 Live from Manhattan, it's theCUBE, covering AWS Summit, New York City, 2017. Brought to you by Amazon Web Services. And we are live at AWS Summit, here at the Javits Center, New York City. We're in Midtown, Manhattan. A lot of activity going on outside. You can imagine all the buzz inside as well. Some are between six, seven, 8,000 attendees, kind of tough to tell right now, but everybody's shamed inside here on the show floor and they've been here all day. They're going to stay for a while, I think, too. As I said, a lot of buzz going on and good buzz too. Along with Stu Miniman, I'm John Wallace and we're now joined by Eric Windish, who is the co-founder and the CTO of IOPyte and Erica. Thanks for being with us here on theCUBE. Thank you, thank you for having me. You have had a big day. Yes, we have. It's always fun to talk about money, but you did have a fairly significant announcement this morning to make. Tell us about that. Yeah, so this morning we announced funding for 2.5 million dollars from several investors, including NEA, Madrona, and Underscore. So yeah, you don't often get to high five everybody, right, for a day like that. I mean, that kind of validation, obviously, is something that not you just take to the bank, you take it to the marketplace too. Yeah, absolutely. And we actually, we started, our first check was from Techstars. So we joined Techstars here in New York City and did that last year for their summer program and it was really great. And that was the first validation that we really had. And then having that further validation from major VCs like NEA and Madrona, Underscore, that really was really validating for us, as well as just the fact that we're building, and we're hiring and we're building and having what I think is an increasingly awesome product. Sure. Well, tell us about IOPyte. I mean, for folks at home who are watching, might not be familiar with your space. What you're doing, how you do it? Yeah. So we provide tools for software developers to build and manage their applications on Amazon Lambda. So basically it's all serverless. We're actually built on serverless as well. We monitor with IOPyte, we dog food everything. And we are providing deeper insights into those application workloads, as well as, you know, correlating the information in more useful ways, deeper knowledge of what exactly is happening in the run time. So like we're able to see like the data we ingest tells us information on the processes and the containers and the virtual machines that are running your Lambda workload. So we can see things like memory leaks and we can see file descriptor leaks and disk space utilization leaks, things like that, that Amazon doesn't collect or at least doesn't give you that information. So we're looking at ways we can provide more value to users of Lambda and also extending it with plugins. So we have a plugin for tracing where you can time aspects of your application as well as profiling. So you can enable a profiling plugin and you get a full flame graph. So you can see these are all the functions and this one ran and this one ran and the stack looks like this. And so you can see the full flame graph of what happened and when and full timing information. This kind of insight that nothing else really gives you. Yeah, Erica, every time we have a new technology we go through this kind of diffusion of innovation that goes through. Remember back, you know, I mean, I go back thinking about, you know, when virtualization came, people, what is it? How do I use it? We saw that containers and each wave seems to be going faster and faster. So there's still plenty of people I talked to that were like serverless what? You know, some new as a service. I mean, I thought I knew it was SaaS and everything else like that. You're digging into these environments further. Can you give us what are some of the key use cases you're seeing? What are the challenges that customers are having? You know, kind of what works, what doesn't work? You know, help us unpack that some. So I think there's a different number of challenges that users run into today. One is the fact that it is new. So some of the tools are still evolving. You know, operations tools, development tools are still evolving. Just this week, then Amazon announced Sam Local so you can do editing and debugging locally on your machine or your laptop that wasn't available before, right? So these tools were very much still in the learning phase for some of the tools. But some of the things like what we're doing with IOPyte in some ways is more traditional because we're bringing in, you know, some of the basic monitoring tools and capabilities that you expect from other platforms. But the other side also innovating because we bring in, you know, we're bridging that development and operations into a single tool. So it's not development and operations. It's, and not even just different tools for those two things, but a single tool for those. So I think that's part of the solution, part of the problem. You know, in terms of workloads, I think there's a lot of ETLs streaming applications, very infrequent things like cron jobs, web applications. You can take Flask applications or Express applications and just port them directly over the Lambda with, you know, almost a lift and shift for those, right? So there's a lot of power for bringing on the web because you pay for the requests. You don't scale your application and build your application for the number of servers that you need to handle the requests. It scales per request and you pay per request. And that's what's powerful in both scale of operations and team and like financially, but also, yeah, I lost train of thought there, but it all scales that way, right? Like just according to the request. Yeah, bring us into a typical customer. And I know there are no typical customers. Everyone's a little bit different, but you've got the developers, you've got the operators. Finance has always had, you know, there's challenges with cloud in general, but serverless, you know, at least promises that it's going to be less expensive. What are those dynamics from an organizational standpoint that you see inside? In terms of cost? Not just cost, but you know, do the developers make something and the operators are like, wait, you know, there's challenges there or who drives this initiative in general? Does finance come and say, has finance heard about this and said, hey, you know, I heard I could save 60 to 70% of my cloud if you just, you know, re-architect this on Lambda. You know, is that the developers coming through and saying, oh, wow, this is great and can do it or operators. Who's driving the initiatives and what are some of those dynamics? Yeah, so I see a combination of these things. Some organizations, and you know, and I don't want to say names because I don't want to like, you know, dictate to this and that's how it is, but you know, I get the impression that certain organizations, they have a top-down approach where they're going like everything is going to be serverless and the cost really matters. So you're going to build serverless unless you can't, right? Serverless by default, anything else as an exception. Then there's organizations where developers are really pushing for it because it simplifies their requirements, right? It's a self-service aspect, right? Even if they can spin up VMs, like even if they have self-service VMs, they don't have to spin up VMs, they don't have to build Docker images, they don't have to look at how the operating system is configured. They write code and they deploy code. There's no other steps, right? They're not like, oh, what version of Python is on here and how do I install all the libraries and how do I, right? Like with serverless, you just write the code and you ship the code, which is really, really nice. So, you know, in a way, it's like having a golden image that you can't change and you just know you're always going to build for in every application that every organization is building to the same golden image, which simplifies a lot of things. Stu and I were talking about serverless, you know, the whole concept because it's probably not truly serverless, it's just different server or different, you know, it's a different flavor of it, basically. So, I mean, so first off, you know, what gave birth to that and then where do you think with serverless computing, serverless application, so on and so forth, where is that going? You know, what's going to be the real value at the end of the day of that? So, I mean, so first of all, the term serverless, I look at it as yes, there are servers. Serverless is servers are not my concern as a developer, right? I am not worrying about what the server looks like or operating those servers necessarily. I care about building my application, which is why we're looking at building tools that are bridging development and operations so that operations is part of your development. But I see the direction of serverless really interesting in a few ways. One is that it's going to be available for more use cases, right? So, right now, there's certain use cases that make sense and one of the challenges is figuring out which use cases it doesn't work for. Eventually, you're not going to have that question, potentially, right? So, maybe we get to a point where you don't have to ask, like, the challenge isn't, is serverless good for this use case? Maybe it's good for all use cases, eventually down the road. Maybe. Another thing is... If I could just follow up on that. Some of the announcements today, like AWS Glue, has serverless in the background there. Seems very promising. Things like machine learning or artificial intelligence that serverless, you know, IOT, where I need to balance the surface area of attack there, but with serverless, it won't be active as much and there'll be links that are a little bit more dynamic. So, lots of those new use cases seem to be built really well for serverless. What aren't some of the cases today that you just say, hey, you know, don't even go serverless there? Oh, don't go serverless, where to do that? Yeah. Well, so, Lambda has an execution time window which can be limiting for some things that you might want to do. So, like, Lambda in particular may not be the best case for all video encoding tasks. Some video encoding tasks, if you can time limit it, can be fine, but it's not good for all video encoding tasks because, you know, it's a batch process, potentially. Serverless processes that can, like, let's say, paralyze that and say, we're going to run Lambda, but we're going to say, split this up into, you know, into segments, for instance. You can do that, or if you do it as a stream, right? Like, you pipe a video and blocks into a kinesis, right? You can make that work, but it becomes a challenge to do those kinds of work use cases. Yeah, it was the example I think in the keynote was this hide process that would have taken five years, we can do 155 seconds. Right, but you have to paralyze it, right? Right, exactly. And if you can't paralyze a task and you can't do it within five or 10 minutes, you can't use Lambda for it today. But that's other things, you know, it's also dependent on how you define serverless. Because if serverless is Lambda, right, that's one thing. But if serverless is these other, you know, SaaS products, as well potentially, like AWS Transcode Service, well, is that serverless? If it is, then, you know, there you go. There's a solution potentially for you. So it's, there's very blurry lines sometimes around what is serverless and like, we're looking at IO pipe around serverless functions, right, and that's like, I feel the same way around cloud in general, was that there's server like cloud compute and it kind of evolved over time and the cloud is everything, right? All these things are in the cloud. But originally, when we're talking cloud, five years ago, 10 years ago, it was all compute. That's what we were talking about. So these terms change over time. So it's hard to say what serverless will be in five years or 10 years because it'll mean something different. But, or next week. Yeah. For that matter. Eric, last question I have. Sure. $2.5 million. What's that going to drive? What do we expect to see from your company? And give us any final thoughts on what you'd like to see for the maturation of the serverless technology field? Yeah. So we've been hiring and building out a team. We're working on improving the user experience of the product. We are adding additional plugins and enhancements to the service. We feel that we have a really good base with our 1.0 announcement. Because we're not just the 2.5 million, we also announced our 1.0. And the 1.0 has a really good base of functionality. And we're looking at adding additional plugins and additional features that can extend the service. So we're looking at doing that without money. And with serverless in general, I think this is really compelling what we're going to see in the next year. Because we're going to see more large enterprises and more enterprise adoption, I think. I mean, I was involved early in cloud. I was involved early in Docker. And, you know, this point of serverless is very much at the early days of those technologies. And I definitely saw a rocket ship taking off. And I think in the next year, it's going to be really interesting to kind of see it starting to, you know, orbit a little bit. Well, new product, new funding, and a new day. So congratulations on a good day. And thank you for being with us here on theCUBE. Thank you very much. You bet. Well, we'll continue here at the Javits Center. We're in Midtown, Manhattan, continuing our coverage of the AWS Summit here on theCUBE.