 Live from Las Vegas, it's theCUBE! Covering AWS re-invent 2019. Brought to you by Amazon Web Services and Intel, along with its ecosystem partners. Welcome back to Las Vegas. Lisa Martin with John Furrier. It's theCUBE at AWS re-invent 19. Lots of buzz, you can probably hear a little bit of it behind us here. There's about 65,000 people projected to be at AWS re-invent this week. Wow, we're very excited to welcome a distinguished guest and a distinguished architect from Splunk, back to theCUBE. Arjun, welcome back. Thank you very much, thanks for having me back. Great to have you here. So let's kind of talk about here we are at re-invent, lots of news, lots of stuff, lots of buzz going on. What's kind of the latest with Splunk and AWS? All right, so the latest with Splunk is, Splunk obviously acquired us SignalFX, the deal closed in October. So we are very excited about that. And we really feel that it's a, it's a manage of complementary technologies, which is one of some of the things we probably can discuss later. We're also very excited because we got acquired, then we were able to go to .conf, where we introduced the combined companies together. But then at KubeCon recently, we made a couple of very interesting product announcements that we're excited about, which is we're discussing also at the re-invent conference. The first one is we have a brand new Kubernetes experience called the Kubernetes Navigator, which we feel is a far, far better way to understand and make sense of the Kubernetes environment. As you know, it's getting a lot of traction as a technology. So we're very excited about that because it not only gives you the infrastructure view, but it also gives you the operator's view, which I think operators will really appreciate. The other thing that we're also focusing on obviously, if Splunk acquired us, so logs is an important part of this equation, we are doubling down on the ability to ingest logs and make metrics out of them. You know, one of the things we've always discussed is how metrics are very lightweight and actionable, things that you can put on dashboard you could put alerts on. And the ability to ingest logs and make them into metrics gives you that capability on the log data. So we had some very interesting announcements around AWS FireLens and so on, where you would be able to take log data from Splunk or other sources and then bring them in as metrics to the system. The third thing has to do with the growing traction of open source standards. So we were actually very excited to make some contributions to the open telemetry project that we can discuss also later. But the idea is we want to promote open standards and open source, especially in instrumentation in the monitoring realm. So that's kind of what's new. The question that's here at Amazon this week and this points to your success is observability. Jassy's laying out this distributed cloud, center of gravity, public cloud edge, outposts, native AWS outposts, 5G with Verizon, Wavelength, all points to a lot of things moving around. Move compute to the edge where the data is. So it speaks of large scale. People having a hard time of doing it themselves on observability is harder and harder to roll your own or manage multiple tools. What are you guys doing to solve that problem and how do you shape that going forward? That's a great question. So the thing that blows my mind every time I come to reinvent is just a sheer variety of new things that comes across and people are adopting them. All of these he mentioned a bunch of different services that have got a lot of traction, got a lot of users. So that's happening across the user base. And then the question on DIY is because it's no longer about just building a database or a thing that you can source some data and make some queries. It's about building the solution. A good solution need to support all the systems and services that the customers, the engineers are using, right? So just keeping up with a sheer pace of innovation, keeping that system up to date is extremely, extremely hard. And so I feel that in general, it's making less and less sense for most companies to try to roll their own observability. They'd rather choose good tools that can sort of empower them, that can enable them to move faster and invest in the people and processes part of it, which is also very, very key, because you cannot have that. What's the downside of rolling your own, doing it yourself? Sure. What are some of the consequences that might happen? So in general, the reason people want to build DIY are a couple of reasons, right? So one is they might undervalue like the capabilities that good observability might provide you. And they might be afraid of the cost. Like if observability was cheap or free, most people probably wouldn't build it. Some of them still would, because they might be afraid of vendor lock-in. If the vendor lock-in is a problem and you don't want to be locked into vendors, right? And what I feel in terms of the risks is, like if you consider observability as a cost center and not as an enabler, then you're probably going to try to do DIY. But I think the view to, the right view to have is think of it as something that accelerates your innovation. And some of the risks of DIY is, if you don't build something that's really capable that can do all the modern awesome things that a system should, you're going to get slowed down. Your innovation is going to get slowed down. Another very thing, a common pattern that we see a lot is maintaining that it takes a lot of resources and people to build and maintain such a system. It's easy to prototype something and get it going. But are you going to be able to maintain the head count, hire and grow the team on a long-term basis, because it's not something you can suddenly decide, oops, I made a mistake, time for a change, right? But change is difficult in any aspect of life. Change management is something that we talk about often. It's way easier said than done. One of the things Andy Jassy talked about this morning and alluded to this, and John's exclusive interview with him the other day was that the transformation needs to start at the top. It needs to be an executive level, a senior level and an aggressive tops-down push. In your experience, in the last couple of years, what are some of the things that you're seeing companies in terms of the senior leadership embracing and understanding where DIY is useful, where it's not, but also pushing that, I want to say, I guess I'll say pushing it down from the top so folks understand why this type of change is fundamental to a business to be competitive? Right, so in general, I think the focus is all on innovating faster, moving faster, keeping customers happy. Fundamentally, that's what we're doing. You know, our CMO Tom Burel likes to say that the business, the internet moves at the speed of life. The speed of life is real time, right? And so outages, any kind of issues, they really affect your brand and that's something that we need to avoid, like the plague, right? And that's kind of where, again, observability comes in because this is the thing that's going to allow you to find out when things are off. But more importantly, even when you don't have outages, the confidence that teams get in making changes, whether it be configuration changes or code pushes, et cetera, because they have a good system backing them up, is very, very critical, right? Now you can go DIY, you can go with a vendor solution, both potentially are fine, especially if you can build one. But I think from top down, the important thing is, like you have to be very clear about what you want out of it and what are those things that you want to accelerate or make better in your organization. So if your goal is, I want faster innovation, more code pushes, more changes, less disruption, like I feel that message needs to be top down so that engineers understand that from a management perspective, there's full support for this and they are empowering you. Again, where the tool comes from is less important, but I think having those goals very clear and having that culture set from the top is very critical. A lot of open source discussions, we're hearing it here, I'm laying out multiple databases, you got PyTorch, you got TensorFlow on the machine learning side, and more and more Kubernetes. Again, this all speaks to where the service meshes are going and microservices. But there's a lot of talk around open instrumentation and open telemetry. What's your take on this? What's going on there? Can you share your commentary on those two things? Yes. So in general, as you know, like from the beginning, since SignalFX started, we always believed that instrumentation should be open standards based. There should not be proprietary instrumentation, there shouldn't be vendor lock-in. It was a little bit perhaps ahead of the time when we started off, but you can see that trend really accelerating now. But at this point, because of the sheer variety of services and so on, it's very, very hard to build proprietary everything that supports all the things out there. What we're seeing is more bottoms up, open source, open standards efforts, right? And that is great because, A, for the guys who are doing DIY because they don't want vendor lock-in, open standards is great because you are not really locked into a vendor in your environment. What you're doing is using a different backend, whether it be your own or whether it be a vendor's. Some of the things that we are doing is we are actually very happy to see this acceleration and we are actually helping make that more. So we just contributed pretty significantly to the OpenTelemetry project, which as you know is a way to instrument your environment for traces and metrics and logs eventually. And so we actually donated the SignalFX smart agent, which is pretty wonderful because it's a service that's an agent that's running on your instances, on your host, and it discovers as new instances pop up. So you know, speaking of Kubernetes, it's a perfect fit for that. And it will start monitoring them and sending you data. And by making it, by donating it to OpenTelemetry, we are hoping to sort of accelerate sort of the goodness and so that you know all customers, all users, whether they're SignalFX customers or not, should be able to benefit from that. Is it open source, is it source code or is it open as in? Yes, it's open source. So there's two aspects to it. There's open standards as well as open source code. Both of them are happening because through the Omniscient Acquisition, we are now actually a pretty core part of the OpenTelemetry effort. So we are not only helping finalize the standards, but also donating actual source code and components. Take a minute to explain SignalFX's evolution. Now that you're in Splunk, what's changed? What's still the same? What's, how has it evolved? How has SignalFX evolved? Because you guys were really early ahead of it. A lot of people, Splunk is a lot of market power, great customer base and tech. What's the impact of Splunk and SignalFX? Yes, so you know there's this cliche which says one plus one equal to three. It kind of almost feels true here because like I really feel every time I think about this acquisition, it just feels how complimentary these two companies were. Because we have metrics and traces, Splunk has the best logs platform. But one of the things that we a lot of times don't understand is they also have a bunch of other technology which is highly relevant to the observability space. For example, they acquired a company called Phantom which is into automation. Which is right up our alley because I feel like after all this mess has died down a little bit on Kubernetes, automation is going to be the next bit frontier. They have fantastic automation platform. They've built a security automation tool called Mission Control based on that. And now we're looking at how we can bring that into observability. Another example is incident management. Splunk goes Victor Ops, which is again exactly right up our alley. So we feel that we can really build a portfolio of solutions that's going to work really, really well. That's one aspect. The other aspect, as you mentioned, is just the market power and the resources that's behind us, which is wonderful. For example, they're quite omniscient, which is a fantastic complimentary technology to us and we are working very quickly to sort of integrate the two together. Similarly, just getting the introductions, having the financial benefit of Splunk behind us is wonderful to have. So I think it'll only accelerate our work. Congratulations on a great venture. I know you guys stayed the course and rightfully so great payday, but great outcome with Splunk as a win-win. Yes. I got to ask you the entrepreneurial question because a lot of people are saying, oh my God, Amazon's sucking up all the oxygen out of the room, large scale, got red shifts, taking over this, that's taking over that. Someone's eating someone. Okay, I don't believe that. I believe that there's still a lot of opportunity for entrepreneurs because of this born in the cloud and reborn in the cloud. A new next gen architectures are developing with Edge. What's your opinion on this? As cloud evolves, what's the dynamics of entrepreneurs and people thinking about innovating and either pivoting or reimagining their business? How should they be thinking about how to win in the new model? What are some of the architectural things they could bet on? What's your expert opinion on that? That's a great question. So again, I have some thoughts on it. Everybody might have different ones, right? So I feel like the move to cloud is just happening. It's happened. Everything's going to move to the cloud. So I think the fundamental technologies like the databases, et cetera, that the cloud providers are always going to have an advantage because they're going to be able to run it in a more performant way. But the thing that are doing us a great favor as entrepreneurs is they're making a lot of different services available to us. Now they are not always necessarily all working well together to solve a specific use case. So I feel that they're giving us the tool set among other things to combine together to provide solutions for the problems that users, organizations are facing. Not necessarily the platform, but the solution, the vertical on top of it. I think there's a lot of opportunity there as well as sort of just new types of technology. I mean, you can, as an entrepreneur, you can still build technology that the cloud provider might find as valuable and they might want to buy you or they might want to use you. So there's always opportunity there. But I think they're so busy building the substrate. There's an enormous amount of opportunity to sort of further up north. That's kind of my opinion. That's a great opinion. Last question for you on the parlay of opportunity and the career that you've had as cloud is evolving, the next gen of the cloud 2.0 that John's calling it and data becomes the critical element that can define business differentiation and competitive advantages. What are some of the next industries that you really think are prime to completely transform if they get it right? I think we are still, there's a whole lot of talk of machine learning. I think we are just scratching the surface. I think what's happened is at this point, it has become accessible enough and viable enough to be applied to different places. So every day we see a new headline where basically similar techniques were applied to this use case or that use case and then its amazing result, be it healthcare, transportation, you name it, like digital business, it's happening all the way. On our side, on our side of the fence, I feel as Plunk or as SignalFX, we're going to see a lot of that happening on our side of the fence because, again, because of the complexity, one of the things that we have discussed with John earlier is how we feel machine learning and artificial intelligence is going to help us operate more efficiently because humans are going to be able to not really grok the entire complexity of what's out there. So I feel there's a lot of assistance that it can provide. So that's one area which I think is interesting. And I feel also that one of the things we discussed within SignalFX is, move towards automation, automated everything because complex systems, they just need to run themselves because at some point humans cannot really go and make all these decisions. Like my main frame, it just kind of operates itself. We are not really in the middle of it, right? To some extent. Similarly, I feel there's a lot of action going to happen on automated cloud and automated observability, automated everything. So I think that's another sort of big area that I see happening. And one of the things I also like to say is I don't want to make predictions because the world is so different from 10 years ago to now. Like it just blows my mind. I don't know whether I would have been able to sort of think what's going to happen. So I only wonder what the next five years are going to bring, right? I love that honest answer. You're right. Even a few years ago, today, my love. Arjun, thank you for joining John and me on theCUBE today. We appreciate your time. Thank you very much. For John Furrier, I'm Lisa Martin. You're watching theCUBE from ReInvent 19 in Vegas. We'll be right back.