.99+ |
zero | QUANTITY | 0.99+ |
0 | QUANTITY | 0.99+ |
170 days | QUANTITY | 0.99+ |
100 million subscribers | QUANTITY | 0.99+ |
Onda Mantis Partnership | ORGANIZATION | 0.99+ |
first phase | QUANTITY | 0.99+ |
100 million | QUANTITY | 0.99+ |
15 minutes | QUANTITY | 0.99+ |
10 gigabytes | QUANTITY | 0.99+ |
first | QUANTITY | 0.99+ |
16 | DATE | 0.99+ |
four years | QUANTITY | 0.99+ |
4 months | QUANTITY | 0.99+ |
one person | QUANTITY | 0.99+ |
49 p | QUANTITY | 0.99+ |
100 million customers | QUANTITY | 0.99+ |
today | DATE | 0.99+ |
one billion | QUANTITY | 0.99+ |
Two sets | QUANTITY | 0.99+ |
155th | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
one key step | QUANTITY | 0.99+ |
last month | DATE | 0.99+ |
first country | QUANTITY | 0.98+ |
3 months | QUANTITY | 0.98+ |
around 100,000 CPU cores | QUANTITY | 0.98+ |
Joe | PERSON | 0.98+ |
100 | QUANTITY | 0.98+ |
27,001 | QUANTITY | 0.98+ |
One | QUANTITY | 0.98+ |
15 different teams | QUANTITY | 0.98+ |
Android IOS | TITLE | 0.98+ |
one month | QUANTITY | 0.98+ |
France | LOCATION | 0.98+ |
506 106 100 million | QUANTITY | 0.98+ |
Geo | ORGANIZATION | 0.98+ |
Elektronik Lee | ORGANIZATION | 0.98+ |
FBI | ORGANIZATION | 0.98+ |
one group | QUANTITY | 0.98+ |
1.6 billion nuclear transactions | QUANTITY | 0.98+ |
Andi | PERSON | 0.97+ |
Geo Mobile Internet | ORGANIZATION | 0.97+ |
five story | QUANTITY | 0.97+ |
Prometheus | TITLE | 0.97+ |
Evan Weaver & Eric Berg, Fauna | Cloud Native Insights
(bright upbeat music) >> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders around the globe, these are Cloud Native Insights. >> Hi, I'm Stu Miniman, the host of Cloud Native Insights. We talk about cloud native, we're talking about how customers can take advantage of the innovation and agility that's out there in the clouds, one of the undercurrents, not so hidden if you've been watching the program so far. We've talked a bit about serverless, say something that's helping remove the friction, allowed developers to take advantage of technology and definitely move really fast. So I'm really happy to welcome to the program, for coming from Fauna. First of all, I have the CTO and Co-founder, who's Evan Weaver. And also joining him is the new CEO Eric Berg. They said, both from Fauna, talking serverless, talking data as an API and talking the modern database. So first of all, thank you both for joining us. >> Thanks for having us Stu. >> Hi, good to be here. >> All right, so Evan, we're going to start with you. I love talking to founders always. If you could take us back a little bit, Fauna as a project first before it was a company, you of course were an early employee at Twitter. So if you could just bring us back a little bit, what created the Fauna project and bring us through a brief history if you would. >> So I was employee 15 and Twitter, I joined in 2008. And I had a database background, I was sort of a performance analyst and worked on Ruby on Rails sites at CNET networks with the team that went on to found GitHub actually. Now I went to Twitter 'cause I wanted Twitter the product to stay alive. And for no greater ambition than that. And I ended up running the back end engineering team there and building out all the distributed storage for the core business objects, tweets, timelines, the social graph, image storage, the cache, that kind of thing. And this was early in the cloud era. API's were new and weird. You couldn't get Amazon EC2 off the shelf easily. We were racking hardware and code ancient center. And there were no databases or platforms for data of any kind. They really let us the Twitter engineering team focus on building the product. And we did a lot of open source work there. Some of which has influenced Fauna, originally, Twitter's open source was hosted on the Fauna GitHub account, which predated Twitter like you mentioned. And I was there for four years build out the team, basically scaled the site, especially scaled the Twitter.com API. And we just never found a platform which was suitable for what we were trying to accomplish. Like a lot of what Twitter did was itself a platform. We had developers all over the world using the Twitter API to interact with tweets. And we're frustrated that we basically had to become specialists in data systems because there wasn't a data API, we can just build the product on. And ultimately, then data API that we wished we had, is now Fauna. >> Well, it's a story we've loved hearing. And it's fascinating one, is that the marketplace wasn't doing what we needed. Often open source is a piece of that, how do we scale that out? How do we build that? Realized that the problem that you have is what others have. And hey, maybe there's a company. So could you give us that transition, Fauna as a product, as a company, where was it understood that, hey, there's a lot of other people that can take advantage from some of the same tools that you needed before. >> I mean, we saw it in the developers working with the Twitter platform. We weren't like, your traditional database experiences, either manage cloud or on-prem, you have to administrate the machine, and you're responsible for its security and its availability and its location and backups and all that kind of thing. People building against Twitter's API weren't doing that. They're just using the web interface that we provided to them. It was our responsibility as a platform provider. We saw lots of successful companies being built on the API, but obviously, it was limited specifically to interacting with tweets. And we also saw peers from Twitter who went on to found companies, other people we knew in the startup scene, struggling to just get something out the door, because they had to do all this undifferentiated heavy lifting, which didn't contribute to their product at all, if they did succeed and they struggled with scalability problems and security problems and that kind of thing. And I think it's been a drag on the market overall, we're essentially, in cloud services. We're more or less built for the enterprise for mature and mid market and enterprise companies that already had resources to put behind these things, then wasn't sort of the cloud equivalent of the web, where individuals, people with fewer resources, people starting new projects, people doing more speculative work, which is what we originally and Jack was doing at Twitter, it just get going and build dynamic web applications. So I think the move to cloud kind of left this gap, which ultimately was starting to be filled with serverless, in particular, that we sort of backtracked from the productivity of the '90s with the lamp era, you can do everything on a single machine, nobody bothered you, you didn't have to pay anyone, just RPM install and you're good to go. To this Kubernetes, containers, cloud, multi site, multi region world where it's just too hard to get a basic product out the door and now serverless is sort of brought that around full circle, we see people building those products again, because the tools have probably matured. >> Well, Evan, I really appreciate you helping set the table. I think you've clearly articulated some of the big challenges we're seeing in the industry right now. Eric, I want to bring you into the conversation. So you relatively recently brought in as CEO, came from Okta a company that is also doing quite well. So give us if you could really the business opportunity here, serverless is not exactly the most mature market, there's a lot of interest excitement, we've been tracking it for years and see some good growth. But what brought you in and what do you see is that big opportunity. >> Yeah, absolutely, so the first thing I'll comment on is what, when I was looking for my next opportunity, what was really important is to, I think you can build some of the most interesting businesses and companies when there are significant technological shifts happening. Okta, which you mentioned, took advantage of the fact of SaaS application, really being adopted by enterprise, which back in 2009, wasn't an exactly a known thing. And similarly, when I look at Fauna, the move that Evan talked about, which is really the maturation of serverless. And therefore, that as an underpinning for a new type of applications is really just starting to take hold. And so then there creates opportunities that for a variety of different people in that stack that to build interesting businesses and obviously, the databases is an incredibly important part of that. And the other thing I've mentioned is that, a lot of people don't know this but there's a very good chunk of Okta's business, which is what they call their customer identity business, which is basically, servicing of identity is a set of API's that people can integrate into their applications. And you see a lot of enterprises using this as a part of their digital transformation effort. And so I was very familiar with that model and how prevalent, how much investment, how much aid was out there for customers, as every company becoming a software company and needing to rethink their business and build applications. And so you put those two trends together and you just see that serverless is going to be able to meet the needs of a lot of those companies. And as Evan mentioned, databases in general and traditionally have come with a lot of complexity from an operational perspective. And so when you look at the technology and some of the problems that Fauna has solved, in terms of really removing all of that operational burden when it comes to starting with and scaling a database, not only locally but globally. It's sort of a new, no brainer, everybody would love to have a database that scales, that is reliable and secure that they don't have to manage. >> Yeah, Eric, one follow up question for you. I think back a few years ago, you talked to companies and it's like, okay, database is the center of my business. It's a big expense. I have a team that works on it. There have been dealt so much change in the database market than most customers I talked to, is I have lots of solutions out there. I'm using Mongo, I've got Snowflake, Amazon has flavors of things I'm looking at. Snowflake just filed for their IPO, so we see the growth in the space. So maybe if you could just obviously serverless is a differentiation. There's a couple of solutions out there, like from Amazon or whether Aurora serverless solution but how does Fauna look to differentiate. Could you give us a little bit of kind of compared to the market out there? >> Sure, yeah, so at the high level, just to clarify, at the super high level for databases, there tends to be two types operational databases and then data warehouse which Snowflake is an example of a data warehouse. And as you probably already know, the former CEO of Snowflake is actually a chairman of Fauna. So Bob Muglia. So we have a lot of good insight into that business. But Fauna is very much on the operational database side. So the other half of that market, if you will, so really focused on being the core operational store for your application. And I think Evan mentioned it a little bit, there's been a lot of the transformation that's happened if we rewind all the way back to the early '90s, when it was Oracle, and Microsoft SQL Server were kind of the big players there. And then as those architectures basically hit limits, when it came to applications moving to the web, you had this whole rise in a lot of different no SQL solutions, but those solutions sort of gave up on some of the promises of a relational database in order to achieve some of the ability to scale in the performance required at the web. But we required then a little bit more sophistication, intelligence, in order to be able to basically create logic in your application that could make up for the fact that those databases didn't actually deliver on the promises of traditional relational databases. And so, enter Fauna and it's really sort of a combination of those two things, which is providing the trust, the security and reliability of a traditional relational database, but offering it as serverless, as we talked about, at the scale that you need it for a web application. And so it's a very interesting combination of those capabilities that we think, as Evan was talking about, allows people who don't have large DevOps teams or very sophisticated developers who can code around some of the limitations of these other databases, to really be able to use a database for what they're looking for. What I write to it is what I'm going to read from it and that we maintain that commitment and make that super easy. >> Yeah, it's important to know that the part of the reason that operational database, the database for mission critical business data has remained a cost center is because the conventional wisdom was that something like Fauna was impossible to build. People said, you literally cannot in information science create a global API for data which is transactional and consistent and suitable for relying on, for mission critical, user login, banking payments, user generated content, social graphs, internal IT data, anything that's irreplaceable. People said, there can be no general service that can do this ubiquitously a global internet scale, you have to do it specifically. So it's sort of like, we had no power company. Instead, you could call up Amazon, they drive a truck with a generator to your house and hook you up. And you're like, right on, I didn't have to like, install the generator myself. But like, it's not a good experience. It's still a pain in the neck, it's still specific to the location you're at. It's not getting utility computing from the cloud the way, it's been a dream for many decades that we get all our services through brokers and API's and the web and it's finally real with serverless. I want to emphasize that the Fauna it technology is new and novel. And based on and inspired by our experience at Twitter and also academic research with some of our advisors like Dr. Daniel Abadi. It's one of the things that attracted us, Snowflake chairman to our company that we'd solve groundbreaking problems in information science in the cloud, just the way Snowflakes had. >> Yeah, well and Evan, yeah please go on Eric. >> Yeah, I'm just going to have one thing to that, which is, in addition, I think when you think about Fauna and you mentioned MongoDB, I think they're one of a great examples of database companies over the last decade, who's been able to build a standalone business. And if you look at it from a business model perspective, the thing that was really successful for them is they didn't go into try to necessarily like, rip and replace in big database migrations, they started evolving with a new class of developers and new applications that were being developed and then rode that obviously into sort of a land and expand model into enterprises over time. And so when you think about Fauna from your business value proposition is harnessing the technological innovation that Evan talked about. And then combining this with a product that bottoms up developer first business motion that kind of rides this technological shift into you creating a presence in the database market over time. >> Well, Evan, I just want to go back to that, it's impossible comment that you made, a lot of people they learn about a technology and they feel that that's the way the technology works. Serverless is obviously often misunderstood from the name itself, too. We had a conversation with Andy Jassy, the CEO of AWS a couple years ago, and he said, "If I could rebuild AWS from the ground up today, "it would be using all serverless," that doesn't mean only lambda, but they're rebuilding a lot of their pieces underneath it. So I've looked at the container world and we're only starting the last year or so, talking about people using databases with Kubernetes and containers, so what is it that allows you to be able to have as you said, there's the consistency. So we're talking about acid there, not worry about things like cold starts, which are thing lots of people are concerned about when it comes to serverless and help us understand a little bit that what you do and the underlying technologies that you leverage. >> Yeah, databases are always the last to evolve because they're the riskiest to change and the hardest to build. And basically, through the cloud era, we've done this lift and shift of existing on premises solutions, especially with databases into cloud machines, but it's still the metaphor of the physical computer, which is the overriding unit of granularity mental concept, everything like you mentioned, containers, like we had machines then we had Vms, now we have containers, it's still a computer. And the database goes in that one computer, in one spot and it sits there and you got to talk to it. Wherever that is in the world, no matter how far away it is from you. And people said, well, the relational database is great. You can use locks within a single machine to make sure that you're not conflicting your data when you update it, you going to have transactionality, you can have serialize ability. What do you do, if you want to make that experience highly available at global scale? We went through a series of evolutions as an industry. From initially that the on-prem RDBMS to things like Google's percolator scheme, which essentially scales that up to data center scale and puts different parts of the traditional database on different physical machines on low latency links, but otherwise doesn't change the consistency properties, then to things like Google Spanner, which rely on synchronized atomic clocks to guarantee consistency. Well, not everyone has synchronized atomic clocks just lying around. And they're also, their issues with noisy neighbors and tenancy and things because you have to make sure that you can always read the clock in a consistent amount of time, not just have the time accurate in the first place. And Fauna is based on and inspired and evolved from an algorithm called Calvin, which came out of a buddy's lab at Yale. And what Calvin does is invert the traditional database relationship and say, instead of doing a bunch of work on the disk and then figuring out which transactions won by seeing what time it is, we will create a global pre determined order of transactions which is arbitrary by journaling them and replicating them. And then we will use that to essentially derive the time from the transactions which have already been committed to disk. And then once we know the order, we can say which one's won and didn't win and which happened before, happen after and present the appearance of consistency to all possible observers. And when this paper came out, it came out about a decade ago now I think, it was very opaque. There's a lot of kind of hand waving exercises left to the reader. Some scary statements about how wasn't suitable for things that in particular SQL requires. We met, my co-founder and I met as Fauna chief architect, he worked on my team at Twitter, at one of the database groups. We were building Fauna we were doing our market discovery or prototyping and we knew we needed to be a global API. We knew we needed low latency, high performance at global scale. We looked at Spanner and Spanner couldn't do it. But we found that this paper proposed a way that could and we can see based on our experience at Twitter that you could overcome all these obstacles which had made the paper overall being neglected by industry and it took us quite a while to implement it at industrial quality and scale, to qualify it with analysts and others, prove to the world that it was real. And Eric mentioned Mongo, we did a lot of work with Cassandra as well at Twitter, we're early in the Cassandra community. Like I wrote, the first tutorial for Cassandra where data stacks was founded. These vendors were telling people that you could not have transactionality and scale at the same time, and it was literally impossible. Then we had this incrementalism like things with Spanner. And it wasn't till Fauna that anyone had proved to the world that that just wasn't true. There was more marketing around their failure to solve the information science problem, than something fundamental. >> Eric, I'm wondering if you're able to share just order of magnitude, how many customers you have out there from a partnership standpoint, we'd like to understand a little bit how you work or fit into the public cloud ecosystems out there. I noticed that Alphabets General Venture Fund was one of the contributors to the last raise. And obviously, there's some underlying Google technology there. So if you could just customers and ecosystem. >> Yeah, so as I mentioned, we've had a very aggressive product lead developer go to market. And so we have 10s of thousands of people now on the service, using Fauna at different levels. And now we're focused on, how do we continue to build that momentum, again, going back to the model of focus on a developer lead model, really what we're focused on there is taking everything that Evan just talked about, which is real and very differentiated in terms of the real core tech in the back end and then combining that with a developer experience that makes it extremely easy to use and really, we think that's the magic in terms of what Fauna is bringing, so we got 10s of thousands of users and we got more signing up every day, coming to the service, we have an aggressive free plan there and then they can migrate up to higher paying plans as they consume over time. And the ecosystem, we're aggressively playing in the broader serverless ecosystem. So what we're looking at is as Evan mentioned, sometimes the databases is the last thing to change, it's also not necessarily the first thing that a developer starts from when they think about building their application or their website. And so we're plugging into the larger serverless ecosystem where people are making their choices about potentially their compute platform or maybe a development platform like I know you've talked to the folks over at JAMstack, sorry at Netlify and Purcell, who are big in the JAMstack community and providing really great workflows for new web and application developers on these platforms. And then at the compute layer, obviously, our Amazon, Google, Microsoft all have a serverless compute solution. CloudFlare is doing some really interesting things out at the edge. And so there's a variety of people up and down that stack, if you will, when people are thinking about this new generation of applications that we're plugging into to make sure that the Fauna is that the default database of choice. >> Wonderful, last question, Evan if I could, I love what I got somebody with your background. Talk about just so many different technologies maturing, give us a little bit as to some of the challenges you see serverless ecosystem, what's being attacked, what do we still need to work on? >> I mean, serverless is in the same place that Lamp was in the in the early '90s. We have the old conservatives ecosystem with the JAMstack players that Eric mentioned. We have closed proprietary ecosystems like the AWS stack or the Google Firebase stack. As to your point, Google has also invested in us so they're placing their bets widely. But it's seeing the same kind of criticism. That Lamp, the Linux, Apache, MySQL, PHP, Perl, it's not mature, it's a toy, no one will ever use this for real business. We can't switch from like DV2 or mumps to MySQL, like no one is doing that. The movement and the momentum in serverless is real. And the challenge now is for all the vendors in collaboration with the community of developers to mature the tools as those the products and applications being built on the new more productive stack also mature, so we have to keep ahead of our audience and make sure we start delivering and this is partly why Eric is here. Those those mid market and ultimately enterprise requirements so that business is built on top of Fauna today, can grow like Twitter did from small to giant. >> Yeah, I'd add on to that, this is reminiscent for me, back in 2009 at Okta, we were one of the early ISVs that built on in relied 100% on AWS. At that time there was still, it was very commonplace for people racking and stacking their own boxes and using Colo and we used to have conversations about I wonder how long it's going to be before we exceed the cost of this AWS thing and we go and run our own data centers. And that would be laughable to even consider today, right, no one would ever even think about that. And I think serverless is in a similar situation where the consumption model is very attractive to get started, some people sitting there, is it going to be too expensive as I scale. And as Evan mentioned, when we think about if you fast forward to kind of what the innovation that we can anticipate both technologically and economically it's just going to be the default model that people are going to wonder why they used to spend all these time managing these machines, if they don't have to. >> Evan and Eric, thank you so much, is great to hear the progress that you've made and big supporters, the serverless ecosystem, so excited to watch the progress there. Thanks so much. >> Thanks Stu. >> Thanks for having us Stu. >> All right and I'm Stu Miniman. Stay tuned. Every week we are putting out the Cloud Native Insights. Appreciate. Thank you for watching. (bright upbeat music)
SUMMARY :
leaders around the globe, of the innovation and going to start with you. We had developers all over the is that the marketplace cloud equivalent of the web, some of the big challenges and secure that they don't have to manage. is the center of my business. of the ability to scale that the part of the reason Yeah, well and Evan, And so when you think about Fauna and the underlying and the hardest to build. or fit into the public the last thing to change, to some of the challenges And the challenge now that people are going to wonder why and big supporters, the the Cloud Native Insights.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Evan | PERSON | 0.99+ |
Eric | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Jack | PERSON | 0.99+ |
Andy Jassy | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
2008 | DATE | 0.99+ |
ORGANIZATION | 0.99+ | |
Bob Muglia | PERSON | 0.99+ |
2009 | DATE | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Palo Alto | LOCATION | 0.99+ |
Eric Berg | PERSON | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
Snowflake | ORGANIZATION | 0.99+ |
Amazo | ORGANIZATION | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
ORGANIZATION | 0.99+ | |
Netlify | ORGANIZATION | 0.99+ |
four years | QUANTITY | 0.99+ |
100% | QUANTITY | 0.99+ |
two types | QUANTITY | 0.99+ |
Fauna | ORGANIZATION | 0.99+ |
Daniel Abadi | PERSON | 0.99+ |
MySQL | TITLE | 0.99+ |
Evan Weaver | PERSON | 0.99+ |
Okta | ORGANIZATION | 0.99+ |
two things | QUANTITY | 0.99+ |
last year | DATE | 0.99+ |
first | QUANTITY | 0.99+ |
one computer | QUANTITY | 0.99+ |
JAMstack | ORGANIZATION | 0.99+ |
both | QUANTITY | 0.99+ |
PHP | TITLE | 0.99+ |
Alphabets General Venture Fund | ORGANIZATION | 0.99+ |
one | QUANTITY | 0.99+ |
early '90s | DATE | 0.98+ |
CNET | ORGANIZATION | 0.98+ |
First | QUANTITY | 0.98+ |
Stu | PERSON | 0.98+ |
Boston | LOCATION | 0.98+ |
Mongo | ORGANIZATION | 0.97+ |
Linux | TITLE | 0.97+ |
single machine | QUANTITY | 0.97+ |
first thing | QUANTITY | 0.97+ |
UNLIST TILL 4/2 - Autonomous Log Monitoring
>> Sue: Hi everybody, thank you for joining us today for the virtual Vertica BDC 2020. Today's breakout session is entitled "Autonomous Monitoring Using Machine Learning". My name is Sue LeClaire, director of marketing at Vertica, and I'll be your host for this session. Joining me is Larry Lancaster, founder and CTO at Zebrium. Before we begin, I encourage you to submit questions or comments during the virtual session. You don't have to wait, just type your question or comment in the question box below the slide and click submit. There will be a Q&A session at the end of the presentation and we'll answer as many questions as we're able to during that time. Any questions that we don't address, we'll do our best to answer them offline. Alternatively, you can also go and visit Vertica forums to post your questions after the session. Our engineering team is planning to join the forums to keep the conversation going. Also, just a reminder that you can maximize your screen by clicking the double arrow button in the lower right corner of the slides. And yes, this virtual session is being recorded and will be available for you to view on demand later this week. We'll send you a notification as soon as it's ready. So, let's get started. Larry, over to you. >> Larry: Hey, thanks so much. So hi, my name's Larry Lancaster and I'm here to talk to you today about something that I think who's time has come and that's autonomous monitoring. So, with that, let's get into it. So, machine data is my life. I know that's a sad life, but it's true. So I've spent most of my career kind of taking telemetry data from products, either in the field, we used to call it in the field or nowadays, that's been deployed, and bringing that data back, like log file stats, and then building stuff on top of it. So, tools to run the business or services to sell back to users and customers. And so, after doing that a few times, it kind of got to the point where I was really sort of sick of building the same kind of thing from scratch every time, so I figured, why not go start a company and do it so that we don't have to do it manually ever again. So, it's interesting to note, I've put a little sentence here saying, "companies where I got to use Vertica" So I've been actually kind of working with Vertica for a long time now, pretty much since they came out of alpha. And I've really been enjoying their technology ever since. So, our vision is basically that I want a system that will characterize incidents before I notice. So an incident is, you know, we used to call it a support case or a ticket in IT, or a support case in support. Nowadays, you may have a DevOps team, or a set of SREs who are monitoring a production sort of deployment. And so they'll call it an incident. So I'm looking for something that will notice and characterize an incident before I notice and have to go digging into log files and stats to figure out what happened. And so that's a pretty heady goal. And so I'm going to talk a little bit today about how we do that. So, if we look at logs in particular. Logs today, if you look at log monitoring. So monitoring is kind of that whole umbrella term that we use to talk about how we monitor systems in the field that we've shipped, or how we monitor production deployments in a more modern stack. And so basically there are log monitoring tools. But they have a number of drawbacks. For one thing, they're kind of slow in the sense that if something breaks and I need to go to a log file, actually chances are really good that if you have a new issue, if it's an unknown unknown problem, you're going to end up in a log file. So the problem then becomes basically you're searching around looking for what's the root cause of the incident, right? And so that's kind of time-consuming. So, they're also fragile and this is largely because log data is completely unstructured, right? So there's no formal grammar for a log file. So you have this situation where, if I write a parser today, and that parser is going to do something, it's going to execute some automation, it's going to open or update a ticket, it's going to maybe restart a service, or whatever it is that I want to happen. What'll happen is later upstream, someone who's writing the code that produces that log message, they might do something really useful for me, or for users. And they might go fix a spelling mistake in that log message. And then the next thing you know, all the automation breaks. So it's a very fragile source for automation. And finally, because of that, people will set alerts on, "Oh, well tell me how many thousands of errors are happening every hour." Or some horrible metric like that. And then that becomes the only visibility you have in the data. So because of all this, it's a very human-driven, slow, fragile process. So basically, we've set out to kind of up-level that a bit. So I touched on this already, right? The truth is if you do have an incident, you're going to end up in log files to do root cause. It's almost always the case. And so you have to wonder, if that's the case, why do most people use metrics only for monitoring? And the reason is related to the problems I just described. They're already structured, right? So for logs, you've got this mess of stuff, so you only want to dig in there when you absolutely have to. But ironically, it's where a lot of the information that you need actually is. So we have a model today, and this model used to work pretty well. And that model is called "index and search". And it basically means you treat log files like they're text documents. And so you index them and when there's some issue you have to drill into, then you go searching, right? So let's look at that model. So 20 years ago, we had sort of a shrink-wrap software delivery model. You had an incident. With that incident, maybe you had one customer and you had a monolithic application and a handful of log files. So it's perfectly natural, in fact, usually you could just v-item the log file, and search that way. Or if there's a lot of them, you could index them and search them that way. And that all worked very well because the developer or the support engineer had to be an expert in those few things, in those few log files, and understand what they meant. But today, everything has changed completely. So we live in a software as a service world. What that means is, for a given incident, first of all you're going to be affecting thousands of users. You're going to have, potentially, 100 services that are deployed in your environment. You're going to have 1,000 log streams to sift through. And yet, you're still kind of stuck in the situation where to go find out what's the matter, you're going to have to search through the log files. So this is kind of the unacceptable sort of position we're in today. So for us, the future will not be index and search. And that's simply because it cannot scale. And the reason I say that it can't scale is because it all kind of is bottlenecked by a person and their eyeball. So, you continue to drive up the amount of data that has to be sifted through, the complexity of the stack that has to be understood, and you still, at the end of the day, for MTTR purposes, you still have the same bottleneck, which is the eyeball. So this model, I believe, is fundamentally broken. And that's why, I believe in five years you're going to be in a situation where most monitoring of unknown unknown problems is going to be done autonomously. And those issues will be characterized autonomously because there's no other way it can happen. So now I'm going to talk a little bit about autonomous monitoring itself. So, autonomous monitoring basically means, if you can imagine in a monitoring platform and you watch the monitoring platform, maybe you watch the alerts coming from it or more importantly, you kind of watch the dashboards and try to see if something looks weird. So autonomous monitoring is the notion that the platform should do the watching for you and only let you know when something is going wrong and should kind of give you a window into what happened. So if you look at this example I have on screen, just to take it really slow and absorb the concept of autonomous monitoring. So here in this example, we've stopped the database. And as a result, down below you can see there were a bunch of fallout. This is an Atlassian Stack, so you can imagine you've got a Postgres database. And then you've got sort of Bitbucket, and Confluence, and Jira, and these various other components that need the database operating in order to function. So what this is doing is it's calling out, "Hey, the root cause is the database stopped and here's the symptoms." Now, you might be wondering, so what. I mean I could go write a script to do this sort of thing. Here's what's interesting about this very particular example, and I'll show a couple more examples that are a little more involved. But here's the interesting thing. So, in the software that came up with this incident and opened this incident and put this root cause and symptoms in there, there's no code that knows anything about timestamp formats, severities, Atlassian, Postgres, databases, Bitbucket, Confluence, there's no regexes that talk about starting, stopped, RDBMS, swallowed exception, and so on and so forth. So you might wonder how it's possible then, that something which is completely ignorant of the stack, could come up with this description, which is exactly what a human would have had to do, to figure out what happened. And I'm going to get into how we do that. But that's what autonomous monitoring is about. It's about getting into a set of telemetry from a stack with no prior information, and understanding when something breaks. And I could give you the punchline right now, which is there are fundamental ways that software behaves when it's breaking. And by looking at hundreds of data sets that people have generously allowed us to use containing incidents, we've been able to characterize that and now generalize it to apply it to any new data set and stack. So here's an interesting one right here. So there's a fella, David Gill, he's just a genius in the monitoring space. He's been working with us for the last couple of months. So he said, "You know what I'm going to do, is I'm going to run some chaos experiments." So for those of you who don't know what chaos engineering is, here's the idea. So basically, let's say I'm running a Kubernetes cluster and what I'll do is I'll use sort of a chaos injection test, something like litmus. And basically it will inject issues, it'll break things in my application randomly to see if my monitoring picks it up. And so this is what chaos engineering is built around. It's built around sort of generating lots of random problems and seeing how the stack responds. So in this particular case, David went in and he deleted, basically one of the tests that was presented through litmus did a delete of a pod delete. And so that's going to basically take out some containers that are part of the service layer. And so then you'll see all kinds of things break. And so what you're seeing here, which is interesting, this is why I like to use this example. Because it's actually kind of eye-opening. So the chaos tool itself generates logs. And of course, through Kubernetes, all the log files locations that are on the host, and the container logs are known. And those are all pulled back to us automatically. So one of the log files we have is actually the chaos tool that's doing the breaking, right? And so what the tool said here, when it went to determine what the root cause was, was it noticed that there was this process that had these messages happen, initializing deletion lists, selection a pod to kill, blah blah blah. It's saying that the root cause is the chaos test. And it's absolutely right, that is the root cause. But usually chaos tests don't get picked up themselves. You're supposed to be just kind of picking up the symptoms. But this is what happens when you're able to kind of tease out root cause from symptoms autonomously, is you end up getting a much more meaningful answer, right? So here's another example. So essentially, we collect the log files, but we also have a Prometheus scraper. So if you export Prometheus metrics, we'll scrape those and we'll collect those as well. And so we'll use those for our autonomous monitoring as well. So what you're seeing here is an issue where, I believe this is where we ran something out of disk space. So it opened an incident, but what's also interesting here is, you see that it pulled that metric to say that the spike in this metric was a symptom of this running out of space. So again, there's nothing that knows anything about file system usage, memory, CPU, any of that stuff. There's no actual hard-coded logic anywhere to explain any of this. And so the concept of autonomous monitoring is looking at a stack the way a human being would. If you can imagine how you would walk in and monitor something, how you would think about it. You'd go looking around for rare things. Things that are not normal. And you would look for indicators of breakage, and you would see, do those seem to be correlated in some dimension? That is how the system works. So as I mentioned a moment ago, metrics really do kind of complete the picture for us. We end up in a situation where we have a one-stop shop for incident root cause. So, how does that work? Well, we ingest and we structure the log files. So if we're getting the logs, we'll ingest them and we'll structure them, and I'm going to show a little bit what that structure looks like and how that goes into the database in a moment. And then of course we ingest and structure the Prometheus metrics. But here, structure really should have an asterisk next to it, because metrics are mostly structured already. They have names. If you have your own scraper, as opposed to going into the time series Prometheus database and pulling metrics from there, you can keep a lot more information about metadata about those metrics from the exporter's perspective. So we keep all of that too. Then we do our anomaly detection on both of those sets of data. And then we cross-correlate metrics and log anomalies. And then we create incidents. So this is at a high level, kind of what's happening without any sort of stack-specific logic built in. So we had some exciting recent validation. So Mayadata's a pretty big player in the Kubernetes space. Essentially, they do Kubernetes as a managed service. They have tens of thousands of customers that they manage their Kubernetes clusters for them. And then they're also involved, both in the OpenEBS project, as well as in the Litmius project I mentioned a moment ago. That's their tool for chaos engineering. So they're a pretty big player in the Kubernetes space. So essentially, they said, "Oh okay, let's see if this is real." So what they did was they set up our collectors, which took three minutes in Kubernetes. And then they went and they, using Litmus, they reproduced eight incidents that their actual, real-world customers had hit. And they were trying to remember the ones that were the hardest to figure out the root cause at the time. And we picked up and put a root cause indicator that was correct in 100% of these incidents with no training configuration or metadata required. So this is kind of what autonomous monitoring is all about. So now I'm going to talk a little bit about how it works. So, like I said, there's no information included or required about, so if you imagine a log file for example. Now, commonly, over to the left-hand side of every line, there will be some sort of a prefix. And what I mean by that is you'll see like a timestamp, or a severity, and maybe there's a PID, and maybe there's function name, and maybe there's some other stuff there. So basically that's kind of, it's common data elements for a large portion of the lines in a given log file. But you know, of course, the contents change. So basically today, like if you look at a typical log manager, they'll talk about connectors. And what connectors means is, for an application it'll generate a certain prefix format in a log. And that means what's the format of the timestamp, and what else is in the prefix. And this lets the tool pick it up. And so if you have an app that doesn't have a connector, you're out of luck. Well, what we do is we learn those prefixes dynamically with machine learning. You do not have to have a connector, right? And what that means is that if you come in with your own application, the system will just work for it from day one. You don't have to have connectors, you don't have to describe the prefix format. That's so yesterday, right? So really what we want to be doing is up-leveling what the system is doing to the point where it's kind of working like a human would. You look at a log line, you know what's a timestamp. You know what's a PID. You know what's a function name. You know where the prefix ends and where the variable parts begin. You know what's a parameter over there in the variable parts. And sometimes you may need to see a couple examples to know what was a variable, but you'll figure it out as quickly as possible, and that's exactly how the system goes about it. As a result, we kind of embrace free-text logs, right? So if you look at a typical stack, most of the logs generated in a typical stack are usually free-text. Even structured logging typically will have a message attribute, which then inside of it has the free-text message. For us, that's not a bad thing. That's okay. The purpose of a log is to inform people. And so there's no need to go rewrite the whole logging stack just because you want a machine to handle it. They'll figure it out for themselves, right? So, you give us the logs and we'll figure out the grammar, not only for the prefix but also for the variable message part. So I already went into this, but there's more that's usually required for configuring a log manager with alerts. You have to give it keywords. You have to give it application behaviors. You have to tell it some prior knowledge. And of course the problem with all of that is that the most important events that you'll ever see in a log file are the rarest. Those are the ones that are one out of a billion. And so you may not know what's going to be the right keyword in advance to pick up the next breakage, right? So we don't want that information from you. We'll figure that out for ourselves. As the data comes in, essentially we parse it and we categorize it, as I've mentioned. And when I say categorize, what I mean is, if you look at a certain given log file, you'll notice that some of the lines are kind of the same thing. So this one will say "X happened five times" and then maybe a few lines below it'll say "X happened six times" but that's basically the same event type. It's just a different instance of that event type. And it has a different value for one of the parameters, right? So when I say categorization, what I mean is figuring out those unique types and I'll show an example of that next. Anomaly detection, we do on top of that. So anomaly detection on metrics in a very sort of time series by time series manner with lots of tunables is a well-understood problem. So we also do this on the event types occurrences. So you can think of each event type occurring in time as sort of a point process. And then you can develop statistics and distributions on that, and you can do anomaly detection on those. Once we have all of that, we have extracted features, essentially, from metrics and from logs. We do pattern recognition on the correlations across different channels of information, so different event types, different log types, different hoses, different containers, and then of course across to the metrics. Based on all of this cross-correlation, we end up with a root cause identification. So that's essentially, at a high level, how it works. What's interesting, from the perspective of this call particularly, is that incident detection needs relationally structured data. It really does. You need to have all the instances of a certain event type that you've ever seen easily accessible. You need to have the values for a given sort of parameter easily, quickly available so you can figure out what's the distribution of this over time, how often does this event type happen. You can run analytical queries against that information so that you can quickly, in real-time, do anomaly detection against new data. So here's an example of that this looks like. And this kind of part of the work that we've done. At the top you see some examples of log lines, right? So that's kind of a snippet, it's three lines out of a log file. And you see one in the middle there that's kind of highlighted with colors, right? I mean, it's a little messy, but it's not atypical of the log file that you'll see pretty much anywhere. So there, you've got a timestamp, and a severity, and a function name. And then you've got some other information. And then finally, you have the variable part. And that's going to have sort of this checkpoint for memory scrubbers, probably something that's written in English, just so that the person who's reading the log file can understand. And then there's some parameters that are put in, right? So now, if you look at how we structure that, the way it looks is there's going to be three tables that correspond to the three event types that we see above. And so we're going to look at the one that corresponds to the one in the middle. So if we look at that table, there you'll see a table with columns, one for severity, for function name, for time zone, and so on. And date, and PID. And then you see over to the right with the colored columns there's the parameters that were pulled out from the variable part of that message. And so they're put in, they're typed and they're in integer columns. So this is the way structuring needs to work with logs to be able to do efficient and effective anomaly detection. And as far as I know, we're the first people to do this inline. All right, so let's talk now about Vertica and why we take those tables and put them in Vertica. So Vertica really is an MPP column store, but it's more than that, because nowadays when you say "column store", people sort of think, like, for example Cassandra's a column store, whatever, but it's not. Cassandra's not a column store in the sense that Vertica is. So Vertica was kind of built from the ground up to be... So it's the original column store. So back in the cStor project at Berkeley that Stonebraker was involved in, he said let's explore what kind of efficiencies we can get out of a real columnar database. And what he found was that, he and his grad students that started Vertica. What they found was that what they can do is they could build a database that gives orders of magnitude better query performance for the kinds of analytics I'm talking about here today. With orders of magnitude less data storage underneath. So building on top of machine data, as I mentioned, is hard, because it doesn't have any defined schemas. But we can use an RDBMS like Vertica once we've structured the data to do the analytics that we need to do. So I talked a little bit about this, but if you think about machine data in general, it's perfectly suited for a columnar store. Because, if you imagine laying out sort of all the attributes of an event type, right? So you can imagine that each occurrence is going to have- So there may be, say, three or four function names that are going to occur for all the instances of a given event type. And so if you were to sort all of those event instances by function name, what you would find is that you have sort of long, million long runs of the same function name over and over. So what you have, in general, in machine data, is lots and lots of slowly varying attributes, lots of low-cardinality data that it's almost completely compressed out when you use a real column store. So you end up with a massive footprint reduction on disk. And it also, that propagates through the analytical pipeline. Because Vertica does late materialization, which means it tries to carry that data through memory with that same efficiency, right? So the scale-out architecture, of course, is really suitable for petascale workloads. Also, I should point out, I was going to mention it in another slide or two, but we use the Vertica Eon architecture, and we have had no problems scaling that in the cloud. It's a beautiful sort of rewrite of the entire data layer of Vertica. The performance and flexibility of Eon is just unbelievable. And so I've really been enjoying using it. I was skeptical, you could get a real column store to run in the cloud effectively, but I was completely wrong. So finally, I should mention that if you look at column stores, to me, Vertica is the one that has the full SQL support, it has the ODBC drivers, it has the ACID compliance. Which means I don't need to worry about these things as an application developer. So I'm laying out the reasons that I like to use Vertica. So I touched on this already, but essentially what's amazing is that Vertica Eon is basically using S3 as an object store. And of course, there are other offerings, like the one that Vertica does with pure storage that doesn't use S3. But what I find amazing is how well the system performs using S3 as an object store, and how they manage to keep an actual consistent database. And they do. We've had issues where we've gone and shut down hosts, or hosts have been shut down on us, and we have to restart the database and we don't have any consistency issues. It's unbelievable, the work that they've done. Essentially, another thing that's great about the way it works is you can use the S3 as a shared object store. You can have query nodes kind of querying from that set of files largely independently of the nodes that are writing to them. So you avoid this sort of bottleneck issue where you've got contention over who's writing what, and who's reading what, and so on. So I've found the performance using separate subclusters for our UI and for the ingest has been amazing. Another couple of things that they have is they have a lot of in-database machine learning libraries. There's actually some cool stuff on their GitHub that we've used. One thing that we make a lot of use of is the sequence and time series analytics. For example, in our product, even though we do all of this stuff autonomously, you can also go create alerts for yourself. And one of the kinds of alerts you can do, you can say, "Okay, if this kind of event happens within so much time, and then this kind of an event happens, but not this one," Then you can be alerted. So you can have these kind of sequences that you define of events that would indicate a problem. And we use their sequence analytics for that. So it kind of gives you really good performance on some of these queries where you're wanting to pull out sequences of events from a fact table. And timeseries analytics is really useful if you want to do analytics on the metrics and you want to do gap filling interpolation on that. It's actually really fast in performance. And it's easy to use through SQL. So those are a couple of Vertica extensions that we use. So finally, I would like to encourage everybody, hey, come try us out. Should be up and running in a few minutes if you're using Kubernetes. If not, it's however long it takes you to run an installer. So you can just come to our website, pick it up and try out autonomous monitoring. And I want to thank everybody for your time. And we can open it up for Q and A.
SUMMARY :
Also, just a reminder that you can maximize your screen And one of the kinds of alerts you can do, you can say,
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
David | PERSON | 0.99+ |
Larry Lancaster | PERSON | 0.99+ |
David Gill | PERSON | 0.99+ |
Vertica | ORGANIZATION | 0.99+ |
100% | QUANTITY | 0.99+ |
Sue LeClaire | PERSON | 0.99+ |
five times | QUANTITY | 0.99+ |
Larry | PERSON | 0.99+ |
S3 | TITLE | 0.99+ |
three minutes | QUANTITY | 0.99+ |
six times | QUANTITY | 0.99+ |
Sue | PERSON | 0.99+ |
100 services | QUANTITY | 0.99+ |
Zebrium | ORGANIZATION | 0.99+ |
today | DATE | 0.99+ |
three | QUANTITY | 0.99+ |
five years | QUANTITY | 0.99+ |
Today | DATE | 0.99+ |
yesterday | DATE | 0.99+ |
both | QUANTITY | 0.99+ |
Kubernetes | TITLE | 0.99+ |
one | QUANTITY | 0.99+ |
thousands | QUANTITY | 0.99+ |
two | QUANTITY | 0.99+ |
SQL | TITLE | 0.99+ |
one customer | QUANTITY | 0.98+ |
three lines | QUANTITY | 0.98+ |
three tables | QUANTITY | 0.98+ |
each event | QUANTITY | 0.98+ |
hundreds | QUANTITY | 0.98+ |
first people | QUANTITY | 0.98+ |
1,000 log streams | QUANTITY | 0.98+ |
20 years ago | DATE | 0.98+ |
eight incidents | QUANTITY | 0.98+ |
tens of thousands of customers | QUANTITY | 0.97+ |
later this week | DATE | 0.97+ |
thousands of users | QUANTITY | 0.97+ |
Stonebraker | ORGANIZATION | 0.96+ |
each occurrence | QUANTITY | 0.96+ |
Postgres | ORGANIZATION | 0.96+ |
One thing | QUANTITY | 0.95+ |
three event types | QUANTITY | 0.94+ |
million | QUANTITY | 0.94+ |
Vertica | TITLE | 0.94+ |
one thing | QUANTITY | 0.93+ |
4/2 | DATE | 0.92+ |
English | OTHER | 0.92+ |
four function names | QUANTITY | 0.86+ |
day one | QUANTITY | 0.84+ |
Prometheus | TITLE | 0.83+ |
one-stop | QUANTITY | 0.82+ |
Berkeley | LOCATION | 0.82+ |
Confluence | ORGANIZATION | 0.79+ |
double arrow | QUANTITY | 0.79+ |
last couple of months | DATE | 0.79+ |
one of | QUANTITY | 0.76+ |
cStor | ORGANIZATION | 0.75+ |
a billion | QUANTITY | 0.73+ |
Atlassian Stack | ORGANIZATION | 0.72+ |
Eon | ORGANIZATION | 0.71+ |
Bitbucket | ORGANIZATION | 0.68+ |
couple more examples | QUANTITY | 0.68+ |
Litmus | TITLE | 0.65+ |
UNLIST TILL 4/2 - Vertica @ Uber Scale
>> Sue: Hi, everybody. Thank you for joining us today, for the Virtual Vertica BDC 2020. This breakout session is entitled "Vertica @ Uber Scale" My name is Sue LeClaire, Director of Marketing at Vertica. And I'll be your host for this webinar. Joining me is Girish Baliga, Director I'm sorry, user, Uber Engineering Manager of Big Data at Uber. Before we begin, I encourage you to submit questions or comments during the virtual session. You don't have to wait, just type your question or comment in the question box below the slides and click Submit. There will be a Q and A session, at the end of the presentation. We'll answer as many questions as we're able to during that time. Any questions that we don't address, we'll do our best to answer offline. Alternately, you can also Vertica forums to post your questions there after the session. Our engineering team is planning to join the forums to keep the conversation going. And as a reminder, you can maximize your screen by clicking the double arrow button, in the lower right corner of the slides. And yet, this virtual session is being recorded, and you'll be able to view on demand this week. We'll send you a notification as soon as it's ready. So let's get started. Girish over to you. >> Girish: Thanks a lot Sue. Good afternoon, everyone. Thanks a lot for joining this session. My name is Girish Baliga. And as Sue mentioned, I manage interactive and real time analytics teams at Uber. Vertica is one of the main platforms that we support, and Vertica powers a lot of core business use cases. In today's talk, I wanted to cover two main things. First, how Vertica is powering critical business use cases, across a variety of orgs in the company. And second, how we are able to do this at scale and with reliability, using some of the additional functionalities and systems that we have built into the Vertica ecosystem at Uber. And towards the end, I also have a little extra bonus for all of you. I will be sharing an easy way for you to take advantage of, many of the ideas and solutions that I'm going to present today, that you can apply to your own Vertica deployments in your companies. So stick around and put on your seat belts, and let's go start on the ride. At Uber, our mission is to ignite opportunity by setting the world in motion. So we are focused on solving mobility problems, and enabling people all over the world to solve their local problems, their local needs, their local issues, in a manner that's efficient, fast and reliable. As our CEO Dara has said, we want to become the mobile operating system of local cities and communities throughout the world. As of today, Uber is operational in over 10,000 cities around the world. So, across our various business lines, we have over 110 million monthly users, who use our rides, services, or eat services, and a whole bunch of other services that we provide to Uber. And just to give you a scale of our daily operations, we in the ride business, have over 20 million trips per day. And that each business is also catching up, particularly during the recent times that we've been having. And so, I hope these numbers give you a scale of the amount of data, that we process each and every day. And support our users in their analytical and business reporting needs. So who are these users at Uber? Let's take a quick look. So, Uber to describe it very briefly, is a lot like Amazon. We are largely an operation and logistics company. And employee work based reflects that. So over 70% of our employees work in teams, which come under the umbrella of Community Operations and Centers of Excellence. So these are all folks working in various cities and towns that we operate around the world, and run the Uber businesses, as somewhat local businesses responding to local needs, local market conditions, local regulation and so forth. And Vertica is one of the most important tools, that these folks use in their day to day business activities. So they use Vertica to get insights into how their businesses are going, to deeply into any issues that they want to triage , to generate reports, to plan for the future, a whole lot of use cases. The second big class of users, are in our marketplace team. So marketplace is the engineering team, that backs our ride shared business. And as part of this, running this business, a key problem that they have to solve, is how to determine what prices to set, for particular rides, so that we have a good match between supply and demand. So obviously the real time pricing decisions they're made by serving systems, with very detailed and well crafted machine learning models. However, the training data that goes into this models, the historical trends, the insights that go into building these models, a lot of these things are powered by the data that we store, and serve out of Vertica. Similarly, in each business, we have use cases spanning all the way from engineering and back-end systems, to support operations, incentives, growth, and a whole bunch of other domains. So the big class of applications that we support across a lot of these business lines, is dashboards and reporting. So we have a lot of dashboards, which are built by core data analysts teams and shared with a whole bunch of our operations and other teams. So these are dashboards and reports that run, periodically say once a week or once a day even, depending on the frequency of data that they need. And many of these are powered by the data, and the analytics support that we provide on our Vertica platform. Another big category of use cases is for growth marketing. So this is to understand historical trends, figure out what are various business lines, various customer segments, various geographical areas, doing in terms of growth, where it is necessary for us to reinvest or provide some additional incentives, or marketing support, and so forth. So the analysis that backs a lot of these decisions, is powered by queries running on Vertica. And finally, the heart and soul of Uber is data science. So data science is, how we provide best in class algorithms, pricing, and matching. And a lot of the analysis that goes into, figuring out how to build these systems, how to build the models, how to build the various coefficients and parameters that go into making real time decisions, are based on analysis that data scientists run on Vertica systems. So as you can see, Vertica usage spans a whole bunch of organizations and users, all across the different Uber teams and ecosystems. Just to give you some quick numbers, we have over 5000 weekly active, people who run queries at least once a week, to do some critical business role or problem to solve, that they have in their day to day operations. So next, let's see how Vertica fits into the Uber data ecosystem. So when users open up their apps, and request for a ride or order food delivery on each platform, the apps are talking to our serving systems. And the serving systems use online storage systems, to store the data as the trips and eat orders are getting processed in real time. So for this, we primarily use an in house built, key value storage system called Schemaless, and an open source system called Cassandra. We also have other systems like MySQL and Redis, which we use for storing various bits of data to support serving systems. So all of this operations generates a lot of data, that we then want to process and analyze, and use for our operational improvements. So, we have ingestion systems that periodically pull in data from our serving systems and land them in our data lake. So at Uber a data lake is powered by Hadoop, with files stored on HDFS clusters. So once the raw data lines on the data lake, we then have ETL jobs that process these raw datasets, and generate, modeled and customize datasets which we then use for further analysis. So once these model datasets are available, we load them into our data warehouse, which is entirely powered by Vertica. So then we have a business intelligence layer. So with internal tools, like QueryBuilder, which is a UI interface to write queries, and look at results. And it read over the front-end sites, and Dashbuilder, which is a dash, board building tool, and report management tool. So these are all various tools that we have built within Uber. And these can talk to Vertica and run SQL queries to power, whatever, dashboards and reports that they are supporting. So this is what the data ecosystem looks like at Uber. So why Vertica and what does it really do for us? So it powers insights, that we show on dashboards as folks use, and it also powers reports that we run periodically. But more importantly, we have some core, properties and core feature sets that Vertica provides, which allows us to support many of these use cases, very well and at scale. So let me take a brief tour of what these are. So as I mentioned, Vertica powers Uber's data warehouse. So what this means is that we load our core fact and dimension tables onto Vertica. The core fact tables are all the trips, all the each orders and all these other line items for various businesses from Uber, stored as partitioned tables. So think of having one partition per day, as well as dimension tables like cities, users, riders, career partners and so forth. So we have both these two kinds of datasets, which will load into Vertica. And we have full historical data, all the way since we launched these businesses to today. So that folks can do deeper longitudinal analysis, so they can look at patterns, like how the business has grown from month to month, year to year, the same month, over a year, over multiple years, and so forth. And, the really powerful thing about Vertica, is that most of these queries, you run the deep longitudinal queries, run very, very fast. And that's really why we love Vertica. Because we see query latency P90s. That is 90 percentile of all queries that we run on our platform, typically finish in under a minute. So that's very important for us because Vertica is used, primarily for interactive analytics use cases. And providing SQL query execution times under a minute, is critical for our users and business owners to get the most out of analytics and Big Data platforms. Vertica also provides a few advanced features that we use very heavily. So as you might imagine, at Uber, one of the most important set of use cases we have is around geospatial analytics. In particular, we have some critical internal dashboards, that rely very heavily on being able to restrict datasets by geographic areas, cities, source destination pairs, heat maps, and so forth. And Vertica has a rich array of functions that we use very heavily. We also have, support for custom projections in Vertica. And this really helps us, have very good performance for critical datasets. So for instance, in some of our core fact tables, we have done a lot of query and analysis to figure out, how users run their queries, what kind of columns they use, what combination of columns they use, and what joints they do for typical queries. And then we have laid out our custom projections to maximize performance on these particular dimensions. And the ability to do that through Vertica, is very valuable for us. So we've also had some very successful collaborations, with the Vertica engineering team. About a year and a half back, we had open-sourced a Python Client, that we had built in house to talk to Vertica. We were using this Python Client in our business intelligence layer that I'd shown on the previous slide. And we had open-sourced it after working closely with Eng team. And now Vertica formally supports the Python Client as an open-source project, which you can download to and integrate into your systems. Another more recent example of collaboration is the Vertica Eon mode on GCP. So as most of or at least some of you know, Vertica Eon mode is formally supported on AWS. And at Uber, we were also looking to see if we could run our data infrastructure on GCP. So Vertica team hustled on this, and provided us early preview version, which we've been testing out to see how performance, is impacted by running on the Cloud, and on GCP. And so far, I think things are going pretty well, but we should have some numbers about this very soon. So here I have a visualization of an internal dashboard, that is powered solely by data and queries running on Vertica. So this GIF has sequence have different visualizations supported by this tool. So for instance, here you see a heat map, downgrading heat map of source of traffic demand for ride shares. And then you will see a bunch of arrows here about source destination pairs and the trip lines. And then you can see how demand moves around. So, as the cycles through the various animations, you can basically see all the different kinds of insights, and query shapes that we send to Vertica, which powers this critical business dashboard for our operations teams. All right, so now how do we do all of this at scale? So, we started off with a single Vertica cluster, a few years back. So we had our data lake, the data would land into Vertica. So these are the core fact and dimension tables that I just spoke about. And then Vertica powers queries at our business intelligence layer, right? So this is a very simple, and effective architecture for most use cases. But at Uber scale, we ran into a few problems. So the first issue that we have is that, Uber is a pretty big company at this point, with a lot of users sending almost millions of queries every week. And at that scale, what we began to see was that a single cluster was not able to handle all the query traffic. So for those of you who have done an introductory course, on queueing theory, you will realize that basically, even though you could have all the query is processed through a single serving system. You will tend to see larger and larger queue wait times, as the number of queries pile up. And what this means in practice for end users, is that they are basically just seeing longer and longer query latencies. But even though the actual query execution time on Vertica itself, is probably less than a minute, their query sitting in the queue for a bunch of minutes, and that's the end user perceived latency. So this was a huge problem for us. The second problem we had was that the cluster becomes a single point of failure. Now Vertica can handle single node failures very gracefully, and it can probably also handle like two or three node failures depending on your cluster size and your application. But very soon, you will see that, when you basically have beyond a certain number of failures or nodes in maintenance, then your cluster will probably need to be restarted or you will start seeing some down times due to other issues. So another example of why you would have to have a downtime, is when you're upgrading software in your clusters. So, essentially we're a global company, and we have users all around the world, we really cannot afford to have downtime, even for one hour slot. So that turned out to be a big problem for us. And as I mentioned, we could have hardware issues. So we we might need to upgrade our machines, or we might need to replace storage or memory due to issues with the hardware in there, due to normal wear and tear, or due to abnormal issues. And so because of all of these things, having a single point of failure, having a single cluster was not really practical for us. So the next thing we did, was we set up multiple clusters, right? So we had a bunch of identities clusters, all of which have the same datasets. So then we would basically load data using ingestion pipelines from our data lake, onto each of these clusters. And then the business intelligence layer would be able to query any of these clusters. So this actually solved most of the issues that I pointed out in the previous slide. So we no longer had a single point of failure. Anytime we had to do version upgrades, we would just take off one cluster offline, upgrade the software on it. If we had node failures, we would probably just take out one cluster, if we had to, or we would just have some spare nodes, which would rotate into our production clusters and so forth. However, having multiple clusters, led to a new set of issues. So the first problem was that since we have multiple clusters, you would end up with inconsistent schema. So one of the things to understand about our platform, is that we are an infrastructure team. So we don't actually own or manage any of the data that is served on Vertica clusters. So we have dataset owners and publishers, who manage their own datasets. Now exposing multiple clusters to these dataset owners. Turns out, it's not a great idea, right? Because they are not really aware of, the importance of having consistency of schemas and datasets across different clusters. So over time, what we saw was that the schema for the same tables would basically get out of order, because they were all the updates are not consistently applied on all clusters. Or maybe they were just experimenting some new columns or some new tables in one cluster, but they forgot to delete it, whatever the case might be. We basically ended up in a situation where, we saw a lot of inconsistent schemas, even across some of our core tables in our different clusters. A second issue was, since we had ingestion pipelines that were ingesting data independently into all these clusters, these pipelines could fail independently as well. So what this meant is that if, for instance, the ingestion pipeline into cluster B failed, then the data there would be older than clusters A and C. So, when a query comes in from the BI layer, and if it happens to hit B, you would probably see different results, than you would if you went to a or C. And this was obviously not an ideal situation for our end users, because they would end up seeing slightly inconsistent, slightly different counts. But then that would lead to a bad situation for them where they would not able to fully trust the data that was, and the results and insights that were being returned by the SQL queries and Vertica systems. And then the third problem was, we had a lot of extra replication. So the 20/80 Rule, or maybe even the 90/10 Rule, applies to datasets on our clusters as well. So less than 10% of our datasets, for instance, in 90% of the queries, right? And so it doesn't really make sense for us to replicate all of our data on all the clusters. And so having this set up where we had to do that, was obviously very suboptimal for us. So then what we did, was we basically built some additional systems to solve these problems. So this brings us to our Vertica ecosystem that we have in production today. So on the ingestion side, we built a system called Vertica Data Manager, which basically manages all the ingestion into various clusters. So at this point, people who are managing datasets or dataset owners and publishers, they no longer have to be aware of individual clusters. They just set up their ingestion pipelines with an endpoint in Vertica Data Manager. And the Vertica Data Manager ensures that, all the schemas and data is consistent across all our clusters. And on the query side, we built a proxy layer. So what this ensures is that, when queries come in from the BI layer, the query was forwarded, smartly and with knowledge and data about which cluster up, which clusters are down, which clusters are available, which clusters are loaded, and so forth. So with these two layers of abstraction between our ingestion and our query, we were able to have a very consistent, almost single system view of our entire Vertica deployment. And the third bit, we had put in place, was the data manifest, which were the communication mechanism between ingestion and proxy. So the data manifest basically is a listing of, which tables are available on which clusters, which clusters are up to date, and so forth. So with this ecosystem in place, we were also able to solve the extra replication problem. So now we basically have some big clusters, where all the core tables, and all the tables, in fact, are served. So any query that hits 90%, less so tables, goes to the big clusters. And most of the queries which hit 10% heavily queried important tables, can also be served by many other small clusters, so much more efficient use of resources. So this basically is the view that we have today, of Vertica within Uber, so external to our team, folks, just have an endpoint, where they basically set up their ingestion jobs, and another endpoint where they can forward their Vertica SQL queries. And they are so to a proxy layer. So let's get a little more into details, about each of these layers. So, on the data management side, as I mentioned, we have two kinds of tables. So we have dimension tables. So these tables are updated every cycle, so the list of cities list of drivers, the list of users and so forth. So these change not so frequently, maybe once a day or so. And so we are able to, and since these datasets are not very big, we basically swap them out on every single cycle. Whereas the fact tables, so these are tables which have information about our trips or each orders and so forth. So these are partition. So we have one partition roughly per day, for the last couple of years, and then we have more of a hierarchical partitions set up for older data. So what we do is we load the partitions for the last three days on every cycle. The reason we do that, is because not all our data comes in at the same time. So we have updates for trips, going over the past two or three days, for instance, where people add ratings to their trips, or provide feedback for drivers and so forth. So we want to capture them all in the row corresponding to that particular trip. And so we upload partitions for the last few days to make sure we capture all those updates. And we also update older partitions, if for instance, records were deleted for retention purposes, or GDPR purposes, for instance, or other regulatory reasons. So we do this less frequently, but these are also updated if necessary. So there are endpoints which allow dataset owners to specify what partitions they want to update. And as I mentioned, data is typically managed using a hierarchical partitioning scheme. So in this way, we are able to make sure that, we take advantage of the data being clustered by day, so that we don't have to update all the data at once. So when we are recovering from an cluster event, like a version upgrade or software upgrade, or hardware fix or failure handling, or even when we are adding a new cluster to the system, the data manager takes care of updating the tables, and copying all the new partitions, making sure the schemas are all right. And then we update the data and schema consistency and make sure everything is up to date before we, add this cluster to our serving pool, and the proxy starts sending traffic to it. The second thing that the data manager provides is consistency. So the main thing we do here, is we do atomic updates of our tables and partitions for fact tables using a two-phase commit scheme. So what we do is we load all the new data in temp tables, in all the clusters in phase one. And then when all the clusters give us access signals, then we basically promote them to primary and set them as the main serving tables for incoming queries. We also optimize the load, using Vertica Data Copy. So what this means is earlier, in a parallel pipelines scheme, we had to ingest data individually from HDFS clusters into each of the Vertica clusters. That took a lot of HDFS bandwidth. But using this nice feature that Vertica provides called Vertica Data Copy, we just load it data into one cluster and then much more efficiently copy it, to the other clusters. So this has significantly reduced our ingestion overheads, and speed it up our load process. And as I mentioned as the second phase of the commit, all data is promoted at the same time. Finally, we make sure that all the data is up to date, by doing some checks around the number of rows and various other key signals for freshness and correctness, which we compare with the data in the data lake. So in terms of schema changes, VDM automatically applies these consistently across all the clusters. So first, what we do is we stage these changes to make sure that these are correct. So this catches errors that are trying to do, an incompatible update, like changing a column type or something like that. So we make sure that schema changes are validated. And then we apply them to all clusters atomically again for consistency. And provide a overall consistent view of our data to all our users. So on the proxy side, we have transparent support for, replicated clusters to all our users. So the way we handle that is, as I mentioned, the cluster to table mapping is maintained in the manifest database. And when we have an incoming query, the proxy is able to see which cluster has all the tables in that query, and route the query to the appropriate cluster based on the manifest information. Also the proxy is aware of the health of individual clusters. So if for some reason a cluster is down for maintenance or upgrades, the proxy is aware of this information. And it does the monitoring based on query response and execution times as well. And it uses this information to route queries to healthy clusters, and do some load balancing to ensure that we award hotspots on various clusters. So the key takeaways that I have from the stock, are primarily these. So we started off with single cluster mode on Vertica, and we ran into a bunch of issues around scaling and availability due to cluster downtime. We had then set up a bunch of replicated clusters to handle the scaling and availability issues. Then we run into issues around schema consistency, data staleness, and data replication. So we built an entire ecosystem around Vertica, with abstraction layers around data management and ingestion, and proxy. And with this setup, we were able to enforce consistency and improve storage utilization. So, hopefully this gives you all a brief idea of how we have been able to scale Vertica usage at Uber, and power some of our most business critical and important use cases. So as I mentioned at the beginning, I have a interesting and simple extra update for you. So an easy way in which you all can take advantage of many of the features that we have built into our ecosystem, is to use the Vertica Eon mode. So the Vertica Eon mode, allows you to set up multiple clusters with consistent data updates, and set them up at various different sizes to handle different query loads. And it automatically handles many of these issues that I mentioned in our ecosystem. So do check it out. We've also been, trying it out on DCP, and initial results look very, very promising. So thank you all for joining me on this talk today. I hope you guys learned something new. And hopefully you took away something that you can also apply to your systems. We have a few more time for some questions. So I'll pause for now and take any questions.
SUMMARY :
Any questions that we don't address, So the first issue that we have is that,
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Girish Baliga | PERSON | 0.99+ |
Uber | ORGANIZATION | 0.99+ |
Girish | PERSON | 0.99+ |
10% | QUANTITY | 0.99+ |
one hour | QUANTITY | 0.99+ |
Sue LeClaire | PERSON | 0.99+ |
90% | QUANTITY | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Sue | PERSON | 0.99+ |
two | QUANTITY | 0.99+ |
Vertica | ORGANIZATION | 0.99+ |
Dara | PERSON | 0.99+ |
first issue | QUANTITY | 0.99+ |
less than a minute | QUANTITY | 0.99+ |
MySQL | TITLE | 0.99+ |
First | QUANTITY | 0.99+ |
first problem | QUANTITY | 0.99+ |
third problem | QUANTITY | 0.99+ |
third bit | QUANTITY | 0.99+ |
less than 10% | QUANTITY | 0.99+ |
each platform | QUANTITY | 0.99+ |
second | QUANTITY | 0.99+ |
one cluster | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
second issue | QUANTITY | 0.99+ |
Python | TITLE | 0.99+ |
today | DATE | 0.99+ |
second phase | QUANTITY | 0.99+ |
two kinds | QUANTITY | 0.99+ |
over 10,000 cities | QUANTITY | 0.99+ |
over 70% | QUANTITY | 0.99+ |
each business | QUANTITY | 0.99+ |
second thing | QUANTITY | 0.98+ |
second problem | QUANTITY | 0.98+ |
Vertica | TITLE | 0.98+ |
both | QUANTITY | 0.98+ |
Vertica Data Manager | TITLE | 0.98+ |
two-phase | QUANTITY | 0.98+ |
first | QUANTITY | 0.98+ |
90 percentile | QUANTITY | 0.98+ |
once a week | QUANTITY | 0.98+ |
each | QUANTITY | 0.98+ |
single point | QUANTITY | 0.97+ |
SQL | TITLE | 0.97+ |
once a day | QUANTITY | 0.97+ |
Redis | TITLE | 0.97+ |
one partition | QUANTITY | 0.97+ |
under a minute | QUANTITY | 0.97+ |
@ Uber Scale | ORGANIZATION | 0.96+ |
Jeremy Daly, Serverless Chats | CUBEConversation January 2020
(upbeat music) >> From the Silicon Angle Media office in Boston, Massachusetts, it's theCube. Now, here's your host, Stu Miniman. >> Hi, I'm Stu Miniman, and welcome to the first interview of theCube in our Boston area studio for 2020. And to help me kick it off, Jeremy Daly who is the host of Serverless Chats as well as runs the Serverless Day Boston. Jeremy, saw you at reInvent, way back in 2019, and we'd actually had some of the people in the community that were like hey, "I think you guys like actually live and work right near each other." >> Right. >> And you're only about 20 minutes away from our office here, so thanks so much for making the long journey here, and not having to get on a plane to join us here. >> Well, thank you for having me. >> All right, so as Calvin from Calvin and Hobbes says, "It's a new decade, but we don't have any base on the moon, "we don't have flying cars that general people can use, "but we do have serverless." >> And our robot vacuum cleaners. >> We do have robot vacuum cleaners. >> Which are run by serverless, as a matter of fact. >> A CUBE alum on the program would be happy that we do get to mention there. So yeah, you know serverless there are things like the iRobot, as well as Alexa, or some of the things that people, you know usually when I'm explaining to people what this is, and they don't understand it, it's like, Oh, you've used Alexa, well those are the functions underneath, and you think about how these things turn on, and off, a little bit like that. But maybe, we don't need to get into the long ontological discussion or everything, but you know you're a serverless hero, so you know give us a little bit, what your hearing from people, what are some of the exciting use cases out there, and you know where serverless is being used in that maturity today. >> Yeah, I mean well, so the funny thing about serverless and the term serverless itself, and I do not want to get into a long discussion about this, obviously. I actually wrote a post last year that was called stop calling everything serverless, because basically people are calling everything serverless. So it really, what it, what I look at it as, is something where, it just makes it really easy for developers to abstract away that back end infrastructure, and not having to worry about setting up Kubernetes, or going through the process of setting up virtual machines and installing software is just, a lot of that stuff is kind of handled for you. And I think that is enabled, a lot of companies, especially start-ups is a huge market for serverless, but also enterprises. Enabled them to give more power to their developers, and be able to look at new products that they want to build, new services they want to tackle or even old services that they need to, you know that may have some stability issues or things like long running ETL tasks, and other things like that, that they found a way to sort of find the preferal edges of these monolithic applications or these mainframes that they are using and find ways to run very small jobs, you know using functions as a server, something like that. And so, I see a lot of that, I think that is a big use case. You see a lot of large companies doing. Obviously, people are building full fledged applications. So, yes, the web facing user application, certainly a thing. People are building API's, you got API Gateway, they just released the new HEDP API which makes it even faster. To run those sort of things, this idea of cold starts, you know in AWS trying to get rid of all that stuff, with the new VPC networking, and some of the things they are doing there. So you have a lot of those type of applications that people are building as well. But it really runs the gambit, there are things all across the board that you can do, and pretty much anything you can do with the traditional computing environment, you can do with a serverless computing environment. And obviously that's focusing quite a bit on the functions as a service side of things, which is a very tiny part of serverless, if you want to look at it, you know sort of the broader picture, this service full or managed services, type approach. And so, that's another thing that you see, where you used to have companies setting up you know, mySQL databases and clusters trying to run these things, or even worse, Cassandra rings, right. Trying to do these things and manage this massive amount of infrastructure, just so that they could write a few records to a database and read them back for their application. And that would take months sometimes, for them to get it setup and even more time to try to keep running them. So this sort of revolution of managed services and all these things we get now, whether that the things like managed elastic search or elastic search cloud doing that stuff for you, or Big Table and Dynamo DB, and Manage Cassandra, whatever those things are. I'm just thinking a lot easier for developers to just say hey, I need a database, and okay, here it is, and I don't have to worry about the infrastructure at all. So, I think you see a lot of people, and a lot of companies that are utilizing all of these different services now, and essentially are no longer trying to re-invent the wheel. >> So, a couple of years ago, I was talking to Andy Jassy, at an interview with theCube, and he said, "If I was to build AWS today, "I would've built it on serverless." And from what I've seen over the last two or three years or so, Amazon is rebuilding a lot of there servers underneath. It's very interesting to watch that platform changing. I think it's had some ripple effect dynamics inside the company 'cause Amazon is very well known for their two pizza teams and for all of their products are there, but I think it was actually in a conversation with you, we're talking about in some ways this new way of building things is, you know a connecting fabric between the various groups inside of Amazon. So, I love your view point that we shouldn't just call everything serverless, but in many ways, this is a revolution and a new way of thinking about building things and therefore, you know there are some organizational and dynamical changes that happen, for an Amazon, but for other people that start using it. >> Yeah, well I mean I actually was having a conversation with a Jay Anear, whose one of the product owners for Lambda, and he was saying to me, well how do we sell serverless. How do we tell people you know this is what the next way to do things. I said, just, it's the way, right. And Amazon is realized this, and part of the great thing about dog fooding your own product is that you say, okay I don't like the taste of this bit, so we're going to change it to make it work. And that's what Amazon has continued to do, so they run into limitations with serverless, just like us early adopters, run into limitations, and they say, we'll how do we make it better, how do we fix it. And they have always been really great to listening to customers. I complain all the time, there's other people that complain all the time, that say, "Hey, I can't do this." And they say, "Well what if we did it this way, and out of that you get things like Lambda Destinations and all different types of ways, you get Event Bridge, you get different ways that you can solve those problems and that comes out of them using their own services. So I think that's a huge piece of it, but that helps enable other teams to get past those barriers as well. >> Jeremy, I'm going to be really disappointed if in 2020, I don't see a T-shirt from one of the Serverless Days, with the Mandalorian on it, saying, "Serverless, this is the way." Great, great, great marketing opportunity, and I do love that, because some of the other spaces, you know we're not talking about a point product, or a simple thing we do, it is more the way of doing things, it's just like I think about Cybersecurity. Yes, there are lots of products involved here but, you know this is more of you know it's a methodology, it needs to be fully thought of across the board. You know, as to how you do things, so, let's dig in a little bit. At reInvent, there was, when I went to the serverless gathering, it was serverless for everyone. >> Serverless for everyone, yes. >> And there was you know, hey, serverless isn't getting talked, you know serverless isn't as front and center as some people might think. They're some people on the outside look at this and they say, "Oh, serverless, you know those people "they have a religion, and they go so deep on this." But I thought Tim Wagner had a really good blog post, that came out right after reInvent, and what we saw is not only Amazon changing underneath the way things are done, but it feel that there's a bridging between what's happening in Kubernetes, you see where Fargate is, Firecracker, and serverless and you know. Help us squint through that, and understand a little bit, what your seeing, what your take was at reInvent, what you like, what you were hoping to see and how does that whole containerization, and Kubernetes wave intersect with what we're doing with serverless? >> Yeah, well I mean for some reason people like Kubernetes. And I honestly, I don't think there is anything wrong with it, I think it's a great container orchestration system, I think containers are still a very important part of the workloads that we are putting into a cloud, I don't know if I would call them cloud native, exactly, but I think what we're seeing or at least what I'm seeing that I think Amazon is seeing, is they're saying people are embracing Kubernetes, and they are embracing containers. And whether or not containers are ephemeral or long running, which I read a statistic at some point, that was 63% of containers, so even running on Kubernetes, or whatever, run for less than 10 minutes. So basically, most computing that's happening now, is fairly ephemeral. And as you go up, I think it's 15 minutes or something like that, I think it's 70% or 90% or whatever that number is, I totally got that wrong. But I think what Amazon is doing is they're trying to basically say, look we were trying to sell serverless to everyone. We're trying to sell this idea of look managed services, managed compute, the idea that we can run even containers as close to the metal as possible with something like Fargate which is what Firecracker is all about, being able to run virtual machines basically, almost you know right on the metal, right. I mean it's so close that there's no level of abstraction that get in the way and slow things down, and even though we're talking about milliseconds or microseconds, it's still something and there's efficiencies there. But I think what they looked at is, they said look at we are not Apple, we can't kill Flash, just because we say we're not going to support it anymore, and I think you mention this to me in the past where the majority of Kubernetes clusters that were running in the Public Cloud, we're running in Amazon anyways. And so, you had using virtual machines, which are great technology, but are 15 years old at this point. Even containerization, there's more problems to solve there, getting to the point where we say, look you want to take this container, this little bit of code, or this small service and you want to just run this somewhere. Why are we spinning up virtual containers. Why are we using 15 or 10 year old technology to do that. And Amazon is just getting smarter about it. So Amazon says hay, if we can run a Lambda function on Firecracker, and we can run a Fargate container on Firecracker, why can't we run, you know can we create some pods and run some pods for Kubernetes on it. They can do that. And so, I think for me, I was disappointed in the keynotes, because I don't think there was enough serverless talk. But I think what they're trying to do, is there trying to and this is if I put my analyst hat on for a minute. I think they're trying to say, the world is at Kubernetes right now. And we need to embrace that in a way, that says we can run your Kubernetes for you, a lot more efficiently and without you having to worry about it than if you use Google or if you use some other cloud provider, or if you run on-prem. Which I think is the biggest competitor to Amazon is still on-prem, especially in the enterprise world. So I see them as saying, look we're going to focus on Kubernetes, but as a way that we can run it our way. And I think that's why, Fargate and Kubernetes, or the Kubernetes for Fargate, or whatever that new product is. Too many product names at AWS. But I think that's what they are trying to do and I think that was the point of this, is to say, "Listen you can run your Kubernetes." And Claire Legore who showed that piece at the keynote, Vernor's keynote that was you know basically how quickly Fargate can scale up Kubernetes, you know individual containers, Kubernetes, as opposed to you know launching new VM's or EC2 instances. So I thought that was really interesting. But that was my overall take is just that they're embracing that, because they think that's where the market is right now, and they just haven't yet been able to sell this idea of serverless even though you are probably using it with a bunch of things anyways, at least what they would consider serverless. >> Yeah, to part a little bit from the serverless for a second. Talk about multi-cloud, it was one of the biggest discussions, we had in 2019. When I talk to customers that are using Kubernetes, one of the reasons that they tell me they're doing it, "Well, I love Amazon, I really like what I'm doing, "but if I needed to move something, it makes it easier." Yes, there are some underlying services I would have to re-write, and I'm looking at all those. I've talked to customers that started with Kubernetes, somewhere other than Amazon, and moved it to Amazon, and they said it did make my life easier to be able to do that fundamental, you know the container piece was easy move that piece of it, but you know the discussion of multi-cloud gets very convoluted, very easily. Most customers run it when I talk to them, it's I have an application that I run, in a cloud, sometimes, there's certain, you know large financials will choose two of everything, because that's the way they've always done things for regulation. And therefore they might be running the same application, mirrored in two different clouds. But it is not follow the sun, it is not I wake up and I look at the price of things, and deploy it to that. And that environment it is a little bit tougher, there's data gravity, there's all these other concerns. But multi-cloud is just lots of pieces today, more than a comprehensive strategy. The vision that I saw, is if multi-cloud is to be a successful strategy, it should be more valuable than the sum of its pieces. And I don't see many examples of that yet. What do you see when it comes to multi-cloud and how does that serverless discussion fit in there? >> I think your point about data gravity is the most important thing. I mean honestly compute is commoditized, so whether your running it in a container, and that container runs in Fargate or orchestrated by Kubernetes, or runs on its own somewhere, or something's happening there, or it's a fast product and it's running on top of K-native or it's running in a Lambda function or in an Azure function or something like that. Compute itself is fairly commoditized, and yes there's wiring that's required for each individual cloud, but even if you were going to move your Kubernetes cluster, like you said, there's re-writes, you have to change the way you do things underneath. So I look at multi-cloud and I think for a large enterprise that has a massive amount of compliance, regulations and things like that they have to deal with, yeah maybe that's a strategy they have to embrace, and hopefully they have the money and tech staff to do that. I think the vast majority of companies are going to find that multi-cloud is going to be a completely wasteful and useless exercise that is essentially going to waste time and money. It's so hard right now, keeping up with everything new that comes out of one cloud right, try keeping up with everything that comes out of three clouds, or more. And I think that's something that doesn't make a lot of sense, and I don't think you're going to see this price gauging like we would see with something. Probably the wrong term to use, but something that we would see, sort of lock-in that you would see with Oracle or with Microsoft SQL, some of those things where the licensing became an issue. I don't think you're going to see that with cloud. And so, what I'm interested in though in terms of the term multi-cloud, is the fact that for me, multi-cloud really where it would be beneficial, or is beneficial is we're talking about SaaS vendors. And I look at it and I say, look it you know Oracle has it's own cloud, and Google has it's own cloud, and all these other companies have their own cloud, but so does Salesforce, when you think about it. So does Twilio, even though Twilio runs inside AWS, really its I'm using that service and the AWS piece of it is abstracted, that to me is a third party service. Stripe is a third-party service. These are multi-cloud structure or SaaS products that I'm using, and I'm going to be integrating with all those different things via API's like we've done for quite some time now. So, to me, this idea of multi-cloud is simply going to be, you know it's about interacting with other products, using the right service for the right job. And if your duplicating your compute or you're trying to write database services or something like that that you can somehow share with multiple clouds, again, I don't see there being a huge value, except for a very specific group of customers. >> Yeah, you mentioned the term cloud-native earlier, and you need to understand are you truly being cloud-native or are you kind of cloud adjacent, are you leveraging a couple of things, but you're really, you haven't taken advantage of the services and the promise of what these cloud options can offer. All right, Jeremy, 2020 we've turned the calendar. What are you looking at, you know you're planning, you got serverless conference, Serverless Days-- >> Serverless Days Boston. >> Boston, coming up-- >> April 6th in Cambridge. >> So give us a little views to kind of your view point for the year, the event itself, you got your podcast, you got a lot going on. >> Yeah, so my podcast, Serverless Chats. You know I talk to people that are in the space, and we usually get really really technical. So if you're a serverless geek or you like that kind of stuff definitely listen to that. But yeah, but 2020 for me though, this is where I see what is happened to serverless, and this goes back to my "Stop calling everything serverless" post, was this idea that we keep making serverless harder. And so, as a someone whose a serverless purist, I think at this point. I recognize and it frustrates me that it is so difficult now to even though we're abstracting away running that infrastructure, we still have to be very aware of what pieces of the infrastructure we are using. Still have setup the SQS Queue, still have to setup Event Bridge. We still have to setup the Lambda function and API gateways and there's services that make it easier for us, right like we can use a serverless framework, or the SAM framework, or ARCH code or architect framework. There's a bunch of these different ones that we can use. But the problem is that it's still very very tough, to understand how to stitch all this stuff together. So for me, what I think we're going to see in 2020, and I know there is hints for this serverless framework just launched their components. There's other companies that are doing similar things in the space, and that's basically creating, I guess what I would call an abstraction as a service, where essentially it's another layer of abstraction, on top of the DSL's like Terraform or Cloud Formation, and essentially what it's doing is it's saying, "I want to launch an API that does X-Y-Z." And that's the outcome that I want. Understanding all the best practices, am I supposed to use Lambda Destinations, do I use DLQ's, what should I throttle it at? All these different settings and configurations and knobs, even though they say that there's not a lot of knobs, there's a lot of knobs that you can turn. Encapsulating that and being able to share that so that other people can use it. That in and of itself would be very powerful, but where it becomes even more important and I think definitely from an enterprise standpoint, is to say, listen we have a team that is working on these serverless components or abstractions or whatever they are, and I want Team X to be able to use, I want them to be able to launch an API. Well you've got security concerns, you've got all kinds of things around compliance, you have what are the vetting process for third-party libraries, all that kind of stuff. If you could say to Team X, hey listen we've got this component, or this piece of, this abstracted piece of code for you, that you can take and now you can just launch an API, serverless API, and you don't have to worry about any of the regulations, you don't have to go to the attorneys, you don't have to do any of that stuff. That is going to be an extremely powerful vehicle for companies to adopt things quickly. So, I think that you have teams now that are experimenting with all of these little knobs. That gets very confusing, it gets very frustrating, I read articles all the time, that come out and I read through it, and this is all out of date, because things have changed so quickly and so if you have a way that your teams, you know and somebody who stays on top of the learning this can keep these things up to date, follow the most, you know leading practices or the best practices, whatever you want to call them. I think that's going to be hugely important step from making it to the teams that can adopt serverless more quickly. And I don't think the major cloud vendors are doing anything in this space. And I think SAM is a good idea, but basically SAM is just a re-write of the serverless framework. Whereas, I think that there's a couple of companies who are looking at it now, how do we take this, you know whatever, this 1500 line Cloud Formation template, how do we boil that down into two or three lines of configuration, and then a little bit of business logic. Because that's where we really want to get to. It's just we're writing business logic, we're no where near there right now. There's still a lot of stuff that has to be done, around configuration and so even though it's nice to say, hey we can just write some business logic and all the infrastructure is handled for us. The infrastructure is handled for us, if we configure it correctly. >> Yeah, really remind me some of the general thread we've been talking about, Cloud for a number of years is, remember back in the early days, is cloud is supposed to be inexpensive and easy to use, and of course in today's world, it isn't either of those things. So serverless needs to follow those threads, you know love some of those view points Jeremy. I want to give you the final word, you've got your Serverless Day Boston, you got your podcast, best way to get in touch with you, and keep up with all you're doing in 2020. >> Yeah, so @Jeremy_daly on Twitter. I'm pretty active on Twitter, and I put all my stuff out there. Serverless Chats podcast, you can just find, serverlesschats.com or any of the Pod catchers that you use. I also publish a newsletter that basically talks about what I'm talking about now, every week called Off by None, which is, collects a bunch of serverless links and gives them some IoPine on some of them, so you can go to offbynone.io and find that. My website is jeremydaly.com and I blog and keep up to date on all the kind of stuff that I do with serverless there. >> Jeremy, great content, thanks so much for joining us on theCube. Really glad and always love to shine a spotlight here in the Boston area too. >> Appreciate it. >> I'm Stu Miniman. You can find me on the Twitter's, I'm just @Stu thecube.net is of course where all our videos will be, we'll be at some of the events for 2020. Look for me, look for our co-hosts, reach out to us if there's an event that we should be at, and as always, thank you for watching theCube. (upbeat music)
SUMMARY :
From the Silicon Angle Media office that were like hey, "I think you guys like actually live and not having to get on a plane to join us here. "we don't have flying cars that general people can use, and you know where serverless is being used that they need to, you know and therefore, you know there are some organizational and out of that you get things like Lambda Destinations You know, as to how you do things, and they say, "Oh, serverless, you know those people and I think you mention this to me in the past and I look at the price of things, and deploy it to that. that you can somehow share with multiple clouds, again, and you need to understand are you truly being cloud-native for the year, the event itself, you got your podcast, and so if you have a way that your teams, I want to give you the final word, serverlesschats.com or any of the Pod catchers that you use. Really glad and always love to shine a spotlight and as always, thank you for watching theCube.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Claire Legore | PERSON | 0.99+ |
15 | QUANTITY | 0.99+ |
Tim Wagner | PERSON | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Jeremy | PERSON | 0.99+ |
2019 | DATE | 0.99+ |
Andy Jassy | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Jeremy Daly | PERSON | 0.99+ |
Boston | LOCATION | 0.99+ |
70% | QUANTITY | 0.99+ |
ORGANIZATION | 0.99+ | |
two | QUANTITY | 0.99+ |
2020 | DATE | 0.99+ |
90% | QUANTITY | 0.99+ |
63% | QUANTITY | 0.99+ |
Cambridge | LOCATION | 0.99+ |
15 minutes | QUANTITY | 0.99+ |
10 year | QUANTITY | 0.99+ |
less than 10 minutes | QUANTITY | 0.99+ |
jeremydaly.com | OTHER | 0.99+ |
Jay Anear | PERSON | 0.99+ |
January 2020 | DATE | 0.99+ |
Calvin | PERSON | 0.99+ |
April 6th | DATE | 0.99+ |
Apple | ORGANIZATION | 0.99+ |
last year | DATE | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
offbynone.io | OTHER | 0.99+ |
three lines | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
serverlesschats.com | OTHER | 0.99+ |
Boston, Massachusetts | LOCATION | 0.99+ |
Lambda | ORGANIZATION | 0.98+ |
two different clouds | QUANTITY | 0.98+ |
@Jeremy_daly | PERSON | 0.98+ |
Twilio | ORGANIZATION | 0.98+ |
three clouds | QUANTITY | 0.98+ |
Kubernetes | TITLE | 0.98+ |
today | DATE | 0.97+ |
about 20 minutes | QUANTITY | 0.97+ |
1500 line | QUANTITY | 0.97+ |
first interview | QUANTITY | 0.96+ |
two pizza teams | QUANTITY | 0.96+ |
Lambda | TITLE | 0.96+ |
one cloud | QUANTITY | 0.96+ |
Alexa | TITLE | 0.96+ |
theCube | ORGANIZATION | 0.95+ |
Azure | TITLE | 0.94+ |
each individual cloud | QUANTITY | 0.94+ |
Serverless Days | EVENT | 0.93+ |
Big Table | ORGANIZATION | 0.93+ |
Joe CaraDonna & Bob Ganley, Dell EMC | AWS re:Invent 2019
(upbeat music) >> Announcer: Live from Las Vegas, it's theCUBE. Covering AWS re:Invent 2019, brought to you by Amazon Web Services and Intel, along with it's Ecosystem partners. >> Good morning, welcome back to theCUBE, Lisa Martin live at AWS re:Invent. Day two of theCUBEs coverage. I am with Stu Miniman, and Stu and I are pleased to welcome a couple of guests of our own from Dell EMC. To my left is Joe CaraDonna, the VP of engineering technology. Welcome to theCUBE. >> Good to be here. >> And then one of our alumni, we've got Bob Ganley, senior consultant Cloud product marketing. Welcome back. >> Thank you. Glad to be here. >> So guys, here we are at AWS re:Invent, with 60 plus thousand people all over the strip here. We know Dell technologies, Dell EMC well, big friends of theCUBE. Joe, Dell, AWS, what's going on? You guys are here. >> Apparently Cloud is a thing. >> Lisa: I heard that. I think I've seen the sticker. >> Yeah, you've seen the sticker. Over the last year, we've been busy rolling out new Cloud services. I mean, look around right. It's important to our customers that we can deliver hybrid Cloud solutions to them, that are meaningful to them and to help them get their workloads to the Cloud. and to be able to migrate, move between Clouds and data center. >> Yeah, Joe, maybe expand a little on this. So we watched when VMware made the partnership announcement with AWS a couple of years ago, which sent ripples through the industry. And VMware has had a large presence at this show, we've seen a lot of announcements and movements with Dell, Dell technologies, Dell EMC over the last year or more, but this is the first year that Dell's actually exhibiting here so help explain for our audience a little bit that dynamic with leveraging VMware and also what Dell is bringing to this ecosystem. >> Yeah, sure. I mean, the way we think about it is, it's really a multi-level stack, you have the application layer and you've got the data layer. So applications with VMware, we're focusing on enabling applications, whether they're VMs or containerized now, being able to move those to the Cloud, move them on-prem. Same is true for data. And data is actually the harder part of the problem, in my opinion, all right, because data has gravity. It's just big, it's hard to move, the principles of data in the Cloud are the same as they are on-prem where you still have to provide the high availability and the accessibility and the security and the capacity and scale in the Cloud as you would in the data center. And what we've been doing here, with our Cloud storage services is bringing essentially our range as a service, to the Cloud. >> You talked about some of those changes and absolutely, data's at the center of everything. We've been saying for a long time, you talk about digital transformation, the outcome of that is if you're not letting data drive your decisions, you really haven't been successful there. One of the biggest challenges beyond data, is the applications. Customers have hundreds, if not thousands of applications, they're building new ones, they're migrating, they're breaking them apart in to micro services, Bob, help us understand where that intersects with what you're talking with customers about. >> Yeah, absolutely. So one of the reasons we're here is most organizations today are leveraging some public Cloud services and at the same time, most organizations have investment on-prem infrastructure. I think we heard Andy say in the keynote yesterday, 97% of all enterprise IT spend is on-prem right now. So organizations are trying to figure out how to make those work together. And that's really what we're here to do, is help organizations figure out how to make their big on-prem investment work well with their public Cloud investment and AWS is clearly the leader there in that space and so we're here to work with our customers in order to help them really bridge that gap between public Cloud and private Cloud and make them work together well. >> And Bob, where does that conversation start? Because one of the other things that Andy talked about is that, his four essentials for transformation is it's got to start at the senior executive level, strategic vision that's aggressively pushed down throughout the organization. Are you now having conversations at that CEO level for them to really include this value of data and apps as part of an overall business transformation? >> Yeah, definitely. If you think about it, it's all about people, process and technology. And technology is only a small part of it. And I think that's the important thing about what Andy was saying in the keynote yesterday, is that it's about making sure that Cloud as an operating model, not as a place, but as an operating model, gets adopted across your organization. And that has to have senior leadership investment. Yeah, they have to be invested in this move, but both from an applications and a data perspective. >> Yeah and on the technology side of things, you want to be able to give the developers the tools they need so they can develop those Cloud native applications. So in the on-prem sphere, we have ECS or objects stored kind of technology for bringing an object to data center. We're plugging into kubernetes every which way. With VMware, we're developing CSI drivers across our storage portfolio to be able to plug in to these kubernetes environments. And we're enabling for data and application migration across environments, as well. >> In many ways, Joe, we've seen, there's a really disaggregation of how people build things. When I talk to the developer community, hybrid is the model that many of them are using, but it used to be nice in the old days as, I bought a box and it had all the feature checklist that I wanted. Now, I need to put together all these micro services. So help us understand some of those services that you provide everywhere. >> It's a horror, right? What did Andy Jassy say yesterday, these are your father's data requirements, right? And he's right about that because what's happening with data is it's sprawling. You have them in data centers, you have them in Cloud, you have them in multiple Clouds, you have them in SaaS portals, you have it on file services and blog services, and how do you wrap your arms around that? And especially when you start looking at use cases like data analytics and you start thinking about data sets, how do you manage data sets? Maybe I had my data born on-prem and I want to do my analytics in the Cloud, how do I even wrap my hands around data sets? So we have a product called ClarityNow, that in fact does that. It indexes billions of files and objects across our storage, across our Cloud services, across Amazon S3, across third party NAS systems as well, and you can get a single pane of glass to see where your files and your objects reside. You can tag it, you can search upon it, you can create data sets based on search, on your tags and your meta data, to then operate on those data sets. So the rules, data's being used in new and different ways, they need new ways to manage it and these are some of the solutions that we're bringing to market. >> You mentioned Multicloud, I wanted to chat about that. We know it's not a word that AWS likes. >> Joe: Can we say that here? >> Yeah. >> On theCUBE, absolutely. >> This is theCUBE, exactly. But the reality is, as we talked to, and Stu knows as well, most CIO's say, we've inherited this mess, of Multicloud, often symptomatically, not as a strategic direction, give us an overview of what Dell EMC, I'll ask you both the same question, and Joe we'll start with you, how are you helping customers address, whether they've inherited Multicloud through M&A acquisition, or developer choice, how do they really extract value from that data, that they know, there's business insights in here that can allow us to differentiate our business, but we have all of this sprawl. What's the answer for that? >> Well some of that is ClarityNow, that I was talking about, the ability to see your data, because half the battle is seeing your data, being able to see it. Also, with Multicloud, whether you inherit it, or whether it was intentional or not, we're setting out our solutions are Multicloud, you can run them anywhere. But not only that, the twist to Multicloud is, well what if you made your data available to multiple clouds simultaneously. And why would you want to do that? One reason we want to go that path is maybe you want to use the best services from each Cloud. But you don't want to move your data around because again it has gravity and it takes time and money and resources to do that. Through our Cloud Storage Services, it's centralized, and you can attach to whatever Cloud you want. So some of that is around taking advantage of that, some of that's around data brokering, we heard Andy talk a little bit about that this morning, where you may have data sets that you want to sell to your customers and they may be running in other Clouds. And some of that is, you may want to switch Clouds due to the services they have, the economics or perhaps even the requirements of your applications. >> Yeah, from an application perspective, for us it's really about consistency, right. So we say it's consistency in two ways, consistent infrastructure and consistent operations. And so we talk about consistent infrastructure, we want to help organizations be able to take that virtual machine and move it. Where is the best place for it, right? So it's about right workload, right Cloud. And we talk about application portfolio analysis and helping organizations figure out, what is that set of applications that they have? What should they do with those applications? Which ones are right to move to Cloud? Which ones should they not invest in and kind of let retire? And so that's another aspect of that people and process thing that we talked about earlier. Helping organizations look at that application portfolio and then take that consistent infrastructure, use that multiple Clouds with that, and then consistent operations which is a single management control plane that can help you have consistency between the way you run your on-prem and the way you run your public Cloud. >> Yeah and give them the freedom to choose the Cloud they want for the workload they want. >> And is that the data level where the differences between, we'll say the public Cloud files, is most exposed? Is it at the data layer where the differences in, we'll say AWS versus it's competitors, is that where the differences between the features and the functionalities is most exposed? >> I think so. I think that one place that we think public Cloud is weak, is file. File workloads. And one of the things we're trying to do is bring consistent file, whether it's on-prem or across the Clouds, through with our Cloud Storage Services at Isilon and the scale and the throughput that those systems can provide, bringing consistent file services, whether it's NFS, SNB or even HDFS or the snapshotting capabilities. And as equally as important, that native replication capabilities across these environments. >> I wonder if we could talk a little bit about some of the organizational changes, the transformation was one of the key takeaways that Andy Jassy was talking about in his three hour keynote yesterday. We've watched for more than a decade now, the role of IT compared to the business, and we know that it's not only does IT need to respond to the business but that data discussion we have better be driving the business, because if you're not leveraging your data, your competition definitely will. I want to get your opinion as to just the positions of power and who you're talking to and what are some of the successful companies doing to help lead this type of change. >> I'll go. I think IT and business are coming together more, the lines are blurring there. And IT's being stretched in to new directions now, they have to serve customers with new demands. So whether it's managing storage or AIs or servers, or VMware environments now being pushed in to things like now managing analytics, kind of environment, right? And all the tools associated with that. Whether it's Cassandra or TetraFlow, being able to stretch, and being able to provide the kind of services that the business requires. >> And up the stack too. >> Yeah. When you talk about the fact that business and IT need to work together, it's kind of like an obvious statement, right? What that really means is, that there needs to be a way to help organizations get to responding more quickly to what the needs of the business are. It's about agility. It's about the ability to respond quickly. So you see organizations moving from waterfall process for development to Agile and you see that being supported by Cloud native architectures, and organizations need to take and be able to do that in a way that preserves the investments that they have today. So most organizations are on this journey from physical to virtual to infrastructure as a service, to container as a service and beyond and they don't want to throw away those investments that they have in existing virtualization, in existing skill sets, and so what we're really doing is helping organizations move to that place where they can adopt Cloud Native while bringing forward those investments they have in traditional infrastructure. So we think that's helping organizations work better together, both from a technology and a business perspective. >> And as far as the kind of people we talk to, I mean data science is growing and growing, data science is becoming more part of the conversation. CIO's as well, right? I mean behind all this, again, is that data that we keep coming back to. You have to ensure the governance of that data, right? That it's being controlled and it's within compliance. >> So we started off the conversation talking about that this was Dell's first year. So 60, 65,000 here. There's a sprawling ecosystem. One of the largest ones here. What do you want to really emphasize? Give us the final takeaway as to how people should think about Dell Technologies in the Cloud ecosystem. >> Yeah, I think, we know our customers want to be able to leverage the Cloud, the kind of conversation we're having with customers is more around, how can I use the Cloud to optimize my business? And that's going to vary on a workload by workload basis. We feel it's our job to arm the customer with the tools they need, right? To be able to have hybrid Cloud architectures, to be able to have the freedom to run the applications wherever they want, consume infrastructure in a way they want it to be consumed, and we're there for them. >> Yeah, I think it's really about a couple of things. One is trust, and the other one is choice. So if you think about it, organizations need to move in to this Cloud world in a way that brings forward those investments that they've made. Dell EMC is the number one provider of hyper-converged infrastructure, of servers, and we can help organizations understand that Cloud operating model, and how to bring the private Cloud investments that they have today forward to work well with the public Cloud investments that they're making, clearly. So it's really about trust and choice of how they implement. >> Trust is a big deal. >> Absolutely. >> I mean, we're the number one storage vendor for a reason. Our customers trust us with their data. >> Well Joe, Bob, thank you so much for joining me and Stu on theCUBE. >> Thank you. >> Thank you. >> And sharing with us what you guys are doing at Dell, AWS. The trust and the choice that you're delivering to your customers, we'll see you at Dell Technologies World. >> We'll see you here next year. >> All right. You got it. All right. For our guests and for Stu Miniman, I'm Lisa Martin and you're watching theCUBE, day two of our coverage of AWS re:Invent '19. Thanks for watching. (upbeat, title music)
SUMMARY :
brought to you by Amazon Web Services and Stu and I are pleased to welcome And then one of our alumni, we've got Bob Ganley, Glad to be here. So guys, here we are at AWS re:Invent, I think I've seen the sticker. and to be able to migrate, over the last year or more, And data is actually the harder part of the problem, and absolutely, data's at the center of everything. and AWS is clearly the leader there in that space is it's got to start at the senior executive level, And that has to have senior leadership investment. Yeah and on the technology side of things, and it had all the feature checklist that I wanted. and how do you wrap your arms around that? I wanted to chat about that. But the reality is, as we talked to, and Stu knows as well, the ability to see your data, and the way you run your public Cloud. Yeah and give them the freedom to choose and the scale and the throughput the role of IT compared to the business, and being able to provide the kind of services It's about the ability to respond quickly. And as far as the kind of people we talk to, One of the largest ones here. the kind of conversation we're having with customers and how to bring the private Cloud investments Our customers trust us with their data. thank you so much for joining me and Stu on theCUBE. And sharing with us what you guys are doing at Dell, AWS. I'm Lisa Martin and you're watching theCUBE,
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Lisa Martin | PERSON | 0.99+ |
Andy | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Bob Ganley | PERSON | 0.99+ |
Andy Jassy | PERSON | 0.99+ |
Stu | PERSON | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
Joe | PERSON | 0.99+ |
Amazon Web Services | ORGANIZATION | 0.99+ |
Joe CaraDonna | PERSON | 0.99+ |
Dell | ORGANIZATION | 0.99+ |
VMware | ORGANIZATION | 0.99+ |
Lisa | PERSON | 0.99+ |
hundreds | QUANTITY | 0.99+ |
Bob | PERSON | 0.99+ |
Isilon | ORGANIZATION | 0.99+ |
yesterday | DATE | 0.99+ |
97% | QUANTITY | 0.99+ |
Intel | ORGANIZATION | 0.99+ |
next year | DATE | 0.99+ |
Las Vegas | LOCATION | 0.99+ |
one | QUANTITY | 0.99+ |
last year | DATE | 0.99+ |
One reason | QUANTITY | 0.98+ |
60, 65,000 | QUANTITY | 0.98+ |
Dell EMC | ORGANIZATION | 0.98+ |
both | QUANTITY | 0.98+ |
two ways | QUANTITY | 0.98+ |
Amazon | ORGANIZATION | 0.98+ |
each Cloud | QUANTITY | 0.97+ |
One | QUANTITY | 0.97+ |
Multicloud | ORGANIZATION | 0.97+ |
first year | QUANTITY | 0.97+ |
today | DATE | 0.96+ |
60 plus thousand people | QUANTITY | 0.96+ |
Cloud | TITLE | 0.95+ |
Cloud Native | TITLE | 0.95+ |
single | QUANTITY | 0.94+ |
this morning | DATE | 0.93+ |
four essentials | QUANTITY | 0.92+ |
ClarityNow | ORGANIZATION | 0.92+ |
Day two | QUANTITY | 0.91+ |
S3 | TITLE | 0.91+ |
billions of files | QUANTITY | 0.91+ |
Cassandra | TITLE | 0.9+ |