>> Live, from The Wigwam, in Phoenix, Arizona, it's theCube, covering Data Platforms 2017. Brought to you by Cue Ball. Hey, welcome back everybody. Jeff Frick here with theCube. Welcome back to Data Platforms 2017, at the historic Wigwam Resort, just outside of Phoenix, Arizona. I'm here all day with George Gilbert from Wikibon, and we're excited to be joined by our next guest. He's Mick Bass, the CEO of 47Lining. Mick, welcome. >> Welcome, thanks for having me, yes. >> Absolutely. So, what is 47Lining, for people that aren't familiar? >> Well, you know every cloud has a silver lining, and if you look at the periodic table, 47 is the atomic number for silver. So, we are a consulting services company that helps customers build out data platforms and ongoing data processes and data machines in Amazon web services. And, one of the primary use cases that we help customers with is to establish data lakes in Amazon web services to help them answer some of their most valuable business questions. >> So, there's always this question about own vs buy, right, with Cloud and Amazon, specifically. >> Mm-hmm, mm-hmm. >> And, with a data lake, the perception right... That's huge, this giant cost. Clearly that's from benefits that come with putting your data lake in AWS vs having it on Primm. What are some of the things you take customers through, and kind of the scenario planning and the value planning? >> Well, just a couple of the really important aspects, one, is this notion of elastic and on-demand pricing. In a Cloud based data lake, you can start out with actually a very small infrastructure footprint that's focused on maybe just one or two business use cases. You can pay only for the data that you need to get your data leg bootstrapped, and demonstrate the business benefit from one of those use cases. But, then it's very easy to scale that up, in a pay as you go kind of a way. The second, you know, really important benefit that customers experience in a platform that's built on AWS, is the breadth of the tools and capabilities that they can bring to bare for their predictive analytics and descriptive analytics, and streaming kinds of data problems. So, you need Spark, you can have it. You need Hive, you can have it. You need a high performance, close to the metal, data warehouse, on a cluster database, you can have it. So, analysts are really empowered through this approach because they can choose the right tool for the right job, and reduce the time to business benefit, based on what their business owners are asking them for. >> You touched on something really interesting, which was... So, when a customer is on Primm, and let's say is evaluating Cloudera, MaPr, Hortonworks, there's a finite set of services or software components within that distro. Once they're on the Cloud, there's a thousand times more... As you were saying, you could have one of 27 different data warehouse products, you could have many different sequel products, some of which are really delivered as services. >> Mm-hmm >> How does the consideration of the customer's choice change when they go to the Cloud? >> Well, I think that what they find is that it's much more tenable to take an agile, iterative process, where they're trying to align the outgoing cost of the data lake build to keep that in alignment with the business benefits that come from it. And, so if you recognize the need for a particular kind of analytics approach, but you're not going to need that until down the road, two or three quarters from now. It's easy to get started with simple use cases, and then like add those incremental services, as the need manifests. One of the things that I mention in my talk, that I always encourage our customers to keep in mind, is that a data lake is more than just a technology construct. It's not just an analysis set of machinery, it's really a business construct. Your data lake has a profit and loss statement, and the way that you interact with your business owners to identify this specific value sources, that you're going to make pop for you company, can be made to align with the cost footprint, as you build your data lake out. >> So I'm curious, when you're taking customers though the journey to start kind of thinking of the data lake and AWS, are there any specific kind of application spaces, or vertical spaces where you have pretty high confidence that you can secure an early, and relatively easy, win to help them kind of move down the road? >> Absolutely. So, you know, many of our customers, in a very common, you know, business need, is to enhance the set of information that they have available for a 360 degree view of the customer. In many cases, this information and data, it's available in different parts of the enterprises, but it might be siloed. And, a data lake approach in AWS really helps you to pull it together in an agile fashion based on particular, quarter by quarter, objectives or capabilities that you're trying to respond to. Another very common example is predictive analytics for things like fraud detection, or mechanical failure. So, in eCommerce kinds of situations, being able to pull together semi-structured information that might be coming from web servers or logs, or like what cookies are associated with this particular user. It's very easy to pull together a fraud oriented predictive analytic. And, then the third area that is very common is internet of things use cases. Many enterprises are augmenting their existing data warehouse with sensor oriented time series data, and there's really no place in the enterprise for that data currently to land. >> So, when you say they are augmenting the data warehouse, are they putting it in the data warehouse, or they putting it in a sort of adjunct, time series database, from which they can sort of curate aggregates, and things like that to put in the data warehouse? >> It's very much the latter, right. And, the time series data itself may come from multiple different vendors and the input formats, in which that information lands, can be pretty diverse. And so, it's not really a good fit for a typical kind of data warehouse ingest or intake process. >> So, if you were to look at, sort of, maturity models for the different use cases, where would we be, you know, like IOT, Customer 360, fraud, things like that? >> I think, you know, so many customers have pretty rich fraud analytics capabilities, but some of the pain points that we hear is that it's difficult for them to access the most recent technologies. In some cases the order management systems that those analytics are running on are quite old. We just finished some work with a customer where literally the order management system's running on a mainframe, even today. Those systems have the ability to accept steer from like a sidecar decision support predictive analytic system. And, one of the things that's really cool about the Cloud is you could build a custom API just for that fraud analytics use case so that you can inject exactly the right information that makes it super cheap and easy for the ops team, that's running that mainframe, to consume the fraud improvement decision signal that you're offering. >> Interesting. And so, this may be diving into the weeds a little bit, but if you've got an order management system that's decades old and you're going to plug-in something that has to meet some stringent performance requirements, how do you, sort of, test... It's not just the end to end performance once, but you know for the 99th percentile, that someone doesn't get locked out for five minutes while he's to trying to finish his shopping cart. >> Exactly. And I mean, I think this is what is important about the concept of building data machines, in the Cloud. This is not like a once and done kind of process. You're not building an analytic that produces a print out that an executive is going to look at (laughing) and make a decision. (laughing) You're really creating a process that runs at consumer scale, and you're going to apply all of the same kinds of metrics of percentile performance that you would apply at any kind of large scale consumer delivery system. >> Do you custom-build, a fraud prevention application for each customer? Or, is there a template and then some additional capabilities that you'll learn by running through their training data? >> Well, I think largely, there are business by business distinctions in the approach that these customers take to fraud detection. There's also business by business direction distinction in their current state. But, what we find is that the commonalities in the kinds of patterns and approaches that you tend to apply. So, you know... We may have extra data about you based on your behavior on the web, and your behavior on a mobile app. The particulars of that data might be different for Enterprise A vs Enterprise B, but this pattern of joining up mobile data plus web data plus, maybe, phone-in call center data. Putting those all together, to increase the signal that can be made available to a fraud prevention algorithm, that's very common across all enterprises. And so, one of the roles that we play is to set up the platform, so that it's really easy to mobilize each of these data sources. So in many cases, it's the customer's data scientist that's saying, I think I know how to do a better job for my business. I just need to be unleashed to be able to access this data, and if I'm blocked, I need a platform where the answer that I get back is oh, you could have that, like, second quarter of 2019. Instead, you want to say, oh, we can onboard that data in an agile fashion pay, and increment a little bit of money because you've identified a specific benefit that could be made available by having that data. >> Alright Mick, well thanks for stopping by. I'm going to send Andy Jassy a note that we found the silver lining to the Cloud (laughing) So, I'm excited for that, if nothing else, so that made the trip well worth while, so thanks for taking a few minutes. >> You bet, thanks so much, guys. >> Alright Mick Bass, George Gilbert, Jeff Frick, you're watching theCube, from Data Platforms 2017. We'll be right back after this short break. Thanks for watching. (computer techno beat)

>>From our studios in the heart of Silicon Valley, Palo Alto, California. This is a CUBE conversation >>and welcome back. You're ready. Jeffrey here with the cue. We're in our Palo Alto studio today for a Q conversation that a little bit of a deeper dive into the Cisco cloud center. We've had an ongoing conversation. There's a, a new component today. We're going to do a deep dive, so we're excited to welcome back to the studio. Uh, Kube alumni, uh, Ali G technical leaders software engineering group from Cisco. All great to see you again. Happy to be here. Absolutely. And joining us from New Jersey via the phone is Michael Chenoweth's. He's a technical marketing engineer from Cisco. Michael, great to see you. Hey rich, see you guys. And I hope you'll go get a cheese steak when they're finished and uh, after grad how you can send it to me. I don't know if that's possible, but uh, yeah. Anyway, welcome. Uh, so let's jump into it. So Cisco cloud center we've been talking about for a while, but today we want to dig into a very specific feature and it's a, it goes technically by a O, but that stands for the action orchestrator Ali. What's action orchestrator? >>Well, action orchestration is a component inside our cloud center suite that brings together cross domain orchestration and it's extremely useful because not only is it valuable for dev ops engineers to orchestrate and maintain and automate their infrastructure, but it's also useful for application developers to define workflow and orchestration in their products as well. So this tool, um, is heavily used throughout the stock, inside the cloud, at the application level, all the way down to the intro level as well. And um, uh, it's made it extremely easy for DevOps engineers to get their hands on the fining workflows and, uh, conditions and logics where they can create, maintain all the appropriate infrastructure that they need. Works very well hand to hand with the current, uh, technology out there like Terraform or Ansible. And, um, it's part of our CloudCenter suites. Huh. >>And is it more on the config side or is it more on kind of the operational workflow side? Correct. >>So it could be used for both. Right. It's so flexible in a matter of, I'm this abstraction of having the orchestration engine outside, uh, enables both developers and dev ops engineers to illustrate and create their workflows. Um, uh, rather, it's again, based on infrastructure or, uh, even networking layers or all the way up the side to the application where if your product requires an orchestration engine in the backend to process work, this, uh, this component definitely plays a big role. Right? So, >>okay, Michael, throw it over to you. >>Yeah, so I think everything that a Ali is saying is absolutely correct. Um, the nice part about it is it's, it's, >>you know, >>it's a product that can really do whatever you imagined. So, I mean, we've seen people use it for business process, for a automation of network, server, cloud, whatever you can think of. It's, it's, um, you know, it's extensible. We're gonna talk about that in a little bit. But really the, the nice part about it is you create the workflows and you designed the way that you want to go. And what I have here, if you could show the next, uh, video is just a little clip of what it would look like to go through a workup. Well, okay, so let's go queue that up and we'll uh, we'll take a walk for it. Let's go to the video number one guys. All right. So yeah, so if you look here, what we're seeing is we're seeing a pre, a view of what Amazon looked like, a beforehand looking at VPCs and subnets. >>And now what we're doing is going through a workflow that is going to show afterwards that those actual VPCs and subnets were created by using a flow. So we're going to do is just pick one flow here, which is called creative for us. And this is just an example. And what you see on the left hand side is something called actions. So these are all the atomic actions that are available. A, but these are just out of the box. We're adding stuff all the time. And these actions can be dragged over to the right and create workflows. And then just think about it as if it's not there, we can create, you can create them in minutes. And we're going to show you that in a little bit too. So right now what I'm gonna show you is the fact that if you click on each one of these actions, there's actually some kind of uh, information that you'll see on the right hand side. >>And this information is how you and figure that particular action. So this particular one's going to create a VPC and you can see the VPC name, you could see the VPC sub-net, um, and whatever other parameters are needed for that particular action. So not a lot to do. You pretty much select the target. And this one already had a target selected, which is Amazon or AWS. And the second action here, if you look down, actually has a parameter two or a couple parameters and one of those parameters you can see the first one is just the name. The second one though is actually using a variable from the previous step. So really, really easy to map stuff different workflow elements and it allows you to quickly kind of glue things together to make things work. So this is just an example again, very simple example that this is going to create infrastructure on Amazon. >>And you can think about using this as part of the process. Like when you're trying to bring up a cloud environment, maybe you run this first, if you run this to say, Hey, I need some infrastructure for that cloud environment and maybe you even want to execute, um, you know, bringing up certain VMs or containers, you can do that afterwards. But this was just a really, really quick showcase. Oh, a simple thing you can do with very few steps that you can then run and it will actually, we're going to run, hit validate here. It just validates the workflow. But once we click around here, it's actually going to create all of that stuff within Amazon. So in the next, in this step, you're going to see the run. You can see that both steps work because they're green. If they didn't work, they'd be red. >>And we're going to show that in one second. Um, but when you click on a step, it actually shows you the input and output of each one of those steps. So it's really, really cool on that all the information that you could possibly think of that you'll need to, to troubleshoot, to look at these things is available in the workflow by just clicking on each one of these steps and seeing what that input and output. So if you can imagine if you had an error there, uh, you could quickly figure out what that is. It would tell you the error, it would tell you what's going on, or if you needed information from a step before you can run it, get the information from the step before and then figure out what values you need for the next step. So really, really cool in that you could look at this workflow, you get all the information you need and it allows you to create these workflows and kind of glue them together really, really quick. >>Uh, and now what I'm going to show you, I believe is in the next part here. I'm just going to illustrate that. If you go over to the runs that we have here, it'll actually keep a list of all of the different runs we did. And you could see one is in red. Well that one in red means that a step didn't work well. Let's click on that step and figure out, Hey, why didn't this step work? Well, this step didn't work because of an error that we got. And if we scroll down to the bottom over here, what we're going to see is the actual error that are had had occurred within this step. So now we know exactly what the problem was and we can fix it within the next step. So in this particular one, um, we, we illustrated right there, uh, that there was some problem with, uh, I think a VPC, um, or the way that I, I sorry, the way that I phrase that VPC or that's something that I'm sorry. >>And uh, it, it, it positive problem, but I fixed it within the next step in. Now you can see that in these declare two screens that the VPC and the sudden that was created automatically within that workflow. Pretty cool. So what, what would they have done to accomplish that in the past? So there'll come a sound the past, and this is the real thing that, that we see. We see that people have all these tools all over the place. Those tools might be, you know, things that are uh, orchestration engines, you know, other products that it might be things, uh, that, uh, they run from the command line, uh, which are, you know, work great together. But what we find is that, you know, there's no central orchestration and when we want to provide is that central orchestration that can run those other tools and also schedule them together. >>So if you use a, if you use other tools besides a AAO, that's fine. We're happy to bring them in. And we could, you could use the valuables, you could use everything that's, that you still use. Okay, now you have all the integration, you have all the variables, you have all the workflow. And not only just for Mayo but from workload manager too. So if you bring up a VM and and bring up a container, you get that information. So there's just a lot of uh, you know, tooling inside that allows you to really take advantage of them. Everything you might already even have. >>Yeah, correct. I mean that was a good demo. And, uh, one of the things I like to point out here is that compared to some of the competitors that are out there with this orchestration engine, uh, I don't want to name anyone particular, but if you look at it, the schema that Michael just showed us in that demo is Jason Bass versus others out. There are some still in XML. The other very beneficial to this is that since this is a component of our cloud center suite, it also gets installed on prem. And what that means is footprint is extremely important when it comes to OnPrem especially. And, uh, with the technology and the cloud native solutions that you know, the team has done inside Cisco, our footprint is very small, uh, due to the technology choices that we use. And writing our services and go and et cetera versus outside competitors are doing it in Java, which have a much more larger footprint on, you know, the infrastructure that clients and customers get to insult. >>So there are a lot of features, uh, with this orchestration engine, uh, that comes when it, uh, when we're trying to compare them with the market and the competitors that are out there. Conditional logic in what Michael just showed us inside the workflows, right. It makes it super simple for someone who has not had any experience coding to put together their workflows and introduced conditions, um, either for loops or if L statements are conditional blocks, whereas in the competitors you have to know a certain amount of programming skills in order for you to do those conditionings. So I feel that that's a great advantage that we have here. So, >>and so do you does a lot of things come packaged out of the box kind of standard processes, standard standard workflows and our processes. Yup. And then what do they coat it in then? If, if, if it is a, a custom workflow that you don't have, how do they go in and manipulate the tool? >>Good question. Because I'm like I mentioned, right? The competitors, you would have to know a certain language in order for you to code those, a logical flows that you want inside your orchestration, right? Inside EO, it's all driven by the DSL, which is all Jason base, right? And the GSL, the DSLR is so powerful that you can introduce if an ELs conditions, you don't have to know a language per se, right? It's just you define your logic, right. And um, the tool actually allows you to provide those flows, those if conditions of the loops, uh, that are required and also defaulting onto fallbacks or etc. So, right. >>I think Becca, you're going to show us a little bit more that, uh, >>yeah, I think that's, that's absolutely key is that, you know, what we're talking about is extensibility here. So the extensibility is, is one thing that we kind of tell because you don't need to be a programmer, but we live in an API world. So we need a way to consume these API. How do we do that in, and you know, companies and businesses that think developer is expensive and it's very hard to get into. So we're trying to take that out of that and say, Hey, we have this engine. So let's take a look at some of that extensibility on the next video that I have here. >>Okay. Pulling that up. So what you're seeing here, uh, is, uh, postmaster. So this is a regular tool that a lot of people use. And what I'm showing is just appall, which is, which is in boost Matt. And this particular call just gets a Smartsheet. So this gets a Smartsheet, uh, from Smartsheets and it just lists what Smartsheets are available and yeah, in a, Oh, I want to be able to create this. And if we look at the time, or I'm doing this in less than five minutes, so I have no calls for Smartsheets, but I want to create a call. So what I did is I created a target for Smartsheets that's an HTTP target. And what that means is that I can connect to Smartsheets and if you look at the bottom, I list the API a address and I list the default path. >>So you don't have to enter that path a million times. So we know that API slash 2.0 is the path that we're always going to use. On top of that, there's always some other kind of, uh, element to that path that you know we're going to need in each particular action that we want to call. So what I'm going to do here is showcase what I did. So in this first step, what I've done is I actually did a generic HTTP requests. So no programming needed. All I had to do is use a URL. People have used the worldwide web, they know how to use URLs. And this one, the cause slash sheets doesn't take a lot of, you know, um, it doesn't take a brain surgeon to figure this out. So ah, really I did slash sheets is, is what I'm calling. And um, you know, I'm using the target and then the next step when I'm doing is I'm setting up a variable that's going to be my output variables. >>So what am I gonna call this? Maybe I'll call it sheets. And really all I'm doing is just setting this up and saying that we are going to call this Sheetz going out of it. And that's about it. So what I've done within a couple minutes is created a new action that's going to be shown on the left hand side. So now you can think of a reusable element. And what I'm showcasing here is I'm actually gonna turn it off and turn it back on just to showcase. But there's something called atomic actions. So I'm just validating that this is running. I'm going to take a look at the atomic action. I'm going to give it a category. So I'm going to put this, the Smartsheet category. So if you could imagine I had a lot of these, a Smartsheet actions, I could just put them all into one category. >>We'll find them on the left hand side, but I'm just going to validate that the atomic action is good. And now what I'm going to show you is that when I call up a new workflow, I can just drag that right from the left hand side and it'll be under smart sheets. It'll be under, you know, get those lists are uh, Smartsheet, um, lists Smartsheets and what it's going to ask for. Now as a token, because you need a token in order to, uh, authenticate with Smartsheet. That's a Smartsheet requirement. So what I'm gonna do is just go over to postman and uh, grabbed that token real quick and um, and then come back over to this page and enter that token in. So, uh, the, the first thing I gonna do is create an input variable and that input variable is going to ask for a token. >>So what that does is it, when I run this in this particular workflow, I could ask for an input variable. And that means every time it runs, it's going to pop up with that variable right now where you're seen as an associate in that variable that I created with that token parameter. And this is a secure string so you can never see what that string is. It's hidden, it's a, you know, it's a, it's made so that it's, it's not ever seen. And um, so now if I run the run, you'll see it asks for a token. Now is actually when I'm going to go over to postman. I'm going to grab that to again a, so you'll see I'm going into postman and post again is just what we use to test these calls. A lot of people use it. It's very industry standard. >>Uh, and I'm just grabbing the token from here. Uh, it's blurred out so that, so that though public can't see it. But I grabbed it and then we'll go back out into here and I hit run and you'll see that I created that action. I brought the accidents who workflow, I ran it, it's running and now it's giving me that exact same output that I would've gotten in postman. But now it's a reusable element. So this just illustrates the extensibility that's available within our product. Again, when we took a couple of minutes and I have an action that I might've needed that wasn't available in this tool, but it was created and it, uh, you know, it works out in the box now, so >>very slick. And so that was with, uh, with Smartsheets, how many connectors do you guys already have pre constructed? >>There are so many. I mean, you know, I don't want to list a lot of different vendors, but you could imagine every dev ops tool is in there. Um, there are connections to Amazon, to Google too, uh, to Coopernetties, to, um, to internally through ACI, through Muraki, through a lot of the Cisco ecosystem. So really there's, there's just a lot available, uh, and it's growing. It's grown tremendously and we're building communities and we just want people to try it, use it, I think really like it. Once they see what it can do. >>Yeah. And I'm just curious all, is this something that then that people are going to be working on all the time or these pretty much, you know, you set your configs and go, go back to work, you set these relationships and go back to work or is this, this is not your work screen, >>this is, I mean, how cool was that, right? Creating those atomic actions and being able to templatize those and, and, and building those building blocks like Lego, right, that in the future you can just build more and more out of and just either add to the complexity without it being complex at all. Right. Um, but going back to your question is a lot of these toolings that are built, um, with EO, the, uh, one of the other advantages that we see that unfortunately some of the competitors don't have outside, um, is that you have the ability of, for different types of events that inside AOL is supportive. So, you know, you as dev ops engineers, they tied them up to scheduling, they tied them up to events coming in from a message queue. So these are workflows that are created get, uh, triggered by these events, which, uh, you know, makes it possible for them to execute at a certain time or for a certain event that gets triggered. Right? So, uh, again, uh, re-usable, uh, Automic workflows and actions that Michael just demonstrated along with, um, having, uh, both engineers and the both engineers, both application developers and dev ops, and I kind of stress it out because how flexible this is, right. Um, for them to define it one time and then have it reusable whenever they want. Right. >>I'm just curious, what's the biggest surprise when you show this to people in the field? Um, what do they get most excited? >>They love it. I mean cut. They immediately say, how can we start using it the next site? Right. And, um, it's, uh, you know, we also have a cloud center suite has a SaaS offering where it's, uh, made it very easy for us to, uh, get them a trial access. So that they can come in, get their foot wet, you know, and try it out. Right. And once they start doing these calls and building these workflows and uh, as a Michael demonstrated these actions where they perform API calls at the very least, right. Uh, they just get hooked to it. Right. And then start using it from their answer. Right. >>Mike, what about you? What's your, uh, what's your favorite response from, from clients when you demo this? W what's the one, two things that really, uh, that really grabs them, gets their attention and gets a big smile on their face? >>Yeah. Well, first and foremost, you see people's minds spinning on, like what use cases have been bothering them that they haven't been able to, to, to like fix, you know, because maybe they're not programmers or maybe they are, but you know, it's just, they thought it would be too complex and too much work. So, you know, I think it's just, it's, it's so open-ended, but you just, the interest in people's faces. It's like the first time, you know, I have a three year old, it's the first time I gave him Legos and he's like, you, I can build stuff. I can do stuff myself. I mean, it's just like that. I mean that's the amazing part of it is that it's so extensible and to build on to what Ali was saying, uh, you know, there's so many ways to trigger it too. So this can work standalone and work by itself. >>Or it can be triggered by an API call. It could be scheduled, it could be called from workload manager. It can be, uh, you know, it can be triggered from a, you know, a rabid. It could be triggered from PACA. There's so many different things that you can do to trigger these workflows that it just makes it so that it can integrate with other products and you can integrate other products. Right? So it really becomes that glue that kind of ties everything together. I mean, we really, really think about it as building blocks or Legos or something like that. Um, it just is really extensible, really easy to use. And you know, we think it's a real game changer. >>Great. All right. All a last word. Where do people go to get more information if they can't see that cool demo on that DVD screen on their phone? >>So, um, we definitely recommend them to go to cloud center suite. Uh, you know, if you easily Google it on Cisco, uh, website or on Google itself, you know, you'll see it, uh, apart from, uh, first or second links. But definitely check out CloudCenter suite action orchestrator is where you would like to visit and learn more about this tool and this component. So. >>All right, well thanks for, uh, for stopping by and uh, thanks for joining us from New Jersey, Michael. Oh, thank you. And I'll send you a cheese. All right. I'm, I don't know if I want that in the mail, but we'll see. We can make fast shit, but all right. Thanks again for stopping by. He's only T's Michael. I'm Jeff. You're watching the cube. We're in our Palo Alto studios. Thanks for watching. We'll see you next time. >>okay.

>> Narrator: Live from San Francisco, it's the CUBE. Covering Samsung Developer Conference 2017, brought to you by Samsung. >> Okay, welcome back everyone. We are here live with the CUBE coverage where Cloud Native and the SmartThings Conference from Samsung Developer Conference. I'm John Furrier, the founder, the co-founder of SiliconANGLE Media. Co-host of the cube here with Redg Snodgrass, who's the chairman of ReadWrite and ReadWrite Labs. >> Hello everybody. >> Also been an entrepreneur, he's done the Wearable World events, done a lot of things in tech, riding the waves. You seen them, a lot of action going on, Redg. Want to get your the thoughts as we wrap up day one of two days of wall-to-wall coverage of the cubes, Samsung Developer Conference, a lot going on. You know Samsung, they're trying to play their best hand that possible. Obviously, they're not going to come out and say, We're not really ready for primetime, for the cloud. But the reality is, they're not ready for primetime for the cloud and IoT. However, huge strides in positioning, messaging, and the self awareness of their stove pipes. They are series of stove pipes that they've recognized, We've got to make this a 2.0 Bixby that crosses across all of Samsung, open up IoT. >> Redg: Which I thought was great. >> Open ecosystem, everything else, to me, is a work in progress, kind of, cover the, hide the ball, a little bit, I mean, what's your thoughts? Do you agree or what's your reaction? >> Oh man, I was on a panel earlier today. And somebody was like, oh, this is great. And I wanted to go back to, back when we did the open API service with Alcatel-Lucent, when we roll out all this stuff for the telcos. I mean, it's just, it's a lot of hype, initially. But what I do like about it is it seems like there's a dogged commitment to creating all the different documentations necessary and bringing that in, I mean, if they really put the full marketing weight behind it, this could get really interesting really fast. I mean, they own almost every device in your home already. >> Well, I said the word hide-the-ball. Maybe I should take a step back and not be too harsh. What I mean by that is, they're not hiding the ball on purpose, I think they're, by design, and I think Greg mentioned this earlier. Greg Narain said, they're doing it by design. And I think that that's a good call. SmarterThings is a good positioning because it highlights multiple devices and connecting it together. I think if they played the data card and the cloud too much, they would've overplayed their hand, and it's not needed. I mean, do you think it's needed? I mean, I don't think it's needed. >> Well, one of the biggest problems with IoT right now is that you have multiple different silos creating data. And then all those data silos have to figure out how to come together and talk about it. I mean, it seems like they're taking a step out, and saying, hey, we want to build that solution. Which is great, I'm more interested in the orchestration between different OSs, like, how are they really going to do that? Because it, we talked a lot about, when you build one of these ecosystems, you're really just building an economy. And the more open that you let your economy, right, the more business models come in, the more people that can be there. And so, if we were to start thinking about these OSs as real economies, like what do you need to have economy work? >> Well, I think this is why, we were talking earlier, I think that you had a good point. I think that validates what I'm thinking out loud here, which is, why play the data card. They don't need to because it's still open-book. They still got to figure it out, and that's not a bad thing. They play with their best hand, which is the consumer hand. >> Redg: It's consumerism is where they're at >> The devices are awesome, the screen on the phones are phenomenal, they got TVs. They got a little bit of a family hub going on with the living room, kitchen thing, with the refrigerators. That's IoT, they got healthcare because it's a device issue. So they're working their way from the consumer edge into the industrial edge. Now, if you're in the IT world, you have security problems. So most people that we talk to, at the humans, they say, hey John, my plate is full, I got to staff up my DevOps and my application developers. I got to unbolt security from my IT department, make that report to the board as a profit center now. And I got all this machine learning and Cloud Ops, and you want me to do what? Like, instrument my entire factory with this IoT thing? So people are holding the brakes. >> Well, I mean think about it. Every day, right, you're confronted with another executive that has like fallen on a sword of a major security hack, a major security issue. And so, as an executive of a major like business unit, with a technology group in front of you, you're sitting there making all these decisions every day. And it used to, you used to come and say, okay, we're going to make decisions every eight, nine months. And you have this big waterfall thing in front of you. And you know that, from your vendors, that. >> John: It's predictable >> Everything was predictable, and now it's like, oh man, I got to get into this Google Glass stuff, and I've got, no, now it's wearables, and wearables, that doesn't work, I need my IoT infrastructure stuff. And so we're moving the court, you know, away from all these CIO, CTOs consistently of what they need to think about next. >> It's interesting, if you look at the stack, go back to the old 80s OSI model, you got the lower level stack, middleware, and then application stacks. If you follow the data, and the networks, and the packets, how it moves, you can almost see the trends, batch versus real time. And I think what we've seen in the big data world, in data sciences, which can be analytics, obviously specialty industry. But the role of data and realtime, self-driving cars, really highlights this really huge wave coming, which is how that people dealt with data and software, the relationship between software and data was different. You store it in a database, build the database, call the database, get the data out, load it in, slow, monolithic, siloed. But now you have data that you need in really low latency at any given time, in any different app, from any different database, in less than a millisecond how do you do that. >> Well, think of it. >> John: That takes intelligence. >> About two years ago, I had a great conversation with a big packet moving company that managed most of the packet movement for most of the internet. And we were talking about, what does it look like per person in the US in the next like three or four years? And it could be up to a petabyte a day at a per person. Now that sounds awesome because if you look at all the different like videos we watch, it's like, oh, that's great, really cool flying car. You know, connecting windows, no one's really doing the math on that. And if it's a petabyte per day per person, like in the US a year even, or you know. I could see models where it could be a month. Think about what that does to the network load. We just don't have the math to be able, you know, possibility to handle that. >> This is why the decentralization with Blockchain is interesting. Even though Blockchain is hyped up, I think it's fundamental to the internet, as this Dr. Wong from Alibaba, who told me that last week. He said it was like a TCP/IP, I agree with him because you have distributed computers, which we know about. We've been there, done that, but now you got decentralized and distributed, two different concepts at the same time. That's a fundamental paradigm shift. >> Well, I mean it's just, so, I mean, you got to. >> It's intoxicating to think about what that disrupts. >> No, no, I love it, I mean, honestly, I've fallen in love with narrow band networks the last week. For some reason, I'm the weirdest person on the planet. Because it's such a solution for security. It's such a solution for a lot of this back calling and data that we're going to have. It'll be interesting to look at, but when you think about the pure math on this. >> John: Are you back calling data or are you back calling compute? >> Oh, well it's so. >> That's a different conversation. The trend is, don't move the data. Throw the compute at it because compute is, this is an architectural renaissance happening, people are re-imagining. >> How many, how many startup. >> In global infrastructure. >> Execs can even like draw architecture? Right, with all the lame startups, I mean, when was the last time you saw like somebody pitch. When they came to pitch, it's like, let me talk about my architecture. >> John: That should be the first slide. >> It should be the slide that you talk about as an executive and everything, I don't see. >> If he can't get on the whiteboard. >> Startups deliver architecture. >> If you can't get on the whiteboard and lay out an architecture on fundamentally the core engine of your technology, you shouldn't get funded. >> Well, so that is a major issue that's happening right now because I do think that we have this group think where we've disallowed a lot of R&D thinking. We don't do longterm R&D before we get a product to market. And now, like all. >> John: Sometimes you can't. Sometimes you have to sprint out and put a stake in the ground and iterate. >> Think about all of the connected device product. How do you test the connected device product to scale? Right, I mean the iPhone, you know Samsung, everybody has all these devices out there, they're getting this data, it's coming in they can actually iterate on that product and make decisions, right? >> Well, that brings up a good point. We saw this at the Cube at VMWorld. For the first time we heard people grumbling in the hallways like, you know, I love the ENC tries, but they just haven't tested this use case. And the use case was a new workload that had unique characteristics. In this case they needed low latency. It was an edge device, so it was mandatory to have no latency with all this was trickling data in. But in this case, they had set up their virtual SAN in a tiered basis. And they needed a certain hardware configuration with vSAN. And they've never tested the hardware stack with the software stack. So it's just one of those things that the hardware vendor just never imagined, you can't QA the unknown. So this is where I'd see Samsung doing things like in-chip and seeing what Intel's doing with some of their FPGA stuff. You can see that these infrastructure guys got to bring that DevOps concept to the consumer world. >> Redg: Oh, it's going to be so hard. >> Which is programming the. >> Redg: So hard. >> The hardware at will. >> Yeah, well. >> John: Like the cloud DevOps ethos. What do you think of that? >> Yeah, no, no, no, look, I mean, I'm such a big fan of being able to get your product in people's hands, to be able to see the use cases, develop them out and push that forward. You know, big corporations can do that. You have 10 iterations of almost every iPhone right now, with thousands of engineers iterating on it. So when you look at like the competitor, which is your device right now, versus every other piece of IoT technology that isn't been perfected or anything. Our biggest issue is we're driven by the success of the smartphone for every other piece of technology today. And that's, that makes it hard to drive adoption for any other devices. >> So I get your thoughts on this, 'cause we wrap up day one. Obviously, let's talk about the developers that they're targeting, okay. >> Okay. >> The Samsung developers that they're targeting is the same kind of developers that Apple's targeting. Let's just call it out, however, you see voice-activated touch, you're seeing the services tools, now they're bringing in an IoT. You're not hearing Apple talk about IoT. This is unique, you got Google onstage, wink, wink, hey, everybody we're here, we're Google, Android, coming together. What is in the mind of the developer in the Samsung ecosystem right now, what's your take on it, what's the psychology of that developer? >> I built an app at one point in time. It was dating app a long time ago, right, with some other guys, they built it, I was just the mouth. It's called Scout and we were on the Simian platform, and the iPhone, and we were on web, we were on mobile web. And in the iPhone app store, all with one engineer. And it was really hard because we had real-time chat. It was just so much crazy things. At the end of the day, what always matters is, again, you're building economies, you're not building fun playgrounds or anything else like that. And if your economy is, your platform is the easiest to use, it has the capabilities and advantages that are the norm, right, you'll win. Bass Diffusion is great it's this guy out here, he won a Nobel prize, but what Bass Diffusion says, in order for you to win in a market, you need two things, imitation and innovation. Imitation, for instance, in TVs, is your TV black and white, is it color. As things move up, innovation eventually overtakes, and always becomes innovation. So when you look at like what's needed in market, the platform that is the easiest to use, the platform that has the most capable imitative qualities, it's just very easy for you to push things to market universally from OS to OS, along with certain pieces of innovation around business models, certain API capabilities that may make it easier for them to deliver revenues. If those are the things that are delivered, that we see pushed out, a good blend of imitation and innovation, the win. It's that person that actually can deliver it. >> Well, we're seeing gaming in entertainment really driving change, Netflix earnings just came out. They blew it away again, you're seeing the cord cutters are clearly there. >> So much for Disney, right? >> E-commerce, yeah, I mean, Amazon's still got to make some moves too, even though they were still winning. No one's really falling out of the chair for Prime. I mean, no, I don't know a lot of people who rigorously turn on Prime, they shop on Prime, but not necessarily watching any entertainment. So I'm a little critical of Amazon on that. But, then again, but Amazon's doing the right thing. Netflix, Amazon, YouTube, you're seeing a culture of digital entertainment shifting. E-commerce is shifting, and now you got web services. I think Amazon encapsulates, in my mind, a great strategy, retail and services, but if you extend that out to the rest of the world, voice-activated apps, you can blend in commerce entertainment, you can replicate Amazon. I mean, they could replicate everything out there in the open. >> Amazon is so good at understanding where they fit in the stack and then, pushing the edge case further and further and further along. They're really brilliant, versus like VMware that's like, oh man, we can make apps, no problem. They went to make apps, and it didn't work out so well, they're great with VMs, so. >> John: They're great with operators in the enterprise, not so much with DevOps. >> No, no, no, no, and it's. >> They got pivotal for that now. Michael Dell bought everyone up. >> Yeah, exactly. It's understanding where you fit in the stack and being able to take advantage of it strategically. I mean, like I said, I think Samsung's positioned really well, I mean, I wouldn't have come and hung out with everybody if I was like, ah, I'm going to be bored all day. There's a lot of really exciting things. >> We got a lot of eye candy, no doubt about it. I love their TVs, love their screens. The new Samsung phone, is spectacular, you what I mean. >> I'm pretty ecstatic. >> It was the first phone that wanted me to get transferred off my iPhone. And I ended up getting the little junior Samsung here, but. >> Oh no, well it'll be interesting as they start to connect their platform together as all a lot of these other developers start pushing the pieces of their strategy together. Remember, it's like whenever you throw a strategy out here like this, it's like you have a big puzzle with a lot of empty pieces. >> I mean, the question I have for you is, let's just close out the segment. What do you think, what area should Samsung really be doubling down on or peddling faster, I should say. What should be developing faster? Is it the open APIs, is it the cloud? And they got to get the open ecosystem going, in my opinion. That's my take, what do you think they should be working on the most right now? >> Yeah, I mean like look, cloud is going to be really, really, there's a lot of competitors out in cloud. There's a lot of multiple, there's a lot of choices, right. Where I've seen them like really do well, I'll go back to the fact that I firmly believe that Google never really monetized the Android that Samsung did that a lot better. And so, by looking at the different points in the market, where they're good, I mean, their ecosystem is solid. I mean, yes, I mean it seems like the sexy thing is Apple, but I've talked to several developers, and I know where they make their money, and they do a strong amount of revenue, if not equivalent to where the iPhone is, at least from what I've heard so far. >> The android market share it's not shabby at all. >> Not, so. >> Damn good. >> So they've, they've been able to do this, like, from that, taken that Android stack, applying that imitation and innovation on top of it, fascinatingly so, I wouldn't count them out for this. And I'm pretty encouraged to see all the other aspects, but I like the ecosystem built out too. >> Redg Snodgrass, ReadWrite Labs, quick plug for you. What's going on in your world? Got some recent activities happening, please share update. >> So, yeah it's great, so we just launched our IOT revolution event series where we look at the atomic unit of different markets. And what that means is, we find the real buyers and sellers, a lot like what Debbie Lann, who I love, did. And we look at the buyers and sellers together, along with the top series A startups, all around newsworthy issues. And so, whatever it's like, is it hacking and Russia. You know, then we'll get cybersecurity experts up, and we'll talk about those issues from an executive point of view. And that's the thing that's making me most excited because I get to have all these conversations with people. It will be on video, onstage, November 13th, is the first one, it's a private event, but we'll work out anybody. >> Where's it going to be? >> It'll be in San Francisco, around 100 Broadway. So it's kind of a quiet thing, but I'd love for everybody to come if you're interested. >> It's a quiet thing but I want everyone to come. It was, not going there, too many people are going. >> It's like my parties, right? >> It's like a Yogi Berra. Well, thanks for coming out, appreciate, wrapping up day one of coverage The Cube. This is Samsung Developer Conference 2017. Hashtag SDC2017, that's what they're calling it. Lot of great guests today go to YouTube.com/siliconangle for all the great footage. And also check the Twitter sphere, lot of photos. And shout-out to Vanessa, out there has like helped us set everything up. Appreciate it and great to the team. That's day one wrap up, thanks for watching. (upbeat music)

(switch clicking) >> Hey, welcome back, everybody. Jeff Frick, here with theCUBE. We're at the Mission Bay Conference Center in downtown San Francisco at Node Summit 2017. TheCUBE's been coming here for a number of years. In fact, Ryan Dahl's one of our most popular interviews in the history of the show, talking about Node. And, the community's growing, the performance is going up and there's a lot of good energy here, so we're excited to be here and there's a lot of big companies that maybe you would or wouldn't expect to be involved. And, we're excited to have Gaurav Seth. He is the Product Manager for Several Things JavaScript. I think that's the first time we've ever had that title on. He's from Microsoft. Thanks for stopping by. >> Yeah, hey, Jeff, nice to be here. Thanks for having me over. >> Absolutely, >> Yes. >> so let's just jump right into it. What is Microsoft doing here in such a big way? >> So, one of the things that Microsoft is, like, I think we really are, now, committed and, you know, we have the mantra that we are trying to follow which is any app, any developer, any platform. You know, Node actually is a great growing community and we've been getting soaked more and more and trying to help the community and build the community and play along and contribute and that's the reason that brings us here, like, it's great to see the energy, the passion with people around here. It's great to get those connections going, have those conversations, hear from the customers as to what they really need, hear from developers about their needs and then having, you know, a close set of collaboration with the Core community members to see how we can even evolve the project further. >> Right, right, and specifically on Azure, which is interesting. You know, it's been interesting to watch Microsoft really go full bore into cloud, via Azure. >> Right. >> I just talked to somebody the other day, I was talking about 365 being >> Uh huh. >> such a game-changer in terms of cloud implementation, as a big company. There was a report that came out about, you know, the path at 20 billion, >> Right. >> so, clearly, Microsoft is not only all-in, but really successfully >> Right. >> executing on that strategy >> Yeah, I mean-- >> and you're a big piece of that. >> Yes, I mean, I think one of the big, big, big pieces, really, is as the developer paradigms are changing, as the app paradigms are changing, you know, how do you really help make developers this transition to a cloud-native world? >> Right, right. >> How do you make sure that the app platforms, the underlying infrastructure, the cloud, the tools that developer use, how do you combine all of them and make sure that you're making it a much easier experience for developers to move on >> Right. >> from their existing paradigms to these new cloud-native paradigms? You know, one of the things we've been doing on the Azure side of the house and when, especially when we look at Node.js as a platform, we've been working on making sure that Node.js has a great story across all the different compute models that we support on Azure, starting from, like, hey, if you you want to do server list of functions, if you want to do BasS, if you want to go the container way, if you want to just use WEAMS, and, in fact, we just announced the Azure container instances, today, >> Right. >> so it's, one of the work, some of the work we are doing is really focused on making sure that the developer experiences as you migrate your workloads from old traditional, monolithic apps are also getting ready to move to this cloud native era. >> Right, so it's an interesting point of view from Microsoft 'cause some people, again, people in-the-know already know, but a lot of people maybe don't know, kind of, Microsoft's heritage in open source. We think, you know, that I used to buy my Office CD, >> Right. >> and my Outlook CD >> Right. >> you know, it's different, especially as you guys go more heavily into cloud, >> Right. >> you need to be more open to the various tools of the developer community. >> That's absolutely true and one of the focus areas for us, really, has been, you know, as we think through the cloud-native transition, what are the big pieces, the main open source tools, the frameworks that are available and how do we provide great experiences for those on Azure? >> Right, right. >> Right, because, at times, people come with the notion that, hey, Azure probably might just be good for dot NET or might just be good for Windows, but, you know, the actual fact, today, is really that Azure has great supporting story for Linux, Azure has great story for a lot of these open source tools and we are continuing to grow our story in that perspective. >> Right. >> So, we really want to make sure that open source developers who come and work on our platform are successful. >> And then, specifically for Node, and you're actually on the Board, so you've got >> Right. >> a leadership position, >> Yep. >> when you look at Node.js within the ecosystem of opensource projects and the growth that we keep hearing about in the sessions, >> Yep. >> you know, how are you, and you specifically and Microsoft generally, kind of helping to guide the growth of this community and the development of this community as it gets bigger and bigger and bigger? >> Right, I think that's a great question. I think from my perspective, and also Microsoft's perspective, there are a bunch of things we are actually doing to engage with the community, so I'll kind of list out three or four things that we are doing. I think the first and foremost is, you know, we are a participant in the Node.js Foundation. >> Right. >> You know, that's where like, hey, we kind of look at the administrative stuff. We are a sponsor of, you know, at the needed levels, et cetera, so that's just the initial monetary support, but then it gets to really being a part of the Node Core Committee, like, as we work on some of the Core pieces, as we evolve Node, how can we actually bring more perspectives, more value, into the actual project? So, that's, you know, we have many set of engineers who are, right now, working across different working groups with Node and helping evolve Node. You know, you might have heard about the NAPI effort. We are working with the Diagnostics Working Group, we are working with the Benchmarking Working Group and, you know, bringing the thing. The third thing that we did, a while back, was we also did this integration of bringing Chakra which is the JavaScript Runtime from Microsoft that powers Microsoft Edge. We made Node work with Chakra because we wanted to bring the power of Node to this new platform called Windows IoT >> Right, right. >> and, you know, the existing Node could not get there because some of the platform limitations. So, those are like some of the few examples that we've, and how we've been actually communicating and contributing. And then, I think the biggest and the foremost for me, really, are the two pillars, like when I think about Microsoft's contribution, it's really, like, you know, the big story or the big pivot for us is, we kind of go create developer tools and help make developer live's easier by giving them the right set of tools to achieve what they want to achieve in less time, be more productive >> Right, right. >> and the second thing is, really, like the cloud platforms, as things are moving. I think across both of those areas, our focus really had been to make sure that Node as a language, Node as a platform has great first-class experiences that we can help define. >> Right. Well, you guys are so fortunate. You have such a huge install base of developers, >> Right. >> but, again, traditionally, it wasn't necessarily cloud application developers and that's been changing >> Yep. >> over time >> Yep. >> and there's such a fierce competition for that guy, >> Yep. >> or gal, who wakes up >> Yep. >> in the morning or not, maybe, the morning, at 10:00, >> Yep. >> has a cup of coffee >> Yep. >> and has to figure out what they're going to develop today >> Right. >> and there's so many options >> Right. >> and it's a fierce competition, >> Right. >> so you need to have an easy solution, you need to have a nice environment, you need to have everything that they want, so they're coding on your stuff and not on somebody else's. >> That's true, I mean I, you know, somehow, I kind of instead of calling it competition, I have started using this term coopetition because between a lot of the companies and vendors that we talk about, right, it's more about, for all of us, it's working together to grow the community. >> Right. >> It's working together to grow the pie. You know, with open source, it's not really one over the other. It's like the more players you have and the more players who engage with great ideas, I think better things come out of that, so it's all about that coopetition, >> rather than competition, >> Right. >> I would say. >> Well, certainly, around and open source project, here, >> Yes, exactly. >> and we see a lot of big names, >> Exactly. >> but I can tell you, I've been to a lot of big shows where they are desperately trying to attract >> Right, right, yes. >> the developer ecosystem. "Come develop on our platforms." >> Yes, yes. >> So, you're in a fortunate spot, you started, >> Yes, I mean that-- >> not from zero, but, but open source is different >> Yes. >> and it's an important ethos because it is much more community >> Exactly, exactly. >> and people look at the name, they don't necessarily look at the title >> Exactly. >> or even the company >> Yep, exactly. >> that people work for. >> Exactly, and I think having more players involved also means, like, it's going to be great for the developer ecosystem, right, because everybody's going to keep pushing for making it better and better, >> Right. >> so, you know, as we grow from a smaller stage to, like, hey, there's actually a lot of enterprised option of these use case scenarios that people are coming up with, et cetera, it's always great to have more parties involved and more people involved. >> Gaurav, thank you very much >> Yeah. >> and, again, congratulations on your work here in Node. Keep this community strong. >> Sure. >> It looks like you guys are well on your way. >> Yeah. Thanks, Jeff. >> All right. >> Thanks for your time, take care, yeah. >> Guarav Seth, he's a Project Lead at Microsoft. I'm Jeff Frick. You're watching theCUBE from Node Summit 2017. Thanks for watching. (upbeat synthpop music)