(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)

>> 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)

>> Narrator: Live from Las Vegas, it's The Cube, covering IBM Think 2018. Brought to you by IBM. >> Hello everyone, welcome to the third day of live coverage here at IBM Think in Las Vegas. This is The Cube, our flagship program, we go out to the events, and extract a civil noise of the leader in live technology coverage. I'm John Furrier, with my co-host Dave Vellante. Our seventh, eighth year covering a bunch of IBM shows. With all now six of them rolled into one IBM Think, this is their big tent event, day three, keynotes just finished, it's blockchain day here at IBM, and as we said, on the opening, on Tuesday, this is like, the innovation sandwich. In the middle is the meat, is data, and then the bread is blockchain and AI. And really that is the architecture of IBM's future strategy, foundationally set up by cloud computing and a variety of other applications and whatnot, but really the future is about data, with blockchain and AI surrounding it. Today's blockchain day, your thoughts on the keynote? Keynote speeches? >> Mm-hm. >> IBM, blockchain, certainly we've seen a lot of advertising on TV. Your thoughts and reaction to the keynote. >> Yeah, and I like your innovation sandwich, I just want to add, that the substrate of all this is cloud. It's critical, if you're going to get network effects, you've got to have the cloud. Today, yeah, was blockchain day, we heard from Marie Wieck, who's the general manager of IBM blockchain. IBM has a tendency, as you know, John, to identify a hot trend, especially some in Open Source, they did this with Linux, they did this with Spark, and they kind of, elbow their way in, you know, maybe that's a pejorative, but they do that, and they say, "Here's some code, here's some resources." They spend money on it, and they give credibility to that Open Source effort. The Hyperledger project is the one they targeted here. It's the fastest growing project in the history of the Linux Foundation. IBM contributed lines of code, people, they've got 15 hundred blockchain experts on this, and they're going all in on blockchain. Which I think, John, is really positive for the blockchain, and even the crypto community, because it brings the credibility of a, you know, a Fortune 100 company to that world. They've announced the blockchain starter kit. All this stuff is available on the IBM cloud. They announced today PWC as an audit partner, which again, brings credibility to the table. Although, I think as you and I know, and we're going to have some guests on later today, there's some other tech emerging, that is going to maybe complement that. >> Yeah. >> And we heard from David Katz, who is the CEO of Plastic Bank, this is the company that's essentially creating currency out of plastic. Allowing disadvantaged people to turn collecting plastic into money. And, at the same time, help save the planet. >> I mean, this is a great example of blockchain as an enabling technology. New ways to do business. As you know, we've been hot on blockchain for the audience watching, you know, we've been covering big data, and AI, that's in our wheelhouse, do all those shows and events, cover that territory with our journalism, and TV and research. But blockchain is an adjacency to storage and infrastructure, and also decentralized applications. The fundamental thing that we're seeing, and we talked to Brian-- Brian Behlendorf, who's with the Hyperledger project, at the Open Source Summit, the Apache Foundation, which IBM is a big sponsor of, IBM needs to do well here. Because they're, again, innovations is essentially betting on blockchain. But it's not just the developers at Open Source, the business users are the ones that are going to create the value, and what I mean by that is, if you look at the blockchain world, and crypto currency and decentralized applications, that's essentially the three components to this market. The blockchain is the infrastructure, ledger, storage of data, et cetera, you know over simplified, but the cryptocurrency runs protocols and infrastructure that power that, and then the application's going to sit on top. We've reported and observed that the secret of success in this new world, is nailing the business logic, and the business model, efficiencies that take advantage of the underlying technology. And that the risk factors in making that success happen, is that business model, not the technology. Although the technology is super important, the technology can be switched out a reduced risk. So the real risk in blockchain and cryptocurrency, and decentralized applications is nailing the business model disruption. This is different than the old way of tech, which was the risk was technology selection. This is a big deal, IBM needs to up their game on that piece of it. I've heard a lot of tech, I've got some nice use cases, but on the outreach basis, they got to go to the business users, and say, "This is an opportunity to leverage the data, "leverage the software and AI with watts and other things." And then leverage the underlying technology, software defined storage, software systems that move to the blockchain, in a decentralized and distributed way. Distributed and decentralized is the future of infrastructure, this is the secret of success, this is where the winners are establishing the clear line of sight. >> Well, one of the things that you're hearing at this conference, Ginny set this up yesterday, was incumbent disrupters, and we were just, kind of, having fun at the open yesterday, but I think it's really smart for IBM. You know me, John, I'm a big fan of saying most of your business is going to come from your existing customers, and if you're chasing all this new business, and start ups, and developers, you're not going to be as productive as if you go to your core. And I think that you're seeing this. IBM back to the core, and they're bringing blockchain to that core as a way to disrupt existing business models, defend against disrupters. So you're absolutely right, companies need to look for inefficiencies where there's a third party taking a toll, and then attack it hard with blockchain. I actually think-- well no, so IBM is really talking business. How do we bring blockchain to the business? They're not really talking about what we talk about a lot, this crypto economy and this whole other mission driven initiative. >> Well, but I mean, if they want to talk business, they got to talk token economics. That's where the business model efficiencies will be rendered on the app side, and the money side. The killer wrap in blockchain and crypto is money. Okay, and marketplaces. IBM got to great marketplace, but it's not just about the developers, that's an organic one stakeholder. The stakeholders that matter is the business guys and the developers coming together. That is absolutely fundamental. If they don't understand that, that's going to be hard to be successful. You can't just throw money at developer programs and say, "Oh, when we win the developers, we win the day." Cloud was, kind of, that playbook, but this world is so fast, and accelerating in it's value creation, that the business users are fundamental in actually grokking what the capabilities are, and putting that into motion quickly, and the proof points is pilots converting to production. That's going to come from the business units. That's where the intellectual property is, is looking at the technology innovations that are possible on the business logic. Business logic is the new IP, this is where the action is, and I haven't heard IBM talk at all about token economics, they kind of talk about it, but that really is the business impact. >> Well, I mean, you sort of heard that today from Plastic Bank, although they didn't talk about a token, they didn't talk about coins, they did talk about monetizing plastic, but in using blockchain to do that, I assume there's tokens behind that, but maybe not. Maybe it's just Fiat currency. It's unclear to me, but I think you're right, the killer app is money. >> Look at it, this is simple. The equation in crypto, and not blockchain, is value creators create value, and they can capture the value. Capturing the value is where the money is, the creating the value is where the technology can happen. So you got to nail both of those as areas. And money is the killer app, so that's going to come from the business side, so the real benefit of decentralization is offering the value capture equation to look different and be different. That's token economics. That's where the action's going to be. So, it really is, it's not mutually exclusive, they're both things. >> Well I think that what you're hearing, so value comes from two places in the simplest form, increased revenue, cut costs. I'm hearing a lot from IBM of cut costs, now again, the Plastic Bank this morning was a really interesting example, I'm glad IBM uses it, but the vast majority of things you're hearing from IBM, like the IBM Maersk relationship, et cetera, are about cutting costs, taking out inefficiencies. >> Well, I mean, the bank thing is easy to look at in your mind, but it's any supply chain. The ICO market that's at a massive bubble right now, is because the supply chain of funding start ups and growth, used to come from private equity and venture capital, that is being disrupted because it certainly hyped up, but that's a supply chain. Any supply chain activities, set of activities, that make up a supply chain, can and will be disrupted by blockchain, crypto, and token economics. >> Yeah, so let's talk about that. Because again, you're not hearing a lot of that from IBM. But I think we have a perspective there. You know, the 1.0 was the wild west, a bunch of developers, blockchain developers, theory developers, doing stuff, building up protocols, making a lot of money. And disintermediating the VCs, right? The new form of raising capital. The VCs are now all in, right? We saw this in Bahamas, you saw this in Puerto Rico, at the two conferences, at four conferences that we covered. So explain that? >> Well, that's just one application, the VCs and these guys are inefficient in some way, but what's happening with crypto currency about access to capital. Now there's a lot of capital being thrown out there. That's mainly because of the hype and the bubble aspect of it, but the real disruption is access to capital, that value chain, value activities are being disrupted and being more efficient. That's a global phenomenon, and that's happening in financing of start ups. Anything with a supply chain, whether it's moving food from point A to point B, is what IBM also highlights as well, anything that's structural incumbent is at risk. And so, this is where, I mean IBM has a ton of supply chain business. They've been doing this for generations in the computer industry. They connect systems together, and create value with using technology. So this is not going to be-- this is a great opportunity for IBM. Again, if they can convert that business value into the blockchain with the value capture, the create capture model, they can run the table. >> But I want to come back to innovation equation. And part of that innovation equation is being able to raise capital. And last I checked, which was last month, about 6.5 billion had been raised in crypto investments. >> And 60% of the projects failed. >> For sure, okay. But failure-- Silicon Valley, fail fest, it's probably up to 10 billion now, much more is being raised through crypto in startups in blockchain than there is in VC. The VCs realized this, and they want a piece of the action, but we're seeing private equity, we're seeing hedge funds, we're seeing crypto billionaires. >> The path of least resistance for the entrepreneur is where the action is. They go right to the new money opportunity. Because they can raise more money. >> So, here's the question. You take Fiocoin, for example, smart guys, trying to go after S3 with peer to peer storage, they raised 250 million dollars in 30 minutes, okay? Is it too much too fast? >> Yes, I think so, but it's what the market's giving. I mean, Fiocoin doesn't even have a product. They're on a roadmap. That's essentially a series A financing. >> Dave: That's a series C. >> Well, no, in terms of the evolution of the startup, it's a seed financing as a series C or D or F financing. >> Yeah, 250 million. >> I mean, it's insane. >> David Scott told us that he needed 85 to start Three Par. I mean that's a storage company 10 years ago, 20 years ago. >> Yeah. >> What a change. At 250 million. >> Look, it's a bubble. But the reality is that it's a bubble that's not going to pop and destroy the sector, it's just a proof point that the efficiency of funding is going to be disrupted. It is being disrupted. >> No, we'll see if it's going to destroy this sector or not. This could, you know-- Warren Buffet says it's going to end badly, others are believers. >> I'm long on blockchain, obviously you know that. I'm pretty biased, but anywhere there's inefficiencies, there's an opportunity for entrepreneurs and business leaders to put new business logic in place to capture that value. That's where the action will be. That's the innovation. And if IBM's innovation sandwich could work, you got a blockchain AI, data in the middle, everyone's going to be full and hungry and eat up everyone's lunch. So, Dave, that's the blockchain day. I'm John Furrier, with Dave Vellante, day three wall to wall coverage here at IBM Think in Las Vegas. More live coverage after this short break. (futuristic music)

(mid-tempo music) >> Announcer: Live, from Los Angeles, it's The Cube. Covering Open source Summit North America 2017. Brought to you by the Linux Foundation and Red Hat. >> Okay welcome back and we're live in Los Angeles for The Cube's exclusive coverage of the Open Source Summit North America. I'm John Furrier, my co-host Stu Miniman, Our next guest is Steve Pousty, who's the Director of Developer Advocacy for Red Hat, Cube alumni, we last spoke at the Cisco Devnet Create, which is their new kind of cloud-native approach. Welcome Back. >> Thank you, thank you, glad to be here. >> We're here at the Open Source Summit, which is a recognition that of all these kind of ... With LinuxCon, all these things, coming events, it's a big ten event, love the direction, >> Yeah Validation to what's already happened and the recognition of open source, where Linux is at the heart of all that, Red Hat also you guys are the Linux standard, and gold standard, but there's more- >> We like to think of it that way, but- >> But there's more than Linux on top of it now, so this is a recognition that open source is so much more. >> For sure, I'm mean you can even see ... Who would've thought that there'd be a whole huge hubbub about Facebook doing a separate license for their react libraries and all the interactions with Apache, the Apache Foundation. Open source is so much ... it's the mainstream now. Like, basically, it's very hard to release a proprietary product right now and come up with some justification about why you have to do it. >> And why, and can it even be as good. >> Steve: Right. >> There's two issues, justification and performance. >> Yeah, quality, all that stuff. And also, customers' acceptability of that. Like, "Oh wait, you mean I can't actually even see the code? "I can't modify the code, I can't pay you to modify the code "and share it with everybody else?" I think customers have come to a whole ... Users of open source stuff, it's so permeated now that I think it's hard to be in the market without ... I mean, look at everybody who's here. Some of the people that are here were some of the biggest closed source people before. >> John: Microsoft is here. >> Exactly. >> John: IBM is here, although they've always been open, they were big on Linux early on. >> Yes. >> But now you're seeing the ecosystem grow, so we see some scale coming, but there's still a lot of work that needs to get done. We see greatness, like Kubernetes and Serverless offering great promise and hope for either multi-cloud workflow, workload management, all those cool stuff. But there's still some work to be done. >> Steve: For sure. >> What's your take on progress, where are we, what's the ... some of those under the hood things that need to get worked on? >> Well so, progress, I think ... the funny part is our expectations have changed so much over time that, so Kubernetes is about a little over two years old, and we're all like, oh it's moving so s-- why is it not doing this, this, and this? Whereas if this was like 10 years ago, the rate at which Kubernetes is moving is phenomenal. So, basically, every quarter there is a new release of Kubernetes, and we basically built OpenShift as a distribution on top of Kubernetes, and so we're delivering to our customers every quarter as well, and a bunch of them are like, "This is too fast, this is too fast, "like, we can't integrate all these changes." But at the same time, they say, "But don't slow down." Because, "Oh, next release we're going to get this thing "that we want and we know we want to go to that release." So, I think Kubernetes definitely has more growing room, but the thing is, how much it's already being seen as the standard, it's the ... so the way I like to talk about it, and I'll talk about this in my talk later, I think for Red Hat, Kubernetes is the cloud Linux kernel. It's the exact same story all over again. It's this infrastructure that everybody's going to build on. Now there are people who are standing up OpenStack on Kubernetes, or on OpenShift. So basically saying, "I don't want to install and manage "my Openstack, it's too difficult. "Give me some JSON and some components "and I'll just use Kubernetes as my operating plane." >> We saw Kubernetes right out of the gates, Stu and I, at the first Cube-Con, we were present at creation, and just on the doorstep of that thing just unfolded, and we saw the orchestration piece is huge, but I want to get your take if you can share with the audience, why Kubernetes has taken the world by storm. Why is it so relevant? What's all the hubbub about with Kubernetes? Share your opinion. >> Okay, so remember ... okay so this is a red shirt, and remember I work at Red Hat, so this obviously a biased opinion. I want to be up front about that. >> John: In your biased opinion ... >> Right, well as opposed to a neutral opinion, right, we definitely, so, I say that in front of my audiences just so that ... go do your own research, but from my perspective and what I've seen in the market place, there was a lot of orchestration and scheduling out there, then it kind of narrowed down, there's three players I would say right now. The three players all end with Kubernetes, but I just started with it (laughs). There's Kubernetes, there is Mesosphere, and there's Docker Swarm. I see those as being the three that are out there right now. And I think the reason we're ... So I won't talk about the others, but I see those ... Why Kubernetes has won is, one, community. So they have done a great job of being upstream, working with all people, being a very open community, open to working with others, not trying to make things just so it benefits Google's business but to benefit everybody. The other reason is the size of that community, right, everybody working together. The third is I think they, so some of it's luck, right? >> John: Yeah, timing is everything. >> Timing is everything. >> John: You're on a wave, and you're on your board and a big wave comes, you surf it, right? >> That's exactly, so I think what happened with Mesosphere is they're a great scheduler, and a lot of people said they were the best scheduler to start with. But they didn't really focus on containers to start with and it seems like they missed ... Like, Kubernetes said, "No, it's all about containers "and we're going to focus on container workload." And that's right where everybody else was. And so it was like, "I don't want to write "all that extra stuff from Mesosphere. "I want to do it with Kubernetes 'cause that's containers." And so that's the bit of luck lining up with the market. So I'd say it's the community but also recognizing that it's about containers to start with and containers are kind of taking over. >> Yeah, Steve, take us inside containers. You're wearing a shirt that says "Linux is Containers" on the front, if our audience could see the back it says "Containers are Linux." >> Steve: Exactly. >> Of course, Red Hat heavily involved. You're in the weeds, dealing with things that we're doing to make stability of containers, make sure it works in other environments. Tell us some of the things you're working on, some of the projects, and the like. >> So, some of the projects I'll be showing today, one is based off of OpenScap, Open S-C-A-P, it's another open consortium for scanning for vulnerabilities. We've written something called Atomic Scan, so it can take any OpenScap provider, plug it in to Atomic Scan, and you can scan a container image without having to actually run it. So, you don't actually have to start it up, it actually just goes in. The other thing I'm going to be talking about today is Bilda, this is part of the CNCF stuff. This is the ability to actually build a runC-compatible container without ever using Docker or MOBI. The way, a totally different approach to it, what you basically do is you say, "I want this container from this other container, or from blank," then you have a container there and then you actually mount the file system. So rather than actually booting a container and doing all sorts of steps in the container itself, you actually mount the file system, do normal operations on your machine like it was your normal file system, and then actually commit at the end. So it's another way for some of our customers that really like that idea of how they want to build and manage containers. But also, there's a bunch more. There's Kryo, which is the common runtime interface, and the implementation of it, so that Kubernetes can now run on an alternative container technology. This is Kryo, it's agnostic. If you looked at Kelsey Hightower's latest "Kubernetes and Anger," I think, or "Kubernetes the Hard Way" or something. His latest is building it all on Kryo. So rather than running on Docker, it runs ... All your container running happens on Kryo. I'm not trying to say, well of course I think it's better, but I think the point that we're really seeing is, by everything moving in to CNCF and the Linux Foundation and getting around standards, it's really enabled the ecosystem to take off. Like, TekTonic and CoreOS have done that with Rocket. We're going to see a lot more blossoming. The fertilizer has been applied, back from our ... >> Yeah, CNCF of two years old, I mean their fertilizer down big time, you got the manure and all the thousand flowers are blooming from that. >> Yeah, between Prometheus, I mean just, Prometheus, Istio, there's just ... I can't even keep track of it all. >> So Steve, you were talking earlier. Customers are having a hard time with that quarterly release. >> Steve: Yes. >> How do they keep up with all these projects, I mean you know, we rattled through all of 'em. You've got 'em all down pat, but the typical customer, do they need to worry about what do they have to focus on, how do they keep up with the pace change, how do they absorb all of this? >> Okay so it highly depends on the customer. There are some customers who are not our customers, I'll just say users, who are advanced enough on their own, who they're out there basically just, they're consuming the tip of what's coming out of CNCF. All that stuff, and they're picking and choosing and they're doing that all. For Red Hat, a lot of our customers are, "I like all that technology, you're our trusted advisor, "when you release it as a product "and I know I can sit on it for three years, "because you'll support it for at least three years, "maybe five years, then I'm going to start to consume it "and you'll actually probably put it into a more usable form for me." 'Cause a lot of the upstream stuff isn't necessary made direct for consumption. >> How are you guys dealing with the growth prospects. We've been talking about this all morning, this has been the big theme of this show is, not only just the renaming of a variety of different events, LinuxCon, but Open Source Summit is an encapsulation of all the projects that are blossoming across the board. So, the scale issues, and as a participant, Red Hat, >> Steve: Yes. >> Your biased opinion, but you're also incentive and you guys are active in the community. The growth that's coming is going to put pressure on the system. It may change the relationship between communities and vendors and how they're all working together, so again, to use the river analogy, there's a lot of water going to be pumping through the system. And so how's that going to impact the ecosystem, is it going to be the great growth that could flood everything, is there a potential for that, I mean you're an ecosystem guy, so the theory is there, it's like, Jim's stepping up with the Linux Foundation. I talked to him yesterday and he recognizes it. >> Steve: Yeah. >> But he also doesn't want to get in the way, either. >> Steve: No, no, no- >> So there's a balance of leadership that's needed. Your thoughts. >> So, I mean I think one of the things ... So I mean you know the Linux kernel has its benevolent dictator, and that works well for that one community, but then you'll see something like Kubernetes, where it's much more of a community base, there is no benevolent dictator for life on Kubernetes. I think one of the nice things that the Linux Foundation has done, and which Red Hat has acknowledged is, you know, let the community govern the way that works for that community. Don't try to force necessarily one model on it. In terms of the flood part that you were talking about, I think, if you want to go back to rivers, there's cycles in terms of 10 year floods, 100 year floods, I think what we're seeing right now is a big flood, and then what'll happen out of this is some things will shake out and other things won't. I don't expect every vendor that's here to be here next year. >> And find the high ground, I mean, I mean the numbers that Jim shared in his opening keynote is by 2026, 400 million libraries are going to be out there versus today's 64 roughly million. >> Steve: Right. >> You know, Ed from Cisco thinks that's understated, but now there's more code coming in, more people, and so a new generation is coming on board. This is going to be the great flood in open source. >> I also think it's a great opportunity for some companies. I mean, I'm not high enough in Red Hat to know what we're doing in that space, but it's also a great opportunity for some companies to help with that. Like, I think, that's one of the other things that Linux Foundation did was set up the Javascript Foundation. That is a community that-- >> But that doesn't have Node.js, it's a little bit separate. >> No, I know, but think-- >> You're talking about the js, okay. >> But I'm talking about, but if you think about the client-side javascript, forget Node. Just think about client-side javascript and how many frameworks are coming up all the time, and new libraries. >> Stu: That's a challenge. >> So I think actually that community could be one that could be good to maybe gain some lessons from, as things happen more in open source. I think there are other open source communities. Like, I'm wondering like GNOME-- >> But the feedback on the js community is that there's a lot of challenges in the volume of things happening. >> And that's coming for us though, right? >> Yeah. >> That's what's coming, that's what's going to come for this larger ecosystem, so I think maybe there's market opportunity, maybe there's new governance models, maybe there's ... I mean, this is where innovation comes from. There's a new problem that's come, it's a good problem. >> Your next point of failure is your opportunity to innovate. >> Exactly, and it's a good problem to have, right, as opposed to, we have too few projects, and we don't really, no one really likes them. Instead, now it's like, we've got so many projects and people are contributing, and everybody's excited, how do we manage that excitement? >> So another dynamic that we're observing, and again we're just speculating, we're pontificating, we're opining ... is fashion. Fashion, fashionable projects. Never fight fashion, my philosophy is. In marketing, don't fight the fashion. >> Steve: Right. >> CNCF is fashionable right now, people love it. It's popular, it's trendy, it's the hip new night club if you will in open source. Other projects are just as relevant. So, relevance and trending sometimes can be misconstrued. How do you guys think about that, because this is a dynamic, everyone wants to go to the best party. There a fear of missing out, I'm going to go check out Kubernetes, but also relevance matters. >> Yes. >> John: Your thoughts. >> So I've seen this discussion internally in engineering all the time, when we're talking about, 'cause you know OpenShift is trying to build a real distribution, not like, "Oh here is Kubernetes," but a real distribution. Like when Red Hat ships you the Linux, gives you Linux, we don't just say, "Here's the Linux kernel, have a good time." We put a whole bunch of stuff around it, and we're trying to do that with Kubernetes as well, so we're constantly evaluating all the like, "Should we switch to Prometheus now, "when's the time to switch to Prometheus? "Oh it's trending really hot. "Oh but does it give us the features?" >> John: It's a balance. >> It's a balance, it's going to have to come down to, I hate to say it-- >> It's a community, people vote with their code, so if something has traction, you got to take a look at it. >> But I would say, and this has been going on for a while, and I've seen other people talk about it, if you are the lead on an open source project, and you want a lot of community, you have to get into marketing. You can't just do-- >> John: You got to market the project. >> You got to, and not in the nasty term of market, which is that I'm going to lie to you and like, what a lot of developers think about like, "Oh I'm just going to give you bullshit and lie to you, "and it's not going to be helpful." No, market in terms of just getting your word out there so at least people know about it. Lead with all your-- >> John: Socialize it. >> Yeah. I mean, that's what you got to get it, so there is a lot of chatter now. How do you get it noticed as a Twitter person, right? You have to do some, it's the same, it's going to be more like that for open source projects. >> John: So we're doing our share to kind of extract the signal from some of the noise out there, and it's great to talk to you about it because you help give perspective. And certainly Red Hat, you're biased, that's okay, you're biased. Now, take your Red Hat off. >> Okay. >> Hat off. Take your Red Hat hat off >> Steve: Propaganda hat off. >> and put your neutral hat on. An observation of Open Source Summit, I'll see that name change kind of significance in the sense it's a big ten event. This event here, what's your thoughts on what it means? >> Hey c'mon Steve, you've got a PhD in ecology, so we want some detailed analysis as to how this all goes together. >> I mean it's good marketing, Open Source Summit, good name change, little bit broader. >> I'm actually glad for it. So, I've gone to some other smaller events, and I actually like this, because it was hard for me to get to the smaller events, or to get quite enough people. Like this actually builds a critical mass, and more cross-fertilization, right, so it's much easier for me to talk to containers to car people. 'Cause automotive Linux is here as well, right? >> John: You can't avoid it, you see 'em in the hallways, you can say, "Hey, let's chat." >> "Let's talk about that stuff," whereas in the small ... So, you know, this is more about conferences. There's a good side and a bad side to everything, just like I tell my kids, "When you pick up a stick, you also have to pick up the other end of the stick." You can't just like have, "Oh this is a great part," but you don't get the bad part. So the great part about this, really easy to see a lot of people, see a lot of interesting things that are happening. Bad part about this, it's going to be hard, like if this was just CNCF, everybody here would be CNCF, all the talks would be CNCF, it's like you could deep dive and really go. So, I think this is great that they have this. I don't think this gets, should get rid of smaller, more focused events. >> Well at CubeCon, our CubeCon, the CNCF event in Austin, we'll be there for The Cube. That will be CNCF all the time. >> Steve: Exactly. I'm glad they're still doing that. >> So they're going to have the satellite event, and I think that's the best way to do it. I think a big ten event like this is good because, this is small even today, but with the growth coming, it'll be convention hall size in a matter of years. >> Well, exactly, and the fact that you made it into a big, and the fact that you've made it into this cohesive event, rather than going to somebody and saying, "Hey, sponsor these five events." Like, No. Sponsor this one big event, and then we'll get most of the people here for you. >> It's also a celebration, too. A lot of these big ten events are ... 'Cause education you can get online, there are all kinds of collaboration tools online, but when you have these big ten events, one of the rare things is it's the face to face, people-centric, in the moment, engagement. So you're learning in a different way. It's a celebration. So I think open source is just too important right now, that this event will grow in my opinion. >> Steve: For sure. >> Bring even thousands and thousands of people. >> I mean, another way-- >> John: 30,000 at some point, easily. >> Yeah, I think definitely it's theirs to lose, let's put it that way. >> John: (laughing) I'll tell that to Jim "Hey, don't screw it up!" >> Don't screw it up. I think the way that you could almost think of this is OSS-Con, right, instead of Comic-Con, this is like, this can become OSS-Con, which is like, they should probably ... In the same way that the Kubernetes Foundation works and grows with a lot of other people, it would be great if they could bring in other Foundations as well to this. I know this is being run by the Linux, but it'd be great if we could get some Apache in here, some Eclipse in here, I mean that would just be-- >> John: A total home run. >> Those foundations bringing it in-- >> That would truly make it an open source summit. >> Yeah, exactly, as opposed to the World Series that's only in the United States. >> Yeah. (laughing) >> Although you know, I was at a hotel recently, and they had baseball on, it was little league baseball though. Their World Series is actually, Little League World Series is actually the World Series. >> John: It's a global World Series. >> Yeah, like their-- >> John: It's the world. >> Yeah, as opposed to the MLB, right? >> Alright, Steve, great to have you on, any final thoughts on interactions you've had, things you've learned from this event you'd like to share and pass on? >> No, I just think the space is great, I'm really excited to be in it. I'm starting to move a little bit more up to the application tier at my role at the company and I'm excited about that, to actually ... So I've been working down at the container tier, and orchestration tier for a while, and now I'm excited to get back to like, "Well now let's actually build some cool stuff "and see what this enables on the up--" >> And DevOps is going mainstream, which is a great trend, you're starting to see that momentum beachhead on the enterprises, so-- >> Oh, one takeaway message, for microservices people, please put an Ops person on your microservice team. Usually they start with the DBA, and then they say the middle person and the front-end people. I really want to make sure that they start including Ops in your microservice teams-- >> John: And why is that, what'd you learn there? >> Well because if you're going to do microservices, you're going to be, the team's going to end up doing Ops-y work. And it's kind of foolish not to bring in someone who already knows ... The reason you want all the team together is because they're going to own that. And you also want them to share knowledge. So, if I was on a microservice team, I would definitely want an Ops person teaching me how to do Ops for our stuff. I don't want to reinvent that myself. >> You got to have the right core competencies on that team. >> Steve: Yeah. It's like having the right people in the right position. >> Steve: Exactly. >> Skill player. >> Steve: Yeah, exactly. Okay we're here live in Los Angeles, The Cube's coverage of Open Source Summit North America. I'm John Furrier, Stu Miniman. More live coverage after this short break. (electronic music)

>> Narrator: Live from Las Vegas, it's theCUBE. Covering Dell EMC World 2017, brought to you by Dell EMC. >> Okay, welcome back everyone, we are live in Las Vegas for Dell EMC World 2017. This is theCUBE's eighth year of coverage of what was once EMC World, now it's Dell EMC World 2017. I'm John Furrier at SiliconANGLE, and also my cohost from SiliconANGLE, Paul Gillin. Our next guest is Vikram Bhambri, who is the Vice President of Product Management at Dell EMC. Formally with Microsoft Azure, knows cloud, knows VIPRE, knows the management, knows storage up and down, the Emerging Technologies Group, formerly of EMC. Good to see you on theCUBE again. >> Good to see you guys again. >> Okay, so Elastic Compute, this is going to be the game changer. We're so excited about one of our favorite interviews was your colleague we had on earlier. Unstructured data, object store, is becoming super valuable. And it was once the throwaway, "Yeah, store, later late ". Now with absent data driven enterprises having access to data is the value proposition that they're all driving towards. >> Absolutely. >> Where are you guys with making that happen and bringing that data to life? >> So, when I think about object storage in general, people talk about it's the S3 protocol, or it's the object protocol versus the file protocol. I think the conversation is not about that. The conversation is about data of the universe is increasing and it's increasing tremendously. We're talking about 44 zettabytes of data by 2020. You need an easier way to consume, store, that data in a meaningful way, and not only just that but being able to derive meaningful insights out of that either when the data is coming in or when the data is stored on a periodic basis being able to drive value. So having access to the data at any point of time, anywhere, is the most important aspect of it. And with ECS we've been able to actually attack the market from both sides. Whether it's talking about moving data from higher cost storage arrays or higher performance tiers down to a more accessible, more cheap storage that is available geographically, that's one market. And then also you have tons of data that's available on the tape drive but that data is so difficult to access, so not available. And if you want to go put that tape back on a actual active system the turnaround time is so long. So being able to turn all of that storage into an active storage system that's accessible all the time is the real value proposition that we have to talk about. >> Well now help me understand this because we have all these different ways to make sense of unstructured data now. We have NoSQL databases, we have JSON, we have HDFS, and we've got object storage. Where does it fit into the hierarchy of making sense of unstructured data? >> The simplest way to think about it is we talk about a data ocean, with the amount of data that's growing. Having the capability to store data that is in a global content repository. That is accessible-- >> Meaning one massive repository. >> One massive repository. And not necessarily in one data center, right? It's spread across multiple data centers, it's accessible, available with a single, global namespace, regardless of whether you're trying to access data from location A or location B. But having that data be available through a single global namespace is the key value proposition that object storage brings to bear. The other part is the economics that we're able to provide consistently better than what the public clouds are able to offer. You're talking about anywhere between 30 to 48% cheaper TCO than what public clouds are able to offer, in your own data center with all the constraints that you want to like upload to it, whether it's regular environments. Whether you're talking about country specific clouds and such, that's where it fits well together. But, exposing that same data out whether through HDFS or a file is where ECS differentiated itself from other cloud platforms. Yes, you can go to a Hadoop cluster and do a separate data processing but then you're creating more copies of the same data that you have in your primary storage. So things like that essentially help position object as the global content repository where you can just dump and forget about, about the storage needs. >> Vikram I want to ask you about the elastic cloud storage, as you mentioned, ECS, it's been around for a couple of years. You just announced a ECS lesser cloud storage, dedicated cloud. Can you tell me what that is and more about that because some people think of elastic they think Amazon, "I'll just throw it in object storage in the cloud." What are you guys doing specifically 'cause you have this hybrid offering. >> Absolutely. >> What is this about, can you explain that? >> Yeah, so if you look at, there are two extremes, or two paradigms that people are attracted by. On one side you have public clouds which give you the ease of use, you just swipe your credit card and you're in business. You don't have to worry about the infrastructure, you don't have to worry about, like, "Where my data is going to be stored?" It's just there. And then on the other side you have regular environments or you just have environments where you cannot move to public clouds so customers end up put in ECS, or other object storage for that matter, though ECS is the best. >> John: Biased, but that's okay. >> Yeah, now we are starting to see customers they're saying, "Can I have the best of both worlds? "Can I have a situation where I like the ease of use "of the public cloud but I don't want to "be in a shared bathtub environment. "I don't want to be in a public cloud environment. "I like the privacy that you are able to provide me "with this ECS in my own data center "but I don't want to take on the infrastructure management." So for those customers we have launched ECS dedicated cloud service. And this is specifically targeted for scenarios where customers have maybe one data center, two data centers, but they want to use the full strength and the capabilities of ECS. So what we're telling them we will actually put their bought ECS in our data centers, ECS team will operate and manage that environment for the customer but they're the only dedicated customer on that cloud. So that means they have their own environment-- >> It's completely secure for their data. >> Vikram: Exactly. >> No multi tenant issues at all. >> No, and you can have either partial capabilities in our data center, or you can fully host in our data center. So you can do various permutation and combinations thus giving customers a lot of flexibility of starting with one point and moving to the other. Let's them start with a private cloud, they want to move to a hybrid version they can move that, or if they start from the hybrid and they want to go back to their own data centers they can do that as well. >> Let's change gears and talk about IoT. You guys had launched Project Nautilus, we also heard that from your boss earlier, two days ago. What is that about? Explain, specifically, what is Project Nautilus? >> So as I was mentioning earlier there is a whole universe of data that is now being generated by these IoT devices. Whether you're talking about connected cars, you're talking about wind sensors, you're talking about anything that collects a piece of data that needs to be not only stored but people want to do realtime analysis on that dataset. And today people end up using a combination of 10 different things. They're using Kafka, Speak, HDFS, Cassandra, DASH storage to build together a makeshift solution, that sort of works but doesn't really. Or you end up, like, if you're in the public cloud you'll end up using some implementation of Lambda Architecture. But the challenge there is you're storing same amount of data in a few different places, and not only that there is no consistent way of managing data, processing data that effectively. So what Project Nautilus is our attempt to essentially streamline all of that. Allow stream of data that's coming from these IoT devices to be processed realtime, or for batch, in the same solution. And then once you've done that processing you essentially push that data down to a tier, whether it's Isilon or ECS, depending on the use case that you are trying to do. So it simplifies the whole story on realtime analytics and you don't want to do it in a closed source way. What we've done is we've created this new paradigm, or new primitive called streaming storage, and we are open sourcing it, we are Project Pravega, which is in the Apache Foundation. We want the whole community, just like there is a common sense of awareness for object file we want to that same thing for streaming storage-- >> So you guys are active in open source. Explain quickly, many might not know that. Talk about that. >> So, yeah, as I mentioned Project Prevega is something we announced at Flink Forward Conference. It's a streaming storage layer which is completely open source in the Apache Foundation and we just open sourced it today. And giving customers the capability to contribute code to it, take their version, or they can do whatever they want to do, like build additional innovation on top. And the goal is to make streaming storage just like a common paradigm like everything else. And in addition we're partnering with another open source component. There is a company called data Artisans based out of Berlin, Germany, and they have a project called Flink, and we're working with them pretty closely to bring Nautilus to fruition. >> theCUBE was there by the way, we covered Flink Forward again, one of the-- >> Paul: True streaming engine. >> Very good, very big open source project. >> Yeah, we we're talking with Jeff Woodrow earlier about software defined storage, self driving storage as he calls it. >> Where does ECS fit in the self driving storage? Is this an important part of what you're doing right now or is it a different use? >> Yeah, our vision right from the beginning itself was when we built this next generation of object storage system it has to be software first. Not only software first where a customer can choose their commodity hardware to bring to bear or we an supply the commodity hardware but over time build intelligence in that layer of software so that you can pull data off smartly to other, from SSDs to more SATA based drives. Or you can bring in smarts around metadata search capabilities that we've introduced recently. Because you have now billions of billions of records that are being stored on ECS. You want ease of search of what specifically you're looking for, so we introduced metadata search capability. So making the storage system and all of the data services that were usually outside of the platform, making them be part of the code platform itself. >> Are you working with Elasticsearch? >> Yes, we are using Elasticsearch more to enable customers who want to get insights about ECS itself. And Nautilus, of course, is also going to integrate with Elasticsearch as well. >> Vikram let's wrap this up. Thank you for coming on theCUBE. Bottom line, what's the bottom line message, quickly, summarize the value proposition, why customers should be using ECS, what's the big aha moment, what's the proposition? >> I would say the value proposition is very simple. Sometimes it can be like, people talk about lots of complex terms, it's very simple. Sustainably, low cost storage, for storing a wide variety of content in a global content repository is the key value proposition. >> And used for application developers to tap into? The whole dev ops, data as code, infrastructure as code movement. >> Yeah, you start, what we have seen in the majority of the used cases customers start with one used case of archiving. And then they very quickly realize that there's, it's like a Swiss Army knife. You start with archiving then you move on to application development, more modern applications, or in the cloud native applications development. And now with IoT and Nautilus being able to leverage data from these IoT devices onto these-- >> As I said two days ago, I think this is a huge, important area for agile developers. Having access to data in less than a hundred milliseconds, from any place in the world, is going to be table steaks. >> ECS has to be, or in general, object storage, has to be part of every important conversation that is happening about digital IT transformation. >> It sounds like eventually most of the data's going to end up there. >> Absolutely. >> Okay, so I'll put ya on the spot. When are we going to be seeing data in less than a hundred milliseconds from any database anywhere in the fabric of a company for a developer to call a data ocean and give me data back from any database, from any transaction in less than a hundred milliseconds? Can we do that today? >> We can do that today, it's available today. The challenge is how quickly enterprises are adopting the technology. >> John: So they got to architect it? >> Yeah. >> They have to architect it. >> Paul: If it's all of Isilon. >> They can pull it, they can cloud pull it down from Isilon to ECS. >> True. >> Yeah. >> Speed, low latency, is the key to success. Congratulations. >> Thank you so much. >> And I love this new object store, love this tier two value proposition. It's so much more compelling for developers, certainly in cloud native. >> Vikram: Absolutely. >> Vikram, here on theCUBE, bringing you more action from Las Vegas. We'll be right back as day three coverage continues here at Dell EMC World 2017. I'm John Furrier with Paul Gillan, we'll be right back.

(Rhythm music) >> Narrator: Live, from Munich, Germany, it's The Cube. Coverage, DataWorks Summit Europe, 2017. Brought to you by Hortonworks. >> Okay, welcome back everyone. We are live in Munich, Germany for DataWorks 2017, formally known as Hadoop Summit. This is The Cube special coverage of the Big Data world. I'm John Furrier my co-host Dave Vallente. Two days of live coverage, day one wrapping up. Now, Dave, we're just kind of reviewing the scene here. First of all, Europe is a different vibe. But the game is still the same. It's about Big Data evolving from Hadoop to full open source penetration. Puppy's now public in markets Hortonworks, Cloudera is now filing an S-1, Neosoft, Talon, variety of the other public companies. Alteryx. Hadoop is not dead, it's not dying. It certainly is going to have a position in the industry, but the Big Data conversation is front and center. And one thing that's striking to me is that in Europe, more than in the North America, is IOT is more centrally themed in this event. Europe is on the Internet of Things because of the manufacturing, smart cities. So this is a lot of IOT happening here, and I think this is a big discovery certainly, Hortonworks event is much more of a community event than Strata Hadoop. Which is much more about making money and modernization. This show's got a lot more engagement with real conversations and developers sessions. Very engaging audience. Well, yeah, it's Europe. So you've go a little bit different smaller show than North America but to me, IOT, Internet of Things, is bringing the other cloud world with Big Data. That's the forcing function. And real time data is the center of the action. I think is going to be a continuing theme as we move forward. >> So, in 2010 John, it was all about 'What is Hadoop?' With the middle part of that decade was all about Hadoop's got to go into the enterprise. It's gone mainstream in to the enterprise, and now it's sort of 'what's next?' Same wine new bottle. But I will say this, Hadoop, as you pointed out, is not dead. And I liken it to the early web. Web one dot O it was profound. It was a new paradigm. The profundity of Hadoop was that you could ship five megabytes of code to a petabyte of data. And that was the new model and that's spawned, that's catalyzed the Big Data movement. That is with us now and it's entrenched, and now you're seeing layers of innovation on top of that. >> Yeah, and I would just reiterate and reinforce that point by saying that Cloudera, the founders of this industry if you will, with Hadoop the first company to be commercially funded to do what Hortonworks came in after the fact out of Yahoo, came out of a web-scale world. So you have the cloud native DevOps culture, Amar Ujala's at Yahoo, Mike Olson, Jeff Hammerbacher, Christopher Vercelli. These guys were hardcore large-scale data guys. Again, this is the continuation of the evolution, and I think nothing is changed it that regard because those pioneers have set the stage for now the commercialization and now the conversation around operationalizing this cloud is big. And having Alan Nance, a practitioner, rock-star, talking about radical deployments that can drop a billion dollars at a cost savings to the bottom line. This is the kind of conversations we're going to see more of this is going to change the game from, you know, "Hey, I'm the CFO buyer" or "CIO doing IT", to an operational CEO, chief operating officer level conversation. That operational model of cloud is now coming into the view what ERP did in software, those kinds of megatrends, this is happening right now. >> As we talk about the open, the people who are going to make the real money on Big Data are the practitioners, those people applying it. We talked about Alan Nance's example of billion dollar, half a billion dollar cost-savings revenue opportunities, that's where the money's being made. It's not being made, yet anyway with these public companies. You're seeing it Splunk, Tableau, now Cloudera, Hortonworks, MapR. Is MapR even here? >> Haven't seen 'em. >> No I haven't seen MapR, they used to have pretty prominent display at the show. >> You brought up point I want to get back to. This relates to those guys, which is, profitless prosperity. >> Yeah. >> A term used for open source. I think there's a trend happening and I can't put a finger on it but I can kind of feel it. That is the ecosystems of open source are now going to a dimension where they're not yet valued in the classic sense. Most people that build platforms value ecosystems, that's where developers came from. Developer ecosystems fuel open source. But if you look at enterprise, at transformations over the decades, you'd see the successful companies have ecosystems of channel partners; ecosystems of indirect sales if you will. We're seeing the formation, at least I can start seeing the formation of an indirect engine of value creation, vis-à-vis this organic developer community where the people are building businesses and companies. Shaun Connolly pointed to Thintech as an example. Where these startups became financial services businesses that became Thintech suppliers, the banks. They're not in the banking business per se, but they're becoming as important as banks 'cuz they're the providers in Thintech, Thintech being financial tech. So you're starting to see this ecosystem of not "channel partners", resell my equipment or software in the classic sense as we know them as they're called channel partners. But if this continues to develop, the thousand flower blooming strategy, you could argue that Hortonworks is undervalued as a company because they're not realizing those gains yet or those gains can't be measured. So if you're an MBA or an investment banker, you've got to be looking at the market saying, "wow, is there a net-present value to an ecosystem?" It begs the question Dave. >> Dave: It's a great question John. >> This is a wealth creation. A rising tide floats all boats, in that rising tide is a ecosystem value number there. No one has their hands on that, no one's talked about that. That is the upshot in my mind, the silver-lining to what some are saying is the consolidation of Hadoop. Some are saying Cloudera is going to get a huge haircut off their four point one billion dollar value. >> Dave: I think that's inevitable. >> Which is some say, they may lose two to three billion in value, in the IPO. Post IPO which would put them in line with Hortonworks based on the numbers. You know, is that good or bad? I don't think it's bad because the value shifts to the ecosystem. Both Cloudera and Hortonworks both play in open source so you can be glass half-full on one hand, on the haircut, upcoming for Cloudera, two saying "No, the glass is half-full because it's a haircut in the short-term maybe", if that happens. I mean some said Pure Storage was going to get a haircut, they never really did Dave. So, again, no one yet has pegged the valuation of an ecosystem. >> Well, and I think that is a great point, personally I think, I've been sort of racking my brain, will this Big Data hike be realized. Like the internet. You remember the internet hyped up, then it crashed; no one wanted to own any of these companies. But it actually lived up to the hype. It actually exceeded the hype. >> You can get pet food online now, it's called amazon. [Co-Hosts Chuckle Together] All the e-commerce played out. >> Right, e-commerce played out. But I think you're right. But everybody's expecting sort of, was expecting a similar type of cycle. "Oh, this will replace that." And that's now what's going to happen. What's going to happen is the ecosystem is going to create a flywheel effect, is really what you're saying. >> Jeff: Yes. >> And there will be huge valuations that emerge out of this. But today, the guys that we know and love, the Hortonworks, the Clouderas, et cetera, aren't really on the winners list, I mean some of their founders maybe are. But who are the winners? Maybe the customers because they saw a big drop in cost. Apache's a big winner here. Wouldn't ya say? >> Yeah. >> Apache's looking pretty good, Apache Foundation. I would say AWS is a pretty big winner. They're drifting off of this. How about Microsoft and IBM? I mean I feel in a way IBM is sort of co-opted this Big Data meme, and said, "okay, cognitive." And layered all of it's stuff on top of it. Bought the weather company, repositioned the company, now it hasn't translated in to growth, but certainly has profitability implications. >> IBM plays well here, I'll tell you why. They're very big in open source, so that's positive. Two, they have huge track record and staff dealing with professional services in the enterprise. So if transformation is the journey conversation, IBM's right there. You can't ignore IBM on this one. Now, the stack might be different, but again, beauty is in the eye of the beholder because depending on what work clothes you have it depends. IBM is not going to leave you high and dry 'cuz they have a really you need for what they can do with their customers. Where people are going to get blindsided in my opinion, the IBMs and Oracles of the world, and even Microsoft, is what Alan Nance was talking about, the radical transformation around the operating model is going to force people to figure out when to start cannibalizing their own stacks. That's going to be a tell sign for winners and losers in the big game. Because if IBM can shift quickly and co-op the megatrends, make it their own, get out in front of that next wave as Pat Gelsinger would say, they could surf that wave and then tweak, and then get out in front. If they don't get behind that next wave, they're driftwood. It really is all about where you are in the spectrum, and analytics is one of those things in data where, you've got to have a cohesive horizontal strategy. You got to be horizontally scalable with data. You got to make data freely available. You have to have an abstraction layer of software that will allow free movement of data, across systems. That's the number one thing that comes out of seeing the Hortonwork's data platform for instance. Shaun Connolly called it 'connective tissue'. Cloudera is the same thing, they have to start figuring out ways to be better at the data across the horizontal view. Cloudera like IBM has an opportunity as well, to get out in front of the next wave. I think you can see that with AI and machine learning, clearly they're going to go after that. >> Just to finish off on the winners and losers; I mean, the other winner is systems integrators to service these companies. But I like what you said about cannibalizing stacks as an indicator of what's happening. So let's talk about that. Oracle clearly cannibalizing it's stacks, saying, "okay, we're going to the red stack to the cloud, go." Microsoft has made that decision to do that. IBM? To a large degree is cannibalizing it's stack. HP sold off it's stack, said, "we don't want to cannibalize our stack, we want to sell and try to retool." >> So, your question, your point? >> So, haven't they already begun to do that, the big legacy companies? >> They're doing their tweaking the collet and mog, as an example. At Oracle Open World and IBM Interconnect, all the shows we, except for Amazon, 'cuz they're pure cloud. All are taking the unique differentiation approach to their own stuff. IBM is putting stuff that's relate to IBM in their cloud. Oracle differentiates on their stack, for instance, I have no problem with Oracle because they have a huge database business. And, you're high as a kite if you think Oracle's going to lose that database business when data is the number one asset in the world. What Oracle's doing which I think is quite brilliant on Oracle's part is saying, "hey, if you want to run on premise with hardware, we got Sun, and oh by the way, our database is the fastest on our stuff." Check. Win. "Oh you want to move to the cloud? Come to the Oracle cloud, our database runs the fastest in our cloud", which is their stuff in the cloud. So if you're an Oracle customer you just can't lose there. So they created an inimitability around their own database. So does that mean they're going to win the new database war? Maybe not, but they can coexist as a system of records so that's a win. Microsoft Office 365, tightly coupling that with Azure is a brilliant move. Why wouldn't they do that? They're going to migrate their customer base to their own clouds. Oracle and Microsoft are going to migrate their customers to their own cloud. Differentiate and give their customers a gateway to the cloud. VVMware is partnering with Amazon. Brilliant move and they just sold vCloud Air which we reported at Silicon Angle last night, to a French company recently so vCloud Air is gone. Now that puts the VMware clearly in bed with Amazon web services. Great move for VMware, benefit to AWS, that's a differentiation for VMware. >> Dave: Somebody bought vCloud Air? >> I think you missed that last night 'cuz you were traveling. >> Chuckling: That's tongue-in-cheek, I mean what did they get for vCloud Air? >> OVH bought them, French company. >> More de-levering by Michael. >> Well, they're inter-clouding right? I mean de-leveraging the focus, right? So OVH, French company, has a very much coexisted... >> What'd they pay? >> ... strategy. It's undisclosed. >> Yeah, well why? 'Cuz it wasn't a big number. That's my point. >> Back to the other cloud players, Google. I think Google's differentiating on their technology. Great move, smart move. They just got to get, as someone who's been following them, and you know, you and I both love an enterprise experience. They got to speak the enterprise language and execute the language. Not through 19 year olds and interns or recent smart college grads ad and say, "we're instantly enterprise." There's a dis-economies of scale for trying to ramp up and trying to be too heavy on the enterprise. Amazon's got the same problem, you can't hire sales guy fast enough, and oh by the way, find me a sales guy that has ten 15 years executive selling experience to a complex strategic sales, like the enterprise where you now have stakeholders that are in multiple roles and changing roles as Alan Nance pointed out. So the enterprise game is very difficult. >> Yup. >> Very very difficult. >> Well, I think these dupe startups are seeing that. None of them are making money. Shaun Connolly basically said, "hey, it used to be growth they would pay for growth, but now their punishing you if you don't have growth plus profitability." By the way, that's not all totally true. Amazon makes no money, unless stock prices go through the roof. >> There is no self-service, there is no self-service business model for digital transformation for enterprise customers today. It doesn't exist. The value proposition doesn't resinate with customers. It works good for Shadow IT, and if you want to roll out G Suite in some pockets of your organization, but an ad-sense sales force doesn't work in the enterprise. Everyone's finding that out right now because they're basically transforming their enterprise. >> I think Google's going to solve their problem. I think Google has to solve their problem 'cuz... >> I think they will, but to me it's, buy a company, there's a zillion company out there they could buy tomorrow that are private, that have like 300 sales people that are senior people. Pay the bucks, buy a sales force, roll your stuff out and start speaking the language. I think Dianne Green gets this. So, I think, I expect to see Google ... >> Dave: Totally. >> do some things in that area. >> And I think, to you're point, I've always said the rich get richer. The traditional legacy companies, they're holding servant in this. They waited they waited they waited, and they said, "okay now we're going to go put our chips on the table." Oracle made it's bets. IBM made it's bets. HP, not really, betting on hardware. Okay. Fine. Cisco, Microsoft, they're all making their bets. >> It's all about bets on technology and profitability. This is what I'm looking at right now Dave. We talked about it on our intro. Shaun Connolly who's in charge of strategy at Hortonworks clarified it that clearly revenue, losing money is not going to solve the problem for credibility. Profitability matters. This comes back to the point we've said on The Cube multiple years ago and even just as recently as last year, that the world's flipping back down to credibility. Customers in the enterprise want to see credibility and track record. And they're going to evaluate the suppliers based upon key fundamentals in their business. Can they make money? Can they deliver SLAs? These are going to be key requirements, not the shiny new toy from Silicon Valley. Or the cool machine learning algorithm. It has to apply to their product, their value, and they're going to look to companies on the scoreboard and say, "are you profitable?" As a proxy for relevance. >> Well I want to keep it, but I do want to, we've been kind of critical of some of the Hadoop players. Cloudera and Hortonworks specifically. But I want to give them props 'cuz you remember well John, when the legacy enterprise guys started coming into the Hadoop market they all said that they had the same messaging, "we're going to make Hadoop enterprise ready." You remember that well, and I have to say that Hortonworks, Cloudera, I would say MapR as well and the ecosystem, have done a pretty good job of making Hadoop and Big Data enterprise ready. They were already working on it very hard, I think they took it seriously and I think that that's why they are in the mix and they are growing as they are. Shaun Connolly talked about them being operating cashflow positive. Eking out some plus cash. On the next earnings call, pressures on. But we want to see, you know, rocket ships. >> I think they've done a good job, I mean, I don't think anyone's been asleep at the switch. At all, enterprise ready. The questions always been "can they get there fast enough?" I think everyone's recognized that cost of ownership's down. We still solicit on the OpenStack ecosystem, and that they move right from the valley properties. So we'll keep an eye on it, tomorrow we'll be checking in. We got a great day tomorrow. Live coverage here in Munich, Germany for DataWorks 2017. More coverage tomorrow, stay with us. I'm John Furrier with Dave Vallente. Be right back with more tomorrow, day two. Keep following us.

>> Narrator: Live from New York, it's the CUBE from Big Data New York City 2016. Brought to you by headline sponsors, Cisco, IBM, Nvidia. And our ecosystem sponsors. Now, here are your hosts: Dave Vellante and Peter Burris. >> Welcome back to New York City, everybody. This is the CUBE, the worldwide leader in live tech coverage. Holden Karau is here, principle software engineer with IBM. Welcome to the CUBE. >> Thank you for having me. It's nice to be back. >> So, what's with Boo? >> So, Boo is my stuffed dog that I bring-- >> You've got to hold Boo up. >> Okay, yeah. >> Can't see Boo. >> So, this is Boo. Boo comes with me to all of my conferences in case I get stressed out. And she also hangs out normally on the podium while I'm giving the talk as well, just in case people get bored. You know, they can look at Boo. >> So, Boo is not some new open source project. >> No, no, Boo is not an open source project. But Boo is really cute. So, that counts for something. >> All right, so, what's new in your world of spark and machinery? >> So, there's a lot of really exciting things, right. Spark 2.0.0 came out, and that's really exciting because we finally got to get rid of some of the chunkier APIs. And data sets are just becoming sort of the core base of everything going forward in Spark. This is bringing the Spark Sequel engine to all sorts of places, right. So, the machine learning APIs are built on top of the data set API now. The streaming APIs are being built on top of the data set APIs. And this is starting to actually make it a lot easier for people to work together, I think. And that's one of the things that I really enjoy is when we can have people from different sort of profiles or roles work together. And so this support of data sets being everywhere in Spark now lets people with more of like a Sequel background still write stuff that's going to be used directly in sort of a production pipeline. And the engineers can build whatever, you know, production ready stuff they need on top of the Sequel expressions from the analysts and do some really cool stuff there. >> So, chunky API, what does that mean to a layperson? >> Sure, um, it means like, for example, there's this thing in Spark where one of the things you want to do is shuffle a whole bunch of data around and then look at all of the records associated with a given key, right? But, you know, when the APIs were first made, right, it was made by university students. Very smart university students, but you know, it started out as like a grad school project, right? And like, um, so finally with 2.0, we were about to get rid of things like places where we use traits like iterables rather than iterators. And because like these minor little drunky things it's like we had to keep supporting this old API, because you can't break people's code in a minor release, but when you do a big release like Spark 2.0, you can actually go, okay, you need to change your stuff now to start using Spark 2.0. But as a result of changing that in this one place, we're actually able to better support spilling to disk. And this is for people who have too much data to fit in memory even on the individual executors. So, being able to spill to disk more effectively is really important from a performance point of view. So, there's a lot of clean up of getting rid of things, which were sort of holding us back performance-wise. >> So, the value is there. Enough value to break the-- >> Yeah, enough value to break the APIs. And 1.6 will continue to be updated for people that are not ready to migrate right today. But for the people that are looking at it, it's definitely worth it, right? You get a bunch of real cool optimizations. >> One of the themes of this event of the last couple of years has been complexity. You guys wrote an article recently in SiliconANGLE some of the broken promises of open source, really the route of it, being complexity. So, Spark addresses that to a large degree. >> I think so. >> Maybe you could talk about that and explain to us sort of how and what the impact could be for businesses. >> So, I think Spark does a really good job of being really user-friendly, right? It has a Sequel engine for people that aren't comfortable with writing, you know, Scala or Java or Python code. But then on top of that, right, there's a lot of analysts that are really familiar with Python. And Spark actually exposes Python APIs and is working on exposing R APIs. And this is making it so that if you're working on Spark, you don't have to understand the internals in a lot of depth, right? There's some other streaming systems where to make them perform really well, you have to have a really deep mental model of what you're doing. But with Spark, it's much simpler and the APIs are cleaner, and they're exposed in the ways that people are already used to working with their data. And because it's exposed in ways that people are used to working with their data, they don't have to relearn large amounts of complexity. They just have to learn it in the few cases where they run into problems, right? Because it will work most of the time just with the sort of techniques that they're used to doing. So, I think that it's really cool. Especially structured streaming, which is new in Spark 2.0. And structured streaming makes it so that you can write sort of arbitrary Sequel expressions on streaming data, which is really awesome. Like, you can do aggregations without having to sit around and think about how to effectively do an aggregation over different microbatches. That's not a problem for you to worry about. That's a problem for the Spark developers to worry about. Which, unfortunately, is sometimes a problem for me to worry about, but you know, not too often. Boo helps out whenever it gets too stressful. >> First of all, a lot to learn. But there's been some great research done in places like Cornell and Penn and others about how the open source community collaborates and works together. And I'm wondering is the open source community that's building things like Spark, especially in a domain like Big Data, which the use cases themselves are so complex and so important. Are we starting to take some of the knowledge in the contributors, or developing, on how to collaborate and how to work together. And starting to find that way into the tools so that the whole thing starts to collaborate better? >> Yeah, I think, actually, if you look at Spark, you can see that there's a lot of sort of tools that are being built on top of Spark, which are also being built in similar models. I mean, the Apache Software Foundation is a really good tool for managing projects of a certain scale. You can see a lot of Spark-related projects that have also decided that become part of Apache Foundation is a good way to manage their governance and collaborate with different people. But then there's people that look at Spark and go like wow, there's a lot of overhead here. I don't think I'm going to have 500 people working on this project. I'm going to go and model my project after something a bit simpler, right? And I think that both of those are really valid ways of building open source tools on Spark. But it's really interesting seeing there's a Spark components page, essentially, a Spark packages list, for community to publish the work that they're doing on top of Spark. And it's really interesting to see all of the collaborations that are happening there. Especially even between vendors sometimes. You'll see people make tools, which help everyone's data access go faster. And it's open source. so you'll see it start to get contributed into other people's data access layers as well. >> So, pedagogy of how the open source community's work starting to find a way into the tools, so people who aren't in the community, but are focused on the outcomes are now able to not only gain the experience about how the big data works, but also how people on complex outcomes need to work. >> I think that's definitely happening. And you can see that a lot with, like, the collaboration layers that different people are building on top of Spark, like the different notebook solutions, are all very focused on ableing collaboration, right? Because if you're an analyst and you're writing some python code on your local machine, you're not going to, like, probably set up a get up recode to share that with everyone, right? But if you have a notebook and you can just send the link to your friends and be like hey, what's up, can you take a look at this? You can share your results more easily and you can also work together a lot more, more collaboratively. And then so data bricks is doing some great things. IBM as well. I'm sure there's other companies building great notebook solutions who I'm forgetting. But the notebooks, I think, are really empowering people to collaborate in ways that we haven't traditionally seen in the big data space before. >> So, collaboration, to stay on that theme. So, we had eight data scientists on a panel the other night and just talking about, collaboration came up, and the question is specifically from an application developer standpoint. As data becomes, you know, the new development kit, how much of a data scientist do you have to become or are you becoming as a developer? >> Right, so, my role is very different, right? Because I focus just on tools, mostly. So, my data science is mostly to make sure that what I'm doing is actually useful to other people. Because a lot of the people that consume my stuff are data scientists. So, for me, personally, like the answer is not a whole lot. But for a lot of my friends that are working in more traditional sort of data engineering roles where they're empowering specific use cases, they find themselves either working really closely with data scientists often to be like, okay, what are your requirements? What data do I need to be able to get to you so you can do your job? And, you know, sometimes if they find themselves blocking on the data scientists, they're like, how hard could it be? And it turns out, you know, statistics is actually pretty complicated. But sometimes, you know, they go ahead and pick up some of the tools on their own. And we get to see really cool things with really, really ugly graphs. 'Cause they do not know how to use graphing libraries. But, you know, it's really exciting. >> Machine learning is another big theme in this conference. Maybe you could share with us your perspectives on ML and what's happening there. >> So, I really thing machine learning is very powerful. And I think machine learning in Spark is also super powerful. And especially just like the traditional things is you down-sample your data. And you train a bunch of your models. And then, eventually, you're like okay, I think this is like the model that I want to like build for real. And then you go and you get your engineer to help you train it on your giant data set. But Spark and the notebooks that are built on top of it actually mean that it's entirely reasonable for data scientists to take the tools which are traditionally used by the data engineering roles, and just start directly applying them during their exploration phase. And so we're seeing a lot of really more interesting models come to life, right? Because if you're always working with down-sampled data, it's okay, right? Like you can do reasonable exploration on down-sampled data. But you can find some really cool sort of features that you wouldn't normally find once you're working with your full data set, right? 'Cause you're just not going to have that show up in your down-sampled data. And I think also streaming machine learning is a really interesting thing, right? Because we see there's a lot of IOT devices and stuff like that. And like the traditional machine learning thing is I'm going to build a model and then I'm going to deploy it. And then like a week later, I'll maybe consider building a new model. And then I'll deploy it. And then so very much it looks like the old software release processes as opposed to the more agile software release processes. And I think that streaming machine learning can look a lot more like, sort of the agile software development processes where it's like cool, I've got a bunch of labeled data from our contractors. I'm going to integrate that right away. And if I don't see any regression on my cross-validation set, we're just going to go ahead and deploy that today. And I think it's really exciting. I'm obviously a little biased, because some of my work right now is on enabling machine learning with structured streaming in Spark. So, I obviously think my work is useful. Otherwise I would be doing something else. But it's entirely possible. You know, everyone will be like Holden, your work is terrible. But I hope not. I hope people find it useful. >> Talking about sampling. In our first at Dupe World 2010, Albi Meta, he stopped by again today, of course, and he made the statement then. Sampling's dead. It's dead. Is sampling dead? >> Sampling didn't quite die. I think we're getting really close to killing sampling. Sampling will only be data once all of the data scientists in the organization have access to the same tools that the data engineers have been using, right? 'Cause otherwise you'll still be sampling. You'll still be implicitly doing your model selection on down-sampled data. And we'll still probably always find an excuse to sample data, because I'm lazy and sometimes I just want to develop on my laptop. But, you know, I think we're getting close to killing a lot more of sampling. >> Do you see an opportunity to start utilizing many of these tools to actually improve the process of building models, finding data sources, identifying individuals that need access to the data? Are we going to start turning big data on the problem of big data? >> No, that's really exciting. And so, okay, so this is something that I find really enjoyable. So, one of the things that traditionally, when everyone's doing their development on their laptop, right? You don't get to collect a lot of metrics about what they're doing, right? But once you start moving everyone into a sort of more integrated notebook environment, you can be like, okay, like, these are data sets that these different people are accessing. Like these are the things that I know about them. And you can actually train a recommendation algorithm on the data sets to recommend other data sets to people. And there are people that are starting to do this. And I think it's really powerful, right? Because it's like in small companies, maybe not super important, right? Because I'll just go an ask my coworker like hey, what data sets do I want to use? But if you're at a company like Google or IBM scale or even like a 500 person company, you're not going to know all of the data sets that are available for you to work with. And the machine will actually be able to make some really interesting recommendations there. >> All right, we have to leave it there. We're out of time. Holden, thanks very much. >> Thank you so much for having me and having Boo. >> Pleasure. All right, any time. Keep right there everybody. We'll be back with our next guest. This is the CUBE. We're live from New York City. We'll be right back.