 From New York City, it's theCUBE, covering New Relic Future Stack 2019, brought to you by New Relic. I'm Stu Miniman. We're here in New York City, right next door to Grand Central Station at the Grand Hyatt, this first year of theCUBE attending New Relic's Future Stack, the seventh year of the show, and happy to welcome to the program Guy Figgle, who's the Vice President and General Manager of New Relic AI. Of course, CEO was up on stage this morning announcing New Relic AI. It's in beta. Lou said, you know, expect early 2020 for to come out. So thanks so much for joining us. Thank you for being here. All right, so Guy, you came to New Relic by way of the acquisition of Signify, and that ends in AI, of course, even though we pronounce it Signify. So help us understand, is this a repackaging, rebranding, you know, New Relic-izing the product that was through the acquisition? Tell us how we've gotten here. Yeah, sure. So New Relic AI is a whole new set of capabilities. It's a suite of capabilities that we are launching today in beta that pretty much augments the set reliability engineers with AI and ML capabilities. It runs on top of the New Relic One platform, which is the first observability platform that is connected, open and programmable. So you have all of the existing information and data that you already have inside New Relic. And we've incorporated a lot of the technologies and the techniques that we have developed as part of Signify with existing capabilities that New Relic already had, and pretty much integrated all of that into single user experience and single type of capabilities across the stack. All right, so Guy, AI is a really broad category. You know, you got your AI and ML and cognitive and all these things, bring us, what was kind of the core IP of Signify when they came in? Sure, so we really focused on correlating and reducing the noise of all of your different alerts and incidents, but not just that. We've actually built a recommendation engine on top of that to provide you much faster context to get into potential root cause of all your different information focused on events. And now we're combining that with all the time series data that New Relic as a platform has to offer. So you're getting a much broader capabilities for understanding. Yeah, you know, definitely there's that promise of AI is we know that humans alone or my traditional tooling just can't keep up, you know, talk about all the different sources of data, you know, the volume of data. I just saw Lou talking about, you know, the amount of, you know, the millions of items being ingested into the New Relic database and the billions of items that are being read, you know, basically per second. So, you know, help us understand you say, you know, we love, we talk about our videos or extracting the signal from the noise. So did I hear it was like 80, 85% to your early customers or helping to reduce that noise? You know, bring us in a little bit more. True, yeah, so definitely early results shows us over 80% noise reduction for some of the customers. And it is important to understand this is automatic relations. So this is truly based on the engines with no human interaction. Now we actually have even greater results when some user input is driven into the system and that raises the capabilities as well. In terms of the number of events, yes, we are dealing with huge amount of events and information in the platform. And I think it's all around not replacing the humans, but actually augmenting the site reliability engineers. So you talked about how systems, you know, there's a great promise for those capabilities. We believe that applied intelligence is a much better term because it is really enabling the augmentation for the site reliability engineers. We don't believe that site reliability engineers needs to go away or can even be replaced anytime soon. We definitely think that we can help them understand better and faster what is the type of problems that they see in their production environments and then help them resolve that much faster and better. Yeah, absolutely. You know, we're huge supporters of really the best solutions are when you have the people plus machines. There's certain things the machines are going to do on their own, but it's the marrying. So help us understand where, you know, who's going to be using New Relic AI, you know, how is it going to change their day-to-day life? And, you know, maybe even kind of organizationally, what would the impact will be? Sure. So if you're a site reliability engineer or a DevOps team depending on how you want to call yourself and, you know, there's a big debate in the industry, whether it's DevOps or site reliability engineers, pretty much anyone who's responsible for uptime in the digital production environments, you're a relevant user. If you carry the pager, if you on-call, you're a relevant user. So you're going to be interacting with the system to be able to actually see what are the problems with potential recommendations, and then you can infuse the system with your own logic. Whether it's based on the logic, we also provide very easy user experience with like thumbs up, thumbs down, different types of feedbacks as part of the workflow. And I think the most important piece is that we are connecting to users where they are, meaning we don't believe we need to change the workflows. So if you're a user and you're already using with a specific incident management providers, and you've already connected some of the additional monitoring tools to those providers, we now offer you a streamline of syncing to those incident management platforms and then enriching them with all of the information that we already have on the platform. So, we've talked about AI, but let's talk a little bit of AIOps. So, I've talked to a number of the vendors, I actually went to an AIOps conference earlier this year, and some of the talk track was APMs the old way. AIOps is going to replace what you were doing before. Let's take all your scattered tools and consolidate them down. Some of the messaging reminds me of what I heard this morning. It's, you know, the New Relic One platform is going to replace a number of tools, pull everything together, help us kind of, you know, square that circle of APM and AIOps and where you see New Relic compared to some of those competitors out there today. Sure. So, APM is application performance monitoring. It's all about monitoring and have that visibility to your application layer. It has nothing to do with AIOps. It has nothing to do with replacing the tools. We believe that everyone should have visibility into their application, and that's a lot of that messaging came through Luz Kino this morning and opening it up to any type of open source instrumentation so we can bring it to the platform. Whether you want to drop an agent, whether you want to use any other open source SDK, we allow you to do that. Pretty much opening up the platform, giving you the option. AIOps is a term coined by Gardner actually and it is pretty much applying some automation, AI capabilities, ML capabilities, statistical analysis capabilities on huge amount of data that you have in a centralized place. It has nothing to do with the monitoring percent. So, I definitely think that the industry is going into a new space where there is a consolidation obviously with different vendors. I believe that Neuraliq is giving customers the choice to make whether they want to go and continue using their old tools, and that's okay, and we are an open platform so we will sync up with their data as part of Neuraliq AI will be able to bring in the new data, whether by again interconnecting with their incident management platform or through a REST API or native integrations, or if customer choose to do that, they can just send us all of the data directly and then we apply the AIOps capabilities on top of the existing platform. So, it's really opening up for the choice of the customer. All right, it's been less than a year since the acquisition of Signify. We know that some of the things when you do an acquisition, it's an area of investment, you're going to have more resources, more people, but you've mentioned customers a couple of times. Maybe give us a little bit of insight as to how the customer conversations have changed now working for Neuraliq as opposed to being a customer and understanding that piece of the Neuraliq ecosystem. Oh, absolutely, I think as you transition from a small startup into a company like Neuraliq, you get much more exposure to enterprise customer, your scaling capabilities are much better. So, we're in serious conversations with a lot of the enterprise customers that have a lot of interest in what we do. A lot of it is part of the brand recognition and all of the great capabilities that Neuraliq has already. And then, marinate that with all of the capabilities that we're bringing or that we brought into Neuraliq as a young startup with all the latest technologies and a lot of the AI capabilities which are truly innovative ones. So, definitely see a lot of traction from the enterprise customers and the more sophisticated ones as well. All right, so the solution announced today is in beta. Give us a little bit of a look forward as to what we should expect to see and what feedback you're hoping to get from customers along the way and how they might get engaged if they want to. Yeah, so definitely we are in beta today. We've engaged with customers prior to the beta so we already got a lot of feedback and great feedback and we make some tweaks to the product based on that. We're actually announcing a GA of a small feature today which is Enhanced Incident Context which provides you active detection for time series data all the way to your Slack channels. But the overall solution is currently in beta and as we are progressing within every month we're going to get more and more customers engaging with the platform and then we're going to release a much more advanced capabilities even than what we have today in GA coming early next year. All right, great. Last thing, big mention and push about observability this morning. Help us understand where AI fits into the broader discussion of observability. So again, as I mentioned before the observability will allow you to see all of your data in a centralized place. So it's combining metrics, events, logs and traces in a specific place that now algorithms and different techniques such as AI and ML based algorithms really, really be successful in gathering understanding because you have all of that different information for the human brain. It's very hard to actually go and crawl and kind of ingest all of that vast amount of different data points from machines, they're very good at that. You know, they're starving for broad amount of data. And so having that capability building on top of a true observability platform is what makes the AI and ML so successful and drive value to customers in really understanding what the data means. All right, well, Guy, thank you so much for sharing. Best of luck on the journey towards GA for the full New Relic AI in the future. We look forward to watching. Thank you so much. All right, and lots more here, walking through at New Relic Future Stack 2019 here in New York City. I'm Stu Miniman and thanks for watching theCUBE.