 From around the globe, it's theCUBE with digital coverage of AIOps Virtual Forum, brought to you by Broadcom. Welcome to our final segment today. So we've discussed today the value that AIOps will bring to organizations in 2021, but we've discussed that through three different perspectives. And so now we want to bring those perspectives together and see if we can get a consensus on where AIOps needs to go for folks to be successful with it in the future. So bringing back some folks, Rich Lane is back with us, senior analysts serving infrastructure and operations professionals at Forrester. Usman Nasir is also back, global product management at Verizon. And Srinivasan Rajagapal, head of products and strategy at Broadcom. Guys, great to have you back. So let's jump in and Rich, we're gonna start with you, but we are gonna give all three of you a chance to answer the questions. So Rich, we've talked about why organizations should adopt AIOps, but what happens if they choose not to? What challenges would they face? Basically, what's the cost of organizations doing nothing? Yeah, it's a really good question because I think in operations for a number of years, we kind of stand, stood Pat where we were, we're afraid to change things sometimes or we just don't think about it tooling as often the last thing to change because we're spending so much time doing project work and modernization and fighting fires on daily basis. That problem is going to get worse if we do nothing. We're building new architectures like containers and microservices, which means more things to mind and keep running. We're building highly distributed systems where we're moving more and more into this hybrid world and a multi-cloud world. It's become over complicated. And I'll give a short anecdote, I think I'll illuminate this. When I go to conferences and give speeches, it's all infrastructure operations people. When I say, how many people have 3X, 5X, things to monitor than they had three years ago, two years ago and everyone's hand goes up. How many people have hired more staff in that time period? Zero hands fill up. That's the gap we have to fill. We have to fill that through better automation, more intelligent systems. It's the only way we're going to be able to fill back out. Nishmin, what's your perspective if organizations choose not to adopt AI ops? Sorry, was it for me? Yeah, it was for you. So I'll do that. I have to do a poll with the name. Yeah, so I think it's, I was just related to a couple of things that probably everybody has heard of lately and everybody can relate to. And this would resonate that we have 5G, which is all set to transform the world as we know it. The world of communication with these smart cities, smart communities, IOT, which is going to become pivotal to the success of businesses. And as we've seen with this COVID transformation of the world, that there's a much bigger cost consciousness out there. People are trying to become much more forward-looking, much more sustainable. And I think it's the heart of all of this, that the necessity that you have intelligent systems which are rationalizing more than enough information that previously could have been overlooked because of, you know, mental engagement, not going right, people not being on the same page. I'm just using two examples for hundreds of things, you know, that play a part in things that not coming together in the best possible way. So I think it is an absolute necessity to drive those cost efficiencies rather than, you know, left, right and center laying off people who are like pivotal to your business and have a great, private knowledge of your business, so to speak. You can drive these efficiencies through automating a lot of those tasks that previously were being very manually intensive or resource intensive. And you could allocate those resources towards doing much better things, which let's be very honest, going into 2021 after what we've seen with 2020 is going to be mandatory. And so Raj, I saw you shaking your head there when Usman was sharing his thoughts. What are your thoughts about this? Sounds like you agree. Yeah, I mean, you know, to put things in perspective, right? I mean, we are firmly in the digital economy, right? Digital economy, according to the Bureau of Economic Analysis is 9% of the US GDP. Just, you know, think about it in the context of the GDP, right? It's only ranked lower, slightly lower than manufacturing, which is at 11.3% GDP and slightly above finance and insurance, which is about seven and a half person GDP. So the digital economy is firmly in our lives, right? And as Usman was talking about it, you know, software eats the world and digital operational excellence is critical for customers to, you know, to drive profitability and growth in the digital economy. It's almost, you know, the key is digital at scale. So when Rich talks about some of the challenges and when Usman highlights 5G as an example, those are the things that come to mind. So to me, what is the cost or perils of doing nothing? You know, it's not an option, I think. You know, more often than not, you know, C-level execs are asking their head of IT and their key influencers a single question. Are you ready? Are you ready in the context of addressing spikes in networks because of the pandemic scenario? Are you ready in the context of automating a wave toil? Are you ready to respond rapidly to the needs of the digital business? I think AIRs is critical. That's a great point, Raj. We're gonna stick with you. So we got kind of consensus there, as you said, wrapping it up. This is basically not an option. This is a must to go forward for organizations to be successful. So let's talk about some quick wins. Raj, you talked about, you know, organizations and C-levels asking, are you ready? What are some quick wins that organizations can achieve when they're adopting AIRs? You know, immediate value, I think I would start with a question. How often do your customers find problems in your digital experience before you do? Think about that, right? You know, if you, you know, there's an interesting website, you know, downdetector.com, right? I think in Europe, there's an equivalent of that as well. It, you know, people post the digital services that are down, whether it's a bank that we, you know, customers are trying to move money from checking account to savings account and that digital services are down and so on and so forth. So some, and many times, customers tend to find problems before IT operation teams do. So a quick win is to be proactive. An immediate value is visibility. If you do not know what is happening in your complex systems that make up your digital supply chain, it's going to be hard to be responsive. So I would start there. Great advice, visibility. Usman, same question over to you from Verizon's perspective, quick wins. Yeah, so I think first of all, there's a need to ingest this multi-layered, multi-spectrum data, which I don't think is humanly possible. You don't have people having expertise, you know, at all seven layers of the U.S.I. model and then across network and security and at the application level. So I think you need systems which are now able to get this data. It shouldn't just be wasted reports that you're paying for on a monthly basis. You know, it's about time that you started making the most of those in the form of identifying, what are the efficiencies within your ecosystem? First of all, what are the things, you know, which could be better utilized? Subsequently, you have the opportunity to reduce the noise of trouble-ticket handle. It sounds pretty trivial, but as an average, you can imagine every trouble-ticket has a cost in dollars, right? So, and there's so many tickets and alerts that get created on a network and across an end-user application value chain, we're talking thousands, you know, across an end-user application value chain could be millions in a year. So, and so many of those are not really, you know, a cause of concern because the problem is somewhere else. So I think that whole triage is an immediate, you know, cost saving and the bigger your network, the bigger the cost savings, whether you're a provider, whether you're, you know, the end customer at the end of the day, not having to deal with problems which nobody can resolve, which are not meant to be dealt with. There's so many of those situations, right? Service has just been adopted, which is just foreign quality, et cetera, et cetera. So many reasons. So those are some of the immediate cost savings and they are really, really significant. Secondly, I would say Raj mentioned something about, you know, this end-user application value chain and an understanding of that, especially with this hybrid cloud environment, et cetera, et cetera, right? The time it takes to identify a problem in an end-user application value chain across the seven layers that I mentioned of the OSI reference body, across network and security and the application environment, it's something that in its own self has massive cost to business, right? There could be point-of-sale transactions that could be obstructed because of this, there could be, and I'm going to use a very interesting example. When we talk IoT, the integrity of the IoT machine is extremely pivotal in this new world that we're stepping into. You could be running commands, which are super efficient. Yes, everything is being told to the machine really fast. We're sending everything there. What if it's hacked? And it's that robotic arm starts to involve the things you don't want it to do. So there's so much of that that becomes a part of this naturally. And I believe, yes, this is not just like from a cost-saving standpoint, but anything going wrong with that code base, et cetera, et cetera. These are massive costs to the business in the form of the revenue they have lost, the perception in the market as a result of all that stuff. So these are a couple of very immediate ones, but then you also have the whole play of virtualized resources, where you can automate the allocation, the quantification of an orchestration of those virtualized resources, rather than a person having to see something and then say, oh yeah, I need to increase capacity over here because then it's going to help this particular application. You have systems doing this stuff. And to, you know, Raj's point, your customer should not be identifying your problem before you because this digital world is all about perception. Absolutely, we definitely don't want the customers finding it before. So Rich, let's wrap this particular question up with you. From that senior analyst perspective, how can companies make big impact quickly with AI ops? Yeah, I think, you know, and it was really summed up some really great use cases there, I think, with the, you know, one of the biggest struggles we've always had in operations isn't, you know, the mean time to resolve or pretty good at resolving the things. We just have to find the thing we have to resolve. That's always been the problem. And using these advanced analytics and machine learning algorithms now across all machine and application data, our tendency as humans is to look at the console and say, what's flashing red? That must be what we have to fix. But it could be something that's yellow, somewhere else six services away. And we have made things so complicated. And I think this is what Ushman was saying, that we can't get there anymore on our own. We need help to get there. And all of this stuff that he outlined, so well, builds up to a higher level thing of what is the customer experience about? What is the customer journey? And we've struggled for years in the digital world measuring that and day to day thing. We know in online retail, if you're having a bad experience at one retailer, you just want your thing. You're going to go to another retailer. Brand loyalty isn't what it was in the brick and mortar world where you had a department store near you. So you were loyal to that because it was in your neighborhood online. That doesn't exist anymore. So we need to be able to understand a customer from that first moment they touch a digital service all the way for their journey through that digital service, the lowest layer, whether it be a database or the network, what have you, and then back to them again. And we understand, is that a good experience we gave them? How does that compare to last week's experience? What should we be doing to improve that next week? And I think companies are starting and then the pandemic certainly pushed this timeline. If you listen to the CEO of Microsoft, he's like 10 years of digital transformation been done in the first several months of this. In banks and financial institutions, I talked to insurance companies aren't slowing down. They're trying to speed up, in fact. What they've discovered is that they're, obviously when we were on lockdown or what have you, the use of digital service is spiked very high. What they've learned is they're never going to go back down. They're never going to return to pre-tentative levels. So now they're stuck with this new reality. Well, how do we service those customers and how do we make sure we keep them loyal to our brand? So they're looking for modernization opportunities. A lot of that, that things have been exposed. And I think Raj touched upon this very early in the conversation is visibility gaps. Now that we're on the outside looking in at the data center, we know we architect things in a very specific way. We need better ways of making these correlations across disparate technologies to understand where the problems lie. So we can give better services to our customers. And I think that's really where we're going to see a lot of the innovation and the people really clamoring for these new ways of doing things. Starting now, I mean, I'm seeing it in customers, but I think really the push through the end of this year to next year when economy and things like that straighten out a little bit more, I think it really, people are going to take a hard look at where they are and is AI ops to wait forward for them. I think they'll find out the answers, yes, for sure. So we've come to a consensus that of what the perils are of organizations, basically the cost of doing nothing. You guys have given some great advice on where some of those quick wins are. Let's talk about something Raj touched on earlier is organizations, are they really ready for truly automated AI? Raj, I want to start with you. Readiness factor, what are your thoughts? You know, I think so. You know, we place our lives on automated systems all the time, right in our day to day lives. In the digital world, I think, you know, over at least the customers that I talked to, our customers are, you know, have sophisticated systems. Like for example, advanced automation is a reality. If you look at social media, AI and ML and automation are used to automate away misinformation, right? If you look at financial institutions, AI and ML are used to automate away fraud, right? So I want to ask our customers, why can't we automate away toil in IT operation systems, right? And that's where our customers are. And, you know, I'm a glass half full kind of a person, right? This pandemic has been harder on many of our customers. But I think what we have learned from our customers is they've rose into the occasion. They've used digital as a key means, right? At scale, that's what we see with, you know, when Usman and his team talk about, you know, network operational intelligence, right? That's what it means to us. So I think they are ready. The intersection of customer experience, IT and OT operational technology is ripe for automation. And, you know, I want to sort of give a shout out to three key personas in this mix. It's about people, right? One is the SRE persona, you know, site reliability engineer. The other is the information security persona. And the third one is the IT operator automation engineer persona. These folks in organizations are building a system of intelligence that can respond rapidly to the needs of their digital business. We at Broadcom, we are in the business of helping them construct a system of intelligence that will create a human augmented solution for them, right? So when I see, when I interact with large enterprise customers, I think they, you know, they want to achieve what I would call advanced automation and AI ML solutions. And that's squarely where AI ops is, you know, is going as in a, you know, when I talk to Rich and what everything that Rich says, you know, that's where it's going. And that's what we want to help our customers do. So Rich, talk to us about your perspective of organizations being ready for truly automated AI. I think, you know, the conversation has shifted a lot in the last, even pre-pandemic, say at the end of last year, we're, you know, two years ago, people, I've go to conferences and people come up and ask me like, this is all smoke and mirrors, right? These systems can't do this because it is such a leap forward for them for where they are today, right? We've sort of, you know, in software and other systems we iterate and we move forward slowly so it's not a big shock. And this is for a lot of organizations, a big, big leap forward in the way that they're running their operations teams today. But now they've come around and say, you know what, we want to do this. We want all the automations. We want my staff not doing the low complexity repetitive task over and over again. You know, and we have a lot of those because the legacy systems were not going to rebuild but they need certain care and feeding. So why are we having operations people do those tasks? Why aren't we automating those out? I think the other pieces, and I'll send this out to the operations teams that are thinking about going down this path is that you have to understand that the operations models that we're operating under in INO and have been for the last 25 years are super outdated and they're fundamentally broken for the digital age. We have to start thinking about different ways of doing things and how do we do that? Well, it's people, organization, people are going to work together differently in an AI ops world for the better. You know, there's going to be the age of the 40 person bridge call thing, troubleshooting is going away. It's going to be three, four, five focused engineers that need to be there for a particular incident. A lot of process, male across we have and now a level one, level two engineering, what have you running of tickets, gathering of artifacts during an incident is going to be automated. That's a good thing. We shouldn't be doing those things by hand anymore. So I'd say that the people start thinking about what this means to your organization. Start thinking about the great things we can do by automating things away from people and having to do them over and over again. And what that means for them, getting them back to what they want to be doing is high level engineering tasks. They want to be doing modernization, working with new tools and technologies. These are all good things that help the organization perform better as a whole. Great advice and great kind of some of the thoughts that you shared, Rich, for what the audience needs to be on the lookout for. Ruslan, I want to go over to you. Give me your thoughts on what the audience should be on the lookout for or put on your agendas in the next 12 months. So there's like a couple of ways to answer that question. One thing would be in the form of, what are some of the things they have to be concerned about in terms of implementing the solution or harnessing its power? The other one could be, what are the perhaps advantages they should look to see? So if I was to talk about the first one, let's say, that what are some of the things they have to watch out for? Like possible pitfalls that everybody has data, right? So yeah, there's one strategy which says, okay, you've got the data, let's see what we can do with them. But then there's the exact opposite side, which has to be considered venture doing that analysis. That is, what are the use cases that you're looking to try about, right? Within use cases, you have to understand, are you taking a reactive use case approach? Are you taking proactive use cases, right? For AI, that's a very, very important consideration. Then you have to be very cognizant of where does this data that you have, where does it reside? What are the systems? And where does it need to go to in order for this AI function to happen? And subsequently, if there needs to be any, you know, backward communication of all of that data in a process manner. So I think these are some of the very critical points because you could have an AI solution which is sitting in a customer data center. It could be in a managed services provider data center like, right, right. It could be in a cloud data center, like an AWS or something, or you could have hybrid scenarios, et cetera, all of that stuff. So you have to be very mindful of where you're going to get the data from. Where is it going to go to? What are the use cases you're trying to do? You have to do a bit of backward forward. Okay, we've got this data, these are use cases, and I think it's a journey. Nobody can come in and say, hey, you built this fantastic AI off thing. It's like Terminator 2. I think it's a journey where we built, starting with the network. My personal focus always comes down to the network and with 5G, so much, so much more, right? With 5G, you're talking low latency communication. That's like the true power of 5G, right? It's low latency, it's ultra high bandwidth, but what's the point of that low latency? It's then subsequently the actions that need to be taken to prevent any problems in critical application, IP application, remote surgeries, sub-driving vehicles, et cetera, et cetera. What if that's where people are sitting and sipping their coffees and trying to take action? That needs to be in low latency as well, right? So these are, I think some of the fundamental things that you have to know, your data, your use cases. The location, where it needs to be exchanged, what are the parameters around that for extending that data? And I think from that point onwards, it's all about realizing a sense of business outcome. Unless AI off comes in as a digital laborer that shows you, I have reduced you this amount of time in that the resolving problems or identified problems or anything. Or I have saved you this much resource, right? In a month, in a year or whatever timeline that people want to see it have. So I think those are some of the initial starting points and then it all starts coming together. But the key is it's not one system that can do everything. You have to have a way where you can share data. Once you've got all of that data into one system, maybe you can send it to another system and take more advantage of it, right? That system might be an AI and IoT system, which is just looking at all of your street lights and making sure that, hey, there switched off just to be more carbon, neutral and all that great stuff, et cetera, et cetera. A lot of folks, for the audience to consider. Raj, take us home from here. What are some of the takeaways that you think the audience really needs to be laser focused on as we move forward into the next year? One thing that I think a key takeaway is, as we embark on 2021, closing the gap between intent and outcome and outputs and outcome will become critical, is critical, especially for digital transformation at scale for organizations. Context for customer experience becomes even more critical. As Usman was talking, being network aware, network availability is a necessary condition, but not sufficient condition anymore, right? What customers have to go towards is going from network availability to network agility with high security, what we call app aware networks, right? How do you differentiate between a trade, a million dollar trade that's happening between London and New York versus YouTube video training that an employee is going through versus a YouTube video that millions of customers are watching, right? Three different context, three different customer scenarios, right? That is going to be critical. And last but not least, feedback loop. Responsiveness is all about feedback loop. You cannot predict everything, but you can respond to things faster. I think these are sort of the three things that customers are going to have to really think about. And that's also where I believe AIOps, by the way, AIOps, and one of the points that Usman showed out to what he was saying was heterogeneity is key, right? There is no homogeneous tool in the world that can solve problems. So you want an open, extensible system of intelligence that can harness data from disparate data sources, provide that visualization, the actionable insight, and the human augmented recommendation systems that are so needed for IT operators to be successful. I think that's where it's going. Amazing, you guys just provided so much content, context recommendations for the audience. I think we accomplished our goal on this, I'll call it power panel, of not only getting to a consensus of what, where AIOps needs to go in the future, but great recommendations for what businesses and any industry need to be on the lookout for. Rich, Usman, Raj, thank you for joining me today. Pleasure. Thank you. We want to thank you for watching. This was such a rich session. You probably want to watch it again. Thanks for your time.