Ram Chakravarti, BMC | BMC Exchange VIP

This is texturong TV. Hey folks, we're at The BMC exchange event. We're talking about Innovation and then Pace in which it's coming and the question I have for you ROM as we start out here is is it coming too fast?

Is it not people seem to be struggling the keep up there like behind on several releases every time you wake up. There's yet another new innovation and I don't want to sound like the guy who's like telling everybody to get off. My lawn question is You know, is there some way to think about consuming this Innovation at this pace?

That's different that we should maybe investigate more fair enough. That's a great start and definitely not a softball mic. Yeah.

So the pace of innovation is certainly daunting, but let's Maybe Define what Innovation is right, it's we are in a in an era where there is so much change being manifested by way of new technology new and previously unavailable forms of data the connectivity and explosive growth in devices. And what have you and what's happening is in organizations our customers. The developers are basically as an example releasing a whole set of new apps and services at a faster pace and they're using new technologies ephemeral Technologies.

The operations folks have the burden of managing all of these and they don't know about some of these new architectures. So how do you basically manage all of these right? That's just one example of the challenge that you're facing from a whole bunch of things being trusted us to me innovation without customer adoption is useless.

So what we are focused on in BMC is basically what can we do to solve business problems with specific technologies that helps it easier for customers to adopt our Solutions. Case and point predictive service apps which you saw a short video of and a full length working demo is available at the marketplace Innovation with these exchange. This is about bringing together an existing set of BMC products as well as new incubations that we've developed in The BMC Innovation Labs bringing all of those together to help customers Auto manage these new applications and services rather than being overwhelmed by the burden of this proliferation of new technologies and a whole host of other things that they frankly cannot keep.

That's a philosophy. It used to be Innovation was primarily driven by a single vendor would get a bunch of Engineers together and something good might hopefully happen over a three to five year window. Or customers now coming to The Innovation lab and participating in the development process more and you're also for that matter seeing more open source software brought into this equation.

And that kind of is the primordial soup for a lot of this stuff. Yeah, all of the above the short answer but let me qualify it right. We established the BMC Innovation Labs back in February 2020.

I mean was impeccable one month before covid and then no customer was coming to us because they had serious problems to solve and Innovation was we've got existential things to solve for you guys have some interesting ideas, but they're going to put a pause on it like okay, that's fine. That makes sense. We were undaunted we went and built out things that we had a lot of faith in Fast Forward after the vaccines rolled out and everything.

We've had a flurry of co-innovations of customers I Define co-innovation in two buckets customer co-innovation and partner co-innovation and we have plenty of both. I'm going to be talking more about it tomorrow during my Keynotes each, but the principle is basically the same. Point about the one vendor versus multiple vendors and what have you our philosophy is it's not just about BMC products.

It's what is the solution that matters that addresses the business problem. The customer is trying to solve so we work with implementation Partners, we work with other independent software vendors, we work with hyperscalers to bring together a compelling integrated solution for that particular business problem that the customer is solving for that's the approach to go innovating with customers and with partners and we're super selective about the partners. They have to have that Innovation mindset and look at it in terms of what is the solution going to provide to the customer not so much in terms of okay.

This is a time and material project that I want to build the customer for that mindset doesn't work for us. We've seen it service management evolve many times over the last few decades today. We hear a lot about aiops devops you guys use the phrase service Ops, I think what how is itsm evolving?

What should we be thinking about here? And how do all these acronyms actually come together in some way that is consumable great question. So so let me demonstrate service Ops and try the other person be a puzzle pieces together.

Service Ops is simply Integrated Service and operations management using a common Foundation that has a common set of AI methods common persistence tier and common Services based on standard constructs, right so. The notion of Integrated Service and operations management is basically to provide an end-to-end solution for customers. a IO is a puzzle piece within service Ops aiops are simply AI for it operations, which is you had your traditional rules-based monitoring processes.

Now, you can apply specific AI methods to provide higher order insights on your underlying technology landscape. And that is AI for it operations and using AI for it operations along with across the entire Tech stack leads to what I call full stack observability that gives you greater insights with full stack observability you again use the appropriate AI method to take the right set of action remediation compliance patching whatever you need to take so that it kind of AI Ops enhances observability observability feeds AI obstetric take the right action. That's how we look at it.

And then there is a whole service context in the middle that brings together Integrated Service and operations management. With respect to devops what we talked about part of this mission of service operations is to enable the SRE Persona whose which is fundamentally important to the devops Continuum. So that's how we look at service operations or service Ops as an enabler of the SRE Persona where a judicious where the desired outcome is reliability and reliability is the right balance of agility or speed and quality.

So how can you release something at the requisite Pace without compromising on quality is what we are looking to solve for. Historically, we've had it administrators. They tended to work with graphical tools.

Now, we have Engineers that are starting to show up and they're using devops processes is this in either or equation or is it going to be more like an hand equation where the two of them have to kind of come together and collaborate in some way that's interesting that we haven't quite wrapped our arms around. Yeah. I I think it's an end.

It's not it developers and then it operation / administrators. The whole notion of devops was predicated on bridging that Gap right and then when devops by itself did not solve for that. That's what saw the rise in the image or their eyes of their sari Persona.

Then you bake insecurity into it because you want Institute the appropriate level of Automation and controls throughout your Dev process as well as your Ops process not as an afterthought, so that's what difficult comes in and that's all of this is predicated on the continuous shift left where you want automate with everything as cold to the EXT. That you can and the whole notion again is to be able to do that for faster release Cycles while balancing quality. That's how I see it.

We've Been talking in the business for I don't know four decades maybe more. Yeah. Do you think that as we make these changes that that divide is going to narrow or has narrowed and and how quickly will it continue to come together?

So the let's look at it in different buckets, right purchasing decisions on technology are not just the realm of it. The business is increasingly. In fact, the business is the decision maker for a whole steer of Technology investment decisions.

So from that standpoint that kind of collaborations already happening, but basically use a certain example to kind of underscore the point. if you Transpose to the whole data and analytics space. I my career was predominantly in that space from the date of days of data warehousing and bi to the current days of AI methods using data stores.

The likelihood of success has been relatively low 75% are thereabouts of data and analytics initiatives have not been successful for a variety of reasons and what the reason that multi-fold but one of the primary reasons is the inability to successfully scale upper and operationalize across the Enterprise so they succeed for one or two use cases, but then they fail when they try to do that so case in point data Ops has come into war as a practice that basically promises to improve the likelihood of success and data Ops is based on applying devops best practices to the field of data management. And how does it answer your question the person that so it's an integrated team across business and it works together on a set of data initiatives and the data Ops part is predicated on two things one is collaboration boring from the devops Mantra where you have a business product owner. So you have a business data product owner.

That's part of the team. I'm most Frank but you cannot get the point. The second is automation an automation is where we play a significant role because automation here refers to a couple of things one is data Pipeline orchestration, and we have control M which is the number one orchestration solution there and a lot of customers are using it for their complex data pipeline orchestration.

Second is the notion of business data observability. In other words. What is the line of sight that you have to data as it flows through the pipeline that informs your business person of the health performance issues and what have you and what insights can you provide so that's what we are solving for that will bring together the business and the IT folks from that plane and I can that's just illustrate the point of the broader set of must have collaboration business between business and it that is necessary for success.

Tina management is always been a challenge. I know very few organizations that would get a Good Housekeeping seal of approval that way they manage their data yet. We talk about data as the new oil but it seems like all our refineries are broken.

So how do we solve this problem? Yeah. So since you brought that up, I'll tell you I got I used to say data as the new bacon or data the new currency.

I definitely used data is a new oil. I managed to a friend people that think oil is not a good source of fuel. I've managed to piss off people that basically said, yeah currency your two monetary focused bacon.

Now, I'm a vegetarian vegan doesn't speak. So now I use data as a new Sunshine but kidding aside hopefully nobody complains about sunshine but kidding aside. To answer your question, right?

It's people really grapple with how to succeed in their data and analytics initiatives and solving for that has kind of been elusive. I think it's the right you really have to figure out. What is the business problem that you solving for?

What is the right set of data? What is a use case? What is the right set of data?

And then only look at what is the appropriate technology a lot of the reasons for the failure have been okay. I want to hone in on a particular platform which is going to give me an advana and then it's debt by technology pre-selection, right? There's so many things that go wrong in this Continuum, but it's really about honing in on what is the use case.

What is the desired outcome then roll back to what is the information said that I need? What is the right set of methods that I can apply to get the insights from this set of information and how do I do it in digestible rights, that would be my approach to solving this kind of conundrum. You cannot walk down the street these days without somebody claiming to have ai for this or AI for that we have algorithms.

They've been around forever and a day. We now have machine and deep learning. What should people expect from AI as we go forward what's real and what's not so if somebody comes and tells you use our AI solution, it's the best thing in the world guaranteed success tomorrow.

Let's snake oil sales. Right? What I would basically say is I mean AI is eventually going to improve upon our traditional approaches, but it requires a lot of help.

There's a lot of training data the methods have to be trained and for that you require a lot of historical data. So the basic premise for the most part in many use cases, I'm not counting deep learning and a bunch of other things but standard NLP or a bunch of traditional AI methods that are being applied. You have a set of historical data.

You apply that you have an AI method to solve a business problem. You basically figure it out or you program it. You apply the tray historical data as training data the model basically learns and then it starts looking at patterns.

And then you apply that pattern recognition to your new set of data and based on that storical data analysis. It's going to give you some results whether it's correlation or whether it's basically detecting anomalies or a bunch of other things. Use the data.

So my advice to customers is start slow take one or two use cases use training data. Learn what you can and you've got your traditional method. You've got your ai-based method.

Take them both out for a spin. If the AI method gives you over time certain percentage order of magnitude improved or improvement over your traditional method embrace. It don't just get taken in by the buzzword and don't expect instant success.

It's going to happen over a period of time. Do you think coming full circle on this conversation at the way that we have consumed it? Doesn't really lend itself to this new pace of innovation because we have a lot of products that we bought with an on-premise mindset and maybe we need to rethink.

What does a product what's the platform and maybe we're subscribing to things instead of buying and Licensing things. But is that all part of this Innovation conversation? It certainly is I think the couple of things happened, right?

So why are the hyperscalers why have they been successful because they help you? Deploy new architectures almost instantaneously on their infrastructure your time purchasing cycle time has gone down. You don't need to own and purchase your additional things on top.

If you're tradition your infrastructure, right you're sad solution or whatever Tech component you want to evolve they've deployed they've developed and deployed new architectures such as microservices containers and other things that can be easily consumable, right? So with all of these They've provided a mechanism for organizations to go and deploy things faster which runs counter to the traditional it approach of the last I mean, maybe 10 years back where okay, let's identify a problem. Let's identify set of requirements.

Let's go through a procurement cycle. Let's get something and then we'll roll this out 12 years back the paces. I mean you can't do that that pace is not available.

So you've got in many companies two camps, right one is the fast-paced and that's why digital transformation became what it is. Can we do will new products and services and roll them out at a pace that is desired by the business as opposed to the more traditional stuff, which is keep your lights on. Let me manage it the traditional way the two kind of coexist today, but I think the pace of innovation is going to dictate and mandate that it moves faster at a pace that the business basically screaming for.

through for a minute What is the one Innovation that you're most excited about right now? The one that if you know you were going to The Innovation Casino you'd place a bet on this and it said this is a winner. So there's a whole slew of things that you can innovate on right?

It's about finding for us. What is the right set of problem that we can solve that lends itself well to extending our knowledge, but it's still valuable to customers and for me that is Edge Computing and iot and the rational is simply as follows, right? BMC has been helping the largest most complex organizations manage their it assets for over 40 years.

We've taken that knowledge now each Computing has come in as a new paradigm where you're doing your there's been an explosive growth in devices and machines and components right connected devices and there's also been a significant increase in computing power. Can we take so the goal is to solve for managing those assets and harnessing that data? Or close to the source of that data or said otherwise add or close to the edge?

What does that mean? It's the same kind of problem for it Asset Management, except that it is not in central compute, which is what BMC has done traditionally, but it's more at Edge compute. So taking that knowledge a for it Asset Management.

We're applying it to OT asset management or operational technology Edge devices. And we had gunko about that. It's the same science sort of problems Edge data management Edge analytics Edge automation Edge asset lifecycle management all coupled with age security.

So that's what I'm betting big on. All right. Well, that's where we are.

Then we're gonna put everything on the edge and see what and it's not an edge or Cloud right? It's it's an additional parrot deployment Paradigm that adds to the already complex hybridity landscape and you have to solve for it. But the point is is we're now trying to process and analyze data at the point where it is being created and consumed.

Yes, and that's a whole other ball game. Absolutely. All right Ram.

Thanks. Come back Mike. Thank you.

It's a pleasure as always.