 From around the globe, it's theCUBE with digital coverage of AIOps Virtual Forum, brought to you by Broadcom. Welcome to the AIOps Virtual Forum, I'm Lisa Martin. Excited to be talking with Rich Lane, now senior analyst serving infrastructure and operations professionals at Forrester. Rich, it's great to have you today. Hey, thank you for having me. I think this is going to be a really fun conversation to have today. It is, we're going to be setting the stage with Rich here for the IT operations challenges and the need for AIOps. That's kind of our objective here in the next 15 minutes. So Rich, talk to us about some of the problems that enterprise IT operations are facing now in this year that is 2020, and that are going to be continuing into the next year. Yeah, I mean, I think we've been on this path for a while with certainly the last eight months has accelerated this problem and brought a lot of things to light that people were going through the day-to-day firefighting as they're going all the way of life. It's just not sustainable anymore, the new highly distributed environment we're in, the need for digital services. And one of the things that's been building for a while really is in the digital age, we're providing so many of the interactions with customers online. We've added these layers of complexity to applications to infrastructure, we're in the cloud, we're a hybrid, we're multi-cloud, you need to use cloud-native technologies, we're using legacy stuff, we still have mainframe out there. It's just the vast amount of things we have to keep track of now and process and look at the data and signals from, it's just, it's really untenable for humans to do that in silos now. And when you add to that, when companies are so heavily invested regarding all the digital transformation power and it's accelerated so much in the last year or so, that we're getting so much for our business and revenue derived from these services that they become core to the business, they're not after thoughts anymore, it's not just about having a website presence, it's about deriving core business value from the services you're providing to your customers and a lot of cases, customers you're never going to meet or see at that. So it's even more important to be vigilant on top of the quality of that service that you're giving them. And then when you think about just the staffing issues we have, there's just not enough bodies to go around in operations anymore. We're not going to be able to hire, like we did 10 years ago even. So that's where we need the systems to be able to bring those operational efficiencies to bear. When we say operational efficiencies, we don't mean lessening headcount because we can't do that, they'll be foolish. What we mean is getting the headcount we have back to working on higher level things, working on technology refreshes and project work that brings better digital services to customers and get them out of doing the sort of low complexity, high volume tasks they're spending at least 20%, if not more on their day each day. So I think the more we can bring intelligence to bear and automation to take those things out of their hands, the better off we are going forward. And I'm sure those workers are wanting to be able to have the time to deliver more value, more strategic value to the organization, to their role. And as you're saying, is the demand for digital services is spiking, it's not going to go down. And as consumers, if we have another option and we're not satisfied, we're going to go somewhere else. So it's really about not just surviving this time right now. It's about how do I become a business that's going to thrive going forward and exceeding expectations that are now just growing and growing. So let's talk about AIOps as a facilitator of collaboration across business folks, IT folks, developers, operations. How can it facilitate collaboration, which is even more important these days? Yeah, so one of the great things about it is now, years ago by gone years, as they say, we would buy a tool to fit each situation. And somebody that worked in networking out of their school, somebody went into infrastructure from a Linux standpoint, have their tool, somebody from stores would have their tool. What we found was we would have an incident, a very high impacting incident occur. Everybody would get on the phone, 20, 30 people, all be looking at their silo tool, their silo pieces of data. And then we'd still have to try to link point A to B to C together just through institutional knowledge. And there was just ended up being a lot of gaps there because we couldn't understand that a certain thing happening over here was related to an event over here. Now when we bring all that data into one umbrella, one data lake, whatever we want to call it, apply the smart analytics to that data and normalize that data in a way we can contextualize it from point A to point B all the way through the application infrastructure stack. Now the conversation changes. Now the conversation changes to here is the problem. How are we going to fix it? And we're getting there immediately versus three, four, five hours of hunting and pecking and looking at things and trying to extrapolate what we're seeing across disparate systems. And that's really valuable. And what that does is now, we can change the conversation for measuring things in sort of a rough time and data center performance metrics as to how are we performing as a business? How are we overall and in real time, how is it in business being impacted by a service disruption? We know how much money we're losing per minute, hour, what have you and what that translates into brand damage and things along those lines that people are very interested in that. And what is the effect of making decisions either from a product change side? If we're always changing the mobile apps and we're always changing the website, but do we understand what value that brings us or what negative impact that has? We can measure that now. And also sales marketing. They run a campaign. Here's your coupon for 12% off today only. What does that drive to us with user engagement? We can measure that now in real time. We don't have to wait for those answers anymore. And I think having all this data and understanding the cause and effect of things increases and enhances these feedback loops of we're making decisions as a business as a whole to bring better value to our customers. How does that tie into ops and dev initiatives? How does everything that we do, if I make a change to the underlying architecture, does that help move the needle forward? Does that hinder things? All these things factor into it and factor into customer experience, which is what we're trying to do at the end of the day. Whether operations people like it or not, we are all in the customer experience business now. And we have to realize that and work closer than ever with our business and dev partners to make sure we're delivering the highest level customer experience we can. Now customer experience is absolutely critical for a number of reasons. I always kind of think it's inextricably linked with employee experience. But let's talk about long-term value because as organizations and every industry have pivoted multiple times this year and will probably continue to do so for the foreseeable future, for them to be able to get immediate value that let's not just stop the bidding, but let's allow them to get a competitive advantage and be really become resilient. What are some of the applications that AIOps can deliver with respect to long-term value for an organization? Yeah, and I think that it's, and you touched upon this very important point that there is a set of short-term goals you want to achieve, but they're really going to be looking towards 12, 18 months down the road, what is it going to have done for you? And I think this helps framing out for you what's most important because it'll be different for every enterprise. And it also shows the ROI of doing this because there is some change that's going to be involved and things you're going to have to do. But when you look at the longer time horizon and what it brings to your business as a whole, to me at least it all seems like a no-brainer to not do it. Think about the basic things like faster remediation of client impacting incidents or maybe even predictive sort of detection of these incidents that will affect clients. So now you're getting at scale, it's very hard to do when you have hundreds of thousands of objects of the management that relate to each other. But now you're letting the machines in the intelligence layer find out where that problem is. It's not the red thing, it's the yellow thing, go look at that. It's reducing the amount of finger pointing and what have you like what's going between teams. Now everybody's looking at the same data, the same sort of symptoms and like, oh yeah, okay, this is telling us, here's the root cause, you should investigate this. Huge, huge thing. And it's something we never thought we'd get to where the systems we smart enough to tell us these things but this again, this is the power of having all the data to one umbrella in the smart analytics. And I think really, it's about, if you look at where infrastructure and operations people are today and especially eight months and nine months, whatever it is into the pandemic, a lot of them are getting really burnt out with doing the same repetitive tasks over and over again. Just trying to keep the lights on. We need to extract those things from those people just because it just makes no sense to do something over and over again, the same remediation step just we should automate those things. So getting that sort of a drudgery off their hands if you will and get them into other important things they should be doing. They're really hard to solve problems. That's where the human shine and that's where having a really high level engineers that's what they should be doing. And just being able to do things, I think in a much faster and more efficient manner when you think about an incident occurring in a level one technician picks that up and he goes in triage, maybe run some tests he has a script or she and they open a ticket they enrich the ticket, they call some log files they go look up through the server zone year and an hour and a half into an incident before anyone's even looked at it. If we could automate all of that, why wouldn't we? That makes it easier for everyone. And I really think that's where the future is is bringing this intelligent automation to bear to take, knock down all little things that consume really the most amount of time when you think about it. If you aggregate it over the course of like a quarter or a year, a great deal of your time is spent just doing that minutia. Again, why don't we automate that we should. So I really think that's where you're gonna look in the longterm, I think also the sense of we're going to be able to measure everything in the sense of business KPIs versus just IT centered KPIs. That's really where we gotta get to in the digital age. And I think we've waited too long to do that. I think our operations models are outmoded. I think a lot of the KPIs we look at today are completely outmoded. They don't really change. If you think about it, we look at the monthly reports over the course of the year. So let's do something different and now having all this data and smart analytics we can do something different. Absolutely. I'm glad that you brought up kind of looking at the impact that AIOps can make on minutia and burnout. That's a really huge problem that so many of us are facing in any industry. And we know that there's some amount of this that's gonna continue for a while longer. So let's leverage intelligent automation as your point because we can to be able to allow our people to not just be more efficient but to be making a bigger impact. And there's that mental component there that I think is absolutely critical. I do want to ask you, what are some of these? So for those folks who are, we've got to do this. It makes sense. We see some short-term things that we need. We need short-term value. We need long-term value as you've just walked us through. What are some of the obstacles that you take? Hey, be on the lookout for this to wipe it out of the way. Yeah. And I think there's, you know, when you think about the obstacles I think people don't think about what a big change is for their organization, right? You know, they're going to change process. They're going to change the way teams interact. They're going to change a lot of things but they're all for the better. So what we're traditionally really bad in infrastructure operations is communication, marketing a new initiative, right? We don't go out and get our peers agreement to it whoever the project owner is, you know, and say, okay, this is what it gets you. This is what it changes. People just hear, I'm losing something. I'm losing control over something. You're going to get rid of the tools that I have that I love, I've spent years building out and perfecting. And that's threatening to people. And understandably so, because people think if I start losing tools, I start losing headcount and then where's my department at that point? But that's not what this is all about. This isn't a replacement for people. This isn't a replacement for teams. This is an augmentation. This is getting them back to doing the things they should be doing and less of the stuff they shouldn't be doing. And frankly, it's about providing better services. So in the end, it's counterintuitive to be against it because it's going to make IT operations look better. It's going to show us that we are the thought leaders in delivering digital services, that we can constantly be perfect in the way we're doing it. And oh, by the way, we can help the business be better also at the same time. I think some of the mistakes people really do make is not looking at their processes today, trying to figure out what they're going to look like tomorrow when we bring in advanced automation and intelligence, but also being prepared for what the future state is. In talking to one company, they were like, yeah, we're so excited for this. We got rid of our 15-year-old monitoring system and the same day we stepped a new system. One problem we had though was we weren't ready for the amount of incidents that had generated on day one. And it wasn't because we did anything wrong or the system was wrong or what have you. It did the right thing actually, almost too well. What it did is it uncovered a lot of really small incidents through advanced correlations we didn't know we had. So there was things lying out there that were always like, that's weird that system acts strange sometimes, but we can never pin it down. We found all those things, which is good, but it kind of made us all kind of sit back and think and then our leadership, these guys doing their job right. And then we had to go through an evolution of just explaining, we were 15 years behind from a visibility standpoint into our environment, but technologies that we deployed and applications had moved ahead and modernized. So this is like a cautionary tale of falling too far behind from a sort of monitoring intelligence and automation standpoint. So I thought that was a really good story for something to think about as you go and deploy these modern systems. But I think if you really, the marketing to people so they're not threatened, I think thinking about your process and then what's your day one and then it would look like and then what's your six and 12 months after that looks like, I think settling all that stuff upfront just sets you up for success. All right, Rich, take us home here. Let's summarize, how can clients build a business case for AIOps? What do you recommend? Yeah, I actually get that question a lot and it's usually almost always the number one question in webinars like this and conversations that the audience puts in. So I wouldn't be surprised if that was true going forward from this one. Yeah, people are like, hey, we're all in. We want to do this. We know this is the way it forward, the guy who writes the checks, the CIO, the VP of ops is like, I've signed lots of checks over the years for tools, why is this different? And what I guide people to do is to sit back and start doing some hard math, right? One of the things that resonates with the leadership is dollars and cents, it's not percentages. So saying, it brings us a 63% reduction and MTTR is not going to resonate. Oh, even though it's a really good number. I think what it is, you have to put it in terms of if we could avoid that 63%, right? You know, what does that mean for our digital services as far as revenue, right? We know that every hour or system down, I think typically in the market you see is about $500,000 an hour for enterprise will add that up over the course of the year while you're losing revenue. Add to that brand damage, loss of customers, Forester puts out a really big customer experience index every year that measures that. If you're delivering good digital services, bad digital services, if you could raise that up, what does that return to you in revenue? And that's a key thing. And then you just look at the hours of loss productivity I call it, I might call it something else but I think that's a catchy name. Meaning if a core internal system is down, say, and you know you have a customer service desk of a thousand customer service people and they can't do that lookup or fix that problem for clients for an hour, how much money does that lose you? And you multiply it out, average customer service desk, a person makes X amount of an hour, times this amount of time, this many times it happens. Then you start seeing the real sort of power of AI ops for this incident avoidance or at least lowering the impact of these incidents. And people have put out in graphs and spreadsheets and all this and I'm doing some research around this actually too to put out something that people can use to say the project funds itself in six to 12 months it's paid for itself and then after that it's returning money to the business. Why would you not do that? And when you start framing the conversation that way, little light bulbs turn on for the people and it's just on the tracks for sure. That's great advice for folks to be thinking about. I love how you talked about 63% reduction and something you think that's great. What is it impact? How does it impact the revenue for the organization? If we're avoiding costs here, how do we drive up revenue? So having that laser focus on revenue is great advice for folks in any industry looking to build a business case for AI ops. I think you set the stage for that rich beautifully and you were right, this was a fun conversation. Thank you for your time. Thank you. And thanks for watching.