 From around the globe, it's theCUBE with digital coverage of AIOps Virtual Forum, brought to you by Broadcom. Welcome back to the AIOps Virtual Forum, Lisa Martin here with Srinivasan Raju Gopal, the head of products and strategy at Broadcom. Raj, welcome. Good to be here, Lisa. I'm excited for our conversation. So I wanted to dive right into a term that we hear all the time, operational excellence. We hear it everywhere in marketing, et cetera. But why is it so important to organizations as they head into 2021? And tell us how AIOps as a platform can help. Yeah, thank you. First off, I want to welcome our viewers back and I'm very excited to share more info on this topic. Here's what we believe as we work with large organizations, we see all our organizations are poised to get out of the pandemic and look for a growth for their own business and helping customers get through this tough time. So Fiscal Year 2021, we believe is going to be a combination of resiliency and agility at the same time. So operational excellence is critical because the business has become more digital, right? There are going to be three things that are going to be more sticky. Remote work is going to be more sticky. Cost savings and efficiency is going to be an imperative for organizations. And the continued acceleration of digital transformation of enterprises at scale is going to be in reality. So when you put all these three things together as a team that's working behind the scenes to help the businesses succeed, operational excellence is going to be make or break for organizations. Raj, with that said, if we kind of strip it down to the key capabilities, what are those key capabilities that companies need to be looking for in an AIOps solution? Yeah, you know, so first and foremost, AIOps means many things to many, many folks. So let's take a moment to simply define it. The way we define AIOps is it's a system of intelligence, a human augmented system that brings together full visibility across app, infra and network elements that brings together disparate data sources and provides actionable intelligence and uniquely offers intelligent automation. Now, the analogy many folks draw is the self-driving car, right? I mean, we are in the world of Teslas. But self-driving data center is still far away, right? Autonomous systems are still far away. However, application of AI ML techniques to help deal with volume, velocity, veracity of information is critical. So that's how we look at AIOps and some of the key capabilities that we work with our customers to help them are around four areas, right? First one is eyes and ears, what we call full stack observability. If you do not know what is happening in your systems, that serve up your business services, it's going to be pretty hard to do anything in terms of responsiveness, right? So full stack observability. The second piece is what we call actionable insights. So when you have disparate data sources, tools, sprawls, data coming at you from database systems, IT systems, customer management systems, ticketing systems, how do you find the needle from the stack? And how do you respond rapidly from a myriad of problems, a sea of red? The third area is what we call intelligent automation. Well, identifying the problem to act on is important and then acting on automating that and creating a recommendation system where you can be proactive about it is even more important. And finally, all of this focuses on efficiency. What about effectiveness? Effectiveness comes when you create a feedback loop, when what happens in production is relayed to your support systems and your developers so that they can respond rapidly. So we call that continuous feedback. So these are the four key capabilities that you should look for in an AIOB system and that's what we offer as well. All right, Raj. So there's four key capabilities that businesses need to be looking for. I'm wondering how those help to align business and IT. It's again, like operational excellence, it's something that we talk about a lot. It's the alignment of business and IT. A lot more challenging is your sum and done, right? But I want you to explain how can AIOBs help with that alignment and align IT outputs to business outcomes. Yeah, so you know, one of the things, I'm going to say something that is simple but this harder, but alignment is not on systems. Alignment is with people, right? So when people align, when organizations align, when cultures align, dramatic things can happen. So in the context of AIOBs, we see when SREs align with the DevOps engineers and information architects and IT operators, they enable organizations to reduce the gap between intent and outcome or output and outcome. That said, these personas need mechanisms to help them better align, right? Help them better visualize, see the, what we call single source of truth, right? So there are four key things that I want to call out. When we work with large enterprises, we find that customer journey alignment with the, you know, what we call IT systems is critical. So how do you understand your business imperatives and your customer journey goals, whether it is car to purchase or whether it is, you know, bill shock scenarios and so on. Alignment on customer journey to your IT systems is one area that you can reduce the gap. The second area is how do you create a scenario where your teams can find problems before your customers do, right? Outage scenarios and so on. So that's the second area of alignment. The third area of alignment is how can you measure business impact driven services, right? There are several services that an organization offers as an IT system. Some services are more critical to the business than others. And these change in a dynamic environment. So how do you understand that? How do you measure that? And how do you find the gaps there? So that's the third area of alignment that we help. And last but not least, there are things like NPS scores and others that help understand alignment, but those are more long-term. But in the context of operating digitally, you want to use customer experience and a single business outcome as a key alignment factor and then work with your systems of engagement and systems of interaction along with your key personas to create that alignment. It's a people process technology challenge, actually. So Ros, one of the things that you said there is that it's imperative for the business to find a problem before a customer does and you talked about outages there. That's always a goal for businesses, right? To prevent those outages. How can AI apps help with that? Yeah. So outages go to the saliency of a system, right? And they also go to agility of the same system. If you're a customer and if you're whipping up your mobile app and it takes more than three milliseconds, you're probably losing that customer, right? So outages mean different things. There's an interesting website called downdetector.com that actually tracks all the outages of publicly available services, whether it's your bank or your telecom service or a mobile service and so on and so forth. In fact, the key question around outages from executives are the question of, are you ready, right? Are you ready to respond to the needs of your customers and your business? Are you ready to rapidly to solve an issue that is impacting customer experience and therefore satisfaction? Are you creating a digital trust system where customers can be, customers can feel that their information is secure when they transact with you? All of these get into the notion of resiliency in outages. Now, one of the things that I often work with customers that we find is the radius of impact is important when you deal with outages. What I mean by that is problems occur, right? How do you respond? How quickly do you take two seconds, two minutes, 20 minutes, two hours, 20 hours, right? To resolve that problem, that radius of impact is important. That's where you have to bring again people process technology together to solve that. And the key thing is you need a system of intelligence that can aid your teams. Look at the same set of parameters so that you can respond faster. That's the key here. But as we look at digital transformation at scale, Raj, how does AI apps help influence that? I'm going to take a slightly long-winded way to answer this question. See, when it comes to digital transformation at scale, the focus on business purpose and business outcome becomes extremely critical. And then the alignment of that to your digital supply chain, right? Are the key factors that differentiate winners in their digital transformation game, really? What we have seen with winners is they operate very differently. Like for example, Nike measures its digital business outcomes by shoes per second, right? Apple by iPhones per minute, Tesla by Model 3s per month. Are you getting it, right? I mean, you want to have a clear business outcome which is a measure of your business in effect. I mean, Etsy, right? Which my daughter use and I use very well, right? They measure by revenue per hour, right? I mean, so these are key measures. And when you have a key business outcome measure like that, you can align everything else because these measures for a bank, it may be deposits per month, right? Now, when you move money from checking account to savings account or when you do direct deposits, those are banks need liquidity and so on and so forth. But the key thing is that single business outcome has a starburst effect inside the IT organization that touches a single money movement from checking account to savings account can touch about 75 disparate systems internally, right? So those think about it, right? I mean, all you're doing is moving money from checking account to savings account. Now, that goes into our IT production system. There are several applications. There is a database. There are infrastructures. There are load balancers. There are web server components which then touches your middleware component which is a queuing system, right? Which then touches your transactional system which may be on your mainframes, what we call mobile to mainframe scenario, right? And we are not done yet. Then you have a security and regulatory compliance system that you have to touch. A fraud prevention system that you have to touch, right? A State Department regulation that you may have to meet and on and on and on, right? This is the challenge that IT operation teams face. And when you have millions of customers transacting, right? Suddenly this challenge cannot be, you know, managed by, you know, human beings alone. So therefore you need a system of intelligence that augments human intelligence and acts as, you know, your eyes and ears in a way to pinpoint where problems are, right? So digital transformation at scale really requires a well thought out AIOps system, a platform, an open, extensible platform that is heterogeneous in nature because there is tools problem in organizations. There is, you know, a lot of databases and systems. There are millions of, you know, customers and hundreds of partners and vendors, you know, making up that digital supply chain. So, you know, AIOps is at the center of enabling an organization, achieve digital transformation at scale. Last but not least, you need continuous feedback loop. Continuous feedback loop is the ability for a production system to inform your DevOps teams, your finance teams, your customer experience teams, your cost modeling teams about what is going on so that they can reduce the intent to outcome gap. All of this need to come together, what we call DevOps for ITOps. That was a great example of how you talked about the starburst effect. I actually never thought about it in that way when you give the banking example, but what you should is the magnitude of systems, the fact that people alone really need help with that and why intelligent automation and AIOps can be transformative and enable that scale. Raj, it's always a pleasure to talk with you. Thanks for joining me today. Great to be here. And we'll be right back with our next segment.