(Upbeat music playing) >> Hey everyone, thanks for joining us today. Welcome to this event of Building your Cloud Center of Excellence with Hitachi Vantara. I'm your host, Lisa Martin. I've got a couple of guests here with me next to talk about redefining cloud operations and application modernization for customers. Please welcome Prem Balasubramanian the SVP and CTO at Hitachi Vantara, and Manoj Narayanan is here as well, the Managing Director of Technology at GTCR. Guys, thank you so much for joining me today. Excited to have this conversation about redefining CloudOps with you. >> Pleasure to be here. >> Pleasure to be here >> Prem, let's go ahead and start with you. You have done well over a thousand cloud engagements in your career. I'd love to get your point of view on how the complexity around cloud operations and management has evolved in the last, say, three to four years. >> It's a great question, Lisa before we understand the complexity around the management itself, the cloud has evolved over the last decade significantly from being a backend infrastructure or infrastructure as a service for many companies to become the business for many companies. If you think about a lot of these cloud bond companies cloud is where their entire workload and their business wants. With that, as a background for this conversation if you think about the cloud operations, there was a lot of there was a lot of lift and shift happening in the market where people lifted their workloads or applications and moved them onto the cloud where they treated cloud significantly as an infrastructure. And the way they started to manage it was again, the same format they were managing there on-prem infrastructure and they call it I&O, Infrastructure and Operations. That's kind of the way traditionally cloud is managed. In the last few years, we are seeing a significant shift around thinking of cloud more as a workload rather than as just an infrastructure. And what I mean by workload is in the cloud, everything is now code. So you are codifying your infrastructure. Your application is already code and your data is also codified as data services. With now that context apply the way you think about managing the cloud has to significantly change and many companies are moving towards trying to change their models to look at this complex environment as opposed to treating it like a simple infrastructure that is sitting somewhere else. So that's one of the biggest changes and shifts that are causing a lot of complexity and headache for actually a lot of customers for managing environments. The second critical aspect is even that, even exasperates the situation is multicloud environments. Now, there are companies that have got it right with things about right cloud for the right workload. So there are companies that I reach out and I talk with. They've got their office applications and emails and stuff running on Microsoft 365 which can be on the Azure cloud whereas they're running their engineering applications the ones that they build and leverage for their end customers on Amazon. And to some extent they've got it right but still they have a multiple cloud that they have to go after and maintain. This becomes complex when you have two clouds for the same type of workload. When I have to host applications for my end customers on Amazon as well as Azure, Azure as well as Google then, I get into security issues that I have to be consistent across all three. I get into talent because I need to have people that focus on Amazon as well as Azure, as well as Google which means I need so much more workforce, I need so many so much more skills that I need to build, right? That's becoming the second issue. The third one is around data costs. Can I make these clouds talk to each other? Then you get into the ingress egress cost and that creates some complexity. So bringing all of this together and managing is really become becoming more complex for our customers. And obviously as a part of this we will talk about some of the, some of the ideas that we can bring for in managing such complex environments but this is what we are seeing in terms of why the complexity has become a lot more in the last few years. >> Right. A lot of complexity in the last few years. Manoj, let's bring you into the conversation now. Before we dig into your cloud environment give the audience a little bit of an overview of GTCR. What kind of company are you? What do you guys do? >> Definitely Lisa. GTCR is a Chicago based private equity firm. We've been in the market for more than 40 years and what we do is we invest in companies across different sectors and then we manage the company drive it to increase the value and then over a period of time, sell it to future buyers. So in a nutshell, we got a large portfolio of companies that we need to manage and make sure that they perform to expectations. And my role within GTCR is from a technology viewpoint so where I work with all the companies their technology leadership to make sure that we are getting the best out of technology and technology today drives everything. So how can technology be a good compliment to the business itself? So, my role is to play that intermediary role to make sure that there is synergy between the investment thesis and the technology lures that we can pull and also work with partners like Hitachi to make sure that it is done in an optimal manner. >> I like that you said, you know, technology needs to really compliment the business and vice versa. So Manoj, let's get into the cloud operations environment at GTCR. Talk to me about what the experience has been the last couple of years. Give us an idea of some of the challenges that you were facing with existing cloud ops and and the solution that you're using from Hitachi Vantara. >> A a absolutely. In fact, in fact Prem phrased it really well, one of the key things that we're facing is the workload management. So there's so many choices there, so much complexities. We have these companies buying more companies there is organic growth that is happening. So the variables that we have to deal with are very high in such a scenario to make sure that the workload management of each of the companies are done in an optimal manner is becoming an increasing concern. So, so that's one area where any help we can get anything we can try to make sure it is done better becomes a huge value at each. A second aspect is a financial transparency. We need to know where the money is going where the money is coming in from, what is the scale especially in the cloud environment. We are talking about an auto scale ecosystem. Having that financial transparency and the metrics associated with that, it, these these become very, very critical to ensure that we have a successful presence in the multicloud environment. >> Talk a little bit about the solution that you're using with Hitachi and, and the challenges that it is eradicated. >> Yeah, so it end of the day, right, we we need to focus on our core competence. So, so we have got a very strong technology leadership team. We've got a very strong presence in the respective domains of each of the portfolio companies. But where Hitachi comes in and HAR comes in as a solution is that they allow us to excel in focusing on our core business and then make sure that we are able to take care of workload management or financial transparency. All of that is taken off the table from us and and Hitachi manages it for us, right? So it's such a perfectly compliment relationship where they act as two partners and HARC is a solution that is extremely useful in driving that. And, and and I'm anticipating that it'll become more important with time as the complexity of cloud and cloud associate workloads are only becoming more challenging to manage and not less. >> Right? That's the thing that complexity is there and it's also increasing Prem, you talked about the complexities that are existent today with respect to cloud operations the things that have happened over the last couple of years. What are some of your tips, Prem for the audience, like the the top two or three things that you would say on cloud operations that that people need to understand so that they can manage that complexity and allow their business to be driven and complimented by technology? >> Yeah, a big great question again, Lisa, right? And I think Manoj alluded to a few of these things as well. The first one is in the new world of the cloud I think think of migration, modernization and management as a single continuum to the cloud. Now there is no lift and shift and there is no way somebody else separately manages it, right? If you do not lift and shift the right applications the right way onto the cloud, you are going to deal with the complexity of managing it and you'll end up spending more money time and effort in managing it. So that's number one. Migration, modernization, management of cloud work growth is a single continuum and it's not three separate activities, right? That's number one. And the, the second is cost. Cost traditionally has been an afterthought, right? People move the workload to the cloud. And I think, again, like I said, I'll refer back to what Manoj said once we move it to the cloud and then we put all these fancy engineering capability around self-provisioning, every developer can go and ask for what he or she wants and they get an environment immediately spun up so on and so forth. Suddenly the CIO wakes up to a bill that is significantly larger than what he or she expected right? And, and this is this is become a bit common nowadays, right? The the challenge is because we think cost in the cloud as an afterthought. But consider this example in, in previous world you buy hard, well, you put it in your data center you have already amortized the cost as a CapEx. So you can write an application throw it onto the infrastructure and the application continues to use the infrastructure until you hit a ceiling, you don't care about the money you spent. But if I write a line of code that is inefficient today and I deploy it on the cloud from minute one, I am paying for the inefficiency. So if I realize it after six months, I've already spent the money. So financial discipline, especially when managing the cloud is now is no more an afterthought. It is as much something that you have to include in your engineering practice as much as any other DevOps practices, right? Those are my top two tips, Lisa, from my standpoint, think about cloud, think about cloud work, cloud workloads. And the last one again, and you will see you will hear me saying this again and again, get into the mindset of everything is code. You don't have a touch and feel infrastructure anymore. So you don't really need to have foot on the ground to go manage that infrastructure. It's codified. So your code should be managing it, but think of how it happens, right? That's where we, we are going as an evolution >> Everything is code. That's great advice, great tips for the audience there. Manoj, I'll bring you back into the conversation. You know, we, we can talk about skills gaps on on in many different facets of technology the SRE role, relatively new, skillset. We're hearing, hearing a lot about it. SRE led DevSecOps is probably even more so of a new skillset. If I'm an IT leader or an application leader how do I ensure that I have the right skillset within my organization to be able to manage my cloud operations to, to dial down that complexity so that I can really operate successfully as a business? >> Yeah. And so unfortunately there is no perfect answer, right? It's such a, such a scarce skillset that a, any day any of the portfolio company CTOs if I go and talk and say, Hey here's a great SRE team member, they'll be more than willing to fight with each of to get the person in right? It's just that scarce of a skillset. So, so a few things we need to look at it. One is, how can I build it within, right? So nobody gets born as an SRE, you, you make a person an SRE. So how do you inculcate that culture? So like Prem said earlier, right? Everything is software. So how do we make sure that everybody inculcates that as part of their operating philosophy be they part of the operations team or the development team or the testing team they need to understand that that is a common guideline and common objective that we are driving towards. So, so that skillset and that associated training needs to be driven from within the organization. And that in my mind is the fastest way to make sure that that role gets propagated across organization. That is one. The second thing is rely on the right partners. So it's not going to be possible for us, to get all of these roles built in-house. So instead prioritize what roles need to be done from within the organization and what roles can we rely on our partners to drive it for us. So that becomes an important consideration for us to look at as well. >> Absolutely. That partnership angle is incredibly important from, from the, the beginning really kind of weaving these companies together on this journey to to redefine cloud operations and build that, as we talked about at the beginning of the conversation really building a cloud center of excellence that allows the organization to be competitive, successful and and really deliver what the end user is, is expecting. I want to ask - Sorry Lisa, - go ahead. >> May I add something to it, I think? >> Sure. >> Yeah. One of the, one of the common things that I tell customers when we talk about SRE and to manages point is don't think of SRE as a skillset which is the common way today the industry tries to solve the problem. SRE is a mindset, right? Everybody in >> Well well said, yeah >> That, so everybody in a company should think of him or her as a cycle liability engineer. And everybody has a role in it, right? Even if you take the new process layout from SRE there are individuals that are responsible to whom we can go to when there is a problem directly as opposed to going through the traditional ways of AI talk to L one and L one contras all. They go to L two and then L three. So we, we, we are trying to move away from an issue escalation model to what we call as a a issue routing or a incident routing model, right? Move away from incident escalation to an incident routing model. So you get to route to the right folks. So again, to sum it up, SRE should not be solved as a skillset set because there is not enough people in the market to solve it that way. If you start solving it as a mindset I think companies can get a handhold of it. >> I love that. I've actually never heard that before, but it it makes perfect sense to think about the SRE as a mindset rather than a skillset that will allow organizations to be much more successful. Prem I wanted to get your thoughts as enterprises are are innovating, they're moving more products and services to the as a service model. Talk about how the dev teams the ops teams are working together to build and run reliable, cost efficient services. Are they working better together? >> Again, a a very polarizing question because some customers are getting it right many customers aren't, there is still a big wall between development and operations, right? Even when you think about DevOps as a terminology the fundamental principle was to make sure dev and ops works together. But what many companies have achieved today, honestly is automating the operations for development. For example, as a developer, I can check in code and my code will appear in production without any friction, right? There is automated testing, automated provisioning and it gets promoted to production, but after production, it goes back into the 20 year old model of operating the code, right? So there is more work that needs to be done for Devon and Ops to come closer and work together. And one of the ways that we think this is achievable is not by doing radical org changes, but more by focusing on a product-oriented single backlog approach across development and operations. Which is, again, there is change management involved but I think that's a way to start embracing the culture of dev ops coming together much better now, again SRE principles as we double click and understand it more and Google has done a very good job playing it out for the world. As you think about SRE principle, there are ways and means in that process of how to think about a single backlog. And in HARC, Hitachi Application Reliability Centers we've really got a way to look at prioritizing the backlog. And what I mean by that is dev teams try to work on backlog that come from product managers on features. The SRE and the operations team try to put backlog into the say sorry, try to put features into the same backlog for improving stability, availability and financials financial optimization of your code. And there are ways when you look at your SLOs and error budgets to really coach the product teams to prioritize your backlog based on what's important for you. So if you understand your spending more money then you reduce your product features going in and implement the financial optimization that came from your operations team, right? So you now have the ability to throttle these parameters and that's where SRE becomes a mindset and a principle as opposed to a skillset because this is not an individual telling you to do. This is the company that is, is embarking on how to prioritize my backlog beyond just user features. >> Right. Great point. Last question for both of you is the same talk kind of take away things that you want me to remember. If I am at an IT leader at, at an organization and I am planning on redefining CloudOps for my company Manoj will start with you and then Prem to you what are the top two things that you want me to walk away with understanding how to do that successfully? >> Yeah, so I'll, I'll go back to basics. So the two things I would say need to be taken care of is, one is customer experience. So all the things that I do end of the day is it improving the customer experience or not? So that's a first metric. The second thing is anything that I do is there an ROI by doing that incremental step or not? Otherwise we might get lost in the technology with surgery, the new tech, et cetera. But end of the day, if the customers are not happy if there is no ROI, everything else you just can't do much on top of that >> Now it's all about the customer experience. Right? That's so true. Prem what are your thoughts, the the top things that I need to be taking away if I am a a leader planning to redefine my cloud eye company? >> Absolutely. And I think from a, from a company standpoint I think Manoj summarized it extremely well, right? There is this ROI and there is this customer experience from my end, again, I'll, I'll suggest two two more things as a takeaway, right? One, cloud cost is not an afterthought. It's essential for us to think about it upfront. Number two, do not delink migration modernization and operations. They are one stream. If you migrate a long, wrong workload onto the cloud you're going to be stuck with it for a long time. And an example of a wrong workload, Lisa for everybody that that is listening to this is if my cost per transaction profile doesn't change and I am not improving my revenue per transaction for a piece of code that's going run in production it's better off running in a data center where my cost is CapEx than amortized and I have control over when I want to upgrade as opposed to putting it on a cloud and continuing to pay unless it gives me more dividends towards improvement. But that's a simple example of when we think about what should I migrate and how will it cost pain when I want to manage it in the longer run. But that's, that's something that I'll leave the audience and you with as a takeaway. >> Excellent. Guys, thank you so much for talking to me today about what Hitachi Vantara and GTCR are doing together how you've really dialed down those complexities enabling the business and the technology folks to really live harmoniously. We appreciate your insights and your perspectives on building a cloud center of excellence. Thank you both for joining me. >> Thank you. >> For my guests, I'm Lisa. Martin, you're watching this event building Your Cloud Center of Excellence with Hitachi Vantara. Thanks for watching. (Upbeat music playing) (Upbeat music playing) (Upbeat music playing) (Upbeat music playing)

(Upbeat music playing) >> Hey everyone, thanks for joining us today. Welcome to this event of Building your Cloud Center of Excellence with Hitachi Vantara. I'm your host, Lisa Martin. I've got a couple of guests here with me next to talk about redefining cloud operations and application modernization for customers. Please welcome Prem Balasubramanian the SVP and CTO at Hitachi Vantara, and Manoj Narayanan is here as well, the Managing Director of Technology at GTCR. Guys, thank you so much for joining me today. Excited to have this conversation about redefining CloudOps with you. >> Pleasure to be here. >> Pleasure to be here >> Prem, let's go ahead and start with you. You have done well over a thousand cloud engagements in your career. I'd love to get your point of view on how the complexity around cloud operations and management has evolved in the last, say, three to four years. >> It's a great question, Lisa before we understand the complexity around the management itself, the cloud has evolved over the last decade significantly from being a backend infrastructure or infrastructure as a service for many companies to become the business for many companies. If you think about a lot of these cloud bond companies cloud is where their entire workload and their business wants. With that, as a background for this conversation if you think about the cloud operations, there was a lot of there was a lot of lift and shift happening in the market where people lifted their workloads or applications and moved them onto the cloud where they treated cloud significantly as an infrastructure. And the way they started to manage it was again, the same format they were managing there on-prem infrastructure and they call it I&O, Infrastructure and Operations. That's kind of the way traditionally cloud is managed. In the last few years, we are seeing a significant shift around thinking of cloud more as a workload rather than as just an infrastructure. And what I mean by workload is in the cloud, everything is now code. So you are codifying your infrastructure. Your application is already code and your data is also codified as data services. With now that context apply the way you think about managing the cloud has to significantly change and many companies are moving towards trying to change their models to look at this complex environment as opposed to treating it like a simple infrastructure that is sitting somewhere else. So that's one of the biggest changes and shifts that are causing a lot of complexity and headache for actually a lot of customers for managing environments. The second critical aspect is even that, even exasperates the situation is multicloud environments. Now, there are companies that have got it right with things about right cloud for the right workload. So there are companies that I reach out and I talk with. They've got their office applications and emails and stuff running on Microsoft 365 which can be on the Azure cloud whereas they're running their engineering applications the ones that they build and leverage for their end customers on Amazon. And to some extent they've got it right but still they have a multiple cloud that they have to go after and maintain. This becomes complex when you have two clouds for the same type of workload. When I have to host applications for my end customers on Amazon as well as Azure, Azure as well as Google then, I get into security issues that I have to be consistent across all three. I get into talent because I need to have people that focus on Amazon as well as Azure, as well as Google which means I need so much more workforce, I need so many so much more skills that I need to build, right? That's becoming the second issue. The third one is around data costs. Can I make these clouds talk to each other? Then you get into the ingress egress cost and that creates some complexity. So bringing all of this together and managing is really become becoming more complex for our customers. And obviously as a part of this we will talk about some of the, some of the ideas that we can bring for in managing such complex environments but this is what we are seeing in terms of why the complexity has become a lot more in the last few years. >> Right. A lot of complexity in the last few years. Manoj, let's bring you into the conversation now. Before we dig into your cloud environment give the audience a little bit of an overview of GTCR. What kind of company are you? What do you guys do? >> Definitely Lisa. GTCR is a Chicago based private equity firm. We've been in the market for more than 40 years and what we do is we invest in companies across different sectors and then we manage the company drive it to increase the value and then over a period of time, sell it to future buyers. So in a nutshell, we got a large portfolio of companies that we need to manage and make sure that they perform to expectations. And my role within GTCR is from a technology viewpoint so where I work with all the companies their technology leadership to make sure that we are getting the best out of technology and technology today drives everything. So how can technology be a good compliment to the business itself? So, my role is to play that intermediary role to make sure that there is synergy between the investment thesis and the technology lures that we can pull and also work with partners like Hitachi to make sure that it is done in an optimal manner. >> I like that you said, you know, technology needs to really compliment the business and vice versa. So Manoj, let's get into the cloud operations environment at GTCR. Talk to me about what the experience has been the last couple of years. Give us an idea of some of the challenges that you were facing with existing cloud ops and and the solution that you're using from Hitachi Vantara. >> A a absolutely. In fact, in fact Prem phrased it really well, one of the key things that we're facing is the workload management. So there's so many choices there, so much complexities. We have these companies buying more companies there is organic growth that is happening. So the variables that we have to deal with are very high in such a scenario to make sure that the workload management of each of the companies are done in an optimal manner is becoming an increasing concern. So, so that's one area where any help we can get anything we can try to make sure it is done better becomes a huge value at each. A second aspect is a financial transparency. We need to know where the money is going where the money is coming in from, what is the scale especially in the cloud environment. We are talking about an auto scale ecosystem. Having that financial transparency and the metrics associated with that, it, these these become very, very critical to ensure that we have a successful presence in the multicloud environment. >> Talk a little bit about the solution that you're using with Hitachi and, and the challenges that it is eradicated. >> Yeah, so it end of the day, right, we we need to focus on our core competence. So, so we have got a very strong technology leadership team. We've got a very strong presence in the respective domains of each of the portfolio companies. But where Hitachi comes in and HAR comes in as a solution is that they allow us to excel in focusing on our core business and then make sure that we are able to take care of workload management or financial transparency. All of that is taken off the table from us and and Hitachi manages it for us, right? So it's such a perfectly compliment relationship where they act as two partners and HARC is a solution that is extremely useful in driving that. And, and and I'm anticipating that it'll become more important with time as the complexity of cloud and cloud associate workloads are only becoming more challenging to manage and not less. >> Right? That's the thing that complexity is there and it's also increasing Prem, you talked about the complexities that are existent today with respect to cloud operations the things that have happened over the last couple of years. What are some of your tips, Prem for the audience, like the the top two or three things that you would say on cloud operations that that people need to understand so that they can manage that complexity and allow their business to be driven and complimented by technology? >> Yeah, a big great question again, Lisa, right? And I think Manoj alluded to a few of these things as well. The first one is in the new world of the cloud I think think of migration, modernization and management as a single continuum to the cloud. Now there is no lift and shift and there is no way somebody else separately manages it, right? If you do not lift and shift the right applications the right way onto the cloud, you are going to deal with the complexity of managing it and you'll end up spending more money time and effort in managing it. So that's number one. Migration, modernization, management of cloud work growth is a single continuum and it's not three separate activities, right? That's number one. And the, the second is cost. Cost traditionally has been an afterthought, right? People move the workload to the cloud. And I think, again, like I said, I'll refer back to what Manoj said once we move it to the cloud and then we put all these fancy engineering capability around self-provisioning, every developer can go and ask for what he or she wants and they get an environment immediately spun up so on and so forth. Suddenly the CIO wakes up to a bill that is significantly larger than what he or she expected right? And, and this is this is become a bit common nowadays, right? The the challenge is because we think cost in the cloud as an afterthought. But consider this example in, in previous world you buy hard, well, you put it in your data center you have already amortized the cost as a CapEx. So you can write an application throw it onto the infrastructure and the application continues to use the infrastructure until you hit a ceiling, you don't care about the money you spent. But if I write a line of code that is inefficient today and I deploy it on the cloud from minute one, I am paying for the inefficiency. So if I realize it after six months, I've already spent the money. So financial discipline, especially when managing the cloud is now is no more an afterthought. It is as much something that you have to include in your engineering practice as much as any other DevOps practices, right? Those are my top two tips, Lisa, from my standpoint, think about cloud, think about cloud work, cloud workloads. And the last one again, and you will see you will hear me saying this again and again, get into the mindset of everything is code. You don't have a touch and feel infrastructure anymore. So you don't really need to have foot on the ground to go manage that infrastructure. It's codified. So your code should be managing it, but think of how it happens, right? That's where we, we are going as an evolution >> Everything is code. That's great advice, great tips for the audience there. Manoj, I'll bring you back into the conversation. You know, we, we can talk about skills gaps on on in many different facets of technology the SRE role, relatively new, skillset. We're hearing, hearing a lot about it. SRE led DevSecOps is probably even more so of a new skillset. If I'm an IT leader or an application leader how do I ensure that I have the right skillset within my organization to be able to manage my cloud operations to, to dial down that complexity so that I can really operate successfully as a business? >> Yeah. And so unfortunately there is no perfect answer, right? It's such a, such a scarce skillset that a, any day any of the portfolio company CTOs if I go and talk and say, Hey here's a great SRE team member, they'll be more than willing to fight with each of to get the person in right? It's just that scarce of a skillset. So, so a few things we need to look at it. One is, how can I build it within, right? So nobody gets born as an SRE, you, you make a person an SRE. So how do you inculcate that culture? So like Prem said earlier, right? Everything is software. So how do we make sure that everybody inculcates that as part of their operating philosophy be they part of the operations team or the development team or the testing team they need to understand that that is a common guideline and common objective that we are driving towards. So, so that skillset and that associated training needs to be driven from within the organization. And that in my mind is the fastest way to make sure that that role gets propagated across organization. That is one. The second thing is rely on the right partners. So it's not going to be possible for us, to get all of these roles built in-house. So instead prioritize what roles need to be done from within the organization and what roles can we rely on our partners to drive it for us. So that becomes an important consideration for us to look at as well. >> Absolutely. That partnership angle is incredibly important from, from the, the beginning really kind of weaving these companies together on this journey to to redefine cloud operations and build that, as we talked about at the beginning of the conversation really building a cloud center of excellence that allows the organization to be competitive, successful and and really deliver what the end user is, is expecting. I want to ask - Sorry Lisa, - go ahead. >> May I add something to it, I think? >> Sure. >> Yeah. One of the, one of the common things that I tell customers when we talk about SRE and to manages point is don't think of SRE as a skillset which is the common way today the industry tries to solve the problem. SRE is a mindset, right? Everybody in >> Well well said, yeah >> That, so everybody in a company should think of him or her as a cycle liability engineer. And everybody has a role in it, right? Even if you take the new process layout from SRE there are individuals that are responsible to whom we can go to when there is a problem directly as opposed to going through the traditional ways of AI talk to L one and L one contras all. They go to L two and then L three. So we, we, we are trying to move away from an issue escalation model to what we call as a a issue routing or a incident routing model, right? Move away from incident escalation to an incident routing model. So you get to route to the right folks. So again, to sum it up, SRE should not be solved as a skillset set because there is not enough people in the market to solve it that way. If you start solving it as a mindset I think companies can get a handhold of it. >> I love that. I've actually never heard that before, but it it makes perfect sense to think about the SRE as a mindset rather than a skillset that will allow organizations to be much more successful. Prem I wanted to get your thoughts as enterprises are are innovating, they're moving more products and services to the as a service model. Talk about how the dev teams the ops teams are working together to build and run reliable, cost efficient services. Are they working better together? >> Again, a a very polarizing question because some customers are getting it right many customers aren't, there is still a big wall between development and operations, right? Even when you think about DevOps as a terminology the fundamental principle was to make sure dev and ops works together. But what many companies have achieved today, honestly is automating the operations for development. For example, as a developer, I can check in code and my code will appear in production without any friction, right? There is automated testing, automated provisioning and it gets promoted to production, but after production, it goes back into the 20 year old model of operating the code, right? So there is more work that needs to be done for Devon and Ops to come closer and work together. And one of the ways that we think this is achievable is not by doing radical org changes, but more by focusing on a product-oriented single backlog approach across development and operations. Which is, again, there is change management involved but I think that's a way to start embracing the culture of dev ops coming together much better now, again SRE principles as we double click and understand it more and Google has done a very good job playing it out for the world. As you think about SRE principle, there are ways and means in that process of how to think about a single backlog. And in HARC, Hitachi Application Reliability Centers we've really got a way to look at prioritizing the backlog. And what I mean by that is dev teams try to work on backlog that come from product managers on features. The SRE and the operations team try to put backlog into the say sorry, try to put features into the same backlog for improving stability, availability and financials financial optimization of your code. And there are ways when you look at your SLOs and error budgets to really coach the product teams to prioritize your backlog based on what's important for you. So if you understand your spending more money then you reduce your product features going in and implement the financial optimization that came from your operations team, right? So you now have the ability to throttle these parameters and that's where SRE becomes a mindset and a principle as opposed to a skillset because this is not an individual telling you to do. This is the company that is, is embarking on how to prioritize my backlog beyond just user features. >> Right. Great point. Last question for both of you is the same talk kind of take away things that you want me to remember. If I am at an IT leader at, at an organization and I am planning on redefining CloudOps for my company Manoj will start with you and then Prem to you what are the top two things that you want me to walk away with understanding how to do that successfully? >> Yeah, so I'll, I'll go back to basics. So the two things I would say need to be taken care of is, one is customer experience. So all the things that I do end of the day is it improving the customer experience or not? So that's a first metric. The second thing is anything that I do is there an ROI by doing that incremental step or not? Otherwise we might get lost in the technology with surgery, the new tech, et cetera. But end of the day, if the customers are not happy if there is no ROI, everything else you just can't do much on top of that >> Now it's all about the customer experience. Right? That's so true. Prem what are your thoughts, the the top things that I need to be taking away if I am a a leader planning to redefine my cloud eye company? >> Absolutely. And I think from a, from a company standpoint I think Manoj summarized it extremely well, right? There is this ROI and there is this customer experience from my end, again, I'll, I'll suggest two two more things as a takeaway, right? One, cloud cost is not an afterthought. It's essential for us to think about it upfront. Number two, do not delink migration modernization and operations. They are one stream. If you migrate a long, wrong workload onto the cloud you're going to be stuck with it for a long time. And an example of a wrong workload, Lisa for everybody that that is listening to this is if my cost per transaction profile doesn't change and I am not improving my revenue per transaction for a piece of code that's going run in production it's better off running in a data center where my cost is CapEx than amortized and I have control over when I want to upgrade as opposed to putting it on a cloud and continuing to pay unless it gives me more dividends towards improvement. But that's a simple example of when we think about what should I migrate and how will it cost pain when I want to manage it in the longer run. But that's, that's something that I'll leave the audience and you with as a takeaway. >> Excellent. Guys, thank you so much for talking to me today about what Hitachi Vantara and GTCR are doing together how you've really dialed down those complexities enabling the business and the technology folks to really live harmoniously. We appreciate your insights and your perspectives on building a cloud center of excellence. Thank you both for joining me. >> Thank you. >> For my guests, I'm Lisa. Martin, you're watching this event building Your Cloud Center of Excellence with Hitachi Vantara. Thanks for watching. (Upbeat music playing) (Upbeat music playing) (Upbeat music playing) (Upbeat music playing)

(Upbeat music playing) >> Hey everyone, thanks for joining us today. Welcome to this event of Building your Cloud Center of Excellence with Hitachi Vantara. I'm your host, Lisa Martin. I've got a couple of guests here with me next to talk about redefining cloud operations and application modernization for customers. Please welcome Param Balasubramanian the SVP and CTO at Hitachi Vantara, and Manoj Narayanan is here as well, the Managing Director of Technology at GTCR. Guys, thank you so much for joining me today. Excited to have this conversation about redefining CloudOps with you. >> Pleasure to be here. >> Pleasure to be here >> Param, let's go ahead and start with you. You have done well over a thousand cloud engagements in your career. I'd love to get your point of view on how the complexity around cloud operations and management has evolved in the last, say, three to four years. >> It's a great question, Lisa before we understand the complexity around the management itself, the cloud has evolved over the last decade significantly from being a backend infrastructure or infrastructure as a service for many companies to become the business for many companies. If you think about a lot of these cloud bond companies cloud is where their entire workload and their business wants. With that, as a background for this conversation if you think about the cloud operations, there was a lot of there was a lot of lift and shift happening in the market where people lifted their workloads or applications and moved them onto the cloud where they treated cloud significantly as an infrastructure. And the way they started to manage it was again, the same format they were managing there on-prem infrastructure and they call it I&O, Infrastructure and Operations. That's kind of the way traditionally cloud is managed. In the last few years, we are seeing a significant shift around thinking of cloud more as a workload rather than as just an infrastructure. And what I mean by workload is in the cloud, everything is now code. So you are codifying your infrastructure. Your application is already code and your data is also codified as data services. With now that context apply the way you think about managing the cloud has to significantly change and many companies are moving towards trying to change their models to look at this complex environment as opposed to treating it like a simple infrastructure that is sitting somewhere else. So that's one of the biggest changes and shifts that are causing a lot of complexity and headache for actually a lot of customers for managing environments. The second critical aspect is even that, even exasperates the situation is multicloud environments. Now, there are companies that have got it right with things about right cloud for the right workload. So there are companies that I reach out and I talk with. They've got their office applications and emails and stuff running on Microsoft 365 which can be on the Azure cloud whereas they're running their engineering applications the ones that they build and leverage for their end customers on Amazon. And to some extent they've got it right but still they have a multiple cloud that they have to go after and maintain. This becomes complex when you have two clouds for the same type of workload. When I have to host applications for my end customers on Amazon as well as Azure, Azure as well as Google then, I get into security issues that I have to be consistent across all three. I get into talent because I need to have people that focus on Amazon as well as Azure, as well as Google which means I need so much more workforce, I need so many so much more skills that I need to build, right? That's becoming the second issue. The third one is around data costs. Can I make these clouds talk to each other? Then you get into the ingress egress cost and that creates some complexity. So bringing all of this together and managing is really become becoming more complex for our customers. And obviously as a part of this we will talk about some of the, some of the ideas that we can bring for in managing such complex environments but this is what we are seeing in terms of why the complexity has become a lot more in the last few years. >> Right. A lot of complexity in the last few years. Manoj, let's bring you into the conversation now. Before we dig into your cloud environment give the audience a little bit of an overview of GTCR. What kind of company are you? What do you guys do? >> Definitely Lisa. GTCR is a Chicago based private equity firm. We've been in the market for more than 40 years and what we do is we invest in companies across different sectors and then we manage the company drive it to increase the value and then over a period of time, sell it to future buyers. So in a nutshell, we got a large portfolio of companies that we need to manage and make sure that they perform to expectations. And my role within GTCR is from a technology viewpoint so where I work with all the companies their technology leadership to make sure that we are getting the best out of technology and technology today drives everything. So how can technology be a good compliment to the business itself? So, my role is to play that intermediary role to make sure that there is synergy between the investment thesis and the technology lures that we can pull and also work with partners like Hitachi to make sure that it is done in an optimal manner. >> I like that you said, you know, technology needs to really compliment the business and vice versa. So Manoj, let's get into the cloud operations environment at GTCR. Talk to me about what the experience has been the last couple of years. Give us an idea of some of the challenges that you were facing with existing cloud ops and and the solution that you're using from Hitachi Vantara. >> A a absolutely. In fact, in fact Param phrased it really well, one of the key things that we're facing is the workload management. So there's so many choices there, so much complexities. We have these companies buying more companies there is organic growth that is happening. So the variables that we have to deal with are very high in such a scenario to make sure that the workload management of each of the companies are done in an optimal manner is becoming an increasing concern. So, so that's one area where any help we can get anything we can try to make sure it is done better becomes a huge value at each. A second aspect is a financial transparency. We need to know where the money is going where the money is coming in from, what is the scale especially in the cloud environment. We are talking about an auto scale ecosystem. Having that financial transparency and the metrics associated with that, it, these these become very, very critical to ensure that we have a successful presence in the multicloud environment. >> Talk a little bit about the solution that you're using with Hitachi and, and the challenges that it is eradicated. >> Yeah, so it end of the day, right, we we need to focus on our core competence. So, so we have got a very strong technology leadership team. We've got a very strong presence in the respective domains of each of the portfolio companies. But where Hitachi comes in and HAR comes in as a solution is that they allow us to excel in focusing on our core business and then make sure that we are able to take care of workload management or financial transparency. All of that is taken off the table from us and and Hitachi manages it for us, right? So it's such a perfectly compliment relationship where they act as two partners and HARC is a solution that is extremely useful in driving that. And, and and I'm anticipating that it'll become more important with time as the complexity of cloud and cloud associate workloads are only becoming more challenging to manage and not less. >> Right? That's the thing that complexity is there and it's also increasing Param, you talked about the complexities that are existent today with respect to cloud operations the things that have happened over the last couple of years. What are some of your tips, Param for the audience, like the the top two or three things that you would say on cloud operations that that people need to understand so that they can manage that complexity and allow their business to be driven and complimented by technology? >> Yeah, a big great question again, Lisa, right? And I think Manoj alluded to a few of these things as well. The first one is in the new world of the cloud I think think of migration, modernization and management as a single continuum to the cloud. Now there is no lift and shift and there is no way somebody else separately manages it, right? If you do not lift and shift the right applications the right way onto the cloud, you are going to deal with the complexity of managing it and you'll end up spending more money time and effort in managing it. So that's number one. Migration, modernization, management of cloud work growth is a single continuum and it's not three separate activities, right? That's number one. And the, the second is cost. Cost traditionally has been an afterthought, right? People move the workload to the cloud. And I think, again, like I said, I'll refer back to what Manoj said once we move it to the cloud and then we put all these fancy engineering capability around self-provisioning, every developer can go and ask for what he or she wants and they get an environment immediately spun up so on and so forth. Suddenly the CIO wakes up to a bill that is significantly larger than what he or she expected right? And, and this is this is become a bit common nowadays, right? The the challenge is because we think cost in the cloud as an afterthought. But consider this example in, in previous world you buy hard, well, you put it in your data center you have already amortized the cost as a CapEx. So you can write an application throw it onto the infrastructure and the application continues to use the infrastructure until you hit a ceiling, you don't care about the money you spent. But if I write a line of code that is inefficient today and I deploy it on the cloud from minute one, I am paying for the inefficiency. So if I realize it after six months, I've already spent the money. So financial discipline, especially when managing the cloud is now is no more an afterthought. It is as much something that you have to include in your engineering practice as much as any other DevOps practices, right? Those are my top two tips, Lisa, from my standpoint, think about cloud, think about cloud work, cloud workloads. And the last one again, and you will see you will hear me saying this again and again, get into the mindset of everything is code. You don't have a touch and feel infrastructure anymore. So you don't really need to have foot on the ground to go manage that infrastructure. It's codified. So your code should be managing it, but think of how it happens, right? That's where we, we are going as an evolution >> Everything is code. That's great advice, great tips for the audience there. Manoj, I'll bring you back into the conversation. You know, we, we can talk about skills gaps on on in many different facets of technology the SRE role, relatively new, skillset. We're hearing, hearing a lot about it. SRE led DevSecOps is probably even more so of a new skillset. If I'm an IT leader or an application leader how do I ensure that I have the right skillset within my organization to be able to manage my cloud operations to, to dial down that complexity so that I can really operate successfully as a business? >> Yeah. And so unfortunately there is no perfect answer, right? It's such a, such a scarce skillset that a, any day any of the portfolio company CTOs if I go and talk and say, Hey here's a great SRE team member, they'll be more than willing to fight with each of to get the person in right? It's just that scarce of a skillset. So, so a few things we need to look at it. One is, how can I build it within, right? So nobody gets born as an SRE, you, you make a person an SRE. So how do you inculcate that culture? So like Param said earlier, right? Everything is software. So how do we make sure that everybody inculcates that as part of their operating philosophy be they part of the operations team or the development team or the testing team they need to understand that that is a common guideline and common objective that we are driving towards. So, so that skillset and that associated training needs to be driven from within the organization. And that in my mind is the fastest way to make sure that that role gets propagated across organization. That is one. The second thing is rely on the right partners. So it's not going to be possible for us, to get all of these roles built in-house. So instead prioritize what roles need to be done from within the organization and what roles can we rely on our partners to drive it for us. So that becomes an important consideration for us to look at as well. >> Absolutely. That partnership angle is incredibly important from, from the, the beginning really kind of weaving these companies together on this journey to to redefine cloud operations and build that, as we talked about at the beginning of the conversation really building a cloud center of excellence that allows the organization to be competitive, successful and and really deliver what the end user is, is expecting. I want to ask - Sorry Lisa, - go ahead. >> May I add something to it, I think? >> Sure. >> Yeah. One of the, one of the common things that I tell customers when we talk about SRE and to manages point is don't think of SRE as a skillset which is the common way today the industry tries to solve the problem. SRE is a mindset, right? Everybody in >> Well well said, yeah >> That, so everybody in a company should think of him or her as a cycle liability engineer. And everybody has a role in it, right? Even if you take the new process layout from SRE there are individuals that are responsible to whom we can go to when there is a problem directly as opposed to going through the traditional ways of AI talk to L one and L one contras all. They go to L two and then L three. So we, we, we are trying to move away from an issue escalation model to what we call as a a issue routing or a incident routing model, right? Move away from incident escalation to an incident routing model. So you get to route to the right folks. So again, to sum it up, SRE should not be solved as a skillset set because there is not enough people in the market to solve it that way. If you start solving it as a mindset I think companies can get a handhold of it. >> I love that. I've actually never heard that before, but it it makes perfect sense to think about the SRE as a mindset rather than a skillset that will allow organizations to be much more successful. Param I wanted to get your thoughts as enterprises are are innovating, they're moving more products and services to the as a service model. Talk about how the dev teams the ops teams are working together to build and run reliable, cost efficient services. Are they working better together? >> Again, a a very polarizing question because some customers are getting it right many customers aren't, there is still a big wall between development and operations, right? Even when you think about DevOps as a terminology the fundamental principle was to make sure dev and ops works together. But what many companies have achieved today, honestly is automating the operations for development. For example, as a developer, I can check in code and my code will appear in production without any friction, right? There is automated testing, automated provisioning and it gets promoted to production, but after production, it goes back into the 20 year old model of operating the code, right? So there is more work that needs to be done for Devon and Ops to come closer and work together. And one of the ways that we think this is achievable is not by doing radical org changes, but more by focusing on a product-oriented single backlog approach across development and operations. Which is, again, there is change management involved but I think that's a way to start embracing the culture of dev ops coming together much better now, again SRE principles as we double click and understand it more and Google has done a very good job playing it out for the world. As you think about SRE principle, there are ways and means in that process of how to think about a single backlog. And in HARC, Hitachi Application Reliability Centers we've really got a way to look at prioritizing the backlog. And what I mean by that is dev teams try to work on backlog that come from product managers on features. The SRE and the operations team try to put backlog into the say sorry, try to put features into the same backlog for improving stability, availability and financials financial optimization of your code. And there are ways when you look at your SLOs and error budgets to really coach the product teams to prioritize your backlog based on what's important for you. So if you understand your spending more money then you reduce your product features going in and implement the financial optimization that came from your operations team, right? So you now have the ability to throttle these parameters and that's where SRE becomes a mindset and a principle as opposed to a skillset because this is not an individual telling you to do. This is the company that is, is embarking on how to prioritize my backlog beyond just user features. >> Right. Great point. Last question for both of you is the same talk kind of take away things that you want me to remember. If I am at an IT leader at, at an organization and I am planning on redefining CloudOps for my company Manoj will start with you and then Param to you what are the top two things that you want me to walk away with understanding how to do that successfully? >> Yeah, so I'll, I'll go back to basics. So the two things I would say need to be taken care of is, one is customer experience. So all the things that I do end of the day is it improving the customer experience or not? So that's a first metric. The second thing is anything that I do is there an ROI by doing that incremental step or not? Otherwise we might get lost in the technology with surgery, the new tech, et cetera. But end of the day, if the customers are not happy if there is no ROI, everything else you just can't do much on top of that >> Now it's all about the customer experience. Right? That's so true. Param what are your thoughts, the the top things that I need to be taking away if I am a a leader planning to redefine my cloud eye company? >> Absolutely. And I think from a, from a company standpoint I think Manoj summarized it extremely well, right? There is this ROI and there is this customer experience from my end, again, I'll, I'll suggest two two more things as a takeaway, right? One, cloud cost is not an afterthought. It's essential for us to think about it upfront. Number two, do not delink migration modernization and operations. They are one stream. If you migrate a long, wrong workload onto the cloud you're going to be stuck with it for a long time. And an example of a wrong workload, Lisa for everybody that that is listening to this is if my cost per transaction profile doesn't change and I am not improving my revenue per transaction for a piece of code that's going run in production it's better off running in a data center where my cost is CapEx than amortized and I have control over when I want to upgrade as opposed to putting it on a cloud and continuing to pay unless it gives me more dividends towards improvement. But that's a simple example of when we think about what should I migrate and how will it cost pain when I want to manage it in the longer run. But that's, that's something that I'll leave the audience and you with as a takeaway. >> Excellent. Guys, thank you so much for talking to me today about what Hitachi Vantara and GTCR are doing together how you've really dialed down those complexities enabling the business and the technology folks to really live harmoniously. We appreciate your insights and your perspectives on building a cloud center of excellence. Thank you both for joining me. >> Thank you. >> For my guests, I'm Lisa. Martin, you're watching this event building Your Cloud Center of Excellence with Hitachi Vantara. Thanks for watching. (Upbeat music playing) (Upbeat music playing) (Upbeat music playing) (Upbeat music playing)

welcome back to the seaport in boston massachusetts with cities crazy with bruins and celtics talk but we're here we're talking red hat linux open shift ansible and ashesh badani is here he's the senior vice president and the head of products at red hat fresh off the keynotes had amex up in the state of great to see you face to face amazing that we're here now after two years of of the isolation economy welcome back thank you great to see you again as well and you as well paul yeah so no shortage of announcements uh from red hat this week paul wrote a piece on siliconangle.com i got my yellow highlights i've been through all the announcements which is your favorite baby hard for me to choose hard for me to choose um i'll talk about real nine right well nine's exciting um and in a weird way it's exciting because it's boring right because it's consistent three years ago we committed to releasing a major well uh every three years right so customers partners users can plan for it so we released the latest version of rel in between we've been delivering releases every six months as well minor releases a lot of capabilities that are bundled in around security automation edge management and then rel is also the foundation of the work we announced with gm with the in-vehicle operating system so you know that's extremely exciting news for us as well and the collaboration that we're doing with them and then a whole host of other announcements around you know cloud services work around devsecops and so on so yeah a lot of news a lot of announcements i would say rel nine and the work with gm probably you know comes right up to the top i wanted to get to one aspect of the rail 9 announcement that is the the rose centos streams in that development now in december i think it was red hat discontinued development or support for for centos and moved to central streams i'm still not clear what the difference is between the two can you clarify that i think we go into a situation especially with with many customers many partners as well that you know didn't sort of quite exactly uh get a sense of you know where centos was from a life cycle perspective so was it upstream to rel was it downstream to rel what's the life cycle for itself as well and then there became some sort of you know implied notions around what that looked like and so what we decided was to say well we'll make a really clean break and we'll say centos stream is the upstream for enterprise linux from day one itself partners uh you know software partners hardware partners can collaborate with us to develop rel and then take it all the way through life cycle right so now it becomes a true upstream a true place for development for us and then rel essentially comes uh out as a series of releases based on the work that we do in a fast-moving center-os environment but wasn't centos essentially that upstream uh development environment to begin with what's the difference between centos stream yeah it wasn't wasn't um it wasn't quite upstream it was actually a little bit downstream yeah it was kind of bi-directional yeah and yeah and so then you know that sort of became an implied life cycle to it when there really wasn't one but it was just became one because of some usage and adoption and so now this really clarifies the relationship between the two we've heard feedback for example from software partners users saying hey what do i do for development because i used you know centervis in the past we're like yup we have real for developers available we have rel for small teams available we have rel available for non-profit organizations up and so we've made rail now available in various form factors for the needs that folks had and they were perhaps using centos for because there was no such alternative or rel history so language so now it's this clarity so that's really the key point there so language matters a lot in the technology business we've seen it over the years the industry coalesces around you know terminology whether it was the pc era everything was pc this pc that the internet era and and certainly the cloud we we learned a lot of language from the likes of you know aws two pizza teams and working backwards and things like that became common commonplace hybrid and multi-cloud are kind of the the parlance of the day you guys use hybrid you and i have talked about this i feel like there's something new coming i don't think my term of super cloud is the right necessary terminology but it signifies something different and i feel like your announcements point to that within your hybrid umbrella point being so much talk about the edge and it's we heard paul cormier talk about new hardware architectures and you're seeing that at the edge you know what you're doing with the in-vehicle operating system these are new the cloud isn't just a a bunch of remote services in the cloud anymore it's on-prem it's a cloud it's cross-clouds it's now going out to the edge it's something new and different i think hybrid is your sort of term for that but it feels like it's transcending hybrid are your thoughts you know really really great question actually since you and i talked dave i've been spending some time you know sort of noodling just over that right and you're right right there's probably some terminology something sort of you know that will get developed you know either by us or you know in collaboration with the industry you know where we sort of almost have the connection almost like a meta cloud right that we're sort of working our way towards because there's if you will you know the cloud right so you know on premise you know virtualized uh bare metal by the way you know increasingly interesting and important you know we do a lot of work with nvidia folks want to run specific workloads there we announced support for arm right another now popular architecture especially as we go out to the edge so obviously there's private cloud public cloud then the edge becomes a continuum now you know on that process we actually have a major uh uh shipping company so uh a cruise lines that's talking about using openshift on cruise lines right so you know that's the edge right last year we had verizon talking about you know 5g and you know ran in the next generation there to then that's the edge when we talk to retail the store front's the edge right you talk to a bank you know the bank environments here so everyone's got a different kind of definition of edge we're working with them and then when we you know announce this collaboration with gm right now the edge there becomes the automobile so if you think of this as a continuum right you know bare metal private cloud public cloud take it out to the edge now we're sort of almost you know living in a world of you know a little bit of abstractions and making sure that we are focused on where uh data is being generated and then how can we help ensure that we're providing a consistent experience regardless of you know where meta meta cloud because i can work in nfts i can work a little bit we're going to get through this whole thing without saying metaverse i was hoping i do want to ask you about about the edge and the proliferation of hardware platforms paul comey mentioned this during the keynote today hardware is becoming important yeah there's a lot of people building hardware it's in development now for areas like uh like intelligent devices and ai how does this influence your development priorities you have all these different platforms that you need to support yeah so um we think about that a lot mostly because we have engagements with so many partners hardware right so obviously there's more traditional partners i'd say like the dell and the hpes that we work with we've historically worked with them also working with them in in newer areas uh with regard to appliances that are being developed um and then the work that we do with partners like nvidia or new architectures like arm and so our perspective is this will be uh use case driven more than anything else right so there are certain environments right where you have arm-based devices other environments where you've got specific workloads that can take advantage of being built on gpus that we'll see increasingly being used especially to address that problem and then provide a solution towards that so our belief has always been look we're going to give you a consistent platform a consistent abstraction across all these you know pieces of hardware um and so you mr miss customer make the best choice for yourself a couple other areas we have to hit on i want to talk about cloud services we've got to talk about security leave time to get there but why the push to cloud services what's driving that it's actually customers they're driving right so we have um customers consistently been asking us say you know love what you give us right want to make sure that's available to us when we consume in the cloud so we've made rel available for example on demand right you can consume this directly via public cloud consoles we are now making available via marketplaces uh talked about ansible available as a managed service on azure openshift of course available as a managed service in multiple clouds um all of this also is because you know we've got customers who've got these uh committed spends that they have you know with cloud providers they want to make sure that the environments that they're using are also counting towards that at the same time give them flexibility give them the choice right if in certain situations they want to run in the data center great we have that solution for them other cases they want to procure from the cloud and run it there we're happy to support them there as well let's talk about security because you have a lot of announcements like security everywhere yeah um and then some specific announcements as well i i always think about these days in the context of the solar wind supply chain hack would this have you know how would this have affected it but tell us about what's going on in security your philosophy there and the announcements that you guys made so our secure announcements actually span our entire portfolio yeah right and and that's not an accident right that's by design because you know we've really uh been thinking and emphasizing you know how we ensure that security profile is raised for users both from a malicious perspective and also helping accidental issues right so so both matters so one huge amounts of open source software you know out of the world you know and then estimates are you know one in ten right has some kind of security vulnerability um in place a massive amount of change in where software is being developed right so rate of change for example in kubernetes is dramatic right much more than even than linux right entire parts of kubernetes get rewritten over over a three-year period of time so as you introduce all that right being able to think for example about you know what's known as shift left security or devsec ops right how do we make sure we move security closer to where development is actually done how do we ensure we give you a pattern so you know we introduced a software supply chain pattern uh via openshift delivers complete stack of code that you know you can go off and run that follows best practices uh including for example for developers you know with git ops and support on the pipelines front a whole bunch of security capabilities in rel um a new image integrity measurement architecture which allows for a better ability to see in a post install environment what the integrity of the packages are signing technology they're incorporating open shift as well as an ansible so it's it's a long long list of cables and features and then also more and more defaults that we're putting in place that make it easier for example for someone not to hurt themselves accidentally on security front i noticed that uh this today's batch of announcements included support within openshift pipelines for sigstor which is an open source project that was birthed actually at red hat right uh we haven't heard a whole lot about it how important is zig store to to you know your future product direction yeah so look i i think of that you know as you know work that's you know being done out of our cto's office and obviously security is a big focus area for them um six store's great example of saying look how can we verify content that's in uh containers make sure it's you know digitally signed that's appropriate uh to be deployed across a bunch of environments but that thinking isn't maybe unique uh for us uh in the container side mostly because we have you know two decades or more of thinking about that on the rel side and so fundamentally containers are being built on linux right so a lot of the lessons that we've learned a lot of the expertise that we've built over the years in linux now we're starting to you know use that same expertise trying to apply it to containers and i'm my guess is increasingly we're going to see more of the need for that you know into the edge as well i i i picked up on that too let me ask a follow-up question on sigstor so if i'm a developer and i and i use that capability it it ensures the provenance of that code is it immutable the the signature uh and the reason i ask is because again i think of everything in the context of the solar winds where they were putting code into the the supply chain and then removing it to see what happened and see how people reacted and it's just a really scary environment yeah the hardest part you know in in these environments is actually the behavior change so what's an example of that um packages built verified you know by red hat when it went from red hat to the actual user have we been able to make sure we verify the integrity of all of those when they were put into use um and unless we have behavior that you know make sure that we do that then we find ourselves in trouble in the earliest days of open shift uh we used to get knocked a lot by by developers because i said hey this platform's really hard to use we investigate hey look why is that happening so by default we didn't allow for root access you know and so someone's using you know the openshift platform they're like oh my gosh i can't use it right i'm so used to having root access we're like no that's actually sealed by default because that's not a good security best practice now over a period of time when we you know randomly enough times explained that enough times now behavior changes like yeah that makes sense now right so even just kind of you know there's behaviors the more that we can do for example in in you know the shift left which is one of the reasons by the way why we bought uh sac rocks a year right right for declarative security contain native security so threat detection network segmentation uh watching intrusions you know malicious behavior is something that now we can you know essentially make native into uh development itself all right escape key talk futures a little bit so i went downstairs to the expert you know asked the experts and there was this awesome demo i don't know if you've seen it of um it's like a design thinking booth with what happened how you build an application i think they were using the who one of their apps um during covet and it's you know shows the the granularity of the the stack and the development pipeline and all the steps that have to take place and it strikes me of something we've talked about so you've got this application development stack if you will and the database is there to support that and then over here you've got this analytics stack and it's separate and we always talk about injecting more ai into apps more data into apps but there's separate stacks do you see a day where those two stacks can come together and if not how do we inject more data and ai into apps what are your thoughts on that so great that's another area we've talked about dave in the past right um so we definitely agree with that right and and what final shape it takes you know i think we've got some ideas around that what we started doing is starting to pick up specific areas where we can start saying let's go and see what kind of usage we get from customers around it so for example we have openshift data science which is basically a way for us to talk about ml ops right and you know how can we have a platform that allows for different models that you can use we can uh test and train data different frameworks that you can then deploy in an environment of your choice right and we run that uh for you up and assist you in in uh making sure that you're able to take the next steps you want with with your machine learning algorithms um there's work that we've uh introduced at summit around databases service so essentially our uh a cloud service that allows for deep as an easy way for customers to access either mongodb or or cockroach in a cloud native fashion and all of these things that we're sort of you know experimenting with is to be able to say look how do we sort of bring the world's closer together right off database of data of analytics with a core platform and a core stack because again right this will become part of you know one continuum that we're going to work with it's not i'd like your continuum that's that's i think really instructive it's not a technical barrier is what i'm hearing it's maybe organizational mindset i can i should be able to insert a column into my my my application you know development pipeline and insert the data i mean kafka tensorflow in there there's no technical reason i can't can't do that it's just we've created these sort of separate stovepipe organizations 100 right right so they're different teams right you've got the platform team or the ops team and you're a separate dev team there's a separate data team there's a separate storage team and each of them will work you know slightly differently independently right so the question then is i mean that's sort of how devops came along then you're like oh wait a minute yeah don't forget security and now we're at devsecops right so the more of that that we can kind of bring together i think the more convergence that we'll see when i think about the in-vehicle os i see the the that is a great use case for real-time ai inferencing streaming data i wanted to ask you that about that real quickly because at the very you know just before the conference began we got an announcement about gm but your partnership with gm it seems like this came together very quickly why is it so important for red hat this is a whole new category of application that you're going to be working on yeah so we've been working with gm not publicly for a while now um and it was very clear that look you know gm believes this is the future right you know electric vehicles into autonomous driving and we're very keen to say we believe that a lot of attributes that we've got in rel that we can bring to bear in a different form factor to assist with the different needs that exist in this industry so one it's interesting for us because we believe that's a use case that you know we can add value to um but it's also the future of automotive right so the opportunity to be able to say look we can get open source technology we can collaborate out with the community to fundamentally help transform that industry uh towards where it wants to go you know that that's just the passion that we have that you know is what wakes us up every morning you're opening into that yeah thank you for coming on the cube really appreciate your time and your insights and uh have a great rest of rest of the event thank you for having me metacloud it's a thing it's a thing right it's it's it's kind of there we're gonna we're gonna see it emerge over the next decade all right you're watching the cube's coverage of red hat summit 2022 from boston keep it right there be right back you

>>from around the globe. It's the Cube covering space and cybersecurity. Symposium 2020 hosted by Cal Poly >>Oven. Welcome back to the Space and Cyber Security Symposium. 2020 I'm John for your host with the Cuban silicon angle, along with Cal Poly, representing a great session here on industry success in developing space and cybersecurity. Resource is Got a great lineup. Brigadier General Steve Hotel, whose are also known as Bucky, is Call Sign director of Space Portfolio Defense Innovation Unit. Preston Miller, chief information security officer at JPL, NASA and Major General retired Clint Crozier, director of aerospace and satellite solutions at Amazon Web services, also known as a W s. Gentlemen, thank you for for joining me today. So the purpose of this session is to spend the next hour talking about the future of workforce talent. Um, skills needed and we're gonna dig into it. And Spaces is an exciting intersection of so many awesome disciplines. It's not just get a degree, go into a track ladder up and get promoted. Do those things. It's much different now. Love to get your perspectives, each of you will have an opening statement and we will start with the Brigadier General Steve Hotel. Right? >>Thank you very much. The Defense Innovation Unit was created in 2015 by then Secretary of Defense Ash Carter. To accomplish three things. One is to accelerate the adoption of commercial technology into the Department of Defense so that we can transform and keep our most relevant capabilities relevant. And also to build what we call now called the national Security Innovation Base, which is inclusive all the traditional defense companies, plus the commercial companies that may not necessarily work with focus exclusively on defense but could contribute to our national security and interesting ways. Um, this is such an exciting time Azul here from our other speakers about space on and I can't, uh I'm really excited to be here today to be able to share a little bit of our insight on the subject. >>Thank you very much. Precedent. Miller, Chief information security officer, Jet Propulsion Lab, NASA, Your opening statement. >>Hey, thank you for having me. I would like to start off by providing just a little bit of context of what brings us. Brings us together to talk about this exciting topic for space workforce. Had we've seen In recent years there's been there's been a trend towards expanding our space exploration and the space systems that offer the great things that we see in today's world like GPS. Um, but a lot of that has come with some Asian infrastructure and technology, and what we're seeing as we go towards our next generation expects of inspiration is that we now want to ensure that were secured on all levels. And there's an acknowledgement that our space systems are just a susceptible to cyber attacks as our terrestrial assistance. We've seen a recent space, uh, policy Directive five come out from our administration, that that details exactly how we should be looking at the cyber principle for our space systems, and we want to prevent. We want to prevent a few things as a result of that of these principles. Spoofing and jamming of our space systems are not authorized commands being sent to those space systems, lots of positive control of our space vehicles on lots of mission data. We also acknowledge that there's a couple of frameworks we wanna adopt across the board of our space systems levers and things like our nice miss cybersecurity frameworks. eso what has been a challenge in the past adopted somebody Cyber principles in space systems, where there simply has been a skill gap in a knowledge gap. We hire our space engineers to do a few things. Very well designed space systems, the ploy space systems and engineer space systems, often cybersecurity is seen as a after thought and certainly hasn't been a line item and in any budget for our spaces in racing. Uh, in the past in recent years, the dynamic started to change. We're now now integrating cyber principles at the onset of development of these life cycle of space. Systems were also taking a hard look of how we train the next generation of engineers to be both adequate. Space engineers, space system engineers and a cyber engineers, as a result to Mrs success on DWI, also are taking a hard look at What do we mean when we talk about holistic risk management for our space assistance, Traditionally risk management and missing insurance for space systems? I've really revolved around quality control, but now, in recent years we've started to adopt principles that takes cyber risk into account, So this is a really exciting topic for me. It's something that I'm fortunate to work with and live with every day. I'm really excited to get into this discussion with my other panel members. Thank you. >>You Preston. Great insight there. Looking forward. Thio chatting further. Um, Clint Closure with a W. S now heading up. A director of aerospace and satellite Solutions, formerly Major General, Your opening statement. >>Thanks, John. I really appreciate that introduction and really appreciate the opportunity to be here in the Space and Cybersecurity Symposium. And thanks to Cal Poly for putting it together, you know, I can't help, but as I think to Cal Poly there on the central California coast, San Luis Obispo, California I can't help but to think back in this park quickly. I spent two years of my life as a launch squadron commander at Vandenberg Air Force Base, about an hour south of Cal Poly launching rockets, putting satellites in orbit for the national intelligence community and so some really fond memories of the Central California coast. I couldn't agree more with the theme of our symposium this week. The space and cyber security we've all come to know over the last decade. How critical spaces to the world, whether it's for national security intelligence, whether it's whether communications, maritime, agriculture, development or a whole host of other things, economic and financial transactions. But I would make the case that I think most of your listeners would agree we won't have space without cybersecurity. In other words, if we can't guaranteed cybersecurity, all those benefits that we get from space may not be there. Preston in a moment ago that all the threats that have come across in the terrestrial world, whether it be hacking or malware or ransomware or are simple network attacks, we're seeing all those migrate to space to. And so it's a really important issue that we have to pay attention to. I also want to applaud Cow Pauling. They've got some really important initiatives. The conference here, in our particular panel, is about developing the next generation of space and cyber workers, and and Cal Poly has two important programs. One is the digital transformation hub, and the other is space data solutions, both of which, I'm happy to say, are in partnership with a W. S. But these were important programs where Cal Poly looks to try to develop the next generation of space and cyber leaders. And I would encourage you if you're interested in that toe. Look up the program because that could be very valuable is well, I'm relatively new to the AWS team and I'm really happy Thio team, as John you said recently retired from the U. S. Air Force and standing up the U. S. Space force. But the reason that I mentioned that as the director of the aerospace and satellite team is again it's in perfect harmony with the theme today. You know, we've recognized that space is critically important and that cyber security is critically important and that's been a W s vision as well. In fact, a W s understands how important the space domain is and coupled with the fact that AWS is well known that at a W s security is job zero and stolen a couple of those to fax A. W. S was looking to put together a team the aerospace and satellite team that focus solely and exclusively every single day on technical innovation in space and more security for the space domain through the cloud and our offerings there. So we're really excited to reimagine agree, envision what space networks and architectures could look like when they're born on the cloud. So that's important. You know, talk about workforce here in just a moment, but but I'll give you just a quick sneak. We at AWS have also recognized the gap in the projected workforce, as Preston mentioned, Um, depending on the projection that you look at, you know, most projections tell us that the demand for highly trained cyber cyber security cloud practitioners in the future outweighs what we think is going to be the supply. And so a ws has leaned into that in a number of ways that we're gonna talk about the next segment. I know. But with our workforce transformation, where we've tried to train free of charge not just a W s workers but more importantly, our customers workers. It s a W s we obsessed over the customer. And so we've provided free training toe over 7000 people this year alone toe bring their cloud security and cyber security skills up to where they will be able to fully leverage into the new workforce. So we're really happy about that too? I'm glad Preston raised SPD five space policy Directive five. I think it's gonna have a fundamental impact on the space and cyber industry. Uh, now full disclosure with that said, You know, I'm kind of a big fan of space policy directives, ESPN, Or was the space policy directive that directed to stand up of the U. S. Space Force and I spent the last 18 months of my life as the lead planner and architect for standing up the U. S. Space force. But with that said, I think when we look back a decade from now, we're going to see that s p d five will have as much of an impact in a positive way as I think SPD for on the stand up of the space Force have already done so. So I'll leave it there, but really look forward to the dialogue and discussion. >>Thank you, gentlemen. Clint, I just wanna say thank you for all your hard work and the team and the people who were involved in standing up Space force. Um, it is totally new. It's a game changer. It's modern, is needed. And there's benefits on potential challenges and opportunities that are gonna be there, so thank you very much for doing that. I personally am excited. I know a lot of people are excited for what the space force is today and what it could become. Thank you very much. >>Yeah, Thanks. >>Okay, So >>with >>that, let me give just jump in because, you know, as you're talking about space force and cybersecurity and you spend your time at Vanderburgh launching stuff into space, that's very technical. Is operation okay? I mean, it's complex in and of itself, but if you think about like, what's going on beyond in space is a lot of commercial aspect. So I'm thinking, you know, launching stuff into space on one side of my brain and the other side of brain, I'm thinking like air travel. You know, all the logistics and the rules of the road and air traffic control and all the communications and all the technology and policy and, you >>know, landing. >>So, Major General Clint, what's your take on this? Because this is not easy. It's not just one thing that speaks to the diversity of workforce needs. What's your reaction to that? >>Yeah. I mean, your observation is right on. We're seeing a real boom in the space and aerospace industry. For all the good reasons we talked about, we're recognizing all the value space from again economic prosperity to exploration to being ableto, you know, improve agriculture and in weather and all those sorts of things that we understand from space. So what I'm really excited about is we're seeing this this blossom of space companies that we sort of referred to his new space. You know, it used to be that really only large governments like the United States and a handful of others could operate in the space domain today and largely infused because of the technological innovation that have come with Cyber and Cyrus Space and even the cloud we're seeing more and more companies, capabilities, countries, all that have the ability, you know. Even a well funded university today can put a cube sat in orbit, and Cal Poly is working on some of those too, by the way, and so it's really expanded the number of people that benefits the activity in space and again, that's why it's so critically important because we become more and more reliant and we will become more and more reliant on those capabilities that we have to protect him. It's fundamental that we do. So, >>Bucky, I want you to weigh in on this because actually, you you've flown. Uh, I got a call sign which I love interviewing people. Anyone who's a call sign is cool in my book. So, Bucky, I want you to react to that because that's outside of the technology, you know, flying in space. There's >>no >>rule. I mean, is there like a rules? I mean, what's the rules of the road? I mean, state of the right. I mean, what I mean, what what's going? What's gonna have toe happen? Okay, just logistically. >>Well, this is very important because, uh and I've I've had access thio information space derived information for most of my flying career. But the amount of information that we need operate effectively in the 21st century is much greater than Thanet has been in the past. Let me describe the environment s so you can appreciate a little bit more what our challenges are. Where, from a space perspective, we're going to see a new exponential increase in the number of systems that could be satellites. Uh, users and applications, right? And so eso we're going we're growing rapidly into an environment where it's no longer practical to just simply evolved or operate on a perimeter security model. We and with this and as I was brought up previously, we're gonna try to bring in MAWR commercial capabilities. There is a tremendous benefit with increasing the diversity of sources of information. We use it right now. The military relies very heavily on commercial SAT com. We have our military capabilities, but the commercial capabilities give us capacity that we need and we can. We can vary that over time. The same will be true for remote sensing for other broadband communications capabilities on doing other interesting effects. Also, in the modern era, we doom or operations with our friends and allies, our regional partners all around the world, in order to really improve our interoperability and have rapid exchange of information, commercial information, sources and capabilities provides the best means of doing that. So that so that the imperative is very important and what all this describes if you want to put one word on it. ISS, we're involving into ah hybrid space architectures where it's gonna be imperative that we protect the integrity of information and the cyber security of the network for the things most important to us from a national security standpoint. But we have to have the rules that that allows us to freely exchange information rapidly and in a way that that we can guarantee that the right users are getting the right information at the right. >>We're gonna come back to that on the skill set and opportunities for people driving. That's just looking. There's so much opportunity. Preston, I want you to react to this. I interviewed General Keith Alexander last year. He formerly ran Cyber Command. Um, now he's building Cyber Security Technologies, and his whole thesis is you have to share. So the question is, how do you share and lock stuff down at the same time when you have ah, multi sided marketplace in space? You know, suppliers, users, systems. This is a huge security challenge. What's your reaction to this? Because we're intersecting all these things space and cybersecurity. It's just not easy. What's your reaction? >>Absolutely, Absolutely. And what I would say in response to that first would be that security really needs to be baked into the onset of how we develop and implement and deploy our space systems. Um, there's there's always going to be the need to collect and share data across multiple entities, particularly when we're changing scientific data with our mission partners. Eso with that necessitates that we have a security view from the onset, right? We have a system spaces, and they're designed to share information across the world. How do we make sure that those, uh, those other those communication channels so secure, free from interception free from disruption? So they're really done? That necessitates of our space leaders in our cyber leaders to be joining the hip about how to secure our space systems, and the communications there in Clinton brought up a really good point of. And then I'm gonna elaborate on a little bit, just toe invite a little bit more context and talk about some the complexities and challenges we face with this advent of new space and and all of our great commercial partners coming into therefore way, that's going to present a very significant supply chain risk management problems that we have to get our hands around as well. But we have these manufacturers developing these highly specialized components for the space instruments, Um, that as it stands right now, it's very little oversight And how those things air produced, manufactured, put into the space systems communication channels that they use ports protocols that they use to communicate. And that's gonna be a significant challenge for us to get get our hands around. So again, cybersecurity being brought in. And the very onset of these development thes thes decisions in these life cycles was certainly put us in a best better position to secure that data in our in our space missions. >>Yeah, E just pick up on that. You don't mind? Preston made such a really good point there. But you have to bake security in up front, and you know there's a challenge and there's an opportunity, you know, with a lot of our systems today. It was built in a pre cyber security environment, especially our government systems that were built, you know, in many cases 10 years ago, 15 years ago are still on orbit today, and we're thankful that they are. But as we look at this new environment and we understand the threats, if we bake cybersecurity in upfront weaken balance that open application versus the risk a long as we do it up front. And you know, that's one of the reasons that our company developed what we call govcloud, which is a secure cloud, that we use thio to manage data that our customers who want to do work with the federal government or other governments or the national security apparatus. They can operate in that space with the built in and baked in cybersecurity protocols. We have a secret region that both can handle secret and top secret information for the same reasons. But when you bake security into the upfront applications, that really allows you to balance that risk between making it available and accessible in sort of an open architecture way. But being sure that it's protected through things like ITAR certifications and fed ramp, uh, another ice T certifications that we have in place. So that's just a really important point. >>Let's stay high level for a man. You mentioned a little bit of those those govcloud, which made me think about you know, the tactical edge in the military analogy, but also with space similar theater. It's just another theater and you want to stand stuff up. Whether it's communications and have facilities, you gotta do it rapidly, and you gotta do it in a very agile, secure, I high availability secure way. So it's not the old waterfall planning. You gotta be fast is different. Cloud does things different? How do you talk to the young people out there, whether it's apparent with with kids in elementary and middle school to high school, college grad level or someone in the workforce? Because there are no previous jobs, that kind of map to the needs out there because you're talking about new skills, you could be an archaeologist and be the best cyber security guru on the planet. You don't have to have that. There's no degree for what, what we're talking about here. This >>is >>the big confusion around education. I mean, you gotta you like math and you could code you can Anything who wants to comment on that? Because I think this >>is the core issue. I'll say there are more and more programs growing around that educational need, and I could talk about a few things we're doing to, but I just wanna make an observation about what you just said about the need. And how do you get kids involved and interested? Interestingly, I think it's already happening, right. The good news. We're already developing that affinity. My four year old granddaughter can walk over, pick up my iPad, turn it on. Somehow she knows my account information, gets into my account, pulls up in application, starts playing a game. All before I really even realized she had my iPad. I mean, when when kids grow up on the cloud and in technology, it creates that natural proficiency. I think what we have to do is take that natural interest and give them the skill set the tools and capabilities that go with it so that we're managing, you know, the the interest with the technical skills. >>And also, like a fast I mean, just the the hackers are getting educated. Justus fast. Steve. I mean e mean Bucky. What do you do here? You CIt's the classic. Just keep chasing skills. I mean, there are new skills. What are some of those skills? >>Why would I amplify eloquent? Just said, First of all, the, uh, you know, cyber is one of those technology areas where commercial side not not the government is really kind of leading away and does a significant amount of research and development. Ah, billions of dollars are spent every year Thio to evolve new capabilities. And a lot of those companies are, you know, operated and and in some cases, led by folks in their early twenties. So the S O. This is definitely an era and a generation that is really poised in position. Well, uh, Thio take on this challenge. There's some unique aspects to space. Once we deploy a system, uh, it will be able to give me hard to service it, and we're developing capabilities now so that we could go up and and do system upgrades. But that's not a normal thing in space that just because the the technical means isn't there yet. So having software to find capabilities, I's gonna be really paramount being able to dio unique things. The cloud is huge. The cloud is centric to this or architectural, and it's kind of funny because d o d we joke because we just discovered the cloud, you know, a couple years ago. But the club has been around for a while and, uh, and it's going to give us scalability on and the growth potential for doing amazing things with a big Data Analytics. But as Preston said, it's all for not if if we can't trust the data that we receive. And so one of the concepts for future architectures is to evolve into a zero trust model where we trust nothing. We verify and authenticate everyone. And, uh, and that's that's probably a good, uh, point of departure as we look forward into our cybersecurity for space systems into the future. >>Block everyone. Preston. Your reaction to all this gaps, skills, What's needed. I mean it Z everyone's trying to squint through this >>absolutely. And I wanna want to shift gears a little bit and talk about the space agencies and organizations that are responsible for deploying these spaces into submission. So what is gonna take in this new era on, and what do we need from the workforce to be responsive to the challenges that we're seeing? First thing that comes to mind is creating a culture of security throughout aerospace right and ensuring that Azzawi mentioned before security isn't an afterthought. It's sort of baked into our models that we deploy and our rhetoric as well, right? And because again we hire our spaces in years to do it very highly. Specialized thing for a highly specialized, uh, it's topic. Our effort, if we start to incorporate rhetorically the importance of cybersecurity two missing success and missing assurance that's going to lend itself toe having more, more prepared on more capable system engineers that will be able to respond to the threats accordingly. Traditionally, what we see in organizational models it's that there's a cyber security team that's responsible for the for the whole kit kaboodle across the entire infrastructure, from enterprise systems to specialize, specialize, space systems and then a small pocket of spaces, years that that that are really there to perform their tasks on space systems. We really need to bridge that gap. We need to think about cybersecurity holistically, the skills that are necessary for your enterprise. I t security teams need to be the same skills that we need to look for for our system engineers on the flight side. So organizationally we need we need to address that issue and approach it, um todo responsive to the challenges we see our our space systems, >>new space, new culture, new skills. One of the things I want to bring up is looking for success formulas. You know, one of the things we've been seeing in the past 10 years of doing the Cube, which is, you know, we've been called the ESPN of Tech is that there's been kind of like a game ification. I want to. I don't wanna say sports because sports is different, but you're seeing robotics clubs pop up in some schools. It's like a varsity sport you're seeing, you know, twitch and you've got gamers out there, so you're seeing fun built into it. I think Cal Poly's got some challenges going on there, and then scholarships air behind it. So it's almost as if, you know, rather than going to a private sports training to get that scholarship, that never happens. There's so many more scholarship opportunities for are not scholarship, but just job opportunities and even scholarships we've covered as part of this conference. Uh, it's a whole new world of culture. It's much different than when I grew up, which was you know, you got math, science and English. You did >>it >>and you went into your track. Anyone want to comment on this new culture? Because I do believe that there is some new patterns emerging and some best practices anyone share any? >>Yeah, I do, because as you talked about robotics clubs and that sort of things, but those were great and I'm glad those air happening. And that's generating the interest, right? The whole gaming culture generating interest Robotic generates a lot of interest. Space right has captured the American in the world attention as well, with some recent NASA activities and all for the right reasons. But it's again, it's about taking that interested in providing the right skills along the way. So I'll tell you a couple of things. We're doing it a w s that we found success with. The first one is a program called A W s Academy. And this is where we have developed a cloud, uh, program a cloud certification. This is ah, cloud curriculum, if you will, and it's free and it's ready to teach. Our experts have developed this and we're ready to report it to a two year and four year colleges that they can use is part of the curriculum free of charge. And so we're seeing some real value there. And in fact, the governor's in Utah and Arizona recently adopted this program for their two year schools statewide again, where it's already to teach curriculum built by some of the best experts in the industry s so that we can try to get that skills to the people that are interested. We have another program called A W s educate, and this is for students to. But the idea behind this is we have 12 cracks and you can get up to 50 hours of free training that lead to A W s certification, that sort of thing. And then what's really interesting about that is all of our partners around the world that have tied into this program we manage what we call it ws educate Job board. And so if you have completed this educate program now, you can go to that job board and be linked directly with companies that want people with those skills we just helped you get. And it's a perfect match in a perfect marriage there. That one other piece real quickly that we're proud of is the aws Uh restart program. And that's where people who are unemployed, underemployed or transitioning can can go online. Self paced. We have over 500 courses they can take to try to develop those initial skills and get into the industry. And that's been very popular, too, So that those air a couple of things we're really trying to lean into >>anyone else want to react. Thio that question patterns success, best practices, new culture. >>I'd like Thio. The the wonderful thing about what you just touched on is problem solving, right, And there's some very, very good methodologies that are being taught in the universities and through programs like Hacking for Defense, which is sponsored by the National Security Innovation Network, a component of the I you where I work but the But whether you're using a lien methodologies or design school principals or any other method, the thing that's wonderful right now and not just, uh, where I work at the U. The Space force is doing this is well, but we're putting the problem out there for innovators to tackle, And so, rather than be prescriptive of the solutions that we want to procure, we want we want the best minds at all levels to be able to work on the problem. Uh, look at how they can leverage other commercial solutions infrastructure partnerships, uh, Thio to come up with a solution that we can that we can rapidly employ and scale. And if it's a dual use solution or whether it's, uh, civil military or or commercial, uh, in any of the other government solutions. Uh, that's really the best win for for the nation, because that commercial capability again allows us to scale globally and share those best practices with all of our friends and allies. People who share our values >>win win to this commercial. There's a business model potential financial benefits as well. Societal impact Preston. I want to come to you, JPL, NASA. I mean, you work in one of the most awesome places and you know, to me, you know, if you said to me, Hey, John, come working JP like I'm not smart enough to go there like I mean, like, it's a pretty It's intimidating, it might seem >>share folks out there, >>they can get there. I mean, it's you can get there if you have the right skills. I mean I'm just making that up. But, I mean, it is known to be super smart And is it attainable? So share your thoughts on this new culture because you could get the skills to get there. What's your take on all this >>s a bucket. Just missing something that really resonated with me, right? It's do it your love office. So if you put on the front engineer, the first thing you're gonna try to do is pick it apart. Be innovative, be creative and ways to solve that issue. And it has been really encouraging to me to see the ground welcome support an engagement that we've seen across our system. Engineers in space. I love space partners. A tackling the problem of cyber. Now that they know the West at risk on some of these cyber security threats that that they're facing with our space systems, they definitely want to be involved. They want to take the lead. They want to figure things out. They wanna be innovative and creative in that problem solving eso jpl We're doing a few things. Thio Raise the awareness Onda create a culture of security. Andi also create cyber advocates, cybersecurity advocates across our space engineers. We host events like hacked the lad, for example, and forgive me. Take a pause to think about the worst case scenarios that could that could result from that. But it certainly invites a culture of creative problem solving. Um, this is something that that kids really enjoy that are system engineers really enjoyed being a part off. Um, it's something that's new refreshing to them. Eso we were doing things like hosting a monthly cybersecurity advocacy group. When we talk about some of the cyber landscape of our space systems and invite our engineers into the conversation, we do outweighs programs specifically designed to to capture, um, our young folks, uh, young engineers to deceive. They would be interested and show them what this type of security has to offer by ways of data Analytic, since the engineering and those have been really, really successful identifying and bringing in new talent to address the skill gaps. >>Steve, I want to ask you about the d. O. D. You mentioned some of the commercial things. How are you guys engaging the commercial to solve the space issue? Because, um, the normalization in the economy with GPS just seeing spaces impacts everybody's lives. We we know that, um, it's been talked about. And and there's many, many examples. How are you guys the D o. D. From a security standpoint and or just from an advancement innovation standpoint, engaging with commercials, commercial entities and commercial folks? >>Well, I'll throw. I'll throw a, uh, I'll throw ah, compliment to Clint because he did such an outstanding job. The space forces already oriented, uh, towards ah, commercial where it's appropriate and extending the arms. Leveraging the half works on the Space Enterprise Consortium and other tools that allow for the entrepreneurs in the space force Thio work with their counterparts in a commercial community. And you see this with the, uh, you know, leveraging space X away to, uh, small companies who are doing extraordinary things to help build space situational awareness and, uh, s So it's it's the people who make this all happen. And what we do at at the D. O. D level, uh, work at the Office of Secretary defense level is we wanna make sure that they have the right tools to be able to do that in a way that allows these commercial companies to work with in this case of a space force or with cyber command and ways that doesn't redefine that. The nature of the company we want we want We want commercial companies to have, ah, great experience working with d o d. And we want d o d toe have the similar experience working, working with a commercial community, and and we actually work interagency projects to So you're going to see, uh, General Raymond, uh, hey, just recently signed an agreement with the NASA Esa, you're gonna see interagency collaborations on space that will include commercial capabilities as well. So when we speak as one government were not. You know, we're one voice, and that's gonna be tremendous, because if you're a commercial company on you can you can develop a capability that solves problems across the entire space enterprise on the government side. How great is that, Right. That's a scaling. Your solution, gentlemen. Let >>me pick you back on that, if you don't mind. I'm really excited about that. I mentioned new space, and Bucky talked about that too. You know, I've been flying satellites for 30 years, and there was a time where you know the U. S. Government national security. We wouldn't let anybody else look at him. Touch him. Plug into, um, anything else, right. And that probably worked at the time. >>But >>the world has changed. And more >>importantly, >>um, there is commercial technology and capability available today, and there's no way the U. S government or national security that national Intel community can afford economically >>to >>fund all that investment solely anymore. We don't have the manpower to do it anymore. So we have this perfect marriage of a burgeoning industry that has capabilities and it has re sources. And it has trained manpower. And we are seeing whether it's US Space Force, whether it's the intelligence community, whether it's NASA, we're seeing that opened up to commercial providers more than I've ever seen in my career. And I can tell you the customers I work with every day in a W s. We're building an entire ecosystem now that they understand how they can plug in and participate in that, and we're just seeing growth. But more importantly, we're seeing advanced capability at cheaper cost because of that hybrid model. So that really is exciting. >>Preston. You know you mentioned earlier supply chain. I don't think I think you didn't use the word supply chain. Maybe you did. But you know about the components. Um, you start opening things up and and your what you said baking it in to the beginning, which is well known. Uh, premise. It's complicated. So take me through again, Like how this all gonna work securely because And what's needed for skill sets because, you know, you're gonna open. You got open source software, which again, that's open. We live in a free society in the United States of America, so we can't lock everything down. You got components that are gonna be built anywhere all around the world from vendors that aren't just a certified >>or maybe >>certified. Um, it's pretty crazy. So just weigh in on this key point because I think Clint has it right. And but that's gonna be solved. What's your view on this? >>Absolutely. And I think it really, really start a top, right? And if you look back, you know, across, um in this country, particularly, you take the financial industry, for example, when when that was a burgeoning industry, what had to happen to ensure that across the board. Um, you know, your your finances were protected these way. Implemented regulations from the top, right? Yeah. And same thing with our health care industry. We implemented regulations, and I believe that's the same approach we're gonna need to take with our space systems in our space >>industry >>without being too directive or prescriptive. Instance she ating a core set of principles across the board for our manufacturers of space instruments for deployment and development of space systems on for how space data and scientific data is passed back and forth. Eso really? We're gonna need to take this. Ah, holistic approach. Thio, how we address this issue with cyber security is not gonna be easy. It's gonna be very challenging, but we need to set the guard rails for exactly what goes into our space systems, how they operate and how they communicate. >>Alright, so let's tie this back to the theme, um, Steve and Clint, because this is all about workforce gaps, opportunities. Um, Steve, you mentioned software defined. You can't do break fix in space. You can't just send a technician up in the space to fix a component. You gotta be software defined. We're talking about holistic approach, about commercial talk about business model technology with software and policy. We need people to think through, like you know. What the hell are you gonna do here, right? Do you just noticed road at the side of the road to drive on? There's no rules of engagement. So what I'm seeing is certainly software Check. If you wanna have a job for the next millennial software policy who solves two problems, what does freedom looked like in space Congestion Contention and then, obviously, business model. Can you guys comment on these three areas? Do you agree? And what specific person might be studying in grad school or undergraduate or in high school saying, Hey, I'm not a techie, but they can contribute your thoughts. I'll >>start off with, uh, speak on on behalf of the government today. I would just say that as policy goes, we need to definitely make sure that we're looking towards the future. Ah, lot of our policy was established in the past under different conditions, and, uh, and if there's anything that you cannot say today is that space is the same as it was even 10 years ago. So the so It's really important that our policy evolves and recognizes that that technology is going to enable not just a new ways of doing things, but also force us to maybe change or or get rid of obsolete policies that will inhibit our ability to innovate and grow and maintain peace with with a rapid, evolving threat. The for the for the audience today, Uh, you know, you want some job assurance, cybersecurity and space it's gonna be It's gonna be an unbelievable, uh, next, uh, few decades and I couldn't think of a more exciting for people to get into because, you know, spaces Ah, harsh environment. We're gonna have a hard time just dud being able differentiate, you know, anomalies that occur just because of the environment versus something that's being hacked. And so JPL has been doing this for years on they have Cem Cem great approaches, but but this is this is gonna be important if you put humans on the moon and you're going to sustain them there. Those life support systems are gonna be using, you know, state of the art computer technology, and which means, is also vulnerable. And so eso the consequences of us not being prepared? Uh, not just from our national security standpoint, but from our space exploration and our commercial, uh, economic growth in space over the long term all gonna be hinged on this cyber security environment. >>Clint, your thoughts on this too ill to get. >>Yeah. So I certainly agree with Bucky. But you said something a moment ago that Bucky was talking about as well. But that's the idea that you know in space, you can't just reach out and touch the satellite and do maintenance on the satellite the way you can't a car or a tank or a plane or a ship or something like that. And that is true. However, right, comma, I want to point out. You know, the satellite servicing industry is starting to develop where they're looking at robotic techniques in Cape abilities to go up in services satellite on orbit. And that's very promising off course. You got to think through the security policy that goes with that, of course. But the other thing that's really exciting is with artificial intelligence and machine learning and edge computing and database analytics and all those things that right on the cloud. You may not even need to send a robotic vehicle to a satellite, right? If you can upload and download software defined, fill in the blank right, maybe even fundamentally changing the mission package or the persona, if you will, of the satellite or the spacecraft. And that's really exciting to, ah, lot >>of >>security policy that you've gotta work through. But again, the cloud just opens up so many opportunities to continue to push the boundaries. You know, on the AWS team, the aerospace and satellite team, which is, you know, the new team that I'm leading. Now our motto is to the stars through the cloud. And there are just so many exciting opportunities right for for all those capabilities that I just mentioned to the stars through the cloud >>President, your thoughts on this? >>Yes, eso won >>a >>little bit of time talking about some of the business model implications and some of the challenges that exists there. Um, in my experience, we're still working through a bit of a language barrier of how we define risk management for our space systems. Traditionally traditionally risk management models is it is very clear what poses a risk to a flight mission. Our space mission, our space system. Um, and we're still finding ways to communicate cyber risk in the same terms that are system engineers are space engineers have traditionally understood. Um, this is a bit of a qualitative versus quantitative, a language barrier. But however adopting a risk management model that includes cybersecurity, a za way to express wish risk to miss the success, I think I think it would be a very good thing is something that that we have been focused on the J. P o as we Aziz, we look at the 34 years beyond. How do >>we >>risk that gap and not only skills but communication of cyber risk and the way that our space engineers and our project engineers and a space system managers understand >>Clinton, like Thio talk about space Force because this is the most popular new thing. It's only a couple of nine months in roughly not even a year, uh, already changing involving based on some of the reporting we've done even here at this symposium and on the Internet. Um, you know, when I was growing up, you know, I wasn't there when JFK said, you know, we're gonna get to the moon. I was born in the sixties, so, you know, when I was graduating my degree, you know, Draper Labs, Lincoln Lab, JPL, their pipeline and people wasn't like a surge of job openings. Um, so this kind of this new space new space race, you know, Kennedy also said that Torch has been passed to a new generation of Americans. So in a way that's happening right now with space force. A new generation is here is a digital generation. It's multi disciplinary generation. Could you take a minute and share, uh, for for our audience? And here at this symposium, um, the mission of Space Force and where you see it going because this truly is different. And I think anyone who's young e I mean, you know, if this was happening when I was in college would be like dropping everything. I'm in there, I think, cause there's so many areas thio jump into, um, it's >>intellectually challenging. >>It's intoxicating in some level. So can you share your thoughts? >>Yeah. Happy to do that. Of course. I I need to remind everybody that as a week ago I'm formally retired. So I'm not an official spokesman for US forces. But with that, you know, it said I did spend the last 18 months planning for it, designing and standing it up. And I'll tell you what's really exciting is you know, the commander of, uh, US Base Force General J. Raymond, who's the right leader at the right time. No question in my >>mind. But >>he said, I want to stand up the Space Force as the first fully digital service in the United States. Right? So he is trying >>to bake >>cloud baked cybersecurity, baked digital transformational processes and everything we did. And that was a guidance he gave us every day, every day. When we rolled in. He said, Remember, guys, I don't wanna be the same. I don't wanna be stale. I want new thinking, new capabilities and I want it all to be digital on. That's one of the reasons When we brought the first wave of people into the space force, we brought in space operations, right. People like me that flew satellites and launch rockets, we brought in cyber space experts, and we brought in intelligence experts. Those were the first three waves of people because of that, you know, perfect synergy between space and cyber and intel all wrapped in >>it. >>And so that was really, really smart. The other thing I'll say just about, you know, Kennedy's work. We're going to get to the moon. So here we are. Now we're going back to the Moon Project Artemus that NASA is working next man first woman on the moon by 2024 is the plan and >>then >>with designs to put a permanent presence on the moon and then lean off to march. So there was a lot to get excited about. I will tell you, as we were taking applications and looking at rounding out filling out the village in the U. S. Space Force, we were overwhelmed with the number of people that wanted, and that was a really, really good things. So they're off to a good start, and they're just gonna accomplishment major things. I know for sure. >>Preston, your thoughts on this new generation people out there were like I could get into this. This is a path. What's your what's your opinion on this? And what's your >>E could, uh, you so bold as to say >>that >>I feel like I'm a part of that new generation eso I grew up very much into space. Uh, looking at, um, listen to my, uh, folks I looked up to like Carl Sagan. Like like Neil Tyson. DeGrasse on did really feeling affinity for what What this country has done is for is a space program are focused on space exploration on bond. Through that, I got into our security, as it means from the military. And I just because I feel so fortunate that I could merge both of those worlds because of because of the generational, um, tailoring that we do thio promote space exploration and also the advent of cybersecurity expertise that is needed in this country. I feel like that. We are We are seeing a conversions of this too. I see a lot of young people really getting into space exploration. I see a lot of young people as well. Um uh, gravitating toward cybersecurity as a as a course of study. And to see those two worlds colliding and converse is something that's very near and dear to me. And again, I I feel like I'm a byproduct of that conversion, which is which, Really, Bothwell for space security in the future, >>we'll your great leader and inspiration. Certainly. Senior person as well. Congratulations, Steve. You know, young people motivational. I mean, get going. Get off the sidelines. Jump in Water is fine, Right? Come on in. What's your view on motivating the young workforce out there and anyone thinking about applying their skills on bringing something to the table? >>Well, look at the options today. You have civil space President represents you have military space. Uh, you have commercial space on and even, you know, in academia, the research, the potential as a as an aspiring cyber professional. All of you should be thinking about when we when we When? When we first invented the orbit, which eventually became the Internet, Uh, on Lee, we were, uh if all we had the insight to think Well, geez, you know whether the security implications 2030 years from now of this thing scaling on growing and I think was really good about today's era. Especially as Clint said, because we were building this space infrastructure with a cyber professionals at ground zero on dso the So the opportunity there is to look out into the future and say we're not just trying to secure independent her systems today and assure the free for all of of information for commerce. You know, the GPS signal, Uh, is Justus much in need of protection as anything else tied to our economy, But the would have fantastic mission. And you could do that. Uh, here on the ground. You could do it, uh, at a great companies like Amazon Web services. But you can also one of these states. Perhaps we go and be part of that contingency that goes and does the, uh, the se's oh job that that president has on the moon or on Mars and, uh, space will space will get boring within a generation or two because they'll just be seen as one continuum of everything we have here on Earth. And, uh, and that would be after our time. But in the meantime, is a very exciting place to be. And I know if I was in in my twenties, I wanna be, uh, jumping in with both feet into it. >>Yeah, great stuff. I mean, I think space is gonna be around for a long long time. It's super exciting and cybersecurity making it secure. And there's so many areas defeating on. Gentlemen, thank you very much for your awesome insight. Great panel. Um, great inspiration. Every one of you guys. Thank you very much for for sharing for the space and cybersecurity symposium. Appreciate it. Thank you very much. >>Thanks, John. Thank you. Thank you. Okay, >>I'm >>John for your host for the Space and Cybersecurity Symposium. Thanks for watching.

>> Narrator: Live from Orlando, Florida, it's theCUBE covering ServiceNOW Knowledge17, brought to you by ServiceNOW. >> Dave: We're back, this is theCUBE, the leader in live tech coverage. We go out to the events and we extract the signal from the noise. I'm Dave Vellante with Jeff Frick. Farrell Hough is here she's the general manager of the service management business unit at ServiceNOW, great to see you. >> Farrell: Yes, great to see you, thanks for having me. >> Dave: Awesome, you're welcome. Awesome keynote this morning, you have your baby, which is ITSM, we know, but at the financial analyst meeting and you know, you represent today's keynote, you represented, you know, more than just ITSM, which is, you know, good. But let's start there, so, awesome keynote, lot of energy, so much meat (chuckles). >> Farrell: Yes. >> Dave: In Jakarta. >> Farrell: Absolutely. We have been busy, for sure, in our IT portfolio. In ITSM we really spent a lot of time and energy in giving back to our customer base and making sure that critical capabilities and features in ITSM, have a lot of depth behind them as well. So making sure service level management's solid, service catalog, which is 99% adopted across our customer base, servicing over half a million end users, that making sure that that's solid. And then additionally, making it really easy for new customers to join onto ITSM as well by giving out of the box best practices and a guided set up format like a wizard format that they can within just a couple of hours stand up a brand new incident management process prescribed by ServiceNOW and feel confident in what they're getting. >> Dave: Yeah, so I didn't realize the number was that high in terms of adoption of service catalog. What do you see for CMDB, I mean, when you first started following ServiceNOW it was mixed, 'cause it kind of gets political, but now, today, when you talk to customers it's like, oh yeah that's a big initiative of ours, or we're already there, or what do you see? >> Farrell: Absolutely. I don't have the exact percentage in front of me but I believe that it's upwards of 70% adoption in our customer base. And that is a difference from where we were in the past, for sure. >> Dave: Which is like the mainspring of innovation, 'cause once you get there, with service catalog and CMDB-- >> Farrell: Yep, you get all your assets in there, you get all your services defined, it's go time. >> Dave: Then your operating leverage is huge in terms of when you bring out new function and the impact on the organization, the business impact, can be really enormous. >> Farrell: Absolutely. >> Jeff: And best practice out of the box is a huge, huge coo, everyone we've talked to, you know, they're smart enough now to now customization is bad. Keep it to a minimum, keep it to a minimum, do config but not customizations, so that all those upgrades are easier, easier, easier. So to come out of the box with an integrated best practices workflow, great, great solutions for the customers to get up and running quickly. >> Farrell: It is, and you know, they're asking for prescription, and we're going to give it to them. We've got our own services arm, we have a partner community, we know between all of us in this huge ecosystem what's working and what's not, and we're going to put it in the product and make sure our customers, existing and new, get best practice out of the box. >> Dave: So, kind of three areas you talked about today: service management, we just touched on, we didn't talk about the surveys, but that's cool, that's a nice little feature you guys have added. >> Farrell: Oh yes, that's right. >> Dave: So, you have new and improved surveys. Operations managements, so that's ITOM piece right? >> Farrell: Yep. >> Dave: And then business management. So give us the high level on office management. >> Farrell: I will, yeah, sure. So we announced this year that we're putting out the cloud management platform, and the adoption of cloud is long past it's tipping point. We're seeing cloud being adopted everywhere and cloud resources are extremely easy to procure, stand up, and use, and IT may or may not know about it. And that becomes just a huge problem in terms of cost and even in terms of security and compliance and when we're able to-- we made an acquisition roughly a year ago, the ITOM team, and this is basically the next generation cloud management platform, where now you're able to have a cloud portal where a end user can go and consume and, just like a service catalog, they're going to have a service catalog of cloud services that you've already provisioned very easily with the drag and drop interface, that accounts for all your policy already in those services. And so it makes it very very easy for the business to continue to operate at the pace and the skill that they need to, but for IT to make sure that we have the consistency and the compliance that we need to protect the business overall and manage cost, all with a really great user experience at the same time. So we're thrilled to be able to put out a cloud management platform. And then the second major thing that came out in the IT operations management space was around service mapping. When we went to market with service mapping it was for all on prem services and mapping out what that looked like. This time around we're just bookending it and kind of closing the gap and saying okay, let's look at what's off prem, and let's look what's in the cloud. So you get a holistic view and are able to discover resources in the cloud and on prem as well and you get that holistic view of your services mapped going forward. >> Dave: So I have to ask you, so we're always asking, when ServiceNOW gets into HR, it's like oh does ServiceNOW compete with Workday, no. And when ServiceNOW gets into security, it's like does ServiceNOW compete with FireEyes, et cetera, no no. Now when you talk about this multi-cloud, sort of mapping visibility, there's a lot of talk about, we call it sometimes inter-clouding and inter-cloud management, how far to do you go into that, I mean, can I actually orchestrate across clouds? Is it just giving you visibility, well not just, but, how should I think about the positioning of ServiceNOW in that space of cloud management? >> Farrell: We're out there to create flexibility for customers and we'll start to make it happen that you can orchestrate across different clouds regardless of what they look like. We're not totally there yet, but that's the direction it's going. >> Dave: Well nobody's there. >> Farrell: Yep. >> Dave: This is jump all for the industry. And it's got to be a huge market, I mean, everybody's doing multi-clouds. In fact somebody told me, today David Flora told me in Europe there was a mandate in the banking sector that you have to have a second source for cloud. >> Jeff: Oh really? >> Dave: Yeah, I don't know the context, but good news for the cloud vendors, right? Good news for somebody-- >> Farrell: Exactly. >> Dave: --who manages that. So, okay, and now what about, are we done with ops-- >> Farrell: That was operations management, yep done with that. >> Dave: And then how about business management? >> Farrell: Alright, on the business management side, the big news if the software asset management. We're able to deliver another new product this year, and that's really going to put a lot of power back in the hands of IT. You're no longer caught on your heels with a software audit, realizing you're out of compliance. We struggle with visibility and understanding where are all these software assets, who are they allocated to, are they actually using them, how much is it costing us, and when we're able to have visualization to that because it's on the ServiceNOW platform and we understand where all those items exist, we're able to go in and very easily reclaim licenses, or reallocate them, and to me that's found money. And I just love that. I think that's going to be great, and guess what? You want to find your sourcing for your next IT project it's right there. >> Jeff: Right, right, and you're being humble. I mean that was the thing where the biggest roar came up from the crowd, without a doubt. Super, super well received. >> Dave: We were talking to CJ this morning about how it works and you get the platform, the platform comes out with all these features, and then the business units take advantage of those features. Now of course he described it differently, he said you start with the customer, and then you figure out what to put in the platform knowing that the business units are going to take advantage of it. But when you think about intelligent automation you gave an example of predictive maintenance today, so that's a use case for that so called AI or deep learning, machine learning. So talk about that a little bit. And then I want to get into the DX continuum piece as well. >> Farrell: Yeah, absolutely. When we're sitting on this data set that our customers have and they want us to take advantage of it for them, on their behalf, we're able to go back and apply algorithms to those data sets to say what's the norm? And did it have a good outcome? And all that data is in there, we're able to model it now, you're not having to go do that in some--export that into some other system to try to figure out, with some advanced analytics, what's that looking like, you're able to be able to say very clearly, listen, here's what the normal pattern of behavior is, and establish that for everything else going forward. So it becomes really clear where outliers exist and what suspect events or suspect alerts look like in your environment and then you can fire off a process to say look, this looks like a problem, and with certain signposts associated to it, go ahead and automatically open up that incident. You apply it to change management where you're talking about predictive maintenance. Something has enough failures automatically schedule a change window or decommission it, fail it over, back it out, move it out of the way, so that it's not causing a problem anymore. We put so much on humans to do for so long because the technology wasn't there to allow us to do it, well it's time, it's here now. And so we can take some of the burden away. >> Dave: I just had a thought, we talk in this industry so much about consumerization of IT and trying to mimic consumers, Fred Luddy talks about all the time. What you just described, I thought about an experience of an iPhone user, and anytime you do a migration, my wife just migrated from an android to an iPhone, what question was asked, is it backed up? What you just described is proactive. You're way beyond is it backed up, you're at the point of, we're going to just eliminate any possibility of a disruption. So I guess my question there is, is enterprise IT finally, not only catching up, but in some regards surpassing, this consumerization trend? >> Farrell: Hey, I think there's an opportunity to leapfrog, all the way, and I'm behind a 100%. I do, I think exactly that. And why not get way out ahead and over our skis with that and over-deliver and show that yep, we can see what's coming, we're sitting on all this data. When you choose to go to the cloud, and all that data is accessible, and you're on a single platform, it's all intermingled. You're not having to stitch together, create a data lake that's got all these different integrations pulling data and trying to sort it out from there with some data scientists or some business analysts looking at it, you're now able to lean in way more with your operation and really start to take care of it and truly own it. >> Jeff: I was just going to say my favorite part of your keynote today was kind of teeing off what you said, which is using machine learning and artificial intelligence on relatively simple looking processes that are painful, cumbersome, and horrible, like categorization, prioritization, assignment, to take the first swag, let the machine take the first swag at that stuff, and take that burden off the person because it's tedious, it's cumbersome, and it's painful, so it's this really elegant use of machine learning and AI, which is talked about all the time, on a relatively, again, simple looking activity, that just delivers tremendous value. >> Farrell: Yeah, I'm really really excited about that part because there's a lot of mystic and-- ah, I don't know what the right word is, maybe misunderstanding potentially, which can lead to mistrust of AI and machine learning and what's really going to come of it. And when we're able to say using supervised machine learning, which is the model that we're going after with the auto-classification, you can work with customers to be able to to let them tune the level of accuracy that they are comfortable with. And so you're building trust right away with a really simple example of auto-classification or auto-categorization, that is so frustrating for both parties. The person who is filing the incident, and the for the person who's going to be supporting and fulfilling on that incident as well. And I just love that fact that we can start to dip our toe into this pool and wade in and create trust along the way so we don't leave anyone behind or create mistrust in our user-base that we're just trying to get rid of them in some capacity or pull the wool over their eyes, we're not and we're going to be really transparent about in the way we do it and I think that's phenomenal. >> Jeff: And it's dynamic right, so it continues to learn. You have Spotify, you have a playlist, I like this, I don't like this, the playlist hopefully gets better, so. >> Farrell: That's right, because it took your input. >> Jeff: Correct, right. >> Farrell: And so taking input from the end users is going to then help train that system over time, that's correct. >> Dave: I got so many questions for you. (Jeff laughs) >> Farrell: Okay! Give 'em to me. >> Dave: So the auto-classification piece, that comes from the DX continuum acquisition-- >> Farrell: It does, yes. >> Dave: So explain that, I know you guys re-platformed everything, but what did that give you and let's get into auto-classification a little bit. >> Farrell: Okay, well it gave us some incredibly talented smart engineers and some really great intellectual property in terms of algorithms that we are able to now apply. When we re-platform something we're making sure that it works in the ServiceNOW platform stack and that it is going to be available and pervasive for every application that gets built on top of the platform. >> Dave: Okay so, you had said before, we're not just building a data lake, which, I want to talk to you about that too, 'cause a date lake as we know turns into a data swamp and it's just a mess and then you got to really do a lot of heavy lifting. >> Farrell: Smelly, don't like that. >> Dave: Right? Not good. So-- >> Jeff: Scary critters. >> Dave: You're auto-classifying at the point of creation I presume, or use of that data set. So how does that all work? How is it being applied? Where do you see customers getting value out of this? Explain that a little. >> Farrell: Well really I see in the ITSM side and the IT Space and in the ITSM side specifically, anything that you've got to apply a drop down field to, whether you're an end customer doing it through a service portal, or you're an IT worker, too, like let's help those guys out, why not? Anytime you need to fill out a field through a drop down mechanism, it's one discreet set of values, that's a candidate there. Now you want to have a large data set, which is why incidents, incident category, or assignment, assignment group, or what skill set might be required to work that particular incident, works because there's tons and tons and tons of incidents out there so we have lots of examples around what it could possibly be. And then that's what the data model would be built on. This auto-classification is not meant for the obscure or the random or the infrequent. So when we're talking about high volumes that a service desk sees, this is the perfect setup to apply it. >> Dave: So how will it work? I'll have a corpus of data with a bunch of incidents and I'll just sort of tell the machine go classify this? >> Dave: And it'll do some kind of process? >> Farrell: You're going to have a set of data a portion of the records you're going to use for the training model, the other portion you're going to leave behind, almost as the control group. And you're going to go apply the algorithms to that training set of data and it's going to start to learn and you're going to tell it what fields you want it to learn from and pay attention to and spit a model out on the other side on and it's going to crunch through all that data and it's going to give you a model on the other side, and you'll look at it and see if you agree, and then you're going to take that model and you'll apply it to that control set and you're going to look at what level of accuracy came out on the other side and you'll decide with that data set what accuracy level you want to have. For me, 70% accuracy will work for me on password reset. 'Cause, in all likelihood, what's it going to be? But maybe for a VPN issue I want 90%. You'll be able to start applying accuracy by category to then tune in exactly how you want things to work to make sure you get that good user experience. >> Dave: And then you'll continue to train that model and iterate. >> Farrell: Yes, absolutely. And you'll be able to train it and often as you like. I mean on demand, like yep, I want to train it again. And when you have a service desk worker who goes back in and re-categorizes, because yeah, that wasn't quite right, that's just the same thing as clicking the like button, thumbs up, thumbs down, on Spotify. You're right that you've just given it feedback. When you train it again, it takes that feedback into account. >> Dave: And then the subsequent incidents get auto-classified. >> Farrell: They get the learning. They get the learning. There's not magical learning that happens in this particular case, the technology's not evolved to that state, there's no unicorn back there that's doing all the learning for you. It takes feedback and it'll take some tuning, but hopefully in being able to make the feedback mechanism very easy, the tuning happens naturally, therefore the model gets better over time. >> Dave: Well it's a great use case because it's relatively narrow, and you have tons of data, and it can be implemented right away. >> Jeff: And like you said, even if it just helps you partially down the road, it's better than zero down the road, especially these repeatable processes that have to happen over and over and over, it's like oh please shoot me, this is the work that machines are supposed to do because it's mundane and repeatable and-- >> Farrell: Mind-numbing. >> Jeff: Mind-numbing, thank you. Let me get to solving the customer problem. >> Farrell: That's right. >> Dave: Okay so when we first encountered ServiceNOW we did our first Knowledge, it was from 2013, and it was at the height of the big data sort of hype-cycle. And so we would ask, of course we asked, well what about data, what about big data? The response was always well we got a lot of data and we're looking at that. But now we're here. And you mentioned earlier, it's not some data lake that you're processing as offloading your data warehouse, so what are you doing in that space? So it's not a data lake, it's a corpus of data and you're basically applying these AI and intelligent automation models to, can you explain a little bit about how that works? >> Farrell: Sure, well first off we won't do anything, we have to have our customer's permission to be able to use their data, they showed interest in machine learning services then they will give us permission to leverage their data and all customer data is separated too, within their own instance, within their own database, there's no co-mingling of data, so there will be no data lake whatsoever. But what we are able to do, and it's on a personal level, which I just love, because that's who we are as a company, that we're offering personalized supervised machine learning, personalized auto-classification, we're not taking all the data of all of our customers, kind of aggregating it up and then building models against that, and then saying oh I think this model would pertain to you and then it's only 25% accurate or even relevant. We're building a model very specific to you. And working with your data set and we have access to it, with your permission, and we'll go build that model, using the training set as we described, and then go test it out, and then help you go re-deploy it. So we'll pull that data into a central instance, help retrain it, and then move it back into your instance so that model is always constantly tuned and then you get to decide when you retrain it. >> Dave: So who's we in that example? You have a team of data scientists that do this? >> Farrell: This will be in our platform team. It's a platform service. You don't need data scientists to, I would say on the customer side, maybe if they were wanting to interpret some of that data or do something with it maybe they'd have a data scientist. This is just tried and true engineering and having a good service model behind it, it's just a central instance. >> Jeff: Do--I'm sorry, I interrupted. >> Farrell: No, I was just going to say through our acquisition DX Continuum, those engineers are building those training models and will keep them up to date, but they're not literally turning a crank when that data comes in and it'll be-- >> Dave: So it's a model that they apply, it scales, it's part of the service. Now you iterate that over time-- >> Farrell: That's right. >> Dave: But it's the-- >> Farrell: And you can build out other training models. So we just talked about auto-classification for instant, but this can extend in other areas as well. >> Jeff: Well I was going to say, do you think it's an opportunity for the ecosystem that has specialty expertise around, pick your favorite topic area, we're talking to someone about oil and gas earlier today, that they know what the model is way beyond just simple correlation to take in this and it flow and predict that, I think the example was that the well cap's going to break, or whatever. So do you see that potentially as an ecosystem contribution as well around more specific use cases? >> Farrell: Well I think that would be super cool. If we had customers of similar ilk, whatever that looked like, wanting to collaborate and share and crowdsource something for a greater good that wasn't competitive, I think that that would be amazing to be able to do that. And we would be able to facilitate it. We don't have any current plans to do that right now but I could absolutely see it. >> Dave: Well we've talked about the ecosystem through for years, to see it just burgeoning and awesome story. Thank you for coming on theCUBE and doing a brain dump on us and educating us. >> Farrell: Yeah, thank you so much-- >> Jeff: You really had a great opening line, "exciting time to be in IT," that was your opening line, the key night, I know you've got the excitement >> Farrell: It is! This is the best time to be in IT. I mean oh my gosh, it's fabulous. >> Dave: You're exploding. Alright Farrell, thanks very much. >> Farrell: Alright, thank you. >> Dave: Alright, keep it right there buddy, we'll be back with our next guest, theCUBE, we're live from Orlando, be right back. (techno music)

>> Announcer: Live from Orlando, Florida, it's The Cube. Covering Service Now Knowledge 17. Brought to you by Service Now. >> we're back, welcome to Orlando, everybody, this is Service Now Knowledge 17, #Know17. I'm Dave Vellante with my cohost, Jeff Frick. Dave Wright is here, he's the chief strategy officer of Service Now and a long time Cube friend. Good to see you again, David. >> Good seeing you again, guys. So off the keynote, we were just talking about intelligent automation and what's new in your world. New way to work is really kind of the broader theme here, people are changing the way they work. So what is intelligent automation and how does it fit in? >> So what we did when we built intelligent automation is we wanted to come at it from a different angle. So we didn't want to build a product and then look for a solution that it'd work with, we wanted to go out and speak to people and see what are the challenges that they faced. So what we did was we came up with kind of four key areas where people wanted to be able to improve or do things differently. We wanted the capability to be able to predict when something was going to happen from an event perspective. We wanted to be able to use machine learning to be able to augment it. So to be able to perhaps order, categorize, or provide severity, or in the case of change, provide risk analysis. We wanted to be able to do that at a machine level rather than use a human triage level. Then people were coming back saying we feel we're doing a good job, but we want to understand if we're doing a good job, so that was the concept of expanding out the benchmarks program to include more and more benchmarks for people to see how they compared against their peers. And the final element was people wanted to set themselves performance targets, but then they wanted to understand when am I going to get to that target. So what we have to do then was augment the whole performance analytics suite to be able to do predictive analytics. So they're kind of the four core areas that sit in the intelligent automation engine. We can go into as much detail as you want around them, but it's pretty interesting. >> So help us understand, 'cause I get a little confused about, you know, when I hear something like a big announcement coming up at Jakarta, platform, but then I see bits and pieces hit the various products. Can you maybe set that up for us and help us understand. >> Yeah, so what'll happen is the benchmarking, the predictive analytics capability, and the ability to do predictive service usage, they will all appear in Jakarta. And then the actual ML side where we can do the auto-categorization, that will appear in the Kingston release. So by the end of the year, everything that's shown will be available. >> And it hits the platform and then the modules take advantage of that, is that correct? >> Yes, so what is happening at the moment is the initial use cases have gone through around IT. So it's IT looking at well how do we process events so that we can get a precursor to a bigger issue and predict the bigger issue. How do we categorize when someone comes in with an IT request or an IT incidence, how do we make sure it goes to the right people and gets the right categorization. And then what'll happen over time is we'll be able to use that for the security module, we'll be able to use it for customer service, for human resources, because it's all, in the same way we said, it's all a different type of service, it's exactly the same process to be able to categorize, to prioritize, to put a severity on something. And then more long term, we can use this technology to look at all kinds of different files on the system. >> And when you say IT first, it's ITSM and ITOM, is that right? >> Yes, ITSM and ITOM. >> Okay, and so good, I like this, this is a very practical example of, generally, AI, as people don't really know what it is. You're going to tell us that something's going to break before it breaks is usually the use case here. >> What we realized is because we can now start to look at time series data and analyze time series data, there's a few things we can do. So the first thing is we can do corelation, so we can start to link events together, so people didn't spend ages just trying to fix the symptoms, they could go right down to the disease and say well, this is what's causing everything else. The other thing we could build in because we could understand what normal looked like is we could build an anomaly detection. So normally, an event says hey, this has got a high CPU, or this switch has gone down. Now we could say this just looks weird. We've got an activity that never normally happens to this level, or it never normally happens at this time of day, or we've never seen this before on a Saturday. And we can actually generate an anomaly alert at that point. Now, the anomaly alert might be a precursor to a traditional alert where you might get. I think the example used in the actual keynote was we get a large number of user threads on a system, that's probably a precursor to high CPU. So once we've started to be able to do that correlation, the more and more examples you get, the more you can start to predict. So you can say as soon as I get that precursor, I have a level of confidence of when we're going to see the next event. So now you get a brand new type of incidence, you'll get an incident for a predicted failure. So the system will say I've seen this, this, and this, I'm 86% confident we've got two hours and we're going to lose this service. So the whole concept of this was how do you work at light speed. And my whole challenge was what happens when you do it before it happens, is that beyond light speed, it was very difficult to try and wrap your mind around it. >> The speed of light is too damn slow. >> Yeah, it's too slow, no one's going to wait for it. >> I did get a tweet back where someone said if you fix everything before it happens, we'll get no budget because everyone will say nothing ever happens. >> If a tree falls and nobody's around. And so there's a risk, sort of risk scoring algorithm in there that helps you say okay, this one is going to fail and you better take advantage of it. >> Yeah, so if you imagine seeing a precursor to something, you look how many times that precursor has caused that event, that allows you to give a degree of probability as to how likely you think it's going to happen. And it might be you decide to set a threshold and say look, if it's below 50%, don't bother doing it. But if it's above 70%, do it. Or if it's a specific type of issue, if it's something around security, and you're above 90% confidence, I want it flagged as a priority one issue. >> Yeah, but if it's my picnic wiki, so can you inject the notion of value in there, I guess the question. >> Dave: Yes, yeah, you can. >> I want to ask you about this categorization piece, even though it's coming down the road with Kingston. That's been a challenge for organizations in so many different use cases. I mean, the one I can think of, you know, is like email archiving and the federal rules of civil procedure, all that stuff when electronic records became admissible. And everybody sort of scrambled to categorize. But it was manual, they were using tags, it just didn't work, it didn't scale. So the answer was always technology to auto-categorize at the point of creation or use. But even then, it was complicated and the math kind of worked but you couldn't apply it. What's changed now and what's the secret sauce behind it? Was that part of the DX Continuum acquisition, maybe you can explain that. >> So we acquired DX Continuum, that gave us eight really bright math Ph.Ds who were data scientists, who could come in, who could look at data in a different way. But I think technology also drove it. So you've got the ability to have the compute power to be able to do the number crunching, but you've got the volume of data as well, I think the more volume of data you get, the more accurate it is. So we found if we're going to train auto-categorization, we need between 50 and 100,000 records to be able to get to a degree of accuracy. And then obviously, we can just keep on doing it again and again and that accuracy gets better and better over time. But even when we ran this out of the box on our system for the very first time before we'd rewritten it on the platform, first time we ran it through, it was 82% accurate straight off. Now, the real interesting thing about when you do something like categorization, it's almost as important what you get right as not guessing when you're going to get it wrong. So we wanted to be be very sure that they system would say I am 100% confident that this is where this is. But if I don't know it, I'm not going to guess. I'm not going to say well, it's 75% confident, so I'm going to say it's this. At that point, you want to say I just don't know. So these, 18%, for example, in this case, I don't know. And then over time, you get to reprocess the things that you don't know, and that percentage gradually goes up. So now, I think in-house, we're running into the 90% region. >> So the math, though, has been around forever. I mean, things like support vector machines and there are other techniques. What is it about this day and age that has allowed us to effectively apply that math and solve this problem? >> So I think what you get now, if you look at the DX Continuum technology used, I think it was five different methodologies for being able to interrogate. And it was neural nets, it was using base, but I think what gives you the big advantage is people have always taken live data and then tried to do this prediction. That's probably the wrong way to do it. If you take historical data and then run it, you just find out which one works. And if this algorithm is working the best for you based on the way you structure your data, then that's the algorithm you focus on. And that's exactly the way predictive analytics works. What we do is we were initially looking, saying okay, well we've got these three different models we can use. We can use projection, we can use seasonal trend lows, we can use AREMA with the auto-regressive moving average type solution. Which one are we going to use? And then we realized we didn't need to guess. What we could do is we could give the system historical data and say which one of these most accurately maps and then use that algorithm for that data set. Because every data set is different, so you might look at one data set where it's really spiky, so you don't want to use projection because if you choose the wrong points, your projection of them is effectively out. So it might be, in that case, you want to use STL and be able to smooth out some of the curves. So you have to, every time you want to do predictive analytics around a specific data set, you need to work out what mathematical model you need to use. >> So the data is then training the models and the models are your models, correct? >> Yes, yeah. >> And now you tell the customer, and I'm sure you do, that this is your data and your data is not going to be shared with anybody outside of your instance. But the model, the gray area between the model and the data, they start to blend together. Is there concern in your customer base about oh, I don't want the model that you train going to my competitors, or is this a different world where they feel as though hey, I want to learn, like, security. What are you seeing there? >> So this is the uniqueness that we, you don't get a generic ML where we look at everyone's instance and train across that. We can only train for your instance. And that's because everyone does things differently. You go to some companies where their highest priority issue is a sev-9, whereas another customer would have sev-1, so you've got people doing different implementations like that. But let's say I tried to do everyone's, and I went through and I said look at this description, this is a networking issue, so I'm going to categorize it as networking. And you haven't got a networking category, you've got networking infrastructure or networking hardware, then it fails. So I have to build a model that's very specific to your instance. So every time we do this, we'll build it for each customer. So it's kind of customized artificial intelligence machine learning models that sit within your instance. >> So my data, your model that you're basically applying for me and only me. Period, the end. >> Yeah, so we do the training on your data and we inject that model, which is your model, back into your instance. >> And now, the benchmarks, you guys have been talking about benchmarks for a while, this is sort of taken it to a new level. So how do you roll that out, how do you charge for it, what's the strategy there? >> So what people do is they effectively subscribe to it. So they're willing to share their data, we're at that point, allowing them, so it's almost a community issue, at this point, everyone is sharing data across the systems. Now, we added another nine benchmarks in the Jakarta release and now I think there's 16 benchmarks. Ive been mainly focused around IT and ITOM, but as we get more and more customers coming on in CSM and more on HR and more on security, we'll be able to start to introduce the whole concept of benchmarking those as well. But the thing you can do now is you don't just see the benchmark and how you perform, we can also use analytics to show how you're trending as well. So you might be better than people of a similar size or people in the same industry, but it might be that you're trending down and you're actually going to start to get close to being worse than them. So the concept here is you can take corrective measures. But also, it gives a lot of power to customers, not just to be able to say I think I'm doing a good job, but to be able to go to senior management and say this is how customers that look like us are currently performing. This is how customers in the finance sector perform. This is how customers with 100,000 people or more perform. And they can see look, we're leading in this, this, and this area, and they can see where they're not leading, and they can actually start to see how they'd address that. Or it might even be that you start to build relationships where they could say to their account manager who are the people who have got this best in performance type thing, could we meet with them, could we exchange with them? The evolution of this will be on the performance analytics side when we start to get to Kingston and beyond will be to be able to do not just the predictive analytics, but to be able to do modeling and to be able to do what-if. And the end goal is we've gotten to the point where we've got predictive, you want to get to the point where you get to prescriptive. Where the system says this is where you are, if you do this, this is where you'll get. >> That's what I was going to ask you, is it intuitive to the client, what they should do, and what role does Service Now play in advising them. And you're saying in the future, the machine is actually going to-- >> Yeah, could be able to say hey, well, if you want to, let's say you want to improve your problem closure rates, you could say well, when you look at other customers, an indicator of this is people have gotten much better first call incident closure. So what you need to do is you need to focus on closing first call incidents because that's going to then have the knock on effect to driving down the way you resolve problems. So we'll be able to get to that, but we'll also be able to allow people to actually model different things. So they could say what happens if I increase this by 10%? What happens if I put another 10 people working on this particular assignment group, what's the effect going to be, and actually start to do those what-if models, and then decide what you're going to do. >> To prioritize the investment to get the numbers down. It's interesting too, 'cause it's a continuous process, as you mentioned, it's this whole do the review once a year, do your KPIs. That's just not the way it works anymore, you don't have time. And to use the integration of the real time streaming data, which is interesting that you said not necessarily always what you want to use first compared to the historical data that's driving the actual business models and the algorithms. >> I think the thing about the whole benchmark concept is it's constantly being updated. So it's not like you take a snapshot and you say okay, we can improve and move here, you see if everyone else is improving at the same time. So there might just be a generic industry trend that everyone is moving in a certain direction. It might be that as we start to see more things coming online from an IOT perspective, I'll be interested to see whether people's CMDBs start to expand. Because I don't know if people have yet established whether IT is going to be responsible for IOT. Because it's using the same protocol for its messaging, how are you going to process those events, how are you going to deal with all that. >> So I guess it's the man versus machine, machines have always replaced humans. But for the first time, it really is happening quickly with cognitive functions. And one of your speakers at the CIO event, Andrew McCafee and his colleague Erik Brynjolfsson have written a book. And in that book, they talked about the middle class getting kind of hollowed out and they theorize that a big part of that is machines replacing them. One of the stats is the median income for U.S. workers has dropped from $55,000 to $50,000 over the last decade. And they posited that cognitive functions are replacing humans, and you see it everywhere. Billboards, the kiosks at airports, et cetera. Should we be alarmed by that? What is your personal opinion here? And I know it's a scary topic for a lot of IT vendors, but it's reality and you're a realist and you're a futurist. What are your thoughts, share them with us. >> People have different views on this. If you look at the view of executives, they see this see this as potentially creating more jobs. If you look at the workforce, I completely agree with you, there's a massive fear that yeah, this is going to take my job away. I think what happens over time is jobs will shift, people will start doing different things. You can go back 150 years and find that 90% of America is working farmland. And you can come now and you can find out they're like 2%. >> Not too many software engineers either back then. >> Not too many. Hard to get that mainframe in the field. What I think you can do is you can not just use AI or machine learning to be able to replace the mundane jobs or the very repetitive jobs, you can actually start to reverse that process. So one of the things we see is initially, when people were talking about concepts like chat bots, it was all about how do you externalize it, how do you have people coming in and being able to interface to a machine. But you can flip that and you can actually have a bot become a virtual assistant. Then what you're doing is you're enabling the person who's dealing with the issue to actually be better than they were. An interesting example is if you look at something like the way people analyze sales prospects. So in the past, people would have a lot of different opportunities they were working on. And the good sales guys would be able to isolate what's going to happen, what's not going to happen. What I can do is can run something like a machine learning algorithm across that and predict which deals are most likely to come in. I then can have a sales guy focusing on those, I've actually improved the skills of that sales guy by using ML and AI to actually get in there. I think a lot of times, you'll be able to move people from a job that was kind of repetitive and dull and be able to augment their skills and perhaps allow them to do a job that they couldn't have done before. So I'm pretty confident just based on the impact that this is going to have from a productivity perspective, where this is going to go from a job perspective. There's a really cool McKinsey report and it talks about the impact of the steam engine on what that drove on productivity and that was a .3% increase in productivity year and year over 50 years. But the prediction around artificial intelligence is it'll produce a productivity increase of 1.4% for the next 50 years. So you're looking at something that people are predicting could be five times as impactful as the industrial revolution. That's pretty significant. >> Next machine age, this is a huge topic. We're out of time, but I would love for you, Dave, to come back to our Silicon Valley studio and maybe talk about this in more depth because it's a really important discussion. >> I'm always around, happy to do it. >> Thanks very much for coming on The Cube it's great to see you again. >> All right, thanks, guys. >> All right, keep it right there, everybody, we're back with our next guest right after this short break. Be right back.

>> Announcer: From Orlando, Florida, it's theCUBE, covering ServiceNow, Knowledge17, brought to you by ServiceNow. (upbeat music) >> In 2004, Fred Luddy had a vision. He was the founder of ServiceNow, and his vision was to create software that was really simple to use, to automate workflows within organizations. Two years later in 2006, was the first ServiceNow Knowledge. He rented out a room at a hotel that could support 50 people. 30 minutes before that event, nobody was in that room. By the time, the time came to start the first ServiceNow Knowledge, 85 people were in the room, talking to each other about this transformation that was occurring in their business. And as they started talking to each other Fred Luddy stepped back and said, you know what, to have a successful conference I just need to let people talk to each other. And here we are today, in 2017. 15,000 people at the ServiceNow Knowledge. Welcome to Orlando, everybody. My name is Dave Vellante, and I'm here with my co-host Jeff Frick. This is, I believe, our fifth Knowledge, Jeff. >> Just look at that. 14, 15, 16, 17. Fourth or fifth. (laughing) >> Fourth or, no. We started at the Aria Hotel in Las Vegas, with about 4,000 people and now we're up to 15,000. This is a story of a company that did an IPO right around 100 million, brought in an excellent CEO, Frank Slootman. In six years his company has exploded to 1.4 billion dollars. They're on a path to do 4 billion dollars of revenue by 2020. They've got a 17 billion dollar market cap. If you look at software companies over a billion dollars, there is no software company that's growing as fast as ServiceNow, 30 plus percent a year, and throwing off as much free cash flow as ServiceNow, growing at about 45%. So they are incomparable in terms of comparing to other software companies. They're on a tear, the stock prices are up. Lo and behold Frank Slootman, the CEO, is getting out at the top. Bringing in a new CEO, John Donahoe. I feel like it's you know, an NFL quarterback, It's Bill Walsh handing the reins over to George Seifert. Maybe, and as I say, getting out at the top. John Donahoe, totally different style. We're going to be talking to him on theCUBE, just finishing up his keynote now. But, Jeff, here we are. Our fourth year, I guess, at Knowledge. And, pretty amazing transformation in this company. >> It is a pretty amazing transformation. We talk a lot about big data, and we talk a lot about cloud in many of the shows we go to but what we probably don't talk about enough, and we are going to for the next three days, is the success of SASS apps. And, as I always like to joke, there's a 60 storey building going up in San Francisco that Salesforce is completing to show you the power of SASS apps. And I think, with the ServiceNow story, is, more of that same story, you know. They started out with a relatively simple idea, Fred wanted to make work easier. And he started with the ITSM because that was an easy place to get going. But really, it's about simplifying workflow in a SASS application, letting people get work done easier. And it's pretty interesting, Because now, as you look around, day of the conference, they've got five bubbles, or five balls, or five posters, to really symbolize how they've moved beyond just ITSM into HR, customer service, biz apps and security. And applying the same foundation, the same method, the same software, to get after more and more of the workloads that are happening inside the enterprise. >> From a company perspective, this story here is about execution. The company, as I said, I gave you, shared with you the financials, they've penetrated the Global 2000, over 50% of their average contract value comes from the Global 2000. And there's significant upside there, as well. In addition, their average contract value is growing very dramatically. I was speaking to some customers and asking them, what was your deal size when you first started with ServiceNow? They were like, it was small, it was like 60,000 contracts. Now they have many, many customers, well over a million dollars, several customers over five million dollars, so this is a company that is largely focused on large organizations, but also governments and mid-sized companies. Not small businesses, yet, Jeff. You and I have been dying to get a hold of ServiceNow for small business. They announced Express a couple years ago, but what Express really was, was a way for larger companies to try, you know, get their feet wet before they really jump all in. So, we are still waiting for that day, but in the meantime, ServiceNow has a lot to do. As they say, their goal now is to be four billion by 2020. It feels like, when we first covered ServiceNow Knowledge, we said wow, this company reminds us of the early days of Salesforce, they've got this platform you can develop on this platform, you know, call it paths, or whatever you want to call it. But, we at the time said they were on a collision course with Salesforce. Now, there's plenty of room for both of those companies in the marketplace. Salesforce obviously focused predominantly on Salesforce automation, ServiceNow really on workflow automation. But you can see, though, two markets coming together. >> Right, right. >> People really, you know SalesForce, we try to use it for a lot of different things. And so giant markets built on the cloud built with flexibility to add volumes we started at problem change management help desk type of things within IT service management, and we're seeing that expand dramatically. And one of the things that you've always emphasized, Jeff, is the ecosystem. Take us back to the early days, of when we walked the floor of the original Knowledge that we did, that was four or five years ago. The companies that you saw there are much different than what you see today. >> But the passion is still the same, and that's why we've loved coming to this thing for so many years. It's because it's one of the companies that has a real passion. There was a shout-out to Fred, which is where it all started you know, I think Frank did a great job continuing that, and now clearly John is a really polished guy. Did his time at Bane, eBay, which he talked about as a community based environment, and that was built on the strength of it. But the other part in terms of their expansion, their TAM expansion, which is always a popular topic is, John talked about IT living at the intersection of interconnectedness across departments. And they've really done a good job of leveraging that. And he talked about a simple HR on-boarding process, to highlight all the departments that are taught. Securities, facilities, you need to get your badge, you need to get your laptop, you need to get checked in. So, they're leveraging this and coming up from the bottom, and we talk about IT being an agent of transformation and not a cost center, well what better way to do that than to continue to simplify all these basically mundane processes. But, again, just start eating them up, and pulling more and more processes into the ServiceNow platform. >> The key to success from a customer standpoint is to adopt a single CMDB, and to adopt a service catalog. Jeff, when we first started following ServiceNow, and we talked to the customers, not everybody was adopting a single CMDB. That was a very political, sort of football. When I talk to customers today, many more, just anecdotally, have adopted the CMDB. What that gives the customer and ServiceNow, is tons of leverage. Because you essentially have that single source of truth, and then you can use that as a ripple effect across all the other innovations that you drive with ServiceNow. So, for example, you start with help desk and change management and problem management, and then you move onto, maybe, IT operations management. And you're automating those tasks. Then might you move onto HR. You might move onto logistics, or marketing. You're now dealing with security. The perfect example they often give is on-boarding. When you on-board a new employee, there's six or seven or eight departments that you have to talk to. There's at least eight, nine, 10 processes. You got to order your laptop, you got to get a phone, you've got to get your office, you've got to get on-boarded to HR. All of these things that have to occur, that are generally separate phone calls, or you're walking down the hall. ServiceNow when you on-board, they give you the example, they're eating their own dog food. You go into the portal and you do all these things. And it has a ripple effect because of that single CMDB, throughout the organization. And so that's given ServiceNow a lot of leverage within these companies. What you hear from customers is: one, it's complicated to install this stuff. And in the early days especially when there weren't as many experts in ServiceNow. So it used to take a couple years to implement this. Second is your price is too high. You know, you hear that a lot. If that's your biggest hurdle, you're in good shape. What ServiceNow has to do in my view, Jeff, is two things. One, is got to tap the ecosystem. And you've seen companies like CSX now, DX Technology, and Accenture, KPMG, EY, join the fray. I always joke that SIs love to eat at the trough. Well, ServiceNow is becoming a big, robust ecosystem, with a giant TAM. So, ServiceNow has to lean on those partners very heavily to go in and accelerate implementation, convey best practices. ServiceNow has a program called Inspire. Which is a lost leader. It's one of the best freebies in the industry. Where they will go in and share best practice with their largest customers. And in doing that in conjunction with the SIs, to accelerate adoption on the price side, this company and I think John Donahoe is perfect for this, really has to increasingly emphasize the value. I think to date Jeff, it's been a comparison. Well, I can get this from BMC for this much, or HPE for this much, or IBM's got versions of that. Or, other competitors in this space. ServiceNow has essentially, their pricing has been compared to them. What they have to do is shift the conversation from cost, and price, to the value of the delivery. >> Biggest surprise. You got to spend a little day, kind of, behind the curtain in the analyst day. Biggest surprise that came out of that, for you? >> I don't know if it's a shocker, but it was certainly underscored, is the actual amount of upside that this company has, because they have, you know, penetrated the Global 2000 pretty substantially. But what struck me was their ability to add new capabilities, and add, expand their TAM. You know, I think I wrote a piece in 2013 basically sizing the TAM. When ServiceNow first IPOed, Gartner came out and said this is a dead market, help desk is an 8 billion dollar market, where are they going? I followed that up with a piece that said you know, this TAM is quite large, it's probably about 30 million. And I shared with the Wikibon audience how it could get there. I think I underestimated that. I think the TAM is 60 to 100 billion dollars. And the reason is that ServiceNow is able, Fred Luddy said when we first interviewed him, it's a platform. I took it out there and said here it is. >> Right. >> And the VC said what can you do with it? And he said anything! >> Revolutionized platforms. >> And they said, well, we're not going to fund it. Right, and so what they've been doing now is adding modules, and one of the ones I'm most excited about is security. And it's not competing with the FireEyes, and the Palo Alto Networks and the McAfees. It's actually automating a lot of the response to security. Automating the run book, automating the incident response. And doing so in a way that actually builds that ecosystem up, and is the glue that hangs it together. So, I guess the biggest eye-opener for me, Jeff, I talked earlier about the revenue growth, and the free cash flow growth, for a billion dollar plus company. What was surprising, the biggest eye opener or surprise to me, was the sustainability, in my opinion, of that upside. >> Right. But if it works, right, no one's going to give it up. And if the efficiencies are so much better, no one's going to give it up. I just, like, it does other huge categories of software, right? There's CRM which they're playing a little bit into not coming at it from kind of a sales perspective, but kind of coming at it from a customer management perspective. There's HR, which they're clearly going after. There's ERP, which they're probably not in a position to do in the immediate term. But there's still a lot of work getting done in large enterprises that can use a significant amount of customization, automation, with a little big data twist in the back. And, a real eye to the customer experiences, as the millennials more and more in the workforce, and the expected behavior of enterprise apps needs to mirror more, what we get on our phones. So I think they're in a pretty good position. >> TSM is the core. Everything stems from that. That's sort of the main-spring. And really, IT are their peeps, as Frank Slootman used to say. (laughing) ITOM, IT operations management, is another large and substantive business. Not as big as ITSM, but bigger than the others. Customer service management is a new and growing area. Security is a huge upside in my opinion. HR they've been at it for a while, we've talked to Jen Straud many times. And that's a big growth area. So these line-of-business entries are what's going to power the growth of ServiceNow going forward. There's also MNA, we haven't talked about MNA. When we first walked around the ecosystem on the exhibit floor at the Aria, four or five years ago, what we saw were a number of companies that could fit right into the ServiceNow platform, so one of the more prominent companies that ServiceNow acquired was DX Continuum. It's sort of an intelligent AI, machine-learning system. They're deploying that to help predict outages, part of their IT operations management service. And they'll use that elsewhere. So it's a very specific AI, we cover AI, we cover autonomous vehicles, and so forth. That's actually a great use case. So much of AI is fuzzy. So much of deep learning and machine learning is like how is that applied? Well, predictive analytics, to say OK this component is going to fail, replace it. Or, move the work off of that server. That's a real tangible use of AI. So we've seen ServiceNow use MNA. So what it does when it acquires a company, it has to go through cycles of re-platforming. ServiceNow doesn't just bolt on third-party products. We basically rebuild them from scratch on the platform. >> Right, right, ease into the platform. Which is what you have to do. Which is, kind of partner what SASS is all about, and in the early days of SASS there was a lot of push-back, because everybody thought they needed customization. Well, you didn't really need customization because you can't have 47 versions of the platform out there. What you need is the ability to configure. And have great configurability, and that's what good platforms do. And that's what Fred tried to build. And oh by the way I got to get started, so I went with the ITSM. So I think they're in a great position, Dave, and, as we know, cloud economics of which this is a big, giant application, get good, as the thing gets bigger and bigger and absorbs more and more functionality. Again, interesting change of management. We're going to talk to John, really look forward to it, fresh new energy. I think they're off to, off to the races, they've been racing for a while. (laughing) >> Some of the other things, let's talk about customers for a minute. So, some of the other things I get from customers when I talk to them is, and again, CMDB, and service catalog, those are two critical. If you want to get the value out of ServiceNow, you got to implement those two things, and others. But as well, this idea of multi-instance, allows you to upgrade at your own pace. What a lot of SASS companies will do, and we know this, as a customer of a lot of SASS companies, they say new upgrade coming, beware. And boom, the function hits, or often times hits, with a price increase. What ServiceNow claims is that because you're in a multi-instance, as opposed to a multi-tenet environment, you can plan your upgrades. Now, having said that, what a lot of customers will do, is they will try to avoid custom-mods, custom modifications, and they will try to take ServiceNow function out of the box. The desirability of that is when a new upgrade comes, you don't have to worry about the modifications you've made. However, it's not always that simple. I talked to a customer this morning on the way over here, they're a big SAP user, and they're doing a lot of custom-mods with their implementation. And I said aren't you worried about that? Yes, we're very worried about that, because that's going to be problematic for us when we upgrade. But they're wed to SAP. So, my advice to customers is always try where possible to avoid custom modifications. You hear that a lot from, for instance, IN4 customers. You frankly hear it a lot from Oracle customers, trying to avoid the modifications. Mods can drive value for your business, but in the cloud world, the cloud era, they can really create problems for you. >> And everyone thinks that they're special, but the reality is that a lot of processes are repeatable across businesses. And actually if you're sitting as a SASS offer provider, you see it across a lot of customers, try to go with what's the standard out of the box, with basic configuration changes, and try to keep away from the customization, or like you said, you can get yourself in serious trouble. And not really take full advantage. 'Cause you want to take advantage of the upgrades, you want the security upgrades, you want the functionality upgrades, you want the latest plug-ins from the ecosystem, so stick with the core and try to really avoid. And you've got stuff that needs to be kept up, and it's old and it's legacy, try to shield it as much as you can from this new-age application. >> So we're here for three days, theCUBE, Knowledge17, #know17, and so we will be covering all the innovations it's an interesting conference because the roles here are IT practitioners, CIOs, line-of-business professionals like those within HR, and other lines of business. So really a diverse crowd. There's a developer conference, a lot of events within the event. There's a women in tech luncheon hosted by John Donahoe, so a lot of stuff going on that we're going to be covering, Jeff Frick and myself. We are going to be right back with John Donahoe, the new CEO of ServiceNow coming fresh off the keynotes. Keep right there everybody. This is theCUBE, we're at Knowledge17, be right back.

>> Announcer: Live from New York, it's theCUBE, covering the IBM Machine Learning Launch Event, brought to you by IBM. Now, here are your hosts, Dave Vellante and Stu Miniman. >> Welcome back to New York City, everybody. We're here at the Waldorf Astoria covering the IBM Machine Learning Launch Event, bringing machine learning to the IBM Z. Bryan Smith is here, he's the vice president of R&D and the CTO of Rocket Software, powering the path to digital transformation. Bryan, welcome to theCUBE, thanks for coming on. >> Thanks for having me. >> So, Rocket Software, Waltham, Mass. based, close to where we are, but a lot of people don't know about Rocket, so pretty large company, give us the background. >> It's been around for, this'll be our 27th year. Private company, we've been a partner of IBM's for the last 23 years. Almost all of that is in the mainframe space, or we focused on the mainframe space, I'll say. We have 1,300 employees, we call ourselves Rocketeers. It's spread around the world. We're really an R&D focused company. More than half the company is engineering, and it's spread across the world on every continent and most major countries. >> You're esstenially OEM-ing your tools as it were. Is that right, no direct sales force? >> About half, there are different lenses to look at this, but about half of our go-to-market is through IBM with IBM-labeled, IBM-branded products. We've always been, for the side of products, we've always been the R&D behind the products. The partnership, though, has really grown. It's more than just an R&D partnership now, now we're doing co-marketing, we're even doing some joint selling to serve IBM mainframe customers. The partnership has really grown over these last 23 years from just being the guys who write the code to doing much more. >> Okay, so how do you fit in this announcement. Machine learning on Z, where does Rocket fit? >> Part of the announcement today is a very important piece of technology that we developed. We call it data virtualization. Data virtualization is really enabling customers to open their mainframe to allow the data to be used in ways that it was never designed to be used. You might have these data structures that were designed 10, 20, even 30 years ago that were designed for a very specific application, but today they want to use it in a very different way, and so, the traditional path is to take that data and copy it, to ETL it someplace else they can get some new use or to build some new application. What data virtualization allows you to do is to leave that data in place but access it using APIs that developers want to use today. They want to use JSON access, for example, or they want to use SQL access. But they want to be able to do things like join across IMS, DB2, and VSAM all with a single query using an SQL statement. We can do that relational databases and non-relational databases. It gets us out of this mode of having to copy data into some other data store through this ETL process, access the data in place, we call it moving the applications or the analytics to the data versus moving the data to the analytics or to the applications. >> Okay, so in this specific case, and I have said several times today, as Stu has heard me, two years ago IBM had a big theme around the z13 bringing analytics and transactions together, this sort of extends that. Great, I've got this transaction data that lives behind a firewall somewhere. Why the mainframe, why now? >> Well, I would pull back to where I said where we see more companies and organizations wanting to move applications and analytics closer to the data. The data in many of these large companies, that core business-critical data is on the mainframe, and so, being able to do more real time analytics without having to look at old data is really important. There's this term data gravity. I love the visual that presents in my mind that you have these different masses, these different planets if you will, and the biggest, massivest planet in that solar system really is the data, and so, it's pulling the smaller satellites if you will into this planet or this star by way of gravity because data is, data's a new currency, data is what the companies are running on. We're helping in this announcement with being able to unlock and open up all mainframe data sources, even some non-mainframe data sources, and using things like Spark that's running on the platform, that's running on z/OS to access that data directly without having to write any special programming or any special code to get to all their data. >> And the preferred place to run all that data is on the mainframe obviously if you're a mainframe customer. One of the questions I guess people have is, okay, I get that, it's the transaction data that I'm getting access to, but if I'm bringing transaction and analytic data together a lot of times that analytic data might be in social media, it might be somewhere else not on the mainframe. How do envision customers dealing with that? Do you have tooling them to do that? >> We do, so this data virtualization solution that I'm talking about is one that is mainframe resident, but it can also access other data sources. It can access DB2 on Linux Windows, it can access Informix, it can access Cloudant, it can access Hadoop through IBM's BigInsights. Other feeds like Twitter, like other social media, it can pull that in. The case where you'd want to do that is where you're trying to take that data and integrate it with a massive amount of mainframe data. It's going to be much more highly performant by pulling this other small amount of data into, next to that core business data. >> I get the performance and I get the security of the mainframe, I like those two things, but what about the economics? >> Couple of things. One, IBM when they ported Spark to z/OS, they did it the right way. They leveraged the architecture, it wasn't just a simple port of recompiling a bunch of open source code from Apache, it was rewriting it to be highly performant on the Z architecture, taking advantage of specialty engines. We've done the same with the data virtualization component that goes along with that Spark on z/OS offering that also leverages the architecture. We actually have different binaries that we load depending on which architecture of the machine that we're running on, whether it be a z9, an EC12, or the big granddaddy of a z13. >> Bryan, can you speak the developers? I think about, you're talking about all this mobile and Spark and everything like that. There's got to be certain developers that are like, "Oh my gosh, there's mainframe stuff. "I don't know anything about that." How do you help bridge that gap between where it lives in the tools that they're using? >> The best example is talking about embracing this API economy. And so, developers really don't care where the stuff is at, they just want it to be easy to get to. They don't have to code up some specific interface or language to get to different types of data, right? IBM's done a great job with the z/OS Connect in opening up the mainframe to the API economy with ReSTful interfaces, and so with z/OS Connect combined with Rocket data virtualization, you can come through that z/OS Connect same path using all those same ReSTful interfaces pushing those APIs out to tools like Swagger, which the developers want to use, and not only can you get to the applications through z/OS Connect, but we're a service provider to z/OS Connect allowing them to also get to every piece of data using those same ReSTful APIs. >> If I heard you correctly, the developer doesn't need to even worry about that it's on mainframe or speak mainframe or anything like that, right? >> The goal is that they never do. That they simply see in their tool-set, again like Swagger, that they have data as well as different services that they can invoke using these very straightforward, simple ReSTful APIs. >> Can you speak to the customers you've talked to? You know, there's certain people out in the industry, I've had this conversation for a few years at IBM shows is there's some part of the market that are like, oh, well, the mainframe is this dusty old box sitting in a corner with nothing new, and my experience has been the containers and cool streaming and everything like that, oh well, you know, mainframe did virtualization and Linux and all these things really early, decades ago and is keeping up with a lot of these trends with these new type of technologies. What do you find in the customers that, how much are they driving forward on new technologies, looking for that new technology and being able to leverage the assets that they have? >> You asked a lot of questions there. The types of customers certainly financial and insurance are the big two, but that doesn't mean that we're limited and not going after retail and helping governments and manufacturing customers as well. What I find is talking with them that there's the folks who get it and the folks who don't, and the folks who get it are the ones who are saying, "Well, I want to be able "to embrace these new technologies," and they're taking things like open source, they're looking at Spark, for example, they're looking at Anaconda. Last week, we just announced at the Anaconda Conference, we stepped on stage with Continuum, IBM, and we, Rocket, stood up there talking about this partnership that we formed to create this ecosystem because the development world changes very, very rapidly. For a while, all the rage was JDBC, or all the rage was component broker, and so today it's Spark and Anaconda are really in the forefront of developers' minds. We're constantly moving to keep up with developers because that's where the action's happening. Again, they don't care where the data is housed as long as you can open that up. We've been playing with this concept that came up from some research firm called two-speed IT where you have maybe your core business that has been running for years, and it's designed to really be slow-moving, very high quality, it keeps everything running today, but they want to embrace some of their new technologies, they want to be able to roll out a brand-new app, and they want to be able to update that multiple times a week. And so, this two-speed IT says, you're kind of breaking 'em off into two separate teams. You don't have to take your existing infrastructure team and say, "You must embrace every Agile "and every DevOps type of methodology." What we're seeing customers be successful with is this two-speed IT where you can fracture these two, and now you need to create some nice integration between those two teams, so things like data virtualization really help with that. It opens up and allows the development teams to very quickly access those assets on the mainframe in this case while allowing those developers to very quickly crank out an application where quality is not that important, where being very quick to respond and doing lots of AB testing with customers is really critical. >> Waterfall still has its place. As a company that predominately, or maybe even exclusively is involved in mainframe, I'm struck by, it must've been 2008, 2009, Paul Maritz comes in and he says VMWare our vision is to build the software mainframe. And of course the world said, "Ah, that's, mainframe's dead," we've been hearing that forever. In many respects, I accredit the VMWare, they built sort of a form of software mainframe, but now you hear a lot of talk, Stu, about going back to bare metal. You don't hear that talk on the mainframe. Everything's virtualized, right, so it's kind of interesting to see, and IBM uses the language of private cloud. The mainframe's, we're joking, the original private cloud. My question is you're strategy as a company has been always focused on the mainframe and going forward I presume it's going to continue to do that. What's your outlook for that platform? >> We're not exclusively by the mainframe, by the way. We're not, we have a good mix. >> Okay, it's overstating that, then. It's half and half or whatever. You don't talk about it, 'cause you're a private company. >> Maybe a little more than half is mainframe-focused. >> Dave: Significant. >> It is significant. >> You've got a large of proportion of the company on mainframe, z/OS. >> So we're bullish on the mainframe. We continue to invest more every year. We invest, we increase our investment every year, and so in a software company, your investment is primarily people. We increase that by double digits every year. We have license revenue increases in the double digits every year. I don't know many other mainframe-based software companies that have that. But I think that comes back to the partnership that we have with IBM because we are more than just a technology partner. We work on strategic projects with IBM. IBM will oftentimes stand up and say Rocket is a strategic partner that works with us on hard problem-solving customers issues every day. We're bullish, we're investing more all the time. We're not backing away, we're not decreasing our interest or our bets on the mainframe. If anything, we're increasing them at a faster rate than we have in the past 10 years. >> And this trend of bringing analytics and transactions together is a huge mega-trend, I mean, why not do it on the mainframe? If the economics are there, which you're arguing that in many use cases they are, because of the value component as well, then the future looks pretty reasonable, wouldn't you say? >> I'd say it's very, very bright. At the Anaconda Conference last week, I was coming up with an analogy for these folks. It's just a bunch of data scientists, right, and during most of the breaks and the receptions, they were just asking questions, "Well, what is a mainframe? "I didn't know that we still had 'em, "and what do they do?" So it was fun to educate them on that. But I was trying to show them an analogy with data warehousing where, say that in the mid-'90s it was perfectly acceptable to have a separate data warehouse separate from your transaction system. You would copy all this data over into the data warehouse. That was the model, right, and then slowly it became more important that the analytics or the BI against that data warehouse was looking at more real time data. So then it became more efficiencies and how do we replicate this faster, and how do we get closer to, not looking at week-old data but day-old data? And so, I explained that to them and said the days of being able to do analytics against old data that's copied are going away. ETL, we're also bullish to say that ETL is dead. ETL's future is very bleak. There's no place for it. It had its time, but now it's done because with data virtualization you can access that data in place. I was telling these folks as they're talking about, these data scientists, as they're talking about how they look at their models, their first step is always ETL. And so I told them this story, I said ETL is dead, and they just look at me kind of strange. >> Dave: Now the first step is load. >> Yes, there you go, right, load it in there. But having access from these platforms directly to that data, you don't have to worry about any type of a delay. >> What you described, though, is still common architecture where you've got, let's say, a Z mainframe, it's got an InfiniBand pipe to some exit data warehouse or something like that, and so, IBM's vision was, okay, we can collapse that, we can simplify that, consolidate it. SAP with HANA has a similar vision, we can do that. I'm sure Oracle's got their vision. What gives you confidence in IBM's approach and legs going forward? >> Probably due to the advances that we see in z/OS itself where handling mixed workloads, which it's just been doing for many of the 50 years that it's been around, being able to prioritize different workloads, not only just at the CPU dispatching, but also at the memory usage, also at the IO, all the way down through the channel to the actual device. You don't see other operating systems that have that level of granularity for managing mixed workloads. >> In the security component, that's what to me is unique about this so-called private cloud, and I say, I was using that software mainframe example from VMWare in the past, and it got a good portion of the way there, but it couldn't get that last mile, which is, any workload, any application with the performance and security that you would expect. It's just never quite got there. I don't know if the pendulum is swinging, I don't know if that's the accurate way to say it, but it's certainly stabilized, wouldn't you say? >> There's certainly new eyes being opened every day to saying, wait a minute, I could do something different here. Muscle memory doesn't have to guide me in doing business the way I have been doing it before, and that's this muscle memory I'm talking about of this ETL piece. >> Right, well, and a large number of workloads in mainframe are running Linux, right, you got Anaconda, Spark, all these modern tools. The question you asked about developers was right on. If it's independent or transparent to developers, then who cares, that's the key. That's the key lever this day and age is the developer community. You know it well. >> That's right. Give 'em what they want. They're the customers, they're the infrastructure that's being built. >> Bryan, we'll give you the last word, bumper sticker on the event, Rocket Software, your partnership, whatever you choose. >> We're excited to be here, it's an exciting day to talk about machine learning on z/OS. I say we're bullish on the mainframe, we are, we're especially bullish on z/OS, and that's what this even today is all about. That's where the data is, that's where we need the analytics running, that's where we need the machine learning running, that's where we need to get the developers to access the data live. >> Excellent, Bryan, thanks very much for coming to theCUBE. >> Bryan: Thank you. >> And keep right there, everybody. We'll be back with our next guest. This is theCUBE, we're live from New York City. Be right back. (electronic keyboard music)