 From Washington DC, it's theCUBE, covering ScienceLogic Symposium 2019. Brought to you by ScienceLogic. Hi, I'm Stu Miniman, and this is theCUBE's coverage of ScienceLogic Symposium 2019, here at the Ritz-Carlton in Washington DC. Been 460 people here, just finished the afternoon keynote and they've actually gone off to the evening event. It's the yet to be finished spy museum. They get a good 360 view of Washington DC. The hallways are a little echoing and quiet, but really excited to have on the final guest of the day, Eric Rudin, who's the Vice President of Business Development and in Alliances at ScienceLogic. Eric, thanks so much for joining me. Thanks Stu, great to be here. All right, so BizDev and Alliances. I've talked to a number of your partners. I've gone through a lot of things, but you wear, I think, just like your CEO, a few different hats in your role. Let's get into what your role is at the company. Yeah, it's actually changed over time, but for the most part, I have two core responsibilities. One is I'm looking after our ecosystem of technology partners, and so we have some key strategics that we work with in the marketplace, in the cloud space, in the data center, all across the ecosystem, a lot of different technologies. But we also have products that we resale and put on our price list that combine to create a solution for our customers. The second half of what my responsibility is really focused on, what is our product strategy around integration automation? Because those are core components to our platform, and I look after that with several different teams. Yeah, so let's talk about the ecosystem person, the alliances, because I go to a lot of shows, I talk to a lot of companies, and it's all too easy for companies to be like, oh, we're the best, and we do so many different things, and when I first heard about the space in AIOps, it's like, oh, well, AIOps is replacing a lot of waves, and your average customer replaces 14 tools. I heard there's one customer that replaces 50 tools, but at the same time, there's a strong focus about integrations in deeper, even some of the products that you say, yeah, there's overlap, and that's competitive, you're working with those environments. So give us a little bit of the philosophy, how you balance that. We want to do it all and help our customers to do lots of different things, and especially when you get to big customers and service providers, we understand that it's a big world, and there never is that mythical single pane of glass. Yep, no, I totally agree, and we hear this a lot. I've got a tool for this, I've got a tool for that, or I had the vendor come in and say that they can do it all, and really at the end of the day, there's no one vendor, and the Venn diagrams of functionalities are overlapping. That's the nature of the industry, and when we saw this in the early days of IT with the big monopolies, but I think right now, it's around how do we solve the customer problem more effectively? From our perspective, we look at the combination of things. First is, what solutions out there give us good data, data that we can use, data that we can enrich, how we can leverage that to help drive better insights from other types of data that we collect. So this is where integration is a key part of this, and what we know is that ultimately in our space, what we're doing about monitoring a core collection, we're going to have to collect with everybody. So we're going to have to integrate with any partner that might have some form of IP or connected through an IP address to some sort of API. We need that data. So we have partnerships on that side. I think really what's interesting is when we think about things like workflow or orchestration or types of remediation, we might integrate with other technologies to enrich that data further. So we look for partners that ultimately our customers are using, things that we can do consolidation and drive better outcome with that enriched data experience. Yeah, so let's drill down one little bit. If you talk about like APM and ITSM tools out there, some recent announcements and you dig in deeper on there, what are some of the highlights? So one thing is if you already have like, agents are often come up, our customer says, well, I've got an APM agent that's already doing some things. Well, that's great, we can leverage that. There's some good insight that we can gather from either topologies or other metrics or like end user experience, but we also go deeper on other aspects like on the network side or on the infrastructure side or on the cloud services side. So ultimately it's a conversation of say, what can we leverage? What's accurate? What's in real time? And if there's things that we can gather, then that's our primary strategy. So I do think the ecosystem plays a key role in AI ops, but really to do that, it's around automation because anything that we do, we have to do it with scale and we have to do it with security. We have to do it with the intent of driving some form of outcome. And so those are the key principles behind selecting technology partners. Okay, let's talk some about that automation. It was a big discussion in the keynote this morning, really talking about the maturity model. One of the analysts up there says you really want to make sure you separate things like the machine learning piece of it with the automation. The observation I've made a couple of times is, yes we all know you can automate a really bad process and so I need to make sure, do I have good data and how am I making automation make me better and not just to change things? Yeah, well I think at ScienceLogs we look at automation as in every part of what we do within the product. From the collection of how we automate at scale, how we consolidate that data, and then we're doing a lot of the data preparation using automation technologies. And then when we start to analyze and enrich that data, we're also using other algorithmic approaches, for example, topology and context. So if we know that something's connected, we can drive an automation to make an inference. And that data then feeds into the final step, which is around how we action on that. So we drive automation in the classic sense to say trigger a workflow, or let's say update another system of record or system of truth like a CMDB or a notification. And so one of the things that we did hear from Gartner this morning is engaging in an ITSM process is a core part of AIOps as much as data collection and driving other forms of automation. All right, do you have some examples of how automations are helping your customers? Love any customer stories you've got along that line? Well, really, there are so many stories we're hearing in the halls of Symposium, and so it's hard to pick one, but I think oftentimes what we say is what's driving your service desk time? Like you've got people looking at all of these different disparate systems, and we can look at let's say a top end of your most sort of frequented events or alerts, or even look at your top service desk incidents and say, how can we automate that? And some of that automation could be at the technology level, as simple as restarting a service or reprovisioning a VM, or it could be clearing a log or even maybe shutting down an event because it's irrelevant. So there's several different examples in the cloud as well in terms of how things are provisioned and attached. And if we see something out of a policy, we can alarm that say, hey, maybe my storage costs are going to accelerate because someone made a bad change. So there's different ways that we can apply automation during the life cycle, but I think enhancing the service management component perhaps is one of the most impactful ones. Yeah, so, Eric, as an industry, automation's been something we've been talking about for quite a while now, and there's sometimes pushback from the end users, especially some of the practitioners out there as to, well, I can do it better, the fear that you're going to lose your job. How are you seeing that progressing and how are things different today, both from a technology standpoint as well as from your customer standpoint? I think if you asked any enterprise CIO or any service provider, service delivery manager, they'd always say, I'd love to operate as much as I can. When you get down to the practitioner level, obviously, I think there's some sort of like, I do my job, thank you very much, I have my favorite whip, my process. So I think there's a conversation depending on, if we're saying, hey, from the practitioner side, is there a set of data that you need or a set of scripts or things that you're doing manually that we can put into a workflow? And at the business layer, it's like, do you feel like you're getting the value from some of the investments you've made and how does automation help you realize that? An example there is, we see oftentimes is around the quality of data that's going into the CMDB. And from a lot of times, we see that their investment in technologies like ServiceNow and other platforms is a fairly high expense, and they want to optimize that, and they want to realize the power of automation at the service level. So if we can convince, if you will, through a set of really concrete use cases that the data coming from ScienceLogic at the speed and the quality can actually improve the CMDB to the level of really efficient automation, all of a sudden people start to see that as a change, as an opportunity. And that's where I think AIOps is helping change the narrative to say how automation can be really applied rather than just being this mystical concept that is hard to do. And people don't like to think that a robot's taking their job. I think what's gonna happen is is that machine learning algorithms are gonna make jobs easier. And ultimately, we're far, far from the point where AI is doing something in some sort of crazy automated way. But I think it's the deep learning, moving to machine learning, to good quality data sets that drive meaningful insights. That's giving us a lot better view onto where automation could play in the future. Yeah, absolutely. It's our belief that automation, there's certain things that you probably don't wanna do because they're repetitive, it's boring or it's mistake prone. And therefore, automation can really help those environments move forward. You can move up the stack, you can manage those environments. There's definitely some retraining that needs to happen often. But the danger is if you're doing now what you were doing five years ago, chances are your competition is moving along and finding a better way to do it. Just a point on this too, is really around the velocity of data that's coming in. So we're seeing, we talk about the three Vs, the volume of data. You have to use automation to be able to manage that huge amount of different data sources, the variety. There's no human that can process the amount of machine information from the amount of technologies that you have. And obviously it's the speed, the velocity. And that is clearly not gonna be something that any human could be capable of doing. And so there is a relationship here between technology and human processes. And ScienceLogic's in a really interesting position right now to really kind of help with that process, but more importantly, accelerate the value by being able to process it and make it intelligent. Wait, Eric, are you saying I'm not Neo from The Matrix and I can't read through everything and be able to move faster than physics allows? Give yourself maybe 15, 20 years. We might be, you know, that that, I don't think that that many people can really predict the impact of the, we'll say machine learning evolving to artificial intelligence. And there's, it's gonna be very use case specific, but we do know one thing is that algorithms are helping, but algorithms are dependent on that clean data stack, right? And if you can't handle the scale, then obviously there's gonna, it's gonna be minimized in terms of this total utility. All right, well, Eric, I get to let you give us the final word from ScienceLogic from Symposium 2019 on theCUBE. So, you know, the first thing is, there's two things that we learned from this event. The first thing is how are customers evolving in this dynamic space? And what we know is that if you don't change, it's gonna be a problem because the only consistent thing is change and change is happening faster in IT. And we call that disruption. And so what we wanna do is we wanna understand how ScienceLogic is a technology company can really help that customer go through that transition with confidence. And then more importantly is what can we do delivering better, more enriched solutions to our customers that actually are changing the way the game is played. And so we feel like we're a disruptor in the AOPS market. We are certainly foresters, helped us recognize that. But we're not done. We're continuing on this journey. All right, well, Eric Rudine, thank you so much for sharing your insights in the journey towards AOPS. Thanks so much, Stu. All right, well, that comes to an end of what we are doing here at ScienceLogic Symposium 2019. I know I learned a lot. I hope you did too. I'm Stu Miniman. Thanks so much from our whole crew here at SiliconANGLE Media's theCUBE. Check out theCUBE.net for all the videos from this show as well as where we'll be in the future. Reach out if you have any questions. And once again, thanks for joining us.