from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante despite all the chatter about cloud repatriation and the exorbitant cost of cloud computing customer spending momentum continues to accelerate in the post-isolation economy if the pandemic was good for the cloud it seems that the benefits of cloud migration remain lasting in the late stages of covid and beyond and we believe this stickiness is going to continue for quite some time we expect i asked revenue for the big four hyperscalers to surpass 115 billion dollars in 2021 moreover the strength of aws specifically as well as microsoft azure remain notable such large organizations showing elevated spending momentum as shown in the etr survey results is perhaps unprecedented in the technology sector hello everyone and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll share some some fresh july survey data that indicates accelerating momentum for the largest cloud computing firms importantly not only is the momentum broad-based but it's also notable in key strategic sectors namely ai and database there seems to be no stopping the cloud momentum there's certainly plenty of buzz about the cloud tax so-called cloud tax but other than wildly assumptive valuation models and some pockets of anecdotal evidence you don't really see the supposed backlash impacting cloud momentum our forecast calls for the big four hyperscalers aws azure alibaba and gcp to surpass 115 billion as we said in is revenue this year the latest etr survey results show that aws lambda has retaken the lead among all major cloud services tracked in the data set as measured in spending momentum this is the service with the most elevated scores azure overall azure functions vmware cloud on aws and aws overall also demonstrate very highly elevated performance all above that of gcp now impressively aws momentum in the all-important fortune 500 where it has always showed strength is also accelerating one concern in the most recent survey data is that the on-prem clouds and so-called hybrid platforms which we had previously reported as showing an upward spending trajectory seem to have cooled off a bit but the data is mixed and it's a little bit too early to draw firm conclusions nonetheless while hyperscalers are holding steady the spending data appears to be somewhat tepid for the on-prem players you know particularly for their cloud we'll study that further after etr drops its full results on july 23rd now turning our attention back to aws the aws cloud is showing strength across its entire portfolio and we're going to show you that shortly in particular we see notable strength relative to others in analytics ai and the all-important database category aurora and redshift are particularly strong but several other aws database services are showing elevated spending velocity which we'll quantify in a moment all that said snowflake continues to lead all database suppliers in spending momentum by a wide margin which again will quantify in this episode but before we dig into the survey let's take a look at our latest projections for the big four hyperscalers in is as you know we track quarterly revenues for the hyperscalers remember aws and alibaba ias data is pretty clean and reported in their respective earnings reports azure and gcp we have to extrapolate and strip out all a lot of the the apps and other certain revenue to make an apples-to-apples comparison with aws and alibaba and as you can see we have the 2021 market exceeding 115 billion dollars worldwide that's a torrid 35 growth rate on top of 41 in 2020 relative to 2019. aggressive yes but the data continues to point us in this direction until we see some clearer headwinds for the cloud players this is the call we're making aws is perhaps losing a sharepoint or so but it's also is so large that its annual incremental revenue is comparable to alibaba's and google's respective cloud business in total is business in total the big three u.s cloud companies all report at the end of july while alibaba is mid mid-august so we'll update these figures at that time okay let's move on and dig into the survey data we don't have the data yet on alibaba and we're limited as to what we can share until etr drops its research update on on the 23rd but here's a look at the net score timeline in the fortune 500 specifically so we filter the fortune 500 for cloud computing you got azure and the yellow aws and the black and gcp in blue so two points here stand out first is that aws and microsoft are converging and remember the customers who respond to the survey they probably include a fair amount of application software spending in their cloud answers so it favors microsoft in that respect and gcp second point is showing notable deceleration relative to the two leaders and the green call out is because this cut is from an aws point of view so in other words gcp declines are a positive for aws so that's how it should be interpreted now let's take a moment to better understand the idea of net score this is one of the fundamental metrics of the etr methodology here's the data for aws so we use that as a as a reference point net score is calculated by asking customers if they're adding a platform new that's the lime green bar that you see here in the current survey they're asking are you spending six percent or more in the second half relative to the first half of the year that's the forest green they're also asking is spending flat that's the gray or are you spending less that's the pink or are you replacing the platform i.e repatriating so not much spending going on in replacements now in fairness one percent of aws is half a billion dollars so i can see where some folks would get excited about that but in the grand scheme of things it's a sliver so again we don't see repatriation in the numbers okay back to net score subtract the reds from the greens and you get net score which in the case of aws is 61 now just for reference my personal subjective elevated net score level is 40 so anything above that is really impressive based on my experience and to have a company of this size be so elevated is meaningful same for microsoft by the way which is consistently well above the 50 mark in net score in the etr surveys so that's you can think about it that's even more impressive perhaps than aws because it's triple the revenue okay let's stay with aws and take a look at the portfolio and the strength across the board this chart shows net score for the past three surveys serverless is on fire by the way not just aws but azure and gcp functions as well but look at the aws portfolio every category is well above the 40 percent elevated red line the only exception is chime and even chime is showing an uptick and chime is meh if you've ever used chime every other category is well above 50 percent next net score very very strong for aws now as we've frequently reported ai is one of the four biggest focus areas from a spending standpoint along with cloud containers and rpa so it stands to reason that the company with the best ai and ml and the greatest momentum in that space has an advantage because ai is being embedded into apps data processes machines everywhere this chart compares the ai players on two dimensions net score on the vertical axis and market share or presence in the data set on the horizontal axis for companies with more than 15 citations in the survey aws has the highest net score and what's notable is the presence on the horizontal axis databricks is a company where high on also shows elevated scores above both google and microsoft who are showing strength in their own right and then you can see data iq data robot anaconda and salesforce with einstein all above that 40 percent mark and then below you can see the position of sap with leonardo ibm watson and oracle which is well below the 40 line all right let's look at at the all-important database category for a moment and we'll first take a look at the aws database portfolio this chart shows the database services in aws's arsenal and breaks down the net score components with the total net score superimposed on top of the bars point one is aurora is highly elevated with a net score above 70 percent that's due to heavy new adoptions redshift is also very strong as are virtually all aws database offerings with the exception of neptune which is the graph database rds dynamodb elastic document db time stream and quantum ledger database all show momentum above that all important 40 line so while a lot of people criticize the fragmentation of the aws data portfolio and their right tool for the right job approach the spending spending metrics tell a story and that that the strategy is working now let's take a look at the microsoft database portfolio there's a story here similar similar to that of aws azure sql and cosmos db microsoft's nosql distributed database are both very highly elevated as are azure database for mysql and mariadb azure cash for redis and azure for cassandra also microsoft is giving look at microsoft's giving customers a lot of options which is kind of interesting you know we've often said that oracle's strategy because we think about oracle they're building the oracle database cloud we've said oracle strategy should be to not just be the cloud for oracle databases but be the cloud for all databases i mean oracle's got a lot of specialty capability there but it looks like microsoft is beating oracle to that punch not that oracle is necessarily going there but we think it should to expand the appeal of its cloud okay last data chart that we'll show and then and then this one looks at database disruption the chart shows how the cloud database companies are doing in ibm oracle teradata in cloudera accounts the bars show the net score granularity as we described earlier and the etr callouts are interesting so first remember this is an aws this is in an aws context so with 47 responses etr rightly indicates that aws is very well positioned in these accounts with the 68 net score but look at snowflake it has an 81 percent net score which is just incredible and you can see google database is also very strong and the high 50 percent range while microsoft even though it's above the 40 percent mark is noticeably lower than the others as is mongodb with presumably atlas which is surprisingly low frankly but back to snowflake so the etr callout stresses that snowflake doesn't have a strong as strong a presence in the legacy database vendor accounts yet now i'm not sure i would put cloudair in the legacy database category but okay whatever cloudera they're positioning cdp is a hybrid platform as are all the on-prem players with their respective products and platforms but it's going to be interesting to see because snowflake has flat out said it's not straddling the cloud and on-prem rather it's all in on cloud but there is a big opportunity to connect on-prem to the cloud and across clouds which snowflake is pursuing that that ladder the cross-cloud the multi-cloud and snowflake is betting on incremental use cases that involve data sharing and federated governance while traditional players they're protecting their turf at the same time trying to compete in cloud native and of course across cloud i think there's room for both but clearly as we've shown cloud has the spending velocity and a tailwind at its back and aws along with microsoft seem to be getting stronger especially in the all-important categories related to machine intelligence ai and database now to be an essential infrastructure technology player in the data era it would seem obvious that you have to have database and or data management intellectual property in your portfolio or you're going to be less valuable to customers and investors okay we're going to leave it there for today remember these episodes they're all available as podcasts wherever you listen all you do is search breaking analysis podcast and please subscribe to the series check out etr's website at etr dot plus plus etr plus we also publish a full report every week on wikibon.com and siliconangle.com you can get in touch with me david.velante at siliconangle.com you can dm me at d vallante or you can hit hit me up on our linkedin post this is dave vellante for the cube insights powered by etr have a great week stay safe be well and we'll see you next time you

>> From the CUBE studios in Palo Alto in Boston, bringing you data-driven insights from the CUBE in ETR. This is breaking analysis with Dave Vellante. >> Earlier these week, the U S department of justice, along with attorneys general from 11 States filed a long expected antitrust lawsuit, accusing Google of being a monopoly gatekeeper for the internet. The suit draws on section two of the Sherman antitrust act, which makes it illegal to monopolize trade or commerce. Of course, Google is going to fight the lawsuit, but in our view, the company has to make bigger moves to diversify its business and the answer we think lies in the cloud and at the edge. Hello everyone. This is Dave Vellante and welcome to this week's Wiki Bond Cube insights powered by ETR. In this Breaking Analysis, we want to do two things. First we're going to review a little bit of history, according to Dave Vollante of the monopolistic power in the computer industry. And then next, we're going to look into the latest ETR data. And we're going to make the case that Google's response to the DOJ suit should be to double or triple its focus on cloud and edge computing, which we think is a multi-trillion dollar opportunity. So let's start by looking at the history of monopolies in technology. We start with IBM. In 1969 the U S government filed an antitrust lawsuit against Big Blue. At the height of its power. IBM generated about 50% of the revenue and two thirds of the profits for the entire computer industry, think about that. IBM has monopoly on a relative basis, far exceeded that of the virtual Wintel monopoly that defined the 1990s. IBM had 90% of the mainframe market and controlled the protocols to a highly vertically integrated mainframe stack, comprising semiconductors, operating systems, tools, and compatible peripherals like terminal storage and printers. Now the government's lawsuit dragged on for 13 years before it was withdrawn in 1982, IBM at one point had 200 lawyers on the case and it really took a toll on IBM and to placate the government during this time and someone after IBM made concessions such as allowing mainframe plug compatible competitors to access its code, limiting the bundling of application software in fear of more government pressure. Now the biggest mistake IBM made when it came out of antitrust was holding on to its mainframe past. And we saw this in the way it tried to recover from the mistake of handing its monopoly over to Microsoft and Intel. The virtual monopoly. What it did was you may not remember this, but it had OS/2 and Windows and it said to Microsoft, we'll keep OS/2 you take Windows. And the mistake IBM was making with sticking to the PC could be vertically integrated, like the main frame. Now let's fast forward to Microsoft. Microsoft monopoly power was earned in the 1980s and carried into the 1990s. And in 1998 the DOJ filed the lawsuit against Microsoft alleging that the company was illegally thwarting competition, which I argued at the time was the case. Now, ironically, this is the same year that Google was started in a garage. And I'll come back to that in a minute. Now, in the early days of the PC, Microsoft they were not a dominant player in desktop software, you had Lotus 1-2-3, WordPerfect. You had this company called Harvard Presentation Graphics. These were discreet products that competed very effectively in the market. Now in 1987, Microsoft paid $14 million for PowerPoint. And then in 1990 launched Office, which bundled Spreadsheets, Word Processing, and presentations into a single suite. And it was priced far more attractively than the some of the alternative point products. Now in 1995, Microsoft launched Internet Explorer, and began bundling its browser into windows for free. Windows had a 90% market share. Netscape was the browser leader and a high flying tech company at the time. And the company's management who pooed Microsoft bundling of IE saying, they really weren't concerned because they were moving up the stack into business software, now they later changed that position after realizing the damage that Microsoft bundling would do to its business, but it was too late. So in similar moves of ineptness, Lotus refuse to support Windows at its launch. And instead it wrote software to support the (indistinct). A mini computer that you probably have never even heard of. Novell was a leader in networking software at the time. Anyone remember NetWare. So they responded to Microsoft's move to bundle network services into its operating systems by going on a disastrous buying spree they acquired WordPerfect, Quattro Pro, which was a Spreadsheet and a Unix OS to try to compete with Microsoft, but Microsoft turned the volume and kill them. Now the difference between Microsoft and IBM is that Microsoft didn't build PC hardware rather it partnered with Intel to create a virtual monopoly and the similarities between IBM and Microsoft, however, were that it fought the DOJ hard, Okay, of course. But it made similar mistakes to IBM by hugging on to its PC software legacy. Until the company finally pivoted to the cloud under the leadership of Satya Nadella, that brings us to Google. Google has a 90% share of the internet search market. There's that magic number again. Now IBM couldn't argue that consumers weren't hurt by its tactics. Cause they were IBM was gouging mainframe customers because it could on pricing. Microsoft on the other hand could argue that consumers were actually benefiting from lower prices. Google attorneys are doing what often happens in these cases. First they're arguing that the government's case is deeply flawed. Second, they're saying the government's actions will cause higher prices because they'll have to raise prices on mobile software and hardware, Hmm. Sounds like a little bit of a threat. And of course, it's making the case that many of its services are free. Now what's different from Microsoft is Microsoft was bundling IE, that was a product which was largely considered to be crap, when it first came out, it was inferior. But because of the convenience, most users didn't bother switching. Google on the other hand has a far superior search engine and earned its rightful place at the top by having a far better product than Yahoo or Excite or Infoseek or even Alta Vista, they all wanted to build portals versus having a clean user experience with some non-intrusive of ads on the side. Hmm boy, is that part changed, regardless? What's similar in this case with, as in the case with Microsoft is the DOJ is arguing that Google and Apple are teaming up with each other to dominate the market and create a monopoly. Estimates are that Google pays Apple between eight and $11 billion annually to have its search engine embedded like a tick into Safari and Siri. That's about one third of Google's profits go into Apple. And it's obviously worth it because according to the government's lawsuit, Apple originated search accounts for 50% of Google search volume, that's incredible. Now, does the government have a case here? I don't know. I'm not qualified to give a firm opinion on this and I haven't done enough research yet, but I will say this, even in the case of IBM where the DOJ eventually dropped the lawsuit, if the U S government wants to get you, they usually take more than a pound of flesh, but the DOJ did not suggest any remedies. And the Sherman act is open to wide interpretation so we'll see. What I am suggesting is that Google should not hang too tightly on to it's search and advertising past. Yes, Google gives us amazing free services, but it has every incentive to appropriate our data. And there are innovators out there right now, trying to develop answers to that problem, where the use of blockchain and other technologies can give power back to us users. So if I'm arguing that Google shouldn't like the other great tech monopolies, hang its hat too tightly on the past, what should Google do? Well, the answer is obvious, isn't it? It's cloud and edge computing. Now let me first say that Google understandably promotes G Suite quite heavily as part of its cloud computing story, I get that. But it's time to move on and aggressively push into the areas that matters in cloud core infrastructure, database, machine intelligence containers and of course the edge. Not to say that Google isn't doing this, but there are areas of greatest growth potential that they should focus on. And the ETR data shows it. But let me start with one of our favorite graphics, which shows the breakdown of survey respondents used to derive net score. Net score remembers ETR's quarterly measurement of spending velocity. And here we show the breakdown for Google cloud. The lime green is new adoptions. The forest green is the percentage of customers increasing spending more than 5%. The gray is flat and the pinkish is decreased by 6% or more. And the bright red is we're replacing or swapping out the platform. You subtract the reds from the greens and you get a net score at 43%, which is not off the charts, but it's pretty good. And compares quite favorably to most companies, but not so favorite with AWS, which is at 51% and Microsoft which is at 49%, both AWS and Microsoft red scores are in the single digits. Whereas Google's is at 10%, look all three are down since January, thanks to COVID, but AWS and Microsoft are much larger than Google. And we'd like to see stronger across the board scores from Google. But there's good news in the numbers for Google. Take a look at this chart. It's a breakdown of Google's net scores over three survey snapshots. Now we skip January in this view and we do that to provide a year of a year context for October. But look at the all important database category. We've been watching this very closely, particularly with the snowflake momentum because big query generally is considered the other true cloud native database. And we have a lot of respect for what Google is doing in this area. Look at the areas of strength highlighted in the green. You've got machine intelligence where Google is a leader AI you've got containers. Kubernetes was an open source gift to the industry, and linchpin of Google's cloud and multi-cloud strategy. Google cloud is strong overall. We were surprised to see some deceleration in Google cloud functions at 51% net scores to be on honest with you, because if you look at AWS Lambda and Microsoft Azure functions, they're showing net scores in the mid to high 60s. But we're still elevated for Google. Now. I'm not that worried about steep declines, and Apogee and Looker because after an acquisitions things kind of get spread out around the ETR taxonomy so don't be too concerned about that. But as I said earlier, G Suite may just not that compelling relative to the opportunity in other areas. Now I won't show the data, but Google cloud is showing good momentum across almost all interest industries and sectors with the exception of consulting and small business, which is understandable, but notable deceleration in healthcare, which is a bit of a concern. Now I want to share some customer anecdotes about Google. These comments come from an ETR Venn round table. The first comment comes from an architect who says that "it's an advantage that Google is "not entrenched in the enterprise." Hmm. I'm not sure I agree with that, but anyway, I do take stock in what this person is saying about Microsoft trying to lure people away from AWS. And this person is right that Google essentially is exposed its internal cloud to the world and has ways to go, which is why I don't agree with the first statement. I think Google still has to figure out the enterprise. Now the second comment here underscores a point that we made earlier about big query customers really like the out of the box machine learning capabilities, it's quite compelling. Okay. Let's look at some of the data that we shared previously, we'll update this chart once the company's all report earnings, but here's our most recent take on the big three cloud vendors market performance. The key point here is that our data and the ETR data reflects Google's commentary in its earning statements. And the GCP is growing much faster than its overall cloud business, which includes things that are not apples to apples with AWS the same thing is true with Azure. Remember AWS is the only company that provides clear data on its cloud business. Whereas the others will make comments, but not share the data explicitly. So these are estimates based on those comments. And we also use, as I say, the ETR survey data and our own intelligence. Now, as one of the practitioners said, Google has a long ways to go as buddy an eighth of the size of AWS and about a fifth of the size of Azure. And although it's growing faster at this size, we feel that its growth should be even higher, but COVID is clear a factor here so we have to take that into consideration. Now I want to close by coming back to antitrust. Google spends a lot on R&D, these are quick estimates but let me give you some context. Google shells out about $26 billion annually on research and development. That's about 16% of revenue. Apple spends less about 16 billion, which is about 6% of revenue, Amazon 23 billion about 8% of the top line, Microsoft 19 billion or 13% of revenue and Facebook 14 billion or 20% of revenue, wow. So Google for sure spends on innovation. And I'm not even including CapEx in any of these numbers and the hype guys as you know, spend tons on CapEx building data centers. So I'm not saying Google cheaping out, they're not. And I got plenty of cash in there balance sheet. They got to run 120 billion. So I can't criticize they're roughly $9 billion in stock buybacks the way I often point fingers at what I consider IBM's overly wall street friendly use of cash, but I will say this and it was Jeff Hammerbacher, who I spoke with on the Cube in the early part of last decade at a dupe world, who said "the best minds of my generation are spending there time, "trying to figure out how to get people to click on ads." And frankly, that's where much of Google's R&D budget goes. And again, I'm not saying Google doesn't spend on cloud computing. It does, but I'm going to make a prediction. The post cookie apocalypse is coming soon, it may be here. iOS 14 makes you opt in to find out everything about you. This is why it's such a threat to Google. The days when Google was able to be the keeper of all of our data and to house it and to do whatever it likes with that data that ended with GDPR. And that was just the beginning of the end. This decade is going to see massive changes in public policy that will directly affect Google and other consumer facing technology companies. So my premise is that Google needs to step up its game and enterprise cloud and the edge much more than it's doing today. And I like what Thomas Kurian is doing, but Google's undervalued relative to some of the other big tech names. And I think it should tell wall street that our future is in enterprise cloud and edge computing. And we're going to take a hit to our profitability and go big in those areas. And I would suggest a few things, first ramp up R&D spending and acquisitions even more. Go on a mission to create cloud native fabric across all on-prem and the edge multicloud. Yes, I know this is your strategy, but step it up even more forget satisfying investors. You're getting dinged in the market anyway. So now's the time the moon wall street and attack the opportunity unless you don't see it, but it's staring you right in the face. Second, get way more cozy with the enterprise players that are scared to death of the cloud generally. And they're afraid of AWS in particular, spend the cash and go way, way deeper with the big tech players who have built the past IBM, Dell, HPE, Cisco, Oracle, SAP, and all the others. Those companies that have the go to market shops to help you win the day in enterprise cloud. Now, I know you partner with these companies already, but partner deeper identify game-changing innovations that you can co-create with these companies and fund it with your cash hoard. I'm essentially saying, do what you do with Apple. And instead of sucking up all our data and getting us to click on ads, solve really deep problems in the enterprise and the edge. It's all about actually building an on-prem to cloud across cloud, to the edge fabric and really making that a unified experience. And there's a data angle too, which I'll talk about now, the data collection methods that you've used on consumers, it's incredibly powerful if applied responsibly and correctly for IOT and edge computing. And I don't mean to trivialize the complexity at the edge. There really isn't one edge it's Telcos and factories and banks and cars. And I know you're in all these places Google because of Android, but there's a new wave of data coming from machines and cars. And it's going to dwarf people's clicks and believe me, Tesla wants to own its own data and Google needs to put forth a strategy that's a win-win. And so far you haven't done that because your head is an advertising. Get your heads out of your ads and cut partners in on the deal. Next, double down on your open source commitment. Kubernetes showed the power that you have in the industry. Ecosystems are going to be the linchpin of innovation over the next decade and transcend products and platforms use your money, your technology, and your position in the marketplace to create the next generation of technology leveraging the power of the ecosystem. Now I know Google is going to say, we agree, this is exactly what we're doing, but I'm skeptical. Now I think you see either the cloud is a tiny little piece of your business. You have to do with Satya Nadella did and completely pivot to the new opportunity, make cloud and the edge your mission bite the bullet with wall street and go dominate a multi-trillion dollar industry. Okay, well there you have it. Remember, all these episodes are available as podcasts, so please subscribe wherever you listen. I publish weekly on Wikibond.com and Siliconangle.com and I post on LinkedIn each week as well. So please comment or DM me @DVollante, or you can email me @David.Vollante @Siliconangle.com. And don't forget to check out etr.plus that's where all the survey action is. This is Dave Vollante for the Cube Insights powered by ETR. Thanks for watching everybody be well. And we'll see you next. (upbeat instrumental)

(upbeat electronic music) >> Narrator: From theCUBE studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE conversation! >> Hi, I'm Stu Miniman, your host for Cloud Native Insight. When we launched this series, one of the things we wanted to talk about was that we're not just using cloud as a destination, but really enabling new ways of thinking, being able to use the innovations underneath the cloud, and that if you use services in the cloud, that you're not necessarily locked into a solution or can't move forward. And that's why I'm really excited to help welcome to the program, I have the co-founders of Vendia. First we have Dr. Tim Wagner, he is the co-founder and CEO of the company, as well as generally known in the industry as the father of Serverless from the AWS Lambda, and his co-founder, Shruthi Rao, she is the chief business officer at Vendia, also came from AWS where she worked on blockchain solutions. Tim, Shruthi, thanks so much for joining us. >> Thanks for having us in here, Stu. Great to join the show. >> All right, so Shruthi, actually if we could start with you because before we get into Vendia, coming out of stealth, you know, really interesting technology space, you and Tim both learned a lot from working with customers in your previous jobs, why don't we start from you. Block chain of course had a lot of learnings, a lot of things that people don't understand about what it is and what it isn't, so give us a little bit about what you've learned and how that lead towards what you and Tim and the team are doing with Vendia. >> Yeah, absolutely, Stu! One, the most important thing that we've all heard of was this great gravitational pull towards blockchain in 2018 and 2019. Well, I was one of the founders and early adopters of blockchain from Bitcoin and Ethereum space, all the way back from 2011 and onwards. And at AWS I started the Amazon Managed Blockchain and launched Quantum Ledger Database, two services in the block chain category. What I learned there was, no surprise, there was a gold rush to blockchain from many customers. We, I personally talked to over 1,092 customers when I ran Amazon Managed Blockchain for the last two years. And I found that customers were looking at solving this dispersed data problem. Most of my customers had invested in IoT and edge devices, and these devices were gathering massive amounts of data, and on the flip side they also had invested quite a bit of effort in AI and ML and analytics to crunch this data, give them intelligence. But guess what, this data existed in multiple parties, in multiple clouds, in multiple technology stacks, and they needed a mechanism to get this data from wherever they were into one place so they could the AI, ML, analytics investment, and they wanted all of this to be done in real time, and to gravitated towards blockchain. But blockchain had quite a bit of limitations, it was not scalable, it didn't work with the existing stack that you had. It forced enterprises to adopt this new technology and entirely new type of infrastructure. It didn't work cross-cloud unless you hired expensive consultants or did it yourself, and required these specialized developers. For all of these reasons, we've seen many POCs, majority of POCs just dying on the vine and not ever reaching the production potential. So, that is when I realized that what the problem to be solved was not a trust problem, the problem was dispersed data in multiple clouds and multiple stacks problem. Sometimes multiple parties, even, problem. And that's when Tim and I started talking about, about how can we bring all of the nascent qualities of Lambda and Serverless and use all of the features of blockchain and build something together? And he has an interesting story on his own, right. >> Yeah. Yeah, Shruthi, if I could, I'd like to get a little bit of that. So, first of all for our audience, if you're watching this on the minute, probably want to hit pause, you know, go search Tim, go watch a video, read his Medium post, about the past, present, and future of Serverless. But Tim, I'm excited. You and I have talked in the past, but finally getting you on theCUBE program. >> Yeah! >> You know, I've looked through my career, and my background is infrastructure, and the role of infrastructure we know is always just to support the applications and the data that run business, that's what is important! Even when you talk about cloud, it is the applications, you know, the code, and the data that are important. So, it's not that, you know, okay I've got near infinite compute capacity, it's the new things that I can do with it. That's a comment I heard in one of your sessions. You talked about one of the most fascinating things about Serverless was just the new creativity that it inspired people to do, and I loved it wasn't just unlocking developers to say, okay I have new ways to write things, but even people that weren't traditional coders, like lots of people in marketing that were like, "I can start with this and build something new." So, I guess the question I have for you is, you know we had this idea of Platform as a Service, or even when things like containers launched, it was, we were trying to get close to that atomic unit of the application, and often it was talked about, well, do I want it for portability? Is it for ease of use? So, you've been wrangling and looking at this (Tim laughing) from a lot of different ways. So, is that as a starting point, you know, what did you see the last few years with Lambda, and you know, help connect this up to where Shruthi just left off her bit of the story. >> Absolutely. You know, the great story, the great success of the cloud is this elimination of undifferentiated heavy lifting, you know, from getting rid of having to build out a data center, to all the complexity of managing hardware. And that first wave of cloud adoption was just phenomenally successful at that. But as you say, the real thing businesses wrestle with are applications, right? It's ultimately about the business solution, not the hardware and software on which it runs. So, the very first time I sat down with Andy Jassy to talk about what eventually become Lambda, you know, one of the things I said was, look, if we want to get 10x the number of people to come and, you know, and be in the cloud and be successful it has to be 10 times simpler than it is today. You know, if step one is hire an amazing team of distributed engineers to turn a server into a full tolerance, scalable, reliable business solution, now that's going to be fundamentally limiting. We have to find a way to put that in a box, give that capability, you know, to people, without having them go hire that and build that out in the first place. And so that kind of started this journey for, for compute, we're trying to solve the problem of making compute as easy to use as possible. You know, take some code, as you said, even if you're not a diehard programmer or backend engineer, maybe you're just a full-stack engineer who loves working on the front-end, but the backend isn't your focus, turn that into something that is as scalable, as robust, as secure as somebody who has spent their entire career working on that. And that was the promise of Serverless, you know, outside of the specifics of any one cloud. Now, the challenge of course when you talk to customers, you know, is that you always heard the same two considerations. One is, I love the idea of Lamdba, but it's AWS, maybe I have multiple departments or business partners, or need to kind of work on multiple clouds. The other challenge is fantastic for compute, what about data? You know, you've kind of left me with, you're giving me sort of half the solution, you've made my compute super easy to use, can you make my data equally easy to use? And so you know, obviously the part of the genesis of Vendia is going and tackling those pieces of this, giving all that promise and ease of use of Serverless, now with a model for replicated state and data, and one that can cross accounts, machines, departments, clouds, companies, as easily as it scales on a single cloud today. >> Okay, so you covered quite a bit of ground there Tim, if you could just unpack that a little bit, because you're talking about state, cutting across environments. What is it that Vendia is bringing, how does that tie into solutions like, you know, Lamdba as you mentioned, but other clouds or even potentially on premises solutions? So, what is, you know, the IP, the code, the solution that Vendia's offering? >> Happy to! So, let's start with the customer problem here. The thing that every enterprise, every company, frankly, wrestles with is in the modern world they're producing more data than ever, IMT, digital journeys, you know, mobile, edge devices. More data coming in than ever before, at the same time, more data getting consumed than ever before with deep analytics, supply chain optimization, AI, ML. So, even more consumers of ever more data. The challenge, of course, is that data isn't always inside a company's four walls. In fact, we've heard 80% or more of that data actually lives outside of a company's control. So, step one to doing something like AI, ML, isn't even just picking a product or selecting a technology, it's getting all of your data back together again, so that's the problem that we set out to solve with Vendia, and we realized that, you know, and kind of part of the genesis for the name here, you know, Vendia comes from Venn Diagram. So, part of that need to bring code and data together across companies, across tech stacks, means the ability to solve some of these long-standing challenges. And we looked at the two sort of big movements out there. Two of them, you know, we've obviously both been involved in, one of them was Serverless, which amazing ability to scale, but single account, single cloud, single company. The other one is blockchain and distributed ledgers, manages to run more across parties, across clouds, across tech stacks, but doesn't have a great mechanism for scalability, it's really a single box deployment model, and obviously there are a lot of limitations with that. So, our technology, and kind of our insight and breakthrough here was bringing those two things together by solving the problems in each of them with the best parts of the other. So, reimagine the blockchain as a cloud data implementation built entirely out of Serverless components that have all of the scale, the cost efficiencies, the high utilization, like all of the ease of deployment that something like Lambda has today, and at the same time, you know, bring state to Serverless. Give things like Lambda and the equivalent of other clouds a simple, easy, built-in model so that applications can have multicloud, multi-account state at all times, rather than turning that into a complicated DIY project. So, that was our insight here, you know and frankly where a lot of the interesting technology for us is in turning those centralized services, a centralized version of Serverless Compute or Serverless Database into a multi-account, multicloud experience. And so that's where we spent a lot of time and energy trying to build something that gives customers a great experience. >> Yeah, so I've got plenty of background in customers that, you know, have the "information silos", if you will, so we know, when the unstructured data, you know so much of it is not searchable, I can't leverage it. Shruthi, but maybe it might make sense, you know, what is, would you say some of the top things some of your early customers are saying? You know, I have this pain point, that's pointing me in your direction, what was leading them to you? And how does the solution help them solve that problem? >> Yeah, absolutely! One of our design partners, our lead design partners is this automotive company, they're a premier automotive company, they want, their end goal is to track car parts for warranty recall issues. So, they want to track every single part that goes into a particular car, so they're about 30 to 35,000 parts in each of these cars, and then all the way from manufacturing floor to when the car is sold, and when that particular part is replaced eventually, towards the end of the lifecycle of that part. So for this, they have put together a small test group of their partners, a couple of the parts manufacturers, they're second care partners, National Highway Safety Administration is part of this group, also a couple of dealers and service centers. Now, if you just look at this group of partners, you will see some of these parties have high technology, technology backgrounds, just like the auto manufacturers themselves or the part manufacturers. Low modality or low IT-competency partners such as the service centers, for them desktop PCs are literally the IT competency, and so does the service centers. Now, most of, majority of these are on multiple clouds. This particular auto customer is on AWS and manufactures on Azure, another one is on GCP. Now, they all have to share these large files between each other, making sure that there are some transparency and business rules applicable. For example, two partners who make the same parts or similar parts cannot see each other's data. Most of the participants cannot see the PII data that are not applicable, only the service center can see that. National Highway Safety Administration has read access, not write access. A lot of that needed to be done, and their alternatives before they started using Vendia was either use point-to-point APIs, which was very expensive, very cumbersome, it works for a finite small set of parties, it does not scale, as in when you add more participants into this particular network. And the second option for them was blockchain, which they did use, and used Hyperledger Fabric, they used Ethereum Private to see how this works, but the scalability, with Ethereum Private, it's about 14 to 15 transactions per second, with Hyperledger Fabric it taps out at 100, or 150 on a good day, transaction through, but it's not just useful. All of these are always-on systems, they're not Serverless, so just provisioning capacity, our customers said it took them two to three weeks per participant. So, it's just not a scalable solution. With Vendia, what we delivered to them was this virtual data lake, where the sources of this data are on multiple clouds, are on multiple accounts owned by multiple parties, but all of that data is shared on a virtual data lake with all of the permissions, with all of the logging, with all of the security, PII, and compliance. Now, this particular auto manufacturer and the National Highway Safety Administration can run their ML algorithms to gain intelligence off of it, and start to understand patterns, so when certain parts go bad, or what's the propensity of a certain manufacturing unit producing faulty parts, and so on, and so forth. This really shows you this concept of unstructured data being shared between parties that are not, you know, connected with each other, when there are data silos. But I'd love to follow this up with another example of, you know, the democratization, democratization is very important to Vendia. When Tim launched Lambda and founded the AWS Serverless movement as a whole, and at AWS, one thing, very important thing happened, it lowered the barrier to entry for a new wave of businesses that could just experiment, try out new things, if it failed, they scrap it, if it worked, they could scale it out. And that was possible because of the entry point, because of the paper used, and the architecture itself, and we are, our vision and mission for Vendia is that Vendia fuels the next generation of multi-party connected distributed applications. My second design partner is actually a non-profit that, in the animal welfare industry. Their mission is to maintain a no-kill for dogs and cats in the United States. And the number one reason for over populations of dogs and cats in the shelters is dogs lost, dogs and cats lost during natural disasters, like the hurricane season. And when that happens, and when, let's say your dogs get lost, and you want to find a dog, the ID or the chip-reading is not reliable, they want to search this through pictures. But we also know that if you look at a picture of a dog, four people can come up with four different breed names, and this particular non-profit has 2,500 plus partners across the U.S., and they're all low to no IT modalities, some of them have higher IT competency, and a huge turnover because of volunteer employees. So, what we did for them was came up with a mechanism where they could connect with all 2,500 of these participants very easily in a very cost-effective way and get all of the pictures of all of the dogs in all these repositories into one data lake so they can run some kind of a dog facial recognition algorithm on it and identify where my lost dog is in minutes as opposed to days it used to take before. So, you see a very large customer with very sophisticated IT competency use this, also a non-profit being able to use this. And they were both able to get to this outcome in days, not months or years, as, blockchain, but just under a few days, so we're very excited about that. >> Thank you so much for the examples. All right, Tim, before we get to the end, I wonder if you could take us under the hood a little bit here. My understanding, the solution that you talk about, it's universal apps, or what you call "unis" -- >> Tim: Unis? (laughs) >> I believe, so if I saw that right, give me a little bit of compare and contrast, if you will. Obviously there's been a lot of interest in what Kubernetes has been doing. We've been watching closely, you know there's connections between what Kubernetes is doing and Serverless with the Knative project. When I saw the first video talking about Vendia, you said, "We're serverless, and we're containerless underneath." So, help us understand, because at, you know, a super high level, some of the multicloud and making things very flexible sound very similar. So you know, how is Vendia different, and why do you feel your architecture helps solve this really challenging problem? >> Sure, sure, awesome! You know, look, one of the tenets that we had here was that things have to be as easy as possible for customers, and if you think about the way somebody walks up today to an existing database system, right? They say, "Look, I've got a schema, I know the shape of my data." And a few minutes later I can get a production database, now it's single user, single cloud, single consumer there, but it's a very fast, simple process that doesn't require having code, hiring a team, et cetera, and we wanted Vendia to work the same way. Somebody can walk up with a JSON schema, hand it to us, five minutes later they have a database, only now it's a multiparty database that's decentralized, so runs across multiple platforms, multiple clouds, you know, multiple technology stacks instead of being single user. So, that's kind of goal one, is like make that as easy to use as possible. The other key tenet though is we don't want to be the least common denominator of the cloud. One of the challenges with saying everyone's going to deploy their own servers, they're going to run all their own software, they're going to build, you know, they're all going to co-deploy a Kubernetes cluster, one of the challenges with that is that, as Shruthi was saying, first, anyone for whom that's a challenge, if you don't have a whole IT department wrapped around you that's a difficult proposition to get started on no matter how amazing that technology might be. The other challenge with it though is that it locks you out, sort of the universe of a lock-in process, right, is the lock-out process. It locks you out of some of the best and brightest things the public cloud providers have come up with, and we wanted to empower customers, you know, to pick the best degree. Maybe they want to go use IBM Watson, maybe they want to use a database on Google, and at the same time they want to ingest IoT on AWS, and they wanted all to work together, and want all of that to be seamless, not something where they have to recreate an experience over, and over, and over again on three different clouds. So, that was our goal here in producing this. What we designed as an architecture was decentralized data storage at the core of it. So, think about all the precepts you hear with blockchain, they're all there, they all just look different. So, we use a no SQL database to store data so that we can scale that easily. We still have a consensus algorithm, only now it's a high speed serverless and cloud function based mechanism. You know, instead of smart contracts, you write things in a cloud function like Lambda instead, so no more learning Solidity, now you can use any language you want. So, we changed how we think about that architecture, but many of those ideas about people, really excited about blockchain and its capabilities and the vision for the future are still alive and well, they've just been implemented in a way that's far more practical and effective for the enterprise. >> All right, so what environments can I use today for your solution, Shruthi talked about customers spanning across some of the cloud, so what's available kind of today, what's on the roadmap in the future? Will this include beyond, you know, maybe the top five or six hyper scalers? Can I do, does it just require Serverless underneath? So, will things that are in a customer's own data center eventually support that. >> Absolutely. So, what we're doing right now is having people sign up for our preview release, so in the next few weeks, we're going to start turning that on for early access to developers. That'll be, the early access program, will be multi-account, focused on AWS, and then end of summer, well be doing our GA release, which will be multicloud, so we'll actually be able to operate across multiple clouds, multiple cloud services, on different platforms. But even from day one, we'll have API support in there. So, if you got a service, could even be running on a mainframe, could be on-prem, if it's API based you can still interact with the data, and still get the benefits of the system. So, developers, please start signing up, you can go find more information on vendia.net, and we're really looking forward to getting some of that early feedback and hear more from the people that we're the most excited to have start building these projects. >> Excellent, what a great call to action to get the developers and users in there. Shruthi, if you could just give us the last bit, you know, the thing that's been fascinating, Tim, when I look at the Serverless movement, you know, I've talked to some amazing companies that were two or three people (Tim laughing) and out of their basement, and they created a business, and they're like, "Oh my gosh, I got VC funding, and it's usually sub $10,000,000. So, I look at your team, I'd heard, Tim, you're the primary coder on the team. (Tim laughing) And when it comes to the seed funding it's, you know, compared to many startups, it's a small number. So, Shruthi, give us a little bit if you could the speeds and feeds of the company, your funding, and any places that you're hiring. Yeah, we are definitely hiring, lets me start from there! (Tim laughing) We're hiring for developers, and we are also hiring for solution architects, so please go to vendia.net, we have all the roles listed there, we would love to hear from you! And the second one, funding, yes. Tim is our main developer and solutions architect here, and look, the Serverless movement really helped quite a few companies, including us, to build this, bring this to market in record speeds, and we're very thankful that Tim and AWS started taking the stands, you know back in 2014, 2013, to bring this to market and democratize this. I think when we brought this new concept to our investors, they saw what this could be. It's not an easy concept to understand in the first wave, but when you understand the problem space, you see that the opportunity is pretty endless. And I'll say this for our investors, on behalf of our investors, that they saw a real founder market-fit between us. We're literally the two people who have launched and ran businesses for both Serverless and blockchain at scale, so that's what they thought was very attractive to them, and then look, it's Tim and I, and we're looking to hire 8 to 10 folks, and I think we have gotten to a space where we're making a meaningful difference to the world, and we would love for more people to join us, join this movement and democratize this big dispersed data problem and solve for this. And help us create more meanings to the data that our customers and companies worldwide are creating. We're very excited, and we're very thankful for all of our investors to be deeply committed to us and having conviction on us. >> Well, Shruthi and Tim, first of all, congratulations -- >> Thank you, thank you. >> Absolutely looking forward to, you know, watching the progress going forward. Thanks so much for joining us. >> Thank you, Stu, thank you. >> Thanks, Stu! >> All right, and definitely tune in to our regular conversations on Cloud Native Insights. I'm your host Stu Miniman, and looking forward to hearing more about your Cloud Native Insights! (upbeat electronic music)

>> Announcer: Live from the Computer History Museum in Mountain View, California. It's theCUBE covering DevNet Create, 2018, brought to you by Cisco. (techy music playing) >> Okay, welcome back, everyone. We're live here in Mountain View, California, in the heart of Silicon Valley for Cisco's DevNet Create. This is their new developer outreach kind of cloud, devops conference, different than DevNet their core, Cisco Networking Developer Conference is kind of an extension, kind of forging new ground. Of course theCUBE's covering, we love devops, we love cloud. I'm John Furrier with Lauren Cooney, my cohost today. Our next guest is Alex Ellis, project founder of OpenFaas, F-A-A-S, function as a service. That's serverless, that's Kubernetes, that's container madness. You name it, that's the cool, important trend, thanks for joining us. >> Yeah, thanks for having me, it's great to be here. >> So, talk about the founding of the project. So, you're the founder of the project-- >> Alex: Yeah. >> And you now work for VmWare, so let's just get this-- >> Yeah. >> On the record, so-- >> Alex: Yeah, I think this is-- >> Take a minute to explain. >> This is important just to set a bit of context now. I started this project from the lens of working with AWS Lambda as a Docker captain. I was writing these Alexa skills and I found that I had to hack in a web editor and click upload, or I had to write a zip file, put dependencies on my laptop, and upload that to the cloud every time I changed it. It just didn't feel right because I was so bought into containers. It's the same everywhere, there's no more, "It works on my machine." >> John: You're going backwards. >> Right? (laughing) So, I put a POC together for Docker Swarm and nobody had done it at that point, and it got really popular. I got to Docker Concourse Hacks Contest and presented to 4,000 people in the closing keynote, and I kind of thought it would just blossom overnight, it would explode, but it didn't happen, and actually, the months... We're going back 14 now, I grew a community and spent most of my time growing the community and extending the project. Now, that has been really fruitful. It's led to over 11,000 stars on GitHub, 91 individual contributors, and much, much more. It's been a really rich experience, but at the same time-- >> So, rather than going big rocket ship you kind of went, hunkered down and got a kernel of core people together. >> Alex: Yeah. >> Kind of set the DNA, what is the DNA of this project if you had to describe it? >> Yeah, so I think at the heart of it it's serverless functions made simple for Docker and Kubernetes. >> Great, and so how does Amazon play into this? You were using Amazon cloud? >> Yeah, I was using AWS and I was using Lambda, and that flow was not what I was used to in the enterprise. It wasn't what I was used to as a Docker captain. You know, I wanted a finite image that I could scan for vulnerabilities. >> John: Yeah. >> I could check off and promote through an environment. >> John: Yeah. >> Couldn't do it, so that was what OpenFaas aimed to do, was to make those serverless functions easy with Docker as a runtime. >> Well, congratulations, it's a lot of hard work. First, building a community's very difficult, and certainly one that's relevant. Cool and relevant, I would say, is serverless and functions. We'll certainly be seeing that now at the uptake. Still early on, but people are working on it. So, then now, let's forward to today. You work for VMWare, so-- >> Alex: Yeah. >> How did they get involved, are you shipping the project to VMWare, do they own it? Do you maintain the independence? What's the relationship between VMWare, yourself, and the project, if you can talk about that. >> Yeah, I think that's a great question. So, I got to the point where I had demands on my time around the clock. I couldn't rest, open source project, weekends, nights, the lot. >> John: You need the beer money, too, by the way. >> Right, yeah. >> You need some beer money. >> And I was working at ADP and just doing all of this in my own time, and then had a number of different options that came up and people saying, "Look, how are you going to sustain this, "how are you going to keep doing what you love?" You know, you should be working on it full time. One of the options that came up was from VMWare to work in the Open Source Technology Center. It's relatively new-- >> John: Mm-hmm. >> And the mission of the OSTC is to show VMWare as a good citizen in the community and to contribute back to meaningful projects, right, that relate to their products. >> Yeah, and they have good leadership, too, at VMWare. A lot of people don't know that. We did a couple CUBE interviews with them last year, and there is a group inside VMWare that just does that, not with the tentacles of VMWare and Dell Technologies in there. It's an independent group. >> Alex: Yeah. >> They probably go to some meetings and do some debrief, but for the most part it's kind of decoupled from VMWare, right. >> Yeah, right. So, the mission is not necessarily to make money and to produce products. It's to contribute to open source. Help with inbound so when we need to consume a project in a product, and outbound when we want to make the world a better place. >> So, I'm not going to put words in VMWare's mouth, but I will speculate covering VMWare since theCUBE started. We've been to every VMWorld and everyone knows we've got the good presence there, but if I'm VMWare I'm like, "Hey, you know what, we just "did a deal with Amazon, our enterprise "group is not so cloud savvy." I mean, the enterprise, there are operators, not true cloud native, but they're bridging that gap. The world of cloud native and enterprise is coming together. Does this project fit into that spot? Is that kind of where they saw it? Did I get that right or what was their interest other than doing-- >> Alex: Yeah. >> Helping the world out and solving world peace in the open source community. >> Yeah, so the mission of OSTC is slightly different. It's to contribute back to meaningful projects and to have this presence in the community. You know, I think OpenFaas is particularly attractive because it has such a broad community. There's people all around the world that are contributing to it, very active. For VMWare it makes a lot of sense because it runs natively on Kubernetes or Docker Swarm, and it's gained a lot of traction, people are using it. >> John: Mm-hmm. >> I had a call with BT Research before I came out and they said, "We've been using it for seven months. "We absolutely love it, it's transforming "how we're doing our microservices," and so I think that's part of it, as well as already have kind of a lead. Already have a lot of momentum with this project. >> So, are you looking to, you know, I know that the organization that you work for is really focused on driving this outbound, right? >> Alex: Yeah, yeah. >> Is VMWare using this internally as well? >> So, I think there's been a number of people who've shown an interest. You can think, "Right, there's a problem "we could solve with this," and I'm just getting my feet under the table, but really my mission is to make serverless functions simple to build this community-- >> Lauren: Mm-hmm. >> And to have something that people can turn to as an alternative. So, one of the things that I did in the talk yesterday was, "How do you explain OpenFaas to your boss," and one of the points there was to unlock your data. >> Lauren: Mm-hmm. >> And I think we talked about this briefly before, now with controversies recently about data and who owns it, what's happening with it, I think it's even more relevant that-- >> John: Yeah. >> You can have full control over the whole stack if you want-- >> John: Yeah. >> Or use a product like Microsoft AKS, their Kubernetes service-- >> Lauren: Mm-hmm. >> Or GKE and actually treat OpenFaas like a very thin layer of automation. >> Lauren: Really, okay. >> Or go full stack and have everything under your control. >> I mean, that's a great conversation to have, too, because obviously you're kind of referring to the Facebook situation. Zuckerberg's testifying it front of Senate yesterday, Congress today, and it's funny because watching him talk to senators in the US, they really don't know how stuff works, and so if you think about what Facebook does... I mean, granted they took some liberties. They're not the perfect citizen, they got slapped. They took it to the woodshed, if you will, but their mission is to use the data, and this is where cloud native's interesting and I think I want to get your reaction to this, you need to use the data, not treat it as a siloed, fenced in data warehouse. That model's old, right-- >> Alex: Yeah. >> It's now horizontal and scalable. Data's got to move and you've got to have data to make other things happen. That's the way these services are working. >> Yeah. >> So, it's really important to have addressability of the data and you know, GDPR takes an attempt at, you know, kind of hand waving that simple argument away. I'm not really a big fan of that, personally, but the role of data's super important. You've got to make it pervasive, so the challenge is how do you manage those controls. Is that an opportunity for functions? What's your reaction to that whole paradigm of data? >> Yeah, so we're talking about anonymous usage data, like Facebook situation or-- >> Just data in general... Oh, no, just data in general, if I'm an application and I have data-- >> Alex: Yeah. >> That I'm generating, same development of service-- >> Alex: Yeah. >> I need, you might want to leverage that data. So, I'm going to have to have a mechanism for you to share that data to make your service better-- >> Alex: Yeah. >> Because data makes data, you know-- >> Alex: Yeah. >> The alchemy side of it is interesting, but then there's all... You get trapped in regulation, licensing, it can be destructive. >> Yes, so as an engineer, and as an open source engineer, you find people that have no clue about what an MIT license is to a GPL or why you'd use one or the other. I think there's a lot we can do to educate the wider community and help them to learn the basics of these issues. When I was at university we had a course on ethics and legal issues and licensing, and I heard on the radio earlier on the Uber that they're starting to try and up the level of that again, and I think it really needs to start at a ground level. We need to educate people about these issues so that they're aware of how to handle the data. I mean, if you look at common tools like Docker and VS Code and Atom, popular editors, they collect anonymous usage statistics and you have to opt out. You know, should OpenFaas collect data as well, because it can be super helpful for us to know the right thing to do. >> Yeah. >> And when you come to open source you get no feedback until somebody wants support from you and it has to be done yesterday for free. >> Yeah, yeah, yeah. >> And so, yeah, getting data can be super powerful. >> Well, Alex, you bring up a great point. I think this is something that's worthy of an ongoing conversation. I think it will be, too, because GPL, Apache license, all these licenses were built when open source was a Tier 2 citizen, so the whole idea of these-- >> Alex: Yeah. >> Licenses was to create a robust sharing economy of code, and you know, with the certain nuances of those licenses. But just like stacks get updated and modernized with what we've seen the containers and now Kubernetes is serverless, the stack is changing and modernizing. The licenses have to, as well, so I think this is something that... I don't, I think it's kind of like we've got to get on it. (laughing) It's like I think we should just, this is a work area. It's not necessarily... It's game changing if you don't do it, right, because it could-- >> Yeah. >> It could flip it either way. So, to me that's my opinion. >> Well, I think you're under MIT, correct, is that-- >> So, it's under MIT right now. >> Lauren: Okay. >> One of the things that I didn't realize when I started the project is if you want to get into a big foundation like the Cloud Native Computing Foundation you need an Apache 2.0 license, and the main difference is that it offers some protections around patent claims, but it's basically-- >> Lauren: Okay. >> Compatible, so it is a minefield, and it's-- >> Lauren: So, that's just for the CNCF? >> Right, and the Apache Foundation, obviously as well. >> Lauren: Yes. >> And probably many others follow suit because I think it, we talk about the-- >> John: It's the dual source, it's the dual source. >> A refresh... >> John: Yeah, yeah. >> Right, it's a compatible license, it seems to help a lot of people. >> Lauren: Mm-hmm. >> That's a huge issue because you could be well down the road with committing code and then the lawyers will make you take it out. >> Right, so that's why organizations like the Open Source Program Office exist within VMWare, to help these issues and to monitor and do compliance. They may use software like Black Duck to check stuff-- >> Lauren: Yep, mm-hmm. >> Automatically because you don't want to be doing checks on your aircraft once it's in the air. >> Lauren: Mm-hmm. >> John: Yeah. >> You want to sort out everything out on the ground. >> You'll be grounding your fleet, that's for sure-- >> Right. >> When it comes to that, how do you handle that with licensing? How do you guys handle that when people contribute? >> Yeah. >> Are they aware of the license or they don't understand the implications? >> So, with OpenFaas we follow a model very similar to the Linux kernel, which is a sign off developer certificate of origin. What you're saying is I'm allowed to give you this code, I'm allowed for this to be a part of the project and I wrote it, I originated it. >> Lauren: Mm-hmm. >> And that's pretty much a good balance between a full contributor license agreement and nothing at all. >> John: Yeah. >> Lauren: Mm-hmm. >> But look, there's a lot of projects in this space right now. I don't know if you've noticed that, Kubernetes serverless projects. >> Yeah, I mean, it's a lot of really interesting, it's why I like this show here. I think what Cisco's smart to do here at DevNet Create is identify the network programmability, which really takes devops, expands the aperture of what devops is, so-- >> Alex: Yeah. >> You know, as you got new applications coming online some developers want nothing to do with the infrastructure. Kubernetes has got a much more active and more prominent role with layer seven primitives, for instance, or-- >> Alex: Yeah. >> Managing things down to the network layer. You're talking about policy services inside services on the fly, so this is really a big, a good thing, in my opinion. So, you know, I think, Kubernetes, most people look at as a kind of generic orchestration, but I think there's so much more there. >> Alex: Yeah. >> I think that to me is attracting some really rockstar developers. >> Yeah, well I think, you know, the fact that you are open, you're under the MIT license, which I am a fan of-- >> Alex: Yeah. >> And you know, it is, you're on a very successful trajectory in terms of, you know, what you're building and who's engaged and the fact that VMWare is behind you means that they're going to put some money into it, hopefully, and help you guys along as it works, but it is also a project that is not... You know, it doesn't have folks just from VMWare. >> Alex: Yeah. >> It's really, really diverse in terms of who's committing the code. So, I think there's a lot of things that are really going for you. Now, who do you see, you mentioned competitors... >> Alex: Yeah. >> So, can you talk a little bit about what the ecosystem there looks like? >> Yeah, so there's a number of projects that I think have made some really good decisions about their architecture and their implementation. They all vary quite subtly, and one of the questions I get asked a lot is, you know, how is this different from X, cubeless nucleo, and if you look at the CNCF landscape there used to be a very small section with OpenFaas, Lambda, and a couple of others. It's now so big it has its own PDF just about serverless, and I think that's super confusing for people. So, part of what we're trying to do is make that simple and say, "Look, there may be many options. "Here's OpenFaas, here's how it works. "You can get it deployed in 60 seconds. "You can have any binary or any programming language "you want and it will scale up over Kubernetes." We'll just make a really deep integration, give you everything you'd expect, really nice developer experience. >> Lauren: That's great. >> What are some of the use cases you see right now, low hanging fruit for developers that want to come in and get involved in the project? Have you guys identified any low hanging fruit use cases? >> So, what I've seen, and I talked about this a bit yesterday in the talk, is three big use cases, really. The first one was Anisha Keshavan at University of Washington. >> Lauren: Mm-hmm. >> Now, she's doing a lot of data science with neuroinformatics, medical images. She's able to take scans of brains and give them to people like you and me, who don't know anything about medical science. We just draw around the lesions and we train her model, and then she makes it competitive like a game, gamefies it, you get more points, but actually, what we're doing is making the world a better place by training her medical imaging database. >> Lauren: Mm-hmm. >> She'll then use that as an OpenFaas function to test real images as part of her postdoctorate. >> So, she's crowd sourcing, wisdom of crowds. >> Alex: Right. >> Collect some intelligence for her research. >> Now, one of the other things that I think's really cool is in the community we built out a project with two 17 year olds. Two 17 year olds built a really cool project, and when I think back to when I was 15, 16, I was playing with something like PHP on Windows Lamp Stack. You know, I had to do everything myself. >> John: Yeah. >> They got, like, this scaffolding built up and they could just go to the tenth story and just keep adding on. >> John: Yeah, yeah. >> And they didn't have to worry about managing this infrastructure at all. >> Or architecture, foundation architecture. >> Alex: Right, right. >> Yeah, and that's exactly the reason why you want to do that. >> So, they wrote some small blocks of Python that we found this machine learning code that could convert a black and white image to color, wrapped it in a box and said, "There's a function," then dropped it into OpenFaas and started feeding tweets in, and that was pretty much it. >> John: Yeah. >> Now we have @ColorizeBot, a bit of a strange spelling but you'll find it on Twitter, and it's been in Le Monde newspaper, all round the world. It was pronounced at CubeCon as well, and it's just a super interesting way of showing how you can take something very complex, right, and democratize it. >> Yeah, we'd love to get those people working for theCUBE and put the little cube box and throw all the tweets in there. >> Alex: Right, yeah. >> Alex, thanks for coming on, congratulations. What's next on your project, tell us what's going on, what's next for you, what are you guys conquering next? >> So, I'm really focused on growing the team and community. We've got an open recruitment position open right now and a small team that's building internally. I think the more people we can get contributing on a regular basis the more support there's going to be for the community, the more people are going to want to use this Actually had 26 people join a call last week. "How to contribute to OpenFaas," that was the name of it. >> Lauren: Mm-hmm. >> Around the world, and the best part for me was where we got to the testimonies and I had people just sharing their tips and experiences. How rewarding it is to contribute something bigger, something that you as a developer will actually want to use. >> Yeah, and the value opportunities, to extract value out of the group-- >> Yeah. >> It's phenomenal, functions as a service. Super relevant in cloud and devops as the middleware, if you want to call it that, expands more capabilities in devops are coming. It's theCUBE coverage here at DevNet Create. We'll be back with more live coverage here in Silicon Valley in Mountain View, California, after this short break. (techy music playing)

>> Announcer: Live from Manhattan, it's theCUBE covering AWS Summit New York City 2017. Brought to you by Amazon Web Services. >> Welcome back live to Midtown Manhattan, along with Stu Miniman, I am John Walls. We're here on theCUBE and we're wrapping up our coverage here at AWS Summit. Again, kind of tough to get a feeling for just how many folks were here. But some were in that seven, eight, $9,000 range and most of them are still here I think, out on the show floor here behind us. Good keynotes this morning. Good programming throughout the day as well and then really good buzz here on the show floor. So, good day I think, for AWS Stu, and we've talked about it, it is kind of remarkable to see the number of people who turned out for a regional show. >> Yeah John, you know I've been to some shows in the Javits Center where people wander in, they get some swag, they look for a free beer and a t-shirt and then that's kind of their... These people are, you know, kind of diggin' in. I know there's a bunch of sessions been going on. The pavilion here has had all these little breakout sessions. There was one on, you know, VMware and VMware and AWS and it was, you know, not only the seats, which usually it was like oh come on in, you know, come get a prize and things like that. >> John: Right, right. >> There was five rows of people standing pressed in and asking questions like, "How do I set up "the networking on this, how does this work?" Things like this, so it's like a mini AWS re:Invent, so their big show, one we've done theCUBE at a number of years, I've been there a number of years. I commented on our intro that this is larger than the first Amazon re:Invent that I went to like four years ago. >> How about that, in that short of period of time? >> Yeah and that's one of the things about Amazon and public Cloud in general and all of these technologies, the growth and the speed of change is just amazing. It used to be we talked from a software standpoint, it was like okay, I'm tied to that Intel release of every 18 months that I'm going to click out, then it was like okay, we kind of go to a yearly cycle. Now it was more like well not only is a lot of software released, you know, continuous integration and continuous deployment CICD, which sometimes it's every six weeks, sometimes it's daily, but Amazon's releasing new features every day. We talked in the intro, oh there were three major releases and we had the guy I'm talking about, the machine learning stuff and he's like oh you mean the three announcements that we had in machine learning? And we're like oh, we only heard about one of those. Wait, you had a couple others underneath there? Oh, let's talk about the F1 compute instance and the FPGAs. There's always so much in Amazon and when you go into any environment in the little boxes that they put in there and you start peeling the onion, it's impressive. >> It is. >> And there's just depth and customers are interested in it and people are using it. You know, I was used to so much in my career where something gets announced and a year later it's like hello, is anybody using this? As opposed to at this show, a bunch of the announcements, I already talked to a bunch of people that have been in private beta, they've been testing this out, they're excited about it and because it's just so easy to get on all of these new features. >> Right, and I mean, we've seen it here, we've heard from many people here from a lot of different walks of life. You mentioned some of the past shows, AWS Public Sector. I was at that not too long ago in Washington, D.C. and you see a company that has its units very focused and very driven and doing very well and the right relationships. Buzzword, serverless, right? We heard it a lot today. Serverless applications, serverless computing. From more than one source, we heard it from several folks and so obviously this is not just a popular piece of nomenclature for the day, this is a trend, a theme that's going to be evolving and maturing over the next year or two. >> Yeah I mean everybody for the last couple years they've kind of been looking at it with their head sideways. I'm not sure that I understand it. We talked to two companies today, it was IOPipe and A Cloud Guru that their company, their IT infrastructure was all built on serverless, and they both got funding recently, so this isn't just oh yeah, some developer does some cool stuff on the side, microservices, buzz buzz, things like that. We talked to FICO is using serverless for their admin functions, certain areas they're not ready to roll it out across the board, governance compliance, things like that, I need to understand it. It is still very early, but that being said, there's a lot of usage in it. Last year it was oh, if you want to develop for the Alexa platform, the Amazon Echo type thing, that uses serverless, so we're seeing lots and lots of cases. That really is a new way of architecting the way to roll out really microservices driven applications and when we talk about the big challenge of our time, it's distributed architectures and how do I have new applications? We talked to a number of companies moving from the old way of doing my application to building new application, that's the long hole in the 10. This is not something that happens overnight, but I can start playing with it in a much smaller form factor and do it for pennies not years and millions of dollars so there is really serverless has really in many ways eclipsed kind of the container's discussion for the hot buzz in the industry. Kubernetes fits into that whole picture, but not just serverless in general, but AWS Lambda is the leader of the pack out there and you know, yet another reason why Amazon just going strong, their revenue still doing well, keeps adding to what they're doing and you don't hear many people griping when you walk around the show floor as to what they wish they had. It's a very positive experience. >> And you hear criticisms saying, "They only had 42% growth year to year." It's not what it used to be. But 42 as you know, most people would gladly be in that position. What about your thoughts about the maturation of the Cloud? You mentioned transformative and things are evolving and growing, where do you put it now? Is this second phase, next phase, late phase? Where are we in terms of what's happening and what AWS is making happen? >> So a couple years ago we know that Cloud is here to stay. There's still the joke a friend of friend of mine in the keynote. 20,000 people registered for this event and it was like well, I guess this Cloud thing might have legs, so we are still early in the overall wave of this. I've been in a number of conferences this year that we've done theCUBE on. You talk about the infrastructure companies and companies that have built on virtualization. They said, "We went through a decade "of tremendous growth with virtualization." Virtualization is still very important. Amazon builds their infrastructure not on VMWare, but they leverage virtualization technologies, but the next 10 years will be this huge wave of really that going up the uptake of the S curve so we're past really the classic crossing the chasm. We're in the early majority going to mid majority of people using it and there's just no shortage of new use cases that people can use it for. We've talked to lots of companies that start up and say, "I'm just leveraging Cloud because it's easy." THere's VCs that look at that as how to get involved and as I've just mentioned before, there's companies now that are building themselves on serverless so this is even kind of the next piece that follows these waves we are early in Cloud if you look at kind of overall ham of IT, public Cloud is still a very small piece. At Wikiban we've been talking for the last I think two years about what we really the multi Cloud environment. There's true private Cloud and there's public Cloud and how do I get that operational model that I can scale, I can build really a distributed architecture? I shift more to an operational expense rather than a capital expense, so it's flexibility, it's agility, it's speed, and it's very interesting, exciting times. There's no more exciting time to be in tech than today, maybe tomorrow, because we know the only thing constant is that the pace of change keeps increasing. >> It does increase and two big drivers of that, we heard again today, artificial intelligence, machine learning. How would you rate or how would you characterize the impotence that they're providing in terms of pushing the envelope? >> Absolutely there was some good announcements today, I don't know that there's any today that you'd say, "I'm going to look back five years from now and be like, 'Wow, I was in New York City when that was announced.'" >> John: Right, but just in general? >> But in general, let me say one of the things that I didn't hear today, I was was little bit disappointed, I mentioned it in the open, we talked to a couple of the partners here, you know the Kubernetes option. Adrian Kovrov got up on stage. He had written a blog post there was an announcement last week, no mention of where Kubernetes is going to fit in here. Definitely they're committed to it, they're making developments, but maybe something will come out in beta soon. I would expect by the time we get to the re:Invent show in November that we will have more clarity here. I was hoping to hear that more and that was something that didn't come out of Amazon, but they're embracing it. Customers are asking for it, developers, there's a ground swell on that, so they're involved with it. Lambda and serverless absolutely. Amazon is at the vanguard, they're pushing things forward. Machine learning and IoT, Amazon is at the table. It is still very early, they're driving a lot of things forward. Yeah, you know, you get enough, it's like come on, there's no BitCoin discussed today, why is that? So some of the other vendors there, but Amazon is in all the appropriate conversations. There's not any wide gaps that you'd say customers like hate these. Amazon's not in this base and I expect them to and therefore I'm going to choose another platform provider. That being said, it's not a winner-take-all, it is a multi Cloud world, most of these environments, we talked about even if I do serverless, if I architect them a certain way I can move them and make changes, Kubernetes the same way. So Amazon, one of the things that they pride themselves on is they need to keep proving to their customers every month that they are the ones that they fuse on because otherwise it is relatively easy to make a change, but they're the big dog, they got the leadership position, and it's always impressive to watch them. >> It is and you speak of impressive. re:Invent, is just what, two and a half months away, three months away, we'll be out there as well. Huge show, probably one of the largest shows by far that we attend and looking forward to that and seeing you down the road. Always a pleasure to be with you. >> Thanks so much. >> And great job as always. Stu Miniman does an outstanding job providing analysis for Wikiban, so on behalf of Stu and all the crew here at theCUBE, we thank you for joining us here at the AWS Summit in Midtown. We've been live at the Javits Center. Have a good week and we'll see you down the road here on theCUBE. (light electronic music)