Breaking Analysis: Grading our 2022 Enterprise Technology Predictions
>>From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from the cube and E T R. This is breaking analysis with Dave Valante. >>Making technology predictions in 2022 was tricky business, especially if you were projecting the performance of markets or identifying I P O prospects and making binary forecast on data AI and the macro spending climate and other related topics in enterprise tech 2022, of course was characterized by a seesaw economy where central banks were restructuring their balance sheets. The war on Ukraine fueled inflation supply chains were a mess. And the unintended consequences of of forced march to digital and the acceleration still being sorted out. Hello and welcome to this week's weekly on Cube Insights powered by E T R. In this breaking analysis, we continue our annual tradition of transparently grading last year's enterprise tech predictions. And you may or may not agree with our self grading system, but look, we're gonna give you the data and you can draw your own conclusions and tell you what, tell us what you think. >>All right, let's get right to it. So our first prediction was tech spending increases by 8% in 2022. And as we exited 2021 CIOs, they were optimistic about their digital transformation plans. You know, they rushed to make changes to their business and were eager to sharpen their focus and continue to iterate on their digital business models and plug the holes that they, the, in the learnings that they had. And so we predicted that 8% rise in enterprise tech spending, which looked pretty good until Ukraine and the Fed decided that, you know, had to rush and make up for lost time. We kind of nailed the momentum in the energy sector, but we can't give ourselves too much credit for that layup. And as of October, Gartner had it spending growing at just over 5%. I think it was 5.1%. So we're gonna take a C plus on this one and, and move on. >>Our next prediction was basically kind of a slow ground ball. The second base, if I have to be honest, but we felt it was important to highlight that security would remain front and center as the number one priority for organizations in 2022. As is our tradition, you know, we try to up the degree of difficulty by specifically identifying companies that are gonna benefit from these trends. So we highlighted some possible I P O candidates, which of course didn't pan out. S NQ was on our radar. The company had just had to do another raise and they recently took a valuation hit and it was a down round. They raised 196 million. So good chunk of cash, but, but not the i p O that we had predicted Aqua Securities focus on containers and cloud native. That was a trendy call and we thought maybe an M SS P or multiple managed security service providers like Arctic Wolf would I p o, but no way that was happening in the crummy market. >>Nonetheless, we think these types of companies, they're still faring well as the talent shortage in security remains really acute, particularly in the sort of mid-size and small businesses that often don't have a sock Lacework laid off 20% of its workforce in 2022. And CO C e o Dave Hatfield left the company. So that I p o didn't, didn't happen. It was probably too early for Lacework. Anyway, meanwhile you got Netscope, which we've cited as strong in the E T R data as particularly in the emerging technology survey. And then, you know, I lumia holding its own, you know, we never liked that 7 billion price tag that Okta paid for auth zero, but we loved the TAM expansion strategy to target developers beyond sort of Okta's enterprise strength. But we gotta take some points off of the failure thus far of, of Okta to really nail the integration and the go to market model with azero and build, you know, bring that into the, the, the core Okta. >>So the focus on endpoint security that was a winner in 2022 is CrowdStrike led that charge with others holding their own, not the least of which was Palo Alto Networks as it continued to expand beyond its core network security and firewall business, you know, through acquisition. So overall we're gonna give ourselves an A minus for this relatively easy call, but again, we had some specifics associated with it to make it a little tougher. And of course we're watching ve very closely this this coming year in 2023. The vendor consolidation trend. You know, according to a recent Palo Alto network survey with 1300 SecOps pros on average organizations have more than 30 tools to manage security tools. So this is a logical way to optimize cost consolidating vendors and consolidating redundant vendors. The E T R data shows that's clearly a trend that's on the upswing. >>Now moving on, a big theme of 2020 and 2021 of course was remote work and hybrid work and new ways to work and return to work. So we predicted in 2022 that hybrid work models would become the dominant protocol, which clearly is the case. We predicted that about 33% of the workforce would come back to the office in 2022 in September. The E T R data showed that figure was at 29%, but organizations expected that 32% would be in the office, you know, pretty much full-time by year end. That hasn't quite happened, but we were pretty close with the projection, so we're gonna take an A minus on this one. Now, supply chain disruption was another big theme that we felt would carry through 2022. And sure that sounds like another easy one, but as is our tradition, again we try to put some binary metrics around our predictions to put some meat in the bone, so to speak, and and allow us than you to say, okay, did it come true or not? >>So we had some data that we presented last year and supply chain issues impacting hardware spend. We said at the time, you can see this on the left hand side of this chart, the PC laptop demand would remain above pre covid levels, which would reverse a decade of year on year declines, which I think started in around 2011, 2012. Now, while demand is down this year pretty substantially relative to 2021, I D C has worldwide unit shipments for PCs at just over 300 million for 22. If you go back to 2019 and you're looking at around let's say 260 million units shipped globally, you know, roughly, so, you know, pretty good call there. Definitely much higher than pre covid levels. But so what you might be asking why the B, well, we projected that 30% of customers would replace security appliances with cloud-based services and that more than a third would replace their internal data center server and storage hardware with cloud services like 30 and 40% respectively. >>And we don't have explicit survey data on exactly these metrics, but anecdotally we see this happening in earnest. And we do have some data that we're showing here on cloud adoption from ET R'S October survey where the midpoint of workloads running in the cloud is around 34% and forecast, as you can see, to grow steadily over the next three years. So this, well look, this is not, we understand it's not a one-to-one correlation with our prediction, but it's a pretty good bet that we were right, but we gotta take some points off, we think for the lack of unequivocal proof. Cause again, we always strive to make our predictions in ways that can be measured as accurate or not. Is it binary? Did it happen, did it not? Kind of like an O K R and you know, we strive to provide data as proof and in this case it's a bit fuzzy. >>We have to admit that although we're pretty comfortable that the prediction was accurate. And look, when you make an hard forecast, sometimes you gotta pay the price. All right, next, we said in 2022 that the big four cloud players would generate 167 billion in IS and PaaS revenue combining for 38% market growth. And our current forecasts are shown here with a comparison to our January, 2022 figures. So coming into this year now where we are today, so currently we expect 162 billion in total revenue and a 33% growth rate. Still very healthy, but not on our mark. So we think a w s is gonna miss our predictions by about a billion dollars, not, you know, not bad for an 80 billion company. So they're not gonna hit that expectation though of getting really close to a hundred billion run rate. We thought they'd exit the year, you know, closer to, you know, 25 billion a quarter and we don't think they're gonna get there. >>Look, we pretty much nailed Azure even though our prediction W was was correct about g Google Cloud platform surpassing Alibaba, Alibaba, we way overestimated the performance of both of those companies. So we're gonna give ourselves a C plus here and we think, yeah, you might think it's a little bit harsh, we could argue for a B minus to the professor, but the misses on GCP and Alibaba we think warrant a a self penalty on this one. All right, let's move on to our prediction about Supercloud. We said it becomes a thing in 2022 and we think by many accounts it has, despite the naysayers, we're seeing clear evidence that the concept of a layer of value add that sits above and across clouds is taking shape. And on this slide we showed just some of the pickup in the industry. I mean one of the most interesting is CloudFlare, the biggest supercloud antagonist. >>Charles Fitzgerald even predicted that no vendor would ever use the term in their marketing. And that would be proof if that happened that Supercloud was a thing and he said it would never happen. Well CloudFlare has, and they launched their version of Supercloud at their developer week. Chris Miller of the register put out a Supercloud block diagram, something else that Charles Fitzgerald was, it was was pushing us for, which is rightly so, it was a good call on his part. And Chris Miller actually came up with one that's pretty good at David Linthicum also has produced a a a A block diagram, kind of similar, David uses the term metacloud and he uses the term supercloud kind of interchangeably to describe that trend. And so we we're aligned on that front. Brian Gracely has covered the concept on the popular cloud podcast. Berkeley launched the Sky computing initiative. >>You read through that white paper and many of the concepts highlighted in the Supercloud 3.0 community developed definition align with that. Walmart launched a platform with many of the supercloud salient attributes. So did Goldman Sachs, so did Capital One, so did nasdaq. So you know, sorry you can hate the term, but very clearly the evidence is gathering for the super cloud storm. We're gonna take an a plus on this one. Sorry, haters. Alright, let's talk about data mesh in our 21 predictions posts. We said that in the 2020s, 75% of large organizations are gonna re-architect their big data platforms. So kind of a decade long prediction. We don't like to do that always, but sometimes it's warranted. And because it was a longer term prediction, we, at the time in, in coming into 22 when we were evaluating our 21 predictions, we took a grade of incomplete because the sort of decade long or majority of the decade better part of the decade prediction. >>So last year, earlier this year, we said our number seven prediction was data mesh gains momentum in 22. But it's largely confined and narrow data problems with limited scope as you can see here with some of the key bullets. So there's a lot of discussion in the data community about data mesh and while there are an increasing number of examples, JP Morgan Chase, Intuit, H S P C, HelloFresh, and others that are completely rearchitecting parts of their data platform completely rearchitecting entire data platforms is non-trivial. There are organizational challenges, there're data, data ownership, debates, technical considerations, and in particular two of the four fundamental data mesh principles that the, the need for a self-service infrastructure and federated computational governance are challenging. Look, democratizing data and facilitating data sharing creates conflicts with regulatory requirements around data privacy. As such many organizations are being really selective with their data mesh implementations and hence our prediction of narrowing the scope of data mesh initiatives. >>I think that was right on J P M C is a good example of this, where you got a single group within a, within a division narrowly implementing the data mesh architecture. They're using a w s, they're using data lakes, they're using Amazon Glue, creating a catalog and a variety of other techniques to meet their objectives. They kind of automating data quality and it was pretty well thought out and interesting approach and I think it's gonna be made easier by some of the announcements that Amazon made at the recent, you know, reinvent, particularly trying to eliminate ET t l, better connections between Aurora and Redshift and, and, and better data sharing the data clean room. So a lot of that is gonna help. Of course, snowflake has been on this for a while now. Many other companies are facing, you know, limitations as we said here and this slide with their Hadoop data platforms. They need to do new, some new thinking around that to scale. HelloFresh is a really good example of this. Look, the bottom line is that organizations want to get more value from data and having a centralized, highly specialized teams that own the data problem, it's been a barrier and a blocker to success. The data mesh starts with organizational considerations as described in great detail by Ash Nair of Warner Brothers. So take a listen to this clip. >>Yeah, so when people think of Warner Brothers, you always think of like the movie studio, but we're more than that, right? I mean, you think of H B O, you think of t n t, you think of C N N. We have 30 plus brands in our portfolio and each have their own needs. So the, the idea of a data mesh really helps us because what we can do is we can federate access across the company so that, you know, CNN can work at their own pace. You know, when there's election season, they can ingest their own data and they don't have to, you know, bump up against, as an example, HBO if Game of Thrones is going on. >>So it's often the case that data mesh is in the eyes of the implementer. And while a company's implementation may not strictly adhere to Jamma Dani's vision of data mesh, and that's okay, the goal is to use data more effectively. And despite Gartner's attempts to deposition data mesh in favor of the somewhat confusing or frankly far more confusing data fabric concept that they stole from NetApp data mesh is taking hold in organizations globally today. So we're gonna take a B on this one. The prediction is shaping up the way we envision, but as we previously reported, it's gonna take some time. The better part of a decade in our view, new standards have to emerge to make this vision become reality and they'll come in the form of both open and de facto approaches. Okay, our eighth prediction last year focused on the face off between Snowflake and Databricks. >>And we realized this popular topic, and maybe one that's getting a little overplayed, but these are two companies that initially, you know, looked like they were shaping up as partners and they, by the way, they are still partnering in the field. But you go back a couple years ago, the idea of using an AW w s infrastructure, Databricks machine intelligence and applying that on top of Snowflake as a facile data warehouse, still very viable. But both of these companies, they have much larger ambitions. They got big total available markets to chase and large valuations that they have to justify. So what's happening is, as we've previously reported, each of these companies is moving toward the other firm's core domain and they're building out an ecosystem that'll be critical for their future. So as part of that effort, we said each is gonna become aggressive investors and maybe start doing some m and a and they have in various companies. >>And on this chart that we produced last year, we studied some of the companies that were targets and we've added some recent investments of both Snowflake and Databricks. As you can see, they've both, for example, invested in elation snowflake's, put money into Lacework, the Secur security firm, ThoughtSpot, which is trying to democratize data with ai. Collibra is a governance platform and you can see Databricks investments in data transformation with D B T labs, Matillion doing simplified business intelligence hunters. So that's, you know, they're security investment and so forth. So other than our thought that we'd see Databricks I p o last year, this prediction been pretty spot on. So we'll give ourselves an A on that one. Now observability has been a hot topic and we've been covering it for a while with our friends at E T R, particularly Eric Bradley. Our number nine prediction last year was basically that if you're not cloud native and observability, you are gonna be in big trouble. >>So everything guys gotta go cloud native. And that's clearly been the case. Splunk, the big player in the space has been transitioning to the cloud, hasn't always been pretty, as we reported, Datadog real momentum, the elk stack, that's open source model. You got new entrants that we've cited before, like observe, honeycomb, chaos search and others that we've, we've reported on, they're all born in the cloud. So we're gonna take another a on this one, admittedly, yeah, it's a re reasonably easy call, but you gotta have a few of those in the mix. Okay, our last prediction, our number 10 was around events. Something the cube knows a little bit about. We said that a new category of events would emerge as hybrid and that for the most part is happened. So that's gonna be the mainstay is what we said. That pure play virtual events are gonna give way to hi hybrid. >>And the narrative is that virtual only events are, you know, they're good for quick hits, but lousy replacements for in-person events. And you know that said, organizations of all shapes and sizes, they learn how to create better virtual content and support remote audiences during the pandemic. So when we set at pure play is gonna give way to hybrid, we said we, we i we implied or specific or specified that the physical event that v i p experience is going defined. That overall experience and those v i p events would create a little fomo, fear of, of missing out in a virtual component would overlay that serves an audience 10 x the size of the physical. We saw that really two really good examples. Red Hat Summit in Boston, small event, couple thousand people served tens of thousands, you know, online. Second was Google Cloud next v i p event in, in New York City. >>Everything else was, was, was, was virtual. You know, even examples of our prediction of metaverse like immersion have popped up and, and and, and you know, other companies are doing roadshow as we predicted like a lot of companies are doing it. You're seeing that as a major trend where organizations are going with their sales teams out into the regions and doing a little belly to belly action as opposed to the big giant event. That's a definitely a, a trend that we're seeing. So in reviewing this prediction, the grade we gave ourselves is, you know, maybe a bit unfair, it should be, you could argue for a higher grade, but the, but the organization still haven't figured it out. They have hybrid experiences but they generally do a really poor job of leveraging the afterglow and of event of an event. It still tends to be one and done, let's move on to the next event or the next city. >>Let the sales team pick up the pieces if they were paying attention. So because of that, we're only taking a B plus on this one. Okay, so that's the review of last year's predictions. You know, overall if you average out our grade on the 10 predictions that come out to a b plus, I dunno why we can't seem to get that elusive a, but we're gonna keep trying our friends at E T R and we are starting to look at the data for 2023 from the surveys and all the work that we've done on the cube and our, our analysis and we're gonna put together our predictions. We've had literally hundreds of inbounds from PR pros pitching us. We've got this huge thick folder that we've started to review with our yellow highlighter. And our plan is to review it this month, take a look at all the data, get some ideas from the inbounds and then the e t R of January surveys in the field. >>It's probably got a little over a thousand responses right now. You know, they'll get up to, you know, 1400 or so. And once we've digested all that, we're gonna go back and publish our predictions for 2023 sometime in January. So stay tuned for that. All right, we're gonna leave it there for today. You wanna thank Alex Myerson who's on production and he manages the podcast, Ken Schiffman as well out of our, our Boston studio. I gotta really heartfelt thank you to Kristen Martin and Cheryl Knight and their team. They helped get the word out on social and in our newsletters. Rob Ho is our editor in chief over at Silicon Angle who does some great editing for us. Thank you all. Remember all these podcasts are available or all these episodes are available is podcasts. Wherever you listen, just all you do Search Breaking analysis podcast, really getting some great traction there. Appreciate you guys subscribing. I published each week on wikibon.com, silicon angle.com or you can email me directly at david dot valante silicon angle.com or dm me Dante, or you can comment on my LinkedIn post. And please check out ETR AI for the very best survey data in the enterprise tech business. Some awesome stuff in there. This is Dante for the Cube Insights powered by etr. Thanks for watching and we'll see you next time on breaking analysis.
SUMMARY :
From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from self grading system, but look, we're gonna give you the data and you can draw your own conclusions and tell you what, We kind of nailed the momentum in the energy but not the i p O that we had predicted Aqua Securities focus on And then, you know, I lumia holding its own, you So the focus on endpoint security that was a winner in 2022 is CrowdStrike led that charge put some meat in the bone, so to speak, and and allow us than you to say, okay, We said at the time, you can see this on the left hand side of this chart, the PC laptop demand would remain Kind of like an O K R and you know, we strive to provide data We thought they'd exit the year, you know, closer to, you know, 25 billion a quarter and we don't think they're we think, yeah, you might think it's a little bit harsh, we could argue for a B minus to the professor, Chris Miller of the register put out a Supercloud block diagram, something else that So you know, sorry you can hate the term, but very clearly the evidence is gathering for the super cloud But it's largely confined and narrow data problems with limited scope as you can see here with some of the announcements that Amazon made at the recent, you know, reinvent, particularly trying to the company so that, you know, CNN can work at their own pace. So it's often the case that data mesh is in the eyes of the implementer. but these are two companies that initially, you know, looked like they were shaping up as partners and they, So that's, you know, they're security investment and so forth. So that's gonna be the mainstay is what we And the narrative is that virtual only events are, you know, they're good for quick hits, the grade we gave ourselves is, you know, maybe a bit unfair, it should be, you could argue for a higher grade, You know, overall if you average out our grade on the 10 predictions that come out to a b plus, You know, they'll get up to, you know,
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Alex Myerson | PERSON | 0.99+ |
Cheryl Knight | PERSON | 0.99+ |
Ken Schiffman | PERSON | 0.99+ |
Chris Miller | PERSON | 0.99+ |
CNN | ORGANIZATION | 0.99+ |
Rob Ho | PERSON | 0.99+ |
Alibaba | ORGANIZATION | 0.99+ |
Dave Valante | PERSON | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
5.1% | QUANTITY | 0.99+ |
2022 | DATE | 0.99+ |
Charles Fitzgerald | PERSON | 0.99+ |
Dave Hatfield | PERSON | 0.99+ |
Brian Gracely | PERSON | 0.99+ |
2019 | DATE | 0.99+ |
Lacework | ORGANIZATION | 0.99+ |
two | QUANTITY | 0.99+ |
GCP | ORGANIZATION | 0.99+ |
33% | QUANTITY | 0.99+ |
Walmart | ORGANIZATION | 0.99+ |
David | PERSON | 0.99+ |
2021 | DATE | 0.99+ |
20% | QUANTITY | 0.99+ |
Kristen Martin | PERSON | 0.99+ |
Palo Alto | LOCATION | 0.99+ |
2020 | DATE | 0.99+ |
Ash Nair | PERSON | 0.99+ |
Goldman Sachs | ORGANIZATION | 0.99+ |
162 billion | QUANTITY | 0.99+ |
New York City | LOCATION | 0.99+ |
Databricks | ORGANIZATION | 0.99+ |
October | DATE | 0.99+ |
last year | DATE | 0.99+ |
Arctic Wolf | ORGANIZATION | 0.99+ |
two companies | QUANTITY | 0.99+ |
38% | QUANTITY | 0.99+ |
September | DATE | 0.99+ |
Fed | ORGANIZATION | 0.99+ |
JP Morgan Chase | ORGANIZATION | 0.99+ |
80 billion | QUANTITY | 0.99+ |
29% | QUANTITY | 0.99+ |
32% | QUANTITY | 0.99+ |
21 predictions | QUANTITY | 0.99+ |
30% | QUANTITY | 0.99+ |
HBO | ORGANIZATION | 0.99+ |
75% | QUANTITY | 0.99+ |
Game of Thrones | TITLE | 0.99+ |
January | DATE | 0.99+ |
2023 | DATE | 0.99+ |
10 predictions | QUANTITY | 0.99+ |
both | QUANTITY | 0.99+ |
22 | QUANTITY | 0.99+ |
ThoughtSpot | ORGANIZATION | 0.99+ |
196 million | QUANTITY | 0.99+ |
30 | QUANTITY | 0.99+ |
each | QUANTITY | 0.99+ |
last year | DATE | 0.99+ |
Palo Alto Networks | ORGANIZATION | 0.99+ |
2020s | DATE | 0.99+ |
167 billion | QUANTITY | 0.99+ |
Okta | ORGANIZATION | 0.99+ |
Second | QUANTITY | 0.99+ |
Gartner | ORGANIZATION | 0.99+ |
Eric Bradley | PERSON | 0.99+ |
Aqua Securities | ORGANIZATION | 0.99+ |
Dante | PERSON | 0.99+ |
8% | QUANTITY | 0.99+ |
Warner Brothers | ORGANIZATION | 0.99+ |
Intuit | ORGANIZATION | 0.99+ |
Cube Studios | ORGANIZATION | 0.99+ |
each week | QUANTITY | 0.99+ |
7 billion | QUANTITY | 0.99+ |
40% | QUANTITY | 0.99+ |
Snowflake | ORGANIZATION | 0.99+ |
Lisa-Marie Namphy, Cockroach Labs & Jake Moshenko, Authzed | KubeCon + CloudNativeCon NA 2022
>>Good evening, brilliant humans. My name is Savannah Peterson and very delighted to be streaming to you. Live from the Cube Studios here in Motor City, Michigan. I've got John Furrier on my left. John, this is our last interview of the day. Energy just seems to keep oozing. How >>You doing? Take two, Three days of coverage, the queue love segments. This one's great cuz we have a practitioner who's implementing all the hard core talks to be awesome. Can't wait to get into it. >>Yeah, I'm very excited for this one. If it's not very clear, we are a community focused community is a huge theme here at the show at Cape Con. And our next guests are actually a provider and a customer. Turning it over to you. Lisa and Jake, welcome to the show. >>Thank you so much for having us. >>It's great to be here. It is our pleasure. Lisa, you're with Cockroach. Just in case the audience isn't familiar, give us a quick little sound bite. >>We're a distributed sequel database. Highly scalable, reliable. The database you can't kill, right? We will survive the apocalypse. So very resilient. Our customers, mostly retail, FinTech game meet online gambling. They, they, they need that resiliency, they need that scalability. So the indestructible database is the elevator pitch >>And the success has been very well documented. Valuation obviously is a scorp guard, but huge customers. We were at the Escape 19. Just for the record, the first ever multi-cloud conference hasn't come back baby. Love it. It'll come back soon. >>Yeah, well we did a similar version of it just a month ago and I was, that was before Cockroach. I was a different company there talking a lot about multi-cloud. So, but I'm, I've been a car a couple of years now and I run community, I run developer relations. I'm still also a CNCF ambassador, so I lead community as well. I still run a really large user group in the San Francisco Bay area. So we've just >>Been in >>Community, take through the use case. Jake's story set us up. >>Well I would like Jake to take him through the use case and Cockroach is a part of it, but what they've built is amazing. And also Jake's history is amazing. So you can start Jake, >>Wherever you take >>Your Yeah, sure. I'm Jake, I'm CEO and co-founder of Offset. Oted is the commercial entity behind Spice Dvy and Spice Dvy is a permission service. Cool. So a permission service is something that lets developers and let's platform teams really unlock the full potential of their applications. So a lot of people get stuck on My R back isn't flexible enough. How do I do these fine grain things? How do I do these complex sharing workflows that my product manager thinks is so important? And so our service enables those platform teams and developers to do those kinds of things. >>What's your, what's your infrastructure? What's your setup look like? What, how are you guys looking like on the back end? >>Sure. Yeah. So we're obviously built on top of Kubernetes as well. One of the reasons that we're here. So we use Kubernetes, we use Kubernetes operators to orchestrate everything. And then we use, use Cockroach TV as our production data store, our production backend data store. >>So I'm curious, cause I love when these little matchmakers come together. You said you've now been presenting on a little bit of a road show, which is very exciting. Lisa, how are you and the team surfacing stories like Jakes, >>Well, I mean any, any place we can obviously all the social medias, all the blogs, How >>Are you finding it though? >>How, how did you Oh, like from our customers? Yeah, we have an open source version so people start to use us a long time before we even sometimes know about them. And then they'll come to us and they'll be like, I love Cockroach, and like, tell me about it. Like, tell me what you build and if it's interesting, you know, we'll we'll try to give it some light. And it's always interesting to me what people do with it because it's an interesting technology. I like what they've done with it. I mean the, the fact that it's globally distributed, right? That was like a really important thing to you. Totally. >>Yeah. We're also long term fans of Cockroach, so we actually all work together out of Workbench, which was a co-working space and investor in New York City. So yeah, we go way back. We knew the founders. I, I'm constantly saying like if I could have invested early in cockroach, that would've been the easiest check I could have ever signed. >>Yeah, that's awesome. And then we've been following that too and you guys are now using them, but folks that are out there looking to have the, the same challenges, what are the big challenges on selecting the database? I mean, as you know, the history of Cockroach and you're originating the story, folks out there might not know and they're also gonna choose a database. What's the, what's the big challenge that they can solve that that kind of comes together? What, what would you describe that? >>Sure. So we're, as I said, we're a permission service and per the data that you store in a permission service is incredibly sensitive. You need it to be around, right? You need it to be available. If the permission service goes down, almost everything else goes down because it's all calling into the permission service. Is this user allowed to do this? Are they allowed to do that? And if we can't answer those questions, then our customer is down, right? So when we're looking at a database, we're looking for reliability, we're looking for durability, disaster recovery, and then permission services are one of the only services that you usually don't shard geographically. So if you look at like AWS's iam, that's a global service, even though the individual things that they run are actually sharded by region. So we also needed a globally distributed database with all of those other properties. So that's what led us >>To, this is a huge topic. So man, we've been talking about all week the cloud is essentially distributed database at this point and it's distributed system. So distributed database is a hot topic, totally not really well reported. A lot of people talking about it, but how would you describe this distributed trend that's going on? What are the key reasons that they're driving it? What's making this more important than ever in your mind, in your opinion? >>I mean, for our use case, it was just a hard requirement, right? We had to be able to have this global service. But I think just for general use cases, a distributed database, distributed database has that like shared nothing architecture that allows you to kind of keep it running and horizontally scale it. And as your requirements and as your applications needs change, you can just keep adding on capacity and keep adding on reliability and availability. >>I'd love to get both of your opinion. You've been talking about the, the, the, the phases of customers, the advanced got Kubernetes going crazy distributed, super alpha geek. Then you got the, the people who are building now, then you got the lagers who are coming online. Where do you guys see the market now in terms of, I know the Alphas are all building all the great stuff and you guys had great success with all the top logos and they're all doing hardcore stuff. As the mainstream enterprise comes in, where's their psychology, what's on their mind? What's, you share any insight into your perspective on that? Because we're seeing a lot more of it folks becoming like real cloud players. >>Yeah, I feel like in mainstream enterprise hasn't been lagging as much as people think. You know, certainly there's been pockets in big enterprises that have been looking at this and as distributed sequel, it gives you that scalability that it's absolutely essential for big enterprises. But also it gives you the, the multi-region, you know, the, you have to be globally distributed. And for us, for enterprises, you know, you need your data near where the users are. I know this is hugely important to you as well. So you have to be able to have a multi-region functionality and that's one thing that distributed SQL lets you build and that what we built into our product. And I know that's one of the things you like too. >>Yeah, well we're a brand new product. I mean we only founded the company two years ago, but we're actually getting inbound interest from big enterprises because we solve the kinds of challenges that they have and whether, I mean, most of them already do have a cockroach footprint, but whether they did or didn't, once they need to bring in our product, they're going to be adopting cockroach transitively anyway. >>So, So you're built on top of Cockroach, right? And Spice dv, is that open source or? >>It >>Is, yep. Okay. And explain the role of open source and your business model. Can you take a minute to talk about the relevance of that? >>Yeah, open source is key. My background is, before this I was at Red Hat. Before that we were at CoreOS, so CoreOS acquisition and before that, >>One of the best acquisitions that ever happened for the value. That was a great, great team. Yeah, >>We, we, we had fun and before that we built Qua. So my co-founders and I, we built Quay, which is a, a first private docker registry. So CoreOS and, and all of those things are all open source or deeply open source. So it's just in our dna. We also see it as part of our go-to market motion. So if you are a database, a lot of people won't even consider what you're doing without being open source. Cuz they say, I don't want to take a, I don't want to, I don't want to end up in an Oracle situation >>Again. Yeah, Oracle meaning they go, you get you locked in, get you in a headlock, Increase prices. >>Yeah. Oh yeah, >>Can, can >>I got triggered. >>You need to talk about your PTSD there >>Or what. >>I mean we have 20,000 stars on GitHub because we've been open and transparent from the beginning. >>Yeah. And it >>Well, and both of your projects were started based on Google Papers, >>Right? >>That is true. Yep. And that's actually, so we're based off of the Google Zans of our paper. And as you know, Cockroach is based off of the Google Span paper and in the the Zanzibar paper, they have this globally distributed database that they're built on top of. And so when I said we're gonna go and we're gonna make a company around the Zabar paper, people would go, Well, what are you gonna do for Span? And I was like, Easy cockroach, they've got us covered. >>Yeah, I know the guys and my friends. Yeah. So the question is why didn't you get into the first round of Cockroach? She said don't answer that. >>The question he did answer though was one of those age old arguments in our community about pronunciation. We used to argue about Quay, I always called it Key of course. And the co-founder obviously knows how it's pronounced, you know, it's the et cd argument, it's the co cuddl versus the control versus coo, CTL Quay from the co-founder. That is end of argument. You heard it here first >>And we're keeping it going with Osted. So awesome. A lot of people will say Zeed or, you know, so we, we just like to have a little ambiguity >>In the, you gotta have some semantic arguments, arm wrestling here. I mean, it keeps, it keeps everyone entertained, especially on the over the weekend. What's, what's next? You got obviously Kubernetes in there. Can you explain the relationship between Kubernetes, how you're handling Spice dv? What, what does the Kubernetes piece fit in and where, where is that going to be going? >>Yeah, great question. Our flagship product right now is a dedicated, and in a dedicated, what we're doing is we're spinning up a single tenant Kubernetes cluster. We're installing all of our operator suite, and then we're installing the application and running it in a single tenant fashion for our customers in the same region, in the same data center where they're running their applications to minimize latency. Because of this, as an authorization service, latency gets passed on directly to the end user. So everybody's trying to squeeze the latency down as far as they can. And our strategy is to just run these single tenant stacks for people with the minimal latency that we can and give them a VPC dedicated link very similar to what Cockroach does in their dedicated >>Product. And the distributed architecture makes that possible because it's lighter way, it's not as heavy. Is that one of the reasons? >>Yep. And Kubernetes really gives us sort of like a, a level playing field where we can say, we're going going to take the provider, the cloud providers Kubernetes offering, normalize it, lay down our operators, and then use that as the base for delivering >>Our application. You know, Jake, you made me think of something I wanted to bring up with other guests, but now since you're here, you're an expert, I wanna bring that up, but talk about Super Cloud. We, we coined that term, but it's kind of multi-cloud, is that having workloads on multiple clouds is hard. I mean there are, they are, there are workloads on, on clouds, but the complexity of one clouds, let's take aws, they got availability zones, they got regions, you got now data issues in each one being global, not that easy on one cloud, nevermind all clouds. Can you share your thoughts on how you see that progression? Because when you start getting, as its distributed database, a lot of good things might come up that could fit into solving the complexity of global workloads. Could you share your thoughts on or scoping that problem space of, of geography? Yeah, because you mentioned latency, like that's huge. What are some of the other challenges that other people have with mobile? >>Yeah, absolutely. When you have a service like ours where the data is small, but very critical, you can get a vendor like Cockroach to step in and to fill that gap and to give you that globally distributed database that you can call into and retrieve the data. I think the trickier issues come up when you have larger data, you have huge binary blobs. So back when we were doing Quay, we wanted to be a global service as well, but we had, you know, terabytes, petabytes of data that we were like, how do we get this replicated everywhere and not go broke? Yeah. So I think those are kind of the interesting issues moving forward is what do you do with like those huge data lakes, the huge amount of data, but for the, the smaller bits, like the things that we can keep in a relational database. Yeah, we're, we're happy that that's quickly becoming a solved >>Problem. And by the way, that that data problem also is compounded when the architecture goes to the edge. >>Totally. >>I mean this is a big issue. >>Exactly. Yeah. Edge is something that we're thinking a lot about too. Yeah, we're lucky that right now the applications that are consuming us are in a data center already. But as they start to move to the edge, we're going to have to move to the edge with them. And it's a story that we're gonna have to figure out. >>All right, so you're a customer cockroach, what's the testimonial if I put you on the spot, say, hey, what's it like working with these guys? You know, what, what's the, what's the, you know, the founders, so you know, you give a good description, little biased, but we'll, we'll we'll hold you on it. >>Yeah. Working with Cockroach has been great. We've had a couple things that we've run into along the way and we've gotten great support from our account managers. They've brought in the right technical expertise when we need it. Cuz what we're doing with Cockroach is not you, you couldn't do it on Postgres, right? So it's not just a simple rip and replace for us, we're using all of the features of Cockroach, right? We're doing as of system time queries, we're doing global replication. We're, you know, we're, we're consuming it all. And so we do need help from them sometimes and they've been great. Yeah. >>And that's natural as they grow their service. I mean the world's changing. >>Well I think one of the important points that you mentioned with multi-cloud, we want you to have the choice. You know, you can run it in in clouds, you can run it hybrid, you can run it OnPrem, you can do whatever you want and it's just, it's one application that you can run in these different data centers. And so really it's up to you how do you want to build your infrastructure? >>And one of the things we've been talking about, the super cloud concept that we've been issue getting a lot of contrary, but, but people are leaning into it is that it's the refactoring and taking advantage of the services. Like what you mentioned about cockroach. People are doing that now on cloud going the lift and shift market kind of had it time now it's like hey, I can start taking advantage of these higher level services or capability of someone else's stack and refactoring it. So I think that's a dynamic that I'm seeing a lot more of. And it sounds like it's working out great in this situation. >>I just came from a talk and I asked them, you know, what don't you wanna put in the cloud and what don't you wanna run in Kubernetes or on containers and good Yeah. And the customers that I was on stage with, one of the guys made a joke and he said I would put my dog in a container room. I could, he was like in the category, which is his right, which he is in the category of like, I'll put everything in containers and these are, you know, including like mis critical apps, heritage apps, since they don't wanna see legacy anymore. Heritage apps, these are huge enterprises and they wanna put everything in the cloud. Everything >>You so want your dog that gets stuck on the airplane when it's on the tarmac. >>Oh >>God, that's, she was the, don't take that analogy. Literally don't think about that. Well that's, >>That's let's not containerize. >>There's always supply chain concern. >>It. So I mean going macro and especially given where we are cncf, it's all about open source. Do y'all think that open source builds a better future? >>Yeah and a better past. I mean this is, so much of this software is founded on open source. I, we wouldn't be here really. I've been in open source community for many, many years so I wouldn't say I'm biased. I would say this is how we build software. I came from like in a high school we're all like, oh let's build a really cool application. Oh you know what? I built this cuz I needed it, but maybe somebody else needs it too. And you put it out there and that is the ethos of Silicon Valley, right? That's where we grew up. So I've always had that mindset, you know, and social coding and why I have three people, right? Working on the same thing when one person you could share it's so inefficient. All of that. Yeah. So I think it's great that people work on what they're really good at. You know, we all, now you need some standardization, you need some kind of control around this whole thing. Sometimes some foundations to, you know, herd the cats. Yeah. But it's, it's great. Which is why I'm a c CF ambassador and I spend a lot of time, you know, in my free time talking about open source. Yeah, yeah. >>It's clear how passionate you are about it. Jake, >>This is my second company that we founded now and I don't think either of them could have existed without the base of open source, right? Like when you look at I have this cool idea for an app or a company and I want to go try it out, the last thing I want to do is go and negotiate with a vendor to get like the core data component. Yeah. To even be able to get to the >>Prototypes. NK too, by the way. Yeah. >>Hey >>Nk >>Or hire, you know, a bunch of PhDs to go and build that core component for me. So yeah, I mean nobody can argue that >>It truly is, I gotta say a best time if you're a developer right now, it's awesome to be a developer right now. It's only gonna get better. As we were riff from the last session about productivity, we believe that if you follow the digital transformation to its conclusion, developers and it aren't a department serving the business, they are the business. And that means they're running the show, which means that now their entire workflow is gonna change. It's gonna be have to be leveraging services partnering. So yeah, open source just fills that. So the more code coming up, it's just no doubt in our mind that that's go, that's happening and will accelerate. So yeah, >>You know, no one company is gonna be able to compete with a community. 50,000 users contributing versus you riding it yourself in your garage with >>Your dogs. Well it's people driven too. It's humans not container. It's humans working together. And here you'll see, I won't say horse training, that's a bad term, but like as projects start to get traction, hey, why don't we come together as, as the world starts to settle and the projects have traction, you start to see visibility into use cases, functionality. Some projects might not be, they have to kind of see more kind >>Of, not every feature is gonna be development. Oh. So I mean, you know, this is why you connect with truly brilliant people who can architect and distribute sequel database. Like who thought of that? It's amazing. It's as, as our friend >>You say, Well let me ask you a question before we wrap up, both by time, what is the secret of Kubernetes success? What made Kubernetes specifically successful? Was it timing? Was it the, the unambitious nature of it, the unification of it? Was it, what was the reason why is Kubernetes successful, right? And why nothing else? >>Well, you know what I'm gonna say? So I'm gonna let Dave >>First don't Jake, you go first. >>Oh boy. If we look at what was happening when Kubernetes first came out, it was, Mesosphere was kind of like the, the big player in the space. I think Kubernetes really, it had the backing from the right companies. It had the, you know, it had the credibility, it was sort of loosely based on Borg, but with the story of like, we've fixed everything that was broken in Borg. Yeah. And it's better now. Yeah. So I think it was just kind and, and obviously people were looking for a solution to this problem as they were going through their containerization journey. And I, yeah, I think it was just right >>Place, the timing consensus of hey, if we just let this happen, something good might come together for everybody. That's the way I felt. I >>Think it was right place, right time, right solution. And then it just kind of exploded when we were at Cores. Alex Povi, our ceo, he heard about Kubernetes and he was like, you know, we, we had a thing called Fleet D or we had a tool called Fleet. And he's like, Nope, we're all in on Kubernetes now. And that was an amazing Yeah, >>I remember that interview. >>I, amazing decision. >>Yeah, >>It's clear we can feel the shift. It's something that's come up a lot this week is is the commitment. Everybody's all in. People are ready for their transformation and Kubernetes is definitely gonna be the orchestrator that we're >>Leveraging. Yeah. And it's an amazing community. But it was, we got lucky that the, the foundational technology, I mean, you know, coming out of Google based on Go conferences, based on Go, it's no to coincidence that this sort of nature of, you know, pods horizontally, scalable, it's all fits together. I does make sense. Yeah. I mean, no offense to Python and some of the other technologies that were built in other languages, but Go is an awesome language. It's so, so innovative. Innovative things you could do with it. >>Awesome. Oh definitely. Jake, I'm very curious since we learned on the way and you are a Detroit native? >>I am. Yep. I grew up in the in Warren, which is just a suburb right outside of Detroit. >>So what does it mean to you as a Michigan born bloke to be here, see your entire community invade? >>It is, I grew up coming to the Detroit Auto Show in this very room >>That brought me to Detroit the first time. Love n a I a s. Been there with our friends at Ford just behind us. >>And it's just so interesting to me to see the accumulation, the accumulation of tech coming to Detroit cuz it's really not something that historically has been a huge presence. And I just love it. I love to see the activity out on the streets. I love to see all the restaurants and coffee shops full of people. Just, I might tear up. >>Well, I was wondering if it would give you a little bit of that hometown pride and also the joy of bringing your community together. I mean, this is merging your two probably most core communities. Yeah, >>Yeah. Your >>Youth and your, and your career. It doesn't get more personal than that really. Right. >>It's just been, it's been really exciting to see the energy. >>Well thanks for going on the queue. Thanks for sharing. Appreciate it. Thanks >>For having us. Yeah, thank you both so much. Lisa, you were a joy of ball of energy right when you walked up. Jake, what a compelling story. Really appreciate you sharing it with us. John, thanks for the banter and the fabulous questions. I'm >>Glad I could help out. >>Yeah, you do. A lot more than help out sweetheart. And to all of you watching the Cube today, thank you so much for joining us live from Detroit, the Cube Studios. My name is Savannah Peterson and we'll see you for our event wrap up next.
SUMMARY :
Live from the Cube Studios here in Motor City, Michigan. implementing all the hard core talks to be awesome. here at the show at Cape Con. case the audience isn't familiar, give us a quick little sound bite. The database you can't And the success has been very well documented. I was a different company there talking a lot about multi-cloud. Community, take through the use case. So you can start Jake, So a lot of people get stuck on My One of the reasons that we're here. Lisa, how are you and the team surfacing stories like Like, tell me what you build and if it's interesting, We knew the founders. I mean, as you know, of the only services that you usually don't shard geographically. A lot of people talking about it, but how would you describe this distributed trend that's going on? like shared nothing architecture that allows you to kind of keep it running and horizontally scale the market now in terms of, I know the Alphas are all building all the great stuff and you And I know that's one of the things you like too. I mean we only founded the company two years ago, but we're actually getting Can you take a minute to talk about the Before that we were at CoreOS, so CoreOS acquisition and before that, One of the best acquisitions that ever happened for the value. So if you are a database, And as you know, Cockroach is based off of the Google Span paper and in the the Zanzibar paper, So the question is why didn't you get into obviously knows how it's pronounced, you know, it's the et cd argument, it's the co cuddl versus the control versus coo, you know, so we, we just like to have a little ambiguity Can you explain the relationship between Kubernetes, how you're handling Spice dv? And our strategy is to just run these single tenant stacks for people And the distributed architecture makes that possible because it's lighter way, can say, we're going going to take the provider, the cloud providers Kubernetes offering, You know, Jake, you made me think of something I wanted to bring up with other guests, but now since you're here, I think the trickier issues come up when you have larger data, you have huge binary blobs. And by the way, that that data problem also is compounded when the architecture goes to the edge. But as they start to move to the edge, we're going to have to move to the edge with them. You know, what, what's the, what's the, you know, the founders, so you know, We're, you know, we're, we're consuming it all. I mean the world's changing. And so really it's up to you how do you want to build your infrastructure? And one of the things we've been talking about, the super cloud concept that we've been issue getting a lot of contrary, but, but people are leaning into it I just came from a talk and I asked them, you know, what don't you wanna put in the cloud and God, that's, she was the, don't take that analogy. It. So I mean going macro and especially given where we are cncf, So I've always had that mindset, you know, and social coding and why I have three people, It's clear how passionate you are about it. Like when you look at I have this cool idea for an app or a company and Yeah. Or hire, you know, a bunch of PhDs to go and build that core component for me. you follow the digital transformation to its conclusion, developers and it aren't a department serving you riding it yourself in your garage with you start to see visibility into use cases, functionality. Oh. So I mean, you know, this is why you connect with It had the, you know, it had the credibility, it was sort of loosely based on Place, the timing consensus of hey, if we just let this happen, something good might come was like, you know, we, we had a thing called Fleet D or we had a tool called Fleet. It's clear we can feel the shift. I mean, you know, coming out of Google based on Go conferences, based on Go, it's no to coincidence that this Jake, I'm very curious since we learned on the way and you are a I am. That brought me to Detroit the first time. And it's just so interesting to me to see the accumulation, Well, I was wondering if it would give you a little bit of that hometown pride and also the joy of bringing your community together. It doesn't get more personal than that really. Well thanks for going on the queue. Yeah, thank you both so much. And to all of you watching the Cube today,
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Jake | PERSON | 0.99+ |
Alex Povi | PERSON | 0.99+ |
John | PERSON | 0.99+ |
Savannah Peterson | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Lisa | PERSON | 0.99+ |
New York City | LOCATION | 0.99+ |
Detroit | LOCATION | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
John Furrier | PERSON | 0.99+ |
two | QUANTITY | 0.99+ |
20,000 stars | QUANTITY | 0.99+ |
Python | TITLE | 0.99+ |
Zeed | PERSON | 0.99+ |
both | QUANTITY | 0.99+ |
Cockroach | ORGANIZATION | 0.99+ |
San Francisco Bay | LOCATION | 0.99+ |
second company | QUANTITY | 0.99+ |
Postgres | ORGANIZATION | 0.99+ |
Ford | ORGANIZATION | 0.99+ |
50,000 users | QUANTITY | 0.99+ |
three people | QUANTITY | 0.99+ |
Red Hat | ORGANIZATION | 0.99+ |
Motor City, Michigan | LOCATION | 0.99+ |
Warren | LOCATION | 0.99+ |
Michigan | LOCATION | 0.99+ |
Spice Dvy | ORGANIZATION | 0.99+ |
Detroit Auto Show | EVENT | 0.99+ |
Cockroach Labs | ORGANIZATION | 0.99+ |
one | QUANTITY | 0.99+ |
Offset | ORGANIZATION | 0.99+ |
Cube Studios | ORGANIZATION | 0.99+ |
KubeCon | EVENT | 0.99+ |
a month ago | DATE | 0.99+ |
two years ago | DATE | 0.98+ |
Jake Moshenko | PERSON | 0.98+ |
One | QUANTITY | 0.98+ |
one person | QUANTITY | 0.98+ |
first time | QUANTITY | 0.98+ |
first | QUANTITY | 0.98+ |
Kubernetes | TITLE | 0.98+ |
Three days | QUANTITY | 0.97+ |
GitHub | ORGANIZATION | 0.97+ |
First | QUANTITY | 0.97+ |
Dave | PERSON | 0.96+ |
this week | DATE | 0.96+ |
CoreOS | ORGANIZATION | 0.96+ |
Quay | ORGANIZATION | 0.96+ |
Silicon Valley | LOCATION | 0.96+ |
Qua | ORGANIZATION | 0.95+ |
one application | QUANTITY | 0.95+ |
Jakes | PERSON | 0.94+ |
first round | QUANTITY | 0.94+ |
today | DATE | 0.94+ |
Oted | ORGANIZATION | 0.93+ |
Google Zans | ORGANIZATION | 0.93+ |
Authzed | ORGANIZATION | 0.92+ |
Cockroach | PERSON | 0.92+ |
Marie Namphy | PERSON | 0.92+ |
James Arlen, Aiven | AWS Summit New York 2022
(upbeat music) >> Hey, guys and girls, welcome back to New York City. Lisa Martin and John Furrier are live with theCUBE at AWS Summit 22, here in The Big Apple. We're excited to be talking about security next. James Arlen joins us, the CISO at Aiven. James, thanks so much for joining us on theCUBE today. >> Absolutely, it's good to be here. >> Tell the audience a little bit about Aiven, what you guys do, what you deliver, and what some of those differentiators are. >> Oh, Aiven. Aiven is a fantastic organization. I'm actually really lucky to work there. It's a database as a service, managed databases, all open source. And we're capital S, serious about open source. So 10 different open source database products delivered as a platform, all managed services, and the game is really about being the most performant, secure, and compliant database as a service on the market, friction free for your developers. You don't need people worrying about how to run databases. You just want to be able to say, here, take care of my data for me. And that's what we do. And that's actually the differentiator. We just take care of it for you. >> Take care of it for you, I like that. >> So they download the open source. They could do it on their own. So all the different projects are out there. >> Yeah, absolutely. >> What do you guys bringing to the table? You said the managed service, can you explain that. >> Yeah, the managed service aspect of it is, really, you could install the software yourself. You can use Postgres or Apache Kafka or any one of the products that we support. Absolutely you can do it yourself. But is that really what you do for a living, or do you develop software, or do you sell a product? So we take and do the hard work of running the systems, running the equipment. We take care of backups, high availability, all the security and compliance things around access and certifications, all of those things that are logging, all of that stuff that's actually difficult to do, well and consistently, that's all we do. >> Talk about the momentum, I see you guys were founded in what? 2016? >> Yes. >> Just in May of '22, raised $210 million in series D funding. >> Yes. >> Talk about the momentum and also from your perspective, all of the massive changes in security. >> It's very interesting to work for a company where you're building more than 100% growth year over year. It's a powers of two thing. Going from one to two, not so scary, two to four, not so scary. 512 to 1024, it's getting scary. (Lisa chuckles) 1024 to 2048, oh crap! I've been with Aiven for just almost two years now, and we are less than 70 when I started, and we're near 500 now. So, explosive growth is very interesting, but it's also that, you're growing within a reasonable burn rate boundary as well. And what that does from a security perspective, is it leaves you in the position that I had. I walked in and I was the first actual CISO. I had a team of four, I now have a team of 40. Because it turns out that like a lot of things in life, as you start unpacking problems, they're kind of fractal. You unpack the problem, you're like oh, well I did deal with that problem, but now I got another problem that I got to deal with. And so there's, it's not turtles all the way down. >> There's a lot of things going on and other authors, survive change. >> And there's fundamental problems that are still not fixed. And yet we treat them like they're fixed. And so we're doing a lot of hard work to make it so that we don't have to do hard work ongoing. >> And that's the value of the managed service. >> Yes. >> Okay, so talk about competition. Obviously, we had ETR on which is Enterprise Research Firm that we trust, we like. And we were looking at the data with the headwinds in the market, looking at the different players like got Amazon has Redshift, Snowflake, and you got Azure Sequence. I think it's called one of those products. The money that's being shifted from on premise data where the old school data warehouse like terra data and whatnot, is going first to Snowflake, then to Azure, then to AWS. Yes, so that points to snowflake being kind of like the bell of the ball if you will, in terms of from a data cloud. >> Absolutely. >> How do you compete with them? What's the pitch 'Cause that seemed to be a knee-jerk reaction from the industry. 'Cause snowflake is hot. They have a good value product. They have a smart team, Databrick is out there too. >> Yeah I mean... >> how do you guys compete against all that. >> So this is that point where you're balancing the value of a specific technology, or a specific technology vendor. And am I going to be stuck with them? So I'm tying my future to their future. With open source, I'm tying my future to the common good right. The internet runs on open source. It doesn't run on anything closed. And so I'm not hitching my wagon to something that I don't control. I'm hitching it to something where, any one of our customers could decide. I'm not getting the value I need from Aiven anymore. I need to go. And we provide you with the tools necessary, to move from our open source managed service to your own. Whether you go on-prem or you run it yourself, on a cloud service provider, move your data to you because it's your data. It's not ours. How can I hold your data? It's like weird extortion ransoming thing. >> Actually speaking, I mean enterprise, it's a big land grab 'cause with cloud you're horizontally scalable. It's a beautiful thing, open source is booming. It's going in Aiven, every day it's just escalating higher and higher. >> Absolutely. >> It is the software business. So open is open. Integration and scale seems to be the competitive advantage. >> Yeah. >> Right. So, how do you guys compete with that? Because now you got open source. How do you offer the same benefits without the lock in, or what's the switching costs? How do you guys maintain that position of not saying the same thing in Snowflake? >> Because all of the biggest data users and consumers tend to give away their data products. LinkedIn gave away their data product. Uber gave away their data product, Facebook gave away their data product. And we now use those as community solutions. So, if the product works for something the scale of LinkedIn, or something the scale of Uber. It will probably work for you too. And scale is just... >> Well Facebook and LinkedIn, they gave away the product to own the data to use against you. >> But it's the product that counts because you need to be able to manipulate data the way they manipulate data, but with yours. >> So low latency needs to work. So horizontally, scalable, fees, machine learning. That's what we're seeing. How do you make that available? Customers want on architecture? What do you recommend? Control plane, data plane, how do you think about that? >> It's interesting. There's architectural reasons to think about it in terms like that. And there's other good architectural reasons to not think about it. There's sort of this dividing line in the cloud, where your cloud service provider, takes over and provides you with the opportunity to say, I don't know. And I don't care >> As long as it's secure >> As long as it's secure absolutely. But there's sort of that water line idea, where if it's below the water line, let somebody else deal. >> What is in the table stakes? 'Cause I like that approach. I think that's a good value proposition. Store it, what boxes have to be checked? Compliance, secure, what are some of the boxes? >> You need to make sure that you've taken care of all of the same basics if you are still running it. Remember you can't absolve yourself of your duty to your customer. You're still on the hook. So, you have to have backups. You have to have access control. You have to understand who's administering it, and how and what they're doing. Good logging, good comprehension there. You have to have anomaly detection, secure operations. You have to have all those compliance check boxes. Especially if you're dealing with regulated data type like PCI data or HIPAA health data or you know what there's other countries besides the United States, there's other kinds of of compliance obligations there. So you have to make sure that you've got all that taken into account. And remember that, like I said, you can't absolve yourself with those things. You can share responsibilities. But you can't walk away from that responsibility. So you still have to make sure that you validate that your vendor knows what they're talking about. >> I wanted to ask you about the cybersecurity skills gap. So I'm kind of giving a little segue here, because you mentioned you've been with Aiven for about two years. >> Almost. >> Almost two years. You've started with a team of four. You've grown at 10X in less than two years. How have you accomplished that, considering we're seeing one of the biggest skills shortages in cyber in history. >> It's amazing, you see this show up in a lot of job Ads, where they ask for 10 years of experience in something that's existed for three years. (John Furrier laughs) And it's like okay, well if I just be logical about this I can hire somebody at less than the skill level that I need today, and bring them up to that skill level. Or I can spend the same amount of time, hoping that I'll find the magical person that has that set of skills that I need. So I can solve the problem of the skills gap by up-skilling the people that I hire. Which is strangely contrary to how this thing works. >> The other thing too, is the market's evolving so fast that, that carry up and pulling someone along, or building and growing your own so to speak is workable. >> It also really helps us with a bunch of sustainability goals. It really helps with anything that has to do with diversity and inclusion, because I can bring forward people who are never given a chance. And say, you know what? You don't have that magical ticket in life, but damn you know what you're talking about? >> It's a classic pedigree. I went to this school, I studied this degree. There's no degree if have to stop a hacker using state of the art malware. (John Furrier laughs) >> Exactly. What I do today as a job, didn't exist when I was in post-secondary at all. >> So when you hire, what do you look for? I mean obviously problem solving. What's your kind of algorithm for hiring? >> Oh, that's a really interesting question. The quickest sort of summary of it is, I'm looking for not a jerk. >> Not a jerk. >> Yeah. >> Okay. >> Because it turns out that the quality that I can't fix in a candidate, is I can't fix whether or not they're a jerk, but I can up-skill them, I can educate them. I can teach them of a part of the world that they've not had any interaction with. But if they're not going to work with the team, if they're going to be, look at me, look at me. If they're going to not have that moment of, I have this great job, and I get to work today. And that's awesome. (Lisa Martin laughs) That's what I'm trying to hire for. >> The essence of this teamwork is fundamental. >> Collaboration. >> Cooperation. >> Curiosity. >> That's the thing yeah, absolutely. >> And everybody? >> Those things, oh absolutely. Those things are really, really hard to interview for. And they're impossible to fix after the fact. So that's where you really want to put the effort. 'Cause I can teach you how to use a computer. I mean it's hard, but it's not that hard. >> Yeah, yeah, yeah. >> Well I love the current state of data management. Good overview, you guys are in the good position. We love open source. Been covering it for, since theCUBE started. It continues to redefine more and more the industry. It is the software industry. Now there's no debate about that. If people want to have that debate, that's kind of waste of time, but there are other ways that are happening. So I have to ask you. As things are going forward with innovation. Okay, if opensource is going to be the software industry. Where's the value? >> That's a fun question wow? >> Is it going to be in the community? Is it the integration? Is it the scale? If you're open and you have low switching costs... >> Yeah so, when you look at Aiven's commitment to open source, a huge part of that is our open source project office, where we contribute back to those core products, whether it's parts of the Apache Foundation, or Postgres, or whatever. We contribute to those, because we have staff who work on those products. They don't work on our stuff. They work on those. And it's like the opposite of a zero sum game. It's more like Nash equilibrium. If you ever watch that movie, "A beautiful mind." That great idea of, you don't have to have winners and losers. You can have everybody loses a little bit but everybody wins a little bit. >> Yeah and that's the open the ethos. >> And that's where it gets tied up. >> Another follow up on that. The other thing I want to get your reaction on is that, now in this modern era of open source, almost all corporations are part of projects. I mean if you're an entrepreneur and you want to get funding it's pretty simple. You start open source project. How many stars you get on GitHub guarantees it's a series C round, pretty much. So open source now has got this new thing going on, where it's not just open source folks who believe in it It's an operating model. What's the dynamic of corporations being part of the system. It used to be, oh what's the balance between corporate and influence, now it's standard. What's your reaction? >> They can do good and they can do harm. And it really comes down to why are you in it? So if you look at the example of open search, which is one of the data products that we operate in the Aiven system. That's a collaboration between Aiven. Hey we're an awesome company, but we're nowhere near the size of AWS. And AWS where we're working together on it. And I just had this conversation with one of the attendees here, where he said, "Well AWS is going to eat your story there. "You're contributing all of this "to the open search platform. "And then AWS is going to go and sell it "and they're going to make more money." And I'm like yep, they are. And I've got staff who work for the organization, who are more fulfilled because they got to deliver something that's used by millions of people. And you think about your jobs. That moment of, (sighs) I did a cool thing today. That's got a lot of value in it. >> And part of something. >> Exactly. >> As a group. >> 100%. >> Exactly. >> And we end up with a product that's used by millions. Some of it we'll capture, because we do a better job running than the AWS does, but everybody ends up winning out of the backend. Again, everybody lost a little, but everybody also won. And that's better than that whole, you have to lose so that I can win. At zero something, that doesn't work. >> I think the silo conversations are coming, what's the balance between siloing something and why that happens. And then what's going to be freely accessible for data. Because the real time information is based upon what you can access. "Hey Siri, what's the weather. "We had a guest on earlier." It says, oh that's a data query. Well, if the weather is, the data weathers stored in a database that's out here and it can't get to the response on the app. Yeah, that's not good, but the data is available. It just didn't get delivered. >> Yeah >> Exactly. >> This is an example of what people are realizing now the consequences of this data, collateral damage or economy value. >> Yeah, and it's understanding how data fits in your environment. And I don't want to get on the accountants too hard, but the accounting organizations, AICPA and ISAE and others, they haven't really done a good job of helping you understand data as an asset, or data as a liability. I hold a lot of customer data. That's a liability to me. It's going to blow up in my face. We don't talk about the income that we get from data, Google. We don't talk about the expense of regenerating that data. We talk about, well what happens if you lose it? I don't know. And we're circling the drain around fiduciary responsibility, and we know how to do this. If you own a manufacturing plant, or if you own a fleet of vehicles you understand the fiduciary duty of managing your asset. But because we can't touch it, we don't do a good job of it. >> How far do you think are people getting into the point where they actually see that asset? Because I think it's out of sight out of mind. Now there's consequences, there's now it's public companies might have to do filings. It's not like sustainability and data. Like, wait a minute, I got to deal with these things. >> It's interesting, we got this great benefit of the move to cloud computing, and the move to utility style computing. But we took away that. I got to walk around and pet my computers. Like oh! This is my good database. I'm very proud of you. Like we're missing that piece now. And when you think about the size of data centers, we become detached from that, you don't really think about, Aiven operates tens of thousands of machines. It would take entire buildings to hold them all. You don't think about it. So how do you recreate that visceral connection to your data? Well, you need to start actually thinking about it. And you need to do some of that tokenization. When was the last time you printed something out, like you get a report and happens to me all the time with security reports. Look at a security report and it's like 150 page PDF. Scroll, scroll, scroll, scroll. Print it out, stump it on the table in front of you. Oh, there's gravitas here. There's something here. Start thinking about those records, count them up, and then try to compare that to something in the real world. My wife is a school teacher, kindergarten to grade three, and tokenizing math is how they teach math to little kids. You want to count something? Here's 10 things, count them. Well, you've got 60,000 customer records, or you have 2 billion data points in your IOT database, tokenize that, what does 2 billion look like? What does $1 million look like in the form of $100 dollars bills on a pallet? >> Wow. >> Right. Tokenize that data, create that visceral connection with it, and then talk about it. >> So when you say tokenized, you mean like token as in decentralization token? >> No, I mean create like a totem or an icon of it. >> Okay, got it. >> A thing you can hold holy. If you're a token company. >> Not token as in Token economics and Crypto. >> If you're a mortgage company, take that customer record for one of your customers, print it out and hold the file. Like in a Manila folder, like it's 1963. Hold that file, and then say yes. And you're explaining to somebody and say yes, and we have 3 million of these. If we printed them all out, it would take up a room this size. >> It shows the scale. >> Right. >> Right. >> Exactly, create that connection back to the human level of interaction with data. How do you interact with a terabyte of data, but you do. >> Right. >> But once she hits upgrade from Google drive. (team laughs) >> What's a terabyte right? We don't hold that anymore. >> Right, right. >> Great conversation. >> Recreate that connection. Talk about data that way. >> The visceral connection with data. >> Follow up after this event. We'd love to dig more and love the approach. Love open source, love what you're doing there. That's a very unique approach. And it's also an alternative to some of the other vast growing plus your valuations are very high too. So you're not like a... You're not too far away from these big valuations. So congratulations. >> Absolutely. >> Yeah excellent, I'm sure there's lots of work to do, lots of strategic work to do with that round of funding. But also lots of opportunity, that it's going to open up, and we know you don't hire jerks. >> I don't >> You have a whole team of non jerks. That's pretty awesome. Especially 40 of 'em. That's impressive James.| >> It is. >> Congratulations to you on what you've accomplished in the course of the team. And thank you for sharing your insights with John and me today, we appreciate it. >> Awesome. >> Thanks very much, it's been great. >> Awesome, for John furrier, I'm Lisa Martin and you're watching theCube, live in New York city at AWS Summit NYC 22, John and I will be right back with our next segment, stick around. (upbeat music)
SUMMARY :
We're excited to be talking what you guys do, what you deliver, And that's actually the differentiator. So all the different You said the managed service, or any one of the Just in May of '22, raised $210 million all of the massive changes in security. that I got to deal with. There's a lot of things have to do hard work ongoing. And that's the value of the ball if you will, 'Cause that seemed to how do you guys compete And am I going to be stuck with them? 'cause with cloud you're It is the software business. of not saying the same thing in Snowflake? Because all of the biggest they gave away the product to own the data that counts because you need So low latency needs to work. dividing line in the cloud, But there's sort of that water line idea, What is in the table stakes? that you validate that your vendor knows I wanted to ask you about How have you accomplished hoping that I'll find the magical person is the market's evolving so fast that has to do with There's no degree if have to stop a hacker What I do today as a job, So when you hire, what do you look for? Oh, that's a really and I get to work today. The essence of this teamwork So that's where you really So I have to ask you. Is it going to be in the community? And it's like the opposite and you want to get funding to why are you in it? And we end up with a product is based upon what you can access. the consequences of this data, of helping you understand are people getting into the point where of the move to cloud computing, create that visceral connection with it, or an icon of it. A thing you can hold holy. Not token as in print it out and hold the file. How do you interact But once she hits We don't hold that anymore. Talk about data that way. with data. and love the approach. that it's going to open up, and Especially 40 of 'em. Congratulations to you and you're watching theCube,
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
John | PERSON | 0.99+ |
Lisa Martin | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
ORGANIZATION | 0.99+ | |
James Arlen | PERSON | 0.99+ |
Uber | ORGANIZATION | 0.99+ |
ORGANIZATION | 0.99+ | |
Apache Foundation | ORGANIZATION | 0.99+ |
2016 | DATE | 0.99+ |
John Furrier | PERSON | 0.99+ |
ORGANIZATION | 0.99+ | |
Postgres | ORGANIZATION | 0.99+ |
2 billion | QUANTITY | 0.99+ |
Aiven | ORGANIZATION | 0.99+ |
$1 million | QUANTITY | 0.99+ |
3 million | QUANTITY | 0.99+ |
New York City | LOCATION | 0.99+ |
10 years | QUANTITY | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
three years | QUANTITY | 0.99+ |
New York | LOCATION | 0.99+ |
James | PERSON | 0.99+ |
$100 dollars | QUANTITY | 0.99+ |
ISAE | ORGANIZATION | 0.99+ |
10 things | QUANTITY | 0.99+ |
millions | QUANTITY | 0.99+ |
$210 million | QUANTITY | 0.99+ |
40 | QUANTITY | 0.99+ |
100% | QUANTITY | 0.99+ |
less than two years | QUANTITY | 0.99+ |
two | QUANTITY | 0.99+ |
Lisa | PERSON | 0.99+ |
Databrick | ORGANIZATION | 0.99+ |
first | QUANTITY | 0.99+ |
four | QUANTITY | 0.99+ |
10X | QUANTITY | 0.99+ |
United States | LOCATION | 0.99+ |
today | DATE | 0.99+ |
one | QUANTITY | 0.98+ |
Siri | TITLE | 0.98+ |
Manila | LOCATION | 0.98+ |
AICPA | ORGANIZATION | 0.98+ |
less than 70 | QUANTITY | 0.98+ |
about two years | QUANTITY | 0.98+ |
May of '22 | DATE | 0.98+ |
Aiven | PERSON | 0.97+ |
150 page | QUANTITY | 0.97+ |
Enterprise Research Firm | ORGANIZATION | 0.97+ |
AWS Summit | EVENT | 0.96+ |
A beautiful mind | TITLE | 0.96+ |
zero | QUANTITY | 0.95+ |
almost two years | QUANTITY | 0.94+ |
NYC 22 | LOCATION | 0.94+ |
Snowflake | TITLE | 0.93+ |
millions of people | QUANTITY | 0.93+ |
10 different open source database products | QUANTITY | 0.92+ |
Almost two years | QUANTITY | 0.92+ |
AWS Summit 22 | EVENT | 0.91+ |
Kevin Farley, MariaDB | AWS Summit New York 2022
>>Good morning from New York city, Lisa Martin and John furrier with the cube. We are at AWS summit NYC. This is a series of summits this year, about 15 summit globally. And we're excited to be here, John, with about 10,000 folks. >>It's crowded. New York is packed big showing here at 80 of us summit. So it's super exciting, >>Super exciting. Just a little bit before the keynote. And we have our first guest, Kevin Farley joins us the director of strategic alliances at Maria DB. Kevin, welcome to >>The program. Thank you very much. Appreciate you guys having us. >>So all of us out from California to NYC. Yeah, lots of eyes. We got keynote with Warner Vogels coming up. We should be some good news, hopefully. Yep. But talk to us about Maria DB Skys cloud native version released a couple years ago. What's going on? >>Yeah, well, it's, you know, Skys SQL for us is really a be on the future. I think when we think about like the company's real mission is it's just creating a database for everyone. It's it's any cloud, any scale, um, any size of performance and really making sure that we're able to deliver on something that really kind of takes advantage of everything we've done in the market to date. If you think about it, there's not very many startups that have a billion downloads and 75% of the fortune 500 already using our service. So what we're really thinking about is how do we bridge that gap? How do we create a natural path for all of these customers? And if you think about not just Maria DB, but anyone else using the sequel query language, all the, my people, what I think most Andy jazzy TK, anyone says, you know, it's about 10% of the market currently is in the clouds. That's 90% of a total addressable market that hasn't done it yet. So creating cloud modernization for us, I think is just a huge opportunity. Do >>You guys have a great history with AWS? I want to just step back, you mentioned some stats on, on success. Can you scope the size and track record of Maria DB for us real quick and set the table? Because I think there's a bigger picture going on that we've been tracking for the past 13 years we address is the role of the database has always been one of those things where they didn't believe a one database fits all things, right. You guys have been part of that track record scope, the size and scale of Maria DB, the usage, the use cases and some of the successes. >>Yeah. I mean, like I said, some of the stats are already threw out there. So, you know, it is pervasive, I think is the best way to put it. I think what you look at what the database market really became is very siloed. Right? I think there was a lot of unique solutions that were built and delivered that had promise, but they also had compromise. And I think once you look at the landscape of a lot of fortune 500 companies, they have probably 10 to 15 different database solutions, right? And they're all doing unique things. They're difficult to manage. They're very costly. So what Marie DB is always kind of focused on is how do we continue to build more and more functionality into the database itself and allow that to be a single source of truth where application developers can seamlessly integrate applications. >>So then the theme of this event in New York city, which is scale dot, dot, dot, anything must align quite well with Maria and your >>Objectives. I mean, honestly, I think when I think of the problems that most database, um, companies, um, face customers, I should say it, it really comes down to performance and scale. Most of them like Maria DB, like you said, they it's like the car, you know, and love you've been driving it for years. You're an expert at it. It works great, but it doesn't have enough range. It doesn't go fast enough. It's hitting walls. That modern data requirements are just breaking. So scale for me is the favorite thing to talk about because what we launched as MariaDB expand, which is a plugable storage engine that is integrated into Skye, and it really gives you dynamic scale. So you can scale in, you can scale out, it's not costly compute to try to get for seasonality. So you can make your black Friday numbers. It's really about the dexterity to be able to come in and out as you need in a share, nothing architecture with full failover sale healing, high availability, married to the cloud for full cloud scale. And that's really the beauty of the AWS partnership. >>Can you elaborate a bit more on the partnership? How long have you guys been partners? Where is it now anything exciting coming out? >>Yeah, it it's, it's actually been a wonderful ride. They've really invested from the very beginning we went for the satisfactory. So they really brought a lot of resources to bear. And I think if you're looking at why it works, um, it's probably two things. I think the number one thing is that we share one of the core tenants and it's customer obsession in a, in a, in an environment where there is co-opetition right. You have to find paths for how do you get the best thing for the customer? And the second is pretty obvious, but if you look at any major cloud, their number one priority is getting large mission critical workloads into their cloud because the revenue is exponential on the backside. So what do we own? Large mission critical workloads. So if you marry that objective with AWS, the partnership is absolutely perfect for driving true revenue, growth scale, and, and revenue across, across both entities in the partner ecosystem. >>So Kevin talk about the, um, the hybrid strategy, cuz you're seeing cloud operations. Yep. Go hybrid. Amazon announced AWS announced outpost like four years ago. Right now edge is super hot. Yeah. So you're seeing like most of the enterprise is saying mm-hmm <affirmative> okay. Love cloud love the cloud database, but I got the on-prem hybrid cloud operations. Right. So it's not just proprietary operations. It's cloud ops. Yeah. How do you guys fit into that? What's the story. >>We, we actually it's. I mean, there's, there's all these new deliverables outposts, you know, come out with a promise. What we have is a reality right now, um, one of the largest, um, networking companies, which I can't mention yet publicly, um, we want a really big sky SQL deal, but what they had manufacturing plants, they needed to have on-prem deployments. So Maria DB naturally syncs with sky SQL. It's the same technology. It works in perfect harmony. So we really already deliver on the promise of hybrid, but of course there's a lot more we can grow in that area. And certainly thinking about app posts and other solutions, um, is definitely on the, the longer term roadmap of what could make sense for in our customer. What, >>What are some of the latest things that, that you guys are doing now that you weren't doing a few years ago that customers should know about the audience should know about? >>I mean, I think the game changer, we're always innovating. I mean, when you're the company that writes the code owns the code, you know, we can do hot fixes, we can do security patches, we can always do the things that give you real time access to what you need. But I think the game changer is what I mentioned a little bit earlier. And I think it's really the, the holy grail of the cloud. It's like, how can we take the, the SQL query language, which is well over 50% of the open source market. Right. And how do we convert that seamlessly into the cloud? How do we help you modernize on that journey? And expand gives you the ability to say, I can be the small, I can be a small startup. I got my C round. I don't wanna manage databases. I can use the exact same service as the largest fortune 100 company that has massive global scale and needs to be able to drive that across globe. Yeah. So I think that's the beauty is that it's really a democratization of the database, >>At least that, you know, we've been covering the big data space for 10 years. Remember all those different conversations had do those days and oh, they have big data and right. But then it's like too hard to set up. Then you had that kind of period where you saw a spark and data lakes emerge. Yeah. Then you, now it almost seems, seems like now more than ever, there's a data revolutions back. Right. It was almost like a lull in the, in, in the, in the market a little bit. Yeah. I'm gonna democratize data science right now. You got data. So now it just seems to be an explosion at that level. What's your analysis on that? Because you you've been in, in, in the weeds and in the, in the, in this market for 10 years. Yeah. And nothing really changed. It's just now it's more ready. Yeah. I think what's your observation. Why >>Is that? I think that's a really good question. And I love it cuz I mean, what the promise of things like could do and net new technologies sort of, it was always out there, but it required this whole net new lift and how do I do it? How do I manage it? How do I optimize it? The beauty of what we can do with Maria DB is that sky SQLs, which you already know and love. Right? And now we can Del you can deliver a data lake on S3, right? You can pull that data. And we also have the ability to do both analytical data and transactional data from the same database. So you can write applications that can pull column, store data up into, um, your application, but you can also have all of your asset transactions, which are absolutely required for all of your mission critical business. So I think that we're seeing more and more adoption. You've seen other companies start to talk about bringing the different elements in, but we're the only ones that really >>Do it and SQL standardizing that front end. Yeah. Even better than ever before. All the stuff under the covers is all being connected. >>That's the awesome part is right. Is you're literally doing what you already know how to do, but you blow it out on the back end, married to the cloud. And that I think is the real revolution of what makes usability real in the data space. And I think that's what was always the problem before >>When you're in partner conversations, you mentioned co-opetition. Yeah. <laugh> so I think when you're in partner conversations and customer conversations, there is a lot of the, the there's a lot of competition out there. Absolutely. Everyone's got their own key messages. What are the key differentiators that you're saying AWS Marie to be together better? And here's why, >>Yeah. I, I think that certainly you, you start with the global footprint of AWS, right? So what we rely on the most is having the ability to truly deal with global customers in availability zones, they're gonna optimize performance from them. But then when we look at what we do that really changes the game, it comes down to scale and performance. We actually just ran, um, a suspense test against cockroach that also does distributed sequel. Absolutely. You know, the results were off the chart. So we went public and said, we have an open challenge. Anyone that wants to try to beat, um, expand and Skye will we'll if you can, we'll put $25,000 towards charity. So we really are putting our money where our mouth is on that challenge. So we believe the performance cuz we've seen it and we know it's real, but then it's really always about data scale. Modern data requirements are breaking the mold of charting. They're breaking the mold of all these bandaids that people have put in these traditional services. And we give them future. We, we feature proof their investments, so they can say, Hey, I can start here. But if I end up being a startup that becomes Airbnb, I'm already built to blow it out on the back end. I can already use what I have. >>Speaking of startups, being the next Airbnb. If you look at behind us here, you can see, this is a really packed event in New York city events are back, but the ecosystem here is even flourishing. So Dave and I and Lisa were observing that we're still kind of in a growth mode, big time. So yeah, there's some market forces headwinds for the big unicorns, overfunded, you know, public companies, maybe the valuations are a little bit off, but there's still a surge of new innovations, new companies coming out of this. Um, and it's all around data and scale. It's all around new names. We've never heard of. Absolutely. What's your take on >>Reaction? Well, actually another awesome segues cuz in addition to the public clouds, I manage the ecosystem. And one of the things that we've really been focused on with Skys SQL is making it accessible API accessible. So if you're a company that has a huge Marine DB footprint change data capture might be the most important thing for you to say, we wanna do this, but we want you to stay in sync with our environments. Um, things like monitoring, things like BI, all of these are ecosystem plays and current partners that we have, um, that we really think about how do you holistically look at not only the database and what it can do, but how does it deliver value to different segments of your customer base or just your employee base that are using that stuff? So I think that's huge for us. >>Well, you know, one of the things that we talk often about is that every company, these days, regardless of industry, has to be a data company. Yep. You've gotta be able to access the data glean insights from an act on it quickly, whether it's manufacturing, retail, healthcare, are there any verticals in where Maria DB really excels? >>Um, so certainly we Excel in areas like financial services is huge DBS bank. Um, in APAC, one of our biggest customers, also one of the largest Oracle migrations, probably the, that we've ever done. A lot of people trying to get off Oracle, we make it seamless to get into Maria DB. Um, you can think about Samsung cloud and another, their entire consumer cloud is built on Maria DB, why it's integrated with expand right seasonality. So there's customers like that that really bring it home for us as far as ServiceNow tech sector. Right? So these are all different ones, but I think we're really strong in those >>Areas. So this brings up a good point. Dave and I a coined a term called super cloud at reinvent and Lisa and Dave were at multiple events we're together at events. And so a lot of people are getting behind this cuz it's multi-cloud sounds like something's broken. Yes. But so we call it super cloud because customers are building on top of ecosystems like Maria DB and others. Yeah. Not just AWS SOS does all the CapEx absolutely provide the value. So now people are having this new super cloud moment. We' saying we can get all the benefits of cloud scale mm-hmm <affirmative> without actually being a cloud. Right. So this is where the next gen layer comes. What's your reaction to, to super cloud. Do you think it's a thing? >>Well, I think it's a thing in the sense, from our perspective as an ISV, we're, we're laser focused on making sure that we support any cloud and we have a truly multicloud cloud platform. But the beauty of that as well is from a single UI, you're able to deploy databases in different clouds underneath that you're not looking at so you can have performance proximity, but you're still driving it through the same Skys UI. So for us it's, it's unequivocally true. Got it. And I think it's only ISVs like Maria DB that can deliver on that value because >>You're enabling, >>We're enabling it. Right. We partner, we build on top of everything. Right. So we can access everything underneath >>And they can then build on top of you. >>Sure, exactly. And that's exactly where it goes. Right? Yeah. So that, I think in that sense, the super cloud is actually already somewhat real. >>It's interesting. You look at the old, it spend, you take a big company. I won't say a name, but a leader in a, a vertical, they have such a big spend. Now they can leverage that spend in with the super cloud model. They then could become a service provider in the vertical. Absolutely capital one S doing it. Yeah. You're seeing, um, Goldman Sachs doing it. They have the power on the spend that they're leveraging in for their business and servicing their vertical and the smaller players. Do you see that trend? >>Well, I think that's the reality is that everyone is getting this place where if you're talking about sort of this broader super concept, you're talking about global scale, right? That's if in order to deliver a backbone that can service that model, you have to have the right data structure and the right database footprint to be able to scale. And I think that's what they all need to be able to do. And that's what we're really well positioned with Skys >>To enable companies, as we talked about a minute ago to truly become data companies. Yeah. And to be competitive and to scale on their own, where are your customer conversations? Are they at the C-suite level? Has that changed in the last couple of years? >>Uh, that's actually a really great way to state that question because I think you would've traditionally probably talked more to, um, the DBAs, right? They're the people that are having headaches. They're having problems. They're, they're trying to solve. We see a lot of developers now tons, right? They're thinking about, I have this, I have this new thing that I need to do to deliver this new application. And here's the requirements and the current model's broken. It doesn't optimize that it's a lot of work and it's hard to manage. So I think that we're in a great position to be able to take that to that next phase and deliver. And then of course, as you get deeper in with AWS, you're talking about, you know, CIO level, CISO level, they're they need to understand how do you fit into our larger paradigm. And many of these guys have, you know, hundreds of million dollar commits with AWS. So they think of their investment in the sense of the cloud stack. And we're part of that cloud stack, just like AWS services. So those conversations continue to happen certainly with our larger customers, cuz it truly is married. >>It is. And they continue to evolve. Kevin, thank you so much >>For joining. You're welcome. Great, >>John and me talking about what's going on with Maria >>D. Thank you, John. Thank you, Lisa. On behalf of Maria B, it was wonderful. Really >>Appreciate it. Fantastic as well for John furrier. I'm Lisa Martin. You're watching the cube live from New York city at AWS summit NYC, John and I we're back with our next guest in a minute.
SUMMARY :
And we're excited to be here, John, with about 10,000 folks. So it's super exciting, And we have our first guest, Kevin Farley joins us the director of strategic alliances Appreciate you guys having us. So all of us out from California to NYC. And if you think about not just Maria I want to just step back, you mentioned some stats on, And I think once you look at the landscape of a lot of fortune 500 companies, So scale for me is the favorite thing to talk about because what we launched as MariaDB expand, And I think if you're looking at why it works, How do you guys fit into that? I mean, there's, there's all these new deliverables outposts, you know, the code owns the code, you know, we can do hot fixes, we can do security patches, we can always do the things So now it just seems to be an explosion at And now we can Del you can deliver a data lake on S3, right? All the stuff under the covers is all being connected. And I think that's what was always the problem before What are the key differentiators that you're saying AWS So we believe the performance cuz we've seen it and we know it's real, but then it's really always about If you look at behind us here, you can see, data capture might be the most important thing for you to say, we wanna do this, but we want you to stay Well, you know, one of the things that we talk often about is that every company, these days, regardless of industry, you can think about Samsung cloud and another, their entire consumer cloud is built on Maria DB, Do you think it's a thing? And I think it's only ISVs like Maria DB that can deliver on that value because So we can access everything underneath So that, I think in that sense, the super cloud is actually already You look at the old, it spend, you take a big company. And I think that's what they all need to be able to do. And to be competitive and to scale on their own, where are your customer conversations? And then of course, as you get deeper in with AWS, you're talking about, And they continue to evolve. You're welcome. On behalf of Maria B, it was wonderful. New York city at AWS summit NYC, John and I we're back with our next guest in
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Maria | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Lisa Martin | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
John | PERSON | 0.99+ |
Lisa | PERSON | 0.99+ |
California | LOCATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Kevin Farley | PERSON | 0.99+ |
NYC | LOCATION | 0.99+ |
Kevin | PERSON | 0.99+ |
10 | QUANTITY | 0.99+ |
90% | QUANTITY | 0.99+ |
Goldman Sachs | ORGANIZATION | 0.99+ |
$25,000 | QUANTITY | 0.99+ |
10 years | QUANTITY | 0.99+ |
75% | QUANTITY | 0.99+ |
New York | LOCATION | 0.99+ |
DBS | ORGANIZATION | 0.99+ |
Maria DB | TITLE | 0.99+ |
two things | QUANTITY | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
MariaDB | TITLE | 0.99+ |
Airbnb | ORGANIZATION | 0.99+ |
Maria B | PERSON | 0.99+ |
one | QUANTITY | 0.98+ |
Andy jazzy TK | PERSON | 0.98+ |
first guest | QUANTITY | 0.98+ |
Maria DB | TITLE | 0.98+ |
New York city | LOCATION | 0.98+ |
second | QUANTITY | 0.98+ |
Excel | TITLE | 0.97+ |
APAC | ORGANIZATION | 0.97+ |
four years ago | DATE | 0.97+ |
this year | DATE | 0.97+ |
single | QUANTITY | 0.97+ |
about 10,000 folks | QUANTITY | 0.96+ |
sky SQL | TITLE | 0.96+ |
black Friday | EVENT | 0.96+ |
about 10% | QUANTITY | 0.95+ |
over 50% | QUANTITY | 0.95+ |
15 different database solutions | QUANTITY | 0.95+ |
AWS | EVENT | 0.94+ |
S3 | TITLE | 0.94+ |
Marie DB | TITLE | 0.93+ |
80 of us | QUANTITY | 0.93+ |
both entities | QUANTITY | 0.92+ |
AWS Summit | EVENT | 0.92+ |
Maria | TITLE | 0.91+ |
Skye | TITLE | 0.9+ |
500 companies | QUANTITY | 0.9+ |
few years ago | DATE | 0.89+ |
Skys | ORGANIZATION | 0.88+ |
couple years ago | DATE | 0.87+ |
AWS summit | EVENT | 0.86+ |
about 15 summit | QUANTITY | 0.85+ |
SQL | TITLE | 0.84+ |
Samsung | ORGANIZATION | 0.83+ |
Tony Coleman, Temenos and Boris Bialek, MongoDB | MongoDB World 2022
>>Yeah, yeah, yeah. We're back at the center of the coverage of the world 20 twenty-two, the first live event in three years. Pretty amazing. And I'm really excited to have Tony Coleman. Here is the c e o of those who changing the finance and banking industry. And this is the global head of industry solutions. That would be welcome. Back to the cube. Welcome. First time. Um, so thanks for coming on. Thank you. >>Thanks for having us, >>Tony. Tell us about what are you guys up to? Disrupting the finance world. >>So tomorrow is everyone's banking platform. So we are a software company. We have over 3000 financial institutions around the world. Marketing tell me that that works out is over 1.2 billion people rely on terminal software for their banking and financial needs. 41 of the top 50 banks in the world run software and we are very proud to be powering all of those entities on their innovation journeys and bringing you know, that digital transformation that we've seen so much all over the past few years and enabling a lot of the world's unbanked through digital banking become, you know, members of the >>community. So basically you're bringing the software platform to enable that to somebody you don't have to build it themselves because they never get there. Absolutely. And and so that's why I don't know if you consider that disruptive. I guess I do to the industry to a certain extent. But when you think of disruption in the business, you think of Blockchain and crypto, and 50 is that is completely separate world and you guys participate in that as well. Well, I >>would say it's related right? I mean, I was doing a podcast recently and they had this idea of, um, buzzword jail where you could choose words to go into jail and I said 50 not because I think they're intrinsically bad, but I think just at the moment they are a rife for scam area. I think it's one of those one of these technologies and investment area that people don't understand it, and there's a lot of a lot of mistakes that can be made in that, >>Yeah, >>I mean, it's a fascinating piece that it could be truly transformative if we get it right, but it's very emerging, so we'll see so don't play a huge part in the Blockchain industry directly. We work with partners in that space, but in terms of digital assets and that sort of thing. Yeah, absolutely. >>So, Boris, you have industry solutions in your title. What does that entail? So >>basically, I'm responsible for all the verticals, and that includes great partners like Tony. And we're doing a lot of verticals by now. When you listen. Today in all these various talks, we have so much stuff ranging from banking, go retail, healthcare, insurance, you name it, we have it by now. And that's obviously the clients moving from the edge solution. Like touching a little toe in the water, but longer to going all in building biggest solutions you saw on stage the lady from this morning. These are not second Great. Yeah, we do something small now. We're part of the transformation journey. And this is where Tony and I can regularly together how we transform things and how we built a new way of banking is done with Michael services and technology surrounding it. Yeah, >>but what about performance in this world? Can you tell me about that? >>Yeah. This is an interesting thing because people always challenging what is performance and document databases. And Tony challenged us actually, six weeks before his own show several weeks ago in London and says, Boris, let's do a benchmark And maybe you bring your story because if I get too excited, I follow. >>Yeah, sure, that performance and efficiency topics close close to my heart. I have been for for years. And so, yeah, we every two or three years, we run a high water. We've got a high water benchmark, and this year we sort of double down literally double down on everything we did previously. So this was 200 million accounts, 100 million customers, and we were thrashing through 102,800 seventy-five transactions a second, which is a phenomenal number. And, uh, >>can I do that on the Blockchain? >>Wow. Yeah, exactly. Right. So this is you know, I get asked why we do such high numbers and the reason is very straightforward. If somebody wants 10,000 transactions a second, we're seeing banks now that need that sort of thing. If I can give them a benchmark report, this is 100,000. I don't need to keep doing benchmarks. 10. >>Yeah. Tell me more about the Anytime you get into benchmarks, you want to understand the configuration. The workload. Tell me more about that. So we have >>a pretty well path of a standard transaction mix. We call it a retail transaction mix. And so it's the tries to the workload. Is that because it's a simulation right around what you would do in your daily basis? So you're going to make payments you're going to check? Your balance is you're going to see what he's moved on your account. So we do all of that and we run it through a proper production, good environment. And this is really important. This is something we do in the lab you couldn't go live on. This is all all of the horrible, non functional requirements around high availability, >>security, security passes, private wings, all these things. And one thing is, they're doing this for a long time. So this is not like let's define something new for the world. Now, this is something Tony's doing for literally 10, 15 years now, right? >>It was only 15 years, but this >>is your benchmark >>top >>developed Okay, >>so we run it through and, um yeah, some fantastic numbers. And not just on the share sort of top-level numbers 100,000 transactions. A second response time out of it was fantastic. One-millisecond, which is just brilliant. So it means you get these really efficient numbers what that helped us do with, you know, some of the other partners that are involved in the benchmark as well. It meant that our throughput court, which is a really good measure of efficiency, is up to four times better than we ran it three years ago. So in terms of a sustainability piece, which is so important that that's really a huge improvement, that's down to application changes, architect changes as well as using appropriate technology in the right place. >>How important? With things like the number, of course, the memory size is the block sizes. All that stuff. >>We are very tiny. So this is the part. When I talk to people, we have what we call a system in the back of people. Look at me. Um, how many transactions on that one? So, to be fair, three-quarters, we're going to be one quarter or something else because we're still putting some components of and start procedures for disclosure. But when I think Seventy-five 1000 transactions on a single single 80 system, which is thirty-two cause you're saying correctly, something like that. This is a tiny machine in the world of banking. So before this was the main friends and now it's wonderful instance on a W s. And this is really amazing. Costed and environmental footprint is so, so important >>and there's a heavy right heavy environment. >>So the the way we the way we architect the solution is it follows something called a command query responsibility, segregated segregation. So what we do, we do all the commands inappropriate database for that piece, and that was running at about Twenty-five 1000 transactions a second and then we're streaming the data out of that directly into So actually I was doing more than the Seventy-five 1000 queries. A second, which is the part of it was also investing Twenty-five 1000 transactions the second at the same time >>and okay, and the workload had a high locality medium locality. It was just give us a picture of what that's like. Sorry. So, >>yeah, >>we don't have that. Yeah, >>so explain that That's not That's not the mindset for a document. Exactly. >>Exactly. In the document database, you don't have the hot spotting the one single field off the table, which is suddenly hot spotting. And now you have literally and recovery comes up and we say, What goes, goes together, get together belongs together, comes out together. So the number of, for example, it's much, much smaller and the document system, then historically, relationship. >>So it is not a good good indicator, necessarily >>anymore. That's what this is so much reduced. The number of access patterns are smaller, and I mean it is highly optimized, for example, internally as well. The internal structures, so that was very close to a >>traditional benchmark, would have a cash in front of a high cash rate. So 100 and 99% right, That's a high locality reference. But that's that's irrelevant. >>It's gone. There's no cashing in the middle anymore. It goes straight against the database. All these things are out, and that's what makes it so exciting and all the things in a real environment. I think we really need to stress it. It's not a test that at home. It's a real life environment out into the wild with the benchmark driving and driving. >>How did your customers respond? You did this for your recent event? >>Yeah, we did it for our use. A conference, our community for, um, which was a few weeks ago in London. Um, and the You know, the reaction was Certainly it was a great reception, of course, but the main thing that people are fascinated about, how much more efficient the whole platform it's explaining. So you know when we can run and it's a great number that we've got the team pulled out, which is so having doubled throughput on the platform from what we did three years ago, we're actually using 20% less infrastructure to give double the performance. Uh, macro-level, that's a phenomenal achievement. And that means that these changes that we make everything that we're doing benefits all of our customers. So all of the banks, when they take the latest release, is they get these benefits. Everything is that much more efficient. So everybody benefits from every investment, >>and this was running in the cloud. Is that correct? You're running out of this. >>So this was list, Um, 80 on a W s with a W s cases and processes. And so it was a really reality driven environment, >>pure pure cloud-native or using mana services on a W s. And then at least for the peace. It's >>awesome. I mean, uh, So now how convenient for the timing from, uh, the world. How are you socializing with your community? >>We're having this afternoon session as well, where we talk a little bit more detail about that, and he has a session as well tomorrow. So we see a lot of good feedback as well when we bring it up with clients. Obviously some clients get very specific because this reduction footprint is so huge when you think a client has 89 environments from early development systems to production to emergency standby, maybe a different cloud. All these things what day talks about the different Atlas features multi cloud environmentally. All this stuff comes to play. And this is why I'm so excited to work with them. We should bring up as well the other things which are available to ready already with your front and solutions with Infinity services because that's the other part of the modernization, the Michael Services, which Tony so politely not mentioning. So there's a lot of cool technology into that one, which fits to how it works in micros services. Happy I first all these what they called factors. Micro service a p. I cloud-native headless. I think that was the right order now. So all these things are reflected as well. But with their leadership chief now, I think a lot of companies have to play Catch-up now to what Tony and his team are delivering on the bank. This >>gets the modernization. We really haven't explicitly talks about that. Everything you've just said talks to modernization. So you typically in financial services find a lot of relation. Database twenty-year-old, hardened, etcetera, high availability. Give them credit for that. But a lot of times you'll see them just shift that into the cloud. You guys chose not to do that. What was the modernization journey look like? >>So it's a bit of, um yeah, a firm believer in pragmatism and using. I think you touched on earlier the appropriate technology. So >>horses for courses >>exactly right out of my mouth. And I was talking to one of the uh, the investor analysts earlier. And you know, the exact same question comes up, right? So if you've got a relation database or you've got a big legacy system and you're not gonna mainframe or whatever it is and you wanna pull that over when you it's not just a case of moving the data model from one paradigm to another. You need to look at it holistically, and you need to be ambitious. I think the industry has got, you know, quite nervous about some of these transformation projects, but in some ways it might be counter intuitive. I think being ambitious and being in bold is a better way. Better way through, you know, take take of you, look at it holistically. Layout of plan. It is hard. It is hard to do these sorts of transformations, but that's what makes it the challenge. That's what makes it fun. Take take those bold steps. Look at it holistically. Look at the end state and then work out a practical way. You can deliver value to the business and your customers as you deliver on the road. So >>did you migrate from a traditional R D B. M s to go. >>So So, Yeah, this is a conversation. So, uh, in the late nineties, the kind of the phrase document model hasn't really been coined yet. And for some of our work at the time, we refer to as a hierarchical model. Um, And at that point in time, really, if you wanted to sell to a bank, you needed to be running Oracle. So we took this data model and we got it running an article and then other relational databases as well, but actually under the colors there it is, sort of as well. So there is a project that we're looking at to say Well, okay, taking that model, which is in a relational database. And of course, you build over time, you do rely on some of the features of relations databases moving that over to something like, isn't it? You know, it's not quite as simple as just changing the data model. Um, so there's a few bits and pieces that we need to work through, but there is a concept that we are running, which is looking really promising and spurred on by the amazing results from the benchmark. That could be something That's really >>yeah, I think you know, 20 years ago you probably wouldn't even thought about it. It's just too risky. But today, with the modern tools and the cloud and you're talking about micro services and containers, it becomes potentially more feasible. >>But the other side of it is, you know, it's only relatively recently the Mongo who's had transaction support across multiple document multi collection transactions and in banking. As we all know, you know, it's highly regulated. That is, all of your worst possible non functional requirement. Security transaction reality. Thomas City You know, the whole the whole shebang. Your worst possible nightmare is Monday morning for >>us. So and I think one part which is exciting about this Tony is a very good practical example about this large scale modernization and cutting out by cutting off that layer and going back to the hierarchical internal structures. We're simply find a lot of the backing components of our because obviously translation which was done before, it's not need it anymore. And that is as well for me, an exciting example to see how long it takes what it is. So Tony space in my life experiments so to speak >>well, you're right because it used to be those migrations. Where how many line of code? How long do I have to freeze it? And that a lot of times lead people to say, Well, forget it, because the business is going to shut down. >>But now we do that. We do that. So I'm working, obviously, besides the work with a lot of financial clients, and but now it's my job is normally shift and left a pain in the game because the result of the work is when they move everything to the cloud and it was bad before. It will not be better in the cloud only because it's in somebody else's data center. So these modernization and innovation factor is absolutely critical. And it's only said that people get it by now. This shift and left over it is how can I innovate? How can accelerate innovation, and that leads very quickly to the document model discussion. >>Yeah, I think the world practitioners will tell you, if you really want to affect the operational model, have a meaningful impact on your business. You have to really modernized. You can't just lift shift that they're absolutely. You know, what's the difference between hundreds of millions or billions in some cases, versus, you know, some nice little hits here or there. >>So we see as well a lot of clients asking for solutions like the terminal solutions. And like others where there is not anymore discussion about how to move to the The question is how fast how can accelerate. We see the services request the first one. It's amazing. After the event, what we had in London, 100 clients calling us. So it's not our sales people calling upon the clients, the clients coming in. I saw it. How do we get started? And that is for me, from the vendor perspective, so to speak. Amazing moment >>yourself. You go, guys, we're gonna go. Thanks so much for that. You have to have you back and see how that goes. That. Yeah, that's a big story of if you're a great All right, keep it right there. Everybody will be right back. This is David for the Cube. You're watching our live coverage of mongo D B World 20 twenty-two from New York City. >>Yeah, >>Yeah, yeah, yeah, yeah
SUMMARY :
Here is the c e o of those Disrupting the finance world. So we are a software And and so that's why I don't know if you consider that disruptive. of, um, buzzword jail where you could choose words to go into I mean, it's a fascinating piece that it could be truly transformative if we get it right, So, Boris, you have industry solutions in your title. And that's obviously the clients moving show several weeks ago in London and says, Boris, let's do a benchmark And maybe you bring your story So this was 200 million accounts, 100 million customers, So this is you know, So we have This is something we do in the lab you couldn't go live on. So this is not like let's define something new for the world. So it means you get these really efficient numbers what that helped us do with, All that stuff. When I talk to people, we have what we call a system So the the way we the way we architect the solution is it follows something and okay, and the workload had a high locality medium locality. we don't have that. so explain that That's not That's not the mindset for a document. In the document database, you don't have the hot spotting the one single field so that was very close to a So 100 and It's a real life environment out into the wild with the benchmark driving and driving. So all of the banks, when they take the latest release, is they get these benefits. and this was running in the cloud. So this was list, Um, 80 on a W s with a W s cases And then at least for the peace. the timing from, uh, the world. So we see a lot of good feedback as well when we bring it So you typically in financial I think you touched on earlier the appropriate technology. And you know, the exact same question comes up, So So, Yeah, this is a conversation. yeah, I think you know, 20 years ago you probably wouldn't even thought about it. But the other side of it is, you know, it's only relatively recently the the backing components of our because obviously translation which was done before, it's not need it anymore. And that a lot of times lead people to say, of financial clients, and but now it's my job is normally shift and left a pain in the what's the difference between hundreds of millions or billions in some cases, versus, you know, So we see as well a lot of clients asking for solutions like You have to have you back and see how that goes.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Boris | PERSON | 0.99+ |
Tony | PERSON | 0.99+ |
100,000 | QUANTITY | 0.99+ |
London | LOCATION | 0.99+ |
Tony Coleman | PERSON | 0.99+ |
100 | QUANTITY | 0.99+ |
20% | QUANTITY | 0.99+ |
Temenos | PERSON | 0.99+ |
41 | QUANTITY | 0.99+ |
100 clients | QUANTITY | 0.99+ |
one quarter | QUANTITY | 0.99+ |
New York City | LOCATION | 0.99+ |
Boris Bialek | PERSON | 0.99+ |
99% | QUANTITY | 0.99+ |
tomorrow | DATE | 0.99+ |
three years | QUANTITY | 0.99+ |
Monday morning | DATE | 0.99+ |
One-millisecond | QUANTITY | 0.99+ |
100 million customers | QUANTITY | 0.99+ |
89 environments | QUANTITY | 0.99+ |
thirty-two | QUANTITY | 0.99+ |
this year | DATE | 0.99+ |
100,000 transactions | QUANTITY | 0.99+ |
Mongo | ORGANIZATION | 0.99+ |
hundreds of millions | QUANTITY | 0.99+ |
102,800 seventy-five transactions | QUANTITY | 0.99+ |
second | QUANTITY | 0.99+ |
Michael Services | ORGANIZATION | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
First time | QUANTITY | 0.98+ |
billions | QUANTITY | 0.98+ |
three-quarters | QUANTITY | 0.98+ |
20 years ago | DATE | 0.98+ |
first one | QUANTITY | 0.98+ |
several weeks ago | DATE | 0.98+ |
Twenty-five 1000 transactions | QUANTITY | 0.98+ |
late nineties | DATE | 0.98+ |
80 | QUANTITY | 0.98+ |
David | PERSON | 0.98+ |
over 3000 financial institutions | QUANTITY | 0.98+ |
three years ago | DATE | 0.98+ |
MongoDB | ORGANIZATION | 0.98+ |
over 1.2 billion people | QUANTITY | 0.97+ |
Today | DATE | 0.97+ |
today | DATE | 0.97+ |
one | QUANTITY | 0.97+ |
200 million accounts | QUANTITY | 0.96+ |
Seventy-five 1000 queries | QUANTITY | 0.96+ |
Seventy-five 1000 transactions | QUANTITY | 0.96+ |
one thing | QUANTITY | 0.95+ |
15 years | QUANTITY | 0.95+ |
about Twenty-five 1000 transactions | QUANTITY | 0.95+ |
this morning | DATE | 0.94+ |
few weeks ago | DATE | 0.94+ |
one paradigm | QUANTITY | 0.94+ |
twenty-year-old | QUANTITY | 0.93+ |
one part | QUANTITY | 0.93+ |
second response | QUANTITY | 0.93+ |
Thomas City | PERSON | 0.93+ |
more | QUANTITY | 0.92+ |
one single field | QUANTITY | 0.92+ |
10, 15 years | QUANTITY | 0.92+ |
10,000 transactions a second | QUANTITY | 0.92+ |
50 banks | QUANTITY | 0.92+ |
Michael | PERSON | 0.92+ |
first | QUANTITY | 0.91+ |
first live event | QUANTITY | 0.9+ |
mongo D B World 20 twenty-two | TITLE | 0.9+ |
six weeks | DATE | 0.9+ |
Infinity services | ORGANIZATION | 0.83+ |
20 twenty-two | QUANTITY | 0.83+ |
single single 80 system | QUANTITY | 0.8+ |
Atlas | ORGANIZATION | 0.8+ |
50 | QUANTITY | 0.75+ |
four times | QUANTITY | 0.72+ |
for years | QUANTITY | 0.68+ |
a second | QUANTITY | 0.63+ |
every two | QUANTITY | 0.61+ |
double | QUANTITY | 0.59+ |
up | QUANTITY | 0.57+ |
The Impact of Exascale on Business | Exascale Day
>>from around the globe. It's the Q with digital coverage of exa scale day made possible by Hewlett Packard Enterprise. Welcome, everyone to the Cube celebration of Exa Scale Day. Shaheen Khan is here. He's the founding partner, an analyst at Orion X And, among other things, he is the co host of Radio free HPC Shaheen. Welcome. Thanks for coming on. >>Thanks for being here, Dave. Great to be here. How are you >>doing? Well, thanks. Crazy with doing these things, Cove in remote interviews. I wish we were face to face at us at a supercomputer show, but, hey, this thing is working. We can still have great conversations. And And I love talking to analysts like you because you bring an independent perspective. You're very wide observation space. So So let me, Like many analysts, you probably have sort of a mental model or a market model that you look at. So maybe talk about your your work, how you look at the market, and we could get into some of the mega trends that you see >>very well. Very well. Let me just quickly set the scene. We fundamentally track the megatrends of the Information Age And, of course, because we're in the information age, digital transformation falls out of that. And the megatrends that drive that in our mind is Ayotte, because that's the fountain of data five G. Because that's how it's gonna get communicated ai and HBC because that's how we're gonna make sense of it Blockchain and Cryptocurrencies because that's how it's gonna get transacted on. That's how value is going to get transferred from the place took place and then finally, quantum computing, because that exemplifies how things are gonna get accelerated. >>So let me ask you So I spent a lot of time, but I D. C and I had the pleasure of of the High Performance computing group reported into me. I wasn't an HPC analyst, but over time you listen to those guys, you learning. And as I recall, it was HPC was everywhere, and it sounds like we're still seeing that trend where, whether it was, you know, the Internet itself were certainly big data, you know, coming into play. Uh, you know, defense, obviously. But is your background mawr HPC or so that these other technologies that you're talking about it sounds like it's your high performance computing expert market watcher. And then you see it permeating into all these trends. Is that a fair statement? >>That's a fair statement. I did grow up in HPC. My first job out of school was working for an IBM fellow doing payroll processing in the old days on and and And it went from there, I worked for Cray Research. I worked for floating point systems, so I grew up in HPC. But then, over time, uh, we had experiences outside of HPC. So for a number of years, I had to go do commercial enterprise computing and learn about transaction processing and business intelligence and, you know, data warehousing and things like that, and then e commerce and then Web technology. So over time it's sort of expanded. But HPC is a like a bug. You get it and you can't get rid of because it's just so inspiring. So supercomputing has always been my home, so to say >>well and so the reason I ask is I wanted to touch on a little history of the industry is there was kind of a renaissance in many, many years ago, and you had all these startups you had Kendall Square Research Danny Hillis thinking machines. You had convex trying to make many supercomputers. And it was just this This is, you know, tons of money flowing in and and then, you know, things kind of consolidate a little bit and, uh, things got very, very specialized. And then with the big data craze, you know, we've seen HPC really at the heart of all that. So what's your take on on the ebb and flow of the HPC business and how it's evolved? >>Well, HBC was always trying to make sense of the world, was trying to make sense of nature. And of course, as much as we do know about nature, there's a lot we don't know about nature and problems in nature are you can classify those problems into basically linear and nonlinear problems. The linear ones are easy. They've already been solved. The nonlinear wants. Some of them are easy. Many of them are hard, the nonlinear, hard, chaotic. All of those problems are the ones that you really need to solve. The closer you get. So HBC was basically marching along trying to solve these things. It had a whole process, you know, with the scientific method going way back to Galileo, the experimentation that was part of it. And then between theory, you got to look at the experiment and the data. You kind of theorize things. And then you experimented to prove the theories and then simulation and using the computers to validate some things eventually became a third pillar of off science. On you had theory, experiment and simulation. So all of that was going on until the rest of the world, thanks to digitization, started needing some of those same techniques. Why? Because you've got too much data. Simply, there's too much data to ship to the cloud. There's too much data to, uh, make sense of without math and science. So now enterprise computing problems are starting to look like scientific problems. Enterprise data centers are starting to look like national lab data centers, and there is that sort of a convergence that has been taking place gradually, really over the past 34 decades. And it's starting to look really, really now >>interesting, I want I want to ask you about. I was like to talk to analysts about, you know, competition. The competitive landscape is the competition in HPC. Is it between vendors or countries? >>Well, this is a very interesting thing you're saying, because our other thesis is that we are moving a little bit beyond geopolitics to techno politics. And there are now, uh, imperatives at the political level that are driving some of these decisions. Obviously, five G is very visible as as as a piece of technology that is now in the middle of political discussions. Covert 19 as you mentioned itself, is a challenge that is a global challenge that needs to be solved at that level. Ai, who has access to how much data and what sort of algorithms. And it turns out as we all know that for a I, you need a lot more data than you thought. You do so suddenly. Data superiority is more important perhaps than even. It can lead to information superiority. So, yeah, that's really all happening. But the actors, of course, continue to be the vendors that are the embodiment of the algorithms and the data and the systems and infrastructure that feed the applications. So to say >>so let's get into some of these mega trends, and maybe I'll ask you some Colombo questions and weaken geek out a little bit. Let's start with a you know, again, it was one of this when I started the industry. It's all it was a i expert systems. It was all the rage. And then we should have had this long ai winter, even though, you know, the technology never went away. But But there were at least two things that happened. You had all this data on then the cost of computing. You know, declines came down so so rapidly over the years. So now a eyes back, we're seeing all kinds of applications getting infused into virtually every part of our lives. People trying to advertise to us, etcetera. Eso So talk about the intersection of AI and HPC. What are you seeing there? >>Yeah, definitely. Like you said, I has a long history. I mean, you know, it came out of MIT Media Lab and the AI Lab that they had back then and it was really, as you mentioned, all focused on expert systems. It was about logical processing. It was a lot of if then else. And then it morphed into search. How do I search for the right answer, you know, needle in the haystack. But then, at some point, it became computational. Neural nets are not a new idea. I remember you know, we had we had a We had a researcher in our lab who was doing neural networks, you know, years ago. And he was just saying how he was running out of computational power and we couldn't. We were wondering, you know what? What's taking all this difficult, You know, time. And it turns out that it is computational. So when deep neural nets showed up about a decade ago, arm or it finally started working and it was a confluence of a few things. Thalib rhythms were there, the data sets were there, and the technology was there in the form of GPS and accelerators that finally made distractible. So you really could say, as in I do say that a I was kind of languishing for decades before HPC Technologies reignited it. And when you look at deep learning, which is really the only part of a I that has been prominent and has made all this stuff work, it's all HPC. It's all matrix algebra. It's all signal processing algorithms. are computational. The infrastructure is similar to H B. C. The skill set that you need is the skill set of HPC. I see a lot of interest in HBC talent right now in part motivated by a I >>mhm awesome. Thank you on. Then I wanna talk about Blockchain and I can't talk about Blockchain without talking about crypto you've written. You've written about that? I think, you know, obviously supercomputers play a role. I think you had written that 50 of the top crypto supercomputers actually reside in in China A lot of times the vendor community doesn't like to talk about crypto because you know that you know the fraud and everything else. But it's one of the more interesting use cases is actually the primary use case for Blockchain even though Blockchain has so much other potential. But what do you see in Blockchain? The potential of that technology And maybe we can work in a little crypto talk as well. >>Yeah, I think 11 simple way to think of Blockchain is in terms off so called permission and permission less the permission block chains or when everybody kind of knows everybody and you don't really get to participate without people knowing who you are and as a result, have some basis to trust your behavior and your transactions. So things are a lot calmer. It's a lot easier. You don't really need all the supercomputing activity. Whereas for AI the assertion was that intelligence is computer herbal. And with some of these exa scale technologies, we're trying to, you know, we're getting to that point for permission. Less Blockchain. The assertion is that trust is computer ble and, it turns out for trust to be computer ble. It's really computational intensive because you want to provide an incentive based such that good actors are rewarded and back actors. Bad actors are punished, and it is worth their while to actually put all their effort towards good behavior. And that's really what you see, embodied in like a Bitcoin system where the chain has been safe over the many years. It's been no attacks, no breeches. Now people have lost money because they forgot the password or some other. You know, custody of the accounts have not been trustable, but the chain itself has managed to produce that, So that's an example of computational intensity yielding trust. So that suddenly becomes really interesting intelligence trust. What else is computer ble that we could do if we if we had enough power? >>Well, that's really interesting the way you described it, essentially the the confluence of crypto graphics software engineering and, uh, game theory, Really? Where the bad actors air Incentive Thio mined Bitcoin versus rip people off because it's because because there are lives better eso eso so that so So Okay, so make it make the connection. I mean, you sort of did. But But I want to better understand the connection between, you know, supercomputing and HPC and Blockchain. We know we get a crypto for sure, like in mind a Bitcoin which gets harder and harder and harder. Um and you mentioned there's other things that we can potentially compute on trust. Like what? What else? What do you thinking there? >>Well, I think that, you know, the next big thing that we are really seeing is in communication. And it turns out, as I was saying earlier, that these highly computational intensive algorithms and models show up in all sorts of places like, you know, in five g communication, there's something called the memo multi and multi out and to optimally manage that traffic such that you know exactly what beam it's going to and worth Antenna is coming from that turns out to be a non trivial, you know, partial differential equation. So next thing you know, you've got HPC in there as and he didn't expect it because there's so much data to be sent, you really have to do some data reduction and data processing almost at the point of inception, if not at the point of aggregation. So that has led to edge computing and edge data centers. And that, too, is now. People want some level of computational capability at that place like you're building a microcontroller, which traditionally would just be a, you know, small, low power, low cost thing. And people want victor instructions. There. People want matrix algebra there because it makes sense to process the data before you have to ship it. So HPCs cropping up really everywhere. And then finally, when you're trying to accelerate things that obviously GP use have been a great example of that mixed signal technologies air coming to do analog and digital at the same time, quantum technologies coming so you could do the you know, the usual analysts to buy to where you have analog, digital, classical quantum and then see which, you know, with what lies where all of that is coming. And all of that is essentially resting on HBC. >>That's interesting. I didn't realize that HBC had that position in five G with multi and multi out. That's great example and then I o t. I want to ask you about that because there's a lot of discussion about real time influencing AI influencing at the edge on you're seeing sort of new computing architectures, potentially emerging, uh, video. The acquisition of arm Perhaps, you know, amore efficient way, maybe a lower cost way of doing specialized computing at the edge it, But it sounds like you're envisioning, actually, supercomputing at the edge. Of course, we've talked to Dr Mark Fernandez about space born computers. That's like the ultimate edge you got. You have supercomputers hanging on the ceiling of the International space station, but But how far away are we from this sort of edge? Maybe not. Space is an extreme example, but you think factories and windmills and all kinds of edge examples where supercomputing is is playing a local role. >>Well, I think initially you're going to see it on base stations, Antenna towers, where you're aggregating data from a large number of endpoints and sensors that are gathering the data, maybe do some level of local processing and then ship it to the local antenna because it's no more than 100 m away sort of a thing. But there is enough there that that thing can now do the processing and do some level of learning and decide what data to ship back to the cloud and what data to get rid of and what data to just hold. Or now those edge data centers sitting on top of an antenna. They could have a half a dozen GPS in them. They're pretty powerful things. They could have, you know, one they could have to, but but it could be depending on what you do. A good a good case study. There is like surveillance cameras. You don't really need to ship every image back to the cloud. And if you ever need it, the guy who needs it is gonna be on the scene, not back at the cloud. So there is really no sense in sending it, Not certainly not every frame. So maybe you can do some processing and send an image every five seconds or every 10 seconds, and that way you can have a record of it. But you've reduced your bandwidth by orders of magnitude. So things like that are happening. And toe make sense of all of that is to recognize when things changed. Did somebody come into the scene or is it just you know that you know, they became night, So that's sort of a decision. Cannot be automated and fundamentally what is making it happen? It may not be supercomputing exa scale class, but it's definitely HPCs, definitely numerically oriented technologies. >>Shane, what do you see happening in chip architectures? Because, you see, you know the classical intel they're trying to put as much function on the real estate as possible. We've seen the emergence of alternative processors, particularly, uh, GP use. But even if f b g A s, I mentioned the arm acquisition, so you're seeing these alternative processors really gain momentum and you're seeing data processing units emerge and kind of interesting trends going on there. What do you see? And what's the relationship to HPC? >>Well, I think a few things are going on there. Of course, one is, uh, essentially the end of Moore's law, where you cannot make the cycle time be any faster, so you have to do architectural adjustments. And then if you have a killer app that lends itself to large volume, you can build silicon. That is especially good for that now. Graphics and gaming was an example of that, and people said, Oh my God, I've got all these cores in there. Why can't I use it for computation? So everybody got busy making it 64 bit capable and some grass capability, And then people say, Oh, I know I can use that for a I And you know, now you move it to a I say, Well, I don't really need 64 but maybe I can do it in 32 or 16. So now you do it for that, and then tens, of course, come about. And so there's that sort of a progression of architecture, er trumping, basically cycle time. That's one thing. The second thing is scale out and decentralization and distributed computing. And that means that the inter communication and intra communication among all these notes now becomes an issue big enough issue that maybe it makes sense to go to a DPU. Maybe it makes sense to go do some level of, you know, edge data centers like we were talking about on then. The third thing, really is that in many of these cases you have data streaming. What is really coming from I o t, especially an edge, is that data is streaming and when data streaming suddenly new architectures like F B G. A s become really interesting and and and hold promise. So I do see, I do see FPG's becoming more prominent just for that reason, but then finally got a program all of these things on. That's really a difficulty, because what happens now is that you need to get three different ecosystems together mobile programming, embedded programming and cloud programming. And those are really three different developer types. You can't hire somebody who's good at all three. I mean, maybe you can, but not many. So all of that is challenges that are driving this this this this industry, >>you kind of referred to this distributed network and a lot of people you know, they refer to this. The next generation cloud is this hyper distributed system. When you include the edge and multiple clouds that etcetera space, maybe that's too extreme. But to your point, at least I inferred there's a There's an issue of Leighton. See, there's the speed of light s So what? What? What is the implication then for HBC? Does that mean I have tow Have all the data in one place? Can I move the compute to the data architecturally, What are you seeing there? >>Well, you fundamentally want to optimize when to move data and when to move, Compute. Right. So is it better to move data to compute? Or is it better to bring compute to data and under what conditions? And the dancer is gonna be different for different use cases. It's like, really, is it worth my while to make the trip, get my processing done and then come back? Or should I just developed processing capability right here? Moving data is really expensive and relatively speaking. It has become even more expensive, while the price of everything has dropped down its price has dropped less than than than like processing. So it is now starting to make sense to do a lot of local processing because processing is cheap and moving data is expensive Deep Use an example of that, Uh, you know, we call this in C two processing like, you know, let's not move data. If you don't have to accept that we live in the age of big data, so data is huge and wants to be moved. And that optimization, I think, is part of what you're what you're referring to. >>Yeah, So a couple examples might be autonomous vehicles. You gotta have to make decisions in real time. You can't send data back to the cloud flip side of that is we talk about space borne computers. You're collecting all this data You can at some point. You know, maybe it's a year or two after the lived out its purpose. You ship that data back and a bunch of disk drives or flash drives, and then load it up into some kind of HPC system and then have at it and then you doom or modeling and learn from that data corpus, right? I mean those air, >>right? Exactly. Exactly. Yeah. I mean, you know, driverless vehicles is a great example, because it is obviously coming fast and furious, no pun intended. And also, it dovetails nicely with the smart city, which dovetails nicely with I o. T. Because it is in an urban area. Mostly, you can afford to have a lot of antenna, so you can give it the five g density that you want. And it requires the Layton sees. There's a notion of how about if my fleet could communicate with each other. What if the car in front of me could let me know what it sees, That sort of a thing. So, you know, vehicle fleets is going to be in a non opportunity. All of that can bring all of what we talked about. 21 place. >>Well, that's interesting. Okay, so yeah, the fleets talking to each other. So kind of a Byzantine fault. Tolerance. That problem that you talk about that z kind of cool. I wanna I wanna sort of clothes on quantum. It's hard to get your head around. Sometimes You see the demonstrations of quantum. It's not a one or zero. It could be both. And you go, What? How did come that being so? And And of course, there it's not stable. Uh, looks like it's quite a ways off, but the potential is enormous. It's of course, it's scary because we think all of our, you know, passwords are already, you know, not secure. And every password we know it's gonna get broken. But give us the give us the quantum 101 And let's talk about what the implications. >>All right, very well. So first off, we don't need to worry about our passwords quite yet. That that that's that's still ways off. It is true that analgesic DM came up that showed how quantum computers can fact arise numbers relatively fast and prime factory ization is at the core of a lot of cryptology algorithms. So if you can fact arise, you know, if you get you know, number 21 you say, Well, that's three times seven, and those three, you know, three and seven or prime numbers. Uh, that's an example of a problem that has been solved with quantum computing, but if you have an actual number, would like, you know, 2000 digits in it. That's really harder to do. It's impossible to do for existing computers and even for quantum computers. Ways off, however. So as you mentioned, cubits can be somewhere between zero and one, and you're trying to create cubits Now there are many different ways of building cubits. You can do trapped ions, trapped ion trapped atoms, photons, uh, sometimes with super cool, sometimes not super cool. But fundamentally, you're trying to get these quantum level elements or particles into a superimposed entanglement state. And there are different ways of doing that, which is why quantum computers out there are pursuing a lot of different ways. The whole somebody said it's really nice that quantum computing is simultaneously overhyped and underestimated on. And that is that is true because there's a lot of effort that is like ways off. On the other hand, it is so exciting that you don't want to miss out if it's going to get somewhere. So it is rapidly progressing, and it has now morphed into three different segments. Quantum computing, quantum communication and quantum sensing. Quantum sensing is when you can measure really precise my new things because when you perturb them the quantum effects can allow you to measure them. Quantum communication is working its way, especially in financial services, initially with quantum key distribution, where the key to your cryptography is sent in a quantum way. And the data sent a traditional way that our efforts to do quantum Internet, where you actually have a quantum photon going down the fiber optic lines and Brookhaven National Labs just now demonstrated a couple of weeks ago going pretty much across the, you know, Long Island and, like 87 miles or something. So it's really coming, and and fundamentally, it's going to be brand new algorithms. >>So these examples that you're giving these air all in the lab right there lab projects are actually >>some of them are in the lab projects. Some of them are out there. Of course, even traditional WiFi has benefited from quantum computing or quantum analysis and, you know, algorithms. But some of them are really like quantum key distribution. If you're a bank in New York City, you very well could go to a company and by quantum key distribution services and ship it across the you know, the waters to New Jersey on that is happening right now. Some researchers in China and Austria showed a quantum connection from, like somewhere in China, to Vienna, even as far away as that. When you then put the satellite and the nano satellites and you know, the bent pipe networks that are being talked about out there, that brings another flavor to it. So, yes, some of it is like real. Some of it is still kind of in the last. >>How about I said I would end the quantum? I just e wanna ask you mentioned earlier that sort of the geopolitical battles that are going on, who's who are the ones to watch in the Who? The horses on the track, obviously United States, China, Japan. Still pretty prominent. How is that shaping up in your >>view? Well, without a doubt, it's the US is to lose because it's got the density and the breadth and depth of all the technologies across the board. On the other hand, information age is a new eyes. Their revolution information revolution is is not trivial. And when revolutions happen, unpredictable things happen, so you gotta get it right and and one of the things that these technologies enforce one of these. These revolutions enforce is not just kind of technological and social and governance, but also culture, right? The example I give is that if you're a farmer, it takes you maybe a couple of seasons before you realize that you better get up at the crack of dawn and you better do it in this particular season. You're gonna starve six months later. So you do that to three years in a row. A culture has now been enforced on you because that's how it needs. And then when you go to industrialization, you realize that Gosh, I need these factories. And then, you know I need workers. And then next thing you know, you got 9 to 5 jobs and you didn't have that before. You don't have a command and control system. You had it in military, but not in business. And and some of those cultural shifts take place on and change. So I think the winner is going to be whoever shows the most agility in terms off cultural norms and governance and and and pursuit of actual knowledge and not being distracted by what you think. But what actually happens and Gosh, I think these exa scale technologies can make the difference. >>Shaheen Khan. Great cast. Thank you so much for joining us to celebrate the extra scale day, which is, uh, on 10. 18 on dso. Really? Appreciate your insights. >>Likewise. Thank you so much. >>All right. Thank you for watching. Keep it right there. We'll be back with our next guest right here in the Cube. We're celebrating Exa scale day right back.
SUMMARY :
he is the co host of Radio free HPC Shaheen. How are you to analysts like you because you bring an independent perspective. And the megatrends that drive that in our mind And then you see it permeating into all these trends. You get it and you can't get rid And it was just this This is, you know, tons of money flowing in and and then, And then you experimented to prove the theories you know, competition. And it turns out as we all know that for a I, you need a lot more data than you thought. ai winter, even though, you know, the technology never went away. is similar to H B. C. The skill set that you need is the skill set community doesn't like to talk about crypto because you know that you know the fraud and everything else. And with some of these exa scale technologies, we're trying to, you know, we're getting to that point for Well, that's really interesting the way you described it, essentially the the confluence of crypto is coming from that turns out to be a non trivial, you know, partial differential equation. I want to ask you about that because there's a lot of discussion about real time influencing AI influencing Did somebody come into the scene or is it just you know that you know, they became night, Because, you see, you know the classical intel they're trying to put And then people say, Oh, I know I can use that for a I And you know, now you move it to a I say, Can I move the compute to the data architecturally, What are you seeing there? an example of that, Uh, you know, we call this in C two processing like, it and then you doom or modeling and learn from that data corpus, so you can give it the five g density that you want. It's of course, it's scary because we think all of our, you know, passwords are already, So if you can fact arise, you know, if you get you know, number 21 you say, and ship it across the you know, the waters to New Jersey on that is happening I just e wanna ask you mentioned earlier that sort of the geopolitical And then next thing you know, you got 9 to 5 jobs and you didn't have that before. Thank you so much for joining us to celebrate the Thank you so much. Thank you for watching.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Shaheen Khan | PERSON | 0.99+ |
China | LOCATION | 0.99+ |
Vienna | LOCATION | 0.99+ |
Austria | LOCATION | 0.99+ |
MIT Media Lab | ORGANIZATION | 0.99+ |
New York City | LOCATION | 0.99+ |
Orion X | ORGANIZATION | 0.99+ |
New Jersey | LOCATION | 0.99+ |
50 | QUANTITY | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Dave | PERSON | 0.99+ |
9 | QUANTITY | 0.99+ |
Shane | PERSON | 0.99+ |
Long Island | LOCATION | 0.99+ |
AI Lab | ORGANIZATION | 0.99+ |
Cray Research | ORGANIZATION | 0.99+ |
Brookhaven National Labs | ORGANIZATION | 0.99+ |
Japan | LOCATION | 0.99+ |
Kendall Square Research | ORGANIZATION | 0.99+ |
5 jobs | QUANTITY | 0.99+ |
Cove | PERSON | 0.99+ |
2000 digits | QUANTITY | 0.99+ |
United States | LOCATION | 0.99+ |
Hewlett Packard Enterprise | ORGANIZATION | 0.99+ |
Danny Hillis | PERSON | 0.99+ |
a year | QUANTITY | 0.99+ |
half a dozen | QUANTITY | 0.98+ |
third thing | QUANTITY | 0.98+ |
both | QUANTITY | 0.98+ |
three | QUANTITY | 0.98+ |
one | QUANTITY | 0.98+ |
64 | QUANTITY | 0.98+ |
Exa Scale Day | EVENT | 0.98+ |
32 | QUANTITY | 0.98+ |
six months later | DATE | 0.98+ |
64 bit | QUANTITY | 0.98+ |
third pillar | QUANTITY | 0.98+ |
16 | QUANTITY | 0.97+ |
first | QUANTITY | 0.97+ |
HBC | ORGANIZATION | 0.97+ |
one place | QUANTITY | 0.97+ |
87 miles | QUANTITY | 0.97+ |
tens | QUANTITY | 0.97+ |
Mark Fernandez | PERSON | 0.97+ |
zero | QUANTITY | 0.97+ |
Shaheen | PERSON | 0.97+ |
seven | QUANTITY | 0.96+ |
first job | QUANTITY | 0.96+ |
HPC Technologies | ORGANIZATION | 0.96+ |
two | QUANTITY | 0.94+ |
three different ecosystems | QUANTITY | 0.94+ |
every 10 seconds | QUANTITY | 0.94+ |
every five seconds | QUANTITY | 0.93+ |
Byzantine | PERSON | 0.93+ |
Exa scale day | EVENT | 0.93+ |
second thing | QUANTITY | 0.92+ |
Moore | PERSON | 0.9+ |
years ago | DATE | 0.89+ |
HPC | ORGANIZATION | 0.89+ |
three years | QUANTITY | 0.89+ |
three different developer | QUANTITY | 0.89+ |
Exascale Day | EVENT | 0.88+ |
Galileo | PERSON | 0.88+ |
three times | QUANTITY | 0.88+ |
a couple of weeks ago | DATE | 0.85+ |
exa scale day | EVENT | 0.84+ |
D. C | PERSON | 0.84+ |
many years ago | DATE | 0.81+ |
a decade ago | DATE | 0.81+ |
about | DATE | 0.81+ |
C two | TITLE | 0.81+ |
one thing | QUANTITY | 0.8+ |
10. 18 | DATE | 0.8+ |
Dr | PERSON | 0.79+ |
past 34 decades | DATE | 0.77+ |
two things | QUANTITY | 0.76+ |
Leighton | ORGANIZATION | 0.76+ |
11 simple way | QUANTITY | 0.75+ |
21 place | QUANTITY | 0.74+ |
three different segments | QUANTITY | 0.74+ |
more than 100 m | QUANTITY | 0.73+ |
FPG | ORGANIZATION | 0.73+ |
decades | QUANTITY | 0.71+ |
five | QUANTITY | 0.7+ |
Armstrong and Guhamad and Jacques V2
>>from around the globe. It's the Cube covering >>space and cybersecurity. Symposium 2020 hosted by Cal Poly >>Over On Welcome to this Special virtual conference. The Space and Cybersecurity Symposium 2020 put on by Cal Poly with support from the Cube. I'm John for your host and master of ceremonies. Got a great topic today in this session. Really? The intersection of space and cybersecurity. This topic and this conversation is the cybersecurity workforce development through public and private partnerships. And we've got a great lineup. We have Jeff Armstrong's the president of California Polytechnic State University, also known as Cal Poly Jeffrey. Thanks for jumping on and Bang. Go ahead. The second director of C four s R Division. And he's joining us from the office of the Under Secretary of Defense for the acquisition Sustainment Department of Defense, D O D. And, of course, Steve Jake's executive director, founder, National Security Space Association and managing partner at Bello's. Gentlemen, thank you for joining me for this session. We got an hour conversation. Thanks for coming on. >>Thank you. >>So we got a virtual event here. We've got an hour, have a great conversation and love for you guys do? In opening statement on how you see the development through public and private partnerships around cybersecurity in space, Jeff will start with you. >>Well, thanks very much, John. It's great to be on with all of you. Uh, on behalf Cal Poly Welcome, everyone. Educating the workforce of tomorrow is our mission to Cal Poly. Whether that means traditional undergraduates, master students are increasingly mid career professionals looking toe up, skill or re skill. Our signature pedagogy is learn by doing, which means that our graduates arrive at employers ready Day one with practical skills and experience. We have long thought of ourselves is lucky to be on California's beautiful central Coast. But in recent years, as we have developed closer relationships with Vandenberg Air Force Base, hopefully the future permanent headquarters of the United States Space Command with Vandenberg and other regional partners, we have discovered that our location is even more advantages than we thought. We're just 50 miles away from Vandenberg, a little closer than u C. Santa Barbara, and the base represents the southern border of what we have come to think of as the central coast region. Cal Poly and Vandenberg Air force base have partner to support regional economic development to encourage the development of a commercial spaceport toe advocate for the space Command headquarters coming to Vandenberg and other ventures. These partnerships have been possible because because both parties stand to benefit Vandenberg by securing new streams of revenue, workforce and local supply chain and Cal Poly by helping to grow local jobs for graduates, internship opportunities for students, and research and entrepreneurship opportunities for faculty and staff. Crucially, what's good for Vandenberg Air Force Base and for Cal Poly is also good for the Central Coast and the US, creating new head of household jobs, infrastructure and opportunity. Our goal is that these new jobs bring more diversity and sustainability for the region. This regional economic development has taken on a life of its own, spawning a new nonprofit called Reach, which coordinates development efforts from Vandenberg Air Force Base in the South to camp to Camp Roberts in the North. Another factor that is facilitated our relationship with Vandenberg Air Force Base is that we have some of the same friends. For example, Northrop Grumman has has long been an important defense contractor, an important partner to Cal poly funding scholarships and facilities that have allowed us to stay current with technology in it to attract highly qualified students for whom Cal Poly's costs would otherwise be prohibitive. For almost 20 years north of grimness funded scholarships for Cal Poly students this year, their funding 64 scholarships, some directly in our College of Engineering and most through our Cal Poly Scholars program, Cal Poly Scholars, a support both incoming freshman is transfer students. These air especially important because it allows us to provide additional support and opportunities to a group of students who are mostly first generation, low income and underrepresented and who otherwise might not choose to attend Cal Poly. They also allow us to recruit from partner high schools with large populations of underrepresented minority students, including the Fortune High School in Elk Grove, which we developed a deep and lasting connection. We know that the best work is done by balanced teams that include multiple and diverse perspectives. These scholarships help us achieve that goal, and I'm sure you know Northrop Grumman was recently awarded a very large contract to modernized the U. S. I. C B M Armory with some of the work being done at Vandenberg Air Force Base, thus supporting the local economy and protecting protecting our efforts in space requires partnerships in the digital realm. How Polly is partnered with many private companies, such as AWS. Our partnerships with Amazon Web services has enabled us to train our students with next generation cloud engineering skills, in part through our jointly created digital transformation hub. Another partnership example is among Cal Poly's California Cybersecurity Institute, College of Engineering and the California National Guard. This partnership is focused on preparing a cyber ready workforce by providing faculty and students with a hands on research and learning environment, side by side with military, law enforcement professionals and cyber experts. We also have a long standing partnership with PG and E, most recently focused on workforce development and redevelopment. Many of our graduates do indeed go on to careers in aerospace and defense industry as a rough approximation. More than 4500 Cal Poly graduates list aerospace and defense as their employment sector on linked in, and it's not just our engineers and computer sciences. When I was speaking to our fellow Panelists not too long ago, >>are >>speaking to bang, we learned that Rachel sins, one of our liberal arts arts majors, is working in his office. So shout out to you, Rachel. And then finally, of course, some of our graduates sword extraordinary heights such as Commander Victor Glover, who will be heading to the International space station later this year as I close. All of which is to say that we're deeply committed the workforce, development and redevelopment that we understand the value of public private partnerships and that were eager to find new ways in which to benefit everyone from this further cooperation. So we're committed to the region, the state in the nation and our past efforts in space, cybersecurity and links to our partners at as I indicated, aerospace industry and governmental partners provides a unique position for us to move forward in the interface of space and cybersecurity. Thank you so much, John. >>President, I'm sure thank you very much for the comments and congratulations to Cal Poly for being on the forefront of innovation and really taking a unique progressive. You and wanna tip your hat to you guys over there. Thank you very much for those comments. Appreciate it. Bahng. Department of Defense. Exciting you gotta defend the nation spaces Global. Your opening statement. >>Yes, sir. Thanks, John. Appreciate that day. Thank you, everybody. I'm honored to be this panel along with President Armstrong, Cal Poly in my long longtime friend and colleague Steve Jakes of the National Security Space Association, to discuss a very important topic of cybersecurity workforce development, as President Armstrong alluded to, I'll tell you both of these organizations, Cal Poly and the N S. A have done and continue to do an exceptional job at finding talent, recruiting them in training current and future leaders and technical professionals that we vitally need for our nation's growing space programs. A swell Asare collective National security Earlier today, during Session three high, along with my colleague Chris Hansen discussed space, cyber Security and how the space domain is changing the landscape of future conflicts. I discussed the rapid emergence of commercial space with the proliferations of hundreds, if not thousands, of satellites providing a variety of services, including communications allowing for global Internet connectivity. S one example within the O. D. We continue to look at how we can leverage this opportunity. I'll tell you one of the enabling technologies eyes the use of small satellites, which are inherently cheaper and perhaps more flexible than the traditional bigger systems that we have historically used unemployed for the U. D. Certainly not lost on Me is the fact that Cal Poly Pioneer Cube SATs 2020 some years ago, and they set the standard for the use of these systems today. So they saw the valiant benefit gained way ahead of everybody else, it seems, and Cal Poly's focus on training and education is commendable. I especially impressed by the efforts of another of Steve's I colleague, current CEO Mr Bill Britain, with his high energy push to attract the next generation of innovators. Uh, earlier this year, I had planned on participating in this year's Cyber Innovation Challenge. In June works Cal Poly host California Mill and high school students and challenge them with situations to test their cyber knowledge. I tell you, I wish I had that kind of opportunity when I was a kid. Unfortunately, the pandemic change the plan. Why I truly look forward. Thio feature events such as these Thio participating. Now I want to recognize my good friend Steve Jakes, whom I've known for perhaps too long of a time here over two decades or so, who was in acknowledge space expert and personally, I truly applaud him for having the foresight of years back to form the National Security Space Association to help the entire space enterprise navigate through not only technology but Polly policy issues and challenges and paved the way for operational izing space. Space is our newest horrifying domain. That's not a secret anymore. Uh, and while it is a unique area, it shares a lot of common traits with the other domains such as land, air and sea, obviously all of strategically important to the defense of the United States. In conflict they will need to be. They will all be contested and therefore they all need to be defended. One domain alone will not win future conflicts in a joint operation. We must succeed. All to defending space is critical as critical is defending our other operational domains. Funny space is no longer the sanctuary available only to the government. Increasingly, as I discussed in the previous session, commercial space is taking the lead a lot of different areas, including R and D, A so called new space, so cyber security threat is even more demanding and even more challenging. Three US considers and federal access to and freedom to operate in space vital to advancing security, economic prosperity, prosperity and scientific knowledge of the country. That's making cyberspace an inseparable component. America's financial, social government and political life. We stood up US Space force ah, year ago or so as the newest military service is like the other services. Its mission is to organize, train and equip space forces in order to protect us and allied interest in space and to provide space capabilities to the joint force. Imagine combining that US space force with the U. S. Cyber Command to unify the direction of space and cyberspace operation strengthened U D capabilities and integrate and bolster d o d cyber experience. Now, of course, to enable all of this requires had trained and professional cadre of cyber security experts, combining a good mix of policy as well as high technical skill set much like we're seeing in stem, we need to attract more people to this growing field. Now the D. O. D. Is recognized the importance of the cybersecurity workforce, and we have implemented policies to encourage his growth Back in 2013 the deputy secretary of defense signed the D. O d cyberspace workforce strategy to create a comprehensive, well equipped cyber security team to respond to national security concerns. Now this strategy also created a program that encourages collaboration between the D. O. D and private sector employees. We call this the Cyber Information Technology Exchange program or site up. It's an exchange programs, which is very interesting, in which a private sector employees can naturally work for the D. O. D. In a cyber security position that spans across multiple mission critical areas are important to the d. O. D. A key responsibility of cybersecurity community is military leaders on the related threats and cyber security actions we need to have to defeat these threats. We talk about rapid that position, agile business processes and practices to speed up innovation. Likewise, cybersecurity must keep up with this challenge to cyber security. Needs to be right there with the challenges and changes, and this requires exceptional personnel. We need to attract talent investing the people now to grow a robust cybersecurity, workforce, streets, future. I look forward to the panel discussion, John. Thank you. >>Thank you so much bomb for those comments and you know, new challenges and new opportunities and new possibilities and free freedom Operating space. Critical. Thank you for those comments. Looking forward. Toa chatting further. Steve Jakes, executive director of N. S. S. A Europe opening statement. >>Thank you, John. And echoing bangs thanks to Cal Poly for pulling these this important event together and frankly, for allowing the National Security Space Association be a part of it. Likewise, we on behalf the association delighted and honored Thio be on this panel with President Armstrong along with my friend and colleague Bonneau Glue Mahad Something for you all to know about Bomb. He spent the 1st 20 years of his career in the Air Force doing space programs. He then went into industry for several years and then came back into government to serve. Very few people do that. So bang on behalf of the space community, we thank you for your long life long devotion to service to our nation. We really appreciate that and I also echo a bang shot out to that guy Bill Britain, who has been a long time co conspirator of ours for a long time and you're doing great work there in the cyber program at Cal Poly Bill, keep it up. But professor arms trying to keep a close eye on him. Uh, I would like to offer a little extra context to the great comments made by by President Armstrong and bahng. Uh, in our view, the timing of this conference really could not be any better. Um, we all recently reflected again on that tragic 9 11 surprise attack on our homeland. And it's an appropriate time, we think, to take pause while the percentage of you in the audience here weren't even born or babies then For the most of us, it still feels like yesterday. And moreover, a tragedy like 9 11 has taught us a lot to include to be more vigilant, always keep our collective eyes and ears open to include those quote eyes and ears from space, making sure nothing like this ever happens again. So this conference is a key aspect. Protecting our nation requires we work in a cybersecurity environment at all times. But, you know, the fascinating thing about space systems is we can't see him. No, sir, We see Space launches man there's nothing more invigorating than that. But after launch, they become invisible. So what are they really doing up there? What are they doing to enable our quality of life in the United States and in the world? Well, to illustrate, I'd like to paraphrase elements of an article in Forbes magazine by Bonds and my good friend Chuck Beans. Chuck. It's a space guy, actually had Bonds job a fuse in the Pentagon. He is now chairman and chief strategy officer at York Space Systems, and in his spare time he's chairman of the small satellites. Chuck speaks in words that everyone can understand. So I'd like to give you some of his words out of his article. Uh, they're afraid somewhat. So these are Chuck's words. Let's talk about average Joe and playing Jane. Before heading to the airport for a business trip to New York City, Joe checks the weather forecast informed by Noah's weather satellites to see what pack for the trip. He then calls an uber that space app. Everybody uses it matches riders with drivers via GPS to take into the airport, So Joe has lunch of the airport. Unbeknownst to him, his organic lunch is made with the help of precision farming made possible through optimized irrigation and fertilization, with remote spectral sensing coming from space and GPS on the plane, the pilot navigates around weather, aided by GPS and nose weather satellites. And Joe makes his meeting on time to join his New York colleagues in a video call with a key customer in Singapore made possible by telecommunication satellites. Around to his next meeting, Joe receives notice changing the location of the meeting to another to the other side of town. So he calmly tells Syria to adjust the destination, and his satellite guided Google maps redirects him to the new location. That evening, Joe watches the news broadcast via satellite. The report details a meeting among world leaders discussing the developing crisis in Syria. As it turns out, various forms of quote remotely sensed. Information collected from satellites indicate that yet another band, chemical weapon, may have been used on its own people. Before going to bed, Joe decides to call his parents and congratulate them for their wedding anniversary as they cruise across the Atlantic, made possible again by communications satellites and Joe's parents can enjoy the call without even wondering how it happened the next morning. Back home, Joe's wife, Jane, is involved in a car accident. Her vehicle skids off the road. She's knocked unconscious, but because of her satellite equipped on star system, the crash is detected immediately and first responders show up on the scene. In time, Joe receives the news books. An early trip home sends flowers to his wife as he orders another uber to the airport. Over that 24 hours, Joe and Jane used space system applications for nearly every part of their day. Imagine the consequences if at any point they were somehow denied these services, whether they be by natural causes or a foreign hostility. And each of these satellite applications used in this case were initially developed for military purposes and continue to be, but also have remarkable application on our way of life. Just many people just don't know that. So, ladies and gentlemen, now you know, thanks to chuck beans, well, the United States has a proud heritage being the world's leading space faring nation, dating back to the Eisenhower and Kennedy years. Today we have mature and robust systems operating from space, providing overhead reconnaissance to quote, wash and listen, provide missile warning, communications, positioning, navigation and timing from our GPS system. Much of what you heard in Lieutenant General J. T. Thompson earlier speech. These systems are not only integral to our national security, but also our also to our quality of life is Chuck told us. We simply no longer could live without these systems as a nation and for that matter, as a world. But over the years, adversary like adversaries like China, Russia and other countries have come to realize the value of space systems and are aggressively playing ketchup while also pursuing capabilities that will challenge our systems. As many of you know, in 2000 and seven, China demonstrated it's a set system by actually shooting down is one of its own satellites and has been aggressively developing counter space systems to disrupt hours. So in a heavily congested space environment, our systems are now being contested like never before and will continue to bay well as Bond mentioned, the United States has responded to these changing threats. In addition to adding ways to protect our system, the administration and in Congress recently created the United States Space Force and the operational you United States Space Command, the latter of which you heard President Armstrong and other Californians hope is going to be located. Vandenberg Air Force Base Combined with our intelligence community today, we have focused military and civilian leadership now in space. And that's a very, very good thing. Commence, really. On the industry side, we did create the National Security Space Association devoted solely to supporting the national security Space Enterprise. We're based here in the D C area, but we have arms and legs across the country, and we are loaded with extraordinary talent. In scores of Forman, former government executives, So S s a is joined at the hip with our government customers to serve and to support. We're busy with a multitude of activities underway ranging from a number of thought provoking policy. Papers are recurring space time Webcast supporting Congress's Space Power Caucus and other main serious efforts. Check us out at NSS. A space dot org's One of our strategic priorities in central to today's events is to actively promote and nurture the workforce development. Just like cow calling. We will work with our U. S. Government customers, industry leaders and academia to attract and recruit students to join the space world, whether in government or industry and two assistant mentoring and training as their careers. Progress on that point, we're delighted. Be delighted to be working with Cal Poly as we hopefully will undertake a new pilot program with him very soon. So students stay tuned something I can tell you Space is really cool. While our nation's satellite systems are technical and complex, our nation's government and industry work force is highly diverse, with a combination of engineers, physicists, method and mathematicians, but also with a large non technical expertise as well. Think about how government gets things thes systems designed, manufactured, launching into orbit and operating. They do this via contracts with our aerospace industry, requiring talents across the board from cost estimating cost analysis, budgeting, procurement, legal and many other support. Tasker Integral to the mission. Many thousands of people work in the space workforce tens of billions of dollars every year. This is really cool stuff, no matter what your education background, a great career to be part of. When summary as bang had mentioned Aziz, well, there is a great deal of exciting challenges ahead we will see a new renaissance in space in the years ahead, and in some cases it's already begun. Billionaires like Jeff Bezos, Elon Musk, Sir Richard Richard Branson are in the game, stimulating new ideas in business models, other private investors and start up companies. Space companies are now coming in from all angles. The exponential advancement of technology and microelectronics now allows the potential for a plethora of small SAT systems to possibly replace older satellites the size of a Greyhound bus. It's getting better by the day and central to this conference, cybersecurity is paramount to our nation's critical infrastructure in space. So once again, thanks very much, and I look forward to the further conversation. >>Steve, thank you very much. Space is cool. It's relevant. But it's important, as you pointed out, and you're awesome story about how it impacts our life every day. So I really appreciate that great story. I'm glad you took the time Thio share that you forgot the part about the drone coming over in the crime scene and, you know, mapping it out for you. But that would add that to the story later. Great stuff. My first question is let's get into the conversations because I think this is super important. President Armstrong like you to talk about some of the points that was teased out by Bang and Steve. One in particular is the comment around how military research was important in developing all these capabilities, which is impacting all of our lives. Through that story. It was the military research that has enabled a generation and generation of value for consumers. This is kind of this workforce conversation. There are opportunities now with with research and grants, and this is, ah, funding of innovation that it's highly accelerate. It's happening very quickly. Can you comment on how research and the partnerships to get that funding into the universities is critical? >>Yeah, I really appreciate that And appreciate the comments of my colleagues on it really boils down to me to partnerships, public private partnerships. You mentioned Northrop Grumman, but we have partnerships with Lockie Martin, Boeing, Raytheon Space six JPL, also member of organization called Business Higher Education Forum, which brings together university presidents and CEOs of companies. There's been focused on cybersecurity and data science, and I hope that we can spill into cybersecurity in space but those partnerships in the past have really brought a lot forward at Cal Poly Aziz mentioned we've been involved with Cube set. Uh, we've have some secure work and we want to plan to do more of that in the future. Uh, those partnerships are essential not only for getting the r and d done, but also the students, the faculty, whether masters or undergraduate, can be involved with that work. Uh, they get that real life experience, whether it's on campus or virtually now during Covic or at the location with the partner, whether it may be governmental or our industry. Uh, and then they're even better equipped, uh, to hit the ground running. And of course, we'd love to see even more of our students graduate with clearance so that they could do some of that a secure work as well. So these partnerships are absolutely critical, and it's also in the context of trying to bring the best and the brightest and all demographics of California and the US into this field, uh, to really be successful. So these partnerships are essential, and our goal is to grow them just like I know other colleagues and C. S u and the U C are planning to dio, >>you know, just as my age I've seen I grew up in the eighties, in college and during that systems generation and that the generation before me, they really kind of pioneered the space that spawned the computer revolution. I mean, you look at these key inflection points in our lives. They were really funded through these kinds of real deep research. Bond talk about that because, you know, we're living in an age of cloud. And Bezos was mentioned. Elon Musk. Sir Richard Branson. You got new ideas coming in from the outside. You have an accelerated clock now on terms of the innovation cycles, and so you got to react differently. You guys have programs to go outside >>of >>the Defense Department. How important is this? Because the workforce that air in schools and our folks re skilling are out there and you've been on both sides of the table. So share your thoughts. >>No, thanks, John. Thanks for the opportunity responded. And that's what you hit on the notes back in the eighties, R and D in space especially, was dominated by my government funding. Uh, contracts and so on. But things have changed. As Steve pointed out, A lot of these commercial entities funded by billionaires are coming out of the woodwork funding R and D. So they're taking the lead. So what we can do within the deal, the in government is truly take advantage of the work they've done on. Uh, since they're they're, you know, paving the way to new new approaches and new way of doing things. And I think we can We could certainly learn from that. And leverage off of that saves us money from an R and D standpoint while benefiting from from the product that they deliver, you know, within the O D Talking about workforce development Way have prioritized we have policies now to attract and retain talent. We need I I had the folks do some research and and looks like from a cybersecurity workforce standpoint. A recent study done, I think, last year in 2019 found that the cybersecurity workforce gap in the U. S. Is nearing half a million people, even though it is a growing industry. So the pipeline needs to be strengthened off getting people through, you know, starting young and through college, like assess a professor Armstrong indicated, because we're gonna need them to be in place. Uh, you know, in a period of about maybe a decade or so, Uh, on top of that, of course, is the continuing issue we have with the gap with with stamps students, we can't afford not to have expertise in place to support all the things we're doing within the with the not only deal with the but the commercial side as well. Thank you. >>How's the gap? Get? Get filled. I mean, this is the this is again. You got cybersecurity. I mean, with space. It's a whole another kind of surface area, if you will, in early surface area. But it is. It is an I o t. Device if you think about it. But it does have the same challenges. That's kind of current and and progressive with cybersecurity. Where's the gap Get filled, Steve Or President Armstrong? I mean, how do you solve the problem and address this gap in the workforce? What is some solutions and what approaches do we need to put in place? >>Steve, go ahead. I'll follow up. >>Okay. Thanks. I'll let you correct. May, uh, it's a really good question, and it's the way I would. The way I would approach it is to focus on it holistically and to acknowledge it up front. And it comes with our teaching, etcetera across the board and from from an industry perspective, I mean, we see it. We've gotta have secure systems with everything we do and promoting this and getting students at early ages and mentoring them and throwing internships at them. Eyes is so paramount to the whole the whole cycle, and and that's kind of and it really takes focused attention. And we continue to use the word focus from an NSS, a perspective. We know the challenges that are out there. There are such talented people in the workforce on the government side, but not nearly enough of them. And likewise on industry side. We could use Maura's well, but when you get down to it, you know we can connect dots. You know that the the aspect That's a Professor Armstrong talked about earlier toe where you continue to work partnerships as much as you possibly can. We hope to be a part of that. That network at that ecosystem the will of taking common objectives and working together to kind of make these things happen and to bring the power not just of one or two companies, but our our entire membership to help out >>President >>Trump. Yeah, I would. I would also add it again. It's back to partnerships that I talked about earlier. One of our partners is high schools and schools fortune Margaret Fortune, who worked in a couple of, uh, administrations in California across party lines and education. Their fifth graders all visit Cal Poly and visit our learned by doing lab and you, you've got to get students interested in stem at a early age. We also need the partnerships, the scholarships, the financial aid so the students can graduate with minimal to no debt to really hit the ground running. And that's exacerbated and really stress. Now, with this covert induced recession, California supports higher education at a higher rate than most states in the nation. But that is that has dropped this year or reasons. We all understand, uh, due to Kobe, and so our partnerships, our creativity on making sure that we help those that need the most help financially uh, that's really key, because the gaps air huge eyes. My colleagues indicated, you know, half of half a million jobs and you need to look at the the students that are in the pipeline. We've got to enhance that. Uh, it's the in the placement rates are amazing. Once the students get to a place like Cal Poly or some of our other amazing CSU and UC campuses, uh, placement rates are like 94%. >>Many of our >>engineers, they have jobs lined up a year before they graduate. So it's just gonna take key partnerships working together. Uh, and that continued partnership with government, local, of course, our state of CSU on partners like we have here today, both Stephen Bang So partnerships the thing >>e could add, you know, the collaboration with universities one that we, uh, put a lot of emphasis, and it may not be well known fact, but as an example of national security agencies, uh, National Centers of Academic Excellence in Cyber, the Fast works with over 270 colleges and universities across the United States to educate its 45 future cyber first responders as an example, so that Zatz vibrant and healthy and something that we ought Teoh Teik, banjo >>off. Well, I got the brain trust here on this topic. I want to get your thoughts on this one point. I'd like to define what is a public private partnership because the theme that's coming out of the symposium is the script has been flipped. It's a modern error. Things air accelerated get you got security. So you get all these things kind of happen is a modern approach and you're seeing a digital transformation play out all over the world in business. Andi in the public sector. So >>what is what >>is a modern public private partnership? What does it look like today? Because people are learning differently, Covert has pointed out, which was that we're seeing right now. How people the progressions of knowledge and learning truth. It's all changing. How do you guys view the modern version of public private partnership and some some examples and improve points? Can you can you guys share that? We'll start with the Professor Armstrong. >>Yeah. A zai indicated earlier. We've had on guy could give other examples, but Northup Grumman, uh, they helped us with cyber lab. Many years ago. That is maintained, uh, directly the software, the connection outside its its own unit so that students can learn the hack, they can learn to penetrate defenses, and I know that that has already had some considerations of space. But that's a benefit to both parties. So a good public private partnership has benefits to both entities. Uh, in the common factor for universities with a lot of these partnerships is the is the talent, the talent that is, that is needed, what we've been working on for years of the, you know, that undergraduate or master's or PhD programs. But now it's also spilling into Skilling and re Skilling. As you know, Jobs. Uh, you know, folks were in jobs today that didn't exist two years, three years, five years ago. But it also spills into other aspects that can expand even mawr. We're very fortunate. We have land, there's opportunities. We have one tech part project. We're expanding our tech park. I think we'll see opportunities for that, and it'll it'll be adjusted thio, due to the virtual world that we're all learning more and more about it, which we were in before Cove it. But I also think that that person to person is going to be important. Um, I wanna make sure that I'm driving across the bridge. Or or that that satellites being launched by the engineer that's had at least some in person training, uh, to do that and that experience, especially as a first time freshman coming on a campus, getting that experience expanding and as adult. And we're gonna need those public private partnerships in order to continue to fund those at a level that is at the excellence we need for these stem and engineering fields. >>It's interesting People in technology can work together in these partnerships in a new way. Bank Steve Reaction Thio the modern version of what a public, successful private partnership looks like. >>If I could jump in John, I think, you know, historically, Dodi's has have had, ah, high bar thio, uh, to overcome, if you will, in terms of getting rapid pulling in your company. This is the fault, if you will and not rely heavily in are the usual suspects of vendors and like and I think the deal is done a good job over the last couple of years off trying to reduce the burden on working with us. You know, the Air Force. I think they're pioneering this idea around pitch days where companies come in, do a two hour pitch and immediately notified of a wooden award without having to wait a long time. Thio get feedback on on the quality of the product and so on. So I think we're trying to do our best. Thio strengthen that partnership with companies outside the main group of people that we typically use. >>Steve, any reaction? Comment to add? >>Yeah, I would add a couple of these air. Very excellent thoughts. Uh, it zits about taking a little gamble by coming out of your comfort zone. You know, the world that Bond and Bond lives in and I used to live in in the past has been quite structured. It's really about we know what the threat is. We need to go fix it, will design it says we go make it happen, we'll fly it. Um, life is so much more complicated than that. And so it's it's really to me. I mean, you take you take an example of the pitch days of bond talks about I think I think taking a gamble by attempting to just do a lot of pilot programs, uh, work the trust factor between government folks and the industry folks in academia. Because we are all in this together in a lot of ways, for example. I mean, we just sent the paper to the White House of their requests about, you know, what would we do from a workforce development perspective? And we hope Thio embellish on this over time once the the initiative matures. But we have a piece of it, for example, is the thing we call clear for success getting back Thio Uh, President Armstrong's comments at the collegiate level. You know, high, high, high quality folks are in high demand. So why don't we put together a program they grabbed kids in their their underclass years identifies folks that are interested in doing something like this. Get them scholarships. Um, um, I have a job waiting for them that their contract ID for before they graduate, and when they graduate, they walk with S C I clearance. We believe that could be done so, and that's an example of ways in which the public private partnerships can happen to where you now have a talented kid ready to go on Day one. We think those kind of things can happen. It just gets back down to being focused on specific initiatives, give them giving them a chance and run as many pilot programs as you can like these days. >>That's a great point, E. President. >>I just want to jump in and echo both the bank and Steve's comments. But Steve, that you know your point of, you know, our graduates. We consider them ready Day one. Well, they need to be ready Day one and ready to go secure. We totally support that and and love to follow up offline with you on that. That's that's exciting, uh, and needed very much needed mawr of it. Some of it's happening, but way certainly have been thinking a lot about that and making some plans, >>and that's a great example of good Segway. My next question. This kind of reimagining sees work flows, eyes kind of breaking down the old the old way and bringing in kind of a new way accelerated all kind of new things. There are creative ways to address this workforce issue, and this is the next topic. How can we employ new creative solutions? Because, let's face it, you know, it's not the days of get your engineering degree and and go interview for a job and then get slotted in and get the intern. You know the programs you get you particularly through the system. This is this is multiple disciplines. Cybersecurity points at that. You could be smart and math and have, ah, degree in anthropology and even the best cyber talents on the planet. So this is a new new world. What are some creative approaches that >>you know, we're >>in the workforce >>is quite good, John. One of the things I think that za challenge to us is you know, we got somehow we got me working for with the government, sexy, right? The part of the challenge we have is attracting the right right level of skill sets and personnel. But, you know, we're competing oftentimes with the commercial side, the gaming industry as examples of a big deal. And those are the same talents. We need to support a lot of programs we have in the U. D. So somehow we have to do a better job to Steve's point off, making the work within the U. D within the government something that they would be interested early on. So I tracked him early. I kind of talked about Cal Poly's, uh, challenge program that they were gonna have in June inviting high school kid. We're excited about the whole idea of space and cyber security, and so on those air something. So I think we have to do it. Continue to do what were the course the next several years. >>Awesome. Any other creative approaches that you guys see working or might be on idea, or just a kind of stoked the ideation out their internship. So obviously internships are known, but like there's gotta be new ways. >>I think you can take what Steve was talking about earlier getting students in high school, uh, and aligning them sometimes. Uh, that intern first internship, not just between the freshman sophomore year, but before they inter cal poly per se. And they're they're involved s So I think that's, uh, absolutely key. Getting them involved many other ways. Um, we have an example of of up Skilling a redeveloped work redevelopment here in the Central Coast. PG and e Diablo nuclear plant as going to decommission in around 2020 24. And so we have a ongoing partnership toe work on reposition those employees for for the future. So that's, you know, engineering and beyond. Uh, but think about that just in the manner that you were talking about. So the up skilling and re Skilling uh, on I think that's where you know, we were talking about that Purdue University. Other California universities have been dealing with online programs before cove it and now with co vid uh, so many more faculty or were pushed into that area. There's going to be much more going and talk about workforce development and up Skilling and Re Skilling The amount of training and education of our faculty across the country, uh, in in virtual, uh, and delivery has been huge. So there's always a silver linings in the cloud. >>I want to get your guys thoughts on one final question as we in the in the segment. And we've seen on the commercial side with cloud computing on these highly accelerated environments where you know, SAS business model subscription. That's on the business side. But >>one of The >>things that's clear in this trend is technology, and people work together and technology augments the people components. So I'd love to get your thoughts as we look at the world now we're living in co vid um, Cal Poly. You guys have remote learning Right now. It's a infancy. It's a whole new disruption, if you will, but also an opportunity to enable new ways to collaborate, Right? So if you look at people and technology, can you guys share your view and vision on how communities can be developed? How these digital technologies and people can work together faster to get to the truth or make a discovery higher to build the workforce? These air opportunities? How do you guys view this new digital transformation? >>Well, I think there's there's a huge opportunities and just what we're doing with this symposium. We're filming this on one day, and it's going to stream live, and then the three of us, the four of us, can participate and chat with participants while it's going on. That's amazing. And I appreciate you, John, you bringing that to this this symposium, I think there's more and more that we can do from a Cal poly perspective with our pedagogy. So you know, linked to learn by doing in person will always be important to us. But we see virtual. We see partnerships like this can expand and enhance our ability and minimize the in person time, decrease the time to degree enhanced graduation rate, eliminate opportunity gaps or students that don't have the same advantages. S so I think the technological aspect of this is tremendous. Then on the up Skilling and Re Skilling, where employees air all over, they can be reached virtually then maybe they come to a location or really advanced technology allows them to get hands on virtually, or they come to that location and get it in a hybrid format. Eso I'm I'm very excited about the future and what we can do, and it's gonna be different with every university with every partnership. It's one. Size does not fit all. >>It's so many possibilities. Bond. I could almost imagine a social network that has a verified, you know, secure clearance. I can jump in, have a little cloak of secrecy and collaborate with the d o. D. Possibly in the future. But >>these are the >>kind of kind of crazy ideas that are needed. Are your thoughts on this whole digital transformation cross policy? >>I think technology is gonna be revolutionary here, John. You know, we're focusing lately on what we call digital engineering to quicken the pace off, delivering capability to warfighter. As an example, I think a I machine language all that's gonna have a major play and how we operate in the future. We're embracing five G technologies writing ability Thio zero latency or I o t More automation off the supply chain. That sort of thing, I think, uh, the future ahead of us is is very encouraging. Thing is gonna do a lot for for national defense on certainly the security of the country. >>Steve, your final thoughts. Space systems are systems, and they're connected to other systems that are connected to people. Your thoughts on this digital transformation opportunity >>Such a great question in such a fun, great challenge ahead of us. Um echoing are my colleague's sentiments. I would add to it. You know, a lot of this has I think we should do some focusing on campaigning so that people can feel comfortable to include the Congress to do things a little bit differently. Um, you know, we're not attuned to doing things fast. Uh, but the dramatic You know, the way technology is just going like crazy right now. I think it ties back Thio hoping Thio, convince some of our senior leaders on what I call both sides of the Potomac River that it's worth taking these gamble. We do need to take some of these things very way. And I'm very confident, confident and excited and comfortable. They're just gonna be a great time ahead and all for the better. >>You know, e talk about D. C. Because I'm not a lawyer, and I'm not a political person, but I always say less lawyers, more techies in Congress and Senate. So I was getting job when I say that. Sorry. Presidential. Go ahead. >>Yeah, I know. Just one other point. Uh, and and Steve's alluded to this in bonded as well. I mean, we've got to be less risk averse in these partnerships. That doesn't mean reckless, but we have to be less risk averse. And I would also I have a zoo. You talk about technology. I have to reflect on something that happened in, uh, you both talked a bit about Bill Britton and his impact on Cal Poly and what we're doing. But we were faced a few years ago of replacing a traditional data a data warehouse, data storage data center, and we partner with a W S. And thank goodness we had that in progress on it enhanced our bandwidth on our campus before Cove. It hit on with this partnership with the digital transformation hub. So there is a great example where, uh, we we had that going. That's not something we could have started. Oh, covitz hit. Let's flip that switch. And so we have to be proactive on. We also have thio not be risk averse and do some things differently. Eyes that that is really salvage the experience for for students. Right now, as things are flowing, well, we only have about 12% of our courses in person. Uh, those essential courses, uh, and just grateful for those partnerships that have talked about today. >>Yeah, and it's a shining example of how being agile, continuous operations, these air themes that expand into space and the next workforce needs to be built. Gentlemen, thank you. very much for sharing your insights. I know. Bang, You're gonna go into the defense side of space and your other sessions. Thank you, gentlemen, for your time for great session. Appreciate it. >>Thank you. Thank you. >>Thank you. >>Thank you. Thank you. Thank you all. >>I'm John Furry with the Cube here in Palo Alto, California Covering and hosting with Cal Poly The Space and Cybersecurity Symposium 2020. Thanks for watching.
SUMMARY :
It's the Cube space and cybersecurity. We have Jeff Armstrong's the president of California Polytechnic in space, Jeff will start with you. We know that the best work is done by balanced teams that include multiple and diverse perspectives. speaking to bang, we learned that Rachel sins, one of our liberal arts arts majors, on the forefront of innovation and really taking a unique progressive. of the National Security Space Association, to discuss a very important topic of Thank you so much bomb for those comments and you know, new challenges and new opportunities and new possibilities of the space community, we thank you for your long life long devotion to service to the drone coming over in the crime scene and, you know, mapping it out for you. Yeah, I really appreciate that And appreciate the comments of my colleagues on clock now on terms of the innovation cycles, and so you got to react differently. Because the workforce that air in schools and our folks re So the pipeline needs to be strengthened But it does have the same challenges. Steve, go ahead. the aspect That's a Professor Armstrong talked about earlier toe where you continue to work Once the students get to a place like Cal Poly or some of our other amazing Uh, and that continued partnership is the script has been flipped. How people the progressions of knowledge and learning truth. that is needed, what we've been working on for years of the, you know, Thio the modern version of what a public, successful private partnership looks like. This is the fault, if you will and not rely heavily in are the usual suspects for example, is the thing we call clear for success getting back Thio Uh, that and and love to follow up offline with you on that. You know the programs you get you particularly through We need to support a lot of programs we have in the U. D. So somehow we have to do a better idea, or just a kind of stoked the ideation out their internship. in the manner that you were talking about. And we've seen on the commercial side with cloud computing on these highly accelerated environments where you know, So I'd love to get your thoughts as we look at the world now we're living in co vid um, decrease the time to degree enhanced graduation rate, eliminate opportunity you know, secure clearance. kind of kind of crazy ideas that are needed. certainly the security of the country. and they're connected to other systems that are connected to people. that people can feel comfortable to include the Congress to do things a little bit differently. So I Eyes that that is really salvage the experience for Bang, You're gonna go into the defense side of Thank you. Thank you all. I'm John Furry with the Cube here in Palo Alto, California Covering and hosting with Cal
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Chuck | PERSON | 0.99+ |
Steve | PERSON | 0.99+ |
Steve Jakes | PERSON | 0.99+ |
John | PERSON | 0.99+ |
Joe | PERSON | 0.99+ |
Steve Jake | PERSON | 0.99+ |
Rachel | PERSON | 0.99+ |
Cal Poly | ORGANIZATION | 0.99+ |
National Security Space Association | ORGANIZATION | 0.99+ |
Jeff Armstrong | PERSON | 0.99+ |
Northrop Grumman | ORGANIZATION | 0.99+ |
PG | ORGANIZATION | 0.99+ |
Chris Hansen | PERSON | 0.99+ |
California | LOCATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Jeff | PERSON | 0.99+ |
Jane | PERSON | 0.99+ |
National Security Space Association | ORGANIZATION | 0.99+ |
Jeff Bezos | PERSON | 0.99+ |
Chuck Beans | PERSON | 0.99+ |
California National Guard | ORGANIZATION | 0.99+ |
New York City | LOCATION | 0.99+ |
Boeing | ORGANIZATION | 0.99+ |
National Security Space Association | ORGANIZATION | 0.99+ |
Cal Poly | ORGANIZATION | 0.99+ |
Bond | PERSON | 0.99+ |
United States Space Force | ORGANIZATION | 0.99+ |
2013 | DATE | 0.99+ |
Singapore | LOCATION | 0.99+ |
94% | QUANTITY | 0.99+ |
Trump | PERSON | 0.99+ |
Richard Branson | PERSON | 0.99+ |
California Cybersecurity Institute | ORGANIZATION | 0.99+ |
United States Space Command | ORGANIZATION | 0.99+ |
June | DATE | 0.99+ |
Thio | PERSON | 0.99+ |
one | QUANTITY | 0.99+ |
Congress | ORGANIZATION | 0.99+ |
Armstrong | PERSON | 0.99+ |
hundreds | QUANTITY | 0.99+ |
United States | LOCATION | 0.99+ |
N S. A | ORGANIZATION | 0.99+ |
four | QUANTITY | 0.99+ |
Cal poly | ORGANIZATION | 0.99+ |
three | QUANTITY | 0.99+ |
Elon Musk | PERSON | 0.99+ |
York Space Systems | ORGANIZATION | 0.99+ |
National Centers of Academic Excellence in Cyber | ORGANIZATION | 0.99+ |
Bezos | PERSON | 0.99+ |
Purdue University | ORGANIZATION | 0.99+ |
One | QUANTITY | 0.99+ |
Shez Partovi MD, AWS | AWS Summit New York 2019
>> live from New York. It's the Q covering AWS Global Summit 2019 brought to you by Amazon Web service, is >> welcome back here to New York City. You're watching the Cube, the worldwide leader in Enterprise Tech cover jumps to minimum. My co host for today is Cory Quinn and happy to welcome to the program. A first time guest on the program, says Heart O. B. Who is a senior leader of global business development with Healthcare Life. Scientists know this group and AWS thanks so much for joining us. All right, so you know, we love digging into some of the verticals here in New York City. Of course, it's been a lot of time on the financial service is peas we actually had, Ah, another one of our teams out of the eight of us. Imagine show going on yesterday in Seattle with a lot of the education pieces. So healthcare, life sciences in genomics, little bit of tech involved in those groups, a lot of change going on in that world. So give us a thumbnail if you would as toe what what's happening in your >> world so well just from a scope one of you Health care includes life set paid on provider Life sciences is far more by attacking its most medical device and then genomics and what we're seeing in those spaces. Let's start with health care. It's such a broad thing, will just sort of back to back and forth in health care itself. What we're sort of seeing their customs ask us to focus on and to help them do falls into three categories. First, is a lot of customers ask us to help them personalized the consumer health journey. You and I, all of us, are so accustomed to that frictionless experiences we have elsewhere and in health care. There's a lot more friction. And so we're getting a lot of enquiries and request for us to help them transform that experience. Make it frictionless. So an example That would be if you're familiar with Doc. Doc started here in New York. Actually, when you want a book, an appointment, Doc, Doc, you can normally, if you go online, I have to put information for insurance. You type it all. Then it's full of friction. Have to put all the fields in. They use one of our A I service's image recognition, and you simply hold up your card to the camera and it able to pull your in transporation, determine eligibility and look the right appointment for you. So that's an example of removing friction for the consumer of the health consume over the patient as they're trying to go to that health care and excessive category one frictionless experiences using AWS to support it with a i service is category, too. We're getting a lot of interest for us to help health systems predict patient health events. So anything of value base care the way you actually are able to change the cost. Quality Curve is predicting events, not just dealing with math and so using a i Am L service is on top of data to predict and forecast events is a big part of one example would be with sooner where they moved, they're healthy and 10 platform, which is a launch to a patient record platform onto AWS. About 223,000,000 individuals that are on that platform Men we did a study with him where way consume about 210,000 individual patient data and created a machine learning model this is published where you can predict congestive heart failure 15 months in advance of it actually occurring. So when you look at that, that prediction are forecasting that sort of one of the powers of this princess. What category number two is predicting health events, and then the last one I'd be remiss in leaving out is that you probably have heard a lot of discussion on physician and a clinician. Burnout to the frustrations of the nurses or doctors and Muslims have the heart of that is not having the right information the right time to take care of the right patient. Data liquidity and in Trop ability is a huge challenge, and a lot of our customers are asking us to help solve those problems with them. You know it hims. This year we announced, together with change Healthcare Change Healthcare said they want to provide free and troubling to the country on AWS, with the platform supporting that. So those are sort of three categories. Personalize the consumer health journey. Predicting patient health events and promoting intra ability is sort of the signals that we're seeing in areas that were actively supporting our customers and sort of elevating the human condition. >> It's very easy to look at the regulation around things like health care and say, Oh, that gets in the way and its onerous and we're not gonna deal with it or it should be faster. I don't think anyone actively wants that. We like the fact that our hospitals were safe, that health care is regulated and in some of the ways that it is at least. But I saw an artifact of that means that more than many other areas of what AWS does is your subject to regulatory speed of Sloane. A speed of feature announcement, as opposed to being able to do it as fast technology allows relatively easy example of this was a few years back. In order to run, get eight of us to sign a B A. For hip, a certification, you have to run dedicated tendency instances and will not changed about a year and 1/2 2 years ago or even longer. Depending it's it all starts to run together after a time, but once people learn something, they don't tend to go back and validate whether it's still true. How do you just find that communicating to your customers about things that were not possible yesterday now are, >> yeah, when you look at hip eligibility. So as you know, a devious is about over 100 him eligible service's, which means that these are so this is that so compliance that you start their compliance, Remember, is an outcome, not a future. So compliance is a combination of people process platform, and we bring the platform that's hip eligible, and our customers bring the people in process, if you will, to use that platform, which then becomes complying with regulatory requirements. And so you're absolutely right. There's a diffusion of sort of understanding of eligibility, a platform, and then they worked with customers have to do in order as a shared responsibility to do it. That diffusion is sometimes slower. In fact, there's sometimes misinformation. So we always see it work with our customers and that shared, responsive model so that they can meet their requirements as they come to the cloud. And we can bring platforms that are eligible for hip. They can actually carry out the work clothes they need to. So it's it's that money, you know, the way I think of it is. This when you think of compliance, is that if if I were to build for you a deadbolt for your door and I can tell you that this complies boasted of things, but you put the key under the mat way might not be complying with security and regular requirements for our house. So it's a share responsible. I'll make the platform be eligible and compliant, and so that collective does daytime and dusting. People are saying that there is a flat from this eligible, and then they have to also, in their response to work to the people in process potion to make the totality of it comply with the requirements for regulatory for healthcare regulatory requirements. >> Some of the interesting conversations I've had in the last few years in health care in the industry is collaborations that are going on, you know, how do we share data while still maintaining all of the regulations that are involved? Where does that leave us get involved? There >> should. That's a fact. There is a data sharing part of that did a liquidity story that we talked about earlier in terms of instability. I'll give an example of where AWS actually actively working in that space. You may be familiar with a service we launched last November at Reinvent called Amazon Campion Medical and Campion Medical. What it does is it looks at a medical note and can extract key information. So if you think back to in high school, when you used to read a book in highlighting yellow key concepts that you wanted to remember for an exam Amazon Carmen Medical Same thing exactly, can lift key elements and goes from a text blob, too discrete data that has relationship ontology and that allows data sharing where you where you need to. But then there's one of the piece, so that's when you're allowed to disclose there's one of me. Sometimes you and I want to work on something, but we want to actually read act the patient information that allows data sharing as well. So Amazon coming medical also allows you to read, act. Think of when a new challenge shows that federally protected doctor that's blacked out Amazon com for American also remove patient identifying information. So if you and I want to collaborate on research project, you have a set of data that you wanna anonima de identify. I have data information of I D identified. To put it together, I can use Amazon com Medical Read Act All the patient information Make it d identified. You can do the same. And now we can combine the three of us that information to build models, to look a research and to do data sharing. So whether you have full authority to to share patient information and use the ontological portion of it, or whether you want to do the identifying matter, Amazon competent medical helps you do that. >> What's impressive and incredible is that whether we like it or not, there's something a little special about health care where I can decide I'm not going to be on the Internet. Social media things all stop tweeting. Most people would thank me for that, or I can opt out of ride sharing and only take taxis, for example. But we're all sooner or later going to be customers of the health care industry, and as a result, this is some of that effects, all of us, whether we want to acknowledge that or not. I mean, where some of us are still young enough to believe that we have this immortality streak going on. So far, so good. But it becomes clear that this is the sort of thing where the ultimate customer is all of us. As you take a look at that, does that inform how AWS is approaching this entire sector? >> Absolutely. In fact, I'd like to think that a W brought a physician toe lead sector because they understood that in addition to our customer obsession that we see through the customer to the individual and that we want to elevate the human condition we wanted obsess over our customers success so that we can affect positive action on the lives of individuals everywhere. To me, that is a turn. The reason I joined it of U. S s. So that's it. Certainly practice of healthcare Life's I said on genomic Seti ws has been around for about six years. A doubIe s double that. And so actually it's a mature practice and our understanding of our customers definitely includes that core flame that it's about people and each of us come with a special story. In fact, you know the people that work in the U. S. Healthcare life, science team people that have been to the bedside there, people that have been adventure that I worked in the farm industry, healthcare, population, health. They all are there because of that thing you just said. Certainly I'm there because that on the entire practice of self life sciences is keenly aware of looking through the customers to the >> individual pieces. All right, how much? You know, mix, you know, definitely an area where compute storage are critically important than we've seen. Dramatic change. You know, in the last 5 to 10 years, anything specific you could share on that >> Genomics genomex is an area where you need incredible computer storage on. In our case, for example, alumina, which is one of our customers, runs about 85% of all gene sequencing on the planet is in aws customer stores. All that data on AWS. So when you look at genomex, real power of genomics is the fact that enables precision diagnostics. And so when you look at one of our customers, Grail Grail, that uses genomic fragments in the blood that may be coming from cancer and actually sequences that fragment and then on AWS will use the power of the computer to do machine learning on that Gino Mexicans from to determine if you might have one of those 1 10 to 12 cancers that they're currently screening for. And so when you talk to a position health, it really can't be done without position diagnostics, which depends on genomex, which really is an example of that. It runs on AWS because we bring compute and storage essentially infinite power. To do that you want, For example, you know the first whole genome sequence took 14 years. And how many billions of dollars Children's Hospital Philadelphia now does 1000 whole genome sequences in two hours and 20 minutes on AWS, they spike up 20,000 see few cores, do that desi and then moved back down. Genomics. The field that literally can't be. My humble opinion can't be done outside the cloud. It just the mechanics of needed. The storage and compute power is one that is born in the cloud on AWS has those examples that I shared with you. >> It's absolutely fantastic and emerging space, and it's it's interesting to watch that despite the fact there is a regulatory burden that everything was gonna dispute that and the gravity of what it does. I'm not left with sense that feature enhancement and development and velocity of releases is slower somehow in health care than it is across the entire rest of the stack. Is that an accurate assessment, or is there a bit of a drag effect on that? >> Do you mean in the health care customers are on AWS speaking >> on AWS aside, citizen customers are going to be customers. Love them. We >> do aws. You know, we obviously innovation is a rowdy and we release gosh everything. About 2011 we released 80 front service than features and jumped 1015 where it was like 702 jumped 2018. Where was 1957 features? That's like a 25 fold. Our pace of innovation is not going to slow down. It's going to continue. It's in our blood in our d. N. A. We in fact, hire people that are just not satisfied. The status quo on want to innovate and change things. Just, you know, innovation is the beginning of the end of the story, so, no, I don't have to spend any slowdown. In fact, when you add machine learning models on machine learning service that we're putting in? I only see it. An even faster hockey stick of the service is that we're gonna bring out. And I want you to come to reinvent where we're going to announce the mall and you you will be there and see that. All >> right, well, on that note thank you so much for giving us the update on healthcare Life Sciences in genomics. Absolutely. Want to see the continued growth and innovation in that? >> My pleasure. Thank you for having a show. All >> right. For Cory, Queen of Stupid Men. The Cube's coverage never stops either. We, of course, will be at eight of us reinvent this fall as well as many other shows. So, as always, thanks for watching the cue.
SUMMARY :
Global Summit 2019 brought to you by Amazon Web service, All right, so you know, we love digging into some of the verticals here of that is not having the right information the right time to take care of the right patient. Oh, that gets in the way and its onerous and we're not gonna deal with it or it should be faster. So it's it's that money, you know, the way I think of it is. ontology and that allows data sharing where you where you need to. of the health care industry, and as a result, this is some of that effects, S. Healthcare life, science team people that have been to the bedside there, You know, mix, you know, definitely an area where compute To do that you want, For example, that despite the fact there is a regulatory burden that everything was gonna dispute that and the on AWS aside, citizen customers are going to be customers. And I want you to come to reinvent where we're going to announce the mall and you you will be there and see that. right, well, on that note thank you so much for giving us the update on healthcare Life Sciences in genomics. Thank you for having a show. of course, will be at eight of us reinvent this fall as well as many other shows.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
New York | LOCATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Seattle | LOCATION | 0.99+ |
New York City | LOCATION | 0.99+ |
Cory Quinn | PERSON | 0.99+ |
1000 whole genome sequences | QUANTITY | 0.99+ |
three | QUANTITY | 0.99+ |
14 years | QUANTITY | 0.99+ |
two hours | QUANTITY | 0.99+ |
yesterday | DATE | 0.99+ |
First | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
Amazon com | ORGANIZATION | 0.99+ |
eight | QUANTITY | 0.99+ |
last November | DATE | 0.99+ |
15 months | QUANTITY | 0.99+ |
first time | QUANTITY | 0.99+ |
25 fold | QUANTITY | 0.98+ |
today | DATE | 0.98+ |
Shez Partovi | PERSON | 0.98+ |
12 cancers | QUANTITY | 0.98+ |
20,000 | QUANTITY | 0.98+ |
2018 | DATE | 0.97+ |
each | QUANTITY | 0.97+ |
10 | QUANTITY | 0.97+ |
about six years | QUANTITY | 0.97+ |
About 223,000,000 individuals | QUANTITY | 0.97+ |
Healthcare Life | ORGANIZATION | 0.97+ |
This year | DATE | 0.97+ |
Queen of Stupid Men | TITLE | 0.97+ |
Medical | ORGANIZATION | 0.96+ |
billions of dollars | QUANTITY | 0.96+ |
first whole genome sequence | QUANTITY | 0.96+ |
aws | ORGANIZATION | 0.96+ |
Campion Medical | ORGANIZATION | 0.95+ |
Reinvent | ORGANIZATION | 0.95+ |
about 85% | QUANTITY | 0.95+ |
Doc | PERSON | 0.94+ |
AWS Global Summit 2019 | EVENT | 0.93+ |
Amazon Web | ORGANIZATION | 0.92+ |
Children's Hospital Philadelphia | ORGANIZATION | 0.91+ |
Heart O. B. Who | PERSON | 0.89+ |
AWS Summit | EVENT | 0.87+ |
one of | QUANTITY | 0.86+ |
U. S | LOCATION | 0.86+ |
702 | QUANTITY | 0.86+ |
2011 | DATE | 0.86+ |
Cube | PERSON | 0.86+ |
double | QUANTITY | 0.85+ |
80 front service | QUANTITY | 0.84+ |
U. S. | LOCATION | 0.83+ |
about 210,000 individual patient data | QUANTITY | 0.82+ |
few years back | DATE | 0.82+ |
1 10 | QUANTITY | 0.81+ |
this fall | DATE | 0.81+ |
2019 | EVENT | 0.8+ |
1015 | QUANTITY | 0.8+ |
1/2 2 years ago | DATE | 0.79+ |
about over 100 | QUANTITY | 0.78+ |
10 years | QUANTITY | 0.77+ |
one of our | QUANTITY | 0.76+ |
i Am | TITLE | 0.76+ |
Amazon Carmen Medical | ORGANIZATION | 0.75+ |
three categories | QUANTITY | 0.75+ |
20 minutes | QUANTITY | 0.74+ |
com Medical Read Act | TITLE | 0.72+ |
American | LOCATION | 0.72+ |
few cores | QUANTITY | 0.71+ |
years | DATE | 0.7+ |
one example | QUANTITY | 0.68+ |
Billie Whitehouse, Wearable X | theCUBE NYC 2018
>> Live from New York, it's theCUBE. Covering theCUBE New York City 2018. Brought to you by Silicon Angle Media and its ecosystem partners. >> Hi, welcome back. I'm your host Sonia Tagare with my cohost Dave Vellante, and we're here at theCUBE NYC covering everything big data, AI, and the cloud. And this week is also New York Fashion Week, and with us today we have a guest who intersects both of those technologies, so Billie Whitehouse, CEO of Wearable X, thank you so much for being on. >> It's a pleasure, thank you for having me. >> Great to see you. >> Thank you. >> So your company Wearable X, which intersects fashion and technology, tell us more about that. >> So Wearable X started five years ago. And we started by building clothes that had integrated haptic feedback, which is just vibrational feedback on the body. And we really believe that we can empower clothing with technology to do far more than it ever has for you before, and to really give you control back of your life. >> That's amazing. So can you tell us more about the haptic, how it works and what the technology is about? >> Absolutely. So the haptics are integrated with accelerometers and they're paired through conductive pathways around the body, and specifically this is built for yoga in a line called NadiX. And Nadi is spelled N-A-D-I. I know that I have a funny accent so sometimes it helps to spell things out. They connect and understand your body orientation and then from understanding your body orientation we pair that back with your smartphone and then the app guides you with audio, how to move into each yoga pose, step by step. And at the end we ask you to address whether you made it into the pose or not by reading the accelerometer values, and then we give you vibrational feedback where to focus. >> And the accelerometer is what exactly? It's just a tiny device... Does it protrude or is it just...? >> I mean it's as invisibly integrated as we can get it so that we can make it washable and tumble-dryable. >> So I know I rented a car recently, big SUV with the family and when I started backing up or when I get close to another car, it started vibrating. So is it that kind of sensation? It was sort of a weird warning but then after a while I got used to it. It was kind of training me. Is that-- >> Precisely. >> Sort of the same thing? And it's just the pants or the leggings, or is it the top as well? >> So it's built in through the ankles, behind the knees and in the hip of the yoga pants, and then we will release upper body work as well. >> Alright, so let's double click on this. So if I'm in a crescent pose and I'm leaning too far forward, will it sort of correct me or hit me in the calf and say, "Put your heel down," or how would that work? >> Exactly. So the audio instructions will give you exactly the kind of instructions you would get if you were in a class. And then similarly to what you would get if you had a personal instructor, the vibrations will show you where to isolate and where to ground down, or where to lift up, or where to rotate, and then at the end of the pose, the accelerometer values are read and we understand whether you made it into the pose or whether you didn't quite get there, and whether you're overextended or not. And then we ask you to either go back and work on the pose again or move forward and move on to the next pose. >> That is amazing. I usually have to ask my daughters or my wife, "Is this right?" And then they'll just shake their heads. Now what do you do with the data? Do you collect the data and can I review and improve, feed it back? How does that all work? >> So the base level membership, which is free, is you don't see your progress tracking as yet. But we're about to release our membership, where you pay $10 a month, and with that you get progress tracking as a customer. Us on the back end, we can see how often people make it into particular poses. We can also see which ones they don't make it into very well, but we don't necessarily share that. >> And so presumably it tracks other things besides, like frequency, duration of the yoga? >> Exactly. Minutes of yoga, precisely right. >> Different body parts, or not necessarily? >> So the accelerometers are just giving us an individual value, and then we determine what pose you're in, so I don't know what you mean by different body parts? >> In other words, which parts of my body I'm working out or maybe need to work on? >> Oh precisely. Yeah if you're overextending a particular knee or an ankle, we can eventually tell you that very detailed. >> And how long have you been doing this? >> It's five years. >> Okay. And so what have you learned so far from all this data that you've collected? >> Well I mean, I'm going to start from a human learning first, and then I'll give you the data learnings. The human learning for me is equally as interesting. The language on the body and how people respond to vibration was learning number one. And we even did tests many years ago with a particular product, an upper body product, with kids, so aged between eight and 13, and I played a game of memory with them to see if they could learn and understand different vibrational sequences and what they meant. And it was astounding. They would get it every single time without fail. They would understand what the vibrations meant and they would remember it. For us, we are then trying to replicate that for yoga. And that has been a really interesting learning, to see how people need and understand and want to have audio cues with their vibrational feedback. From a data perspective, the biggest learning for us is that people are actually spending between 13 to 18 minutes inside the app. So they don't necessarily want an hour and a half class, which is what we originally thought. They want short, quick, easy-to-digest kind of flows. And that for me was very much a learning. They're also using it at really interesting times of the day. So it's before seven AM, in the middle of the day between 11 and three, and then after nine PM. And that just so happens to be when studios are shut. So it makes sense that they want to use something that's quick and easy for them, whether it's early morning when they have a big, full day, or late night 'cause they need to relax. >> Sounds like such a great social impact. Can you tell us more about why you decided to make this? >> Yeah, for me there was a personal problem. I was paying an extraordinary amount to go to classes, I was often in a class with another 50 people and not really getting any of the attention that I guess I thought I deserved, so I was frustrated. I was frustrated that I was paying so much money to go into class and not getting the attention, had been working with haptic feedback for quite some time at that point, realized that there was this language on the body that was being really underutilized, and then had this opportunity to start looking at how we could do it for yoga. Don't get me wrong, I had several engineers tell me this wasn't possible about three and a half years ago, and look at us now, we're shipping product and we're in retail and it's all working, but it took some time. >> So you're not an engineer, I take it? >> I am not an engineer. >> You certainly don't dress like an engineer, but you never know. What's your background? >> My background is in design. And I truly think that design, for us, has always come first. And I hope that it continues to be that way. I believe that designers have an ability to solve problems in, dare I say, in a horizontal way. We can understand pockets of things that are going on, whether it's the problem, whether it's ways to solve the solutions, and we can combine the two. It's not just about individual problem solving on a minute level; it's very much a macro view. And I hope that more and more designers go into this space because I truly believe that they have an ability to solve really interesting problems by asking empathetic questions. >> And how does the tech work? I mean, what do you need besides the clothing and the accelerometers to make this work? >> So we have a little device called the pulse. And the pulse has our Bluetooth module and our battery and our PCB, and that clips just behind the left knee. Now that's also the one spot on the body that during yoga doesn't get in the way, and we have tested that on every body shape you can imagine across five different continents, because we wanted to make sure that the algorithms that we built to understand the poses were going to be fair for everybody. So in doing that, that little pulse, you un-clip when you want to wash and dry. >> And is that connected to the app as well? >> Exactly, that's connected via Bluetooth to your app. >> That's great. So you have all your data in your hand and you know exactly what kind of yoga poses you're doing, where you need to strengthen up. >> Exactly. >> That's great. >> And is it a full program? In other words, are there different yoga programs I can do, or am I on my own for that? How does that work? >> So with the base level membership, you can choose different yoga instructors around New York that you'd like to follow, and then you can get progress tracking, you can get recommendations, and they are timed between that 10 to 20 minutes. If you want to pay the slightly more premium membership, you can actually build your own playlists, and that's something that our customers have said they're really interested in. It means that you can build a sequence of poses that is really defined by you, that is good for your body. So that means instead of going to a class where you end up getting a terrible teacher, or music that you don't like, you can actually build your own class and then share that with your friends as well. >> Is it a Spotify-like model, where the teachers get compensation at the back end, or how does that all work? >> Exactly. Yes, precisely. >> And what do you charge for this? >> So the pants are $250, and then the base level membership is $10 a month, and then the slightly more premium is $30 a month. >> If you think about how much you would spend for a yoga class, that actually seems like a pretty good deal. >> And trust me, when you start calculating, when you go to yoga at least once a week, and it's $20 a week and then you're like, "Oh, and I went every week this year," you realize that it racks up very quickly. >> Well plus the convenience of doing it... I love having... To be able to do it at six a.m. without having to go to a class, especially where I live in Boston, when it's cold in the winter, you don't even want to go out. (all laughing) >> So what do you think the future of the wearable industry is? >> This is a space that I get really excited about. I believe in a version of the future, which has been titled "enchanted objects." And the reason I sort of put it in inverted commas is I think that often has sometimes a magical element to it that people think is a little too far forward. But for me, I really believe that this is possible. So not only do I believe that we will have our own body area network, which I like to call an app store for the body, but I believe every object will have this. And there was a beautiful Wired article last month that actually described why the Japanese culture are adopting robotics and automation in a way that western culture often isn't. And that is because the Shinto religion is the predominant religion in Japan, and they believe that every object has a soul. And if in believing that, you're designing for that object to have a soul and a personality and an ecosystem, and dare we call it, a body area network for each object, then that area network can interface with yours or mine or whoever's, and you can create this really interesting communication that is enchanted and delightful, and not about domination. It's not about screens taking over the world and being in charge of you, and us being dominated by them, as often we see in culture now. It's about having this really beautiful interface between technology and objects. And I really believe that's going to be the version of the future. >> And looking good while you do it. >> Precisely. >> You've got visions to take this beyond yoga, is that right? Other sports, perhaps cycling and swimming and skiing, I can think of so many examples. >> Exactly. Well for us, we're focused on yoga to start with. And certainly areas that I would say are in the gaps. I like to think of our products as being very touch-focused and staying in areas of athleisure or sports that are around touch. So where you would get a natural adjustment from a coach or a teacher, our products can naturally fit into that space. So whether it is squats or whether it is Pilates, they're certainly in our pipeline. But in the immediate future, we're certainly looking at the upper body and in meditation, and how we can remind you to roll your shoulders back and down, and everyone sits up straight. And then longer term, we're looking at how we can move this into physiotherapy, and so as you mentioned, you can enter in that you have a left knee injury, and we'll be able to adjust what you should be working on because of that. >> Is there a possibility of a breathing component, or is that perhaps there today? Such an important part of yoga is breathing. >> 100%. That is very much part of what we're working on. I would say more silently, but very much will launch soon. >> Well it sounds like it's going to have such a positive impact on so many people and that it's going to be in so many different industries. >> I hope so. Yeah that's the plan. >> Well Billie Whitehouse, thank you so much for being on theCUBE, and Dave, thank you. We're here at theCUBE NYC, and stay tuned, don't go anywhere, we'll be back. (inquisitive electronic music)
SUMMARY :
Brought to you by Silicon Angle Media thank you so much for being on. thank you for having me. and technology, tell us more about that. for you before, and to really give you So can you tell us more about the haptic, And at the end we ask you to address And the accelerometer is what exactly? so that we can make it So is it that kind of sensation? and then we will release me or hit me in the calf And then similarly to what you would get Now what do you do with the data? is you don't see your Minutes of yoga, precisely right. you that very detailed. And so what have you learned and then I'll give you the data learnings. why you decided to make this? and then had this opportunity to start engineer, but you never know. And I hope that it and our PCB, and that clips via Bluetooth to your app. and you know exactly what kind and then you can get progress tracking, Exactly. So the pants are $250, and how much you would spend when you go to yoga at least once a week, in the winter, you don't And that is because the Shinto religion while you do it. is that right? how we can remind you or is that perhaps there today? of what we're working on. that it's going to be Yeah that's the plan. thank you so much
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Vellante | PERSON | 0.99+ |
Sonia Tagare | PERSON | 0.99+ |
Boston | LOCATION | 0.99+ |
Billie Whitehouse | PERSON | 0.99+ |
New York | LOCATION | 0.99+ |
$250 | QUANTITY | 0.99+ |
Dave | PERSON | 0.99+ |
Silicon Angle Media | ORGANIZATION | 0.99+ |
Wearable X | ORGANIZATION | 0.99+ |
10 | QUANTITY | 0.99+ |
Japan | LOCATION | 0.99+ |
five years | QUANTITY | 0.99+ |
Wearable X | ORGANIZATION | 0.99+ |
two | QUANTITY | 0.99+ |
last month | DATE | 0.99+ |
13 | QUANTITY | 0.99+ |
six a.m. | DATE | 0.99+ |
today | DATE | 0.98+ |
each object | QUANTITY | 0.98+ |
five years ago | DATE | 0.98+ |
20 minutes | QUANTITY | 0.98+ |
this year | DATE | 0.98+ |
50 people | QUANTITY | 0.98+ |
18 minutes | QUANTITY | 0.97+ |
an hour and a half class | QUANTITY | 0.97+ |
both | QUANTITY | 0.97+ |
first | QUANTITY | 0.97+ |
New York Fashion Week | EVENT | 0.97+ |
$30 a month | QUANTITY | 0.96+ |
five different continents | QUANTITY | 0.96+ |
$10 a month | QUANTITY | 0.96+ |
$20 a week | QUANTITY | 0.96+ |
NYC | LOCATION | 0.95+ |
theCUBE | ORGANIZATION | 0.94+ |
one spot | QUANTITY | 0.93+ |
Spotify | ORGANIZATION | 0.93+ |
New York City | LOCATION | 0.93+ |
this week | DATE | 0.92+ |
11 | DATE | 0.92+ |
Japanese | OTHER | 0.91+ |
about three and a half years ago | DATE | 0.89+ |
double | QUANTITY | 0.88+ |
eight | QUANTITY | 0.87+ |
many years ago | DATE | 0.86+ |
after | DATE | 0.84+ |
each yoga | QUANTITY | 0.84+ |
much | QUANTITY | 0.81+ |
objects | TITLE | 0.8+ |
2018 | DATE | 0.78+ |
yoga | TITLE | 0.78+ |
100% | QUANTITY | 0.76+ |
every week | QUANTITY | 0.75+ |
single time | QUANTITY | 0.75+ |
before seven AM | DATE | 0.75+ |
every object | QUANTITY | 0.73+ |
three | DATE | 0.71+ |
Wired | TITLE | 0.71+ |
N-A-D-I | OTHER | 0.7+ |
nine PM | DATE | 0.7+ |
at least once a week | QUANTITY | 0.7+ |
CEO | PERSON | 0.65+ |
number one | QUANTITY | 0.64+ |
Shinto | ORGANIZATION | 0.61+ |
2018 | EVENT | 0.61+ |
Pilates | TITLE | 0.6+ |
Nadi | COMMERCIAL_ITEM | 0.6+ |
NadiX | COMMERCIAL_ITEM | 0.47+ |
Brent Compton, Red Hat | theCUBE NYC 2018
>> Live from New York, it's theCUBE, covering theCUBE New York City 2018. Brought to you by SiliconANGLE Media and its ecosystem partners. >> Hello, everyone, welcome back. This is theCUBE live in New York City for theCUBE NYC, #CUBENYC. This is our ninth year covering the big data ecosystem, which has now merged into cloud. All things coming together. It's really about AI, it's about developers, it's about operations, it's about data scientists. I'm John Furrier, my co-host Dave Vellante. Our next guest is Brent Compton, Technical Marketing Director for Storage Business at Red Hat. As you know, we cover Red Hat Summit and great to have the conversation. Open source, DevOps is the theme here. Brent, thanks for joining us, thanks for coming on. >> My pleasure, thank you. >> We've been talking about the role of AI and AI needs data and data needs storage, which is what you do, but if you look at what's going on in the marketplace, kind of an architectural shift. It's harder to find a cloud architect than it is to find diamonds these days. You can't find a good cloud architect. Cloud is driving a lot of the action. Data is a big part of that. What's Red Hat doing in this area and what's emerging for you guys in this data landscape? >> Really, the days of specialists are over. You mentioned it's more difficult to find a cloud architect than find diamonds. What we see is the infrastructure, it's become less about compute as storage and networking. It's the architect that can bring the confluence of those specialties together. One of the things that we see is people bringing their analytics workloads onto the common platforms where they've been running the rest of their enterprise applications. For instance, if they're running a lot of their enterprise applications on AWS, of course, they want to run their analytics workloads in AWS and that's EMRs long since in the history books. Likewise, if they're running a lot of their enterprise applications on OpenStack, it's natural that they want to run a lot of their analytics workloads on the same type of dynamically provisioned infrastructure. Emerging, of course, we just announced on Monday this week with Hortonworks and IBM, if they're running a lot of their enterprise applications on a Kubernetes substrate like OpenShift, they want to run their analytics workloads on that same kind of agile infrastructure. >> Talk about the private cloud impact and hybrid cloud because obviously we just talked to the CEO of Hortonworks. Normally it's about early days, about Hadoop, data legs and then data planes. They had a good vision. They're years into it, but I like what Hortonworks is doing. But he said Kubernetes, on a data show Kubernetes. Kubernetes is a multi-cloud, hybrid cloud concept, containers. This is really enabling a lot of value and you guys have OpenShift which became very successful over the past few years, the growth has been phenomenal. So congratulations, but it's pointing to a bigger trend and that is that the infrastructure software, the platform as a service is becoming the middleware, the glue, if you will, and Kubernetes and containers are facilitating a new architecture for developers and operators. How important is that with you guys, and what's the impact of the customer when they think, okay I'm going to have an agile DevOps environment, workload portability, but do I have to build that out? You mentioned people don't have to necessarily do that anymore. The trend has become on-premise. What's the impact of the customer as they hear Kubernetese and containers and the data conversation? >> You mentioned agile DevOps environment, workload portability so one of the things that customers come to us for is having that same thing, but infrastructure agnostic. They say, I don't want to be locked in. Love AWS, love Azure, but I don't want to be locked into those platforms. I want to have an abstraction layer for my Kubernetese layer that sits on top of those infrastructure platforms. As I bring my workloads, one-by-one, custom DevOps from a lift and shift of legacy apps onto that substrate, I want to have it be independent, private cloud or public cloud and, time permitting, we'll go into more details about what we've seen happening in the private cloud with analytics as well, which is effectively what brought us here today. The pattern that we've discovered with a lot of our large customers who are saying, hey, we're running OpenStack, they're large institutions that for lots of reasons they store a lot of their data on-premises saying, we want to use the utility compute model that OpenStack gives us as well as the shared data context that Ceph gives us. We want to use that same thing for our analytics workload. So effectively some of our large customers taught us this program. >> So they're building infrastructure for analytics essentially. >> That's what it is. >> One of the challenges with that is the data is everywhere. It's all in silos, it's locked in some server somewhere. First of all, am I overstating that problem and how are you seeing customers deal with that? What are some of the challenges that they're having and how are you guys helping? >> Perfect lead in, in fact, one of our large government customers, they recently sent us an unsolicited email after they deployed the first 10 petabytes in a deca petabyte solution. It's OpenStack based as well as Ceph based. Three taglines in their email. The first was releasing the lock on data. The second was releasing the lock on compute. And the third was releasing the lock on innovation. Now, that sounds a bit buzzword-y, but when it comes from a customer to you. >> That came from a customer? Sounds like a marketing department wrote that. >> In the details, as you know, traditional HDFS clusters, traditional Hadoop clusters, sparklers or whatever, HDFS is not shared between clusters. One of our large customers has 50 plus analytics clusters. Their data platforms team employ a maze of scripts to copy data from one cluster to the other. And if you are a scientist or an engineer, you'd say, I'm trying to obtain these types of answers, but I need access to data sets A, B, C, and D, but data sets A and B are only on this cluster. I've got to go contact the data platforms team and have them copy it over and ensure that it's up-to-date and in sync so it's messy. >> It's a nightmare. >> Messy. So that's why the one customer said releasing the lock on data because now it's in a shared. Similar paradigm as AWS with EMR. The data's in a shared context, an S3. You spin up your analytics workloads on AC2. Same paradigm discussion as with OpenStack. Your spinning up your analytics workloads via OpenStack virtualization and their sourcing is shared data context inside of Ceph, S3 compatible Ceph so same architecture. I love his last bit, the one that sounds the most buzzword-y which was releasing lock on innovation. And this individual, English was not this person's first language so love the word. He said, our developers no longer fear experimentation because it's so easy. In minutes they can spin up an analytics cluster with a shared data context, they get the wrong mix of things they shut it down and spin it up again. >> In previous example you used HDFS clusters. There's so many trip wires, right. You can break something. >> It's fragile. >> It's like scripts. You don't want to tinker with that. Developers don't want to get their hand slapped. >> The other thing is also the recognition that innovation comes from data. That's what my takeaway is. The customer saying, okay, now we can innovate because we have access to the data, we can apply intelligence to that data whether it's machine intelligence or analytics, et cetera. >> This the trend in infrastructure. You mentioned the shared context. What other observations and learnings have you guys come to as Red Hat starts to get more customer interactions around analytical infrastructure. Is it an IT problem? You mentioned abstracting the way different infrastructures, and that means multi-cloud's probably setup for you guys in a big way. But what does that mean for a customer? If you had to explain infrastructure analytics, what needs to get done, what does the customer need to do? How do you describe that? >> I love the term that industry uses of multi-tenant workload isolation with shared data context. That's such a concise term to describe what we talk to our customers about. And most of them, that's what they're looking for. They've got their data scientist teams that don't want their workloads mixed in with the long running batch workloads. They say, listen, I'm on deadline here. I've got an hour to get these answers. They're working with Impala. They're working with Presto. They iterate, they don't know exactly the pattern they're looking for. So having to take a long time because their jobs are mixed in with these long MapReduce jobs. They need to be able to spin up infrastructure, workload isolation meaning they have their own space, shared context, they don't want to be placing calls over to the platform team saying, I need data sets C, D, and E. Could you please send them over? I'm on deadline here. That phrase, I think, captures so nicely what customers are really looking to do with their analytics infrastructure. Analytics tools, they'll still do their thing, but the infrastructure underneath analytics delivering this new type of agility is giving that multi-tenant workload isolation with shared data context. >> You know what's funny is we were talking at the kickoff. We were looking back nine years. We've been at this event for nine years now. We made prediction there will be no Red Hat of big data. John, years ago said, unless it's Red Hat. You guys got dragged into this by your customers really is how it came about. >> Customers and partners, of course with your recent guest from Hortonworks, the announcement that Red Hat, Hortonworks, and IBM had on Monday of this week. Dialing up even further taking the agility, okay, OpenStack is great for agility, private cloud, utility based computing and storage with OpenStack and Ceph, great. OpenShift dials up that agility another notch. Of course, we heard from the CEO of Hortonworks how much they love the agility that a Kubernetes based substrate provides their analytics customers. >> That's essentially how you're creating that sort of same-same experience between on-prem and multi-cloud, is that right? >> Yeah, OpenShift is deployed pervasively on AWS, on-premises, on Azure, on GCE. >> It's a multi-cloud world, we see that for sure. Again, the validation was at VMworld. AWS CEO, Andy Jassy announced RDS which is their product on VMware on-premises which they've never done. Amazon's never done any product on-premises. We were speculating it would be a hardware device. We missed that one, but it's a software. But this is the validation, seamless cloud operations on-premise in the cloud really is what people want. They want one standard operating model and they want to abstract away the infrastructure, as you were saying, as the big trend. The question that we have is, okay, go to the next level. From a developer standpoint, what is this modern developer using for tools in the infrastructure? How can they get that agility and spinning up isolated, multi-tenant infrastructure concept all the time? This is the demand we're seeing, that's an evolution. Question for Red Hat is, how does that change your partnership strategy because you mentioned Rob Bearden. They've been hardcore enterprise and you guys are hardcore enterprise. You kind of know the little things that customers want that might not be obvious to people: compliance, certification, a decade of support. How is Red Hat's partnership model changing with this changing landscape, if you will? You mentioned IBM and Hortonworks release this week, but what in general, how does the partnership strategy look for you? >> The more it changes, the more it looks the same. When you go back 20 years ago, what Red Hat has always stood for is any application on any infrastructure. But back in the day it was we had n-thousand of applications that were certified on Red Hat Linux and we ran on anybody's server. >> Box. >> Running on a box, exactly. It's a similar play, just in 2018 in the world of hybrid, multi-cloud architectures. >> Well, you guys have done some serious heavy lifting. Don't hate me for saying this, but you're kind of like the mules of the industry. You do a lot of stuff that nobody either wants to do or knows how to do and it's really paid off. You just look at the ascendancy of the company, it's been amazing. >> Well, multi-cloud is hard. Look at what it takes to do multi-cloud in DevOps. It's not easy and a lot of pretenders will fall out of the way, you guys have done well. What's next for you guys? What's on the horizon? What's happening for you guys this next couple months for Red Hat and technology? Any new announcements coming? What's the vision, what's happening? >> One of the announcements that you saw last week, was Red Hat, Cloudera, and Eurotech as analytics in the data center is great. Increasingly, the world's businesses run on data-driven decisions. That's great, but analytics at the edge for more realtime industrial automation, et cetera. Per the announcements we did with Cloudera and Eurotech about the use of, we haven't even talked about Red Hat's middleware platforms, such as AMQ Streams now based on Kafka, a Kafka distribution, Fuze, an integration master effectively bringing Red Hat technology to the edge of analytics so that you have the ability to do some processing in realtime before back calling all the way back to the data center. That's an area that you'll also see is pushing some analytics to the edge through our partnerships such as announced with Cloudera and Eurotech. >> You guys got the Red Hat Summit coming up next year. theCUBE will be there, as usual. It's great to cover Red Hat. Thanks for coming on theCUBE, Brent. Appreciate it, thanks for spending the time. We're here in New York City live. I'm John Furrier, Dave Vallante, stay with us. All day coverage today and tomorrow in New York City. We'll be right back. (upbeat music)
SUMMARY :
Brought to you by SiliconANGLE Media Open source, DevOps is the theme here. Cloud is driving a lot of the action. One of the things that we see is people and that is that the infrastructure software, the shared data context that Ceph gives us. So they're building infrastructure One of the challenges with that is the data is everywhere. And the third was releasing the lock on innovation. That came from a customer? In the details, as you know, I love his last bit, the one that sounds the most buzzword-y In previous example you used HDFS clusters. You don't want to tinker with that. that innovation comes from data. You mentioned the shared context. I love the term that industry uses of You guys got dragged into this from Hortonworks, the announcement that Yeah, OpenShift is deployed pervasively on AWS, You kind of know the little things that customers want But back in the day it was we had n-thousand of applications in the world of hybrid, multi-cloud architectures. You just look at the ascendancy of the company, What's on the horizon? One of the announcements that you saw last week, You guys got the Red Hat Summit coming up next year.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Vallante | PERSON | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
John | PERSON | 0.99+ |
Brent Compton | PERSON | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
John Furrier | PERSON | 0.99+ |
Eurotech | ORGANIZATION | 0.99+ |
Hortonworks | ORGANIZATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Brent | PERSON | 0.99+ |
New York City | LOCATION | 0.99+ |
2018 | DATE | 0.99+ |
Red Hat | ORGANIZATION | 0.99+ |
Rob Bearden | PERSON | 0.99+ |
nine years | QUANTITY | 0.99+ |
Andy Jassy | PERSON | 0.99+ |
last week | DATE | 0.99+ |
first language | QUANTITY | 0.99+ |
Three taglines | QUANTITY | 0.99+ |
SiliconANGLE Media | ORGANIZATION | 0.99+ |
first | QUANTITY | 0.99+ |
tomorrow | DATE | 0.99+ |
second | QUANTITY | 0.99+ |
One | QUANTITY | 0.99+ |
Cloudera | ORGANIZATION | 0.99+ |
next year | DATE | 0.99+ |
third | QUANTITY | 0.99+ |
New York | LOCATION | 0.99+ |
Impala | ORGANIZATION | 0.99+ |
Monday this week | DATE | 0.99+ |
VMworld | ORGANIZATION | 0.98+ |
one cluster | QUANTITY | 0.98+ |
Red Hat Summit | EVENT | 0.98+ |
ninth year | QUANTITY | 0.98+ |
one | QUANTITY | 0.98+ |
OpenStack | TITLE | 0.98+ |
today | DATE | 0.98+ |
NYC | LOCATION | 0.97+ |
20 years ago | DATE | 0.97+ |
Kubernetese | TITLE | 0.97+ |
Kafka | TITLE | 0.97+ |
First | QUANTITY | 0.96+ |
this week | DATE | 0.96+ |
Red Hat | TITLE | 0.95+ |
English | OTHER | 0.95+ |
Monday of this week | DATE | 0.94+ |
OpenShift | TITLE | 0.94+ |
one standard | QUANTITY | 0.94+ |
50 plus analytics clusters | QUANTITY | 0.93+ |
Ceph | TITLE | 0.92+ |
Azure | TITLE | 0.92+ |
GCE | TITLE | 0.9+ |
Presto | ORGANIZATION | 0.9+ |
agile DevOps | TITLE | 0.89+ |
theCUBE | ORGANIZATION | 0.88+ |
DevOps | TITLE | 0.87+ |
Kevin Kroen, PWC | Automation Anywhere Imagine 2018
>> From Times Square, in the heart of New York City, it's theCUBE. Covering Imagine 2018. Brought to you by Automation Anywhere. >> Welcome back everybody, Jeff Frick here with theCUBE, we are at Automation Anywhere in midtown Manhattan, 2018, excited to have our next guest, he's Kevin Kroen, he's partner of financial services, intelligent automation leader at PWC, Kevin, great to see you. >> Thank you. >> So financial services seems to be a theme, we're here in Manhattan, why is financial services an early adopter or maybe a frequent adopter or an advanced adopter of the RPA technology? >> Sure, so I think as we see our financial services clients and their agendas, there's been a huge focus on productivity and simplifying their overall operating model over the past couple of years. Banks in particular have gone through several years of having to focus their spending on non discretionary manners like regulatory compliance and risk management. And what that's generated is a need, as they started looking towards the next generation to really start thinking about what they're gonna look like in a post regulatory environment. And automation has quickly risen to the top of the agenda. >> What they're gonna look like in a post regulatory environment. >> Yes. >> Why a post regulate? >> Well I mean if you look through, you know what banks have had to deal with in term of Dodd-Frank, in terms of CCAR, you know, the regulation from federal reserve, these are things that took a lot of spending both on implementing operational processes and on implementing technology. A lot of that work is starting to you know, the banks are putting that behind themselves and so as they look forward and look at how they're going to gain more profitability in the future, the challenge becomes, there's not necessarily a new set of product innovation coming in, and so you have to really look at the expense line. >> Right. >> And so because of that automation has risen to the top of that agenda and so this continues to be one of the top areas of interest that we're getting from our clients. >> Right, so when you say post regulatory, you mean like a new regulation that they have to respond to, not that they're suddenly not gonna be regulated. >> There's not a lot of new regulations coming in right now, especially- >> That pesky one last week, GDRP. >> Yeah but in the US we're in an environment right now, there was just, you know, the revisions to the Dodd-Frank bill that were passed a lot of regulatory rules were actually being loosened so you don't necessarily have an increase in dollars that are going to be going into that. >> Right right, so it just always fascinates me, right, I thought ERP was supposed to wring out all the efficiency in our systems but that was not the case, not even by a long shot and now we continue to find these new avenues for more efficiency and clearly this is a big one that we've stumbled upon. >> Yeah, you know I think it's interesting, when you look at big technology investment over the last decade or two, you could argue a lot of efforts been focused at what I call the kind of core infrastructure and core plumbing so you know, how do I consolidate data into a single location? How do I make sure that data reconciles into different parts of my organization but that like kind of last mile of what someone does as part of their day to day business process was never really addressed, you know or is only addressed in pieces, and so I think as you start looking at the productivity term and how you actually start getting efficiency, we have very few clients that are saying, I want to take on that next big ERP type of limitation or I'm ready to spend 300 million dollars on a new project, they're looking to try to get the most value out of what they already have and they're actually looking to look at that last mile and how can they actually gain some benefit off it so the RPA technologies I think we're one of the catalysts of just being the perfect technology in the right place at the right time from a current business environment, a current technology spend perspective. >> Yeah it's pretty interesting Mihir was talking about, you know one of the big benefits is that you can take advantage of your existing infrastructure, you know, it's not a big giant rip and replace project but it's, again, it's this marginal incremental automation that you just get little benefit, little benefit, little benefit, end of the day, turns into a big benefit. >> Yeah, and I think that's, you know, it's quick, it's fast, it's, you know it can be implemented in an agile manner and you know, our clients are continuously telling us over and over again, they're willing to invest, but they wanna invest where they're gonna see a tangible payback immediately. >> Right. >> And I think when you start to talk the concept of digital transformation, it can mean a lot of different things to a lot of different people but there are big picture changes that could be made, those may be longer term trends but they're more immediate things and more immediate benefits that could be gained and I think that's really the sweet spot of where RPA and Automation Anywhere fall into. >> I was just looking up Jeff Immelt in his key note said this is the easy fountain money of any digital transformation project, I think that was the quote, that you'll ever do. That's a pretty nice endorsement. >> Yeah and it's, as we go out, we talk to CFOs, COOs, CIOs, you know, it's, the value proposition is really attractive because, you know, there have been, there's a track record of failed, technology projects failed big transformation projects and, you know, no one wants to necessarily risk their career on creating the next big failure and so I think using technology like RPA almost as an entry point or kind of like a gateway drug into the digital world, see the benefits, start to understand what are some of the business problems and historical kind of, you know, things you're trying to untangle in your infrastructure, attack that and then, you know, start to layer on additional things on top of that, once you get good with RPA and then you can start figuring out, okay, that's they gateway to artificial intelligence, okay how do I start to apply AI across my organization? As you get beyond AI, okay, how do I get into, more advanced state infrastructure and you can start thinking about this world where you can, you know, rather than do the big, five year project where you're gonna try to solve world hunger, it gives you a chance to kind of incrementally go digital over time and I think that's definitely the direction we see a lot of our clients wanting to go in. >> Right, Kevin I want to get your feedback on another topic that came up again in the keynote, was just security, you know it was like the last thing that was mentioned, you know, like A B C D E F G and security, financial services, obviously security is number one, it's baked into everything that everyone's trying to do now, it's no longer this big moat and wall, but it's got to be everywhere so I'm just curious, from the customer adoption point of view, where does security come up in the conversation, has it been a big deal, is it just assumed, is there a lot of good stuff that you can demonstrate to clients, how does security fit within this whole RPA world? >> You know with security and I would just say the broader kind of risk management pieces to the operator infrastructure are one of the first questions we get asked and a highly regulated environment like financial services, you know, the technology is easy and powerful with RPA but you also have to take a step back and say okay, I can program a bot to go do anything in my infrastructure, and that could mean running a reconciliation or it could mean going to our wire system and trying to send money out the door. And so there's a lot of concern around, not only understanding the technical aspects to you know, how the tools work with different types of security technologies, but more looking at your approach to entitlements and your approach to how you actually manage who has access to code bots, deployed bots in production, the overtime, understand what happens, you know we did a presentation to a board of directors a couple months ago on kind of automation more broadly and you know this is, you know, senior level executives the first question we got was, you know, okay, how do I prevent the 22 year old kid that just came off of campus from building a bot that no one knows about, setting it loose in our infrastructure and it going rogue, right? And so I mean this group was pretty savvy, they caught onto it very quickly and you know, the CIO of this client was sitting next to me and she kind of didn't have an immediate answer to that and I think that was kind of the a-ha moment, this is something we really need to put some thought into around you know, who are we gonna let build bots, what policies are gonna be set around how bots get deployed into our production environment, how are we gonna monitor what happens? You know how are we gonna get our auditors, our operational risk folks, our regulators, how are we gonna get all our different stakeholder groups comfortable that we have a well controlled, well functioning bot infrastructure that exists? >> Right, cause the bots actually act like people, they're entitled as like a role right, within the organization? >> We have clients that have literally had to set bots up as new employees, like they get onboarded, they have a, you go to the corporate directory and you can see a picture of R2D2, right like and it's the way they get around how they get a bot intel to a system but it's still, it's not a human right, so you still have to have a policy for how you actually will get code that uses that bot entitlement to function right and so that has to be done in a well disciplined, well controlled manner. >> Right, because to give them the ability to provide information to help a person make a decision is very different then basically enabling them to make that decision and take proactive action. >> Exactly. >> Yeah, it's funny we talked to Dr. Robert Gates at a show a little while ago and he said the only place in the US military where a machine can actually shoot a gun is on the Korean border, but every place else they can make suggestions but ultimately it's gotta be a person that makes the decision to push the button. >> And we're seeing, you know, trying to equate that to financial services, you see a similar pattern where there are certain areas where people are very comfortable playing this technology, you know you get into accounting and reporting and you know more back office type processes, you got other areas that people are a little less comfortable, you know anything that touches kind of wire systems or touches things that, you know, going out the door, touches kind of core trading processes, things like that there's a different risk profile associated with it. I think the other challenge is too is RPA is getting the gateway drug into this going back to my previous point, as you start to layer additional technologies into this, you might have less transparency over understanding clearly what's happening, especially as artificial intelligence takes a much broader role in this and so there's gonna be a lot of scrutiny I think over the next couple years put into like how do I understand the models that are created by artificial intelligence technologies and those decisions that are being made because you, if your regulator says, okay, why did you make this decision, you have to be able to explain it as the supervisor of that intelligent bot, you can't just say, oh it's cause what the machine told me to do, as so, that'll be one of the interesting challenges that's ahead of us. >> Yeah it's good, I mean it's part of the whole scale of conversation, I had interesting conversation with a guy, talking about really opening up those AI boxes so that you have an auditable process, right, you can actually point to why it made the decision even if you're not the one that made it in real time and it's doing it really really quickly so. >> Exactly. >> Really important piece. >> Yeah and as PWC, it's one of our challenges, as a consultant I'm helping clients implement this, my colleagues in our audit practice are now grappling with that same question because we're increasingly being asked to audit that type of infrastructure and have to prove that something did what it was suppose to have done. >> Right, right, alright Kevin, well nothing but opportunities for you ahead and thanks for taking a few minutes to stop by. >> Okay, thank you for having me. >> Alright, he's Kevin, I'm Jeff, you're watching theCUBE from Automation Anywhere, Imagine 2018 in Manhattan, thanks for watching. (upbeat music)
SUMMARY :
Brought to you by Automation Anywhere. Kevin, great to see you. of having to focus their spending on in a post regulatory environment. to you know, the banks are this continues to be one of the that they have to respond to, there was just, you know, the revisions in our systems but that was not the case, and so I think as you start looking is that you can take advantage Yeah, and I think that's, you know, And I think when you I think that was the and historical kind of, you know, to you know, how the tools work with and so that has to be done Right, because to give them the ability that makes the decision and you know more back right, you can actually point being asked to audit opportunities for you ahead Imagine 2018 in Manhattan,
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Jeff Frick | PERSON | 0.99+ |
Kevin Kroen | PERSON | 0.99+ |
Jeff Immelt | PERSON | 0.99+ |
Manhattan | LOCATION | 0.99+ |
Kevin | PERSON | 0.99+ |
Jeff | PERSON | 0.99+ |
New York City | LOCATION | 0.99+ |
300 million dollars | QUANTITY | 0.99+ |
Times Square | LOCATION | 0.99+ |
22 year | QUANTITY | 0.99+ |
PWC | ORGANIZATION | 0.99+ |
2018 | DATE | 0.99+ |
Dr. | PERSON | 0.99+ |
first question | QUANTITY | 0.99+ |
Robert Gates | PERSON | 0.99+ |
US | LOCATION | 0.98+ |
last week | DATE | 0.98+ |
one | QUANTITY | 0.98+ |
both | QUANTITY | 0.98+ |
Automation Anywhere | ORGANIZATION | 0.97+ |
five year | QUANTITY | 0.96+ |
theCUBE | ORGANIZATION | 0.96+ |
CCAR | ORGANIZATION | 0.96+ |
single location | QUANTITY | 0.94+ |
first questions | QUANTITY | 0.93+ |
Dodd-Frank | TITLE | 0.91+ |
midtown Manhattan | LOCATION | 0.9+ |
Mihir | PERSON | 0.89+ |
couple months ago | DATE | 0.87+ |
Korean | LOCATION | 0.85+ |
two | QUANTITY | 0.85+ |
Automation | ORGANIZATION | 0.78+ |
past couple of years | DATE | 0.77+ |
Automation Anywhere Imagine | TITLE | 0.76+ |
Dodd-Frank | ORGANIZATION | 0.76+ |
next couple years | DATE | 0.73+ |
rules | QUANTITY | 0.73+ |
a little while ago | DATE | 0.67+ |
US military | ORGANIZATION | 0.66+ |
last decade | DATE | 0.65+ |
challenges | QUANTITY | 0.6+ |
of new regulations | QUANTITY | 0.6+ |
D | TITLE | 0.59+ |
lot | QUANTITY | 0.55+ |
Automation Anywhere | TITLE | 0.52+ |
top areas | QUANTITY | 0.52+ |
R2D2 | TITLE | 0.51+ |
Imagine | TITLE | 0.39+ |
Weston Jones, EY | Automation Anywhere Imagine 2018
>> From Times Square, in the heart of New York City, it's theCUBE. Covering Imagine 2018. Brought to you by Automation Anywhere. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in Manhattan at the Automation Everywhere Imagine 2018. About 1,100 people talking about RPA, Robotics Process Automation, bots, really bringing automation to the crappy processes that none of us like to do in our day to day job. And, we're excited to have a practitioner. He's out in the field. He's talking to customers all the time. It's Weston Jones, and he's the global intelligent automation leader for EY. Weston, great to see you. >> Yeah, thank you, good to be here. >> Absolutely, so it's funny, you said you've been with these guys for a number of years, so when did you get started, how did you see the vision when nobody else saw it, and here we are five years later, I think, since you first met 'em. >> Oh, I know, it's just funny. I mean, years ago I saw Automation Anywhere at conferences. They were one of the small booths, just like everybody else was, talking about automation. I watched them for several years, and then I decided one year when we were looking at some of our offerings to bring in RPA and talk to our leadership about it, and kinda the light bulbs went off. So, from five, six years ago 'til today we've been working with them, and it's really amazing to see kind of how things have changed, and how the adoption has taken place. >> You know, it's such a big moment in a startup, especially software company, when you get a big global integrator like you guys to jump in, you know, advisory service. It's really hard to do. I've been in that position myself, and you guys don't make the move unless you really see a big opportunity. So, what did you see in terms of the big opportunity that made you, you know, basically bet your career on this vertical? >> Well, so when I went to our leadership, in the meeting I had our global shared services leader. So, we have 7,000 plus people on our shared services, and he was very skeptical. We had to do 20 plus proof of concepts with him, and HR, IT, finance, et cetera, to get him excited about it. Now, he's our biggest fan, and actually we promoted him to run our global internal automation team where now we think we're one of the largest users of automation. We're one of the biggest users within tax. We use Automation Anywhere within tax. We have over 750 bots working, and we have a goal to have 10,000 plus by 2022. So, we're really pushing the bar in scaling. >> From 750 to 10,000, what are we, 2018, in four years. >> In four years. That's our goal. >> So, where did you find the early successes, what kind of bots specifically, what type of processes are kind of right for people that are interested, see the potential, but aren't really sure kinda how to get started, or to get that early success? >> Yeah, I mean, it's just almost like anything else, the quick wins, you know. Start with things that are very rules-based, that have a lot of people, FTs associated with them. You know, our thing wasn't that we were actually eliminating FTs, we were just developing capacity, 'cause we're a company that's growing, so instead of hiring more and more people, we took all that mundane work out of people's jobs and allowed them to focus on things that were more value-added. So, the block and tackle stuff-- >> Like what? Like, give me a couple of, you know, just simple stuff-- >> well, we have like HR onboarding, you know, we onboard 60,000 people a year. HR onboarding is something that's very repetitive activity, logging in and out of multiple systems. And, it was something where we were hiring HR professionals that knew how to do talent management, that knew how to do all these things we really wanted them to do, but we had 'em focused on doing a lot of very transactional type activities. So, we said why don't we use the technology for that. Let's free these people up so they can then focus on developing talent, career ladders, other things that we really wanted them to focus on. Other things like, you know, payments, matching, and payment application, things like that, password resets, you know, a lot of stuff that you, I mean, you can just think of in your head. A lot of stuff in finance, a lot of stuff in HR and IT. Even our supply chain, too. We're doing like T and Es, we're doing a lot of automation in our T and E area. But, that to say, I mean, I've mentioned all back office things. We're also doing a lot of front office. So, for example, in our tax department we use almost exclusively Automation Anywhere to do tax returns for clients. And, we have, I think, over a million plus hours that we've eliminated using Automation Anywhere. >> Now, how do you Automation Anywhere a tax return? >> Well, tax return is a very complex set of rules, and you basically, once you kind of load the rules in for certain activities, it's stuff like pulling data from one system into another, you know, doing multiple taxed jurisdictions. >> Is it just like particular steps within that, you just kinda pick off one little process at a time, one little process at a time? >> True, and then you can also put in, you can do a nice interface in the front, and you can have people giving you the data, and then you let the automation then get the data to the right parts within the tax return. >> So, I'm curious in terms of the people that create the bots. Who are they, kinda what skill sets do they have, and do you see that changing over time as you try to go from 750, whatever it is, a 20x multiple, over four years? Do you see kinda the population of people that are able to create and implement the bots growing? How do you, kinda, managing the supply side on on that? >> We have a philosophy that 70% of it's process, 30% of it's technology. We're fortunate that in our advisory area across all the major functional areas, supply chain, HR, finance, et cetera, we have process experts. So, we use those process experts to get the process down, and then what we do is we have core development teams around the world. We have a big team in India, a big team in Costa Rica. We have a team in China, and elsewhere. And, those are the developers. And, so our process people map out the process and then hand that off to the developer. So, developers, you know, we basically, I mean, with Automation Anywhere's help, we've trained them to do the work and they've made it more and more, as time goes on, they made it easier and easier for them to develop bots. And, so We've been able to take people almost right out of college. We've hired some high school students. We take people that, you know, two thirds of the American population doesn't have a college degree, so we hire non-college degrees and teach them how to do this. Not that it's easy, and to be really good you have to have time and experience, but we can teach them to do these types of activities for us. >> That's amazing. So, I wonder if you can share what are some of the biggest surprises, you know, kind of implementation surprises, or ROI types of surprises that you found in implementing these 750. >> Yeah, so one thing I tell people about is if you talk about the Gartner Hype Curve, you go up and you fall into the valley of disillusionment, and, you know, there's gonna be four or five of those valleys that are gonna happen, and you just need to power through them because the technology is so compelling, and the benefits are so compelling. I mean, there's over a dozen benefits whether it's cost savings, improved security, better accuracy, whatever. So, some of the surprises were scaling. Like, when I talk about the DIPSS, the D-I-P-S-S, DIPPS, the first one is gonna be data. People are gonna realize that their data isn't quite there in order to do the more intelligent activities. The integration, so integrating the RPA with the more intelligent pieces of the IQ bot, and other things, how do you do those integrations, how do you take other tools outside of that and integrate them. The third is penetration. I mean, penetration is very small right now. What happens is people tend to look at a whole process that needs to be automated when what you need to do is you need to think about breaking those processes apart. Like FPNA, for example, may have a couple dozen steps to it, but there are pockets of steps that are very automatable. For example, pulling data, structuring it, normalizing it, getting it into some kind of report, that can all be done by automation, then hand it off to someone to do more cognitive activities. So, the penetration is very small right now, but will continue to grow. The savings, you know, have realistic expectations on savings. When this first came out of the door a lot of people were talking very, very high numbers. I mean, you can get it every once in a while, but, the saving numbers, just be realistic about that. And, the last part is scaling. We found scaling to be something that, you know, at the time when we were doing it, very few people had done it. So, to figure out how do you scale, and how do you develop a bot control room, how do you manage the bots, how do you manage the bots interfacing with people, how do you manage the bots interfacing with other technologies. It's a lot more to it than just putting the bot up and letting it work, because they need care and feeding ongoing, because it's not related to the Automation Anywhere technology, it's more of the other things it touches, like website changes, like upgrades to different systems that the bot has to execute with. Those are gonna constantly change and you just need to make sure you're adjusting the bot to actually work in those environments. So, those are kinda the four or five things that we've seen. And, when we go from 750, to 1,000, to 10,000, I mean, we think we're gonna see much more orchestration type things. You know, how do you orchestrate in a more automated way across the bots, the people, and then the other technology. >> Right, it's funny on the scale issue 'cause they were talking about, you know, how do you go from 10 bots, you got 750 to 10,000, and there's been a concept under it that they are a digital workforce, implying that you have to manage 'em like a workforce. You gotta hire 'em, you gotta train 'em, you gotta put 'em in place, you gotta kinda keep an eye on 'em, you gotta review 'em every now and then, and really it's an active management process, it's not just set and forget. >> Yeah, we're hoping that we'll have, I mean, we have some of this already, but we'll have bots managing bots. Well, bots auditing bots. We'll have bots orchestrating bots. That's all gonna eventually happen. I think we can do some of it today, but it's gonna be more and more common. The orchestration piece is really the thing that is gonna be new, that is gonna drive a lot of people this hard to scale. >> The other two consistent themes that you just touched on that we talked a little bit before we turned the cameras on, is Amara's Law, my favorite. You know, we overestimate the short term, which Gartner might call the Hype cycle, but we underestimate in the long term. Really, the other one is kinda just DevOps, and there's DevOps as a way to write code, but I think, more importantly, is DevOps as a culture, which is just look for little wins, little wins, little wins, little wins, little wins, and, before you know it, you've automated a lot and you're gonna start seeing massive returns on that effort versus the, oh, let's throw it in, we're gonna get this tremendous cost savings on day zero, day one, or day 10, or whatever it is. That's really not the strategy. >> Well, I think a lot of people maybe don't like to hear this, but it's a journey. I mean, you start out using the technology where you can. So, it's not a technology play, it's solving your biggest, most complicated problems, that's the key. And, whatever technology you need to do that, use that. So, you do the RPA, then you get more benefit when you add the IQ bots, and the intelligent stuff, and you get more benefit when you start adding, you know, technologies that are even ancillary, like Blockchain, IoT, and things like that. You'll get more and more kind of benefits from this technology. >> All right, Weston, well, thank you for sharing your stories. It's good to get it from the front lines. And, good luck on making 20,000 bots in four years. >> Thank you, thank you. >> He's Weston, I'm Jeff, you're watching theCUBE from Automation Anywhere Imagine 2018. Thanks for watching. (upbeat music)
SUMMARY :
Brought to you by Automation Anywhere. and he's the global intelligent so when did you get started, and how the adoption has taken place. and you guys don't make the move and we have a goal to From 750 to 10,000, what That's our goal. the quick wins, you know. like HR onboarding, you know, and you basically, once you and then you let the and do you see that changing over time So, developers, you know, we basically, So, I wonder if you can share So, to figure out how do you scale, implying that you have to a lot of people this hard to scale. themes that you just touched on the technology where you can. All right, Weston, well, thank you Thanks for watching.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Jeff Frick | PERSON | 0.99+ |
China | LOCATION | 0.99+ |
India | LOCATION | 0.99+ |
70% | QUANTITY | 0.99+ |
10 bots | QUANTITY | 0.99+ |
Jeff | PERSON | 0.99+ |
30% | QUANTITY | 0.99+ |
New York City | LOCATION | 0.99+ |
Times Square | LOCATION | 0.99+ |
Costa Rica | LOCATION | 0.99+ |
20,000 bots | QUANTITY | 0.99+ |
Manhattan | LOCATION | 0.99+ |
2018 | DATE | 0.99+ |
five | QUANTITY | 0.99+ |
750 | QUANTITY | 0.99+ |
five years later | DATE | 0.99+ |
four | QUANTITY | 0.99+ |
Weston | PERSON | 0.99+ |
Gartner | ORGANIZATION | 0.99+ |
20x | QUANTITY | 0.99+ |
third | QUANTITY | 0.99+ |
10,000 | QUANTITY | 0.99+ |
1,000 | QUANTITY | 0.99+ |
five | DATE | 0.99+ |
first | QUANTITY | 0.98+ |
2022 | DATE | 0.98+ |
over 750 bots | QUANTITY | 0.98+ |
over four years | QUANTITY | 0.98+ |
four years | QUANTITY | 0.98+ |
EY | ORGANIZATION | 0.98+ |
Amara's Law | TITLE | 0.97+ |
10,000 plus | QUANTITY | 0.97+ |
Automation Anywhere | ORGANIZATION | 0.97+ |
today | DATE | 0.97+ |
five things | QUANTITY | 0.97+ |
day zero | QUANTITY | 0.97+ |
two consistent themes | QUANTITY | 0.97+ |
one | QUANTITY | 0.96+ |
Weston Jones | PERSON | 0.96+ |
one system | QUANTITY | 0.96+ |
D-I-P-S-S | COMMERCIAL_ITEM | 0.96+ |
DevOps | TITLE | 0.96+ |
years ago | DATE | 0.96+ |
About 1,100 people | QUANTITY | 0.95+ |
over a dozen | QUANTITY | 0.95+ |
day 10 | QUANTITY | 0.95+ |
first one | QUANTITY | 0.95+ |
six years ago | DATE | 0.95+ |
day one | QUANTITY | 0.94+ |
one thing | QUANTITY | 0.94+ |
7,000 plus people | QUANTITY | 0.94+ |
FPNA | TITLE | 0.94+ |
Automation Anywhere Imagine | TITLE | 0.9+ |
two thirds | QUANTITY | 0.89+ |
60,000 people a year | QUANTITY | 0.89+ |
theCUBE | ORGANIZATION | 0.85+ |
couple dozen steps | QUANTITY | 0.84+ |
one little process | QUANTITY | 0.82+ |
20 plus proof | QUANTITY | 0.81+ |
over a million plus hours | QUANTITY | 0.79+ |
T and Es | ORGANIZATION | 0.78+ |
one of | QUANTITY | 0.77+ |
Gartner Hype Curve | ORGANIZATION | 0.75+ |
one little process | QUANTITY | 0.7+ |
several years | QUANTITY | 0.7+ |
Automation Everywhere Imagine | ORGANIZATION | 0.69+ |
year | QUANTITY | 0.69+ |
Automation Anywhere | TITLE | 0.68+ |
Automation | TITLE | 0.58+ |
one | DATE | 0.55+ |
Imagine | TITLE | 0.55+ |
American | OTHER | 0.51+ |
booths | QUANTITY | 0.48+ |
Automation Anywhere | ORGANIZATION | 0.42+ |
Jeremy Gardner & Genevieve Roch Decter | Blockchain Week NYC 2018
from New York it's the cube covering blockchain week now here's John furry hello everyone welcome back to this special cube exclusive on the water coverage of the awesome cryptocurrency event going on this week blockchain week New York City D central Anthony do re oh seven a big special event launching some great killer products me up to cube alumni that we introduced at polycon 2018 Genevieve Dec Monroe and Jeromy Gartner great to see you guys thanks for having us so you guys look fabulous you look beautiful you're smart we're on a boat we're partying it feels like Prague it feels like prom feels like we are at the top of another bubble couldn't feel better five more boat parties and then the bubbles officially at the top but we're only had the first boat party well the real existential question is what do we view next you know we've we've graduated from nightclubs and strip clubs and now two super yachts like do we go on a spaceship neck's or a Boeing Jets yeah I mean the options are somewhat limited in how we scale up the crypto parties I actually heard today one of my clients is launching in space a crypto mining operation that's fueled by solar power so we might be going to space Elon Musk wants to get involved I agree like where are we going you guys are awesome I love the creative so this party to me is really a testament of the community talk about the community I see polycon was great in Puerto Rico they had restart week and that but I heard these guys saying here at the central that the community's fragmented is the community fragmented seems like it's not out there or just only one pocket of the community I think the community so we have 10,000 people at consensus okay so these are 10,000 people that have gone down the rabbit hole and they're all at the Hilton in midtown Manhattan kind of going like how'd you get involved why are you here 10,000 people is a lot but I think that yeah we're we're at the decentral party so some of the yeast communities are being fragmented but I think we're having like infrastructure built to kind of connect the broader world to the things whether it's custodial services whether it's like tonight the jocks 2.0 wallet and you know everything that's getting involved there I don't know Jeremy Jeremy it's like an international traveler so you Carly Jeremy it's 100 percent in an echo chamber more importantly rabbit holes are like dark and confusing places that there are they're winding and a lot of people are here for very different reasons and thus when you have all these new entrants to the industry to this technology here for all these different reasons of course you have some fragmentation you know in many regards the ideological and philosophical roots of Bitcoin and blotchy technology have been lost son on many of the new entrants and and so it takes time to get to the point where we're all winding I think different blockchains and different applications of this technology will have different kind of approaches to how people think about investors always gonna be pragma because this is a massively growing industry that touches upon every kind of business and governmental and non-governmental it's actually fragmentation is a relative chairman is Genevieve you I saw you and you guys are working with things from cannabis coin I think you had to cannabis cabin this week in New Yorker yeah we're doing that tomorrow night actually so crypto and cannabis are two the hottest millennial sectors right and so we kind of like to say Agri capital we like to dance on the edge of chaos I actually found out about a cannabis company in Vancouver so just outside Vancouver that is using a crypto mining operation and all the excess heat that is coming off that to power a grow-op so we're literally at the intersection of crypto and cannabis not just for our handling money but handling energy in a different way which is so fast that's real mission impact investing right there you know using energy to grow weed that's the Seidel impact isn't it good bad I mean even as you look at it you know better cannabis healthy cannabis is a mission people look care about we're helping people's wallets and we're helping people's minds right in like ways that the government banks and pharmaceutical companies are fighting against so you know if you can't beat them join them so I welcome Astra Zeneca and the Bank of Canada to come on board our mission this is specially turning into a cube after dark episode Jeremy I gotta get your thoughts on these industries because look at cannabis we joke about it but that's an example of another market this zilean markets that are coming online that are gonna be impacted so fragmentation is a relative terms but hey look at it I mean energy tech is infrastructure tech and solid that's what I'm concerned about who nails the infrastructure for network effects and what's the instrumentation for that that's the number one question that is essential question for the protocols whether it's Theory amore Bitcoin oreos Definity so forth the protocol that provides the strongest and and most adaptable and infrastructure and foundational technology is going to be one of the main ones are those will be the main winners and so the names I mentioned they're up there they're very competitive but it's anybody's game right now I think any blockchain can come along right now and be the winner a decade from now and for entrepreneurs represents a challenge because you have to figure out what blocks came to go build on this is why I am big on investing in interoperable Ledger's technologies that enable the kind of transfer smart contracts and crypto assets between blockchains it's a great great segue let's just get an update since we last talked what are you working on what are you investing in what's new in your world share the update on strangers so now my fund is officially launched where how much we launched with just over 15 million dollars and amazingly we launched at the perfect time we're already up 55% and we got making an investment for a venture fund we actually did the exact WA T investment which transferred over from my personal investment portfolio but doing great I have really run the gamut in terms of investments we're making on the equity side of things and in crypto assets but what we're seeing is really accomplished entrepreneurs coming to this space continue actually more optimism than I had felt at polygon poly car and I was like this market needs to correct in a real way today I think that Corrections been prolonged if we were gonna feel a lot of pain it was gonna be two months ago but instead I think it's gonna be one to three years before the market goes through the correction that we need to see for the real shakeout to happen because so many of these teams that I think are garbage have so much money yeah and they're just floating around they got has worked their way out it's just like a bad burrito at some point it's got a pass Genevieve what are you working on I'll see you've got grit capital what's the update on your end what's new yeah amazing actually literally tonight probably about 60 minutes ago my business partner and I signed one of the fastest-growing exchanges in Canada called Einstein exchanges of quiet so these guys have only ever raised like one and a half million u.s. and they're the biggest exchange in Canada by sign ups active accounts so they're probably doing like almost a hundred million in top-line transaction volumes and they're probably never going public somebody's probably gonna buy them but we're gonna be marketing them across the country getting customers I mean the tagline is it doesn't take I'm Stein to open an account it shouldn't take n Stein it by Bitcoin you can literally get this account set up in under 60 seconds so they're vampires ease-of-use surety reducing the steps it takes to do it and get it up and running fast absolutely like my dad could do it and like alright so we say now follow you on Instagram and Facebook which is phenomenal by the way I got a great lifestyle what's the coolest thing you've done since we last talked to Polycom Wow polycon was kind of a high really peaked and then everyone got sick like our team got said polymath untraceable cuz everybody just got the flu yeah we were like on adrenaline and we kept going ah what's the coolest thing that we've done since then I think it's signing up like cool companies like Einstein we also signed a big cannabis company in Colombia called Chiron they're about to go public I don't know Cole what do you think I don't know maybe what's the coolest thing you've done travel what's your good so last night Jeremy and I just met we're together on a blockchain Research Institute project that Sonova Financial is backing and meeting him so you guys working together on a special project right now how's that going what's that about JCO which is a new sort of financial services firm they're creating what it could effectively be understood as a compliant coin offering that is available to more than just accredited investors and that's they're making ico something that falls within the pre-existing regulatory framework and also accessible to your average Joe which I think it's really important if we're going to follow the initial vision for both blockchain technology and offerings all right final question I know you guys want to get back to your dancing and schmoozing networking doing big deals having fun what is blockchain New York we call about we could pop chain we here in New York what the hell's happening there's been a lot of events what's your guy's assessment of you observed and saw anything can you share for the people who didn't make it to New York or not online reading all the action what's happened so as someone that did not attend consensus spoke at three other events or speaking at three other events I can say with certainty that the New York box chain week has been about bringing together virtually everyone in the industry to connect and kind of catch up with one another which is really important we we don't have that many events Miami was too short the industry's gotten too big but having a full week of activities in New York City has enabled me to kind of foster relationships are oh I yeah man get a lot of work John well I've gotten so much work done I haven't had to actually be a date conferences to reconnect with just about everyone that I want to industry that's really special Genevieve what is your observation what have you observed share some in anecdote some insight on what happened this week I know fluid he started I saw Bilt's I was just chatting with him about it it was started in over the weekend it's gone up and we're now into Thursday tomorrow coming up well I don't think it's a coincidence that Goldman Sachs came out today and said that they were launching some sort of digital currency marketing yeah exactly using the power of the 10,000 people i consensus but yeah i know i agree with what jeremy says it's not really about being at consensus it's about what happens like behind closed doors it's all these decentralized parties that are happening yeah open doors but like it's you know like we hosted a core capital asset we had a hundred people in a suite at the dream hotel and it was just like you put the biggest CEOs of the mining companies in the world together and like put those with investors in a room it's like you know 100 people and that's where the deals happen it's not like in the big you know huge auditorium where like nobody looks at each other and everyone's on their phone well I gotta tell you how do we know we the Entrepreneurship side is booming so I totally love the entrepreneurial side check check check access to capital new kinds of business model stuff economics so we reported on all that to me the big story is Wall Street in New York City has been kind of stuck the products kind of like our old is antiquated like the financial products and like that's why Goldman's coming out they got nothing what they don't have anything what are they got so you see in a stagnant they got a traditional product approximately nothing really like new fresh so you got in comes crypto just do a crypto washer so I think I see the New York crowd going this is something that is exciting and we could product ties potentially so I don't think they know yet what that is but I think some of the things that are going on you guys I like I like so I my dad's always the kind of barometer to this whole thing and he's like when are they gonna come out with like a Salesforce stock column for the blockchain right like some sort of application that it doesn't matter if you're like illegal if you're like in investment banking like some sort of pervasive application that just goes wild you have that yet what is that happening Jeremy Jeremy did the date was it's the Netscape moment if you will the moment that blotching technology becomes tangible and now and in retrospect a few years out we may decide that's great for all the young browsers is a browser the original browse for the Internet that was that moment may have already happened we don't really know it maybe it been something like a theory a more augered you know something where there's a use case but people haven't wrapped their heads around it yet but if that hasn't happened yet it's coming it's where we're on the cusp of it because people know what bitcoin is they've heard of the blockchain it is part of the zeitgeist now and and that cultural relevance it's so important for having that Netscape moment Jeremy Jeremy thanks so much to spend the time here on the ground on the water for our special cube coverage of blockchain week new york city consensus you had all kinds of different events you had the crypto house where we were at tons of fluidity conference all this stuff going on good to see you guys you look great thanks for sharing the update here and the cube special coverage I'm John Faria thanks for watching Thanks
SUMMARY :
like in the big you know huge auditorium
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Jeremy | PERSON | 0.99+ |
Canada | LOCATION | 0.99+ |
Vancouver | LOCATION | 0.99+ |
Colombia | LOCATION | 0.99+ |
Bank of Canada | ORGANIZATION | 0.99+ |
Goldman Sachs | ORGANIZATION | 0.99+ |
Sonova Financial | ORGANIZATION | 0.99+ |
Puerto Rico | LOCATION | 0.99+ |
New York | LOCATION | 0.99+ |
100 percent | QUANTITY | 0.99+ |
Jeromy Gartner | PERSON | 0.99+ |
Jeremy Gardner | PERSON | 0.99+ |
New York | LOCATION | 0.99+ |
John Faria | PERSON | 0.99+ |
Elon Musk | PERSON | 0.99+ |
jeremy | PERSON | 0.99+ |
New York City | LOCATION | 0.99+ |
JCO | ORGANIZATION | 0.99+ |
100 people | QUANTITY | 0.99+ |
Chiron | ORGANIZATION | 0.99+ |
Astra Zeneca | ORGANIZATION | 0.99+ |
New Yorker | LOCATION | 0.99+ |
New York City | LOCATION | 0.99+ |
Jeremy Jeremy | PERSON | 0.99+ |
10,000 people | QUANTITY | 0.99+ |
three other events | QUANTITY | 0.99+ |
Genevieve | PERSON | 0.99+ |
Carly Jeremy | PERSON | 0.99+ |
today | DATE | 0.99+ |
10,000 people | QUANTITY | 0.99+ |
Miami | LOCATION | 0.99+ |
tomorrow night | DATE | 0.98+ |
two months ago | DATE | 0.98+ |
10,000 people | QUANTITY | 0.98+ |
over 15 million dollars | QUANTITY | 0.98+ |
three other events | QUANTITY | 0.98+ |
John | PERSON | 0.98+ |
55% | QUANTITY | 0.98+ |
two | QUANTITY | 0.98+ |
Einstein | ORGANIZATION | 0.98+ |
Joe | PERSON | 0.98+ |
Jeremy Jeremy | PERSON | 0.98+ |
under 60 seconds | QUANTITY | 0.98+ |
about 60 minutes ago | DATE | 0.98+ |
this week | DATE | 0.98+ |
one and a half million | QUANTITY | 0.97+ |
one | QUANTITY | 0.97+ |
two super yachts | QUANTITY | 0.97+ |
Genevieve Dec Monroe | PERSON | 0.97+ |
five more boat parties | QUANTITY | 0.97+ |
tonight | DATE | 0.97+ |
both | QUANTITY | 0.97+ |
this week | DATE | 0.96+ |
Goldman | ORGANIZATION | 0.96+ |
Prague | LOCATION | 0.95+ |
Genevieve Roch Decter | PERSON | 0.95+ |
blockchain Research Institute | ORGANIZATION | 0.95+ |
first boat party | QUANTITY | 0.95+ |
polycon 2018 | EVENT | 0.94+ |
John furry | PERSON | 0.94+ |
Netscape | TITLE | 0.94+ |
Polycom | ORGANIZATION | 0.94+ |
u.s. | LOCATION | 0.93+ |
Blockchain Week | EVENT | 0.93+ |
new york | LOCATION | 0.93+ |
this week | DATE | 0.92+ |
NYC | LOCATION | 0.92+ |
almost a hundred million | QUANTITY | 0.91+ |
Thursday tomorrow | DATE | 0.91+ |
New York City D central | LOCATION | 0.9+ |
Hilton | LOCATION | 0.9+ |
midtown Manhattan | LOCATION | 0.89+ |
Cole | PERSON | 0.89+ |
one pocket | QUANTITY | 0.89+ |
lot of people | QUANTITY | 0.87+ |
ORGANIZATION | 0.86+ | |
lot of events | QUANTITY | 0.78+ |
ORGANIZATION | 0.78+ | |
three years | QUANTITY | 0.75+ |
last night | DATE | 0.74+ |
2018 | DATE | 0.74+ |
Salesforce | ORGANIZATION | 0.73+ |
Al Burgio, DigitalBits.io & Nithin Eapen, Arcadia Crypto Ventures | Blockchain Week NYC 2018
(techno music) >> Announcer: Live, from New York, it's theCUBE. Covering Blockchain Week. Now, here's John Furrier. (techno music) >> Hello and welcome back. this is the exclusive coverage from theCUBE. I'm John Furrier, the co-host. We're here in New York City for special on the ground coverage. We go out where all the action is. It's happening here in New York City for Blockchain Week, New York, #BlockchainWeekNY Of course, Consensus 2018 and a variety of other events, happening all over the place. We got D-Central having a big boat event here, tons of events from Hollywood. We got New York money, we got Hollywood money, we got nerd money, it's money everywhere, and of course great deals are happening, and I'm here with two friends who have done a deal. Al Burgio is a CEO of DigitalBits co-founder, and Nithin who's the partner at Arcadia Crypto Ventures. You guys we've, you know, we're like family now, and you're hiding secrets from me. You did a deal. Al, what's going on here? Some news. >> Yeah, well first John, thanks for having us. We always love coming on the show, and really enjoy spending time with you and so forth. We, you know previous conversations that we've had, we were not out there fundraising. But really had the opportunity to meet a lot of great people Nithin and his firm being definitely one of them. And as a result of that, really building this, say, following, these relationships within the venture community, more specifically the crypto venture community. When we were ready to actually go out and do, let's say a first round, for us it happened very quickly, and it was a result of being able to leverage those relationships that we had. For me, it was kind of remarkable to see that support come and happen so quickly. Normally venture, it's just a process. Many many months. >> John: Long road. >> Then a month to close. >> John: Kiss all the frogs. >> Yeah, here it's like, you know, people can do due diligence on the fly, You have an opportunity with events like this. >> John: They're smart. >> They're smart, and and there's an opportunity to really foster these relationships in this really tight-knit community. And, you know, Nithin and his firm being obviously one of those. And so when we were ready to go out and do our first round, it happened quickly, and I'd like to think that in a lot of ways, it happened amongst friends. >> Well, you're being humble. We've been covering you, you've been on theCUBE earlier, when you just started the idea, so it's fun to watch you have this idea come to fruition, but you're in a, you're hitting a TAM a Total Available Market that's pretty large. And that's one of the secrets, to have a TAM. Aggressive bold move, we'll how it turns out for you, but you know, you got to have the moonshot, you're going after the loyalty market, which is completely run by the syndicate, what do you want to call it, the mafia of loyalty. >> Yeah, well, I would say that in some cases, those that are supporting us see that as really just one use case. Because we built this general-purpose blockchain, one of the use cases and one of the first use cases that were out there to support, happens to be the loyalty space. >> John: Big. And it's massive, highly fragmented but massive market, and we can solve a lot of liquidity issues with our technology. But then it goes beyond that. So it's a big market at the start, and then that can scale even greater from there. and I think that's part of what, I mean obviously, I'm not going to speak for Nithin. >> Nithin, let me weigh in here, pass the mic over. Nithin talk about the deal, why these guys? I know you met 'em, you like Al, and the feedback I've heard from other folks is he's a classic entrepreneur and that obviously, the entrepreneur gets the deal, but obviously you don't just give money 'cause you like someone. What about this deal is it that you guys like? You guys been there early, you got some great people on your team, what about this deal is it that you like? >> Sure, for us, Al met pretty much most of, almost all the criteria that we had, okay. That we had when we go, the thesis before we go fund someone. We don't get so many deals like that. Usually we get you know, they made 50% of the criteria, we might still put money because you can't get the 100%. So one thing, Al as a founder, he's experienced, he has done it multiple times before, he sold companies. Tech guy, which is very key for us. A tech project is very key. Okay, second thing, he's built the whole thing. It's not like he's raising the money to go and build it. He built it, now he's raising money to go for go to market strategies, which makes sense. He's shown it, and we tested it out. So like, we were completely blown away. He has a team behind 'im. He's built a team on every side, on the marketing side, on PR, events. And the idea, this is a general blockchain, but he's addressing a very specific issue. It is a real problem. Loyalty points, or rewards points, or gift points. Or whatever you call them. It is segmented, it's fragmented, and this is a chance. And there might be many people who are trying to solve this problem, but I think Al has the greatest possibility, or probability, of becoming the winner. >> You and I have talked on theCUBE before, both of you guys are CUBE alumni, I know you both, so I'll ask you, 'cause I'll just remind everyone, we've talked about token economics. One of the things that's coming up here at the Consensus 2018 event in New York, onstage certainly, and some fireworks in one of the sessions, is like if you're not decentralized, why the hell are you doing a decentralized model? So one of the criterias is, the fit for the business model, has to fit the notion of a decentralized world, with the ability of tokens becoming an integral part. What about this deal makes that happen? Obviously, fragmentation, is that still decentralized? So, how are you sorting through the nuances of saying, okay, is it decentralized the market for him, and this deal? Or does it fit? >> See no, decentralize is one thing okay, in here, more than decentralized, I would say there was the platform, so that all the companies can come in, use this common platform, release it, and as a user you're getting a chance to atomically swap it if you don't like something. Most of the reward points or loyalty points go waste. Maybe the companies want it to go waste, I don't know if that is. >> It's a natural burn at equilibrium going on anyway right? Perfect fit! >> So that is the only, that was the only doubt that we had. Would companies want this, because do they want their customers' loyalty points going waste rather than swapping it for something else? That was the only question that we had. Well, that's a question that will get answered in the market. But otherwise we hadn't seen something like this before. >> What's your take of the show so far? We saw each other in the hallway as we were getting set up for theCUBE, for two days of coverage, in New York, for Blockchain Week, New York, what's your take? Obviously pretty packed. >> Oh my god, it's so packed, and it's great, the show is going on. It is bringing a lot of money in, it's bringing all the investors in a new money, old money, traditional money, nerd money as you said. >> It smells like money! >> Everybody's coming in. See the beauty about those things coming in is, you're going to get a lot of people from other fields that are going to come into this field to solve problems. 'Cause earlier, if there is no money coming in, you're going to have very smart people, or very intelligent people stick with physics or whichever was their field. Now, they're going to look into the space because they're getting paid. See that brings more people who are intelligent, and who can solve problems. That is very key for me. >> Al, I want to ask you as an entrepreneur, one things you usually have to struggle with, as any entrepreneur, is navigating the 3-D chess you got to play, whether it's competitive strategy, market movement, certainly the market's moving and shifting very quickly, but you've got growth, big tailwind for you. What's your takeaway? Because now you have new things coming on. Every every day it seems like a new shoe is dropping. SEC's firing a warning on utility tokens, security tokens are still coming, are now coming online, but that looks very promising, and then ecosystems become super important. You guys just announced news this morning around the ecosystem. >> Yeah, tomorrow we have some. We had some news today, but we have more tomorrow. >> John: Well talk about the news. >> Yeah, so we have a multi-tiered go to market strategy. Obviously in the loyalty space, again I want to emphasize, it's just one use case, but it's a massive one. You have brands, the enterprise. And many of those those enterprises or brands may operate their loyalty program internally, in terms of like back offices systems, in some cases they're outsourcing the app to a SAS provider, some application provider, that's kind of hidden in the background. But let's just say like Hilton. I use Hilton, it's the location for the event, but Hilton, you have this user experience using this app, but maybe that technology, the SAS application that's powering that, is actually not Hilton technology. And so let's just say, there's 30 million people in the Hilton program and there may be 30 million of them on the Marriott, coexisting on some SAS application. And so that's another important category for us. SAS providers and so forth, supporting that industry. And then last but not least, today, whether enterprise or SAS company, many cases not touching their own hardware, right? They're using the cloud. >> So they're outsourcing the backend. >> Yeah, and so you have managed cloud providers. >> So what does it mean for the market? I don't understand, I'm not following you. >> Well, I guess what I'm saying is that there needs to be a common standard, across enterprise application provider, in global cloud community, cloud is the new hardware. >> True. So horizontally scaling loyalties as we were (mumbles). >> Exactly, so we have, we're basically securing partnerships on all three levels, to make sure that, if you want to use new technology, you want to ensure that it's widely supported, across a variety of partners you may want to work with if you're an enterprise. Whether, a software company, cloud company, and so forth. You want to be able to ensure that it can back up the truck. So we've basically signed partnerships at all of these tiers. You're going to see news in the morning. It's late here on a Monday evening. So tomorrow 9:00 a.m, major cloud company, one of the major cloud companies, and there's more to follow, making an announcement that they've joined our ecosystem partner program, and supporting this open source technology in a number of different ways. Which we're really excited about. >> You see ecosystem as a strategic move for you. >> Absolutely, this is, for us, this is, it's all about helping the consumer, but it's not about one consumer at a time for us. It's very much an enterprise play. It's one enterprise at a time. And with each enterprise we basically add to the ecosystem millions if not tens of millions of consumers instantly. >> Nithin I want to ask you a question, because what he just brought up is interesting to me as well. As a new thing, it's not new, but it's new to the crypto world, new to the analog world, that's not in the tech field. Tech business, we all know about global system integrators, we know about ecosystems, we know the value of developer programs, and community, all those things, check, check, check. But now those things are coming to new markets. People have never seen an ecosystem play before. So it's kind of, not new, it's new for some people, it's a competitive advantage opportunity. >> True, it is. See the whole thing is so new, that you can't even define it at this point. It's very hard to define. It's like, see, as an example I would say, none of us thought that when the iPhone came, there would be a 60 billion dollar taxi sharing economy that comes out of it, right? Same thing. Blockchain comes, we just don't know. And it's very hard to predict. >> New brands are going to emerge, I mean if you look at every major inflection point, I point to a couple that I think are relevant, TCP/IP was created, internetworking. >> Yep. >> That essentially went after proprietary networks, like IBM, Digital, Stacks, but it didn't replace, it wasn't a new functionality, it was interoperability. >> Yes. >> The web, HTTP, created a whole new functionality. >> Yep. >> Out of that emerged new brands. >> Yeah. >> So I think this wave's coming is a, new brands are going to emerge. >> Here, what's the brand, I don't know what's going to emerge. There it was interoperability. >> John: Well, new players. >> It's here, it's more, the collaboration. The collaboration is so huge, it's the scale is so huge, in the sense you can collaborate across the world. You're cutting those borders, there are no borders that can hold you. Even though interoperability happened in internet, There were the Googles, and the Facebook, that still had those borders. >> Well, don't put it, Cisco came out of that, 3Com, and those generations, but the hyper-scalers came out of the web. >> Yep. >> So I'm saying, well I'm saying, I want to get your reaction to, is I think that is such a small scale relative to blockchain and crypto because it's global, it's every industry, it's not just tech it's just like everything. So there's got to be new brands. Startups going to come out of the woodwork, that's my point. >> It's not yet time for the brands to come in. See that's the whole thing. So let's put it this way, the internet was there from 1978, if you really look at it, ARPANET or DARPA, those things were there. Email was there, but it was by 1997, or by the time we all came to know Google it was 2001. There is that gap between the brand forming, because it has to permeate first, more people have to use it, like what is the user-- >> Everything was was a bubble, but everything happened. I got food delivered to my house today, right? It happened, people were saying that's a crazy idea. >> It's now it's going on, right. So it's the timing and they know the time for it to permeate so here, how many people are using Bitcoin, and to do what? Most of them are just speculating right? There's very few real use case of remittance or speculative trading, that's what's happening. See that's what I said. The other use cases, it has to permeate. And that comes with more user adoption. And the user adoption initially is going to come from the speculation. >> I think it's a good sign, honestly I think it's a tell sign, because I remember when the web was new, I was in coming out right and growing in the industry. People were poo poo, oh that's just for kids. The big company's said, we wouldn't, who the hell is going to use the World Wide Web? Enter the search engines. >> I remember that like it was yesterday. I forget that I'm not a kid anymore, and I had the opportunity to be an entrepreneur during that era. One of the things I want to add is that, we had, I think what Nithin is really pointing out, it started with the infrastructure, you had network engineers and ISPs, you know, and email. But what was the enterprise application here? What was that consumer application, and that followed right? So it started infrastructure, then it evolved. Once we saw these applications, enterprises started to go crazy. Whether it was the Ubers of the world surfacing, or enterprises reinventing themselves, that's kind of the next wave. >> Well, this is why I think you're a good opportunity. 'Cause I remember licking stamps and sending out envelopes to get people to come to a seminar, held at a hotel. That's how you did it in the old world. The web replaced that with direct response. >> But there's some, there's something else-- >> The mainframe ran faster than the web. You're replacing an old loyalty, that's like licking the stamps. It's not about comparing what you're doing to something else. >> There's also something that helps, that we're not acknowledging, that really helped take internet from 1.0 to 2.0, it's Linux. You know I remember websites were insanely expensive. It was Windows servers, it was Sun Solaris, all of this crazy, expensive, server systems, that you needed to have, so the barrier of entry was extremely high. Then Linux came along, and you still needed to have your own data center space, and so still high, but the licensing fees kind of went away. >> And now with containers and Kubernetes-- >> Exactly. >> I made a bet I was going to get Kubernetes in a crypto show. >> Anybody from a bedroom could start a company, right? You could do it with your pajamas still on. >> John: Well orchestration's easier. >> Absolutely. So this has started, this really, revolution. Now you have blockchain and you start to introduce enterprise-grade blockchain technologies, it's the next wave, you know, it's not VoIP, it's value over IP. >> Okay, I'm going to ask both you guys a final question, to end this segment here at the block event. I know you guys want to get back, and I'm taking you anyway from the schmoozing and networking and the fun out there, deejay. Predictions, next year this time, what are we going to be? What's the we're going to look like? What's going to evolve? I mean we had a conversation with Richard, who partnered with you guys at Arcadia Crypto Partners, saying the trading things interesting, the liquidity has changed. What's your take? I want you guys both to take a minute to make a prediction. Next year, what's different, who's out, who's in, what's happening, is it growing? >> So I, you know, I would say this, surprisingly, CTOs, I love CTOs, but many CTOs, I would say that well above 50% of CTOs, still can't spell blockchain. Really, and what I mean by that, really understand the transformational power what this is, in terms of how this is really web 3.0. This is going to change so many industries, create so much value for consumers, help businesses and so forth, and we're going to cross that 50% mark. >> Next year. >> With CTOs-- >> 50% of what? Be clear on-- >> Basically, we're going, in terms of the net, that blockchain's going to capture, and really enterprises and not just enterprises, service providers and so forth-- >> 50% of the mind share or 50% of the projects? >> Yeah no, I'm talking it's, people aren't going to be saying, oh, blockchain, isn't that Bitcoin? They're going to really understand, and they're going to understand that impact. And over the course of the next 12 months, we're going to see that. And it starts, obviously in many cases, with the CIO, CTO of many companies. There are definitely a lot of CIOs and CTOs on the forefront of innovation that get it, but what I'm saying is that more than 50% don't. >> So you're saying-- They're very busy in doing what they're doing today, and it hasn't hit them yet. >> To recap, you're saying by next year, 50% of CTOs or CTO equivalents, will have a clear understanding of what blockchain is-- >> Absolutely. >> And what it can do. >> Absolutely. >> Nithin, your prediction, next year, this time, what's different, what's new, what's the prediction? >> So, one of the key things that I think is going to happen is there's going to be a lot more training, and knowledge that's going to spread out, so that a lot more people understand, what blockchain is and what bitcoin is. Even now, as Al said, he was telling about CTOs, if the CTOs are, that's the state, that they can't spell blockchain, imagine where the real common man is. You've got people like Jamie Dimon coming on TV and saying he doesn't like Bitcoin, but he likes blockchain. I'm like, what the heck is he saying? That he likes a database? >> He was selling it short 100% (chuckles) >> Yeah, he likes a database. And then you have Warren Buffett coming over there-- >> Rat poison. >> And then this is rat poison. And like my question is, does any of his funds buy gold? Do they buy gold? He was telling that this is only worth as much as the next buy buying at a higher price. >> What's Warren Buffett's best tech investment? >> I don't know, I think he bought Apple, he started buying Apple now, right? When it's reached a thousand bucks? Or it reached a trillion dollars or close to that, or 750 billion? >> The Apple buy was 2006. If you were there, then you were good. >> Yeah, but-- >> So, your prediction? >> Market wise I don't know, what's going to happen? I'm expecting this, the crypto, the utility token, or the crypto market, to be at least a six trillion dollar business. But it'll happen next year? Definitely not. But I've been proven wrong, like I was expecting it to happen by 2025, but then it went to 750 billion by December. Well, it's not too far. >> You did get the prediction right, in the Bahamas at POLYCON18, about the drop around the tax consequences of the-- >> Right. >> People slinging trades around, not knowing the tax consequences. >> Right, right. We don't know because, who knows? Because what is going on over there, is IRS is still saying it's a property. That's what the last (slurs) is. SEC is saying it is all equity, and the CFTC was saying it's commodity. So what tax do I pay? >> Okay, lightning round question, 'cause I want to, one more popped in my head. The global landscape, from an investor standpoint, the US, we know what's going on in the US, accredited, SEC is throwing, firing across, bullets across the bow of the boats, kind of holding people in line. What percentage of US big investors will be overseas by next year? >> Percentage of-- >> Having, meaning having deals being done, proxy deals being down outside the US, what percentage? >> It's still going to be low though. That is going to be low, because that, I don't think the US investor, means the large scale of those investors-- >> You don't think the big funds will co-locate outside the US? >> There will be some, but not enough. >> Put a number, a percentage. >> Percentage-wise I think it's still going to be less than 10%. >> Al, your prediction? >> In terms of investment? >> Investment, investors saying hey, I got money here, I want to put it out there. >> Outside of the United States? >> Share money, not move their whole fund, but do deals from a vehicle. >> Do deals outside. I think I agree with Nithin. >> Throwing darts at the board here. >> No, I'm going to clarify. There's definitely massive investment happening overseas. In some respects probably bigger than the United States. So that's not going away. If anything that's going to grow. But your question is, in terms of US entities, making abroad investments, overseas investments, versus just domestic? I think that trend doesn't necessarily change. You have the venture community, there are certain bigger venture funds that can have global operations 'cause at the end of the day, they need to have global operations, to be able to do that, and most venture funds aren't that massive, they don't have that infrastructure. So they're going to focus on their own backyard. So I don't necessarily think blockchain changes the venture mindset. It's just easier for them logistically to do due diligence on their own backyard and invest in those. >> Guys, always a pleasure. Great to see you. You guys are like friends with entourage here, great to get the update here at Blockchain Week. We get to Silicon Valley week, we'll connect up again. I'm John Furrier, here in New York, theCUBE's continuing coverage of crypto, decentralized applications, and blockchain of course, we're all over it. You'll see us all over, all of the web, all the shows. Thanks for watching. (techno music)
SUMMARY :
Announcer: Live, from New York, it's theCUBE. I'm John Furrier, the co-host. But really had the opportunity to meet a lot of great people people can do due diligence on the fly, it happened quickly, and I'd like to think And that's one of the secrets, to have a TAM. one of the use cases and one of the first use cases So it's a big market at the start, and the feedback I've heard from other folks is It's not like he's raising the money to go and build it. So one of the criterias is, the fit for the business model, so that all the companies can come in, So that is the only, that was the only doubt that we had. We saw each other in the hallway and it's great, the show is going on. See the beauty about those things coming in is, is navigating the 3-D chess you got to play, We had some news today, but we have more tomorrow. Obviously in the loyalty space, again I want to emphasize, So what does it mean for the market? is that there needs to be a common standard, So horizontally scaling loyalties as we were (mumbles). and there's more to follow, it's all about helping the consumer, but it's new to the crypto world, See the whole thing is so new, I point to a couple that I think are relevant, it wasn't a new functionality, it was interoperability. new brands are going to emerge. There it was interoperability. in the sense you can collaborate across the world. but the hyper-scalers came out of the web. So there's got to be new brands. There is that gap between the brand forming, I got food delivered to my house today, right? So it's the timing and they know the time for it to permeate Enter the search engines. One of the things I want to add is that, we had, to get people to come to a seminar, held at a hotel. that's like licking the stamps. and so still high, but the licensing fees kind of went away. You could do it with your pajamas still on. it's the next wave, you know, Okay, I'm going to ask both you guys a final question, This is going to change so many industries, And over the course of the next 12 months, and it hasn't hit them yet. So, one of the key things that I think is going to happen And then you have Warren Buffett coming over there-- as much as the next buy buying at a higher price. If you were there, then you were good. or the crypto market, to be at least not knowing the tax consequences. and the CFTC was saying it's commodity. the US, we know what's going on in the US, That is going to be low, because that, I want to put it out there. but do deals from a vehicle. I think I agree with Nithin. You have the venture community, We get to Silicon Valley week, we'll connect up again.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Richard | PERSON | 0.99+ |
Nithin | PERSON | 0.99+ |
Cisco | ORGANIZATION | 0.99+ |
John | PERSON | 0.99+ |
2001 | DATE | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Al | PERSON | 0.99+ |
Warren Buffett | PERSON | 0.99+ |
Al Burgio | PERSON | 0.99+ |
John Furrier | PERSON | 0.99+ |
SEC | ORGANIZATION | 0.99+ |
Arcadia Crypto Ventures | ORGANIZATION | 0.99+ |
1997 | DATE | 0.99+ |
New York | LOCATION | 0.99+ |
1978 | DATE | 0.99+ |
two days | QUANTITY | 0.99+ |
IRS | ORGANIZATION | 0.99+ |
50% | QUANTITY | 0.99+ |
Bahamas | LOCATION | 0.99+ |
Hilton | ORGANIZATION | 0.99+ |
Apple | ORGANIZATION | 0.99+ |
next year | DATE | 0.99+ |
New York City | LOCATION | 0.99+ |
100% | QUANTITY | 0.99+ |
Jamie Dimon | PERSON | 0.99+ |
750 billion | QUANTITY | 0.99+ |
30 million | QUANTITY | 0.99+ |
tomorrow | DATE | 0.99+ |
two friends | QUANTITY | 0.99+ |
2006 | DATE | 0.99+ |
Next year | DATE | 0.99+ |
Marriott | ORGANIZATION | 0.99+ |
Linux | TITLE | 0.99+ |
Arcadia Crypto Partners | ORGANIZATION | 0.99+ |
ORGANIZATION | 0.99+ | |
United States | LOCATION | 0.99+ |
December | DATE | 0.99+ |
tomorrow 9:00 a.m | DATE | 0.99+ |
both | QUANTITY | 0.99+ |
US | LOCATION | 0.99+ |
Nithin Eapen | PERSON | 0.99+ |
DigitalBits | ORGANIZATION | 0.99+ |
today | DATE | 0.99+ |
first round | QUANTITY | 0.99+ |
one | QUANTITY | 0.99+ |
2025 | DATE | 0.99+ |
Monday evening | DATE | 0.99+ |
ORGANIZATION | 0.99+ | |
more than 50% | QUANTITY | 0.99+ |
yesterday | DATE | 0.99+ |
less than 10% | QUANTITY | 0.99+ |
iPhone | COMMERCIAL_ITEM | 0.99+ |
DigitalBits.io | ORGANIZATION | 0.98+ |
60 billion dollar | QUANTITY | 0.98+ |
30 million people | QUANTITY | 0.98+ |
Blockchain Week | EVENT | 0.98+ |
first | QUANTITY | 0.98+ |
Daniel Hernandez, Analytics Offering Management | IBM Data Science For All
>> Announcer: Live from New York City, it's theCUBE. Covering IBM Data Science For All. Brought to you by IBM. >> Welcome to the big apple, John Walls and Dave Vellante here on theCUBE we are live at IBM's Data Science For All. Going to be here throughout the day with a big panel discussion wrapping up our day. So be sure to stick around all day long on theCUBe for that. Dave always good to be here in New York is it not? >> Well you know it's been kind of the data science weeks, months, last week we're in Boston at an event with the chief data officer conference. All the Boston Datarati were there, bring it all down to New York City getting hardcore really with data science so it's from chief data officer to the hardcore data scientists. >> The CDO, hot term right now. Daniel Hernandez now joins as our first guest here at Data Science For All. Who's a VP of IBM Analytics, good to see you. David thanks for being with us. >> Pleasure. >> Alright well give us first off your take, let's just step back high level here. Data science it's certainly been evolving for decades if you will. First off how do you define it today? And then just from the IBM side of the fence, how do you see it in terms of how businesses should be integrating this into their mindset. >> So the way I describe data science simply to my clients is it's using the scientific method to answer questions or deliver insights. It's kind of that simple. Or answering questions quantitatively. So it's a methodology, it's a discipline, it's not necessarily tools. So that's kind of the way I approach describing what it is. >> Okay and then from the IBM side of the fence, in terms of how wide of a net are you casting these days I assume it's as big as you can get your arms out. >> So when you think about any particular problem that's a data science problem, you need certain capabilities. We happen to deliver those capabilities. You need the ability to collect, store, manage, any and all data. You need the ability to organize that data so you can discover it and protect it. You got to be able to analyze it. Automate the mundane, explain the past, predict the future. Those are the capabilities you need to do data science. We deliver a portfolio of it. Including on the analyze part of our portfolio, our data science tools that we would declare as such. >> So data science for all is very aspirational, and when you guys made the announcement of the Watson data platform last fall, one of the things that you focused on was collaboration between data scientists, data engineers, quality engineers, application development, the whole sort of chain. And you made the point that most of the time that data scientists spend is on wrangling data. You're trying to attack that problem, and you're trying to break down the stovepipes between those roles that I just mentioned. All that has to happen before you can actually have data science for all. I mean that's just data science for all hardcore data people. Where are we in terms of sort of the progress that your clients have made in that regard? >> So you know, I would say there's two majors vectors of progress we've made. So if you want data science for all you need to be able to address people that know how to code and people that don't know how to code. So if you consider kind the history of IBM in the data science space especially in SPSS, which has been around for decades. We're mastering and solving data science problems for non-coders. The data science experience really started with embracing coders. Developers that grew up in open source, that lived and learned Jupiter or Python and were more comfortable there. And integration of these is kind of our focus. So that's one aspect. Serving the needs of people that know how to code and don't in the kind of data science role. And then for all means supporting an entire analytics life cycle from collecting the data you need in order to answer the question that you're trying to answer to organizing that information once you've collected so you can discover it inside of tools like our own data science experience and SPSS, and then of course the set of tools that around exploratory analytics. All integrated so that you can do that end to end life cycle. So where clients are, I think they're getting certainly much more sophisticated in understanding that. You know most people have approached data science as a tool problem, as a data prep problem. It's a life cycle problem. And that's kind of how we're thinking about it. We're thinking about it in terms of, alright if our job is answer questions, delivering insights through scientific methods, how do we decompose that problem to a set of things that people need to get the job done, serving the individuals that have to work together. >> And when you think about, go back to the days where it's sort of the data warehouse was king. Something we talked about in Boston last week, it used to be the data warehouse was king, now it's the process is much more important. But it was very few people had access to that data, you had the elapsed time of getting answers, and the inflexibility of the systems. Has that changed and to what degree has it changed? >> I think if you were to go ask anybody in business whether or not they have all the data they need to do their job, they would say no. Why? So we've invested in EDW's, we've invested in Hadoop. In part sometimes, the problem might be, I just don't have the data. Most of the time it is I have the data I just don't know where it is. So there's a pretty significant issue on data discoverability, and it's important that I might have data in my operational systems, I might have data inside my EDW, I don't have everything inside my EDW, I've standed up one or more data lakes, and to solve my problem like customer segmentation I have data everywhere, how do I find and bring it in? >> That seems like that should be a fundamental consideration, right? If you're going to gather this much more information, make it accessible to people. And if you don't, it's a big flaw, it's a big gap is it not? >> So yes, and I think part of the reason why is because governance professionals which I am, you know I spent quite a bit of time trying to solve governance related problems. We've been focusing pretty maniacally on kind of the compliance, and the regulatory and security related issues. Like how do we keep people from going to jail, how do we ensure regulatory compliance with things like e-discovery, and records for instance. And it just so happens the same discipline that you use, even though in some cases lighter weight implementations, are what you need in order to solve this data discovery problem. So the discourse around governance has been historically about compliance, about regulations, about cost takeout, not analytics. And so a lot of our time certainly in R&D is trying to solve that data discovery problem which is how do I discover data using semantics that I have, which as a regular user is not physical understandings of my data, and once I find it how am I assured that what I get is what I should get so that it's, I'm not subject to compliance related issues, but also making the company more vulnerable to data breach. >> Well so presumably part of that anyway involves automating classification at the point of creation or use, which is actually was a technical challenge for a number of years. Has that challenge been solved in your view? >> I think machine learning is, and in fact later on today I will be doing some demonstrations of technology which will show how we're making the application of machine learning easy, inside of everything we do we're applying machine learning techniques including to classification problems that help us solve the problem. So it could be we're automatically harvesting technical metadata. Are there business terms that could be automatically extracted that don't require some data steward to have to know and assert, right? Or can we automatically suggest and still have the steward for a case where I need a canonical data model, and so I just don't want the machine to tell me everything, but I want the machine to assist the data curation process. We are not just exploring the application of machine learning to solve that data classification problem, which historically was a manual one. We're embedding that into most of the stuff that we're doing. Often you won't even know that we're doing it behind the scenes. >> So that means that often times well the machine ideally are making the decisions as to who gets access to what, and is helping at least automate that governance, but there's a natural friction that occurs. And I wonder if you can talk about the balance sheet if you will between information as an asset, information as a liability. You know the more restrictions you put on that information the more it constricts you know a business user's ability. So how do you see that shaping up? >> I think it's often a people process problem, not necessarily a technology problem. I don't think as an industry we've figured it out. Certainly a lot of our clients haven't figured out that balance. I mean there are plenty of conversation I'll go into where I'll talk to a data science team in a same line of business as a governance team and what the data science team will tell us is I'm building my own data catalog because the stuff that the governance guys are doing doesn't help me. And the reason why it doesn't help me is because it's they're going through this top down data curation methodology and I've got a question, I need to go find the data that's relevant. I might not know what that is straight away. So the CDO function in a lot of organizations is helping bridge that. So you'll see governance responsibilities line up with the CDO with analytics. And I think that's gone a long way to bridge that gaps. But that conversation that I was just mentioning is not unique to one or two customers. Still a lot of customers are doing it. Often customers that either haven't started a CDO practice or are early days on it still. >> So about that, because this is being introduced to the workplace, a new concept right, fairly new CDOs. As opposed to CIO or CTO, you know you have these other. I mean how do you talk to your clients about trying to broaden their perspective on that and I guess emphasizing the need for them to consider putting somebody of a sole responsibility, or primary responsibility for their data. Instead of just putting it lumping it in somewhere else. >> So we happen to have one of the best CDO's inside of our group which is like a handy tool for me. So if I go into a client and it's purporting to be a data science problem and it turns out they have a data management issue around data discovery, and they haven't yet figured out how to install the process and people design to solve that particular issue one of the key things I'll do is I'll bring in our CDO and his delegates to have a conversation around them on what we're doing inside of IBM, what we're seeing in other customers to help institute that practice inside of, inside of their own organization. We have forums like the CDO event in Boston last week, which are designed to, you know it's not designed to be here's what IBM can do in technology, it's designed to say here's how the discipline impacts your business and here's some best practices you should apply. So if ultimately I enter into those conversations where I find that there's a need, I typically am like alright, I'm not going to, tools are part of the problem but not the only issue, let me bring someone in that can describe the people process related issues which you got to get right. In order for, in some cases to the tools that I deliver to matter. >> We had Seth Dobrin on last weekend in Boston, and Inderpal Bhandari as well, and he put forth this enterprise, sort of data blueprint if you will. CDO's are sort of-- >> Daniel: We're using that in IBM by the way. >> Well this is the thing, it's a really well thought out sort of structure that seems to be trickling down to the divisions. And so it's interesting to hear how you're applying Seth's expertise. I want to ask you about the Hortonworks relationship. You guys have made a big deal about that this summer. To me it was a no brainer. Really what was the point of IBM having a Hadoop distro, and Hortonworks gets this awesome distribution channel. IBM has always had an affinity for open source so that made sense there. What's behind that relationship and how's it going? >> It's going awesome. Perhaps what we didn't say and we probably should have focused on is the why customers care aspect. There are three main by an occasion use cases that customers are implementing where they are ready even before the relationship. They're asking IBM and Hortonworks to work together. And so we were coming to the table working together as partners before the deeper collaboration we started in June. The first one was bringing data science to Hadoop. So running data science models, doing data exploration where the data is. And if you were to actually rewind the clock on the IBM side and consider what we did with Hortonworks in full consideration of what we did prior, we brought the data science experience and machine learning to Z in February. The highest value transactional data was there. The next step was bring data science to where the, often for a lot of clients the second most valuable set of data which is Hadoop. So that was kind of part one. And then we've kind of continued that by bringing data science experience to the private cloud. So that's one use case. I got a lot data, I need to do data science, I want to do it in resident, I want to take advantage of the compute grid I've already laid down, and I want to take advantage of the performance benefits and the integrated security and governance benefits by having these things co-located. That's kind of play one. So we're bringing in data science experience and HDP and HDF, which are the Hortonworks distributions way closer together and optimized for each other. Another component of that is not all data is going to be in Hadoop as we were describing. Some of it's in an EDW and that data science job is going to require data outside of Hadoop, and so we brought big SQL. It was already supporting Hortonworks, we just optimized the stack, and so the combination of data science experience and big SQL allows you to data science against a broader surface area of data. That's kind of play one. Play two is I've got a EDW either for cost or agility reasons I want to augment it or some cases I might want to offload some data from it to Hadoop. And so the combination of Hortonworks plus big SQL and our data integration technologies are a perfect combination there and we have plenty of clients using that for kind of analytics offloading from EDW. And then the third piece that we're doing quite a bit of engineering, go-to-market work around is govern data lakes. So I want to enable self service analytics throughout my enterprise. I want self service analytics tools to everyone that has access to it. I want to make data available to them, but I want that data to be governed so that they can discover what's in it in the lake, and whatever I give them is what they should have access to. So those are the kind of the three tracks that we're working with Hortonworks on, and all of them are making stunning results inside of clients. >> And so that involves actually some serious engineering as well-- >> Big time. It's not just sort of a Barney deal or just a pure go to market-- >> It's certainly more the market texture and just works. >> Big picture down the road then. Whatever challenges that you see on your side of the business for the next 12 months. What are you going to tackle, what's that monster out there that you think okay this is our next hurdle to get by. >> I forgot if Rob said this before, but you'll hear him say often and it's statistically proven, the majority of the data that's available is not available to be Googled, so it's behind a firewall. And so we started last year with the Watson data platform creating an integrating data analytics system. What if customers have data that's on-prem that they want to take advantage of, what if they're not ready for the public cloud. How do we deliver public benefits to them when they want to run that workload behind a firewall. So we're doing a significant amount of engineering, really starting with the work that we did on a data science experience. Bringing it behind the firewall, but still delivering similar benefits you would expect if you're delivering it in the public cloud. A major advancement that IBM made is run IBM cloud private. I don't know if you guys are familiar with that announcement. We made, I think it's already two weeks ago. So it's a (mumbles) foundation on top of which we have micro services on top of which our stack is going to be made available. So when I think of kind of where the future is, you know our customers ultimately we believe want to run data and analytic workloads in the public cloud. How do we get them there considering they're not there now in a stepwise fashion that is sensible economically project management-wise culturally. Without having them having to wait. That's kind of big picture, kind of a big problem space we're spending considerable time thinking through. >> We've been talking a lot about this on theCUBE in the last several months or even years is people realize they can't just reform their business and stuff into the cloud. They have to bring the cloud model to their data. Wherever that data exists. If it's in the cloud, great. And the key there is you got to have a capability and a solution that substantially mimics that public cloud experience. That's kind of what you guys are focused on. >> What I tell clients is, if you're ready for certain workloads, especially green field workloads, and the capability exists in a public cloud, you should go there now. Because you're going to want to go there eventually anyway. And if not, then a vendor like IBM helps you take advantage of that behind a firewall, often in form facts that are ready to go. The integrated analytics system, I don't know if you're familiar with that. That includes our super advanced data warehouse, the data science experience, our query federation technology powered by big SQL, all in a form factor that's ready to go. You get started there for data and data science workloads and that's a major step in the direction to the public cloud. >> Alright well Daniel thank you for the time, we appreciate that. We didn't get to touch at all on baseball, but next time right? >> Daniel: Go Cubbies. (laughing) >> Sore spot with me but it's alright, go Cubbies. Alright Daniel Hernandez from IBM, back with more here from Data Science For All. IBM's event here in Manhattan. Back with more in theCUBE in just a bit. (electronic music)
SUMMARY :
Brought to you by IBM. So be sure to stick around all day long on theCUBe for that. to the hardcore data scientists. Who's a VP of IBM Analytics, good to see you. how do you see it in terms of how businesses should be So that's kind of the way I approach describing what it is. in terms of how wide of a net are you casting You need the ability to organize that data All that has to happen before you can actually and people that don't know how to code. Has that changed and to what degree has it changed? and to solve my problem like customer segmentation And if you don't, it's a big flaw, it's a big gap is it not? And it just so happens the same discipline that you use, Well so presumably part of that anyway We're embedding that into most of the stuff You know the more restrictions you put on that information So the CDO function in a lot of organizations As opposed to CIO or CTO, you know you have these other. the process and people design to solve that particular issue data blueprint if you will. that seems to be trickling down to the divisions. is going to be in Hadoop as we were describing. just a pure go to market-- that you think okay this is our next hurdle to get by. I don't know if you guys are familiar And the key there is you got to have a capability often in form facts that are ready to go. We didn't get to touch at all on baseball, Daniel: Go Cubbies. IBM's event here in Manhattan.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
IBM | ORGANIZATION | 0.99+ |
Daniel Hernandez | PERSON | 0.99+ |
Daniel | PERSON | 0.99+ |
February | DATE | 0.99+ |
Boston | LOCATION | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
one | QUANTITY | 0.99+ |
David | PERSON | 0.99+ |
Manhattan | LOCATION | 0.99+ |
Inderpal Bhandari | PERSON | 0.99+ |
June | DATE | 0.99+ |
Rob | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
New York | LOCATION | 0.99+ |
New York City | LOCATION | 0.99+ |
last year | DATE | 0.99+ |
Seth | PERSON | 0.99+ |
Python | TITLE | 0.99+ |
third piece | QUANTITY | 0.99+ |
EDW | ORGANIZATION | 0.99+ |
second | QUANTITY | 0.99+ |
Hortonworks | ORGANIZATION | 0.99+ |
last week | DATE | 0.99+ |
today | DATE | 0.99+ |
First | QUANTITY | 0.99+ |
SQL | TITLE | 0.99+ |
two customers | QUANTITY | 0.99+ |
Hadoop | TITLE | 0.99+ |
first | QUANTITY | 0.99+ |
SPSS | TITLE | 0.98+ |
Seth Dobrin | PERSON | 0.98+ |
three tracks | QUANTITY | 0.98+ |
John Walls | PERSON | 0.98+ |
IBM Analytics | ORGANIZATION | 0.98+ |
first guest | QUANTITY | 0.97+ |
two weeks ago | DATE | 0.97+ |
one aspect | QUANTITY | 0.96+ |
first one | QUANTITY | 0.96+ |
Barney | ORGANIZATION | 0.96+ |
two majors | QUANTITY | 0.96+ |
last weekend | DATE | 0.94+ |
this summer | DATE | 0.94+ |
Hadoop | ORGANIZATION | 0.93+ |
decades | QUANTITY | 0.92+ |
last fall | DATE | 0.9+ |
two | QUANTITY | 0.85+ |
IBM Data Science For All | ORGANIZATION | 0.79+ |
three main | QUANTITY | 0.78+ |
next 12 months | DATE | 0.78+ |
CDO | TITLE | 0.77+ |
D | ORGANIZATION | 0.72+ |
Day Two Kick Off | Splunk .conf 2017
>> Announcer: Live from Washington D. C., it's the CUBE. Covering .conf2017. Brought to you by Splunk. (electronic music) >> Welcome back to the nation's capitol everybody. This is the CUBE, the leader in live tech coverage. And we're here at day two covering Splunk's .conf user conference #splunkconf17, and my name is Dave Vellante, I'm here with with co-host, George Gilbert. As I say, this is day two. We just came off the keynotes. I'm over product orientation today. George, what I'd like to do is summarize the day and the quarter that we've had so far, and then bring you into the conversation and get your opinion on what you heard. You were at the analyst event yesterday. I've been sitting in keynotes. We've been interviewing folks all day long. So let me start, Splunk is all about machine data. They ingest machine data, they analyze machine data for a number of purposes. The two primary use cases that we've heard this week are really IT, what I would call operations management. Understanding the behavior of your systems. What's potentially going wrong, what needs to be remediated. to avoid an outage or remediate an outage. And of course the second major use case that we've heard here is security. Some of the Wall Street guys, I've read some of the work this morning. Particularly Barclays came out with a research note. They had concerns about that, and I really don't know what the concerns are. We're going to talk about it. I presume it's that they're looking for a TAM expansion strategy to support a ten billion dollar valuation, and potentially a much higher valuation. It's worth noting the conference this year is 7,000 attendees, up from 5,000 last year. That's a 40% increase, growing at, or above actually, the pace of revenue growth at Splunk. Pricing remains a concern for some of the users that I've talked to. And I want to talk to you about that. And then of course, there's a lot of product updates that I want to get into. Splunk Enterprise 7.0 which is really Splunk's core analytics platform ITSI which is what I would, their 3.0, which I would call their ITOM platform. UBA which is user behavior analytics 4.0. Updates to Splunk Cloud, which is a service for machine data in the cloud. We've heard about machine learning across the portfolio, really to address alert fatigue. And a new metrics engine called Mstats. And of course we heard today, enterprise content security updates and many several security-oriented solutions throughout the week on fraud detection, ransomware, they've got a deal with Booz Allen Hamilton on Cyber4Sight which is security as a service that involves human intelligence. And a lot of ecosystem partnerships. AWS, DellEMC was on yesterday, Atlassian, Gigamon, et cetera, growing out the ecosystem. That's a quick rundown, George. I want to start with the pricing. I was talking to some users last night before the party. You know, "What do you like about Splunk? "What don't you like about Splunk? "Are you a customer?" I talked to one prospective customer said, "Wow, I've been trying to do "this stuff on my own for years. "I can't wait to get my hands on this." Existing customers, though, only one complaint that I heard was your price is to high, essentially is what they were telling Splunk. Now my feeling on that, and Raymo from Barclays mentioned that in his research note this morning. Raymo Lencho, top securities analyst following software industry. And my feeling George is that historically, "Your price is too high," has never been a headwind for software companies. You look at Oracle, you look at ServiceNow, sometimes customers complain about pricing too high. Splunk, and those companies tend to do very well. What's your take on pricing as a headwind or tailwind indicator? >> Well the way, you always set up these questions in a way that makes answering them easy. Because it's a tailwind in the sense that the deal sizes feed an enterprise sales force. And you need an enterprise sales force ultimately to be pervasive in an organization. 'Cause you can't just throw up like an Amazon-style console and say, "Pick your poison and put it all together." There has to be an advisory, consultative approach to working with a customer to tell them how best to fit their portfolio. >> Right. >> And their architecture. So yes, the price helps you feed that what some people in the last era of enterprise software used to call the most expensive migratory workforce in the world., which is the sales, enterprise sales organization. >> Sure, right. >> But what's happened in the different, in the change from the last major enterprise applications, ERPCRM, and what we're getting into now, is that then the data was all generated and captured by humans. It was keyboard entry. And so there was no, the volumes of data just weren't that great. It was human, essentially business transactions. Now we're capturing data streaming off everything. And you could say Splunk was sort of like the first one out of the gate doing that. And so if you take the new types of data, customer interactions, there are about ten to a hundred customer interactions for every business transaction. Then the information coming out of the IT applications and infrastructure. It's about ten to a hundred times what the customer interactions were. >> Yeah. >> So you can't price the, Your pricing model, if it stays the same will choke you. >> So you're talking about multiple orders of magnitude >> Yes. >> Of more data. >> Yeah. >> And if you're pricing by the terabyte, >> Right. >> Then that's going to cross your customers. >> Right. But here's what I would argue though George. I mean, and you mentioned AWS. AWS is another one where complaints of high pricing. But if, to me, if the company is adding value, the clients will pay for it. And when you get to the point where it becomes a potential headwind, the company, Oracle is a classic at this, will always adjust its pricing to accommodate both its needs as a public organization and a company that has to make money and fund R & D, and the customers needs, and find that balance where the competition can't get in. And so it seems to me, and we heard this from Doug Merritt yesterday, that his challenge is staying ahead of the game. Staying, moving faster than the cloud guys. >> Yeah. >> In what they do well. And to the extent that they do that, I feel like their customers will reward them with their loyalty. And so I feel as though they can adjust their pricing mechanisms. Yeah, everybody's worried about 606, and of course the conversions to subscriptions. I feel as though a high growth, and adjustments to your pricing strategy, I think can address that. What do you think about that? >> It's... It sounds like one of those sayings where, the friends say, "Well it works in practice, "but does it work in theory?" >> No, no. But it has worked in practice in the industry hasn't it? So what's different now? >> Okay. So take Oracle, at list price for Oracle 12C, flagship database. The price per processor core, with all the features thrown in, is something like three hundred thousand, three hundred fifty thousand per core. So you take an average Intel high end server chip, that might have 24 cores, and then you have two sockets, so essentially one node server is 48 times 350. And then of course, Oracle will say, "But for a large customer, we'll knock 90% off that," or something like that. >> Yeah, well exactly. >> Which is exactly what the Splunk guys told me yesterday. But it's-- >> But that's what I'm saying. They'll do what they have to do to maintain the footprint in the customer, do right by the customer, and keep the competition out. >> But if it's multiple orders of magnitude different. If you take the open source guys where essentially the software's free and you're just paying for maintenance. >> (laughs) Yeah and humans. >> Yeah, yeah. >> Okay, that's the other advantage of Splunk, as you pointed out yesterday, they've got a much more integrated set of offerings and services that dramatically lower. I mean, we all know the biggest cost of IT is people. It's not the hardware and software but, all right, I don't want to rat hole on pricing, but that was a good discussion. What did you learn yesterday? You've sat through the analyst meeting. Give us the rundown on George Gilbert's analysis of .conf generally and Splunk as a company specifically. >> Okay, so for me it was a bit of an eye opener because I got to understand sort of, I've always had this feeling about where Splunk fits relative to the open source big data ecosystem. But now I got a sense for what their ambitions are, and what their tactical plan is. I've said for awhile, Splunk's the anti-Hadoop. You know, Hadoop is multiple, sort of dozens of animals with three zookeepers. And I mean literally. >> Yeah. >> And the upside of that is, those individual projects are advancing with a pace of innovation that's just unheard of. The problem is the customer bears the burden of putting it all together. Splunk takes a very different approach which is, they aspire apparently to be just like Hadoop in terms of platform for modern operational analytic applications, but they start much narrower. And it gets to what Ramie's point was in that Wall Street review, where if you take at face value what they're saying, or you've listened just to the keynote, it's like, "Geez, they're in this IT operations ghetto, "in security and that's a La Brea tar pit, "and how are they ever going to climb out of that, "to something really broad?" But what they're doing is, they're not claiming loudly that they're trying to topple the giants and take on the world. They're trying to grow in their corner where they have a defensible moat. And basically the-- >> Let me interrupt you. >> Yeah. >> But to get to five billion >> Yeah. >> Or beyond, they have to have an aggressive TAM expansion strategy, kind of beyond ITOM and security, don't they? >> Right. And so that's where they start generalizing their platform. The data store they had on the platform, the original one, is kind of like a data lake in the sense that it really was sort of the same searchable type index that you would put under a sort of a primitive search engine. They added a new data store this time that handles numbers really well and really fast. That's to support the metrics so they can have richer analytics on the dashboard. Then they'll have other data stores that they add over time. And for each one, you're able to now build with their integrated tool set, more and more advanced apps. >> So you can't use a general purpose data store. You've got to use the Splunk within data. It's kind of like Work Day. >> Yeah, well except that they're adding more over time, and then they're putting their development tools over these to shield them. Now how seamlessly they can shield them remains to be seen. >> Well, but so this is where it gets interesting. >> Yeah. >> Splunk as a platform, as an application development platform on which you can build big data apps, >> Yeah. >> It's certainly, conceptually, you can see how you could use Splunk to do that right? >> And so their approaches out of the box will help you with enterprise security, user, they call it user behavior analytics, because it's a term another research firm put on it, but it's really any abnormal behavior of an entity on the network. So they can go in and not sell this fuzzy concept of a big data platform. They said, they go in and sell, to security operations center, "We make your life much, much easier. "And we make your organization safer." And they call these curated experiences. And the reason this is important is, when Hadoop sells, typically they go in, and they say, "Well, we have this data lake. "which is so much cheaper and a better way "to collect all your data than a data warehouse." These guys go in and then they'll add what more and more of these curated experiences, which is what everyone else would call applications. And then the research Wikibon's done, depth first, or rather breadth first versus depth first. Breadth first gives you the end to end visibility across on prem, across multiple clouds, down to the edge. But then, when they put security apps on it, when they put dev ops or, some future big data analytics apps as their machine learning gets richer and richer, then all of a sudden, they're not selling the platform, because that's a much more time-intensive sale, and lots more of objectives, I'm sorry, objections. >> It's not only the solutions, those depth solutions. >> Yes, and then all of a sudden, the customer wakes up and he's got a dozen of these things, and all of a sudden this is a platform. >> Well, ServiceNow is similar in that it's a platform. And when Fred Luddy first came out with it, it's like, "Here." And everybody said, "Well, what do I do with it?" So he went back and wrote a IT service management app. And they said, "Oh okay, we get it." Splunk in a similar way has these depth apps, and as you say, they're not selling the platform, because they say, "Hey, you want to buy a platform?" people don't want to buy a platform, they want to buy a solution. >> Right. >> Having said that, that platform is intrinsic to their solutions when they deliver it. It's there for them to leverage. So the question is, do they have an application developer kit strategy, if you will. >> Yeah. >> Whether it's low code or even high code. >> Yeah. >> Where, and where they're cultivating a developer community. Is there anything like that going on here at .conf? >> Yeah, they're not making a big deal about the development tools, 'cause that makes it sound more like a platform. >> (laughs) But they could! >> But they could. And the tools, you know, so that you can build a user interface, you can build dashboards, you can build machine learning models. The reason those tools are simpler and more accessible to developers, is because they were designed to fit the pieces underneath, the foundation. Whereas if you look at some of the open source big data ecosystem, they've got these notebooks and other tools where you address one back end this way, another back end that way. It's sort of, you know, you can see how Frankenstein was stitched together, you know? >> Yeah so, I mean to your point, we saw fraud detection, we saw ransomware, we see this partnership with Booz Allen Hamilton on Cyber4Sight. We heard today about project Waytono, which is unified monitoring and troubleshooting. And so they have very specific solutions that they're delivering, that presumably many of them are for pay. And so, and bringing ML across the platform, which now open up a whole ton of opportunities. So the question is, are these incremental, defend the base and then grow the core solutions, or are they radical innovations in your view? >> I think they're trying to stay away from the notion of radical innovation, 'cause then that will create more pushback from organizations. So they started out with a google-search-like product for log analytics. And you can see that as their aspirations grow for a broader set of applications, they add in a richer foundation. There's more machine learning algorithms now. They added that new data store. And when we talked about this with the CEO, Doug Merritt yesterday at the analyst day, he's like, "Yes, you look out three to five years, "and the platform gets more and more broad. "and at some point customers wake up "and they realize they have a new strategic platform." >> Yeah, and platforms do beat products, and even though it's hard sell, if you have a platform like Splunk does, you're in a much better strategic position. All right, we got to wrap. George thanks for joining me for the intro. I know you're headed to New York City for Big Data NYC down there, which is the other coverage that we have this week. So thank you again for coming on. >> Okay. >> All right, keep it right there. We'll be back with our next guest, we're live. This is the CUBE from Splunk .conf2017 in the nation's capitol, be right back. (electronic music)
SUMMARY :
Brought to you by Splunk. And of course the second major use case Well the way, you always set up these questions So yes, the price helps you feed that And so if you take the new types of data, So you can't price the, Then that's going to And so it seems to me, and we heard this and of course the conversions to subscriptions. the friends say, "Well it works in practice, in the industry hasn't it? and then you have two sockets, Which is exactly what the Splunk guys told me yesterday. and keep the competition out. If you take the open source guys It's not the hardware and software but, I've said for awhile, Splunk's the anti-Hadoop. And it gets to what Ramie's point was in the sense that it really was So you can't use a general purpose data store. and then they're putting their development tools And the reason this is important is, It's not only the solutions, the customer wakes up and he's got and as you say, they're not selling the platform, So the question is, do they have an application developer and where they're cultivating a developer community. about the development tools, And the tools, you know, And so, and bringing ML across the platform, And you can see that as their aspirations grow So thank you again for coming on. This is the CUBE from Splunk
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Dave Vellante | PERSON | 0.99+ |
George Gilbert | PERSON | 0.99+ |
George | PERSON | 0.99+ |
Barclays | ORGANIZATION | 0.99+ |
AWS | ORGANIZATION | 0.99+ |
Doug Merritt | PERSON | 0.99+ |
90% | QUANTITY | 0.99+ |
24 cores | QUANTITY | 0.99+ |
Splunk | ORGANIZATION | 0.99+ |
five billion | QUANTITY | 0.99+ |
yesterday | DATE | 0.99+ |
Ramie | PERSON | 0.99+ |
three hundred thousand | QUANTITY | 0.99+ |
New York City | LOCATION | 0.99+ |
Washington D. C. | LOCATION | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
Fred Luddy | PERSON | 0.99+ |
three | QUANTITY | 0.99+ |
last year | DATE | 0.99+ |
two sockets | QUANTITY | 0.99+ |
Cyber4Sight | ORGANIZATION | 0.99+ |
three zookeepers | QUANTITY | 0.99+ |
Atlassian | ORGANIZATION | 0.99+ |
Wikibon | ORGANIZATION | 0.99+ |
today | DATE | 0.99+ |
last night | DATE | 0.99+ |
7,000 attendees | QUANTITY | 0.99+ |
Gigamon | ORGANIZATION | 0.99+ |
five years | QUANTITY | 0.98+ |
ten billion dollar | QUANTITY | 0.98+ |
Amazon | ORGANIZATION | 0.98+ |
48 times | QUANTITY | 0.98+ |
TAM | ORGANIZATION | 0.98+ |
both | QUANTITY | 0.98+ |
NYC | LOCATION | 0.98+ |
each one | QUANTITY | 0.98+ |
three hundred fifty thousand per core | QUANTITY | 0.98+ |
one complaint | QUANTITY | 0.97+ |
this year | DATE | 0.97+ |
this week | DATE | 0.97+ |
Intel | ORGANIZATION | 0.97+ |
5,000 | QUANTITY | 0.97+ |
Hadoop | ORGANIZATION | 0.97+ |
two primary use cases | QUANTITY | 0.96+ |
first | QUANTITY | 0.96+ |
first one | QUANTITY | 0.96+ |
about ten | QUANTITY | 0.96+ |
about ten | QUANTITY | 0.96+ |
DellEMC | ORGANIZATION | 0.96+ |
one | QUANTITY | 0.95+ |
Booz Allen Hamilton | ORGANIZATION | 0.95+ |
350 | QUANTITY | 0.95+ |
second major use case | QUANTITY | 0.94+ |
Covering | EVENT | 0.93+ |
day two | QUANTITY | 0.92+ |
ServiceNow | TITLE | 0.92+ |
7.0 | TITLE | 0.91+ |
Big Data | ORGANIZATION | 0.89+ |
a hundred times | QUANTITY | 0.89+ |
dozens of animals | QUANTITY | 0.88+ |
Dr. Mark Ramsey & Bruno Aziza | BigData NYC 2017
>> Live from Mid Town Manhattan. It's the Cube, covering BIGDATA New York City 2017. Brought to you by, SiliconANGLE Media and it's ecosystems sponsors. >> Hey welcome back everyone live here in New York City for the Cube special presentation of BIGDATA NYC. Here all week with the Cube in conjunction with Strata Data even happening around the corner. I'm John Furrier the host. James Kobielus, our next two guests Doctor Mark Ramsey, chief data officer and senior vice president of R&D at GSK, Glasgow Pharma company. And Bruno as he's the CMO at Fscale, both Cube alumni. Welcome back. >> Thank for having us. >> So Bruno I want to start with you because I think that Doctor Mark has some great use cases I want to dig into and go deep on with Jim. But Fscale, give us the update of the company. You guys doing well, what's happening? How's the, you have the vision of this data layer we talked a couple years ago. It's working so tell us, give us the update. >> A lot of things have happened since we talked last. I think you might have seen some of the news in terms of growth. Ten X growth since we started and mainly driven around the customer use cases. That's why I'm excited to hear from Mark and share his stories with the rest of the audience here. We have a presentation at Strata tomorrow with Vivens. It's a great IOT use case as well. So what we're seeing is the industry is changing in terms of how it's spying the idea platforms. In the past, people would buy idea platforms vertically. They'd buy the visualization, they'd buy the sementic and buy the best of great integration. We're now live in a world where there's a multitude of BI tools. And the data platforms are not standardized either. And so what we're kind of riding as a trend is this idea of the need for the universal semantic layer. This idea that you can have a universal set of semantics. In a dictionary or ontology. that can be shared across all types of business users and business use cases. Or across any data. That's really the trend that's driving our growth. And you'll see it today at this show with the used cases and the customers. And of course some of the announcements that we're doing. We're announcing a new offer with cloud there and tableau. And so we're really excited about again how they in space and the partner ecosystems embracing our solutions. >> And you guys really have a Switzerland kind of strategy. You're going to play neutral, play nicely with everybody. Because you're in a different, your abstraction layer is really more on the data. >> That's right. The whole value proposition is that you don't want to move your data. And you don't want to move your users away from the tools that they already know but you do want them to be able to take advantage of the data that you store. And this concept of virtualized layer and you're universal semantic layer that enables the use case to happen faster. Is a big value proposition to all of them. >> Doctor Mark Ramsey, I want to get your quick thoughts on this. I'm obviously your customer so. I mean you're not bias, you ponder pressure everyday. Competitive noise out there is high in this area and you're a chief data officer. You run R&D so you got that 20 miles stare into the future. You've got experience running data at a wide scale. I mean there's a lot of other potential solutions out there. What made it attractive for you? >> Well it feels a need that we have around really that virtualization. So we can leave the data in the format that it is on the platform. And then allow the users to use like Bruno was mentioning. Use a number of standardized tools to access that information. And it also gives us an ability to learn how folks are consuming the data. So they will use a variety of tools, they'll interact with the data. At scale gives us a great capability to really look under the cover, see how they're using the data. And if we need to physicalize some of that to make easier access in the long term. It gives us that... >> It's really an agility model kind to data. You're kind of agile. >> Yeah its kind of a way to make, you know so if you're using a dash boarding tool it allows you to interact with the data. And then as you see how folks are actually consuming the information. Then you can physicalize it and make that readily available. So it is, it gives you that agile cycles to go through. >> In your use of the solution, what have you seen in terms of usage patterns. What are your users using at scale for? Have you been surprised by how they're using it? And where do you plan to go in terms of the use cases you're addressing going forward with this technology? >> This technology allows us to give the users the ability to query the data. So for example we use standardized ontologies in several of the areas. And standardized ontologies are great because the data is in one format. However that's not necessarily how the business would like to look at the data and so it gives us an ability to make the data appear like the way the users would like to consume the information. And then we understand which parts of the model they're actually flexing and then we can make the decision to physicalize that. Cause again it's a great technology but virtualization there is a cost. Because the machines have to create the illusion of the data being a certain way. If you know it's something that's going to be used day in and day out then you can move it to a physicalized version. >> Is there a specific threshold when you were looking at the metrics of usage. When you know that particular data, particular views need to be physicalized. What is that threshold or what are those criteria? >> I think it's, normally is a combination of the number of connections that you have. So the joins of the data across the number of repositories of data. And that balanced with the volume of data so if you're dealing with thousands of rows verses billions of rows then that can lead you to make that decision faster. There isn't a defined metric that says, well we have this number of rows and this many columns and this size that it really will lead you down that path. But the nice thing is you can experiment and so it does give you that ability to sort of prototype and see, are folks consuming the data before you evoke the energy to make it physical. >> You know federated, I use the word federated but semantic virtualization layers clearly have been around for quite sometime. A lot of solution providers offer them. A lot of customers have used them for disparate use cases. One of the wraps traditionally again estimating virtualization is that it's simply sort of a stop gap between chaos on the one end. You know where you have dozens upon dozens of databases with no unified roll up. That's a stop gap on the way to full centralization or migration to a big data hub. Did you see semantic virtualization as being sort of your target architecture for your operational BI and so forth? Or do you on some level is it simply like I said a stop gap or transitional approach on the way to some more centralized environment? >> I think you're talking about kind of two different scenarios here. One is in federated I would agree, when folks attempted to use that to bring disparate data sources together to make it look like it was consolidated. And they happen to be on different platforms, that was definitely a atop gap on a journey to really addressing the problem. Thing that's a little different here is we're talking about this running on a standardized platform. So it's not platformed disparate it's on the platform the data is being accessed on the platform. It really gives us that flexibility to allow the consumer of the data to have a variety of views of the data without actually physicalizing each of them. So I don' know that it's on a journey cause we're never going to get to where we're going to make the data look as so many different ways. But it's very different than you know ten, 15 years ago. When folks were trying to solve disparate data sources using federation. >> Would it be fair to characterize what you do as agile visualization of the data on a data lake platform? Is that what it's essentially about? >> Yeah that, it certainly enables that. In our particular case we use the data lake as the foundation and then we actually curate the data into standardized ontologies and then really, the consumer access layer is where we're applying virtualization. In the creation of the environment that we have we've integrated about a dozen different technologies. So one of the things we're focused on is trying to create an ecosystem. And at scale is one of the components of that. It gives us flexibility so that we don't have to physicalize. >> Well you'd have to stand up any costs. So you have the flexibility with at scale. I get this right? You get the data and people can play with it without actually provisioning. It's like okay save some cash, but then also you double down on winners that come in. >> Things that are a winner you check the box, you physicalize it. You provide that access. >> You get crowd sourcing benefits like going on in your. >> You know exactly. >> The curation you mentioned. So the curation goes on inside of at scale. Are you using a different tool or something you hand wrote in house to do that? Essentially it's a data governance and data cleansing. >> That is, we use technology called Tamer. That is a machine learning based data curation tool, that's one of our fundamental tools for curation. So one of the things in the life sciences industry is you tend to have several data sources that are slightly aligned. But they're actually different and so machine learning is an excellent application. >> Lets get into the portfolio. Obviously as a CTO you've got to build a holistic view. You have a tool chest of tools and a platform. How do you look at the big picture? On that scale if it's been beautifully makes a lot of sense. So good for those guys. But you know big picture is, you got to have a variety of things in your arsenal. How do you architect that tool shed or your platform? Is everything a hammer, everything's a nail. You've got all of them though. All the things to build. >> You bring up a great point cause unfortunately a lot of times. We'll use your analogy, it's like a tool shed. So you don't want 12 lawnmowers right? In your tool shed right? So one of the challenges is that a lot of the folks in this ecosystem. They start with one area of focus and then they try to grow into area of focuses. Which means that suddenly everybody's starts to be a lawnmower, cause they think that's... >> They start as a hammer and turn into a lawn mower. >> Right. >> How did that happen, that's called pivoting. >> You can mow your lawn with a hammer but. So it's really that portfolio of tools that all together get the job done. So certainly there's a data acquisition component, there's the curation component. There's visualization machines learning, there's the foundational layer of the environment. So all of those things, our approach has been to select. The kind of best in class tools around that and then work together and... Bruno and the team at scale have been part of this. We've actually had partner summits of how do we bring that ecosystem together. >> Is your stuff mostly on prime, obviously a lot of pharma IP there. So you guys have the game that poll patent thing which is well documented. You don't want to open up the kimono and start the cloth until it's releasing so. You obviously got to keep things confidential. Mix of cloud, on prime, is it 100 percent on prime? Is there some versing for the cloud? Is it a private cloud, how do you guys look at the cloud piece? >> Yeah majority of what we're doing is on prime. The profile for us is that we persist the data. So it's not. In some cases when we're doing some of the more advanced analytics we burst to the cloud for additional processors. But the model of persisting the data means that it's much more economical to have on prime instance of what we're doing. But it is a combination, but the majority of what we're doing is on prime. >> So will you hold on Jim, one more question. I mean obviously everyone's knocking on your door. You know how to get in that account. They spend a lot of money. But you're pretty disciplined it sounds like you've got to a good view of you don't want people to come in and turn into someone that you don't want them to be. But you also run R&D so you got to have to understand the head room. How do you look at the head room of what you need down the road in terms of how you interface with the suppliers that knock on your door. Whether it's at scale currently working with you now. And then people just trying to get in there and sell you a hammer or a lawn mower. Whatever they have they're going to try, you know you're dealing with the vendor pressure. >> Right well a lot of that is around what problem we're trying to solve. And we drive all of that based on the use cases and the value to the business. I mean and so if we identify gaps that we need to address. Some of those are more specific to life sciences types of challenges where they're very specific types of tools that the population of partners is quite small. And other things. We're building an actual production, operational environment. We're not building a proof of concept, so security is extremely important. We're coberosa enabled end to end to out rest inflight. Which means it breaks some of the tools and so there's criteria of things that need to be in place in order to... >> So you got anything about scale big time? So not just putting a beach head together. But foundationally building out platform. Having the tools that fit general purpose and also specialty but scales a big thing right? >> And it's also we're addressing what we see is three different cohorts of consumers of the data. One is more in the guided analytics, the more traditional dashboards, reports. One is in more of computational notebooks, more of the scientific using R, Python, other languages. The third is more kind of almost at the bare middle level machine learning, tenser flow a number of tools that people directly interact. People don't necessarily fit nicely into those three cohorts so we're also seeing that, there's a blend. And that's something that we're also... >> There's a fourth cohort. >> Yeah well you know someone's using a computational notebook but they want to draw upon a dashboard graphic. And then they want to run a predefined tenser flow and pull all that together so. >> And what you just said, tied up the question I was going to ask. So it's perfect so. One of my core focuses is as a Wikibon analyst is on deep learning. On AI so in semantic data virtualization in a life sciences pharma context. You have undoubtedly a lot of image data, visual data. So in terms of curating that and enabling you know virtualized access to what extent are you using deep learning, tenser flow, convolutional neural networks to be able to surface up the visual patterns that can conceivably be searched using a variety of techniques. Is that a part of your overall implementation of at scale for your particular use cases currently? Or do you plan to go there in terms of like tenser flow? >> No I mean we're active, very active. In deep learning, artificial intelligence, machine learning. Again it depends on which problem you're trying to solve and so we again, there's a number of components that come together when you're looking at the image analytics. Verses using data to drive out certain decisions. But we're acting in all of those areas. Our ultimate goal is to transform the way that R&D is done within a pharmaceutical company. To accelerate the, right now it takes somewhere between five and 15 years to develop a new medicine. The goal is to really to do a lot more analytics to shorten that time significantly. Helps the patients, gets the medicines to market faster. >> That's your end game you've got to create an architecture that enables the data to add value. >> Right. >> The business. Doctor Mark Ramsey thanks so much for sharing the insight from your environment. Bruno you got something there to show us. What do you got there? He always brings a prop on. >> A few years ago I think I had a tattoo on my neck or something like this. But I'm happy that I brought this because you could see how big Mark's vision is. the reason why he's getting recognized by club they're on the data awards and so forth. Is because he's got a huge vision and it's a great opportunity for a lot of CTOs out there. I think the average CEO spent a 100 million dollars to deploy big data solutions over the last five years. But they're not able to consumer all the data they produce. I think in your case you consume about a 100 percent of the instructor data. And the average in this space is we're able to consume about one percent of the data. And this is essentially the analogy today that you're dealing with if you're on the enterprise. We'd spent a lot of time putting data in large systems and so forth. But the tool set that we give, that you did officers in their team is a cocktail straw lik this in order to drink out of it. >> That's a data lake actually. >> It's an actual lake. It's a Slurpee cup. Multiple Slurpees with the same straw. >> Who has the Hudson river water here? >> I can't answer that question I think I'd have to break a few things if I did. But the idea here is that it's not very satisfying. Enough the frustration business users and business units. When at scale's done is we built this, this is the straw you want. So I would kind of help CTOs contemplate this idea of the Slurpee and the cocktail straw. How much money are you spending here and how much money are you spending there. Because the speed at which you can get the insights to the business user. >> You got to get that straw you got to break it down so it's available everywhere. So I think that's a great innovation and it makes me thirsty. >> You know what, you can have it. >> Bruno thanks for coming from at scale. Doctor Mark Ramsey good to see you again great to have you come back. Again anytime love to have chief data officers on. Really a pioneering position, is the critical position in all organizations. It will be in the future and will continue being. Thanks for sharing your insights. It's the Cube, more live coverage after this short break. (tech music)
SUMMARY :
Brought to you by, And Bruno as he's the CMO at Fscale, So Bruno I want to start with you And of course some of the announcements that we're doing. And you guys really have a Switzerland And you don't want to move your users You run R&D so you got that in the format that it is on the platform. It's really an agility model kind to data. So it is, it gives you that agile cycles to go through. And where do you plan to go and day out then you can move it to a physicalized version. When you know that particular data, particular views But the nice thing is you can experiment You know where you have dozens upon dozens of databases So it's not platformed disparate it's on the platform So one of the things we're focused on So you have the flexibility with at scale. Things that are a winner you check the box, You get crowd sourcing benefits So the curation goes on So one of the things in the life sciences industry you got to have a variety of things in your arsenal. So one of the challenges is that a lot of the folks Bruno and the team at scale have been part of this. So you guys have the game that poll patent thing but the majority of what we're doing is on prime. of what you need down the road and the value to the business. So you got anything about scale big time? more of the scientific using R, Python, other languages. Yeah well you know someone's using to what extent are you using deep learning, Helps the patients, gets the medicines to market faster. that enables the data to add value. Bruno you got something there to show us. that you did officers in their team is a cocktail straw It's a Slurpee cup. Because the speed at which you can get the insights you got to break it down so it's available everywhere. Doctor Mark Ramsey good to see you again
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Jim | PERSON | 0.99+ |
James Kobielus | PERSON | 0.99+ |
Mark | PERSON | 0.99+ |
Bruno | PERSON | 0.99+ |
New York City | LOCATION | 0.99+ |
John Furrier | PERSON | 0.99+ |
20 miles | QUANTITY | 0.99+ |
Mark Ramsey | PERSON | 0.99+ |
100 percent | QUANTITY | 0.99+ |
12 lawnmowers | QUANTITY | 0.99+ |
GSK | ORGANIZATION | 0.99+ |
100 million dollars | QUANTITY | 0.99+ |
Fscale | ORGANIZATION | 0.99+ |
third | QUANTITY | 0.99+ |
dozens | QUANTITY | 0.99+ |
SiliconANGLE Media | ORGANIZATION | 0.99+ |
One | QUANTITY | 0.99+ |
15 years | QUANTITY | 0.99+ |
Python | TITLE | 0.99+ |
today | DATE | 0.99+ |
Bruno Aziza | PERSON | 0.99+ |
both | QUANTITY | 0.99+ |
one | QUANTITY | 0.98+ |
each | QUANTITY | 0.98+ |
fourth cohort | QUANTITY | 0.98+ |
NYC | LOCATION | 0.98+ |
Cube | ORGANIZATION | 0.98+ |
Hudson river | LOCATION | 0.98+ |
Vivens | ORGANIZATION | 0.98+ |
Switzerland | LOCATION | 0.98+ |
three cohorts | QUANTITY | 0.98+ |
Doctor | PERSON | 0.98+ |
billions of rows | QUANTITY | 0.97+ |
Ten X | QUANTITY | 0.97+ |
tomorrow | DATE | 0.97+ |
two guests | QUANTITY | 0.97+ |
one format | QUANTITY | 0.97+ |
thousands of rows | QUANTITY | 0.97+ |
BIGDATA | ORGANIZATION | 0.97+ |
prime | COMMERCIAL_ITEM | 0.96+ |
one more question | QUANTITY | 0.96+ |
couple years ago | DATE | 0.96+ |
Dr. | PERSON | 0.96+ |
agile | TITLE | 0.96+ |
R&D | ORGANIZATION | 0.95+ |
two different scenarios | QUANTITY | 0.95+ |
about one percent | QUANTITY | 0.95+ |
five | QUANTITY | 0.93+ |
Strata Data | ORGANIZATION | 0.93+ |
three different cohorts | QUANTITY | 0.92+ |
Mid Town Manhattan | LOCATION | 0.92+ |
dozens of databases | QUANTITY | 0.92+ |
Wikibon | ORGANIZATION | 0.92+ |
ten, | DATE | 0.89+ |
about a 100 percent | QUANTITY | 0.89+ |
BigData | ORGANIZATION | 0.88+ |
2017 | DATE | 0.86+ |
one area | QUANTITY | 0.81+ |
BIGDATA New York City 2017 | EVENT | 0.79+ |
last five years | DATE | 0.78+ |
15 years ago | DATE | 0.78+ |
about a dozen different technologies | QUANTITY | 0.76+ |
A few years ago | DATE | 0.76+ |
one end | QUANTITY | 0.74+ |
Glasgow Pharma | ORGANIZATION | 0.7+ |
things | QUANTITY | 0.69+ |
R | TITLE | 0.65+ |
Bill Shinn, AWS | AWS Summit 2017
>> Announcer: Live from Manhattan It's theCUBE! Covering AWS Summit New York City 2017. Brought to you by Amazon Web Services. >> And welcome back here to New York. We're at the Javits Center here in midtown Manhattan for AWS Summit 2017. Along with Stu Miniman, I'm John Walls. Glad to have you here on theCUBE we continue our coverage here from New York City. Well, if you're making that move to the cloud these days, you're thinking about privacy, you're thinking about security, you're thinking about compliance. Big questions, and maybe some big problems that Bill Shin can answer for you. He is the Principal Security Architect at AWS, and Bill, thanks for being with us. >> Thanks for giving me the time. >> Hey CUBE rookie, right? This is- >> This is my first time. >> Your maiden voyage. >> First time for everything. >> Glad to have you, yeah. So I just hit on some of the high points, these are big, big questions for a lot of folks I would say. Just in general, before we jump in, how do you go about walking people into the water a little bit, and getting them thinking, get their arms around these topics? >> Absolutely. It's still among the first conversations we have with customers, it's our top priority at AWS, the security, and customers are concerned about their data security, regardless of where that data is. Once they move it into the cloud it's a real opportunity to be more secure, it's an opportunity to think about how they're doing security, and adapt and be a little faster. So we have a really prescriptive methodology for helping customers understand how to do a clouded option, and improve their security at the same time. We have a framework called the Well-Architected Framework, and there's a security pillar in that framework, it's built around five key areas. Identity access management, which is really what you should be thinking about first, because authorization is everything. Everything is code, everything is in API, so it all has to be authorized properly. Then we move into detective controls and talk about visibility and control, turning on CloudTrail, getting logging set up. All the detective controls so that before you even move a workload into the cloud, you know exactly what's happening, right? And then we move into infrastructure security, which includes your network trust boundaries, zone definition, things like firewall rules, load balancers, segmentation, as well as system security. Hardening and configuration state of all the resources in their account. Then we move on to data protection as we walk customers through this adoption journey. Things like encryption, backup, recovery, access control on data. And then finally incident response. We want to make sure that they have a really good, solid plan for incident response as they begin to move more and more of their business into the cloud. So to help them wade through the waters we bring it up. The CSO is a key partner in a clouded option, organizations need to make sure security is in lockstep with engineering as they move to the cloud. So we want to help with that. We also have the Cloud Adoption Framework, and there's a security perspective in that framework. Methodology for really treating security more like engineering these days. So you have Dev Ops and you have Dev Sec Ops. Security needs to have a backlog, they need to have sprints, they need to have user stories. It's very similar to how engineering would do it. In that way their partnering together as they move workloads into the cloud. >> Amazon's releasing so many new features, it's tough for a lot of us to keep up. Andy Jassey last year said, "Every day when you wake up, there's at least three new announcements coming out." So it's a new day, there are a number of announcements in your space, maybe bring us up to speed as to what we missed if you just woke up on the West Coast. >> Sure, sure. Customers love the pace of innovation, especially security organizations, they really like the fact that when we innovate on something, it means they might not have to put as much resources on that particular security opportunity or security concern. They can focus more on their code quality, more on engineering principles, things like that. So today, we happily announced Amazon Macie, love it, it performs data classification on your S3 objects. It provides user activity monitoring for who's accessing that data. It uses a lot of our machine learning algorithms under the hood to determine what is normal access behavior for that data. It has a very differentiated classification engine. So it does things like topic modeling, regular expressions, and a variety of other things to really identify that data. People were storing trillions of objects in S3, and they really want to know what their data is, whether it's important to them. Certainly customer's data is the most important thing, so being able to classify that data, perform user analytics on it, and then be able to alert and alarm on inappropriate activities. So take a look at Macie, it's really going make a big difference for customers who want to know that their data is secure in S3. >> Actually I got a question from the community looking at Macie came out, we've got a lot of questions about JDPR coming out. >> Bill: Okay sure, yeah. >> So Macie, or the underlying tech, can that be- >> Bill: Absolutely a great tool. We think the US is the greatest place to be to perform JDPR compliance. You really got to know your data, you have to know if you're moving data by European citizens around, you really have to understand that data. I think Macie will be a big part of a lot of customer strategy on JDPR compliance. To finish your question, we've announced quite a few things today, so Macie's one of them. We announced the next iteration of Cloud HSM, so it's cheaper, more automated, deals more with the clustering that you don't have to do. Deeper integration with things like CloudTrail. Customers really wanted a bit more control and integration with the services that what the previous iteration was, so we've offered that. We announced EFS volume encryption too, so EFS, or Elastic File System encryption at rest. It natively integrates with the key management system the same way that the many of our services do when you're storing data. We announced some config rules today to help customers better understand the access policies on their S3 buckets. So yeah, good stuff. >> John: Busy day, >> Busy day. >> I mean just from a security standpoint, when you are working with a new client, do you ever uncover, or do they discover things about themselves that need to be addressed? >> Bill: Yeah. I think the number one thing, and it's true for many organizations when they move to the cloud, is they want that agility, right? And when we talk to security organizations, one of the top things we advise them on is how to move faster. As much as we're having great conversations about WAF and Shield, the Web Application Firewall, and Shield, our D-DOS solution, Inspector, which performs configuration assessments, all the security services that we've launched, we're also having pretty deep conversations with security organizations these days about CodeStar, CodePipeline, CodeDeploy, and then DevOps tool chains, because security can get that fast engineering principles down, and their just as responsive. It also puts security in the hands of engineers and developers, you know that's the kind of conversations we're having. They discover that they kind of need to get a little closer to how development does their business. You know, talking in the same vocabulary as engineering and development. That's one of the things I think customers discover. Also it's a real opportunity, right? So if you don't have to look after a data center footprints and all the patch panels and switches and routers and firewalls and load balancers and things you have on premises, it really does allow a shift in focus for security organizations to focus on code quality, focus on user behavior, focus on a lot of things that every CSO would like to spend more time on. >> Bill, one of the things a lot of companies struggle with is how they keep up with everything that's happening, all the change there, when I talk to my friends in the security industry it's one of the things that they're most excited about. Is we need to be up on the latest fixes and the patches, and when I go to public cloud you don't ask somebody "Hey what version of AWS or Azure are you running on?" You're going to take care of that behind the scenes. How do you manage the application portfolio for customers, and get them into that framework so that they can, you know we were talking about, Cameron, Jean Kim just buy into that as security just becomes part of the process, as I get more out of agile. >> Yeah, so the question is really about helping customers understand all the services, and really get them integrated deeply. A couple of things, certainly the well architected framework, like I mentioned, is helpful for that. We have solution architects, professional services consultants, a very, very rich partner ecosystem that helps customers. A lot of training for security, there's some free training online, there's classroom, instructor-led training as well, so that training piece is important. I think the solutions are better together. We have a lot of great building blocks, but when you look at something like CloudTrail Cloud Watch Events, and Lambda together, we try and talk about the solutions, not just the individual building blocks. I think that's one key component too, to help them understand how to solve a security problem. Take, for example, monitoring the provisioning of identities and roles and permissions. We really want customers to know that that CloudTrail log, when someone attaches a role to a policy, that can go all the way to a slack channel, that can go all the way to a ticket system. You really want to talk about the end-to-end integration with our customers. Really to help them keep pace with our pace of innovation. We really try and get the blog in front of them, the security blog is a great source of information for all the security announcements we make. Follow Jeff Bar's Twitter, a bunch of things to help keep pace with all of our launches and things, yeah. >> You brought up server lists, if I look at the container space, which is related of course, security has been one of those questions. Bring us up to speed as to where you are with security containers, Lambda- >> Sure, I think Lambda's isolation is very strong, in Lambda we have a really confidence in the tenant isolation model for those functions. The nice thing about server lists is, when there's no code running, you really don't have a surface area to defend. I think from a security perspective, if you were building an application today, and you go to your security team and say "I'd really like to build this little piece of code, and tie these pieces of code together, and when they're not running there's nothing there that you need to defend." Or, would I like to build this big set of operating systems and fleet management and all the things I have to do. It's kind of a, it's a pretty easy conversation right? All the primitives are there in server-less. You have strong cryptography TLSM endpoints, you've got the IM policy framework so that identity access management has really consistent language across all the services, so principles, actions, resources, and conditions is the same across every service. It's not any different for server-less, so they can leverage the knowledge they have of how to manage identities and authorization in the same way. You've got integration of CloudTrail. So all the primitives are there, so customers can focus on their code and being builders. >> Stu: So it sounds like that's part of the way to attach security for IOT then if we're using those. >> I think for IOT it's a very similar architecture too, so you have similar policies that you can apply to what a device you can write to in the cloud. We have a really strong set of authorization and authentication features within the IOT platform so that it makes it easy for developers to build things, deploy them, and maintain them in a secure state. But you can go back to the Well-Architected Framework and the CAF, the Cloud Adoption Framework, you take those five key areas, you know identity, detective controls, infrastructure security, data protection, and IR incident response. It's pretty similar across all the different services. >> It just comes back to the fundamentals. >> It does, absolutely. And for customers, you know those control objectives haven't changed right? They have those control objectives today, they'll have them in the cloud, and we just want to make it easier and faster. >> Well Bill, thanks for being with us. >> You bet, thank you very much. >> Good to have you on theCUBE, look forward to seeing you again for the second time around. >> See you then hopefully >> Bill Shin, from AWS joining us here on theCUBE. Continuing our coverage from the AWS Summit here in New York in just a bit. (techno music)
SUMMARY :
Brought to you by Amazon Web Services. Glad to have you here on theCUBE So I just hit on some of the high points, We have a framework called the Well-Architected Framework, "Every day when you wake up, and then be able to alert and alarm Actually I got a question from the community deals more with the clustering that you don't have to do. and things you have on premises, and when I go to public cloud you don't ask somebody that can go all the way to a slack channel, if I look at the container space, and all the things I have to do. Stu: So it sounds like that's part of the way to attach to what a device you can write to in the cloud. And for customers, you know those control objectives Good to have you on theCUBE, Continuing our coverage from the AWS Summit
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
AWS | ORGANIZATION | 0.99+ |
John Walls | PERSON | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
John | PERSON | 0.99+ |
Bill Shin | PERSON | 0.99+ |
Amazon Web Services | ORGANIZATION | 0.99+ |
Andy Jassey | PERSON | 0.99+ |
Bill Shinn | PERSON | 0.99+ |
Cameron | PERSON | 0.99+ |
New York City | LOCATION | 0.99+ |
New York | LOCATION | 0.99+ |
last year | DATE | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Jean Kim | PERSON | 0.99+ |
first time | QUANTITY | 0.99+ |
Bill | PERSON | 0.99+ |
Macie | ORGANIZATION | 0.99+ |
second time | QUANTITY | 0.99+ |
Jeff Bar | PERSON | 0.99+ |
one | QUANTITY | 0.99+ |
S3 | TITLE | 0.99+ |
first conversations | QUANTITY | 0.99+ |
first | QUANTITY | 0.98+ |
First time | QUANTITY | 0.98+ |
Cloud Adoption Framework | TITLE | 0.98+ |
Lambda | TITLE | 0.98+ |
WAF | TITLE | 0.98+ |
Javits Center | LOCATION | 0.98+ |
AWS Summit 2017 | EVENT | 0.98+ |
trillions of objects | QUANTITY | 0.98+ |
today | DATE | 0.98+ |
CloudTrail | TITLE | 0.97+ |
CodeDeploy | ORGANIZATION | 0.97+ |
CodePipeline | ORGANIZATION | 0.97+ |
D-DOS | TITLE | 0.96+ |
Cloud HSM | TITLE | 0.96+ |
Manhattan | LOCATION | 0.95+ |
JDPR | ORGANIZATION | 0.94+ |
agile | TITLE | 0.94+ |
one key component | QUANTITY | 0.93+ |
AWS Summit | EVENT | 0.93+ |
five key areas | QUANTITY | 0.93+ |
Cloud Watch Events | TITLE | 0.91+ |
AWS Summit New York City 2017 | EVENT | 0.91+ |
CodeStar | ORGANIZATION | 0.88+ |
CUBE | ORGANIZATION | 0.87+ |
Shield | TITLE | 0.87+ |
US | LOCATION | 0.84+ |
midtown Manhattan | LOCATION | 0.83+ |
Macie | COMMERCIAL_ITEM | 0.82+ |
Azure | TITLE | 0.82+ |
ORGANIZATION | 0.81+ | |
West Coast | LOCATION | 0.77+ |
at least three new announcements | QUANTITY | 0.76+ |
S3 | COMMERCIAL_ITEM | 0.57+ |
European | OTHER | 0.56+ |
DevOps | ORGANIZATION | 0.55+ |
CSO | ORGANIZATION | 0.55+ |
CAF | TITLE | 0.55+ |
theCUBE | ORGANIZATION | 0.53+ |
Jay Chaudhry, Zscaler | CUBE Conversations July 2017
>> Hey, welcome back, everybody. Jeffrey here with the cue, we're having acute conversation that are probably out. The studio's a little bit of a break in the conference schedule, which means we're gonna have a little bit more intimate conversations outside of the context of a show we're really excited to have. Our next guest is running $1,000,000,000 company evaluation that been added for almost 10 years. Cloud first from the beginning, way ahead of the curve. And I think the curves probably kind of catching up to him in terms of really thinking about security in a cloud based way. It's J. Charger. He's the founder and CEO of Ze Scaler. J Welcome. Thank you, Jeff. So we've had a few of your associates on, but we've never had you on. So a great to have you on the Cube >> appreciate the opportunity. >> Absolutely. So you guys from the get go really took a cloud native approach security when everyone is building appliances and shipping appliances and a beautiful fronts and flashing lights and everyone's neighborhood appliances. You took a very different tact explain kind of your thinking when you founded the company. >> So all the companies I had done. I looked for a fuss to move her advantage. So if you are first mover, then you got significant advantage. A lot of others. So look at 2008 we were goingto Internet for a whole range of service is lots of information sitting there from weather to news and all the other stuff right now on Cloud Applications. Point of view sales force was doing very well. Net Suite was doing well, and I have been using sales force in that suite and all of my start up since the year 2001. Okay, when each of them was under 10,000,000 in sales. So my notion was simple. Will more and more information sit on the Internet? Answer was yes. If sales force the nets weed is so good, why won't other applications move? The cloud answer was yes. So if that's the case, why should security appliances sit in the data? Security should sit in the cloud as well. So with that simple notion, I said, if I start a new company, no legacy boxes to what he bought, you start a clean slate, clean architecture designed for the cloud. What we like to call. Born in the cloud for a cloud. That's what I did. What >> great foresight. I mean trying in 2008 if tha the enterprise Adoption of cloud I mean sales was really was the first application to drive that. I mean, I just think poor 80 p gets no credit for being really the earliest cloud that they weren't really a solution right there. That's the service provider. But sales force really kind of cracked the enterprise, not four. Trust with SAS application wasn't even turn back back then. So So, taking a cloud approach to security. Very different strategy than an appliance. And, you know, credit to you for thinking about you know, you could no longer build the wall in the moat anymore. Creon and Internet world. Yeah. >> So my no show, no simple. The old world off security Waas What you just mentioned castle and moat. I am safe in my castle. But when people wanted to go out to call it greener pastures, right, you needed to build a drawbridge. And that's the kind of drawbridge these appliances bills. And then if you really want to be outside for business and all other reasons you're not coming in right? So notion of Castle and Motors, No good. So we said, Let's give it up. So let's get away from the notion that I must secure my network on which users and applications are sitting. I really need to make sure the right user has access to write application or service, which may be on the Internet, which may be on a public cloud, which may be a sass application like Salesforce. Or it may be the data center. So we really thought very differently, Right? Network security will become irrelevant. Internet will become your corporate network, and we connect the right user to write application, Right? Very logical. It took us a while to evangelize and convince a bunch of customers, right. But as G and Nestle and Seaman's off, the Wolf jumped on it because they love the technology. We got fair amount of momentum, and then lots of other enterprises came along >> right, right. It's so interesting that nobody ever really talked about the Internet, has an application delivery platform back in the day, right? It was just it was Bbn. And then we had a few pictures. Thank you Netscape, but really to think of the Internet as a way to deliver application and an enterprise applications with great foresight that you had there. >> Yes. So I think we built >> on the foresight off sales force in that suite and other information sources on the great. I >> came from security side off it. I built a number of companies that build and sold appliances, right. But it was obvious that in the new world, security will become a service. So think of cloud computing. People get surprised about cloud computing being big. It's natural. It's a utility service. If I'm in the business on manufacturing veg, it's a B and C. Gray computing is not my business. If just like I plug into the wall socket, get electricity right, I should be able to turn on some device and terminal and access abdication, sitting somewhere right and managed by someone right and all. So we re needed good connectivity over the Internet to do that. As that has matured over the past 10 years, as devices have become more capable and mobile, it's a natural way to go to cloud computing, and for us to do cloud security was a very natural >> threat. Right. So then you use right place right time, right. So then you picked up on a couple These other tremendous trends that that that ah cloud centric application really take advantage of first is mobile. Next is you know, B Bring your own global right B y o d. And then this this funky little thing called Shadow I T. Which Amazon enabled by having a data center of the swipe of a credit card. Your application, your technology. This works great with all those various kind of access methodologies. Still consistently right >> now. And that is because the traditional security vendors so called network security vendors but protecting the network they assumed that you sat in an office on the Net for great. Only if you're outside. You came back to the network through vpn, right? We assume that Forget the network. Ah, user sitting in the office or at home or coffee shop airport has to get to some destination over some network. That's not What about securing the net for Let's have a policy and security. It says Whether you are on a PC auto mobile phone, you're simply connecting through our security check post. Do what you want to go. So mobile and clothes for the natural. Two things mobile became the user cloud became the destination, and Internet became the connector off the two. And we became the policy check post in the middle. >> So what? So what do you do in terms of your security application? Are you looking at, you know, Mac addresses? Are you looking at multi factor authentication? Cause I would assume if you're not guarding the network per se, you're really must be all about the identity and the rules that go along with that identity. >> It's a good question, so user needs to get to certain applications, and service is so you put them into buckets. First is external service is external means that a company doesn't need to management, and that is either open Internet, which could be Google Search could be Facebook lengthen and type of stuff. Or it could be SAS applications that Salesforce offers on Microsoft Office E 65. So in that case, we want to make sure that been uses. Go to those sites. Nothing bad should comment. That means the malware stuff and nothing good chili con you confidential information. So we are inspecting traffic going in and out. So we are about inspecting the traffic, the packets, the packets to make sure this is not malicious. Okay, Now, for authentication, we use third party serves like Microsoft A D or Octagon. They tell us who the user is into what the group is. And based on that sitting in the traffic path were that I who enforce the policy so that is for external applications. Okay, the second part of the secular service, what we called the school a private access is to make sure that you can get to your internal applications. Either in your data center, all this sitting in a public cloud, such chance as your eight of us there were less. Whatever mouth we're more worried about is the right person getting to the right application and the other checks are different. There you are connecting the right parties, Okay. Unless worried about >> security, and then does it work with the existing, um, turn of the of, you know, the internal corporate systems. Who identified you? Integrate, I assume, with all those existing types of systems. >> Yes. So we look at the destination you did. Existing system could be sitting on in your data center or in the cloud. It doesn't really matter. We look at your data center as a destination. OK, we look at stuff sitting in Azure as a destiny. >> And then and then this new little twist. So obviously Salesforce's been very successfully referenced them a few times, and I just like to point to the new 60 story tower. If anyone ever questions whether people think Cloud of Secures, go look downtown at the new school. But there's a big new entrance in play on kind of the Enterprise corporate SAS side. And that's office 3 65 It's not that noone you are still relatively new. I'm just curious to get your perspective. You've been at this for 10 years? Almost, um, the impact of that application specifically to this evolution to really pure SAS base model, getting more and more of the enterprise software stack. >> So number one application in any enterprise is email >> before you gotta think that's gonna be your next started. We gotta fix today after another e >> mail calendar ring sharing files and what it used to sit in your data center and you had to buy deploy manage Sutter was with in a Microsoft exchange. So Microsoft said, Forget about you managing it. I've will manage your exchange, uh, with a new name, all 50 65 in the clout so you don't what he bought it and are You come to me and I'll take care off it. I think it's a brilliant move by Microsoft, and customers are ready to give up. The headaches are maintaining the boxes, the software and sordid and everything. Right now, when the biggest application moves the cloud, every CEO pays attention to it. So as Office God embraced the corporate network start to break. Now, why would that happen if you aren't in 50 cities and on the globe, your exchanges? Sitting in Chicago Data Center every employee from every city came to Chicago. Did know Microsoft Office. This is sun setting something. Why should every employee go to Chicago? That's the networks on and then try to go to cloud right? So they're back. Haul over traditional corporate network using Mpls technology very expensive, and then they go to them. Then they go to the Internet to go to office. If the 65 slow slow. No one likes it. Microsatellite. >> Get too damn slow >> speed. OnlyTest Fetal light. You can only go so far. It's >> not fast. If you're going around the world and you're waiting for something, I >> have to go to New York City to my data center so I could come to a local site in San Francisco. It is hard, right? Right, And that's what our traditional networks have done. That's what traditional security boxes down what Z's killer says. Don't worry about having two or three gateways to the Internet. You have as many gay tricks as your employees because every employee simply points to the Z's. Killers near this data center were the security stack. We take care of security inspection and policy, and you get to where you need to get to the fastest way. So Office 3 65 is a great catalyst for the skin. Asked customers of struggling with user experience and the traffic getting clogged on the traditional network. We go in and say, if you did local Internet breakout, you go direct, but you couldn't go direct without us because you need some security check personally. So we are the checkpost sitting 100 data centers around the globe and uses a happy customer. We are happy. >> So I was gonna be my next point. Begs the question, How many access points do you guys have just answered? You have hundreds. So you worked with local Coehlo. You got a short You got a short hop from your device into the sea scaler system and then you you're into your network. >> You know, we are deployed and 100 data center. These are generally cola is coming from leading vendors. Maybe it connects maybe level three tire cities of gold and the goal is to shorten the distance. I'll tell you two interesting anecdotes. I talked to a C i o last year. I said, How many employees do you have? He said 10,000 said, How many Internet gateways do you have? I tell you, it's safe. I he's a 10,000. I said What? He said. Every employee has a laptop and laptop goes with it. Employee goes and indirectly goes the Internet. It's a gate for you, Right? Then he said, Sorry, I'm Miss Booke. Every employee is a smartphone, and many have tablets to have 25,000 gate. So if you start thinking that way, trying to take all the traffic back to some security appliance is sitting in a data center or 10 branch offices, right? Makes no sense. So that's where we come in. And I had an interesting discussion with a very large consumer company out of Europe. I went to see them to one of her early customers. I >> met the >> head of security. I said, I'm here to understand how well these killers working. Since our security is so good, you must be loving it. He smiled, and he said, I love you security, but I love something more than your security. I said, Huh? What is that? He said. Imagine if the world had four airport hubs to connect through and you are a world traveler. You'll be missing, he said. I have 160,000 employees in hundreds, 30 countries. I have four Internet gateways with security appliance sitting there and everyone has to go to one of those four before they get out, right, so they were miserable. Now they are blogging on the Internet than entrant has become very fast, she said. As a C so I love it because security leaders are blamed for slowing you down in the name of security. Now I have made uses happy abroad in better security. So it's all wonderful. >> Hey, sounds like you're a virtual networking company that Trojan horsed in as a security company >> way. So let's put it this way. I >> mean, the value problem. Like I'm just I'm teasing you. But it's really interesting, you know, kind of twisted tale, >> so don't know you actually making a very good point. So So this is what happening Every c. I is talking about digital transformation through I t transmission Right now. If you start drilling down, what does that mean? Applications are moving in the cloud. So that's the application transformation going on because applications are no longer in your data center, which was the central gravity. If applications the move to the cloud, the network that designed to bring everything to the data center becomes irrelevant. It's no good. So no companies are transforming the data center bit. Sorry, they're transforming the network not to transform network so you could directly go to the application. The only thing that's holding you back is security, so we essentially built a new type of security, so we're bringing security transformation, which is needed. Do transform your network and transfer your application. Right? So that's why people customers who buy us is typically the head off application, head of security and head of networking. All three come together because transformation doesn't happen in isolation. Traditional security boxes are bought, typically by the security team only because they said, put a box here, you need to inspect the traffic. We go in and say the old world off ideas change. Let me help you transform to the New World. Why we call it cloned enabled enterprise, right? And that's what we come >> pretty interesting, too, when you think of the impact that not only are you leveraging us and security layer in this cloud and getting in the way of the phone traffic in the laptop traffic, but to as people migrate to Maura and Maur of these enterprise SAS APS, you're leveraging their security infrastructure, which is usually significantly bigger than any particular individual company can ever afford. >> That that's correct. So a point there so sales force an enterprise doesn't need to worry about protecting Salesforce, they need to make sure they can have a shortest path and the right user is getting so. We help as a policy jackboots in the middle, and also we make sure employees on downloading confidential customer information and sending out in Gmail to somebody else. But when applications moved to Azure or eight of us, you as an enterprise have to what he bought securing it if you expose them. If there is all to the Internet, then somebody can discover you. Somebody can do denial of service attack. So how do you handle that? So that's where we come in. We kind of say even 1,000,000,000 applications are in azure. I will give you the shortest bat with all the technology that you need to secure your internal >> happy. It's interesting because there's been recent breaches reported at Amazon, where the Emma's the eight of US customer didn't secure their own instance. Inside of eight of us, it wasn't an eight of US problems configuration problem >> or it could be the policy problem or possible. Somebody, for example, came into your data center over vpn, and once they're on you network, they can have what we call the lateral boom and they can go around to see what's out there. And they could get to applications. So we overcome all those security >> issues. Okay, so you've been at this for a while. 3 65 is a game changer and kind of accelerating as you look forward, Um, what excites you? What scares you? You know, where do you see kind of security world evolving? Obviously, you know, here in the news all the time that the attacks now or, you know, oftentimes nation states and you know it's it's the security challenges grown significantly higher than just the crazy hacker working out of his mom's basement. A CZ You see the evolution? You know what, What, what's kind of scary and what's exciting. >> I think the scary part is inertia. People kind of say this high done security than the castle and moat. That's still still because they feel like I can put my arms that only I can see the drawbridge. And I got to see the airplane right over the missing on that. So so one someone gets into your castle, you're in trouble, right? So in the new approach we advocate, don't worry about castles, and moats. The desk applications are out there somewhere. Your users are out there somewhere, right? And they just need to reach the right application. So we are focuses connecting the right people. Now, more and more devices coming in. We all here. But I owe tease out. The I. O. T. At the end of the day is a copier printer of video camera or some machine controls >> or a nuclear power plant. >> They all need to talk to something, something right if they got hijacked. You thinkyou nuclear power plant is sending information about its health to place a. But it's going to Ukraine, right? That's a problem. How do you make sure that the coyote controls in a plant are talking right parties? So we actually sit in the middle, are connecting the party. So that's another area for us. For potential, right? Looking at opportunity. >> So another big one like mobile and in 3 65 wasn't enough. Now you have I a t. >> It's a natural hanging out with you. So today, every day we see tens of thousands of cameras and copiers calling the Internet, and customers have no idea know why are they calling. Generally, there's no malicious motive. The vendor wanted to know if the toner is down or not. Are things are working fine, but they have no security control. R. C So does a demo from the Internet. He logs onto the camera, are the printer and copier and actually gets can show that information can be obtained. So those are some of the things we must control and protect. And you do it not by doing network security but a policy base access from a right device to alright, destiny. >> So, are you seeing an increase in the in the, you know, kind of machine machine? A tremendous amount of >> traffic machine to machine. So is io to traffic, and there's a machine to machine traffic. So when you have a bunch of applications said in our data center and you a bunch of applications sitting an azure eight of us, they need to talk. So lot of that traffic goes through Z Skinner. Okay, so we're long enforcing it, then you're an application that needs to go and get, say, some market pricing information from Internet. So the machine a sitting in your data center or in azure is calling someone out. There are some server to get that information. So we come in in between as a checkpost too. Have right connectivity. >> You're saying I proper. Same value difference. Very simple, but elegant. J I'm hanging out of the more you see now, the touch to nowhere to be at the right time. We're having fun. It's a great story, and and I really appreciate you taking a few minutes out of your day to stop. But I >> have a great team that makes it happen. >> That's a big piece of it. Well, and good leadership as well. Obviously >> great leaders in the company. >> All right, Thank you. J Child Reza, founder and CEO of Ze Scaler. Check it out. Thanks again for stopping by the Cube. I'm Jeff. Rick. Thanks for watching. We'll catch you next time.
SUMMARY :
So a great to have you on the Cube So you guys from the get go really took a cloud So if you are first mover, then you got significant advantage. So So, taking a cloud approach to security. So let's get away from the notion that I must secure my network on which It's so interesting that nobody ever really talked about the Internet, has an application on the foresight off sales force in that suite and other information sources connectivity over the Internet to do that. So then you use right place right time, right. So mobile and clothes for the natural. So what do you do in terms of your security application? That means the malware stuff and nothing good chili con you confidential of the of, you know, the internal corporate systems. We look at your data center as a destination. And that's office 3 65 It's not that noone you are still relatively new. before you gotta think that's gonna be your next started. So as Office God embraced the You can only go so far. If you're going around the world and you're waiting for something, I We go in and say, if you did local Internet breakout, you go direct, device into the sea scaler system and then you you're into your network. So if you start thinking that way, hubs to connect through and you are a world traveler. So let's put it this way. you know, kind of twisted tale, So that's the application transformation going on because applications pretty interesting, too, when you think of the impact that not only are you leveraging us and security layer all the technology that you need to secure your internal the eight of US customer didn't secure their own instance. So we overcome all Obviously, you know, here in the news all the time that the attacks now or, you know, So in the new approach we advocate, don't worry about So we actually sit in the middle, are connecting the party. Now you have I a t. And you do it not by doing So the machine a sitting in your data center out of the more you see now, the touch to nowhere to be at the right time. That's a big piece of it. Thanks again for stopping by the Cube.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Jeff | PERSON | 0.99+ |
Chicago | LOCATION | 0.99+ |
Jeffrey | PERSON | 0.99+ |
Jay Chaudhry | PERSON | 0.99+ |
2008 | DATE | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
July 2017 | DATE | 0.99+ |
$1,000,000,000 | QUANTITY | 0.99+ |
two | QUANTITY | 0.99+ |
San Francisco | LOCATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
eight | QUANTITY | 0.99+ |
New York City | LOCATION | 0.99+ |
hundreds | QUANTITY | 0.99+ |
100 data centers | QUANTITY | 0.99+ |
Rick | PERSON | 0.99+ |
J Child Reza | PERSON | 0.99+ |
50 cities | QUANTITY | 0.99+ |
10 years | QUANTITY | 0.99+ |
Ukraine | LOCATION | 0.99+ |
160,000 employees | QUANTITY | 0.99+ |
Gmail | TITLE | 0.99+ |
Booke | PERSON | 0.99+ |
second part | QUANTITY | 0.99+ |
2001 | DATE | 0.99+ |
today | DATE | 0.99+ |
First | QUANTITY | 0.99+ |
J. Charger | PERSON | 0.99+ |
one | QUANTITY | 0.99+ |
10,000 | QUANTITY | 0.99+ |
two interesting anecdotes | QUANTITY | 0.99+ |
Coehlo | ORGANIZATION | 0.98+ |
first application | QUANTITY | 0.98+ |
Bbn | ORGANIZATION | 0.98+ |
100 data center | QUANTITY | 0.98+ |
four | QUANTITY | 0.98+ |
80 p | QUANTITY | 0.98+ |
last year | DATE | 0.98+ |
US | LOCATION | 0.98+ |
under 10,000,000 | QUANTITY | 0.98+ |
Ze Scaler | ORGANIZATION | 0.98+ |
each | QUANTITY | 0.98+ |
Chicago Data Center | LOCATION | 0.98+ |
three gateways | QUANTITY | 0.97+ |
60 story | QUANTITY | 0.97+ |
ORGANIZATION | 0.97+ | |
Two things | QUANTITY | 0.96+ |
almost 10 years | QUANTITY | 0.96+ |
first | QUANTITY | 0.96+ |
1,000,000,000 applications | QUANTITY | 0.96+ |
Mac | COMMERCIAL_ITEM | 0.95+ |
first mover | QUANTITY | 0.95+ |
65 slow slow | QUANTITY | 0.94+ |
Salesforce | ORGANIZATION | 0.94+ |
four airport hubs | QUANTITY | 0.94+ |
Azure | TITLE | 0.94+ |
tens of thousands of cameras | QUANTITY | 0.93+ |
50 65 | OTHER | 0.93+ |
Netscape | ORGANIZATION | 0.93+ |
Zscaler | PERSON | 0.92+ |
Microsatellite | ORGANIZATION | 0.92+ |
Office | TITLE | 0.92+ |
Cube | ORGANIZATION | 0.92+ |
hundreds, 30 countries | QUANTITY | 0.92+ |
SAS | ORGANIZATION | 0.89+ |
Salesforce | TITLE | 0.89+ |
Microsoft Office | ORGANIZATION | 0.88+ |
Maura | PERSON | 0.87+ |
3 65 | OTHER | 0.87+ |
25,000 gate | QUANTITY | 0.87+ |
Maur | PERSON | 0.87+ |
J | PERSON | 0.86+ |
Emma | ORGANIZATION | 0.85+ |
three | QUANTITY | 0.84+ |
10 branch offices | QUANTITY | 0.84+ |
G and | ORGANIZATION | 0.78+ |
Office E 65 | TITLE | 0.78+ |
Octagon | ORGANIZATION | 0.77+ |
Lenovo Transform 2017 Keynote
(upbeat techno music) >> Announcer: Good morning ladies and gentlemen. This is Lenovo Transform. Please welcome to the stage Lenovo's Rod Lappin. (upbeat instrumental) >> Alright, ladies and gentlemen. Here we go. I was out the back having a chat. A bit faster than I expected. How are you all doing this morning? (crowd cheers) >> Good? How fantastic is it to be in New York City? (crowd applauds) Excellent. So my name's Rod Lappin. I'm with the Data Center Group, obviously. I do basically anything that touches customers from our sales people, our pre-sales engineers, our architects, et cetera, all the way through to our channel partner sales engagement globally. So that's my job, but enough of that, okay? So the weather this morning, absolutely fantastic. Not a cloud in the sky, perfect. A little bit different to how it was yesterday, right? I want to thank all of you because I know a lot of you had a lot of commuting issues getting into New York yesterday with all the storms. We have a lot of people from international and domestic travel caught up in obviously the network, which blows my mind, actually, but we have a lot of people here from Europe, obviously, a lot of analysts and media people here as well as customers who were caught up in circling around the airport apparently for hours. So a big round of applause for our team from Europe. (audience applauds) Thank you for coming. We have some people who commuted a very short distance. For example, our own server general manager, Cameron (mumbles), he's out the back there. Cameron, how long did it take you to get from Raleigh to New York? An hour-and-a-half flight? >> Cameron: 17 hours. >> 17 hours, ladies and gentleman. That's a fantastic distance. I think that's amazing. But I know a lot of us, obviously, in the United States have come a long way with the storms, obviously very tough, but I'm going to call out one individual. Shaneil from Spotless. Where are you Shaneil, you're here somewhere? There he is from Australia. Shaneil how long did it take you to come in from Australia? 25 hour, ladies and gentleman. A big round of applause. That's a pretty big effort. Shaneil actually I want you to stand up, if you don't mind. I've got a seat here right next to my CEO. You've gone the longest distance. How about a big round of applause for Shaneil. We'll put him in my seat, next to YY. Honestly, Shaneil, you're doing me a favor. Okay ladies and gentlemen, we've got a big day today. Obviously, my seat now taken there, fantastic. Obviously New York City, the absolute pinnacle of globalization. I first came to New York in 1996, which was before a lot of people in the room were born, unfortunately for me these days. Was completely in awe. I obviously went to a Yankees game, had no clue what was going on, didn't understand anything to do with baseball. Then I went and saw Patrick Ewing. Some of you would remember Patrick Ewing. Saw the Knicks play basketball. Had no idea what was going on. Obviously, from Australia, and somewhat slightly height challenged, basketball was not my thing but loved it. I really left that game... That was the first game of basketball I'd ever seen. Left that game realizing that effectively the guy throws the ball up at the beginning, someone taps it, that team gets it, they run it, they put it in the basket, then the other team gets it, they put it in the basket, the other team gets it, and that's basically the entire game. So I haven't really progressed from that sort of learning or understanding of basketball since then, but for me, personally, being here in New York, and obviously presenting with all of you guys today, it's really humbling from obviously some of you would have picked my accent, I'm also from Australia. From the north shore of Sydney. To be here is just a fantastic, fantastic event. So welcome ladies and gentlemen to Transform, part of our tech world series globally in our event series and our event season here at Lenovo. So once again, big round of applause. Thank you for coming (audience applauds). Today, basically, is the culmination of what I would classify as a very large journey. Many of you have been with us on that. Customers, partners, media, analysts obviously. We've got quite a lot of our industry analysts in the room. I know Matt Eastwood yesterday was on a train because he sent a Tweet out saying there's 170 people on the WIFI network. He was obviously a bit concerned he was going to get-- Pat Moorhead, he got in at 3:30 this morning, obviously from traveling here as well with some of the challenges with the transportation, so we've got a lot of people in the room that have been giving us advice over the last two years. I think all of our employees are joining us live. All of our partners and customers through the stream. As well as everybody in this packed-out room. We're very very excited about what we're going to be talking to you all today. I want to have a special thanks obviously to our R&D team in Raleigh and around the world. They've also been very very focused on what they've delivered for us today, and it's really important for them to also see the culmination of this great event. And like I mentioned, this is really the feedback. It's not just a Lenovo launch. This is a launch based on the feedback from our partners, our customers, our employees, the analysts. We've been talking to all of you about what we want to be when we grow up from a Data Center Group, and I think you're going to hear some really exciting stuff from some of the speakers today and in the demo and breakout sessions that we have after the event. These last two years, we've really transformed the organization, and that's one of the reasons why that theme is part of our Tech World Series today. We're very very confident in our future, obviously, and where the company's going. It's really important for all of you to understand today and take every single snippet that YY, Kirk, and Christian talk about today in the main session, and then our presenters in the demo sections on what Lenovo's actually doing for its future and how we're positioning the company, obviously, for that future and how the transformation, the digital transformation, is going ahead globally. So, all right, we are now going to step into our Transform event. And I've got a quick agenda statement for you. The very first thing is we're going to hear from YY, our chairman and CEO. He's going to discuss artificial intelligence, the evolution of our society and how Lenovo is clearly positioning itself in the industry. Then, obviously, you're going to hear from Kirk Skaugen, our president of the Data Center Group, our new boss. He's going to talk about how long he's been with the company and the transformation, once again, we're making, very specifically to the Data Center Group and how much of a difference we're making to society and some of our investments. Christian Teismann, our SVP and general manager of our client business is going to talk about the 25 years of ThinkPad. This year is the 25-year anniversary of our ThinkPad product. Easily the most successful brand in our client branch or client branch globally of any vendor. Most successful brand we've had launched, and this afternoon breakout sessions, obviously, with our keynotes, fantastic sessions. Make sure you actually attend all of those after this main arena here. Now, once again, listen, ask questions, and make sure you're giving us feedback. One of the things about Lenovo that we say all the time... There is no room for arrogance in our company. Every single person in this room is a customer, partner, analyst, or an employee. We love your feedback. It's only through your feedback that we continue to improve. And it's really important that through all of the sessions where the Q&As happen, breakouts afterwards, you're giving us feedback on what you want to see from us as an organization as we go forward. All right, so what were you doing 25 years ago? I spoke about ThinkPad being 25 years old, but let me ask you this. I bet you any money that no one here knew that our x86 business is also 25 years old. So, this year, we have both our ThinkPad and our x86 anniversaries for 25 years. Let me tell you. What were you guys doing 25 years ago? There's me, 25 years ago. It's a bit scary, isn't it? It's very svelte and athletic and a lot lighter than I am today. It makes me feel a little bit conscious. And you can see the black and white shot. It shows you that even if you're really really short and you come from the wrong side of the tracks to make some extra cash, you can still do some modeling as long as no one else is in the photo to give anyone any perspective, so very important. I think I might have got one photo shoot out of that, I don't know. I had to do it, I needed the money. Let me show you another couple of photos. Very interesting, how's this guy? How cool does he look? Very svelte and athletic. I think there's no doubt. He looks much much cooler than I do. Okay, so ladies and gentlemen, without further ado, it gives me great honor to obviously introduce our very very first guest to the stage. Ladies and gentlemen, our chairman and CEO, Yuanqing Yang. or as we like to call him, YY. A big round of applause, thank you. (upbeat techno instrumental) >> Good morning everyone. Thank you, Rod, for your introduction. Actually, I didn't think I was younger than you (mumbles). I can't think of another city more fitting to host the Transform event than New York. A city that has transformed from a humble trading post 400 years ago to one of the most vibrant cities in the world today. It is a perfect symbol of transformation of our world. The rapid and the deep transformations that have propelled us from the steam engine to the Internet era in just 200 years. Looking back at 200 years ago, there was only a few companies that operated on a global scale. The total value of the world's economy was around $188 billion U.S. dollars. Today, it is only $180 for each person on earth. Today, there are thousands of independent global companies that compete to sell everything, from corn and crude oil to servers and software. They drive a robust global economy was over $75 trillion or $1,000 per person. Think about it. The global economy has multiplied almost 450 times in just two centuries. What is even more remarkable is that the economy has almost doubled every 15 years since 1950. These are significant transformation for businesses and for the world and our tiny slice of pie. This transformation is the result of the greatest advancement in technology in human history. Not one but three industrial revolutions have happened over the last 200 years. Even though those revolutions created remarkable change, they were just the beginning. Today, we are standing at the beginning of the fourth revolution. This revolution will transform how we work (mumbles) in ways that no one could imagine in the 18th century or even just 18 months ago. You are the people who will lead this revolution. Along with Lenovo, we will redefine IT. IT is no longer just information technology. It's intelligent technology, intelligent transformation. A transformation that is driven by big data called computing and artificial intelligence. Even the transition from PC Internet to mobile Internet is a big leap. Today, we are facing yet another big leap from the mobile Internet to the Smart Internet or intelligent Internet. In this Smart Internet era, Cloud enables devices, such as PCs, Smart phones, Smart speakers, Smart TVs. (mumbles) to provide the content and the services. But the evolution does not stop them. Ultimately, almost everything around us will become Smart, with building computing, storage, and networking capabilities. That's what we call the device plus Cloud transformation. These Smart devices, incorporated with various sensors, will continuously sense our environment and send data about our world to the Cloud. (mumbles) the process of this ever-increasing big data and to support the delivery of Cloud content and services, the data center infrastructure is also transforming to be more agile, flexible, and intelligent. That's what we call the infrastructure plus Cloud transformation. But most importantly, it is the human wisdom, the people learning algorithm vigorously improved by engineers that enables artificial intelligence to learn from big data and make everything around us smarter. With big data collected from Smart devices, computing power of the new infrastructure under the trend artificial intelligence, we can understand the world around us more accurately and make smarter decisions. We can make life better, work easier, and society safer and healthy. Think about what is already possible as we start this transformation. Smart Assistants can help you place orders online with a voice command. Driverless cars can run on the same road as traditional cars. (mumbles) can help troubleshoot customers problems, and the virtual doctors already diagnose basic symptoms. This list goes on and on. Like every revolution before it, intelligent transformation, will fundamentally change the nature of business. Understanding and preparing for that will be the key for the growth and the success of your business. The first industrial revolution made it possible to maximize production. Water and steam power let us go from making things by hand to making them by machine. This transformed how fast things could be produced. It drove the quantity of merchandise made and led to massive increase in trade. With this revolution, business scale expanded, and the number of customers exploded. Fifty years later, the second industrial revolution made it necessary to organize a business like the modern enterprise, electric power, and the telegraph communication made business faster and more complex, challenging businesses to become more efficient and meeting entirely new customer demands. In our own lifetimes, we have witnessed the third industrial revolution, which made it possible to digitize the enterprise. The development of computers and the Internet accelerated business beyond human speed. Now, global businesses have to deal with customers at the end of a cable, not always a handshake. While we are still dealing with the effects of a digitizing business, the fourth revolution is already here. In just the past two or three years, the growth of data and advancement in visual intelligence has been astonishing. The computing power can now process the massive amount of data about your customers, suppliers, partners, competitors, and give you insights you simply could not imagine before. Artificial intelligence can not only tell you what your customers want today but also anticipate what they will need tomorrow. This is not just about making better business decisions or creating better customer relationships. It's about making the world a better place. Ultimately, can we build a new world without diseases, war, and poverty? The power of big data and artificial intelligence may be the revolutionary technology to make that possible. Revolutions don't happen on their own. Every industrial revolution has its leaders, its visionaries, and its heroes. The master transformers of their age. The first industrial revolution was led by mechanics who designed and built power systems, machines, and factories. The heroes of the second industrial revolution were the business managers who designed and built modern organizations. The heroes of the third revolution were the engineers who designed and built the circuits and the source code that digitized our world. The master transformers of the next revolution are actually you. You are the designers and the builders of the networks and the systems. You will bring the benefits of intelligence to every corner of your enterprise and make intelligence the central asset of your business. At Lenovo, data intelligence is embedded into everything we do. How we understand our customer's true needs and develop more desirable products. How we profile our customers and market to them precisely. How we use internal and external data to balance our supply and the demand. And how we train virtual agents to provide more effective sales services. So the decisions you make today about your IT investment will determine the quality of the decisions your enterprise will make tomorrow. So I challenge each of you to seize this opportunity to become a master transformer, to join Lenovo as we work together at the forefront of the fourth industrial revolution, as leaders of the intelligent transformation. (triumphant instrumental) Today, we are launching the largest portfolio in our data center history at Lenovo. We are fully committed to the (mumbles) transformation. Thank you. (audience applauds) >> Thanks YY. All right, ladies and gentlemen. Fantastic, so how about a big round of applause for YY. (audience applauds) Obviously a great speech on the transformation that we at Lenovo are taking as well as obviously wanting to journey with our partners and customers obviously on that same journey. What I heard from him was obviously artificial intelligence, how we're leveraging that integrally as well as externally and for our customers, and the investments we're making in the transformation around IoT machine learning, obviously big data, et cetera, and obviously the Data Center Group, which is one of the key things we've got to be talking about today. So we're on the cusp of that fourth revolution, as YY just mentioned, and Lenovo is definitely leading the way and investing in those parts of the industry and our portfolio to ensure we're complimenting all of our customers and partners on what they want to be, obviously, as part of this new transformation we're seeing globally. Obviously now, ladies and gentlemen, without further ado once again, to tell us more about what's going on today, our announcements, obviously, that all of you will be reading about and seeing in the breakout and the demo sessions with our segment general managers this afternoon is our president of the data center, Mr. Kirk Skaugen. (upbeat instrumental) >> Good morning, and let me add my welcome to Transform. I just crossed my six months here at Lenovo after over 24 years at Intel Corporation, and I can tell you, we've been really busy over the last six months, and I'm more excited and enthusiastic than ever and hope to share some of that with you today. Today's event is called "Transform", and today we're announcing major new transformations in Lenovo, in the data center, but more importantly, we're celebrating the business results that these platforms are going to have on society and with international supercomputing going on in parallel in Frankfurt, some of the amazing scientific discoveries that are going to happen on some of these platforms. Lenovo has gone through some significant transformations in the last two years, since we acquired the IBM x86 business, and that's really positioning us for this next phase of growth, and we'll talk more about that later. Today, we're announcing the largest end-to-end data center portfolio in Lenovo's history, as you heard from YY, and we're really taking the best of the x86 heritage from our IBM acquisition of the x86 server business and combining that with the cost economics that we've delivered from kind of our China heritage. As we've talked to some of the analysts in the room, it's really that best of the east and best of the west is combining together in this announcement today. We're going to be announcing two new brands, building on our position as the number one x86 server vendor in both customer satisfaction and in reliability, and we're also celebrating, next month in July, a very significant milestone, which will we'll be shipping our 20 millionth x86 server into the industry. For us, it's an amazing time, and it's an inflection point to kind of look back, pause, but also share the next phase of Lenovo and the exciting vision for the future. We're also making some declarations on our vision for the future today. Again, international supercomputing's going on, and, as it turns out, we're the fastest growing supercomputer company on earth. We'll talk about that. Our goal today that we're announcing is that we plan in the next several years to become number one in supercomputing, and we're going to put the investments behind that. We're also committing to our customers that we're going to disrupt the status quo and accelerate the pace of innovation, not just in our legacy server solutions, but also in Software-Defined because what we've heard from you is that that lack of legacy, we don't have a huge router business or a huge sand business to protect. It's that lack of legacy that's enabling us to invest and get ahead of the curb on this next transition to Software-Defined. So you're going to see us doing that through building our internal IP, through some significant joint ventures, and also through some merges and acquisitions over the next several quarters. Altogether, we're driving to be the most trusted data center provider in the industry between us and our customers and our suppliers. So a quick summary of what we're going to dive into today, both in my keynote as well as in the breakout sessions. We're in this transformation to the next phase of Lenovo's data center growth. We're closing out our previous transformation. We actually, believe it or not, in the last six months or so, have renegotiated 18,000 contracts in 160 countries. We built out an entire end-to-end organization from development and architecture all the way through sales and support. This next transformation, I think, is really going to excite Lenovo shareholders. We're building the largest data center portfolio in our history. I think when IBM would be up here a couple years ago, we might have two or three servers to announce in time to market with the next Intel platform. Today, we're announcing 14 new servers, seven new storage systems, an expanded set of networking portfolios based on our legacy with Blade Network Technologies and other companies we've acquired. Two new brands that we'll talk about for both data center infrastructure and Software-Defined, a new set of premium premiere services as well as a set of engineered solutions that are going to help our customers get to market faster. We're going to be celebrating our 20 millionth x86 server, and as Rod said, 25 years in x86 server compute, and Christian will be up here talking about 25 years of ThinkPad as well. And then a new end-to-end segmentation model because all of these strategies without execution are kind of meaningless. I hope to give you some confidence in the transformation that Lenovo has gone through as well. So, having observed Lenovo from one of its largest partners, Intel, for more than a couple decades, I thought I'd just start with why we have confidence on the foundation that we're building off of as we move from a PC company into a data center provider in a much more significant way. So Lenovo today is a company of $43 billion in sales. Absolutely astonishing, it puts us at about Fortune 202 as a company, with 52,000 employees around the world. We're supporting and have service personnel, almost a little over 10,000 service personnel that service our servers and data center technologies in over 160 countries that provide onsite service and support. We have seven data center research centers. One of the reasons I came from Intel to Lenovo was that I saw that Lenovo became number one in PCs, not through cost cutting but through innovation. It was Lenovo that was partnering on the next-generation Ultrabooks and two-in-ones and tablets in the modem mods that you saw, but fundamentally, our path to number one in data center is going to be built on innovation. Lastly, we're one of the last companies that's actually building not only our own motherboards at our own motherboard factories, but also with five global data center manufacturing facilities. Today, we build about four devices a second, but we also build over 100 servers per hour, and the cost economics we get, and I just visited our Shenzhen factory, of having everything from screws to microprocessors come up through the elevator on the first floor, go left to build PCs and ThinkPads and go right to build server technology, means we have some of the world's most cost effective solutions so we can compete in things like hyperscale computing. So it's with that that I think we're excited about the foundation that we can build off of on the Data Center Group. Today, as we stated, this event is about transformation, and today, I want to talk about three things we're going to transform. Number one is the customer experience. Number two is the data center and our customer base with Software-Defined infrastructure, and then the third is talk about how we plan to execute flawlessly with a new transformation that we've had internally at Lenovo. So let's dive into it. On customer experience, really, what does it mean to transform customer experience? Industry pundits say that if you're not constantly innovating, you can fall behind. Certainly the technology industry that we're in is transforming at record speed. 42% of business leaders or CIOs say that digital first is their top priority, but less than 50% actually admit that they have a strategy to get there. So people are looking for a partner to keep pace with that innovation and change, and that's really what we're driving to at Lenovo. So today we're announcing a set of plans to take another step function in customer experience, and building off of our number one position. Just recently, Gartner shows Lenovo as the number 24 supply chains of companies over $12 billion. We're up there with Amazon, Coca-Cola, and we've now completely re-architected our supply chain in the Data Center Group from end to end. Today, we can deliver 90% of our SKUs, order to ship in less than seven days. The artificial intelligence that YY mentioned is optimizing our performance even further. In services, as we talked about, we're now in 160 countries, supporting on-site support, 50 different call centers around the world for local language support, and we're today announcing a whole set of new premiere support services that I'll get into in a second. But we're building on what's already better than 90% customer satisfaction in this space. And then in development, for all the engineers out there, we started foundationally for this new set of products, talking about being number one in reliability and the lowest downtime of any x86 server vendor on the planet, and these systems today are architected to basically extend that leadership position. So let me tell you the realities of reliability. This is ITIC, it's a reliability report. 750 CIOs and IT managers from more than 20 countries, so North America, Europe, Asia, Australia, South America, Africa. This isn't anything that's paid for with sponsorship dollars. Lenovo has been number one for four years running on x86 reliability. This is the amount of downtime, four hours or more, in mission-critical environments from the leading x86 providers. You can see relative to our top two competitors that are ahead of us, HP and Dell, you can see from ITIC why we are building foundationally off of this, and why it's foundational to how we're developing these new platforms. In customer satisfaction, we are also rated number one in x86 server customer satisfaction. This year, we're now incentivizing every single Lenovo employee on customer satisfaction and customer experience. It's been a huge mandate from myself and most importantly YY as our CEO. So you may say well what is the basis of this number one in customer satisfaction, and it's not just being number one in one category, it's actually being number one in 21 of the 22 categories that TBR talks about. So whether it's performance, support systems, online product information, parts and availability replacement, Lenovo is number one in 21 of the 22 categories and number one for six consecutive studies going back to Q1 of 2015. So this, again, as we talk about the new product introductions, it's something that we absolutely want to build on, and we're humbled by it, and we want to continue to do better. So let's start now on the new products and talk about how we're going to transform the data center. So today, we are announcing two new product offerings. Think Agile and ThinkSystem. If you think about the 25 years of ThinkPad that Christian's going to talk about, Lenovo has a continuous learning culture. We're fearless innovators, we're risk takers, we continuously learn, but, most importantly, I think we're humble and we have some humility. That when we fail, we can fail fast, we learn, and we improve. That's really what drove ThinkPad to number one. It took about eight years from the acquisition of IBM's x86 PC business before Lenovo became number one, but it was that innovation, that listening and learning, and then improving. As you look at the 25 years of ThinkPad, there were some amazing successes, but there were also some amazing failures along the way, but each and every time we learned and made things better. So this year, as Rod said, we're not just celebrating 25 years of ThinkPad, but we're celebrating 25 years of x86 server development since the original IBM PC servers in 1992. It's a significant day for Lenovo. Today, we're excited to announce two new brands. ThinkSystem and ThinkAgile. It's an important new announcement that we started almost three years ago when we acquired the x86 server business. Why don't we run a video, and we'll show you a little bit about ThinkSystem and ThinkAgile. >> Narrator: The status quo is comfortable. It gets you by, but if you think that's good enough for your data center, think again. If adoption is becoming more complicated when it should be simpler, think again. If others are selling you technology that's best for them, not for you, think again. It's time for answers that win today and tomorrow. Agile, innovative, different. Because different is better. Different embraces change and makes adoption simple. Different designs itself around you. Using 25 years of innovation and design and R&D. Different transforms, it gives you ThinkSystem. World-record performance, most reliable, easy to integrate, scales faster. Different empowers you with ThinkAgile. It redefines the experience, giving you the speed of Cloud and the control of on-premise IT. Responding faster to what your business really needs. Different defines the future. Introducing Lenovo ThinkSystem and ThinkAgile. (exciting and slightly aggressive digital instrumental) >> All right, good stuff, huh? (audience applauds) So it's built off of this 25-year history of us being in the x86 server business, the commitment we established three years ago after acquiring the x86 server business to be and have the most reliable, the most agile, and the most highest-performing data center solutions on the planet. So today we're announcing two brands. ThinkSystem is for the traditional data center infrastructure, and ThinkAgile is our brand for Software-Defined infrastructure. Again, the teams challenge themselves from the start, how do we build off this rich heritage, expanding our position as number one in customer satisfaction, reliability, and one of the world's best supply chains. So let's start and look at the next set of solutions. We have always prided ourself that little things don't mean a lot. Little things mean everything. So today, as we said on the legacy solutions, we have over 30 world-record performance benchmarks on Intel architecture, and more than actually 150 since we started tracking this back in 2001. So it's the little pieces of innovation. It's the fine tuning that we do with our partners like an Intel or a Microsoft, an SAP, VMware, and Nutanix that's enabling us to get these world-record performance benchmarks, and with this next generation of solutions we think we'll continue to certainly do that. So today we're announcing the most comprehensive portfolio ever in our data center history. There's 14 servers, seven storage devices, and five network switches. We're also announcing, which is super important to our customer base, a set of new premiere service options. That's giving you fast access directly to a level two support person. No automated response system involved. You get to pick up the phone and directly talk to a level two support person that's going to have end-to-end ownership of the customer experience for ThinkSystem. With ThinkAgile, that's going to be completely bundled with every ThinkAgile you purchase. In addition, we're having white glove service on site that will actually unbox the product for you and get it up and running. It's an entirely new set of solutions for hybrid Cloud, for big data analytics and database applications around these engineered solutions. These are like 40- to 50-page guides where we fine-tuned the most important applications around virtual desktop infrastructure and those kinds of applications, working side by side with all of our ISP partners. So significantly expanding, not just the hardware but the software solutions that, obviously, you, as our customers, are running. So if you look at ThinkSystem innovation, again, it was designed for the ultimate in flexibility, performance, and reliability. It's a single now-unified brand that combines what used to be the Lenovo Think server and the IBM System x products now into a single brand that spans server, storage, and networking. We're basically future-proofing it for the next-generation data center. It's a significantly simplified portfolio. One of the big pieces that we've heard is that the complexity of our competitors has really been overwhelming to customers. We're building a more flexible, more agile solution set that requires less work, less qualification, and more future proofing. There's a bunch of things in this that you'll see in the demos. Faster time-to-service in terms of the modularity of the systems. 12% faster service equating to almost $50 thousand per hour of reduced downtime. Some new high-density options where we have four nodes and a 2U, twice the density to improve and reduce outbacks and mission-critical workloads. And then in high-performance computing and supercomputing, we're going to spend some time on that here shortly. We're announcing new water-cooled solutions. We have some of the most premiere water-cooled solutions in the world, with more than 25 patents pending now, just in the water-cooled solutions for supercomputing. The performance that we think we're going to see out of these systems is significant. We're building off of that legacy that we have today on the existing Intel solutions. Today, we believe we have more than 50% of SAP HANA installations in the world. In fact, SAP just went public that they're running their internal SAP HANA on Lenovo hardware now. We're seeing a 59% increase in performance on SAP HANA generation on generation. We're seeing 31% lower total cost to ownership. We believe this will continue our position of having the highest level of five-nines in the x86 server industry. And all of these servers will start being available later this summer when the Intel announcements come out. We're also announcing the largest storage portfolio in our history, significantly larger than anything we've done in the past. These are all available today, including some new value class storage offerings. Our network portfolio is expanding now significantly. It was a big surprise when I came to Lenovo, seeing the hundreds of engineers we had from the acquisition of Blade Network Technologies and others with our teams in Romania, Santa Clara, really building out both the embedded portfolio but also the top racks, which is around 10 gig, 25 gig, and 100 gig. Significantly better economics, but all the performance you'd expect from the largest networking companies in the world. Those are also available today. ThinkAgile and Software-Defined, I think the one thing that has kind of overwhelmed me since coming in to Lenovo is we are being embraced by our customers because of our lack of legacy. We're not trying to sell you one more legacy SAN at 65% margins. ThinkAgile really was founded, kind of born free from the shackles of legacy thinking and legacy infrastructure. This is just the beginning of what's going to be an amazing new brand in the transformation to Software-Defined. So, for Lenovo, we're going to invest in our own internal organic IP. I'll foreshadow: There's some significant joint ventures and some mergers and acquisitions that are going to be coming in this space. And so this will be the foundation for our Software-Defined networking and storage, for IoT, and ultimately for the 5G build-out as well. This is all built for data centers of tomorrow that require fluid resources, tightly integrated software and hardware in kind of an appliance, selling at the rack level, and so we'll show you how that is going to take place here in a second. ThinkAgile, we have a few different offerings. One is around hyperconverged storage, Hybrid Cloud, and also Software-Defined storage. So we're really trying to redefine the customer experience. There's two different solutions we're having today. It's a Microsoft Azure solution and a Nutanix solution. These are going to be available both in the appliance space as well as in a full rack solution. We're really simplifying and trying to transform the entire customer experience from how you order it. We've got new capacity planning tools that used to take literally days for us to get the capacity planning done. It's now going down to literally minutes. We've got new order, delivery, deployment, administration service, something we're calling ThinkAgile Advantage, which is the white glove unboxing of the actual solutions on prem. So the whole thing when you hear about it in the breakout sessions about transforming the entire customer experience with both an HX solution and an SX solution. So again, available at the rack level for both Nutanix and for Microsoft Solutions available in just a few months. Many of you in the audience since the Microsoft Airlift event in Seattle have started using these things, and the feedback to date has been fantastic. We appreciate the early customer adoption that we've seen from people in the audience here. So next I want to bring up one of our most important partners, and certainly if you look at all of these solutions, they're based on the next-generation Intel Xeon scalable processor that's going to be announcing very very soon. I want to bring on stage Rupal Shah, who's the corporate vice president and general manager of Global Data Center Sales with Intel, so Rupal, please join me. (upbeat instrumental) So certainly I have long roots at Intel, but why don't you talk about, from Intel's perspective, why Lenovo is an important partner for Lenovo. >> Great, well first of all, thank you very much. I've had the distinct pleasure of not only working with Kirk for many many years, but also working with Lenovo for many years, so it's great to be here. Lenovo is not only a fantastic supplier and leader in the industry for Intel-based servers but also a very active partner in the Intel ecosystem. In the Intel ecosystem, specifically, in our partner programs and in our builder programs around Cloud, around the network, and around storage, I personally have had a long history in working with Lenovo, and I've seen personally that PC transformation that you talked about, Kirk, and I believe, and I know that Intel believes in Lenovo's ability to not only succeed in the data center but to actually lead in the data center. And so today, the ThinkSystem and ThinkAgile announcement is just so incredibly important. It's such a great testament to our two companies working together, and the innovation that we're able to bring to the market, and all of it based on the Intel Xeon scalable processor. >> Excellent, so tell me a little bit about why we've been collaborating, tell me a little bit about why you're excited about ThinkSystem and ThinkAgile, specifically. >> Well, there are a lot of reasons that I'm excited about the innovation, but let me talk about a few. First, both of our companies really stand behind the fact that it's increasingly a hybrid world. Our two companies offer a range of solutions now to customers to be able to address their different workload needs. ThinkSystem really brings the best, right? It brings incredible performance, flexibility in data center deployment, and industry-leading reliability that you've talked about. And, as always, Xeon has a history of being built for the data center specifically. The Intel Xeon scalable processor is really re-architected from the ground up in order to enhance compute, network, and storage data flows so that we can deliver workload optimized performance for both a wide range of traditional workloads and traditional needs but also some emerging new needs in areas like artificial intelligence. Second is when it comes to the next generation of Cloud infrastructure, the new Lenovo ThinkAgile line offers a truly integrated offering to address data center pain points, and so not only are you able to get these pretested solutions, but these pretested solutions are going to get deployed in your infrastructure faster, and they're going to be deployed in a way that's going to meet your specific needs. This is something that is new for both of us, and it's an incredible innovation in the marketplace. I think that it's a great addition to what is already a fantastic portfolio for Lenovo. >> Excellent. >> Finally, there's high-performance computing. In high-performance computing. First of all, congratulations. It's a big week, I think, for both of us. Fantastic work that we've been doing together in high-performance computing and actually bringing the best of the best to our customers, and you're going to hear a whole lot more about that. We obviously have a number of joint innovation centers together between Intel and Lenovo. Tell us about some of the key innovations that you guys are excited about. >> Well, Intel and Lenovo, we do have joint innovation labs around the world, and we have a long and strong history of very tight collaboration. This has brought a big wave of innovation to the marketplace in areas like software-defined infrastructure. Yet another area is working closely on a joint vision that I think our two companies have in artificial intelligence. Intel is very committed to the world of AI, and we're committed in making the investments required in technology development, in training, and also in R&D to be able to deliver end-to-end solutions. So with Intel's comprehensive technology portfolio and Lenovo's development and innovation expertise, it's a great combination in this space. I've already talked a little bit about HPC and so has Kirk, and we're going to hear a little bit more to come, but we're really building the fastest compute solutions for customers that are solving big problems. Finally, we often talk about processors from Intel, but it's not just about the processors. It's way beyond that. It's about engaging at the solution level for our customers, and I'm so excited about the work that we've done together with Lenovo to bring to market products like Intel Omni-Path Architecture, which is really the fabric for high-performance data centers. We've got a great showing this week with Intel Omni-Path Architecture, and I'm so grateful for all the work that we've done to be able to bring true solutions to the marketplace. I am really looking forward to our future collaboration with Lenovo as we have in the past. I want to thank you again for inviting me here today, and congratulations on a fantastic launch. >> Thank you, Rupal, very much, for the long partnership. >> Thank you. (audience applauds) >> Okay, well now let's transition and talk a little bit about how Lenovo is transforming. The first thing we've done when I came on board about six months ago is we've transformed to a truly end-to-end organization. We're looking at the market segments I think as our customers define them, and we've organized into having vice presidents and senior vice presidents in charge of each of these major groups, thinking really end to end, from architecture all the way to end of life and customer support. So the first is hyperscale infrastructure. It's about 20% on the market by 2020. We've hired a new vice president there to run that business. Given we can make money in high-volume desktop PCs, it's really the manufacturing prowess, deep engineering collaboration that's enabling us to sell into Baidu, and to Alibaba, Tencent, as well as the largest Cloud vendors on the West Coast here in the United States. We believe we can make money here by having basically a deep deep engineering engagement with our key customers and building on the PC volume economics that we have within Lenovo. On software-defined infrastructure, again, it's that lack of legacy that I think is propelling us into this space. We're not encumbered by trying to sell one more legacy SAN or router, and that's really what's exciting us here, as we transform from a hardware to a software-based company. On HPC and AI, as we said, we'll talk about this in a second. We're the fastest-growing supercomputing company on earth. We have aspirations to be the largest supercomputing company on earth, with China and the U.S. vying for number one in that position, it puts us in a good position there. We're going to bridge that into artificial intelligence in our upcoming Shanghai Tech World. The entire day is around AI. In fact, YY has committed $1.2 billion to artificial intelligence over the next few years of R&D to help us bridge that. And then on data center infrastructure, is really about moving to a solutions based infrastructure like our position with SAP HANA, where we've gone deep with engineers on site at SAP, SAP running their own infrastructure on Lenovo and building that out beyond just SAP to other solutions in the marketplace. Overall, significantly expanding our services portfolio to maintain our number one customer satisfaction rating. So given ISC, or International Supercomputing, this week in Frankfurt, and a lot of my team are actually over there, I wanted to just show you the transformation we've had at Lenovo for delivering some of the technology to solve some of the most challenging humanitarian problems on earth. Today, we are the fastest-growing supercomputer company on the planet in terms of number of systems on the Top 500 list. We've gone from zero to 92 positions in just a few short years, but IDC also positions Lenovo as the fast-growing supercomputer and HPC company overall at about 17% year on year growth overall, including all of the broad channel, the regional universities and this kind of thing, so this is an exciting place for us. I'm excited today that Sergi has come all the way from Spain to be with us today. It's an exciting time because this week we announce the fastest next-generation Intel supercomputer on the planet at Barcelona Supercomputer. Before I bring Sergi on stage, let's run a video and I'll show you why we're excited about the capabilities of these next-generation supercomputers. Run the video please. >> Narrator: Different creates one of the most powerful supercomputers for the Barcelona Supercomputer Center. A high-performance, high-capacity design to help shape tomorrow's world. Different designs what's best for you, with 25 years of end-to-end expertise delivering large-scale solutions. It integrates easily with technology from industry partners, through deep collaboration with the client to manufacture, test, configure, and install at global scale. Different achieves the impossible. The first of a new series. A more energy-efficient supercomputer yet 10 times more powerful than its predecessor. With over 3,400 Lenovo ThinkSystem servers, each performing over two trillion calculations per second, giving us 11.1 petaflop capacity. Different powers MareNostrum, a supercomputer that will help us better understand cancer, help discover disease-fighting therapies, predict the impact of climate change. MareNostrom 4.0 promises to uncover answers that will help solve humanities greatest challenges. (audience applauds) >> So please help me in welcoming operations director of the Barcelona Supercomputer Center, Sergi Girona. So welcome, and again, congratulations. It's been a big week for both of us. But I think for a long time, if you haven't been to Barcelona, this has been called the world's most beautiful computer because it's in one of the most gorgeous chapels in the world as you can see here. Congratulations, we now are number 13 on the Top500 list and the fastest next-generation Intel computer. >> Thank you very much, and congratulations to you as well. >> So maybe we can just talk a little bit about what you've done over the last few months with us. >> Sure, thank you very much. It is a pleasure for me being invited here to present to you what we've been doing with Lenovo so far and what we are planning to do in the next future. I'm representing here Barcelona Supercomputing Center. I am presenting high-performance computing services to science and industry. How we see these science services has changed the paradigm of science. We are coming from observation. We are coming from observation on the telescopes and the microscopes and the building of infrastructures, but this is not affordable anymore. This is very expensive, so it's not possible, so we need to move to simulations. So we need to understand what's happening in our environment. We need to predict behaviors only going through simulation. So, at BSC, we are devoted to provide services to industry, to science, but also we are doing our own research because we want to understand. At the same time, we are helping and developing the new engineers of the future on the IT, on HPC. So we are having four departments based on different topics. The main and big one is wiling to understand how we are doing the next supercomputers from the programming level to the performance to the EIA, so all these things, but we are having also interest on what about the climate change, what's the air quality that we are having in our cities. What is the precision medicine we need to have. How we can see that the different drugs are better for different individuals, for different humans, and of course we have an energy department, taking care of understanding what's the better optimization for a cold, how we can save energy running simulations on different topics. But, of course, the topic of today is not my research, but it's the systems we are building in Barcelona. So this is what we have been building in Barcelona so far. From left to right, you have the preparation of the facility because this is 160 square meters with 1.4 megabytes, so that means we need new piping, we need new electricity, at the same time in the center we have to install the core services of the system, so the management practices, and then on the right-hand side you have installation of the networking, the Omni-Path by Intel. Because all of the new racks have to be fully integrated and they need to come into operation rapidly. So we start deployment of the system May 15, and we've now been ending and coming in production July first. All the systems, all the (mumbles) systems from Lenovo are coming before being open and available. What we've been installing here in Barcelona is general purpose systems for our general workload of the system with 3,456 nodes. Everyone of those having 48 cores, 96 gigabytes main memory for a total capacity of about 400 terabytes memory. The objective of this is that we want to, all the system, all the processors, to work together for a single execution for running altogether, so this is an example of the platinum processors from Intel having 24 cores each. Of course, for doing this together with all the cores in the same application, we need a high-speed network, so this is Omni-Path, and of course all these cables are connecting all the nodes. Noncontention, working together, cooperating. Of course, this is a bunch of cables. They need to be properly aligned in switches. So here you have the complete presentation. Of course, this is general purpose, but we wanted to invest with our partners. We want to understand what the supercomputers we wanted to install in 2020, (mumbles) Exascale. We want to find out, we are installing as well systems with different capacities with KNH, with power, with ARM processors. We want to leverage our obligations for the future. We want to make sure that in 2020 we are ready to move our users rapidly to the new technologies. Of course, this is in total, giving us a total capacity of 13.7 petaflops that it's 12 times the capacity of the former MareNostrum four years ago. We need to provide the services to our scientists because they are helping to solve problems for humanity. That's the place we are going to go. Last is inviting you to come to Barcelona to see our place and our chapel. Thank you very much (audience applauds). >> Thank you. So now you can all go home to your spouses and significant others and say you have a formal invitation to Barcelona, Spain. So last, I want to talk about what we've done to transform Lenovo. I think we all know the history is nice but without execution, none of this is going to be possible going forward, so we have been very very busy over the last six months to a year of transforming Lenovo's data center organization. First, we moved to a dedicated end-to-end sales and marketing organization. In the past, we had people that were shared between PC and data center, now thousands of sales people around the world are 100% dedicated end to end to our data center clients. We've moved to a fully integrated and dedicated supply chain and procurement organization. A fully dedicated quality organization, 100% dedicated to expanding our data center success. We've moved to a customer-centric segment, again, bringing in significant new leaders from outside the company to look end to end at each of these segments, supercomputing being very very different than small business, being very very different than taking care of, for example, a large retailer or bank. So around hyperscale, software-defined infrastructure, HPC, AI, and supercomputing and data center solutions-led infrastructure. We've built out a whole new set of global channel programs. Last year, or a year passed, we have five different channel programs around the world. We've now got one simplified channel program for dealer registration. I think our channel is very very energized to go out to market with Lenovo technology across the board, and a whole new set of system integrator relationships. You're going to hear from one of them in Christian's discussion, but a whole new set of partnerships to build solutions together with our system integrative partners. And, again, as I mentioned, a brand new leadership team. So look forward to talking about the details of this. There's been a significant amount of transformation internal to Lenovo that's led to the success of this new product introduction today. So in conclusion, I want to talk about the news of the day. We are transforming Lenovo to the next phase of our data center growth. Again, in over 160 countries, closing on that first phase of transformation and moving forward with some unique declarations. We're launching the largest portfolio in our history, not just in servers but in storage and networking, as everything becomes kind of a software personality on top of x86 Compute. We think we're very well positioned with our scale on PCs as well as data center. Two new brands for both data center infrastructure and Software-Defined, without the legacy shackles of our competitors, enabling us to move very very quickly into Software-Defined, and, again, foreshadowing some joint ventures in M&A that are going to be coming up that will further accelerate ourselves there. New premiere support offerings, enabling you to get direct access to level two engineers and white glove unboxing services, which are going to be bundled along with ThinkAgile. And then celebrating the milestone of 25 years in x86 server compute, not just ThinkPads that you'll hear about shortly, but also our 20 million server shipping next month. So we're celebrating that legacy and looking forward to the next phase. And then making sure we have the execution engine to maintain our position and grow it, being number one in customer satisfaction and number one in quality. So, with that, thank you very much. I look forward to seeing you in the breakouts today and talking with many of you, and I'll bring Rod back up to transition us to the next section. Thank you. (audience applauds) >> All right, Kirk, thank you, sir. All right, ladies and gentlemen, what did you think of that? How about a big round of applause for ThinkAgile, ThinkSystems new brands? (audience applauds) And, obviously, with that comes a big round of applause, for Kirk Skaugen, my boss, so we've got to give him a big round of applause, please. I need to stay employed, it's very important. All right, now you just heard from Kirk about some of the new systems, the brands. How about we have a quick look at the video, which shows us the brand new DCG images. >> Narrator: Legacy thinking is dead, stuck in the past, selling the same old stuff, over and over. So then why does it seem like a data center, you know, that thing powering all our little devices and more or less everything interaction today is still stuck in legacy thinking because it's rigid, inflexible, slow, but that's not us. We don't do legacy. We do different. Because different is fearless. Different reduces Cloud deployment from days to hours. Different creates agile technology that others follow. Different is fluid. It uses water-cooling technology to save energy. It co-innovates with some of the best minds in the industry today. Different is better, smarter. Maybe that's why different already holds so many world-record benchmarks in everything. From virtualization to database and application performance or why it's number one in reliability and customer satisfaction. Legacy sells you what they want. Different builds the data center you need without locking you in. Introducing the Data Center Group at Lenovo. Different... Is better. >> All right, ladies and gentlemen, a big round of applause, once again (mumbles) DCG, fantastic. And I'm sure all of you would agree, and Kirk mentioned it a couple of times there. No legacy means a real consultative approach to our customers, and that's something that we really feel is differentiated for ourselves. We are effectively now one of the largest startups in the DCG space, and we are very much ready to disrupt. Now, here in New York City, obviously, the heart of the fashion industry, and much like fashion, as I mentioned earlier, we're different, we're disruptive, we're agile, smarter, and faster. I'd like to say that about myself, but, unfortunately, I can't. But those of you who have observed, you may have noticed that I, too, have transformed. I don't know if anyone saw that. I've transformed from the pinstripe blue, white shirt, red tie look of the, shall we say, our predecessors who owned the x86 business to now a very Lenovo look. No tie and consequently a little bit more chic New York sort of fashion look, shall I say. Nothing more than that. So anyway, a bit of a transformation. It takes a lot to get to this look, by the way. It's a lot of effort. Our next speaker, Christian Teismann, is going to talk a lot about the core business of Lenovo, which really has been, as we've mentioned today, our ThinkPad, 25-year anniversary this year. It's going to be a great celebration inside Lenovo, and as we get through the year and we get closer and closer to the day, you'll see a lot more social and digital work that engages our customers, partners, analysts, et cetera, when we get close to that birthday. Customers just generally are a lot tougher on computers. We know they are. Whether you hang onto it between meetings from the corner of the Notebook, and that's why we have magnesium chassis inside the box or whether you're just dropping it or hypothetically doing anything else like that. We do a lot of robust testing on these products, and that's why it's the number one branded Notebook in the world. So Christian talks a lot about this, but I thought instead of having him talk, I might just do a little impromptu jump back stage and I'll show you exactly what I'm talking about. So follow me for a second. I'm going to jaunt this way. I know a lot of you would have seen, obviously, the front of house here, what we call the front of house. Lots of videos, et cetera, but I don't think many of you would have seen the back of house here, so I'm going to jump through the back here. Hang on one second. You'll see us when we get here. Okay, let's see what's going on back stage right now. You can see one of the team here in the back stage is obviously working on their keyboard. Fantastic, let me tell you, this is one of the key value props of this product, obviously still working, lots of coffee all over it, spill-proof keyboard, one of the key value propositions and why this is the number one laptop brand in the world. Congratulations there, well done for that. Obviously, we test these things. Height, distances, Mil-SPEC approved, once again, fantastic product, pick that up, lovely. Absolutely resistant to any height or drops, once again, in line with our Mil-SPEC. This is Charles, our producer and director back stage for the absolute event. You can see, once again, sand, coincidentally, in Manhattan, who would have thought a snow storm was occurring here, but you can throw sand. We test these things for all of the elements. I've obviously been pretty keen on our development solutions, having lived in Japan for 12 years. We had this originally designed in 1992 by (mumbles), he's still our chief development officer still today, fantastic, congratulations, a sand-enhanced notebook, he'd love that. All right, let's get back out front and on with the show. Watch the coffee. All right, how was that? Not too bad (laughs). It wasn't very impromptu at all, was it? Not at all a set up (giggles). How many people have events and have a bag of sand sitting on the floor right next to a Notebook? I don't know. All right, now it's time, obviously, to introduce our next speaker, ladies and gentlemen, and I hope I didn't steal his thunder, obviously, in my conversations just now that you saw back stage. He's one of my best friends in Lenovo and easily is a great representative of our legendary PC products and solutions that we're putting together for all of our customers right now, and having been an ex-Pat with Lenovo in New York really calls this his second home and is continually fighting with me over the fact that he believes New York has better sushi than Tokyo, let's welcome please, Christian Teismann, our SVP, Commercial Business Segment, and PC Smart Office. Christian Teismann, come on up mate. (audience applauds) >> So Rod thank you very much for this wonderful introduction. I'm not sure how much there is to add to what you have seen already back stage, but I think there is a 25-year of history I will touch a little bit on, but also a very big transformation. But first of all, welcome to New York. As Rod said, it's my second home, but it's also a very important place for the ThinkPad, and I will come back to this later. The ThinkPad is thee industry standard of business computing. It's an industry icon. We are celebrating 25 years this year like no other PC brand has done before. But this story today is not looking back only. It's a story looking forward about the future of PC, and we see a transformation from PCs to personalized computing. I am privileged to lead the commercial PC and Smart device business for Lenovo, but much more important beyond product, I also am responsible for customer experience. And this is what really matters on an ongoing basis. But allow me to stay a little bit longer with our iconic ThinkPad and history of the last 25 years. ThinkPad has always stand for two things, and it always will be. Highest quality in the industry and technology innovation leadership that matters. That matters for you and that matters for your end users. So, now let me step back a little bit in time. As Rod was showing you, as only Rod can do, reliability is a very important part of ThinkPad story. ThinkPads have been used everywhere and done everything. They have survived fires and extreme weather, and they keep surviving your end users. For 25 years, they have been built for real business. ThinkPad also has a legacy of first innovation. There are so many firsts over the last 25 years, we could spend an hour talking about them. But I just want to cover a couple of the most important milestones. First of all, the ThinkPad 1992 has been developed and invented in Japan on the base design of a Bento box. It was designed by the famous industrial designer, Richard Sapper. Did you also know that the ThinkPad was the first commercial Notebook flying into space? In '93, we traveled with the space shuttle the first time. For two decades, ThinkPads were on every single mission. Did you know that the ThinkPad Butterfly, the iconic ThinkPad that opens the keyboard to its size, is the first and only computer showcased in the permanent collection of the Museum of Modern Art, right here in New York City? Ten years later, in 2005, IBM passed the torch to Lenovo, and the story got even better. Over the last 12 years, we sold over 100 million ThinkPads, four times the amount IBM sold in the same time. Many customers were concerned at that time, but since then, the ThinkPad has remained the best business Notebook in the industry, with even better quality, but most important, we kept innovating. In 2012, we unveiled the X1 Carbon. It was the thinnest, lightest, and still most robust business PC in the world. Using advanced composited materials like a Formula One car, for super strengths, X1 Carbon has become our ThinkPad flagship since then. We've added an X1 Carbon Yoga, a 360-degree convertible. An X1 Carbon tablet, a detachable, and many new products to come in the future. Over the last few years, many new firsts have been focused on providing the best end-user experience. The first dual-screen mobile workstation. The first Windows business tablet, and the first business PC with OLED screen technology. History is important, but a massive transformation is on the way. Future success requires us to think beyond the box. Think beyond hardware, think beyond notebooks and desktops, and to think about the future of personalized computing. Now, why is this happening? Well, because the business world is rapidly changing. Looking back on history that YY gave, and the acceleration of innovation and how it changes our everyday life in business and in personal is driving a massive change also to our industry. Most important because you are changing faster than ever before. Human capital is your most important asset. In today's generation, they want to have freedom of choice. They want to have a product that is tailored to their specific needs, every single day, every single minute, when they use it. But also IT is changing. The Cloud, constant connectivity, 5G will change everything. Artificial intelligence is adding things to the capability of an infrastructure that we just are starting to imagine. Let me talk about the workforce first because it's the most important part of what drives this. The millennials will comprise more than half of the world's workforce in 2020, three years from now. Already, one out of three millennials is prioritizing mobile work environment over salary, and for nearly 60% of all new hires in the United States, technology is a very important factor for their job search in terms of the way they work and the way they are empowered. This new generation of new employees has grown up with PCs, with Smart phones, with tablets, with touch, for their personal use and for their occupation use. They want freedom. Second, the workplace is transforming. The video you see here in the background. This is our North America headquarters in Raleigh, where we have a brand new Smart workspace. We have transformed this to attract the new generation of workers. It has fewer traditional workspaces, much more meaning and collaborative spaces, and Lenovo, like many companies, is seeing workspaces getting smaller. An average workspace per employee has decreased by 30% over the last five years. Employees are increasingly mobile, but, if they come to the office, they want to collaborate with their colleagues. The way we collaborate and communicate is changing. Investment in new collaboration technology is exploding. The market of collaboration technology is exceeding the market of personal computing today. It will grow in the future. Conference rooms are being re-imagined from a ratio of 50 employees to one large conference room. Today, we are moving into scenarios of four employees to one conference room, and these are huddle rooms, pioneer spaces. Technology is everywhere. Video, mega-screens, audio, electronic whiteboards. Adaptive technologies are popping up and change the way we work. As YY said earlier, the pace of the revolution is astonishing. So personalized computing will transform the PC we all know. There's a couple of key factors that we are integrating in our next generations of PC as we go forward. The most important trends that we see. First of all, choose your own device. We talked about this new generation of workforce. Employees who are used to choosing their own device. We have to respond and offer devices that are tailored to each end user's needs without adding complexity to how we operate them. PC is a service. Corporations increasingly are looking for on-demand computing in data center as well as in personal computing. Customers want flexibility. A tailored management solution and a services portfolio that completes the lifecycle of the device. Agile IT, even more important, corporations want to run an infrastructure that is agile, instant respond to their end-customer needs, that is self provisioning, self diagnostic, and remote software repair. Artificial intelligence. Think about artificial intelligence for you personally as your personal assistant. A personal assistant which does understand you, your schedule, your travel, your next task, an extension of yourself. We believe the PC will be the center of this mobile device universe. Mobile device synergy. Each of you have two devices or more with you. They need to work together across different operating systems, across different platforms. We believe Lenovo is uniquely positioned as the only company who has a Smart phone business, a PC business, and an infrastructure business to really seamlessly integrate all of these devices for simplicity and for efficiency. Augmented reality. We believe augmented reality will drive significantly productivity improvements in commercial business. The core will be to understand industry-specific solutions. New processes, new business challenges, to improve things like customer service and sales. Security will remain the foundation for personalized computing. Without security, without trust in the device integrity, this will not happen. One of the most important trends, I believe, is that the PC will transform, is always connected, and always on, like a Smart phone. Regardless if it's open, if it's closed, if you carry it, or if you work with it, it always is capable to respond to you and to work with you. 5G is becoming a reality, and the data capacity that will be out there is by far exceeding today's traffic imagination. Finally, Smart Office, delivering flexible and collaborative work environments regardless on where the worker sits, fully integrated and leverages all the technologies we just talked before. These are the main challenges you and all of your CIO and CTO colleagues have to face today. A changing workforce and a new set of technologies that are transforming PC into personalized computing. Let me give you a real example of a challenge. DXC was just formed by merging CSE company and HP's Enterprise services for the largest independent services company in the world. DXC is now a 25 billion IT services leader with more than 170,000 employees. The most important capital. 6,000 clients and eight million managed devices. I'd like to welcome their CIO, who has one of the most challenging workforce transformation in front of him. Erich Windmuller, please give him a round of applause. (audience applauds). >> Thank you Christian. >> Thank you. >> It's my pleasure to be here, thank you. >> So first of all, let me congratulation you to this very special time. By forming a new multi-billion-dollar enterprise, this new venture. I think it has been so far fantastically received by analysts, by the press, by customers, and we are delighted to be one of your strategic partners, and clearly we are collaborating around workforce transformation between our two companies. But let me ask you a couple of more personal questions. So by bringing these two companies together with nearly 200,00 employees, what are the first actions you are taking to make this a success, and what are your biggest challenges? >> Well, first, again, let me thank you for inviting me and for DXC Technology to be a part of this very very special event with Lenovo, so thank you. As many of you might expect, it's been a bit of a challenge over the past several months. My goal was really very simple. It was to make sure that we brought two companies together, and they could operate as one. We need to make sure that could continue to support our clients. We certainly need to make sure we could continue to sell, our sellers could sell. That we could pay our employees, that we could hire people, we could do all the basic foundational things that you might expect a company would want to do, but we really focused on three simple areas. I called it the three Cs. Connectivity, communicate, and collaborate. So we wanted to make sure that we connected our legacy data centers so we could transfer information and communicate back and forth. We certainly wanted to be sure that our employees could communicate via WIFI, whatever locations they may or may not go to. We certainly wanted to, when we talk about communicate, we need to be sure that everyone of our employees could send and receive email as a DXC employee. And that we had a single-enterprise directory and people could communicate, gain access to calendars across each of the two legacy companies, and then collaborate was also key. And so we wanted to be sure, again, that people could communicate across each other, that our legacy employees on either side could get access to many of their legacy systems, and, again, we could collaborate together as a single corporation, so it was challenging, but very very, great opportunity for all of us. And, certainly, you might expect cyber and security was a very very important topic. My chairman challenged me that we had to be at least as good as we were before from a cyber perspective, and when you bring two large companies together like that there's clearly an opportunity in this disruptive world so we wanted to be sure that we had a very very strong cyber security posture, of which Lenovo has been very very helpful in our achieving that. >> Thank you, Erich. So what does DXC consider as their critical solutions and technology for workplace transformation, both internally as well as out on the market? >> So workplace transformation, and, again, I've heard a lot of the same kinds of words that I would espouse... It's all about making our employees productive. It's giving the right tools to do their jobs. I, personally, have been focused, and you know this because Lenovo has been a very very big part of this, in working with our, we call it our My Style Workplace, it's an offering team in developing a solution and driving as much functionality as possible down to the workstation. We want to be able, for me, to avoid and eliminate other ancillary costs, audio video costs, telecommunication cost. The platform that we have, the digitized workstation that Lenovo has provided us, has just got a tremendous amount of capability. We want to streamline those solutions, as well, on top of the modern server. The modern platform, as we call it, internally. I'd like to congratulate Kirk and your team that you guys have successfully... Your hardware has been certified on our modern platform, which is a significant accomplishment between our two companies and our partnership. It was really really foundational. Lenovo is a big part of our digital workstation transformation, and you'll continue to be, so it's very very important, and I want you to know that your tools and your products have done a significant job in helping us bring two large corporations together as one. >> Thank you, Erich. Last question, what is your view on device as a service and hardware utility model? >> This is the easy question, right? So who in the room doesn't like PC or device as a service? This is a tremendous opportunity, I think, for all of us. Our corporation, like many of you in the room, we're all driven by the concept of buying devices in an Opex versus a Capex type of a world and be able to pay as you go. I think this is something that all of us would like to procure, product services and products, if you will, personal products, in this type of a mode, so I am very very eager to work with Lenovo to be sure that we bring forth a very dynamic and constructive device as a service approach. So very eager to do that with Lenovo and bring that forward for DXC Technology. >> Erich, thank you very much. It's a great pleasure to work with you, today and going forward on all sides. I think with your new company and our lineup, I think we have great things to come. Thank you very much. >> My pleasure, great pleasure, thank you very much. >> So, what's next for Lenovo PC? We already have the most comprehensive commercial portfolio in the industry. We have put the end user in the core of our portfolio to finish and going forward. Ultra mobile users, like consultants, analysts, sales and service. Heavy compute users like engineers and designers. Industry users, increasingly more understanding. Industry-specific use cases like education, healthcare, or banking. So, there are a few exciting things we have to announce today. Obviously, we don't have that broad of an announcement like our colleagues from the data center side, but there is one thing that I have that actually... Thank you Rod... Looks like a Bento box, but it's not a ThinkPad. It's a first of it's kind. It's the world's smallest professional workstation. It has the power of a tower in the Bento box. It has the newest Intel core architecture, and it's designed for a wide range of heavy duty workload. Innovation continues, not only in the ThinkPad but also in the desktops and workstations. Second, you hear much about Smart Office and workspace transformation today. I'm excited to announce that we have made a strategic decision to expand our Think portfolio into Smart Office, and we will soon have solutions on the table in conference rooms, working with strategic partners like Intel and like Microsoft. We are focused on a set of devices and a software architecture that, as an IoT architecture, unifies the management of Smart Office. We want to move fast, so our target is that we will have our first product already later this year. More to come. And finally, what gets me most excited is the upcoming 25 anniversary in October. Actually, if you go to Japan, there are many ThinkPad lovers. Actually beyond lovers, enthusiasts, who are collectors. We've been consistently asked in blogs and forums about a special anniversary edition, so let me offer you a first glimpse what we will announce in October, of something we are bring to market later this year. For the anniversary, we will introduce a limited edition product. This will include throwback features from ThinkPad's history as well as the best and most powerful features of the ThinkPad today. But we are not just making incremental adjustments to the Think product line. We are rethinking ThinkPad of the future. Well, here is what I would call a concept card. Maybe a ThinkPad without a hinge. Maybe one you can fold. What do you think? (audience applauds) but this is more than just design or look and feel. It's a new set of advanced materials and new screen technologies. It's how you can speak to it or write on it or how it speaks to you. Always connected, always on, and can communicate on multiple inputs and outputs. It will anticipate your next meeting, your next travel, your next task. And when you put it all together, it's just another part of the story, which we call personalized computing. Thank you very much. (audience applauds) Thank you, sir. >> Good on ya, mate. All right, ladies and gentlemen. We are now at the conclusion of the day, for this session anyway. I'm going to talk a little bit more about our breakouts and our demo rooms next door. But how about the power with no tower, from Christian, huh? Big round of applause. (audience applauds) And what about the concept card, the ThinkPad? Pretty good, huh? I love that as well. I tell you, it was almost like Leonardo DiCaprio was up on stage at one stage. He put that big ThinkPad concept up, and everyone's phones went straight up and took a photo, the whole audience, so let's be very selective on how we distribute that. I'm sure it's already on Twitter. I'll check it out in a second. So once again, ThinkPad brand is a core part of the organization, and together both DCG and PCSD, what we call PCSD, which is our client side of the business and Smart device side of the business, are obviously very very linked in transforming Lenovo for the future. We want to also transform the industry, obviously, and transform the way that all of us do business. Lenovo, if you look at basically a summary of the day, we are highly committed to being a top three data center provider. That is really important for us. We are the largest and fastest growing supercomputing company in the world, and Kirk actually mentioned earlier on, committed to being number one by 2020. So Madhu who is in Frankfurt at the International Supercomputing Convention, if you're watching, congratulations, your targets have gone up. There's no doubt he's going to have a lot of work to do. We're obviously very very committed to disrupting the data center. That's obviously really important for us. As we mentioned, with both the brands, the ThinkSystem, and our ThinkAgile brands now, highly focused on disrupting and ensuring that we do things differently because different is better. Thank you to our customers, our partners, media, analysts, and of course, once again, all of our employees who have been on this journey with us over the last two years that's really culminating today in the launch of all of our new products and our profile and our portfolio. It's really thanks to all of you that once again on your feedback we've been able to get to this day. And now really our journey truly begins in ensuring we are disrupting and enduring that we are bringing more value to our customers without that legacy that Kirk mentioned earlier on is really an advantage for us as we really are that large startup from a company perspective. It's an exciting time to be part of Lenovo. It's an exciting time to be associated with Lenovo, and I hope very much all of you feel that way. So a big round of applause for today, thank you very much. (audience applauds) I need to remind all of you. I don't think I'm going to have too much trouble getting you out there, because I was just looking at Christian on the streaming solutions out in the room out the back there, and there's quite a nice bit of lunch out there as well for those of you who are hungry, so at least there's some good food out there, but I think in reality all of you should be getting up into the demo sessions with our segment general managers because that's really where the rubber hits the road. You've heard from YY, you've heard from Kirk, and you've heard from Christian. All of our general managers and our specialists in our product sets are going to be out there to obviously demonstrate our technology. As we said at the very beginning of this session, this is Transform, obviously the fashion change, hopefully you remember that. Transform, we've all gone through the transformation. It's part of our season of events globally, and our next event obviously is going to be in Tech World in Shanghai on the 20th of July. I hope very much for those of you who are going to attend have a great safe travel over there. We look forward to seeing you. Hope you've had a good morning, and get into the sessions next door so you get to understand the technology. Thank you very much, ladies and gentlemen. (upbeat innovative instrumental)
SUMMARY :
This is Lenovo Transform. How are you all doing this morning? Not a cloud in the sky, perfect. One of the things about Lenovo that we say all the time... from the mobile Internet to the Smart Internet and the demo sessions with our segment general managers and the cost economics we get, and I just visited and the control of on-premise IT. and the feedback to date has been fantastic. and all of it based on the Intel Xeon scalable processor. and ThinkAgile, specifically. and it's an incredible innovation in the marketplace. the best of the best to our customers, and also in R&D to be able to deliver end-to-end solutions. Thank you. some of the technology to solve some of the most challenging Narrator: Different creates one of the most powerful in the world as you can see here. So maybe we can just talk a little bit Because all of the new racks have to be fully integrated from outside the company to look end to end about some of the new systems, the brands. Different builds the data center you need in the DCG space, and we are very much ready to disrupt. and change the way we work. and we are delighted to be one of your strategic partners, it's been a bit of a challenge over the past several months. and technology for workplace transformation, I've heard a lot of the same kinds of words Last question, what is your view on device and be able to pay as you go. It's a great pleasure to work with you, and most powerful features of the ThinkPad today. and get into the sessions next door
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Shaneil | PERSON | 0.99+ |
Erich Windmuller | PERSON | 0.99+ |
Richard Sapper | PERSON | 0.99+ |
Lenovo | ORGANIZATION | 0.99+ |
Europe | LOCATION | 0.99+ |
1992 | DATE | 0.99+ |
two | QUANTITY | 0.99+ |
Patrick Ewing | PERSON | 0.99+ |
Microsoft | ORGANIZATION | 0.99+ |
Data Center Group | ORGANIZATION | 0.99+ |
Dell | ORGANIZATION | 0.99+ |
Romania | LOCATION | 0.99+ |
Rupal Shah | PERSON | 0.99+ |
Matt Eastwood | PERSON | 0.99+ |
Christian Teismann | PERSON | 0.99+ |
May 15 | DATE | 0.99+ |
Rod | PERSON | 0.99+ |
Erich | PERSON | 0.99+ |
Australia | LOCATION | 0.99+ |
Rupal | PERSON | 0.99+ |
Alibaba | ORGANIZATION | 0.99+ |
Japan | LOCATION | 0.99+ |
IBM | ORGANIZATION | 0.99+ |
Pat Moorhead | PERSON | 0.99+ |
Spain | LOCATION | 0.99+ |
Amazon | ORGANIZATION | 0.99+ |
Raleigh | LOCATION | 0.99+ |
Tencent | ORGANIZATION | 0.99+ |
Asia | LOCATION | 0.99+ |
2001 | DATE | 0.99+ |
25 gig | QUANTITY | 0.99+ |
Blade Network Technologies | ORGANIZATION | 0.99+ |
New York | LOCATION | 0.99+ |
Madhu | PERSON | 0.99+ |
DCG | ORGANIZATION | 0.99+ |
Leonardo DiCaprio | PERSON | 0.99+ |
40 | QUANTITY | 0.99+ |
Kirk | PERSON | 0.99+ |
100% | QUANTITY | 0.99+ |
14 servers | QUANTITY | 0.99+ |
Barcelona | LOCATION | 0.99+ |
12 times | QUANTITY | 0.99+ |
2020 | DATE | 0.99+ |
12 years | QUANTITY | 0.99+ |
Bryan Smith, Rocket Software - IBM Machine Learning Launch - #IBMML - #theCUBE
>> Announcer: Live from New York, it's theCUBE, covering the IBM Machine Learning Launch Event, brought to you by IBM. Now, here are your hosts, Dave Vellante and Stu Miniman. >> Welcome back to New York City, everybody. We're here at the Waldorf Astoria covering the IBM Machine Learning Launch Event, bringing machine learning to the IBM Z. Bryan Smith is here, he's the vice president of R&D and the CTO of Rocket Software, powering the path to digital transformation. Bryan, welcome to theCUBE, thanks for coming on. >> Thanks for having me. >> So, Rocket Software, Waltham, Mass. based, close to where we are, but a lot of people don't know about Rocket, so pretty large company, give us the background. >> It's been around for, this'll be our 27th year. Private company, we've been a partner of IBM's for the last 23 years. Almost all of that is in the mainframe space, or we focused on the mainframe space, I'll say. We have 1,300 employees, we call ourselves Rocketeers. It's spread around the world. We're really an R&D focused company. More than half the company is engineering, and it's spread across the world on every continent and most major countries. >> You're esstenially OEM-ing your tools as it were. Is that right, no direct sales force? >> About half, there are different lenses to look at this, but about half of our go-to-market is through IBM with IBM-labeled, IBM-branded products. We've always been, for the side of products, we've always been the R&D behind the products. The partnership, though, has really grown. It's more than just an R&D partnership now, now we're doing co-marketing, we're even doing some joint selling to serve IBM mainframe customers. The partnership has really grown over these last 23 years from just being the guys who write the code to doing much more. >> Okay, so how do you fit in this announcement. Machine learning on Z, where does Rocket fit? >> Part of the announcement today is a very important piece of technology that we developed. We call it data virtualization. Data virtualization is really enabling customers to open their mainframe to allow the data to be used in ways that it was never designed to be used. You might have these data structures that were designed 10, 20, even 30 years ago that were designed for a very specific application, but today they want to use it in a very different way, and so, the traditional path is to take that data and copy it, to ETL it someplace else they can get some new use or to build some new application. What data virtualization allows you to do is to leave that data in place but access it using APIs that developers want to use today. They want to use JSON access, for example, or they want to use SQL access. But they want to be able to do things like join across IMS, DB2, and VSAM all with a single query using an SQL statement. We can do that relational databases and non-relational databases. It gets us out of this mode of having to copy data into some other data store through this ETL process, access the data in place, we call it moving the applications or the analytics to the data versus moving the data to the analytics or to the applications. >> Okay, so in this specific case, and I have said several times today, as Stu has heard me, two years ago IBM had a big theme around the z13 bringing analytics and transactions together, this sort of extends that. Great, I've got this transaction data that lives behind a firewall somewhere. Why the mainframe, why now? >> Well, I would pull back to where I said where we see more companies and organizations wanting to move applications and analytics closer to the data. The data in many of these large companies, that core business-critical data is on the mainframe, and so, being able to do more real time analytics without having to look at old data is really important. There's this term data gravity. I love the visual that presents in my mind that you have these different masses, these different planets if you will, and the biggest, massivest planet in that solar system really is the data, and so, it's pulling the smaller satellites if you will into this planet or this star by way of gravity because data is, data's a new currency, data is what the companies are running on. We're helping in this announcement with being able to unlock and open up all mainframe data sources, even some non-mainframe data sources, and using things like Spark that's running on the platform, that's running on z/OS to access that data directly without having to write any special programming or any special code to get to all their data. >> And the preferred place to run all that data is on the mainframe obviously if you're a mainframe customer. One of the questions I guess people have is, okay, I get that, it's the transaction data that I'm getting access to, but if I'm bringing transaction and analytic data together a lot of times that analytic data might be in social media, it might be somewhere else not on the mainframe. How do envision customers dealing with that? Do you have tooling them to do that? >> We do, so this data virtualization solution that I'm talking about is one that is mainframe resident, but it can also access other data sources. It can access DB2 on Linux Windows, it can access Informix, it can access Cloudant, it can access Hadoop through IBM's BigInsights. Other feeds like Twitter, like other social media, it can pull that in. The case where you'd want to do that is where you're trying to take that data and integrate it with a massive amount of mainframe data. It's going to be much more highly performant by pulling this other small amount of data into, next to that core business data. >> I get the performance and I get the security of the mainframe, I like those two things, but what about the economics? >> Couple of things. One, IBM when they ported Spark to z/OS, they did it the right way. They leveraged the architecture, it wasn't just a simple port of recompiling a bunch of open source code from Apache, it was rewriting it to be highly performant on the Z architecture, taking advantage of specialty engines. We've done the same with the data virtualization component that goes along with that Spark on z/OS offering that also leverages the architecture. We actually have different binaries that we load depending on which architecture of the machine that we're running on, whether it be a z9, an EC12, or the big granddaddy of a z13. >> Bryan, can you speak the developers? I think about, you're talking about all this mobile and Spark and everything like that. There's got to be certain developers that are like, "Oh my gosh, there's mainframe stuff. "I don't know anything about that." How do you help bridge that gap between where it lives in the tools that they're using? >> The best example is talking about embracing this API economy. And so, developers really don't care where the stuff is at, they just want it to be easy to get to. They don't have to code up some specific interface or language to get to different types of data, right? IBM's done a great job with the z/OS Connect in opening up the mainframe to the API economy with ReSTful interfaces, and so with z/OS Connect combined with Rocket data virtualization, you can come through that z/OS Connect same path using all those same ReSTful interfaces pushing those APIs out to tools like Swagger, which the developers want to use, and not only can you get to the applications through z/OS Connect, but we're a service provider to z/OS Connect allowing them to also get to every piece of data using those same ReSTful APIs. >> If I heard you correctly, the developer doesn't need to even worry about that it's on mainframe or speak mainframe or anything like that, right? >> The goal is that they never do. That they simply see in their tool-set, again like Swagger, that they have data as well as different services that they can invoke using these very straightforward, simple ReSTful APIs. >> Can you speak to the customers you've talked to? You know, there's certain people out in the industry, I've had this conversation for a few years at IBM shows is there's some part of the market that are like, oh, well, the mainframe is this dusty old box sitting in a corner with nothing new, and my experience has been the containers and cool streaming and everything like that, oh well, you know, mainframe did virtualization and Linux and all these things really early, decades ago and is keeping up with a lot of these trends with these new type of technologies. What do you find in the customers that, how much are they driving forward on new technologies, looking for that new technology and being able to leverage the assets that they have? >> You asked a lot of questions there. The types of customers certainly financial and insurance are the big two, but that doesn't mean that we're limited and not going after retail and helping governments and manufacturing customers as well. What I find is talking with them that there's the folks who get it and the folks who don't, and the folks who get it are the ones who are saying, "Well, I want to be able "to embrace these new technologies," and they're taking things like open source, they're looking at Spark, for example, they're looking at Anaconda. Last week, we just announced at the Anaconda Conference, we stepped on stage with Continuum, IBM, and we, Rocket, stood up there talking about this partnership that we formed to create this ecosystem because the development world changes very, very rapidly. For a while, all the rage was JDBC, or all the rage was component broker, and so today it's Spark and Anaconda are really in the forefront of developers' minds. We're constantly moving to keep up with developers because that's where the action's happening. Again, they don't care where the data is housed as long as you can open that up. We've been playing with this concept that came up from some research firm called two-speed IT where you have maybe your core business that has been running for years, and it's designed to really be slow-moving, very high quality, it keeps everything running today, but they want to embrace some of their new technologies, they want to be able to roll out a brand-new app, and they want to be able to update that multiple times a week. And so, this two-speed IT says, you're kind of breaking 'em off into two separate teams. You don't have to take your existing infrastructure team and say, "You must embrace every Agile "and every DevOps type of methodology." What we're seeing customers be successful with is this two-speed IT where you can fracture these two, and now you need to create some nice integration between those two teams, so things like data virtualization really help with that. It opens up and allows the development teams to very quickly access those assets on the mainframe in this case while allowing those developers to very quickly crank out an application where quality is not that important, where being very quick to respond and doing lots of AB testing with customers is really critical. >> Waterfall still has its place. As a company that predominately, or maybe even exclusively is involved in mainframe, I'm struck by, it must've been 2008, 2009, Paul Maritz comes in and he says VMWare our vision is to build the software mainframe. And of course the world said, "Ah, that's, mainframe's dead," we've been hearing that forever. In many respects, I accredit the VMWare, they built sort of a form of software mainframe, but now you hear a lot of talk, Stu, about going back to bare metal. You don't hear that talk on the mainframe. Everything's virtualized, right, so it's kind of interesting to see, and IBM uses the language of private cloud. The mainframe's, we're joking, the original private cloud. My question is you're strategy as a company has been always focused on the mainframe and going forward I presume it's going to continue to do that. What's your outlook for that platform? >> We're not exclusively by the mainframe, by the way. We're not, we have a good mix. >> Okay, it's overstating that, then. It's half and half or whatever. You don't talk about it, 'cause you're a private company. >> Maybe a little more than half is mainframe-focused. >> Dave: Significant. >> It is significant. >> You've got a large of proportion of the company on mainframe, z/OS. >> So we're bullish on the mainframe. We continue to invest more every year. We invest, we increase our investment every year, and so in a software company, your investment is primarily people. We increase that by double digits every year. We have license revenue increases in the double digits every year. I don't know many other mainframe-based software companies that have that. But I think that comes back to the partnership that we have with IBM because we are more than just a technology partner. We work on strategic projects with IBM. IBM will oftentimes stand up and say Rocket is a strategic partner that works with us on hard problem-solving customers issues every day. We're bullish, we're investing more all the time. We're not backing away, we're not decreasing our interest or our bets on the mainframe. If anything, we're increasing them at a faster rate than we have in the past 10 years. >> And this trend of bringing analytics and transactions together is a huge mega-trend, I mean, why not do it on the mainframe? If the economics are there, which you're arguing that in many use cases they are, because of the value component as well, then the future looks pretty reasonable, wouldn't you say? >> I'd say it's very, very bright. At the Anaconda Conference last week, I was coming up with an analogy for these folks. It's just a bunch of data scientists, right, and during most of the breaks and the receptions, they were just asking questions, "Well, what is a mainframe? "I didn't know that we still had 'em, "and what do they do?" So it was fun to educate them on that. But I was trying to show them an analogy with data warehousing where, say that in the mid-'90s it was perfectly acceptable to have a separate data warehouse separate from your transaction system. You would copy all this data over into the data warehouse. That was the model, right, and then slowly it became more important that the analytics or the BI against that data warehouse was looking at more real time data. So then it became more efficiencies and how do we replicate this faster, and how do we get closer to, not looking at week-old data but day-old data? And so, I explained that to them and said the days of being able to do analytics against old data that's copied are going away. ETL, we're also bullish to say that ETL is dead. ETL's future is very bleak. There's no place for it. It had its time, but now it's done because with data virtualization you can access that data in place. I was telling these folks as they're talking about, these data scientists, as they're talking about how they look at their models, their first step is always ETL. And so I told them this story, I said ETL is dead, and they just look at me kind of strange. >> Dave: Now the first step is load. >> Yes, there you go, right, load it in there. But having access from these platforms directly to that data, you don't have to worry about any type of a delay. >> What you described, though, is still common architecture where you've got, let's say, a Z mainframe, it's got an InfiniBand pipe to some exit data warehouse or something like that, and so, IBM's vision was, okay, we can collapse that, we can simplify that, consolidate it. SAP with HANA has a similar vision, we can do that. I'm sure Oracle's got their vision. What gives you confidence in IBM's approach and legs going forward? >> Probably due to the advances that we see in z/OS itself where handling mixed workloads, which it's just been doing for many of the 50 years that it's been around, being able to prioritize different workloads, not only just at the CPU dispatching, but also at the memory usage, also at the IO, all the way down through the channel to the actual device. You don't see other operating systems that have that level of granularity for managing mixed workloads. >> In the security component, that's what to me is unique about this so-called private cloud, and I say, I was using that software mainframe example from VMWare in the past, and it got a good portion of the way there, but it couldn't get that last mile, which is, any workload, any application with the performance and security that you would expect. It's just never quite got there. I don't know if the pendulum is swinging, I don't know if that's the accurate way to say it, but it's certainly stabilized, wouldn't you say? >> There's certainly new eyes being opened every day to saying, wait a minute, I could do something different here. Muscle memory doesn't have to guide me in doing business the way I have been doing it before, and that's this muscle memory I'm talking about of this ETL piece. >> Right, well, and a large number of workloads in mainframe are running Linux, right, you got Anaconda, Spark, all these modern tools. The question you asked about developers was right on. If it's independent or transparent to developers, then who cares, that's the key. That's the key lever this day and age is the developer community. You know it well. >> That's right. Give 'em what they want. They're the customers, they're the infrastructure that's being built. >> Bryan, we'll give you the last word, bumper sticker on the event, Rocket Software, your partnership, whatever you choose. >> We're excited to be here, it's an exciting day to talk about machine learning on z/OS. I say we're bullish on the mainframe, we are, we're especially bullish on z/OS, and that's what this even today is all about. That's where the data is, that's where we need the analytics running, that's where we need the machine learning running, that's where we need to get the developers to access the data live. >> Excellent, Bryan, thanks very much for coming to theCUBE. >> Bryan: Thank you. >> And keep right there, everybody. We'll be back with our next guest. This is theCUBE, we're live from New York City. Be right back. (electronic keyboard music)
SUMMARY :
Event, brought to you by IBM. powering the path to close to where we are, but and it's spread across the Is that right, no direct sales force? from just being the Okay, so how do you or the analytics to the data versus Why the mainframe, why now? data is on the mainframe, is on the mainframe obviously It's going to be much that also leverages the architecture. There's got to be certain They don't have to code up some The goal is that they never do. and my experience has been the containers and the folks who get it are the ones who You don't hear that talk on the mainframe. the mainframe, by the way. It's half and half or whatever. half is mainframe-focused. of the company on mainframe, z/OS. in the double digits every year. the days of being able to do analytics directly to that data, you don't have it's got an InfiniBand pipe to some for many of the 50 years I don't know if that's the in doing business the way I is the developer community. They're the customers, bumper sticker on the the developers to access the data live. very much for coming to theCUBE. This is theCUBE, we're
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
IBM | ORGANIZATION | 0.99+ |
Bryan | PERSON | 0.99+ |
Dave Vellante | PERSON | 0.99+ |
Paul Maritz | PERSON | 0.99+ |
Dave | PERSON | 0.99+ |
Stu Miniman | PERSON | 0.99+ |
Rocket Software | ORGANIZATION | 0.99+ |
50 years | QUANTITY | 0.99+ |
2009 | DATE | 0.99+ |
New York City | LOCATION | 0.99+ |
2008 | DATE | 0.99+ |
Oracle | ORGANIZATION | 0.99+ |
27th year | QUANTITY | 0.99+ |
New York City | LOCATION | 0.99+ |
first step | QUANTITY | 0.99+ |
two | QUANTITY | 0.99+ |
JDBC | ORGANIZATION | 0.99+ |
1,300 employees | QUANTITY | 0.99+ |
Continuum | ORGANIZATION | 0.99+ |
Last week | DATE | 0.99+ |
New York | LOCATION | 0.99+ |
Anaconda | ORGANIZATION | 0.99+ |
two things | QUANTITY | 0.99+ |
mid-'90s | DATE | 0.99+ |
Spark | TITLE | 0.99+ |
Rocket | ORGANIZATION | 0.99+ |
z/OS Connect | TITLE | 0.99+ |
10 | DATE | 0.99+ |
two teams | QUANTITY | 0.99+ |
Linux | TITLE | 0.99+ |
today | DATE | 0.99+ |
two-speed | QUANTITY | 0.99+ |
two separate teams | QUANTITY | 0.99+ |
Z. Bryan Smith | PERSON | 0.99+ |
SQL | TITLE | 0.99+ |
Bryan Smith | PERSON | 0.99+ |
z/OS | TITLE | 0.98+ |
two years ago | DATE | 0.98+ |
ReSTful | TITLE | 0.98+ |
Swagger | TITLE | 0.98+ |
last week | DATE | 0.98+ |
decades ago | DATE | 0.98+ |
DB2 | TITLE | 0.98+ |
HANA | TITLE | 0.97+ |
IBM Machine Learning Launch Event | EVENT | 0.97+ |
Anaconda Conference | EVENT | 0.97+ |
Hadoop | TITLE | 0.97+ |
Spark | ORGANIZATION | 0.97+ |
One | QUANTITY | 0.97+ |
Informix | TITLE | 0.96+ |
VMWare | ORGANIZATION | 0.96+ |
More than half | QUANTITY | 0.95+ |
z13 | COMMERCIAL_ITEM | 0.95+ |
JSON | TITLE | 0.95+ |
Amy Lewis & John Troyer | EMC World 2014
>> A cube at DMC World twenty fourteen is brought to you by D. M. C. Redefine, see innovating the world's first converged infrastructure solution for private cloud computing brocade. Say goodbye to the status quo and hello to Brocade. >> Welcome back to the Cube. This silken angle TVs live wall to wall Coverage of DMC World twenty fourteen here in the Sands Convention Center in Las Vegas. We've got three days to stage is over eighty guests. Lots of practitioners, execs, business leaders got a special segment. I'm bringing you today, bringing onto two thirds of the geek whispers, podcasts, Those in the story for the virtual ization and Claude Communities. No art is to guess. Well, let me introduce it's John Troyer, who's making his debut as the founder of tech reckoning. >> Thanks for having me. >> And we've got Amy Lewis influence marketing from Cisco. Name is your first time on the Cube, so, you know, welcome to the program. >> Thank you for having me on. >> All right, so So, guys, you know, we've been to a lot of conferences way we've hung out with, You know, the various influencers bloggers. It's changed a lot. This is my twelfth year coming M. C World. If you had told me twelve years ago some of things I'd be doing at this show, I wouldn't have believed you. I mean, I was one of the guys in a polo that only got out of out of the office once a year to give a presentation and, you know, talks in people about some cool tak um, and you know, social media is one of those things that, you know turn my career. Eleven. So you know what? Let's have a conversation about what's going on in the industry with kind of community influences and everything. John, maybe you could start us often. You know, Maybe if it leads in tow your new gigs? >> Sure, sure, on one on one, and things have changed. On the other hand, the same dynamics are playing out. Buying the buying cycle has changed. The buying process has changed. Customers are looking much more to their peers and not to traditional media analysts. Marketing folks, they can't find more ads. You can't send out more E mail. So what do you do? You need to get part of the conversation. We've been saying that for five or ten years, that's actually happened. Now the folks that were early on into the blogging space have turned themselves into communicators as well as technologists. We've seen, you know, their careers have have gone and all sorts of interesting places, for instance, you. But I think now that even we could talk about his art Is blogging dead? But I think now we're seeing it. We're seeing social media not as a trade or a practice practice, but simply a tool set that we all use. So that's all I'm saying is it's a It's more of a it spread throughout our organization. Not so much in one tiny niche, right? >> Yeah, Jonah, I love that point. I I I've been preaching for a bunch of years that this is an important skill, something you have to have their wonderful tools. But you've been doing community for a lot longer than Social Media has been around, and, you know, so it's peace, Amy, your influence marketing. What would please way out on this? >> Yeah, I chose the title, actually myself on purpose. To say it's not just social media, think social Media is very important, but like John was saying that to me is a set of tools. They're important platforms or important communications channels, but influencers the people who between the term citizen analysts they are unpaid analyst. But people are very passionate about technology, and they want to write on block and share, really engage their community. That's an important group of people. It's a really a buying center, and we have to find new ways to address them. So community is more important than >> ever. Citizen analysts thought, Let's focus that >> some of the >> people you know, I say some people goto event and they get it, get it, get wined and dined and they get to, you know, write about a bunch of stuff I'm like, you know you're better than journalists, you know, you'll You know you do some really good stuff and sometimes it's a little bit too friendly to the people that are doing it. So you know where do you see the role of kind of the press? You know, the analyst and the influencer? >> It's a great question I've been checking. We need to abstract the or chart. It is. It is a complicated question, but I think the traditional presses really trained and rightfully so in giving us that neutrality. So that is still a very important role. I think the analysts are paid Tio Tio, analyze particular sets, etcetera. They have nation specialty. I think the citizen analyst is interesting because they are what you don't know about the neutrality. But you do know that there are people who roll up their sleeves and really touched the technology. So that becomes a very interesting set because they really care about the technology Kazakh but could become their problem if they don't, you know, raise our voice and sort of engaged with technology and let the community know what, what the new trends are, what they need, what business needs. Our etcetera gives us a really applied version, the PR in the e R outside. >> Don't you want to comment on matter? >> I mean, these are the folks that they lose their jobs if they picked the wrong technology. So they have much more. Their discussions have it. They have more skin in the game. >> Aye, that's right. If you've got the practitioner, you know whether it be the end user sometime times it's the you know channel guy that they do that that's good, You know? What about the people inside the corporations that are also using these? >> I'm super bullish about the use of employees as advocates and evangelists in our community, both for technical education. And for the commercial part of our conversation in the enterprise space, we don't sell solutions with Russia. Your hair's a pressure and very nice calm. Give me a call. We sell it with relationships with people. I've been working on the social media since it existed, I suppose. And what we've seen over and over again is the social channels are really great for getting the word out. But without that personal component, it's like just handing out brochures. So you need your employees out there. You need your employees talking to folks. You need your employees without their representing your brand, just like they would have an event. I've seen that at something. On one hand, it's something that's so trivial that we all agree it's true. On the other hand, I don't. I think a lot of people are just realizing that now. >> So, John, you know, there's some some big companies, you know, creative certification programs to do some of this. There's some companies that just, you know, sign everybody up and, you know, it could be kind of an echo chamber or things like that. You know what? What do you see in these days? To kind of help out. You know the community >> well. There's a lot of software and a lot of programmatic things you could do. Those may be useful in terms of organizing you. It comes down to the people in the culture of the company and help much. You trust your people to go out. I think the best thing we can do is sit up platform for folks to be able to, to communicate. I think that's actually what Amy does really well at Cisco. >> X. It's, um I always talk about influence marketing as being people, platforms in content. And so I agree. I think that we sorted out some of the platform issues as we've learned about social media and grew up with it. I think that we are still working out the people in the content side and what's appropriate, how we can join together and do that and how we can creates a mute platforms may be using the tools of social tio to drive the conversation forward. >> All right. So, I mean, I got one for you. You know, how do we balance the kind of creation of information and kind of the community and fund? I mean, you do a lot of fun event you've got, you know, awful club this week. You've got, you know, bacon, stack and B bacon and bacon. I e I mean, I can't keep track of you, deport vacants and everything. And, you know, there'd be some executives here that would be like that, That social stuff. And they're playing games and things like that. So how do we balance kind of attic business value and greeting, you know, value to the community. And, you know, having fun in building community. >> No, it's a great question. A couple of years ago, I got a text in the middle of the night that said, Please explain to me how the bacon is a marketing play. Please explain this and you know, I need a power point slide. So if you've never had to explain, be bacon on the power points, I for that challenge out to everyone. But I think in the last couple of years people started to see it more and more as we're, uh, we're similar to the sales role, and that's how we've sort of changed the language. So I perform a sales like function, except I don't carry a quota. So it is about building the relationship like John was saying, and it is about balancing fun with your intent. So I think that if you create a fun environment, if you create an openness and willingness to listen, then the good things will follow. So you form the relationships of people. You open up their ability to create content with you because they don't feel under attack. They're ready to share. And again, it's it's kind of a magical formula. Be nice and create opportunity. >> Yeah, so >> I think we'll part of it's a generational ship. I think part of it a generational shift and part of it is a temperamental she So tradition again, going back to sales traditional enterprise sales. You might go and play golf with somebody, cause that's what you enjoy doing for our kind of geeks. Our golf is eating bacon and talking about the duplication strategies, right? That's where we're having the most fun. So it's It's just it's same sort of thing. Just a shift in generations. >> Yeah, I wonder if you know what, what role this community help in kind of careers. You know, I think you know, we're talking so much of these shows about, you know, if your storage admin. If you're networking admin and you know you're down there, you know, configuring Luns or setting up the land, you know, we're going to have a job in a couple of years because automation is gonna change. You know, how much does the community help in kind of those career paths and education? >> So, John, I think we should interview stew on this one. Should we have the geek whispers takeover. I think this is your great example. You've talked about you, you were on a career path and we hear this a lot, and when you raise your hand to volunteer, we sort of jokingly call the spokes uniforms. You both really enjoy the technology and like to communicate about it. When you raise your hand and make yourself known to the community, to your employers, to the world at large, it gives you different opportunities. And I think I don't think you go into technology really without wanting to have an evolving, exciting career. So I think that he's becoming proficient in these tools. Joining your community is an opportunity to learn from your peers to get back to your peers and to raise her profile and open yourself up to the possibility of a new opportunity or a new idea or different engagement. A new way to learn >> In today's business environment, communication is a key part of whatever you do, even if you're the guy sitting there configuring the lungs, because if you're not communicating with your teams and the application teams and the storage of network virtualization team, you're not going to succeed so I think that's an important part of it, right? Being a communicator, absolutely critical and art. Barney. >> All right, so either one of you feel free to answer, but I think back to my early days, you know, two thousand eight, I was so excited when I got invited to a couple of conferences. A blogger, you could kind of get a pass, and I would, You know, ten might take my own vacation time and usually spend that on expenses because my employer at the time didn't get it. It was this innovation conference in, like, in a New York City with four hundred people, and it was like, kind of amazing. I've seen people go to B m world on their own dime where they can get a pass. I mean, you know, it's great to see when you when you got the passion. So I guess the question I wanted to ask is, you know, with companies today, who should they be inviting? How do they do it? You know? You know. Is it you know, the blogger Or is it the, you know, empty Alexis co expert? You know, bm where be expert, you know, What? How's that? How's that changing? Or is it >> changing? Well, I think what you've seen happen over the years is something that was a little more unstructured, which was a kind of blogger relations program. Working with both customers partners, employees in your ecosystem has turned into something a little more formal. We created the V Expert program in two thousand nine to formalize what we were already doing. It's an analogy to the endless relations, press relations, investor relations, sorts of programs. So I mean, it's it's it's a little more buttoned up. It's a little more of a membership thing, but we I know both of DMC and BM where and it Cisco, Francisco champions to try to embrace all the folks that are out there blogging. I think you know, if you're a market or you need to make sure that you're keep your eyes open and you don't just talk to the people that you've gathered in your living room, Bye. You know, a lot of it's pretty easy if you're enthusiastic about technology, if you're engaged with the technology, if you put some effort into it, it's actually pretty easy to get involved with one of these programs there, there, there and there, there, fourth of people in them right there. They're not there to say the glory of the emcee and glory of Cisco and glory of'em, where they're there to help you with your career. They're there to give you tools to give you networking and, you know, hopefully get you to places like this. So I encourage everybody that that's interested in starting, you know, go ahead and get started. It's easier than you think to get involved. >> I agree with that, and I think that way want to be almost like an airline program that you'd actually want to participate. And it's sort of my job like this is a customer service activity, and I often talk about if you talk about the large pool of influencers. Maybe they haven't identified yet. Or maybe they prefer to stay independent. Or maybe they do have interest in a lot of different technologies. Me for them to engage in one of these programs, that stolen, important set of people that you have to deal with the mark, you know, and again set up these blogger days have longer briefings. But like John was saying, When you have the group of people that you name and give it a program name, this is a little bit of inside baseball if we don't talk about giving program a name and funding can follow. So if you're working in a corporate marketing environment, it's really important to explain to people that marketing structure behind what you're doing and when you treat them as a class, it gives you some advantage is you can scale out a little easier. You can provide more assets to those individuals, and it frees you up to Dio. What I love to do, which is is to really engage with those individuals and create content with them. So, >> yeah, so how is engagement these days? You know, I think back, you know, that you know, ten years ago, you talk. You know, one percent of the community would, you know, be doing almost all the contribution. Ten percent might be a little active and everybody else's lurker. You know, when we founded Wicked Bond Day, Volonte actually has on his business card that he's a one percenter which goes back to you know it. It's, you know, the one percent that causes all the trouble, the one percent that causes all all of the commotion. So, you know, with this wave, I mean, we were founded off of, you know, economics in crowd sourcing and everything else, and the Cube is all about, you know, sharing information. We put it all out there. We want everybody to contribute and, you know, give that feedback. You know, How are we along now? You know that that journey to get more people involved. >> I think the opportunity is there more than ever. I think you're right. I mean, there's always gonna be a percentage of people who want to raise her hand, the class that want to give up their PTO to go to a conference that that had this other life they just can't help themselves. And so in some ways it's finding the most impassioned and giving them opportunities. But I think that with the platforms and the scale, there is a greater opportunity for people. They don't want to start their own block. For instance, one of the things we do it Cisco champions is allowed people to guess, block or allow them to come post a podcast. So I think there are more more ways to and there, you know, that's one example. There's lots of other groups that provide people again a little bit a dose of it so they might not want to run a full media company on their own. They don't wanna build Q, but they want to participate. And I think that we have so many more opportunities for them to do that that we're seeing group. >> We're seeing platform ships over the years. I think we as technologists human beings have a tendency to forget their past relatively quickly, as people have moved from the MySpace world to the Facebook Twitter world. I think actually, we're headed for I don't call it I don't want to call it post Facebook, but it certainly is. A multi platform world made >> it just like >> it's a multi device world. We're not opposed PC world in that. I think you're seeing the rise of more specialized communities. They come back again from from our from our origins back ten or twenty years ago. I think we're seeing that people want more deeper engagement along the company. A lot of the report building and kind of conversation. And hey, how are you? Goes on on Twitter. But I think people are really looking for a place where they can have a better conversation, more interaction, more lasting death that might not be on their own. Blogger in their own kind of indie web sort of style, roll your own block. But there are more and more platforms that people are making available for this kind of connection again. What was once niche eventually permeates the whole >> yes. So, you know, the concern I have is it's tough because it is so dispersed right now, you know? You know, I love Twitter, you know? Hi, I'm stew, you know, on Twitter. And I know you guys are big on it, too. And I don't love the multi platform discussion. You know, I always love when you dropped that kind information on the community. But, you know, how >> do we How do we get that >> depth? It's one of the things I always worry about is, you know, people will read the headline and, you know, just react at it and, you know, they might even share it a bunch, but they haven't read it. Uh, so how do we get that deeper engagement? Deeper understanding. I mean, you know, I always say, you know, the I'm too busy is a poor excuse because, you know, you know Michelangelo and I'd sign that many hours in the day way we did and, you know, sure they didn't have their phone buzzing all over >> the place. >> I actually think we should do less. Not more. I think I think too much information, too many channels, too many corporate channels, too many personal channels, too much bad content. The world does not need more crappy content. So whether you're a individual, blogger or marketer, I'd say just turn the dial back a little bit. Did work on better, longer pieces that add more? I think that's the only way that we can shift the conversation. >> Yeah, long for love it. Oh, no, absolutely. I still read so >> well. It's a curatorial function as well, that we have to be responsible. And that's yet one more way people can participate. We see people rise and in the community because they're really great curator Sze, because they syndicate the content in ways are interesting to others because time is of a value so that becomes a real asset. And the skill is Well, >> yeah, great. Great point. Could you know, so many times I'm like I really like to do a thousand word post on this, but, you know, sometimes all I'll come out of this show and take, you know, I did a year ago. I did it. I didn't article on the federation. You know, the ZPM were pivotal and coming out of the show, I've got a lot of new data, and I could really quickly take some photos. I've done. Takes some of the notes. I take some of the tweets and, you know, put together an order. Won't take me as long. I mean, I'll probably do it on the plane ride home. So what I wanna ask next is, you know, you guys see a lot of things out there. What coolest thing you're seeing either at a at a conference or event or you know what? What? What's catching, right? What? What's interesting? Done. >> There's a whole new side out there called Tech, right? I don't know what's cool out there again. I'm seeing multi channel multi, a lot of experiments. There's some cool stuff going on with the indie web. There's I mean, everything is mobile. I don't know. There's just a lot of places. It >> sounds like you Let's give the plug. Integrity has finally cool things and, you know, solid. But something >> like that tech reckoning is a site that's gonna bring. It's an independent site. It's not associate with any vendor. It's going to bring some of the community and enterprise community together to talk about some of these things about Where is it going as a whole? Where's technology going, where our career is going to try to help us get to whatever this you know, it is a service. Third platform, Whatever you wanna call it, where the heck were going? It looks pretty interesting, and it looks like it isn't gonna be quite the same thing. So we're trying to bring together a set of people and just tackle some of those problem and also work together and collaborate. It's so much easier with open source with cloud. With all the tools we have available, it's so cheap and easy to build new pieces of technology, not just a type of each other words online, but to actually build stuff that I'm very excited about. The power taking going far. This from open source, right? Taking the power of people to come together and build cool new stuff. That's what I would like to. >> Still, I'm just angry that you scooped Matt and I on getting to interview John first about >> tech recognition. So, Amy, you you do some cool things that some of events we talk about, the waffle bacon, you What have you seen out there that that's kind of interesting? Or, you know, how do you find some of the cool new ideas? >> Yeah, I think you always I'm working with a really talented events team right now. And I think one of the things I've seen them sort of transform is that social is not other, you know? And we're seeing the social and this concept of community permeate and really think about our audience to really engage that core base, those those tech enthusiasts, and to see what you can do to in engage them. So I'm saying it in real life and in these community platforms. So I think that's been one of the other great trends is watching people band together and various kinds of consortiums. I won't name names, but there's a few folks outlook community. We're seeing a lot of this happen where they're sort of grouping together, and they're saying if they pull their resource is what happens, they might be able to gather enough money to go to a conference or to fund a buddy or to get a hotel room that they've got extra spaces somebody can crash. So I'm saying it's very cool, sort of stitching together opportunity and working together to learn more. So again, the combination of the platforms, using the technology and then in real life connection. >> All right, so I've been asking all the questions here. So before we wrap up, you know, Amy, anything you want, Johnny, when as me, John same, we throw it open. When Whenever >> you first signed up for your Twitter account, did you think it would lead you here because you have the best Twitter >> account? No, actually, a friend of mine for me and Steve Todd, who was blogging before I was, and he said, You know, when there's trepidation when you're gonna get published and you never know where it leads. And we were talking about this after he and I were on the stage at Radio City Music Hall right after Bill Clinton had been on because they brought the bloggers down when we were there. And it's like, Come on, you know, I'm, you know, I'm an engineer by training, you know, I've done. You know, I've done some sales. I've done engineering. I've done you no operations. Technologist is hard. So you know, some of the places the people I've met. I mean, if you just reach out to people, it still, even though there's so many people on Twitter, you know, the people that right and our authors and bloggers, If you comment or you reach out to them, a lot of them reach back. I mean, you know, I still amazed at some of the people I've met get to rub elbows with. No, just just have had a blast with him. So >> get another one. So do you think unicorns can be trained? Do you think people have to be born with the skill set, Or do you think you can be a uniformed rancher? >> No, I think I think I think they could be trained. You know, it's absolutely it's Ah, it's a tough skill set. I mean, you know, doing video is not easy. First couple of times you do it. It's different there's there's all these muscles. You know, Writing is one of those things that you know. I thought I was an okay writer, but hadn't done a lot of it. They're things you do. So try it out. And that thing I tell you, you got to stick with it for a while. I thought Twitter was pretty stupid. First Go on it. But, you know, I stuck on it for another six months and have some fun with it. No, here we are six years later and you know it is a lot and, you know, blocking of writing and blogging and everything else you know all over. I >> like the muscle memory idea. >> It's hard. You were on camera, have remember not to scratch my face. Strange. He'll set, I ask. I actually, I'm seeing a lot of interest in short form video. I know the kids are all doing it. I mean, obviously, we're doing it here. You do it. It's part of your practice. But in talking with people about our new activities, it's just so easy to take a chair. I think that's actually, even though it's been coming up for years, I think where I think that's an interesting thing >> on all right now, I'll give one of those inside tips videos. Great. Some people don't like to watch video. Yeah, broadcaster great. Some people don't like to listen to him, you know, writing's great. Some people won't read. So you know what? One of the early lessons I had is when I was, you know, being a, you know, active member on standard evangelizing of solution. I did it everywhere it you know that give presentations that shows you put it up on slide chair. You do you two videos, you blogged about it. You talk to everybody, you bet that you can everywhere. And you know, it just permeates out there. It could be a bunch of works and then there's tools that are out there. >> They're all connected events, right? I've discovered recently, and I can't believe I just realized this. But it was with the conversation with Amy on our Christmas broadcast that even though I've been part of an online group for years, I'm part of digital marketing for BM. Where for years, Uh, actually, most of my work. Half of my work is off line having my workers meeting people in person, getting to meet them and connecting that online and offline. And the synergy there is just is immense. >> Yeah, absolutely. I mean, other than the keynotes, my phone stays in my pocket for the most time. Unless I'm going between events. It's the in real life and nearly getting to know things. I was joking, You know, Twitter went away. Tomorrow might be a little sad, but I can connect the most. All those people, we got him on LinkedIn, Facebook and, you know, email. I still use something. Don't taking their holds. Absolutely. So you know, to wrap. I guess if you want to, just You know what people find more on your podcast. Find your website. You know Amy, Like it start? Well, >> where >> are Equus? Versace, of course. Geek hyphen whispers dot com on way, published every week. So give us a listen. See what you think. And I'm >> Matthew Brender. Sorry you couldn't join this time, but it's a lot as it were. A DMC world and you two are here in Matthew's. >> It's hard. We're going toe to toe. It's true. We're going to record with him like it's a Max headroom figure on a yes tomorrow, so and also I'm on Twitter as calms mention and I block under that same constantly dot com girls have engineers. That's true. I have engineers, unplug dot com as well. And now sixty second Tech, the short first on the popcorn version >> and I. J. Troia on Twitter and tech reckoning dot com. I went inside. >> Hey, Amy, John. Thanks so much. We We love taking the podcast. Inception. Sile inside the Cube. Look forward to seeing you lost events connecting with the community and everybody. Definitely check out their stuff. I'm at stew on Twitter with yvonne dot org's is where most of my articles go, and, of course, silicon angled on TV is where you can find all the video. Thanks for joining us. We will be back with the rest of DMC world covered.
SUMMARY :
A cube at DMC World twenty fourteen is brought to you by D. I'm bringing you today, bringing onto two thirds of the geek whispers, Cube, so, you know, welcome to the program. and you know, social media is one of those things that, you know turn my career. We've seen, you know, been around, and, you know, so it's peace, Amy, your influence marketing. Yeah, I chose the title, actually myself on purpose. get to, you know, write about a bunch of stuff I'm like, you know you're better than journalists, you know, you'll You know you you know, raise our voice and sort of engaged with technology and let the community know what, I mean, these are the folks that they lose their jobs if they picked the wrong technology. you know channel guy that they do that that's good, You know? So you need your employees out there. There's some companies that just, you know, sign everybody up and, you know, it could be kind of an echo chamber or things There's a lot of software and a lot of programmatic things you could do. I think that we sorted out some of the platform issues as we've I mean, you do a lot of fun event you've got, you know, So I think that if you create a fun environment, cause that's what you enjoy doing for our kind of geeks. You know, I think you know, we're talking so much of these shows about, you know, if your storage admin. and when you raise your hand to volunteer, we sort of jokingly call the spokes uniforms. In today's business environment, communication is a key part of whatever you do, even if you're the guy sitting there configuring the lungs, I mean, you know, it's great to see when you when you got the passion. you know, if you're a market or you need to make sure that you're keep your eyes open and you don't just talk to the people that you've gathered the mark, you know, and again set up these blogger days have longer briefings. You know, one percent of the community would, you know, there, you know, that's one example. I think we as technologists human beings have a tendency But I think people are really looking for a place where they can have a better conversation, more interaction, And I know you guys are big on it, too. It's one of the things I always worry about is, you know, people will read the headline and, I think that's the only way that we can shift the conversation. I still read so And the skill is Well, I take some of the tweets and, you know, put together an order. I don't know what's cool out there you know, solid. where our career is going to try to help us get to whatever this you know, it is a service. the waffle bacon, you What have you seen out there that that's kind of interesting? and to see what you can do to in engage them. So before we wrap up, you know, Amy, anything you want, I mean, you know, I still amazed at some of the people I've met Do you think people have to be born with the skill set, Or do you think you can be a uniformed rancher? I mean, you know, doing video is not easy. I know the kids are all doing it. One of the early lessons I had is when I was, you know, being a, And the synergy there is just is So you know, to wrap. See what you think. you two are here in Matthew's. And now sixty second Tech, the short first on the I went inside. Look forward to seeing you lost events connecting with the community and everybody.
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
John Troyer | PERSON | 0.99+ |
Steve Todd | PERSON | 0.99+ |
John | PERSON | 0.99+ |
Amy | PERSON | 0.99+ |
Matthew Brender | PERSON | 0.99+ |
Matt | PERSON | 0.99+ |
Cisco | ORGANIZATION | 0.99+ |
Bill Clinton | PERSON | 0.99+ |
DMC | ORGANIZATION | 0.99+ |
Johnny | PERSON | 0.99+ |
Jonah | PERSON | 0.99+ |
New York City | LOCATION | 0.99+ |
Amy Lewis | PERSON | 0.99+ |
five | QUANTITY | 0.99+ |
one percent | QUANTITY | 0.99+ |
ten years | QUANTITY | 0.99+ |
BM | ORGANIZATION | 0.99+ |
twelfth year | QUANTITY | 0.99+ |
two videos | QUANTITY | 0.99+ |
Tomorrow | DATE | 0.99+ |
Volonte | PERSON | 0.99+ |
D. M. C. Redefine | PERSON | 0.99+ |
both | QUANTITY | 0.99+ |
Sands Convention Center | LOCATION | 0.99+ |
six years later | DATE | 0.99+ |
Ten percent | QUANTITY | 0.99+ |
ORGANIZATION | 0.99+ | |
twelve years ago | DATE | 0.99+ |
First | QUANTITY | 0.98+ |
Las Vegas | LOCATION | 0.98+ |
One | QUANTITY | 0.98+ |
four hundred people | QUANTITY | 0.98+ |
Christmas | EVENT | 0.98+ |
three days | QUANTITY | 0.98+ |
Matthew | PERSON | 0.98+ |
tomorrow | DATE | 0.98+ |
first time | QUANTITY | 0.98+ |
one | QUANTITY | 0.98+ |
one example | QUANTITY | 0.98+ |
first | QUANTITY | 0.98+ |
ORGANIZATION | 0.97+ | |
ten | QUANTITY | 0.97+ |
six months | QUANTITY | 0.97+ |
ten | DATE | 0.97+ |
ten years ago | DATE | 0.97+ |
today | DATE | 0.97+ |
Eleven | QUANTITY | 0.97+ |
Wicked Bond Day | ORGANIZATION | 0.97+ |
Versace | PERSON | 0.97+ |
DMC World | ORGANIZATION | 0.96+ |
Michelangelo | PERSON | 0.96+ |
stew | PERSON | 0.96+ |
sixty second | QUANTITY | 0.96+ |
ORGANIZATION | 0.96+ | |
I. J. Troia | PERSON | 0.95+ |
two | QUANTITY | 0.95+ |
once a year | QUANTITY | 0.95+ |
twenty years ago | DATE | 0.95+ |
this week | DATE | 0.95+ |
Half | QUANTITY | 0.95+ |
Aaron T. Myers Cloudera Software Engineer Talking Cloudera & Hadooop
>>so erin you're a technique for a Cloudera, you're a whiz kid from Brown, you have, how many Brown people are engineers here at Cloudera >>as of monday, we have five full timers and two interns at the moment and we're trying to hire more all the time. >>Mhm. So how many interns? >>Uh two interns from Brown this this summer? A few more from other schools? Cool, >>I'm john furry with silicon angle dot com. Silicon angle dot tv. We're here in the cloud era office in my little mini studio hasn't been built out yet, It was studio, we had to break it down for a doctor, ralph kimball, not richard Kimble from uh I called him on twitter but coupon um but uh the data warehouse guru was in here um and you guys are attracting a lot of talent erin so tell us a little bit about, you know, how Claudia is making it happen and what's the big deal here, people smart here, it's mature, it's not the first time around this company, this company has some some senior execs and there's been a lot, a lot of people uh in the market who have been talking about uh you know, a lot of first time entrepreneurs doing their startups and I've been hearing for some folks in in the, in the trenches that there's been a frustration and start ups out there, that there's a lot of first time entrepreneurs and everyone wants to be the next twitter and there's some kind of companies that are straddling failure out there? And and I was having that conversation with someone just today and I said, they said, what's it like Cloudera and I said, uh, this is not the first time crew here in Cloudera. So, uh, share with the folks out there, what you're seeing for Cloudera and the management team. >>Sure. Well, one of the most attractive parts about working Cloudera for me, one of the reasons I, I really came here was have been incredibly experienced management team, Mike Charles, they've all there at the top of this Oregon, they have all done this before they founded startups, Growing startups, old startups and uh, especially in contrast with my, the place where I worked previously. Uh, the amount of experience here is just tremendous. You see them not making mistakes where I'm sure others would. >>And I mean, Mike Olson is veteran. I mean he's been, he's an adviser to start ups. I know he's been in some investors. Amer was obviously PhD candidates bolted out the startup, sold it to yahoo, worked at, yahoo, came back finish his PhD at stanford under Mendel over there in the PhD program over this, we banged in a speech. He came back entrepreneur residents, Excel partners. Now it does Cloudera. Um, when did you join the company and just take us through who you are and when you join Cloudera, I want your background. >>Sure. So I, I joined a little over a year ago is about 30 people at the time. Uh, I came from a small start up of the music online music store in new york city um uh, which doesn't really exist all that much anymore. Um but you know, I I sort of followed my other colleagues from Brown who worked here um was really sold by the management team and also by the tremendous market opportunity that that Hadoop has right now. Uh Cloudera was very much the first commercial player there um which is really a unique experience and I think you've covered this pretty well before. I think we all around here believe that uh the markets only growing. Um and we're going to see the market and the big data market in general get bigger and bigger in the next few years. >>So, so obviously computer science is all the rage and and I'm particularly proud of hangout, we've had conversations in the hallway while you're tweeting about this and that. Um, but you know, silicon angles home is here, we've had, I've had a chance to watch you and the other guys here grow from, you know, from your other office was a san mateo or san Bruno somewhere in there. Like >>uh it was originally in burlingame, then we relocate the headquarters Palo Alto and now we have a satellite up in san Francisco. >>So you guys bolted out. You know, you have a full on blow in san Francisco office. So um there was a big busting at the seams here in Palo Alto people commuting down uh even building their burning man. Uh >>Oh yeah sure >>skits here and they're constructing their their homes here, but burning man, so we're doing that in san Francisco, what's the vibe like in san Francisco, tell us what's going on >>in san Francisco, san Francisco is great. It's, I'm I live in san Francisco as do a lot of us. About half the engineering team works up there now. Um you know we're running out of space there certainly. Um and you're already, oh yeah, oh yeah, we're hiring as fast as we absolutely can. Um so definitely not space to build the burning man huts there like like there is down, down in Palo Alto but it's great up there. >>What are you working on right now for project insurance? The computer science is one of the hot topics we've been covering on silicon angle, taking more of a social angle, social media has uh you know, moves from this pr kind of, you know, check in facebook fan page to hype to kind of a real deal social marketplace where you know data, social data, gestural data, mobile data geo data data is the center of the value proposition. So you live that every day. So talk about your view on the computer science landscape around data and why it's such a big deal. >>Oh sure. Uh I think data is sort of one of those uh fundamental uh things that can be uh mind for value across every industry, there's there's no industry out there that can't benefit from better understanding what their customers are doing, what their competitors are doing etcetera. And that's sort of the the unique value proposition of, you know, stuff like Hadoop. Um truly we we see interest from every sector that exists, which is great as for what the project that I'm specifically working on right now, I primarily work on H. D. F. S, which is the Hadoop distributed file system underlies pretty much all the other um projects in the Hadoop ecosystem. Uh and I'm particularly working with uh other colleagues at Cloudera and at other companies, yahoo and facebook on high availability for H. D. F. S, which has been um in some deployments is a serious concern. Hadoop is primarily a batch processing system, so it's less of a concern than in others. Um but when you start talking about running H base, which needs to be up all the time serving live traffic than having highly available H DFS is uh necessity and we're looking forward to delivering that >>talk about the criticism that H. D. F. S has been having. Um Well, I wouldn't say criticism. I mean, it's been a great, great product that produced the HDs, a core parts of how do you guys been contributing to the standard of Apache, that's no secret to the folks out there, that cloud area leads that effort. Um but there's new companies out there kind of trying a new approach and they're saying they're doing it better, what are they saying in terms and what's really happening? So, you know, there's some argument like, oh, we can do it better. And what's the what, why are they doing it, that was just to make money do a new venture, or is that, what's your opinion on that? Yeah, >>sure. I mean, I think it's natural to to want to go after uh parts of the core Hadoop system and say, you know, Hadoop is a great ecosystem, but what if we just swapped out this part or swapped out that part, couldn't couldn't we get some some really easy gains. Um and you know, sometimes that will be true. I have confidence that that that just will not simply not be true in in the very near future. One of the great benefits about Apache, Hadoop being open source is that we have a huge worldwide network of developers working at some of the best engineering organizations in the world who are all collaborating on this stuff. Um and, you know, I firmly believe that the collaborative open source process produces the best software and that's that's what Hadoop is at its very core. >>What about the arguments are saying that, oh, I need to commercialize it differently for my installed base bolt on a little proprietary extensions? Um That's legitimate argument. TMC might take that approach or um you know, map are I was trying to trying to rewrite uh H. T. F. >>S. To me, is >>it legitimate? I mean is there fighting going on in the standards? Maybe that's a political question you might want to answer. But give me a shot. >>I mean the Hadoop uh isn't there's no open standard for Hadoop. You can't say like this is uh this is like do compatible or anything like that. But you know what you can say is like this is Apache Hadoop. Uh And so in that sense there's no there's no fighting to be had there. Um Yeah, >>so yeah. Who um struggling as a company. But you know, there's a strong head Duke D. N. A. At yahoo, certainly, I talked with the the founder of the startup. Horton works just announced today that they have a new board member. He's the guy who's the Ceo of Horton works and now on bluster, I'm sorry, cluster announced they have um rob from benchmark on the board. Uh He's the Ceo of Horton works and and one of my not criticisms but points about Horton was this guy's an engineer, never run a company before. He's no Mike Olson. Okay, so you know, Michaelson has a long experience. So this guy comes into running and he's obviously in in open source, is that good for Yahoo and open sources. He they say they're going to continue to invest in Hadoop? They clearly are are still using a lot of Hadoop certainly. Um how is that changing Apache, is that causing more um consolidation, is that causing more energy? What's your view on the whole Horton works? Think >>um you know, yahoo is uh has been and will continue to be a huge contributor. Hadoop, they uh I can't say for sure, but I feel pretty confident that they have more data under management under Hadoop than anyone else in the world and there's no question in my mind that they'll continue to invest huge amounts of both key way effort and engineering effort and uh all of the things that Hadoop needs to to advance. Um I'm sure that Horton works will continue to work very closely with with yahoo. Um And you know, we're excited to see um more and more contributors to to Hadoop um both from Horton works and from yahoo proper. >>Cool, Well, I just want to clarify for the folks out there who don't understand what this whole yahoo thing is, It was not a spin out, these were key Hadoop core guys who left the company to form a startup of which yahoo financed with benchmark capital. So, yahoo is clearly and told me and reaffirm that with me that they are clearly investing more in Hadoop internally as well. So there's more people inside, yahoo that work on Hadoop than they are in the entire Horton's work company. So that's very clear. So just to clear that up out there. Um erin. so you're you're a young gun, right? You're a young whiz like Todd madam on here, explain to the folks out there um a little bit older maybe guys in their thirties or C IOS a lot of people are doing, you know, they're kicking the tires on big data, they're hearing about real time analytics, they're hearing about benefits have never heard before. Uh Dave a lot and I on the cube talk about, you know, the transformations that are going on, you're seeing AMC getting into big data, everyone's transforming at the enterprise level and service provider. What explains the folks why Hadoop is so important. Why is that? Do if not the fastest or one of the fastest growing projects in Apache ever? Sure. Even faster than the web server project, which is one of the better, >>better bigger ones. >>Why is the dupes and explain to them what it is? Well, you know, >>it's been it's pretty well covered that there's been an explosion of data that more data is produced every every year over and over. We talk about exabytes which is a quantity of data that is so large that pretty much no one can really theoretically comprehend it. Um and more and more uh organizations want to store and process and learn from, you know, get insights from that data um in addition to just the explosion of data um you know that there is simply more data, organizations are less willing to discard data. One of the beauties of Hadoop is truly that it's so very inexpensive per terabyte to store data that you don't have to think up front about what you want to store, what you want to discard, store it all and figure out later what is the most useful bits we call that sort of schema on read. Um as opposed to, you know, figuring out the schema a priority. Um and that is a very powerful shift in dynamics of data storage in general. And I think that's very attractive to all sorts of organizations. >>Your, I'll see a Brown graduate and you have some interns from Brown to Brown um, Premier computer science program almost as good as when I went to school at Northeastern University. >>Um >>you know, the unsung heroes of computer science only kidding Brown's great program, but you know, cutting edge computer science areas known as obviously leading in a lot of the computer science areas do in general is known that you gotta be pretty savvy to be either masters level PhD to kind of play in this area? Not a lot of adoption, what I call the grassroots developers. What's your vision and how do you see the computer science, younger generation, even younger than you kind of growing up into this because those tools aren't yet developed. You still got to be, you're pretty strong from a computer science perspective and also explained to the folks who aren't necessarily at the browns of the world or getting into computer science, what about, what is that this revolution about and where is it going? What are some of the things you see happening around the corner that that might not be obvious. >>Sure there's a few questions there. Um part of it is how do people coming out of college get into this thing, It's not uh taught all that much in school, How do how do you sort of make the leap from uh the standard computer science curriculum into this sort of thing? And um you know, part of it is that really we're seeing more and more schools offering distributed computing classes or they have grids available um to to do this stuff there there is some research coming out of Brown actually and lots of other schools about Hadoop proper in the behavior of Hadoop under failure scenarios, that sort of stuff, which is very interesting. Google uh actually has classes that they teach, I believe in conjunction with the University of Washington um where they teach undergraduates and your master's level, graduate students about mass produced and distributed computing and they actually use Hadoop to do it because it is the architecture of Hadoop is modeled after um >>uh >>google's internal infrastructure. Um So you know that that's that's one way we're seeing more and more people who are just coming out of college who have distributed systems uh knowledge like this? Um Another question? the other part of the question you asked is how does um how does the ordinary developer get into this stuff? And the answer is we're working hard, you know, we and others in the hindu community are working hard on making it, making her do just much easier to consume. We released, you cover this fair bit, the ECM Express project that lets you install Hadoop with just minimal effort as close to 11 click as possible. Um and there's lots of um sort of layers built on top of Hadoop to make it more easily consumed by developers Hive uh sort of sequel like interface on top of mass produce. And Pig has its own DSL for programming against mass produce. Um so you don't have to write heart, you don't have to write straight map produced code, anything like that. Uh and it's getting easier for operators every day. >>Well, I mean, evolution was, I mean, you guys actually working on that cloud era. Um what about what about some of the abstractions? You're seeing those big the Rage is, you know, look back a year ago VM World coming up and uh little plugs looking angle dot tv will be broadcasting live and at VM World. Um you know, he has been on the Q XV m where um Spring Source was a big announcement that they made. Um, Haruka brought by Salesforce Cloud Software frameworks are big, what does that look like and how does it relate to do and the ecosystem around Hadoop where, you know, the rage is the software frameworks and networks kind of collide and you got the you got the kind of the intersection of, you know, software frameworks and networks obviously, you know, in the big players, we talk about E M C. And these guys, it's clear that they realize that software is going to be their key differentiator. So it's got to get to a framework stand, what is Hadoop and Apache talking about this kind of uh, evolution for for Hadoop. >>Sure. Well, you know, I think we're seeing very much the commoditization of hardware. Um, you just can't buy bigger and bigger computers anymore. They just don't exist. So you're going to need something that can take a lot of little computers and make it look like one big computer. And that's what Hadoop is especially good at. Um we talk about scaling out instead of scaling up, you can just buy more relatively inexpensive computers. Uh and that's great. And sort of the beauty of Hadoop, um, is that it will grow linearly as your data set as your um, your your scale, your traffic, whatever grows. Um and you don't have to have this exponential price increase of buying bigger and bigger computers, You can just buy more. Um and that that's sort of the beauty of it is a software framework that if you write against it. Um you don't have to think about the scaling anymore. It will do that for you. >>Okay. The question for you, it's gonna kind of a weird question but try to tackle it. You're at a party having a few cocktails, having a few beers with your buddies and your buddies who works at a big enterprise says man we've got all this legacy structured data systems, I need to implement some big data strategy, all this stuff. What do I do? >>Sure, sure. Um Not the question I thought you were going to ask me that you >>were a g rated program here. >>Okay. I thought you were gonna ask me, how do I explain what I do to you know people that we'll get to that next. Okay. Um Yeah, I mean I would say that the first thing to do is to implement a start, start small, implement a proof of concept, get a subset of the data that you would like to analyze, put it, put Hadoop on a few machines, four or five, something like that and start writing some hive queries, start writing some some pig scripts and I think you'll you know pretty quickly and easily see the value that you can get out of it and you can do so with the knowledge that when you do want to operate over your entire data set, you will absolutely be able to trivially scale to that size. >>Okay. So now the question that I want to ask is that you're at a party and I want to say, what do you >>do? You usually tell people in my hedge fund manager? No but seriously um I I tell people I work on distributed supercomputers. Software for distributed supercomputers and that people have some idea what distributed means and supercomputers and they figure that out. >>So final question for I know you gotta go get back to programming uh some code here. Um what's the future of Hadoop in the sense of from a developer standpoint? I was having a conversation with a developer who's a big data jockey and talking about Miss kelly gets anything and get his hands on G. O. Data, text data because the data data junkie and he says I just don't know what to build. Um What are some of the enabling apps that you may see out there and or you have just conceiving just brainstorming out there, what's possible with with data, can you envision the next five years, what are you gonna see evolve and what some of the coolest things you've seen that might that are happening right now. >>Sure. Sure. I mean I think you're going to see uh just the front ends to these things getting just easier and easier and easier to interact with and at some point you won't even know that you're interacting with a Hadoop cluster that will be the engine underneath the hood but you know, you'll you'll be uh from your perspective you'll be driving a Ferrari and by that I mean you know, standard B. I tool, standard sequel query language. Um we'll all be implemented on top of this stuff and you know from that perspective you could implement, you know, really anything you want. Um We're seeing a lot of great work coming out of just identifying trends amongst masses of data that you know, if you tried to analyze it with any other tool, you'd either have to distill it down so far that you would you would question your results or that you could only run the very simplest sort of queries over um and not really get those like powerful deep insights, those sort of correlative insights um that we're seeing people do. So I think you'll see, you'll continue to see uh great recommendations systems coming out of this stuff. You'll see um root cause analysis, you'll see great work coming out of the advertising industry um to you know to really say which ad was responsible for this purchase. Was it really the last ad they clicked on or was it the ad they saw five weeks ago they put the thought in mind that sort of correlative analysis is being empowered by big data systems like a dupe. >>Well I'm bullish on big data, I think people I think it's gonna be even bigger than I think you're gonna have some kids come out of college and say I could use big data to create a differentiation and build an airline based on one differentiation. These are cool new ways and, and uh, data we've never seen before. So Aaron, uh, thanks for coming >>on the issue >>um, your inside Palo Alto Studio and we're going to.
SUMMARY :
the market who have been talking about uh you know, a lot of first time entrepreneurs doing their startups and I've been Uh, the amount of experience take us through who you are and when you join Cloudera, I want your background. Um but you know, I I sort of followed my other colleagues you know, from your other office was a san mateo or san Bruno somewhere in there. So you guys bolted out. Um you know we're running out of space there certainly. on silicon angle, taking more of a social angle, social media has uh you know, Um but when you start talking about running H base, which needs to be up all the time serving live traffic So, you know, there's some argument like, oh, we can do it better. Um and you know, sometimes that will be true. TMC might take that approach or um you know, map are I was trying to trying to rewrite Maybe that's a political question you might want to answer. But you know what you can say is like this is Apache Hadoop. so you know, Michaelson has a long experience. Um And you know, we're excited to see um more and more contributors to Uh Dave a lot and I on the cube talk about, you know, per terabyte to store data that you don't have to think up front about what Your, I'll see a Brown graduate and you have some interns from Brown to Brown What are some of the things you see happening around the corner that And um you know, part of it is that really we're seeing more and more schools offering And the answer is we're working hard, you know, we and others in the hindu community are working do and the ecosystem around Hadoop where, you know, the rage is the software frameworks and Um and that that's sort of the beauty of it is a software framework I need to implement some big data strategy, all this stuff. Um Not the question I thought you were going to ask me that you the value that you can get out of it and you can do so with the knowledge that when you do and that people have some idea what distributed means and supercomputers and they figure that out. apps that you may see out there and or you have just conceiving just brainstorming out out of just identifying trends amongst masses of data that you know, if you tried Well I'm bullish on big data, I think people I think it's gonna be even bigger than I think you're gonna have some kids come out of college
SENTIMENT ANALYSIS :
ENTITIES
Entity | Category | Confidence |
---|---|---|
Mike Olson | PERSON | 0.99+ |
yahoo | ORGANIZATION | 0.99+ |
Mike Charles | PERSON | 0.99+ |
san Francisco | LOCATION | 0.99+ |
Palo Alto | LOCATION | 0.99+ |
Yahoo | ORGANIZATION | 0.99+ |
Aaron | PERSON | 0.99+ |
Aaron T. Myers | PERSON | 0.99+ |
University of Washington | ORGANIZATION | 0.99+ |
Hadoop | TITLE | 0.99+ |
ORGANIZATION | 0.99+ | |
Cloudera | ORGANIZATION | 0.99+ |
richard Kimble | PERSON | 0.99+ |
Michaelson | PERSON | 0.99+ |
two interns | QUANTITY | 0.99+ |
Oregon | LOCATION | 0.99+ |
ORGANIZATION | 0.99+ | |
Todd | PERSON | 0.99+ |
Claudia | PERSON | 0.99+ |
AMC | ORGANIZATION | 0.99+ |
five weeks ago | DATE | 0.99+ |
Northeastern University | ORGANIZATION | 0.99+ |
monday | DATE | 0.99+ |
first time | QUANTITY | 0.99+ |
both | QUANTITY | 0.99+ |
Dave | PERSON | 0.99+ |
TMC | ORGANIZATION | 0.99+ |
ralph kimball | PERSON | 0.99+ |
burlingame | LOCATION | 0.99+ |
Ferrari | ORGANIZATION | 0.98+ |
today | DATE | 0.98+ |
five | QUANTITY | 0.98+ |
Brown | ORGANIZATION | 0.98+ |
thirties | QUANTITY | 0.98+ |
one | QUANTITY | 0.98+ |
Horton | ORGANIZATION | 0.98+ |
Apache | ORGANIZATION | 0.98+ |
Hadoop | ORGANIZATION | 0.98+ |
erin | PERSON | 0.98+ |
ORGANIZATION | 0.97+ | |
One | QUANTITY | 0.97+ |
ORGANIZATION | 0.97+ | |
Brown | PERSON | 0.97+ |
a year ago | DATE | 0.97+ |
Salesforce | ORGANIZATION | 0.97+ |
john furry | PERSON | 0.96+ |
one big computer | QUANTITY | 0.95+ |
new york city | LOCATION | 0.95+ |
Mendel | PERSON | 0.94+ |