(soothing music) >> Hey everyone, welcome to this event, "Build Your Cloud Center of Excellence." I'm your host, Lisa Martin. In the next 15 minutes or so my guest and I are going to be talking about redefining cloud operations, an application modernization for customers, and specifically how partners are helping to speed up that process. As you saw on our first two segments, we talked about problems enterprises are facing with cloud operations. We talked about redefining cloud operations as well to solve these problems. This segment is going to be focusing on how Hitachi Vantara's partners are really helping to speed up that process. We've got Johnson Controls here to talk about their partnership with Hitachi Vantara. Please welcome both of my guests, Prem Balasubramanian is with us, SVP and CTO Digital Solutions at Hitachi Vantara. And Suresh Mothikuru, SVP Customer Success Platform Engineering and Reliability Engineering from Johnson Controls. Gentlemen, welcome to the program, great to have you. >> Thank. >> Thank you, Lisa. >> First question is to both of you and Suresh, we'll start with you. We want to understand, you know, the cloud operations landscape is increasingly complex. We've talked a lot about that in this program. Talk to us, Suresh, about some of the biggest challenges and pin points that you faced with respect to that. >> Thank you. I think it's a great question. I mean, cloud has evolved a lot in the last 10 years. You know, when we were talking about a single cloud whether it's Azure or AWS and GCP, and that was complex enough. Now we are talking about multi-cloud and hybrid and you look at Johnson Controls, we have Azure we have AWS, we have GCP, we have Alibaba and we also support on-prem. So the architecture has become very, very complex and the complexity has grown so much that we are now thinking about whether we should be cloud native or cloud agnostic. So I think, I mean, sometimes it's hard to even explain the complexity because people think, oh, "When you go to cloud, everything is simplified." Cloud does give you a lot of simplicity, but it also really brings a lot more complexity along with it. So, and then next one is pretty important is, you know, generally when you look at cloud services, you have plenty of services that are offered within a cloud, 100, 150 services, 200 services. Even within those companies, you take AWS they might not know, an individual resource might not know about all the services we see. That's a big challenge for us as a customer to really understand each of the service that is provided in these, you know, clouds, well, doesn't matter which one that is. And the third one is pretty big, at least at the CTO the CIO, and the senior leadership level, is cost. Cost is a major factor because cloud, you know, will eat you up if you cannot manage it. If you don't have a good cloud governance process it because every minute you are in it, it's burning cash. So I think if you ask me, these are the three major things that I am facing day to day and that's where I use my partners, which I'll touch base down the line. >> Perfect, we'll talk about that. So Prem, I imagine that these problems are not unique to Johnson Controls or JCI, as you may hear us refer to it. Talk to me Prem about some of the other challenges that you're seeing within the customer landscape. >> So, yeah, I agree, Lisa, these are not very specific to JCI, but there are specific issues in JCI, right? So the way we think about these are, there is a common issue when people go to the cloud and there are very specific and unique issues for businesses, right? So JCI, and we will talk about this in the episode as we move forward. I think Suresh and his team have done some phenomenal step around how to manage this complexity. But there are customers who have a lesser complex cloud which is, they don't go to Alibaba, they don't have footprint in all three clouds. So their multi-cloud footprint could be a bit more manageable, but still struggle with a lot of the same problems around cost, around security, around talent. Talent is a big thing, right? And in Suresh's case I think it's slightly more exasperated because every cloud provider Be it AWS, JCP, or Azure brings in hundreds of services and there is nobody, including many of us, right? We learn every day, nowadays, right? It's not that there is one service integrator who knows all, while technically people can claim as a part of sales. But in reality all of us are continuing to learn in this landscape. And if you put all of this equation together with multiple clouds the complexity just starts to exponentially grow. And that's exactly what I think JCI is experiencing and Suresh's team has been experiencing, and we've been working together. But the common problems are around security talent and cost management of this, right? Those are my three things. And one last thing that I would love to say before we move away from this question is, if you think about cloud operations as a concept that's evolving over the last few years, and I have touched upon this in the previous episode as well, Lisa, right? If you take architectures, we've gone into microservices, we've gone into all these server-less architectures all the fancy things that we want. That helps us go to market faster, be more competent to as a business. But that's not simplified stuff, right? That's complicated stuff. It's a lot more distributed. Second, again, we've advanced and created more modern infrastructure because all of what we are talking is platform as a service, services on the cloud that we are consuming, right? In the same case with development we've moved into a DevOps model. We kind of click a button put some code in a repository, the code starts to run in production within a minute, everything else is automated. But then when we get to operations we are still stuck in a very old way of looking at cloud as an infrastructure, right? So you've got an infra team, you've got an app team, you've got an incident management team, you've got a soft knock, everything. But again, so Suresh can talk about this more because they are making significant strides in thinking about this as a single workload, and how do I apply engineering to go manage this? Because a lot of it is codified, right? So automation. Anyway, so that's kind of where the complexity is and how we are thinking, including JCI as a partner thinking about taming that complexity as we move forward. >> Suresh, let's talk about that taming the complexity. You guys have both done a great job of articulating the ostensible challenges that are there with cloud, especially multi-cloud environments that you're living in. But Suresh, talk about the partnership with Hitachi Vantara. How is it helping to dial down some of those inherent complexities? >> I mean, I always, you know, I think I've said this to Prem multiple times. I treat my partners as my internal, you know, employees. I look at Prem as my coworker or my peers. So the reason for that is I want Prem to have the same vested interest as a partner in my success or JCI success and vice versa, isn't it? I think that's how we operate and that's how we have been operating. And I think I would like to thank Prem and Hitachi Vantara for that really been an amazing partnership. And as he was saying, we have taken a completely holistic approach to how we want to really be in the market and play in the market to our customers. So if you look at my jacket it talks about OpenBlue platform. This is what JCI is building, that we are building this OpenBlue digital platform. And within that, my team, along with Prem's or Hitachi's, we have built what we call as Polaris. It's a technical platform where our apps can run. And this platform is automated end-to-end from a platform engineering standpoint. We stood up a platform engineering organization, a reliability engineering organization, as well as a support organization where Hitachi played a role. As I said previously, you know, for me to scale I'm not going to really have the talent and the knowledge of every function that I'm looking at. And Hitachi, not only they brought the talent but they also brought what he was talking about, Harc. You know, they have set up a lot and now we can leverage it. And they also came up with some really interesting concepts. I went and met them in India. They came up with this concept called IPL. Okay, what is that? They really challenged all their employees that's working for GCI to come up with innovative ideas to solve problems proactively, which is self-healing. You know, how you do that? So I think partners, you know, if they become really vested in your interests, they can do wonders for you. And I think in this case Hitachi is really working very well for us and in many aspects. And I'm leveraging them... You started with support, now I'm leveraging them in the automation, the platform engineering, as well as in the reliability engineering and then in even in the engineering spaces. And that like, they are my end-to-end partner right now? >> So you're really taking that holistic approach that you talked about and it sounds like it's a very collaborative two-way street partnership. Prem, I want to go back to, Suresh mentioned Harc. Talk a little bit about what Harc is and then how partners fit into Hitachi's Harc strategy. >> Great, so let me spend like a few seconds on what Harc is. Lisa, again, I know we've been using the term. Harc stands for Hitachi application reliability sectors. Now the reason we thought about Harc was, like I said in the beginning of this segment, there is an illusion from an architecture standpoint to be more modern, microservices, server-less, reactive architecture, so on and so forth. There is an illusion in your development methodology from Waterfall to agile, to DevOps to lean, agile to path program, whatever, right? Extreme program, so on and so forth. There is an evolution in the space of infrastructure from a point where you were buying these huge humongous servers and putting it in your data center to a point where people don't even see servers anymore, right? You buy it, by a click of a button you don't know the size of it. All you know is a, it's (indistinct) whatever that name means. Let's go provision it on the fly, get go, get your work done, right? When all of this is advanced when you think about operations people have been solving the problem the way they've been solving it 20 years back, right? That's the issue. And Harc was conceived exactly to fix that particular problem, to think about a modern way of operating a modern workload, right? That's exactly what Harc. So it brings together finest engineering talent. So the teams are trained in specific ways of working. We've invested and implemented some of the IP, we work with the best of the breed partner ecosystem, and I'll talk about that in a minute. And we've got these facilities in Dallas and I am talking from my office in Dallas, which is a Harc facility in the US from where we deliver for our customers. And then back in Hyderabad, we've got one more that we opened and these are facilities from where we deliver Harc services for our customers as well, right? And then we are expanding it in Japan and Portugal as we move into 23. That's kind of the plan that we are thinking through. However, that's what Harc is, Lisa, right? That's our solution to this cloud complexity problem. Right? >> Got it, and it sounds like it's going quite global, which is fantastic. So Suresh, I want to have you expand a bit on the partnership, the partner ecosystem and the role that it plays. You talked about it a little bit but what role does the partner ecosystem play in really helping JCI to dial down some of those challenges and the inherent complexities that we talked about? >> Yeah, sure. I think partners play a major role and JCI is very, very good at it. I mean, I've joined JCI 18 months ago, JCI leverages partners pretty extensively. As I said, I leverage Hitachi for my, you know, A group and the (indistinct) space and the cloud operations space, and they're my primary partner. But at the same time, we leverage many other partners. Well, you know, Accenture, SCL, and even on the tooling side we use Datadog and (indistinct). All these guys are major partners of our because the way we like to pick partners is based on our vision and where we want to go. And pick the right partner who's going to really, you know make you successful by investing their resources in you. And what I mean by that is when you have a partner, partner knows exactly what kind of skillset is needed for this customer, for them to really be successful. As I said earlier, we cannot really get all the skillset that we need, we rely on the partners and partners bring the the right skillset, they can scale. I can tell Prem tomorrow, "Hey, I need two parts by next week", and I guarantee it he's going to bring two parts to me. So they let you scale, they let you move fast. And I'm a big believer, in today's day and age, to get things done fast and be more agile. I'm not worried about failure, but for me moving fast is very, very important. And partners really do a very good job bringing that. But I think then they also really make you think, isn't it? Because one thing I like about partners they make you innovate whether they know it or not but they do because, you know, they will come and ask you questions about, "Hey, tell me why you are doing this. Can I review your architecture?" You know, and then they will try to really say I don't think this is going to work. Because they work with so many different clients, not JCI, they bring all that expertise and that's what I look from them, you know, just not, you know, do a T&M job for me. I ask you to do this go... They just bring more than that. That's how I pick my partners. And that's how, you know, Hitachi's Vantara is definitely one of a good partner from that sense because they bring a lot more innovation to the table and I appreciate about that. >> It sounds like, it sounds like a flywheel of innovation. >> Yeah. >> I love that. Last question for both of you, which we're almost out of time here, Prem, I want to go back to you. So I'm a partner, I'm planning on redefining CloudOps at my company. What are the two things you want me to remember from Hitachi Vantara's perspective? >> So before I get to that question, Lisa, the partners that we work with are slightly different from from the partners that, again, there are some similar partners. There are some different partners, right? For example, we pick and choose especially in the Harc space, we pick and choose partners that are more future focused, right? We don't care if they are huge companies or small companies. We go after companies that are future focused that are really, really nimble and can change for our customers need because it's not our need, right? When I pick partners for Harc my ultimate endeavor is to ensure, in this case because we've got (indistinct) GCI on, we are able to operate (indistinct) with the level of satisfaction above and beyond that they're expecting from us. And whatever I don't have I need to get from my partners so that I bring this solution to Suresh. As opposed to bringing a whole lot of people and making them stand in front of Suresh. So that's how I think about partners. What do I want them to do from, and we've always done this so we do workshops with our partners. We just don't go by tools. When we say we are partnering with X, Y, Z, we do workshops with them and we say, this is how we are thinking. Either you build it in your roadmap that helps us leverage you, continue to leverage you. And we do have minimal investments where we fix gaps. We're building some utilities for us to deliver the best service to our customers. And our intention is not to build a product to compete with our partner. Our intention is to just fill the wide space until they go build it into their product suite that we can then leverage it for our customers. So always think about end customers and how can we make it easy for them? Because for all the tool vendors out there seeing this and wanting to partner with Hitachi the biggest thing is tools sprawl, especially on the cloud is very real. For every problem on the cloud. I have a billion tools that are being thrown at me as Suresh if I'm putting my installation and it's not easy at all. It's so confusing. >> Yeah. >> So that's what we want. We want people to simplify that landscape for our end customers, and we are looking at partners that are thinking through the simplification not just making money. >> That makes perfect sense. There really is a very strong symbiosis it sounds like, in the partner ecosystem. And there's a lot of enablement that goes on back and forth it sounds like as well, which is really, to your point it's all about the end customers and what they're expecting. Suresh, last question for you is which is the same one, if I'm a partner what are the things that you want me to consider as I'm planning to redefine CloudOps at my company? >> I'll keep it simple. In my view, I mean, we've touched upon it in multiple facets in this interview about that, the three things. First and foremost, reliability. You know, in today's day and age my products has to be reliable, available and, you know, make sure that the customer's happy with what they're really dealing with, number one. Number two, my product has to be secure. Security is super, super important, okay? And number three, I need to really make sure my customers are getting the value so I keep my cost low. So these three is what I would focus and what I expect from my partners. >> Great advice, guys. Thank you so much for talking through this with me and really showing the audience how strong the partnership is between Hitachi Vantara and JCI. What you're doing together, we'll have to talk to you again to see where things go but we really appreciate your insights and your perspectives. Thank you. >> Thank you, Lisa. >> Thanks Lisa, thanks for having us. >> My pleasure. For my guests, I'm Lisa Martin. Thank you so much for watching. (soothing music)

(soothing music) >> Hey everyone, welcome to this event, "Build Your Cloud Center of Excellence." I'm your host, Lisa Martin. In the next 15 minutes or so my guest and I are going to be talking about redefining cloud operations, an application modernization for customers, and specifically how partners are helping to speed up that process. As you saw on our first two segments, we talked about problems enterprises are facing with cloud operations. We talked about redefining cloud operations as well to solve these problems. This segment is going to be focusing on how Hitachi Vantara's partners are really helping to speed up that process. We've got Johnson Controls here to talk about their partnership with Hitachi Vantara. Please welcome both of my guests, Prem Balasubramanian is with us, SVP and CTO Digital Solutions at Hitachi Vantara. And Suresh Mothikuru, SVP Customer Success Platform Engineering and Reliability Engineering from Johnson Controls. Gentlemen, welcome to the program, great to have you. >> Thank. >> Thank you, Lisa. >> First question is to both of you and Suresh, we'll start with you. We want to understand, you know, the cloud operations landscape is increasingly complex. We've talked a lot about that in this program. Talk to us, Suresh, about some of the biggest challenges and pin points that you faced with respect to that. >> Thank you. I think it's a great question. I mean, cloud has evolved a lot in the last 10 years. You know, when we were talking about a single cloud whether it's Azure or AWS and GCP, and that was complex enough. Now we are talking about multi-cloud and hybrid and you look at Johnson Controls, we have Azure we have AWS, we have GCP, we have Alibaba and we also support on-prem. So the architecture has become very, very complex and the complexity has grown so much that we are now thinking about whether we should be cloud native or cloud agnostic. So I think, I mean, sometimes it's hard to even explain the complexity because people think, oh, "When you go to cloud, everything is simplified." Cloud does give you a lot of simplicity, but it also really brings a lot more complexity along with it. So, and then next one is pretty important is, you know, generally when you look at cloud services, you have plenty of services that are offered within a cloud, 100, 150 services, 200 services. Even within those companies, you take AWS they might not know, an individual resource might not know about all the services we see. That's a big challenge for us as a customer to really understand each of the service that is provided in these, you know, clouds, well, doesn't matter which one that is. And the third one is pretty big, at least at the CTO the CIO, and the senior leadership level, is cost. Cost is a major factor because cloud, you know, will eat you up if you cannot manage it. If you don't have a good cloud governance process it because every minute you are in it, it's burning cash. So I think if you ask me, these are the three major things that I am facing day to day and that's where I use my partners, which I'll touch base down the line. >> Perfect, we'll talk about that. So Prem, I imagine that these problems are not unique to Johnson Controls or JCI, as you may hear us refer to it. Talk to me Prem about some of the other challenges that you're seeing within the customer landscape. >> So, yeah, I agree, Lisa, these are not very specific to JCI, but there are specific issues in JCI, right? So the way we think about these are, there is a common issue when people go to the cloud and there are very specific and unique issues for businesses, right? So JCI, and we will talk about this in the episode as we move forward. I think Suresh and his team have done some phenomenal step around how to manage this complexity. But there are customers who have a lesser complex cloud which is, they don't go to Alibaba, they don't have footprint in all three clouds. So their multi-cloud footprint could be a bit more manageable, but still struggle with a lot of the same problems around cost, around security, around talent. Talent is a big thing, right? And in Suresh's case I think it's slightly more exasperated because every cloud provider Be it AWS, JCP, or Azure brings in hundreds of services and there is nobody, including many of us, right? We learn every day, nowadays, right? It's not that there is one service integrator who knows all, while technically people can claim as a part of sales. But in reality all of us are continuing to learn in this landscape. And if you put all of this equation together with multiple clouds the complexity just starts to exponentially grow. And that's exactly what I think JCI is experiencing and Suresh's team has been experiencing, and we've been working together. But the common problems are around security talent and cost management of this, right? Those are my three things. And one last thing that I would love to say before we move away from this question is, if you think about cloud operations as a concept that's evolving over the last few years, and I have touched upon this in the previous episode as well, Lisa, right? If you take architectures, we've gone into microservices, we've gone into all these server-less architectures all the fancy things that we want. That helps us go to market faster, be more competent to as a business. But that's not simplified stuff, right? That's complicated stuff. It's a lot more distributed. Second, again, we've advanced and created more modern infrastructure because all of what we are talking is platform as a service, services on the cloud that we are consuming, right? In the same case with development we've moved into a DevOps model. We kind of click a button put some code in a repository, the code starts to run in production within a minute, everything else is automated. But then when we get to operations we are still stuck in a very old way of looking at cloud as an infrastructure, right? So you've got an infra team, you've got an app team, you've got an incident management team, you've got a soft knock, everything. But again, so Suresh can talk about this more because they are making significant strides in thinking about this as a single workload, and how do I apply engineering to go manage this? Because a lot of it is codified, right? So automation. Anyway, so that's kind of where the complexity is and how we are thinking, including JCI as a partner thinking about taming that complexity as we move forward. >> Suresh, let's talk about that taming the complexity. You guys have both done a great job of articulating the ostensible challenges that are there with cloud, especially multi-cloud environments that you're living in. But Suresh, talk about the partnership with Hitachi Vantara. How is it helping to dial down some of those inherent complexities? >> I mean, I always, you know, I think I've said this to Prem multiple times. I treat my partners as my internal, you know, employees. I look at Prem as my coworker or my peers. So the reason for that is I want Prem to have the same vested interest as a partner in my success or JCI success and vice versa, isn't it? I think that's how we operate and that's how we have been operating. And I think I would like to thank Prem and Hitachi Vantara for that really been an amazing partnership. And as he was saying, we have taken a completely holistic approach to how we want to really be in the market and play in the market to our customers. So if you look at my jacket it talks about OpenBlue platform. This is what JCI is building, that we are building this OpenBlue digital platform. And within that, my team, along with Prem's or Hitachi's, we have built what we call as Polaris. It's a technical platform where our apps can run. And this platform is automated end-to-end from a platform engineering standpoint. We stood up a platform engineering organization, a reliability engineering organization, as well as a support organization where Hitachi played a role. As I said previously, you know, for me to scale I'm not going to really have the talent and the knowledge of every function that I'm looking at. And Hitachi, not only they brought the talent but they also brought what he was talking about, Harc. You know, they have set up a lot and now we can leverage it. And they also came up with some really interesting concepts. I went and met them in India. They came up with this concept called IPL. Okay, what is that? They really challenged all their employees that's working for GCI to come up with innovative ideas to solve problems proactively, which is self-healing. You know, how you do that? So I think partners, you know, if they become really vested in your interests, they can do wonders for you. And I think in this case Hitachi is really working very well for us and in many aspects. And I'm leveraging them... You started with support, now I'm leveraging them in the automation, the platform engineering, as well as in the reliability engineering and then in even in the engineering spaces. And that like, they are my end-to-end partner right now? >> So you're really taking that holistic approach that you talked about and it sounds like it's a very collaborative two-way street partnership. Prem, I want to go back to, Suresh mentioned Harc. Talk a little bit about what Harc is and then how partners fit into Hitachi's Harc strategy. >> Great, so let me spend like a few seconds on what Harc is. Lisa, again, I know we've been using the term. Harc stands for Hitachi application reliability sectors. Now the reason we thought about Harc was, like I said in the beginning of this segment, there is an illusion from an architecture standpoint to be more modern, microservices, server-less, reactive architecture, so on and so forth. There is an illusion in your development methodology from Waterfall to agile, to DevOps to lean, agile to path program, whatever, right? Extreme program, so on and so forth. There is an evolution in the space of infrastructure from a point where you were buying these huge humongous servers and putting it in your data center to a point where people don't even see servers anymore, right? You buy it, by a click of a button you don't know the size of it. All you know is a, it's (indistinct) whatever that name means. Let's go provision it on the fly, get go, get your work done, right? When all of this is advanced when you think about operations people have been solving the problem the way they've been solving it 20 years back, right? That's the issue. And Harc was conceived exactly to fix that particular problem, to think about a modern way of operating a modern workload, right? That's exactly what Harc. So it brings together finest engineering talent. So the teams are trained in specific ways of working. We've invested and implemented some of the IP, we work with the best of the breed partner ecosystem, and I'll talk about that in a minute. And we've got these facilities in Dallas and I am talking from my office in Dallas, which is a Harc facility in the US from where we deliver for our customers. And then back in Hyderabad, we've got one more that we opened and these are facilities from where we deliver Harc services for our customers as well, right? And then we are expanding it in Japan and Portugal as we move into 23. That's kind of the plan that we are thinking through. However, that's what Harc is, Lisa, right? That's our solution to this cloud complexity problem. Right? >> Got it, and it sounds like it's going quite global, which is fantastic. So Suresh, I want to have you expand a bit on the partnership, the partner ecosystem and the role that it plays. You talked about it a little bit but what role does the partner ecosystem play in really helping JCI to dial down some of those challenges and the inherent complexities that we talked about? >> Yeah, sure. I think partners play a major role and JCI is very, very good at it. I mean, I've joined JCI 18 months ago, JCI leverages partners pretty extensively. As I said, I leverage Hitachi for my, you know, A group and the (indistinct) space and the cloud operations space, and they're my primary partner. But at the same time, we leverage many other partners. Well, you know, Accenture, SCL, and even on the tooling side we use Datadog and (indistinct). All these guys are major partners of our because the way we like to pick partners is based on our vision and where we want to go. And pick the right partner who's going to really, you know make you successful by investing their resources in you. And what I mean by that is when you have a partner, partner knows exactly what kind of skillset is needed for this customer, for them to really be successful. As I said earlier, we cannot really get all the skillset that we need, we rely on the partners and partners bring the the right skillset, they can scale. I can tell Prem tomorrow, "Hey, I need two parts by next week", and I guarantee it he's going to bring two parts to me. So they let you scale, they let you move fast. And I'm a big believer, in today's day and age, to get things done fast and be more agile. I'm not worried about failure, but for me moving fast is very, very important. And partners really do a very good job bringing that. But I think then they also really make you think, isn't it? Because one thing I like about partners they make you innovate whether they know it or not but they do because, you know, they will come and ask you questions about, "Hey, tell me why you are doing this. Can I review your architecture?" You know, and then they will try to really say I don't think this is going to work. Because they work with so many different clients, not JCI, they bring all that expertise and that's what I look from them, you know, just not, you know, do a T&M job for me. I ask you to do this go... They just bring more than that. That's how I pick my partners. And that's how, you know, Hitachi's Vantara is definitely one of a good partner from that sense because they bring a lot more innovation to the table and I appreciate about that. >> It sounds like, it sounds like a flywheel of innovation. >> Yeah. >> I love that. Last question for both of you, which we're almost out of time here, Prem, I want to go back to you. So I'm a partner, I'm planning on redefining CloudOps at my company. What are the two things you want me to remember from Hitachi Vantara's perspective? >> So before I get to that question, Lisa, the partners that we work with are slightly different from from the partners that, again, there are some similar partners. There are some different partners, right? For example, we pick and choose especially in the Harc space, we pick and choose partners that are more future focused, right? We don't care if they are huge companies or small companies. We go after companies that are future focused that are really, really nimble and can change for our customers need because it's not our need, right? When I pick partners for Harc my ultimate endeavor is to ensure, in this case because we've got (indistinct) GCI on, we are able to operate (indistinct) with the level of satisfaction above and beyond that they're expecting from us. And whatever I don't have I need to get from my partners so that I bring this solution to Suresh. As opposed to bringing a whole lot of people and making them stand in front of Suresh. So that's how I think about partners. What do I want them to do from, and we've always done this so we do workshops with our partners. We just don't go by tools. When we say we are partnering with X, Y, Z, we do workshops with them and we say, this is how we are thinking. Either you build it in your roadmap that helps us leverage you, continue to leverage you. And we do have minimal investments where we fix gaps. We're building some utilities for us to deliver the best service to our customers. And our intention is not to build a product to compete with our partner. Our intention is to just fill the wide space until they go build it into their product suite that we can then leverage it for our customers. So always think about end customers and how can we make it easy for them? Because for all the tool vendors out there seeing this and wanting to partner with Hitachi the biggest thing is tools sprawl, especially on the cloud is very real. For every problem on the cloud. I have a billion tools that are being thrown at me as Suresh if I'm putting my installation and it's not easy at all. It's so confusing. >> Yeah. >> So that's what we want. We want people to simplify that landscape for our end customers, and we are looking at partners that are thinking through the simplification not just making money. >> That makes perfect sense. There really is a very strong symbiosis it sounds like, in the partner ecosystem. And there's a lot of enablement that goes on back and forth it sounds like as well, which is really, to your point it's all about the end customers and what they're expecting. Suresh, last question for you is which is the same one, if I'm a partner what are the things that you want me to consider as I'm planning to redefine CloudOps at my company? >> I'll keep it simple. In my view, I mean, we've touched upon it in multiple facets in this interview about that, the three things. First and foremost, reliability. You know, in today's day and age my products has to be reliable, available and, you know, make sure that the customer's happy with what they're really dealing with, number one. Number two, my product has to be secure. Security is super, super important, okay? And number three, I need to really make sure my customers are getting the value so I keep my cost low. So these three is what I would focus and what I expect from my partners. >> Great advice, guys. Thank you so much for talking through this with me and really showing the audience how strong the partnership is between Hitachi Vantara and JCI. What you're doing together, we'll have to talk to you again to see where things go but we really appreciate your insights and your perspectives. Thank you. >> Thank you, Lisa. >> Thanks Lisa, thanks for having us. >> My pleasure. For my guests, I'm Lisa Martin. Thank you so much for watching. (soothing music)

(soothing music) >> Hey everyone, welcome to this event, "Build Your Cloud Center of Excellence." I'm your host, Lisa Martin. In the next 15 minutes or so my guest and I are going to be talking about redefining cloud operations, an application modernization for customers, and specifically how partners are helping to speed up that process. As you saw on our first two segments, we talked about problems enterprises are facing with cloud operations. We talked about redefining cloud operations as well to solve these problems. This segment is going to be focusing on how Hitachi Vantara's partners are really helping to speed up that process. We've got Johnson Controls here to talk about their partnership with Hitachi Vantara. Please welcome both of my guests, Prem Balasubramanian is with us, SVP and CTO Digital Solutions at Hitachi Vantara. And Suresh Mothikuru, SVP Customer Success Platform Engineering and Reliability Engineering from Johnson Controls. Gentlemen, welcome to the program, great to have you. >> Thank. >> Thank you, Lisa. >> First question is to both of you and Suresh, we'll start with you. We want to understand, you know, the cloud operations landscape is increasingly complex. We've talked a lot about that in this program. Talk to us, Suresh, about some of the biggest challenges and pin points that you faced with respect to that. >> Thank you. I think it's a great question. I mean, cloud has evolved a lot in the last 10 years. You know, when we were talking about a single cloud whether it's Azure or AWS and GCP, and that was complex enough. Now we are talking about multi-cloud and hybrid and you look at Johnson Controls, we have Azure we have AWS, we have GCP, we have Alibaba and we also support on-prem. So the architecture has become very, very complex and the complexity has grown so much that we are now thinking about whether we should be cloud native or cloud agnostic. So I think, I mean, sometimes it's hard to even explain the complexity because people think, oh, "When you go to cloud, everything is simplified." Cloud does give you a lot of simplicity, but it also really brings a lot more complexity along with it. So, and then next one is pretty important is, you know, generally when you look at cloud services, you have plenty of services that are offered within a cloud, 100, 150 services, 200 services. Even within those companies, you take AWS they might not know, an individual resource might not know about all the services we see. That's a big challenge for us as a customer to really understand each of the service that is provided in these, you know, clouds, well, doesn't matter which one that is. And the third one is pretty big, at least at the CTO the CIO, and the senior leadership level, is cost. Cost is a major factor because cloud, you know, will eat you up if you cannot manage it. If you don't have a good cloud governance process it because every minute you are in it, it's burning cash. So I think if you ask me, these are the three major things that I am facing day to day and that's where I use my partners, which I'll touch base down the line. >> Perfect, we'll talk about that. So Prem, I imagine that these problems are not unique to Johnson Controls or JCI, as you may hear us refer to it. Talk to me Prem about some of the other challenges that you're seeing within the customer landscape. >> So, yeah, I agree, Lisa, these are not very specific to JCI, but there are specific issues in JCI, right? So the way we think about these are, there is a common issue when people go to the cloud and there are very specific and unique issues for businesses, right? So JCI, and we will talk about this in the episode as we move forward. I think Suresh and his team have done some phenomenal step around how to manage this complexity. But there are customers who have a lesser complex cloud which is, they don't go to Alibaba, they don't have footprint in all three clouds. So their multi-cloud footprint could be a bit more manageable, but still struggle with a lot of the same problems around cost, around security, around talent. Talent is a big thing, right? And in Suresh's case I think it's slightly more exasperated because every cloud provider Be it AWS, JCP, or Azure brings in hundreds of services and there is nobody, including many of us, right? We learn every day, nowadays, right? It's not that there is one service integrator who knows all, while technically people can claim as a part of sales. But in reality all of us are continuing to learn in this landscape. And if you put all of this equation together with multiple clouds the complexity just starts to exponentially grow. And that's exactly what I think JCI is experiencing and Suresh's team has been experiencing, and we've been working together. But the common problems are around security talent and cost management of this, right? Those are my three things. And one last thing that I would love to say before we move away from this question is, if you think about cloud operations as a concept that's evolving over the last few years, and I have touched upon this in the previous episode as well, Lisa, right? If you take architectures, we've gone into microservices, we've gone into all these server-less architectures all the fancy things that we want. That helps us go to market faster, be more competent to as a business. But that's not simplified stuff, right? That's complicated stuff. It's a lot more distributed. Second, again, we've advanced and created more modern infrastructure because all of what we are talking is platform as a service, services on the cloud that we are consuming, right? In the same case with development we've moved into a DevOps model. We kind of click a button put some code in a repository, the code starts to run in production within a minute, everything else is automated. But then when we get to operations we are still stuck in a very old way of looking at cloud as an infrastructure, right? So you've got an infra team, you've got an app team, you've got an incident management team, you've got a soft knock, everything. But again, so Suresh can talk about this more because they are making significant strides in thinking about this as a single workload, and how do I apply engineering to go manage this? Because a lot of it is codified, right? So automation. Anyway, so that's kind of where the complexity is and how we are thinking, including JCI as a partner thinking about taming that complexity as we move forward. >> Suresh, let's talk about that taming the complexity. You guys have both done a great job of articulating the ostensible challenges that are there with cloud, especially multi-cloud environments that you're living in. But Suresh, talk about the partnership with Hitachi Vantara. How is it helping to dial down some of those inherent complexities? >> I mean, I always, you know, I think I've said this to Prem multiple times. I treat my partners as my internal, you know, employees. I look at Prem as my coworker or my peers. So the reason for that is I want Prem to have the same vested interest as a partner in my success or JCI success and vice versa, isn't it? I think that's how we operate and that's how we have been operating. And I think I would like to thank Prem and Hitachi Vantara for that really been an amazing partnership. And as he was saying, we have taken a completely holistic approach to how we want to really be in the market and play in the market to our customers. So if you look at my jacket it talks about OpenBlue platform. This is what JCI is building, that we are building this OpenBlue digital platform. And within that, my team, along with Prem's or Hitachi's, we have built what we call as Polaris. It's a technical platform where our apps can run. And this platform is automated end-to-end from a platform engineering standpoint. We stood up a platform engineering organization, a reliability engineering organization, as well as a support organization where Hitachi played a role. As I said previously, you know, for me to scale I'm not going to really have the talent and the knowledge of every function that I'm looking at. And Hitachi, not only they brought the talent but they also brought what he was talking about, Harc. You know, they have set up a lot and now we can leverage it. And they also came up with some really interesting concepts. I went and met them in India. They came up with this concept called IPL. Okay, what is that? They really challenged all their employees that's working for GCI to come up with innovative ideas to solve problems proactively, which is self-healing. You know, how you do that? So I think partners, you know, if they become really vested in your interests, they can do wonders for you. And I think in this case Hitachi is really working very well for us and in many aspects. And I'm leveraging them... You started with support, now I'm leveraging them in the automation, the platform engineering, as well as in the reliability engineering and then in even in the engineering spaces. And that like, they are my end-to-end partner right now? >> So you're really taking that holistic approach that you talked about and it sounds like it's a very collaborative two-way street partnership. Prem, I want to go back to, Suresh mentioned Harc. Talk a little bit about what Harc is and then how partners fit into Hitachi's Harc strategy. >> Great, so let me spend like a few seconds on what Harc is. Lisa, again, I know we've been using the term. Harc stands for Hitachi application reliability sectors. Now the reason we thought about Harc was, like I said in the beginning of this segment, there is an illusion from an architecture standpoint to be more modern, microservices, server-less, reactive architecture, so on and so forth. There is an illusion in your development methodology from Waterfall to agile, to DevOps to lean, agile to path program, whatever, right? Extreme program, so on and so forth. There is an evolution in the space of infrastructure from a point where you were buying these huge humongous servers and putting it in your data center to a point where people don't even see servers anymore, right? You buy it, by a click of a button you don't know the size of it. All you know is a, it's (indistinct) whatever that name means. Let's go provision it on the fly, get go, get your work done, right? When all of this is advanced when you think about operations people have been solving the problem the way they've been solving it 20 years back, right? That's the issue. And Harc was conceived exactly to fix that particular problem, to think about a modern way of operating a modern workload, right? That's exactly what Harc. So it brings together finest engineering talent. So the teams are trained in specific ways of working. We've invested and implemented some of the IP, we work with the best of the breed partner ecosystem, and I'll talk about that in a minute. And we've got these facilities in Dallas and I am talking from my office in Dallas, which is a Harc facility in the US from where we deliver for our customers. And then back in Hyderabad, we've got one more that we opened and these are facilities from where we deliver Harc services for our customers as well, right? And then we are expanding it in Japan and Portugal as we move into 23. That's kind of the plan that we are thinking through. However, that's what Harc is, Lisa, right? That's our solution to this cloud complexity problem. Right? >> Got it, and it sounds like it's going quite global, which is fantastic. So Suresh, I want to have you expand a bit on the partnership, the partner ecosystem and the role that it plays. You talked about it a little bit but what role does the partner ecosystem play in really helping JCI to dial down some of those challenges and the inherent complexities that we talked about? >> Yeah, sure. I think partners play a major role and JCI is very, very good at it. I mean, I've joined JCI 18 months ago, JCI leverages partners pretty extensively. As I said, I leverage Hitachi for my, you know, A group and the (indistinct) space and the cloud operations space, and they're my primary partner. But at the same time, we leverage many other partners. Well, you know, Accenture, SCL, and even on the tooling side we use Datadog and (indistinct). All these guys are major partners of our because the way we like to pick partners is based on our vision and where we want to go. And pick the right partner who's going to really, you know make you successful by investing their resources in you. And what I mean by that is when you have a partner, partner knows exactly what kind of skillset is needed for this customer, for them to really be successful. As I said earlier, we cannot really get all the skillset that we need, we rely on the partners and partners bring the the right skillset, they can scale. I can tell Prem tomorrow, "Hey, I need two parts by next week", and I guarantee it he's going to bring two parts to me. So they let you scale, they let you move fast. And I'm a big believer, in today's day and age, to get things done fast and be more agile. I'm not worried about failure, but for me moving fast is very, very important. And partners really do a very good job bringing that. But I think then they also really make you think, isn't it? Because one thing I like about partners they make you innovate whether they know it or not but they do because, you know, they will come and ask you questions about, "Hey, tell me why you are doing this. Can I review your architecture?" You know, and then they will try to really say I don't think this is going to work. Because they work with so many different clients, not JCI, they bring all that expertise and that's what I look from them, you know, just not, you know, do a T&M job for me. I ask you to do this go... They just bring more than that. That's how I pick my partners. And that's how, you know, Hitachi's Vantara is definitely one of a good partner from that sense because they bring a lot more innovation to the table and I appreciate about that. >> It sounds like, it sounds like a flywheel of innovation. >> Yeah. >> I love that. Last question for both of you, which we're almost out of time here, Prem, I want to go back to you. So I'm a partner, I'm planning on redefining CloudOps at my company. What are the two things you want me to remember from Hitachi Vantara's perspective? >> So before I get to that question, Lisa, the partners that we work with are slightly different from from the partners that, again, there are some similar partners. There are some different partners, right? For example, we pick and choose especially in the Harc space, we pick and choose partners that are more future focused, right? We don't care if they are huge companies or small companies. We go after companies that are future focused that are really, really nimble and can change for our customers need because it's not our need, right? When I pick partners for Harc my ultimate endeavor is to ensure, in this case because we've got (indistinct) GCI on, we are able to operate (indistinct) with the level of satisfaction above and beyond that they're expecting from us. And whatever I don't have I need to get from my partners so that I bring this solution to Suresh. As opposed to bringing a whole lot of people and making them stand in front of Suresh. So that's how I think about partners. What do I want them to do from, and we've always done this so we do workshops with our partners. We just don't go by tools. When we say we are partnering with X, Y, Z, we do workshops with them and we say, this is how we are thinking. Either you build it in your roadmap that helps us leverage you, continue to leverage you. And we do have minimal investments where we fix gaps. We're building some utilities for us to deliver the best service to our customers. And our intention is not to build a product to compete with our partner. Our intention is to just fill the wide space until they go build it into their product suite that we can then leverage it for our customers. So always think about end customers and how can we make it easy for them? Because for all the tool vendors out there seeing this and wanting to partner with Hitachi the biggest thing is tools sprawl, especially on the cloud is very real. For every problem on the cloud. I have a billion tools that are being thrown at me as Suresh if I'm putting my installation and it's not easy at all. It's so confusing. >> Yeah. >> So that's what we want. We want people to simplify that landscape for our end customers, and we are looking at partners that are thinking through the simplification not just making money. >> That makes perfect sense. There really is a very strong symbiosis it sounds like, in the partner ecosystem. And there's a lot of enablement that goes on back and forth it sounds like as well, which is really, to your point it's all about the end customers and what they're expecting. Suresh, last question for you is which is the same one, if I'm a partner what are the things that you want me to consider as I'm planning to redefine CloudOps at my company? >> I'll keep it simple. In my view, I mean, we've touched upon it in multiple facets in this interview about that, the three things. First and foremost, reliability. You know, in today's day and age my products has to be reliable, available and, you know, make sure that the customer's happy with what they're really dealing with, number one. Number two, my product has to be secure. Security is super, super important, okay? And number three, I need to really make sure my customers are getting the value so I keep my cost low. So these three is what I would focus and what I expect from my partners. >> Great advice, guys. Thank you so much for talking through this with me and really showing the audience how strong the partnership is between Hitachi Vantara and JCI. What you're doing together, we'll have to talk to you again to see where things go but we really appreciate your insights and your perspectives. Thank you. >> Thank you, Lisa. >> Thanks Lisa, thanks for having us. >> My pleasure. For my guests, I'm Lisa Martin. Thank you so much for watching. (soothing music)

>> Narrator: From New York, it's theCube. Covering Escape/19. (music plays) >> Welcome back everyone. It's Cube coverage for the first inaugural multicloud conference, Escape 2019. We are here with at Bassam Tabbara who is the CEO of Upbound, hot start-up, has not yet released their product but they're working on it. Good friend of theCube, Cube alumni. Bassam, good to see you again. >> Thank you, glad to be back on the Cube. >> Well we know your guys are beavering away, digging away at the product, building it out. You have a very compelling background coming into the cloud world. You're here at the multicloud, first ever conference >> That's right. >> There is hybrid cloud, but this is like being billed as the first multicloud conference. A lot of technical people here. >> Lots of. >> Lot of industry insiders setting the foundation is one theme I'm hearing and then the other theme is data. >> Yeah. >> These are the two dynamics. What's your take on this multicloud conference opportunity? >> Look, I think it's really interesting, it reflects kind of what's happening. Multicloud's becoming a reality, more and more people are, whether they like it or not, are actually using multiple vendors and they're trying to figure it out so I think it's great that we are now a forum, I mean there are likely to be more. We're doing one of the Atlanta Gitlab at the next KubeCon which is kind of cool. But you know so getting all the right people in here, focusing on the data problem. Where we look at from a universal control plain standpoint. There are lots of people here talking about the economics of this and what it means for venture capital in the next five years and what it means for acquisition patterns and NMA. There are lots of really interesting aspects being covered today. >> Yeah it's a classic inaugural conference where with the organic communities here you have a range of personas. Entrepreneurs, founder, executive, venture capitalists, all kind of having those candid conversations. What to do next. >> That's right. >> Kind of all ger multiclouds here. Questions is, what's it going to be? >> What's it going to be. Well I think I was trying to figure that out. Honestly, anything that makes it easy for enterprises to do this massive lifting and shifting of infrastructure and being able to control their data, deal with multiple vendors, the world is increasingly heterogeneous. That's another way of saying multicloud is just dealing with the heterogeneity. And it's going to be more and more heterogeneous because if you look at the trends, it's hard to imagine that all innovation is going to come out of one cloud company. Right. So if that's not the case then you have people innovating, people creating all sorts of new platforms and infrastructure. Ways of dealing with data, ways of dealing with networking. Or ways of dealing with storage. Data bases and everything else. Now that you've got this innovation happening, whether it's open source communities or not. And then as an enterprise user, I want to consume it, well I have to deal with the heterogeneity. How do I consume it? How do I bring it together? How do I make sense of it? How do I get it all secured? How do I get it all under my compliance department? Those are the opportunities that are on multicloud and it is a reality. So at some level I'd be hard pressed to find someone that says I'm using Amazon or Google or Azure only and not say using a boutique cloud or another service or something else. Everybody's got some set of services that are... >> I mean multicloud and multivendor are two words that you go back to the history of the computer industry >> That's right. multivendor is a heterogeneous environment. There's benefits of that. But all that was based upon the lock-in fear. And you'll be hearing some of that here. So what's your view of lock-in because if value creation is the lock-in, the red hat guys giving a talk about Wal-Mart cloud versus niche clouds, it's all open source so where's the lock-in? >> Yeah I don't know if I would subscribe to this as solving the lock-in problem and every time you use a vendor at some level you're kind of relying on them. If they have a good service you're kind of tied to them right? But the more interesting aspect to me is having a choice. So being able to say I'm going to pick the best data based vendor out there. One that suits my problem and being able to do that without having to let go of the integration aspect of us. If I have to choose a data based SaaS service that I really like but the cost of doing that involves me creating a new vendor or doing some custom automation, custom integration, figuring out monitoring, figuring out logging doing billing, doing metering. All of that stuff so that I can actually just consume one amazing service. That's a really large hurdle to kind of step over. And so, I think part of multicloud is reducing friction for being able to use things that you choose to. >> Do you have any commentary or advice for other founders or other CEOs or even any younger developers because we have a classical trained software developers, they think a certain way. They either were pipe lining it different, not doing Agile, their trained at Agile, but now micro service is a whole nother ballgame. How do you get people to think microservices when they've been classically trained Agile. >> Like Waterfall you're saying? >> Or Waterfall, both, both. >> I think there's a lot happening right now. I would start with looking at some of the best practices around building modern services. Things like Kubernetes and others help. Microservice adoption and all that stuff. But start with, honestly starting with a bunch of open sources probably not a bad place to be. But then find vendors that actually can support in one what you want to do. >> Final question. Tell us about your company. What's going on with you guys. Give an update on Upbound. What's going on? It's going great. We're growing. We launched this project called Crossplain. Like earlier or late last year. It's doing great. We're getting a ton of adoption on it. We're super happy with it. And we're growing the company. We're almost tripled the company this year. Which is fantastic. And working on a SaaS offering that we're exciting about. Hopefully we'll come back here and talk about it when it's... >> And you guys hiring? Looking for people? What's the update there? >> We are. We're hiring on the engineering side, we're hiring on the product side. It's start up so. You never stop hiring. >> Not for the faint of heart. >> Definitely not. >> Bassam, thanks for coming out. >> Yeah absolutely. Always fun. >> Here at the multicloud inaugural event. Escape. Here in New York City. Escape 2019 I'm John Furrier with theCube. Back with more after this short break.

(upbeat music) >> Narrator: Live from Boston, MA it's theCUBE covering Red Hat Summit 2019. Brought to you by Red Hat. (upbeat music continues) >> It is so good to have you back with us here on theCUBE as we continue our live coverage here at the BCEC at Red Hat Summit 2019. Glad to have you watching wherever you might be, Eastern Time Zone or maybe out West. Stu Miniman, John Walls here. Our coverage continuing; sixth year we've been at this summit. Eric Kern now joins us here. Both from Lenovo, Eric and Steve Brown. Eric is the Executive Distinguished Engineer. And Steve is the Managing Partner in the Software Business Unit and the DevOps practice leader. So gentlemen good to have you with us on theCUBE. Good to see you today! >> Thanks for having us. >> Thank you. >> No surprise, right, that you're here; long term partnership, very successful get together. First off, I want your ideas or your impressions of what you've hear or what you've seen so far here in the day and a half that we've been underway. And whether it's keynote or maybe one of the side sessions, just what's your first impression of what's goin' on here? >> Yeah, I mean it's great. There's a lot of people here, a lot of activity. I mean we can see the Expo behind us. You know the food is great, lunch is great so- (laughter) >> Rub it in. (laughter continues) Rub it in just a little bit. Okay, so a little bit of news this week with regard to what you're up to. And if you would, I'm not gonna ask you to go terribly deep, but just give us an idea of what some of the headlines are you guys were sending out this week. Steve, why don't you take that? >> Yeah, so this week we announced six new reference designs and solutions, engineered solutions. But pretty excited about OpenShift 4 and certainly Rel8 after a five year I guess pause, if you will, on major releases. So that's exciting. >> So, Eric, why don't we start with building on those partnerships, talk about some of the solutions your talking to customers and some of the latest and greatest? There's a lot of interesting things we're doing; one of the things we've been doing recently is around TruScale. So TruScale is our infrastructure as a service on premise. So one of the things we do with it is we build overall solutions. So there's a number of reference architectures that we talked about with Red Hat. These solutions, think about them as having an overall CapEx price and then we convert that into a OpEx price. Probably one of the neat novel things, and this is kind of the area that I really got into, right, is around how do we build a metering system that doesn't require us to install a bunch of software and can be compatible with everything? So with TruScale what we've done is we've leveraged our what's called our xclarity controller, it's the chip basically on the motherboard, and that xclarity controller has the ability to measure power. And measure power both at the overall input consumption, as well measuring power in the CPU, the memory and the eye out. And we built an infrastructure around that. We can actually tell you exactly what percentage the system is being used and consumed based on that. And we can charge for the overall system on a monthly basis. So we have a portal that's set up for that, whether it be our hardware on its own or our hardware with the Red Hat software installed on top of it. >> So how's that effect the customer relationship then? All the sudden your- whether there was a- not I'd say a dispute, but might of been questions about how much usage am I getting? How am I using this? Why am I being billed as I'm being billed? So on and so forth. Now all the sudden you can just deliver the proof's in the pudding, right? You can say this is exactly what you're doing with this, this is exactly how much you're consuming. And I would assume from a pricing standpoint for that modeling standpoint, you give everybody a lot of comfort, I would think; right? >> You do, right. Not only do they see exactly what they're being charged for, they see exactly some of the usage on their own systems. A lot of times they don't know how well-balanced or unbalanced their systems are. And so we're actually providing real usage data. It's different than what you get in public cloud. It's different in what you get in other solutions where it's virtual allocation. So there's a difference in knowing the physical utilization versus the allocated utilization. What a lot of people do, a lot of companies do when they're renting public cloud infrastructure is they spend a lot of time in automation to actually deallocate. Right, so they're doing all this work just to try to save money. Whereas in the TruScale model, you just run it like you normally run it and you save money because you know, if you're not using it, you're not paying for it. >> John: You don't pay for it. >> Exactly, exactly. >> All right, well Steve, a lot of discussion at the show this week about OpenShift, not least this morning, OpenShift 4 was released. We've had a chance to talk to a number of customers, bring us inside, you know, Lenovo's worked with OpenShift for awhile. Oftentimes we think about the application layers like oh, it's totally divorced, I don't need to think of it. Well, we understand there's integration work that happens there and would love your insight into what is happening at he integration, where it's progressed, and any customer stories that you've got along those lines. >> Well, yeah, we've been doing a lot of work with OpenShift. I would say for an upwards of more than two years. We started with Intel and Red Hat and built a number of Intel Select solutions, reference designs, both bare metal and hyper converged. We are on our fifth edition now of the OpenShift design on Cascade Lake. We're the, I wanna say the pioneers in the industry. We have a center of competency in DevOps with software to really promote software development solutions. And we're excited with OpenShift 4 because of the CoreOS integration as well as the auto-provisioning. Key things, it makes it so much easier to adopt and integrate. >> Any customer deployments? When they come to you, what's the kind of a-ha moment that they have? Is it just the agility that it brings them? Is there anything you can share as to the customers that are actually doing this in the field? >> Well, I like to think the customers get the a-ha when they realize that there is an engineered platform that's been purpose built and they're not coddling software and tools together. It helps with the CI/CD pipeline process templating much more effectively. Overall it's, I think, a lot more streamlined than it was in the earlier editions of OpenShift, especially Open Source. So we're pretty excited with comprehensive business support. I think that businesses feel comfortable. >> Kind of a simple question, but what do you, in terms of what TruScale operates now, what is the- what are you allowing people to do now that they didn't do before? In the latest version here, what exactly is- where's, you think, this improvement? Or where's the new efficiency? What are they getting out of it that would make me, as a customer, have that- if I haven't converted yet, or if I'm perhaps ripe for the taking, what would make me jump? >> Part of it is customers don't want to be managing their infrastructure. And so this there's a big push to public cloud. They just wanna be managing their applications. They just wanna focus on what's paying the bills, right? And paying the bills are providing the IT service is all in the application layer for the most part. What TruScale allows them to do is to have that public cloud kind of management platform. So it's Lenovo premium support behind the scenes; so Lenovo is managing the hardware itself, Lenovo maintains the ownership of the hardware, so they're not even owning the hardware, very similar to public cloud. And they can go and use it on FREM. So they don't have to worry about any security issues with the public cloud. They don't have to worry about any kind of network issues, right, it's all in their data center. It's running just exactly the way they'd run CapEx, but they're running in the way that they have really liked with the public cloud infrastructure. >> So confidence, comfort, security and all that stuff right? >> Eric: There ya go. Yeah. >> Yeah, that's just- I'll pay for that! >> Sure! (laughter) So, we've seen software move heavily towards this model whether it be SaaS or various moving CapEx to OpEx. When I look at infrastructure it's been a little bit of a slower move, especially, I've got some background on the storage side, if you look at storage, it's like oh okay. I'm conditioned as a customer to think about my capacity, my performance, and how I'm tuning everything, and I need to make adjustments, and making changes usually takes a little bit longer. Red Hat's got a lot of software products in the storage space. Help us understand how this fits in and are customers gettin' more comfortable moving from the CapEx to the OpEx for their uses? >> Yeah, good segue. So Ceph and Gluster are some really interesting storage products from Red Hat. And they fit right on our servers, and so we install them; we build big solutions around both of them. I'm actually working on big architecture for another company, for another customer out in Germany. So it's huge stuff cluster. The neat thing about it is our TruScale model allows us to actually sell them on OpEx in a storage product. And what we're measuring is the storage, what I call storage in motion versus the storage at rest. So we see all the different usages of the different servers. The servers are acting as controllers, a multi-tenant controller. And there's a lot of information that's being stored and transmitted through the systems. TruScale's just accumulating all the usage of that. And Steve, maybe you want to talk about some of the software side of it from the storage perspective, but it's really, TruScale fits right in real nicely with the storage side of it. >> I'd actually like to talk about it more comprehensively from the Red Hat software side of it. Anywho, let's talk about how they're already no certification needed. We're looking at all Red Hat applications on TruScale; whether it's OpenShift, or Rel8, Gluster, Ceph, Ansible. So we're really excited because we're not limited in the portfolio. >> Exactly. Exactly. >> Yeah. >> So, Steve, it's interesting, you used to think about, okay, what boxes am I buying, what license I'm doing. If you talk about a real true software world it should be a platform that unifies these things together. So it sounds like you're saying we're getting there. I shouldn't have to think about- give us a little bit, kind of the old way and where customers are seeing it today. >> Yeah, well we're not getting there. We're there. What that allows us to do is to take the reference designs that we have and the testing that we've previously validated with Intel and Red Hat and be able to snap pieces together. So it's just a matter of what's different and unique for the client and the client's situation and their growth pattern. What's great about TruScale is that in this model we can predicatively analyze their consumption forward based on the business growth. So for example, if you're using OpenShift and you start with a small cluster for one or two lines of business, as they adopt DevOps methodologies going from either Waterfall or Agile, we can predicatively analyze the consumption forward that they're gonna need. So they can plan years in advance as they progress. And as such, the other snap-ins, say storage, that they're gonna need for data in motion or data at rest. So it's actually smarter. And what that ends up doing is obviously saving them money, but it saves them time. The typical model is going back to IT and saying we need these severs, we need the storage and the software, and bolt it altogether. And the IT guys are hair on fire running around already. So they can, as long as IT approves it, they can sort of bypass that big, heavy lift. >> So from what you've heard of this week, with Rel8, the big launch last night, a lot of fun, right? >> Steve: Yeah. >> And then OpenShift 4 earlier today talked about- >> Yeah. >> What if there are elements to those two, either one of them, that you find most attractive? Or that really kinda jump off the page to you? Is there anything out there that you're seein' or through the demos that we saw today, or last night even that you think wow, that's cool, that's good, that this is gonna be useful for us? >> OpenShift is one of the things that we're seeing in the industry that's just really enabling the whole DevOps practice. So OpenShift is interesting from the perspective of flexibility, automation, the tooling. Rel8, of course, we've all been waiting for it, I guess for a while now probably. >> Host: Right. >> It's just the next level, the next generation. The Red Hat software, see I'm a big fan of Ceph. I mean I just like Ceph, it's just a neat storage product. It's been around for awhile, but it keeps getting better. It's kinda like the old storage product that first came out with some soft-refined storage. But the whole ecosystem around Red Hat is just very appealing. I actually, Cloudforms is one I think is a little under-utilized today. Cloudforms is a real nice cloud management platform as well. So there's a lot of interesting Red Hat software. Steve, we've done all these reference architectures, are there any ones that stick out to you? I've just been kind of rattling off some of the ones that I like. >> Yeah, I really like the CoreOS integration, 'cause we now see that acquisition really taking shape in a true productization sense, in a practical use sense. I think with Red Hat owning that asset and controlling the development, they can build out features as needed. They're not having to wait on the ecosystem or to spin different cycles for growth. So I think that's my highlight. I've been looking for that. And auto-provisioning as well. I think that's a really key benefit to it, just to make things more smooth and simple. >> Well gentlemen, thanks for the time. >> Guest: Sure. >> Nice to meet you. Look forward to seeing you down the road. We were talkin' about Lenovo, Stu and I were there a couple of years ago, Ashton Kutcher out in San Francisco, so now we get the two of you guys. You're right there with Ashton, right? (laughter) >> That's right. >> Same celebrity! Thanks for sharing the time. Good to see you guys. >> Eric: Thank you. >> Steve: You too. >> Back with more live here at Red Hat Summit 2019, we're in Boston, and you're watching theCube. (electronic music)

>> Announcer: Live from Las Vegas, it's The Cube, covering IBM Think 2018, brought to you by IBM. (lively music) >> Hello everyone, welcome back to The Cube. We're here live in Las Vegas for IBM Think 2018. It's where all the action's happening. Third day of three days, wall to wall coverage, I'm John Furrier, co-host of The Cube, we have two great guests here, Paul Papas, Global Leader of Digital Strategy at IBM's iX, new digital agency, and his cohort Matt Candy, European leader of IBM iX, a new agency within IBM specifically developed for expanding the digital services to their customers, to create the best experiences, using technology, data, and other analog and digital capabilities. Wimbledon and among others. Guys, welcome to The Cube. >> Thank you, thank you, and thanks for that great introduction. >> So Paul, so take a minute, this is a novel concept. When I think of agency I think ad agency, buy some keywords, PR firms, you know, more of an adjunct to a core organization, kind of a service provider. >> Yeah. >> You guys have it a little bit different agency focus, more like management consultants meets World Economic Forum, meets, you know, UX UI design, because you are building this company. Take a minute to explain what iX is, and what's different about it in context what people might think it is. >> Sure, and thanks, a great set up in there it's like you melded a lot in there of what we do. So you can think of us as a combination of strategy consultancy, digital agency, consulting systems integrator. So we do three things with our clients, we help them design, well we help them define, their digital strategies, really their business strategy in a digital world. We help them design world-class customer experiences. Experiences that are going to be personalized, and have an impact. And then lastly we help them implement the technology. Implement the customer platforms that they use to engage with their customers in a personalized, meaningful, omni-channel way, all of those things that we do help drive a measurable business impact so nothing we do is hypothetical, everything we do is real and drives a real business impact for our clients. So, where if you might look at an agency a lot of people think of agency as marketing communications agencies, and the world has changed so fast around digital, >> Or ad agencies. >> Or advertising agencies, you know, in that vein, we're on the more transformational side. In fact we consider ourselves a business design partner. So what we're trying to do with our clients around the world is help them redefine, redesign their businesses, so that they're fit for purpose, so that they can survive and thrive in this modern world. >> Yeah, I want to get your thoughts on this, because you know looking back as a historian if you will of evolution, technology used to be slower, so agencies added value on something complex, ad agencies would create ad campaigns and some glam, glamour around something. And we even saw it in some of the lead gen side of the business, where this beautiful micro-site and the graphics are amazing, it looked great but actually didn't scale there's no tech behind it. Now fast forward, you have the requirement for cool, relevant, and glamorous, but actually having tech involved. Cloud computing has really enabled this, and the role of data has really enabled it, so this is now the new normal, the new normal for these higher-end functionalities is actually having a tech stack, technology stack, combined with business engineering logic, >> Paul: Yeah. >> And real business outcome, like profit, money outcome objectives that people might want. How do you guys explain that story because, you know, I would just call a consultant up in the past, are you guys combining it to make it easier? What's the purpose that customers call you guys in for? What are they asking for from you guys? >> So I'll start off and then Matt, you can add color commentaries, so, the way we describe what you just, what you just brought to life there, was, we have multi-disciplinary teams, so we have a combination of business strategists right, so when our clients are engaging us, they could be working with a business strategist who's really comfortable showing up for work and wearing a suit and tie, and he could be sitting next to, in our studio, sitting next to one of our creative designers who's tattooed from his wrist to his neck. >> The hoodie guy building everything. >> The hoodie guy, right, sitting there building there, next to one of our data scientists who's popping open his Lenovo laptop, it's got the latest chip in it, and he's so pumped 'cause he's going to run some crazy data analytics on it, applying AI on top of it. And all of these people work together using Design Thinking so we have an approach we call IBM Design Thinking, they've all been trained, we've trained over 16 thousand people on Design Thinking, and they all work together and come together to solve our clients' ploblems. They work in a studio environment, and we've opened up 38 studios around the world. Studios are places where we co-create with our clients, or we invite our clients in to ideate, innovate and co-create >> So it's agile on the format, on the projects, not like Waterfall, hey now you pass the ball to the other guy, it's all integrated team. >> Yes, and what you end up having is, you end up having the view of understanding the business and the client's business challenge, which is where we start when we define the strategy, when we do the design work, it's underpinned with an understanding of the technology that's going to bring this to life. So we like to say that we don't do creative for creative's sake or creative just for the beauty of the art, we do creative that can actually be made real. >> Yeah, you guys put a relevant package together. So I got to ask you now, the beauty of cloud computing was, is that you don't have to provision a data center if you don't need it. Now you see people needing a data center for privacy reasons they store their data, hence the hybrid cloud strategy, et cetera et cetera, but if I want to do something like what you guys are doing, it's going to cost me money to build it out. One, where are the people? Skills of the people, salaries of the people, tools for the people, all that is expensive to build out. So it's natural to go to someone who's already got it. So I want you guys to talk about that dynamic, of buy versus build, what stays in-house that's core competency, and what's the scale leverage that the clients get from working with you guys, 'cause you have that advantage. >> Yeah, and actually what I like to tee up is, this cost effective approach that we use to help our clients jumpstart the work that they're doing, we call it an innovation garage, and Matt and the team in the UK and in Europe have really been champions of this approach. Why don't you share some of the work we do around innovation garages. >> Yeah, so, I mean, one example is our client BP who we've been working with in this space, and helping them drive a lot of the digital reinvention of their business. And so, teams of data scientists, designers, developers, working hand in hand with product owners from the client side but ideating, finding new different digital products and services that help improve advocacy of customers drive loyalty, drive new revenue streams but very quickly taking those ideas and turning them into prototypes right, paper prototypes, actual MVPs, minimum viable products, launching them into market right, choosing some target markets, but putting very measurable KPIs around each of those things >> What's the timetable on that roughly, ballpark? >> Probably getting those MVPs out at eight to 10 weeks right >> So, fast. >> Oh yeah, fast. >> It's not months, not eight months. >> No, no, there's no Waterfall. And so a radically different approach to getting things out there, in the hands of real users. And then testing and learning, iterating, and then based on the data, actual fact and data backed against those KPIs and measurements then starting taking the decision around whether we're going to scale that into a global product. >> Yeah before we go to drill down on that, what's the alternative to doing that? How many months would it take if I want to do it from scratch in-house? >> Spinning up large transformation programs right, and >> John: A year. >> Yeah, at least, multi-years >> John: At minimum. >> Multi-years, and I think the other thing John, that's kind of key about this way of working, is that you're starting to infuse new ways of working and new ways of thinking into the client's organization right, and so Design Thinking: lean, agile, dev ops, right all of these approaches to get things done in a more rapid way and so, you're kind of driving change and transformation through making and creating and doing, not through some big change management program. And so we've been, if I took BP for example, training and certifying their people in IBM Design Thinking, certifying them as product owners and so, through the act of making and creating these services, it's changing their culture and changing how they get stuff done and it's a bit like a fire, kind of a little fire that burns and spreads within the organization as people see what's going on and want to become part of it. >> And one of the ways we do that we actually co-locate in these innovation garages. So you take a company like BP, if you go to our South Bank office, we have a dedicated floor where you have a hundred BP people with the IBM iX team, working in this innovation garage model, >> So they're learning too with you it's not like you're doing all the work and they're integrating in. No, no, we're learning together and they're building new skills and we're building new skills, and we're coming up with new ideas and innovations we're doing it in a cost-effective way, to your point before, in the past companies would spend a lot of money to try to go down a big path and try to in essence, boil an ocean sometimes. >> Yeah and your one guy quits, you got to replace, skill gaps, massive challenges. >> But also I find that from the client's perspective the thing that they're most proud of, some of the things they're most proud of, is the bin, what they call the bin. And so it's all of those ideas that we've killed as far to the left as possible right, and taking an idea that traditionally may have turned into some big program, multi-millions spent on doing it to find that it actually didn't deliver the outcome for the end consumer. >> So Matt, talk about the example with Wimbledon 'cause obviously everyone kind of can recognize that brand, you guys have been working at Wimbledon, you have a relationship with them so they've known IBM for years. What's the current state of the art with Wimbledon? What are some of the things you're doing for those guys and how is iX team, your integrated design team, working with those guys? >> So we've been partnering with Wimbledon now for about 28 years, so relationship goes back to 1990, I mean Wimbledon's been around back since the 1870s, you know, the home of kind of tennis, tennis in an English garden, so complete with rain and drizzle and gray clouds and everything else. And so, probably over the last seven years we've been working with them to drive their digital transformation, and so, how they engage with fans, and so how they use data and analytics to drive insights to put very personalized experiences in the hands of fans. So if you think about an event like Wimbledon, runs for 13 days, and about 500 thousand people get to physically experience Wimbledon in the grounds. And so their whole strategy from a digital perspective is taking the beauty of the grounds and the experience, and how they can manifest that digitally to millions of people around the world. >> And that's more than live streaming that's more than highlights, that's replicating the vibe the buzz, the experience of being there. >> Completely, so if you look at the web channel right when you go to that website, you don't actually see tennis players and stuff on there. What you might see is a beautiful flower just wafting in the breeze right, so a lot of the technology and the experience that we put together is trying to bring to life the beauty of the grounds right, through those digital mediums. And also being very thoughtful and purposeful about the different channels, so when you think about the mobile app right people use that to get snack access to data they're on the move, they want to understand the scores, alerts, iPad, people tend to use that sat on the sofa in front of the telly, you know, second screen experience so there's a different set of use cases and demands. We launched the first Apple TV app for grand slam tennis tournaments. So again, people tend to be using that for catch up and replays and so, being very thoughtful and purposeful about the... >> And you got to keep track of the digital culture 'cause it's like fashion, you got to know what's state of the art, what's going to sell VR, AR, whole new creatives coming out >> You do but you also have to do it in a way that's authentic to the product. >> Tech fashion. (laughter) The latest and greatest. >> Hashtag new hashtag tech fashion But you also have to do it, what I was going to say, you have to do it in a way that's authentic to the brand that you're representing. >> John: And relevant. >> Correct, so we're expressing the brand of Wimbledon online through digital channels and mobile channels, it has to be consistent with the brand, the brand values, the brand purpose, the brand mission. >> And that goes in to the design side of it 'cause they're going to tell you look if we go off the brand, we're not... >> The beauty, the elegance, the elegance of the sport, the elegance of the All England Tennis Club, you have to capture all of that and represent it in a way that's genuine. >> Alright so this is where the melting pot between agency, creative, ad agency, where it's much more about experience, less about the tech, and tech come together. So I wanted to ask you, I did a panel this year at Sundance called the New Creative, with Intel and it was all about the emerging new creative artists that have tech behind it, and here's what we talked about, I want to get your reaction to it. Agile, which killed Waterfall development, made things less risky, the old days was, you build something, a lot of craftsmanship goes into it, but you ship it, you don't know if it's going to work, and you hope it works and sells. Then Agile de-risked that, but you're shipping code every day. But what we lost with Agile that's now coming back, and I think this is where you guys are hitting the mark, the idea of craftsmanship in the product is coming back. So you got Agile, that's good, but it felt boring, it felt, the products didn't feel great. Yeah, certainly they were successful and they used data to be agile and always be iterating, fail fast, et cetera, but now the users want craftsmanship, they want art, they want more experience in the tech product What's your reaction to that, what's your vision? Do you agree and, if you do, what's your opinion? >> Well I agree on the recommitment to craft, and the approach that we take to that is really starting with Design Thinking, and we view this a couple different ways. One, we think Design Thinking is a way to actually solve business problems in the modern world. Now design, we view as a craft. So we have very specific craftspeople that are pure designers, that's what they do every day for a living. Everyone in our organization practices Design Thinking. So I believe that the use of Design Thinking coupled with our design community and the world-class talent that we have there, has enabled to really get an underlying need, right. So when you're doing a design, you have to have the understanding of the underlying need of the customers that you're trying to serve. And that's what we really get at, so the craftsmanship that comes in through applying Design Thinking, applying your design principles to creating something that can then be made real and have an impact. If you ask our designers, in our 38 studios around the world what they love about being part of IBM iX and being part of IBM, it's the impact that they can have. That they can see their design scale, they can see it brought to life in a way that is far beyond anything they could've done at any agency >> Can't fake design, it's like security, you can't fake it, it either works or it doesn't. >> And the way we think about design right is about almost design with a capital D. And so it's not just about how things look and feel, it's about how they work, and so how you can apply design to help solve problems in a very different way right. And how you apply design to strategy because designers are problem solvers. And so actually having people apply a designer's mindset to problem solving, you end up with very different outcomes right, you end up with a lot more innovation driving into what you're building, and I think you end up with products and services that actually help make somebody's life a little bit easier right, you're taking friction out of their life you're delivering something meaningful and of value to them. >> You're doing empathy mapping, you're doing customer journey mapping, you're doing a persona development. I want to build on what Matt said though that designers are problem solvers. When we look at Design Thinking, we have a method called IBM Design Thinking, and the logo that we use for Design Thinking is actually an infinity loop. So what we do is we combine Design Thinking with Agile and I think of IBM Design Thinking as a 3-D printing of a solution to a problem. We're designing it, we're getting at an underlying need, we're prototyping something fitting a proof of concept, we're learning, we're now doing another iteration of Design Thinking and learning more about the underlying need, testing something, and as we keep testing and learning, we add more texture to the solution of the problem and it starts coming into focus for us. >> Yeah, and the key word's problem. I interviewed a Stanford professor on the cutting edge of innovation, design she said, "Don't fall in love with your product. Fall in love with solving problems." And I think that's kind of what you guys believe. >> And I think John, to the point that you raised, about Agile, you know, we see many organizations driving kind of Agile transformation and shifting, and you know, I think our perspective is very much is you need this combination of design, of Agile and dev-ops together, because Agile allows you to pivot quickly, dev-ops allows you to kind of learn and get rapid feedback from production and putting things out there, and you've got to have this kind of design-led approach to doing stuff, because you've got to make sure that what you're building and putting out there serves a purpose and a real outcome for the end user. >> That's perfect, and most people think oh, we're Agile, check. No, whoa, hold on, stop, yeah it's not a silver bullet. >> You brought up a great point from a business leadership perspective that don't fall in love with your products, fall in love with the problems that you're solving, We are seeing that across every industry we work in, and I think this new digital age, with all these emerging technologies going mainstream so fast, AI, AR, VR, blockchain, it's allowing companies to, in some ways, reimagine their purpose, but in some ways, revisit their original purpose. So if you look at, Ford as an example, they've declared that they're going from pure car manufacturing, to mobility services. If you look at our clients in the life sciences industry, years ago they would've declared themselves as pharmaceutical manufacturers right? But now they would look at themselves as partners in health and partners in the health ecosystem. And every industry we're operating in, there's that re-imagining or revisit of the core mission. >> I think this is the only interview I haven't asked about blockchain, but I was just talking to Jesse Lund about blockchain and we talked about digital currencies, digital, and we observed, and we were talking about things are happening faster. So what's happening on digital it's a speed gain, across the board, with currency there's no clearing, it's digital, it moves instantly. So his banking side, that's his thesis, but here, your customers are challenged with looking down the barrel and being scared when, damn, this is going to be fast, what if I screw this up? I mean this is kind of how I see it happening, like it's accelerated in all aspects. >> And this is where I think, in terms of the business that we're in how we're different, and you've kind of raised the traditional agencies and stuff earlier, John. I think the difference for us is, you know when you think about the world of advertising, and companies driving their message out through shouting loudly and campaigns and building micro-sites, actually, our perspective very much is that these, most organizations need to look at how they digitally reinvent, right. And so therefore the scale of change needed as they look to reinvent their businesses, the business models, the skill pools within the organization, how they're going to use data and insights to drive different experiences you start to move to a very different level of change and transformation right, and one where these technology platforms, and becoming a platform business in these organizations, right, need a partner fundamentally who can help them scale and drive that change. >> And the data's critical, using data, using cloud, dev-ops, Agile, design, all rolled into a highly accelerated process, that's hard. >> It is hard but, >> You guys are doing it though. >> Well yeah, that's what we do for a living. It's what our clients are faced with right now. It's kind of a like a Dickensian-like challenge, right, it's A Tale of Two Cities. With all the emerging tech that we were talking about before there's never been a better time to create new innovations. To be innovative in some of the things that we're doing with BP was a great example of that. And some of the bigger things we're doing with some clients that are trying to reinvent their organization around a renewed purpose. But at the same time, there's never been a bigger threat to existing companies, in terms of there's never been more opportunity to be disrupted. So between these two poles of never been a better time to be in business, never been a tougher time to be disrupted, that's where our clients are operating. And this juxtaposition of core and new where our clients have mostly been in business for more than a few years. They have a core business that they need to grow and optimize, while they also need to expand into the new. And they can't do one or the other, they have to do both at the same time. >> And you know the customers I talk to in the industry, around this area, really look down, they look at three choices. Go for it, that's scary, need a partner to do that you guys are there for that. Don't do anything, put your head in the sand. Or three, create blockers and ban stuff. So you're seeing, you kind of walk in and you kind of figure out who's doing what. You see the blockers with all these excuses, no well we've got this other... And then the head, well we should be, they don't do anything, they're not moving. And then people who move. >> Yeah. >> I mean that's the reality right now. >> You know, what we see, we just published this research you know, a C-suite study, so we interviewed 12,000 C-suite executives, over 2,500 CEOs, and the title of this study's The Incumbents Strike Back, and that's what we're seeing now, so we're not seeing folks kind of sitting or putting their heads in the sand, they're looking at their legacy business, and the competitive advantage they have because of all the knowledge and incumbent advantage that they have, and now applying that. >> Well Paul and Matt, we don't have enough time to go into the impact of blockchain and cryptocurrencies, and initial coin offering's impact, to the token economics of how your business will change but we'll do that another time. >> Fantastic. >> Alright thanks for joining The Cube. I'm John Furrier here live in Las Vegas for IBM Think 2018. A lot of great conversations here in The Cube number one live tech coverage, extracting the signal from the noise. We'll be back with more after this short break. (techno music)

>> Announcer: Live from Barcelona, Spain It's theCUBE Covering Cisco Live 2018 Brought to you by Cisco Veeam, and theCUBE's Ecosystem partner's. >> John: Hello everyone and welcome to a special CUBE presentation here in Barcelona, Spain, we're live at Cisco Live! In Europe, I'm John Furrier, my co-host Stuart Miniman, Head Analyst for Networking and for Wikibon. Stu we're kicking off Cisco Live in Barcelona It's a European show to the main North America show in the US. But really kicking of 2018 for Cisco and some stark changes to Cisco's positioning. Really, they've always been innovative, but you're startin' to see what they're thinking, in terms of cloud, multi-cloud, IOT, and the role of the network and the networking industry, two different things. Again, we're going to break that down. Day one of two days of wall-to-wall coverage. Again, I'm John Furrier with theCUBE, Stu, I got to get your take, yesterday was kind of a set-up day, everyone's kind of coming in for these conferences. Big story was the Connected Women's Conference with DevNet and across Cisco. Great turnout, great energy. And then today the keynote, with Rowan who's up on stage for Chuck Robbins who did not make the trip. Really kind of laying out the vision for Cisco. Your take so far on Cisco, DevNet, the Women's Conference, and the Keynote. >> Stu: Yeah, so John, first of all, I know we're excited to be here. So it's the first time we've had theCUBE at one of the Cisco live events. We've done plenty of shows with Cisco, tons of Cisco people in the alumni database. It's actually the second time I've done Cisco live, but the last time was 2009. And my description in 2009 was you had network engineers that were in their wiring closets or somewhere in a dark dungeon. They kind of crawled out, got their CCIE re-certification, got a couple of free beers and t-shirts, and then kind of went back home after they did some networking. It's a very different vibe here. My question coming into this show is how much is Cisco a software company? Used to, you talk about, Chuck Robbins isn't here, but, Chuck and John Chambers before him used to, they talked about the software innovation and then they'd pull a chip out of their pocket and say we spent a billion dollars innovating on this chip. Now, what was nice here, in the the keynote this morning there was a lot of talk about the future. Software is a piece of it. Intent based, content managing the pieces. Meraki getting up talking about wireless. It's not about boxes, ports, cabling. It is about software, but Cisco's going through their transition, John, how do they go from kind of the quarterly sales targets of working with their traditional partners to this multi-cloud software world. Intent, absolutely a big piece of it. Cisco's got such a broad portfolio, John So much to get into in the next couple of days. >> John: And good points too about the software role and then Cisco's always been moving up the stack if you've been following theCUBE, you know we've been talking about this if you look at the old guard companies, Cisco falls in that category. Okay, the new guard companies, Amazon Cloud, and some new start-ups, they're playing with Cloud economics. They're playing with a whole new generation of software developers. Gone are the days of Waterfall, hello Agile, Agile programming and development. But Stu, the big contrast now with Cloud is the perimeter does not exist. This opens up security, which the number one thing on the keynote that Rowan brought up, as well as the main speakers, this is huge, because now there's no perimeter. Classic networking days are changed. Cisco's always been talking internally about moving up the stack, they're finally doing it. They're doing it fast. And they have to because they're under siege. >> Stu: Yeah, John, dig into that a little bit, I mean, you think back, Cisco was one of the four horsemen of the internet era. It was Sun, Oracle, Cisco, and I'm tryin' to remember who the fourth one was. But, I think Intel was there. So Cisco's been there. Security, always been part of the Cisco portfolio. Front and center, any customer I've talked to, I loved, there was a stat up there that 71% of customers said that security might be impacting innovation for customers. And I joked, I said well 29% are living in hermetically sealed underground bunker if they aren't worried about how security's going to impact what they're doing. Maybe they feel that they've solved it and they're not slowing down because of it but absolutely security front and center, a lot going on in the space. IOT, I have to be honest, Cisco's been talking about IOT for many years and I felt like they kind of for years it was like well there's going to be trillions of devices and we're going to network them. And I kind of said, okay, that's nice, but really how are you solving the business problem, how are you helping me and really that's where kind of the update as to where they're going, where's Cisco positioned to where they have the assets. They made a number of acquisitions in this space, everything from the SD-WAN vIPtela's company we followed pretty closely for a number of years as well as, AppDynamics, we interviewed them at Amazon reinvent, over a billion dollars for that acquisition, really a software company, doesn't mesh with the traditional Cisco model, so a lot of changes goin' on. Cisco positioned for a lot of those pieces but definitely a lot of challenges as well as opportunities for them. >> John: Stu, you mentioned IOT, one of the things that people, if you follow the industry, know if you're a historian, like us, they got it right Stu, their vision of internet, of everything was absolutely spot on, just 10 years too early. They had that awesome campaign, it was more window dressing and vision, but it actually was panning out. If you look at what they were talking about 10 years ago about connecting devices, they pretty much nailed it. However they missed a lot of things. So they didn't whoop the stack fast enough, in my opinion. And two, the Cloud came on really really fast. But now, they're already seeing that as an opportunity But it's a double-edged sword like I said on my tweet during the keynote. They could make a lot of money with the Cloud by doing multi-cloud, but it's a double-edged sword if they misfire, Stu, this could be a problem. So let's talk about that. What does Cisco need to do, in multi-cloud, to really be that TCPIP moment. Because you got all kinds of new dynamics with networking. You got end-to-end, but now you have a surface area including IOT that's everywhere, smart cities, sensors, on-premises, and in the Cloud. All over the place, so this is a huge, complex equation but Cisco's not new complexity, your thoughts. >> Stu: Yeah, first of all John, nice job on premises, we got it right. >> John: (laughs) On prem is the shortcut that I always use, Stu. >> Stu: Absolutely, still talking about data centers, talking about edge computing, talking about those, but Cisco like many of the, hate to say legacy companies, had a little bit of falter when we talked about public cloud. The whole inter-cloud message really was a little bit complicated. We talked some really smart Cisco DE's and got to really understand a little bit, but at the end of the day Cisco really understands they have a huge piece of their ecosystem as the service providers and that's who they're working with. Cisco is not selling to Amazon. Amazon buys from some of Cisco's competitors. But they're not selling to a couple of the biggest hyper-scalers out there and that is a risk for Cisco but huge ecosystem, thousands of service providers, that's who Cisco needs to partner with, that was part of the inter-cloud message and that's been rebooted with how they're doing it. They really look at - in Rowan's keynote this morning it was about the management interface. Cisco's always made lots of pieces, but the challenge is is I've got lots of device managers and how do I get multi-cloud. I'm using Amazon, I'm using Azure, I'm using Google, I've got my own data center. IBM, Oracle, Cisco partners with lots of these companies, how are they going to make it easy and why do they have the right to be in the center of a lot of those discussions. >> John: They partner yes, but I would argue that if I'm going to be critical of Cisco, they got to partner smart in a smart way. So the kind of partnerships that they need to do now is really joint engineering partnerships because if you look at the big whales right now, it's Amazon, Microsoft, and Google. The rest are all either customers, like the Facebook and those guys. But the real Cloud that they really need to go after and don't forget Alibaba and all the Chinese and European Clouds as well, with GDPR, a lot of complexity there as well they got to do partnering at a deeper level. So the new Intel Inside model is over. This now Cloud Inside with Cisco, they got to think differently. This is not an alliance with them as a channel partner or them in charge, they have to come in and understand that they have to peer with these clouds. I mean Google's at such a large scale, I met with them last week their site reliability engineering team is freaking phenomenal. They got chops, they know networking, they got to push Cisco hard. Your thoughts. >> Stu: Look Google, when Google Cloud launched, I said Google has the best network in the world. Stop. Bar none. Absolutely. Their SRE's setting the bar for how people look at these environments. I didn't hear much public cloud discussion. Cisco I'm worrying is a little bit over-rotating towards that IOT and Edge piece. Edge does not get rid of Cloud. Amazon's not goin' away at all. >> John: Cloud and Edge go together. >> Stu: Google, Amazon, Microsoft, you think they understand The Edge and what that's going to take there all of them have a play with devices even Microsoft's phone might have failed, but absolutely they've got applications and they know what's happening at The Edge. Google, come on, who created android. >> John: (laughs) >> Stu: They understand how to get there. Amazon's got Alexa all over the place, Google of course has their smart devices So John, didn't hear anything about voice in the discussion here. They talked about things like telepathy, which was struck me as a little bit interesting. Google has communications, they've got WebEx as a platform. They've got Spark on the phone to be able to communicate. They've got a lot of unified communications. Collaboration, I mean John, I know one of your top contenders, not just the networking of devices but the networking of people and Cisco looks a lot at that. Any take you want to have on that piece of it? >> John: Yeah, I mean, here's my take I love this intent networking concept with context I think they're spot on on that. I think Cisco really needs to add attention and reputation because as you have promiscuous devices out there from IOT to wearables, to automotive, you're going to have trust issues around the network nodes, now that these network nodes are going to have different personas if you will. So if you look at that, I think they really need to add attention and reputation to what to pay attention to in real time and the reputation of say a device or node on the network. That has to be added on top of intent because intent is just contextual and they've addressed that. So to me, that's the holy grail for Cisco. They got to build these new stacks with these new software variables so they can scale both in real time and kind of in typical network way which is normal for them, but real time's where it's at low latency, wire speed, this is the language we understand, but bring it to the cars, bring it to those devices, they got to nail that. So Stu, they have to think differently and I think the re-imagining of Cisco, the vision is about looking forward, Rowan's speech today was awesome on that front. He took us to 2015. >> Stu: 2050. >> John: 2050 I mean, Phenomenal. That is what Cisco needs to do. Show their customers that they're not just a gear company. They can't be gear company anymore. They got to move to the software model, and they got to have proof points. They got to look at apps that they don't want anymore and either get rid of them or double down. It would be interesting to see that Stu, what they will double down on. Is it Spark, I mean, I download the Spark app, I have no friends. Is it a social network or is it a collaboration tool like Alibaba Talk, it's not WeChat. I's not Facebook or Twitter. >> Stu: Yeah. >> John: Applications, Stu, they're kind of looking at The Edge, they have to have a position there, your thoughts. >> Stu: Yeah, so John, I think you're right, I was happy not to see a bunch of boxes up on stage talking about that. Now, not to get me wrong, we're going to be talking about a lot of the networking technologies, were is the - intent-based networking lives on the portfolio Cisco products, there is what they're doing with the service providers what they're doing in the campus environment and from a wireless standpoint Meraki obviously center to what they're doing there. They have - UCS has been the workhouse, really, Cisco in the virtualization age, they felt that they missed out on buying Vmware, but UCS really took the virtualization age and drove them into a market that everybody didn't think that they could get into. Kind of expanded the town, but UCS is kind of plateaued out from a revenue standpoint, and where can they go in the future. You don't see - UCS is built for kind of big workloads when we hear Dell and HP talking about how did they take compute to the edge, haven't heard Cisco saying oh, their architecture wasn't built for kind of those small low-cost, low-margin pieces, so where will they add value and get revenue there, I think hardware gets deprecated over time and it really is software. Where are they going to get that move, first of all they made a number of big acquisitions, but John, we haven't talked about, they've got somewhere between 50 and 60 billion dollars that's going to be repatriated back to the United States this year and that can make them even more aquisitive than usual. >> John: Yeah, they're going to have to definitely take that money from overseas, bring it in like Apple did and then go on a spending spree, but Stu, let's kind of wrap the segment up on the kick-off talk about kind of where they should go and to me the big story out of Cisco and following these guys over the past decade or so you've seen them foundationally rock solid on networking no doubt about it and even UCS, you're kind of critical, but also they've done a good job there. They have the foundational footprint and you're starting to see them move the stack and I think the big story to me is what DevNet's doing going into their network engineering community and turning those guys into modern Cloud native developers, to me, that is critical to Cisco. It's an investment. Is it going to be long on the tooth? Will it be real? To me it looks real. DevNet can transform and create an innovation surge Cisco needs that innovation to come from their own community. They need it to come from new developers while keeping their existing. Because that's going to be ultimately what's going to be built on top of the Cisco foundation, that is the network and to me, I don't think they need to be making a lot of moves right now. I think let the developers be creative with innovation use the cash to buy companies and let those flowers bloom To me that's the model. If they try to do the old internet days where they would just integrate companies in there's not a lot of companies out there they can just plug into their model right now. >> Stu: Yeah definitely John and we've been tracking for years a lot of the software pieces that Cisco's been working in. They've been big supporters of us at OpenStack, in Docker, The Container World, at the Cooper and Eddie Show So Cisco absolutely beating the drum towards that software, it just takes a little while for the big tanker ship that is dominant player in networking to move from relying on that hardware there's that big iron. It's not like they can just flip a switch and say hey, we're software and our margins and our sales are all going to be different. UCS, great, but it kind of reached a high-water mark and where does that transition and move forward to and as you said, partnerships are going to be key and not just lip service but true engineering where are they going to develop where are they going to find there - and DevNet great buzz already. The labs here have been just crankin' non-stop since I showed up. Lots of people diggin' in and not just the old certifications, it's really builders, John is something that you hear the Amazon community talk a lot about definitely the DevNet group. >> John: And the community's technical too, so they love to get their teeth on these demos. This Black Hat demos, there's White Hat demos for security always good. I want to give a shout-out to the connected women's group at Cisco, I attended their session they had yesterday it was kind of a get-together. Very inspiring and as a man, inclusion is very key and Cisco actually, Stu, is doing something really I noticed, they've swapped diversity and inclusion and they call it inclusion and diversity and they recognize that the conversations need to include everyone, then the diversity is just going to be addressed. So shout-out to the women's connected network here at Cisco for that great event and got to great group of people. Also want to shout-out to our sponsors that allow us to come to Europe to get all the top stories here at Cisco Live. That's the Cisco team here on the partner group and of DevNet, thank you to those guys at Cisco. So check 'em out. Veeam, IBM, and NetApp thanks for your support, allowed two days of wall-to-wall coverage here in Barcelona, live with theCUBE We'll be back with more coverage and interviews after this short break. (techno music)

(click) >> Welcome this special Cube conversation in the Intel Tech Lounge at the Sundance Film Festival. I'm John Furrier with The Cube. We are here with Ari Kuschnir, who is the founder and managing partner of Missing Pieces. Doing some really amazing work on the future of filmmaking. He's got a great entrepreneurial spirit. And creative desire to deliver great product. Welcome! >> Thank you, thank you. >> So, tell them about Missing Pieces and what's going on in your world. So, there's context. Take a minute to explain what you are working on. >> Well, the premise is to be at this intersection of storytelling technology. And to make stuff people actually want to watch. And VR and AR are parts of it. But not the whole. So, I know some of the conversation focus is on, is on VR, and we're just as excited about where storytelling is headed. In terms of what technology allows us to do. But the key for me is. I'm just passionate about, a new thing comes out. And I want to figure out how to make something really great. But meaningful, and powerful with that. >> We were talking before you came out about filmmaking, obviously trained in the discipline, obviously a variety of other things. But I want to get your perspective, we're on top of this new generation, what does that mean to you? When you hear that new generation, a new creative is coming? What does that mean to you? >> Yeah, I feel like I've ridden the wave of the thing as it's happened. And I mean, the company has too. So, I went to film school in the late 90s. And it was the first time you could buy like, first Final Cut, and the first wave of that. So you could make art little movies on the weekend, you no longer needed even to go to the school itself to borrow the equipment. That was revolutionary in 1999. And then 2005, when we started thinking about the company. You know, your Vimeo, YouTube, video i-Pod all come out within five months of each other. Towards the later part of the year. And it's a revolution. It's clear that with distribution, now not only can we make it and edit it in our laptops. But we can put it out, and millions of people could watch it. And that was the first time that was possible. And it was revolutionary. And I think it still is, to some degree. So, we've just, you know, as it evolves what I see is that, it's not, I've always felt like it's not enough to make the sausage as they say. You know, the directors, the talent that I sign now. Like the project we have now here at Sundance, young Jake. Jake is a great example of a creative who you can't fit in a box. He's an Internet artist, he's a rapper. He's an interactive video maker. He did an app called Emoji.Ink. And he does celebrity emoji portraits. He has a hundred thousand followers on Instagram. So, he can command his own audience. So, when a brand, or an agency comes to him. It's a very different approach than when they come for a very straight up work for hire, director's commercial kind of thing. That is the future, I mean. The future is about having a passionate audience, making things for that audience, understanding it. And being able to communicate with them on a daily basis, or a weekly basis in a powerful way, right? Through story. >> Yeah, I mean, you're riding the wave. And the waves are getting bigger. One of the things we do, we do a lot of tech coverage. And we see this in Cloud computing where software changed from Waterfall to Agile. And now the craft's coming back on the software side. But still now, software is eating the creative world. Because now a new wave is coming. So, speak to that, because you're, this is, you can almost look at the old ways. You mentioned the commercials and films. Almost like the Waterfall. You know, crafts, craft it up and you ship it. And you hope it works well. >> Ari: Yeah. >> But now, you have this new model of iteration. Where it's more Agile creative. How do you do Agile, like your artist, and not lose the craft? >> Yeah, well it's a challenge. Look, I've had so many opportunities in our 10 plus year career to kind of go in that direction of just like quantity over quality. And we could just never do it. I mean we're just not cut out for it. But at the same time, I'm not, I never ignore, how to optimize the content based on data, and based on what the landscape is looking like. So, an important thing for example that we consider in every project is context. Like what, how is this project going to be released? Oh, it turns out that, it's really a big social media push. It's not a TV thing. Or it turns out specifically it's Facebook versus Instagram. And that's a very different type of edit. And a very different type of way you start the video. 'Cause you've got a certain, even a different format, and a different way of looking at the content. So, you start to get into, and then you start to iterate, and look at the different ways in which you can repurpose, and rerelease the content, but customize it for each thing. So, you get into this really interesting place where the data is driving the story. And the feedback is driving the story. >> And the audience is part of the journey. >> Yes. And the comments, and the way in which people are taking the thing that you've made and re-interpreting it, is really interesting. And part of the story. >> You trigger a lot of emotion with me, when we're talking, because, you know, as an entrepreneur, I started media businesses turning into, and no-one has even seen this kind of media business before. But I have no media training of any kind. I did a science major. So, there's certain, and I've observed that there's dogma in the journalism business. And there's, but you know, how dare I challenge that, or others. You're doing the same thing. >> I love that by the way. >> So, I want to ask you. What is the dogma with the old world, 'cause the naysayers are usually the ones with the dogma. "Oh, it will never work!" >> Ari: Yeah. >> So, you're on the front end of this new trend. But you're going to have a visibility into what they're thinking, what is that? >> The dogma is, you know, the whole like, there's only big name directors, and you know, it's a certain caliber of work. And that craft is the ultimate thing. And that you just have to make the thing great. And it'll do the thing that is needs to do. Without any thinking in terms of context, or media buyer. How it can actually become a social, socially engaged piece. So, the thing that we're always fighting is some version of that. And then because we came from a scrappy place, but we're now, you know, a pretty legit thing, I think people, some people will still be like, well that's the kind of like, the problem solving sometimes gets interpreted as scrappy. Which is a word I really don't like. And I think-- >> It's a compliment on one hand. >> Yeah. >> But some people look at it as an insult. "Oh, he's just scrappy!" >> Well-- >> "He's not legit!" >> You never want to be the cheap solution. You want to be the solution that people call because nobody else can solve this problem for you. I think we, there's a strand of the company that's like, the kind of like, pick up the phone and we'll figure it out. And, the impossible project that nobody else can do. And then there's another strand where it's just like, you just want to make stuff people actually want to watch. How hard it that? The thing where you could just buy the media, and expect the results is trickier and trickier. >> I mean you could be different, and innovative, but that might not be good. But if you're good doing it, you're differentiated and you're innovating. >> Ari: That's right. >> What's the filmmaking track on that line. Because certainly there's a lot of innovation. And with innovation comes failure. But people are trying to be different. And being different actually is a good thing. What are some of the trends that you're seeing where people are having some success. And where people are stumbling. >> Yeah, that's a good. I mean what I see is, the things that do well take cultural context into account, and again speak to the people in that way. So, it's like a feedback loop that it's creating with its own audience. And we almost always, there's almost always a time in the process when we're dealing with an agency, or a brand where things start to go a little bit like, too, too much, and in that direction that you don't want it to take. Somebody, usually me, or someone will say, "Look, if we make these changes. "Or if we go in this direction. "We won't want to share it. "And if we don't want to share it, "nobody's going to want to share it." So, that becomes a key thing. Whereas before you could sort of away with some of that, now it's like, well, it has to pass this sort of, kind of litmus test in terms of like, are you comfortable with sharing this thing, because it speaks to you or not. >> So, I want to ask you the hard question, we're here at the Intel Tech Lounge, obviously Intel is doing a lot of tech things. They're trying to get all this new tech. And I see it on, whether you watch the NFL playoffs, with, you know, with the camera angles, the games, on basketball games. You see them using the power of technology-- >> We're actually working on an Intel Olympics VR related project that got a little tease ad, CES. So, I can just say that. >> Yeah I know, so what's the tech? What's the cool new game changer in your mind. As a tool that you need to be more successful, and other artists could use? >> Hmmm, well, you tend to, yeah I mean, I think we-- >> John: More horsepower, more compute, more-- >> No, I mean it's really the, What happened with the AR was really interesting, which was, everyone realized, oh, the phone's already in our pocket. While the headset needs to be something that really needs to be standalone. It needs to be $200. You know, like, you sort of, there's different kinds of headsets, of course. They do different kinds of things. But that's an extra hardware. The phone we already have in our pockets. So, everyone's started taking AR seriously. Including the big players. And what that allowed was a, a rethinking of what the possibilities with story would be. So, in some ways this last year has been a readjustment, and a rethinking of, well, what can you do with the phone that you've already got in your pocket. In terms of expanding the storytelling. Or placing a story in the middle of your living room, you know. A layer, using the phone as a window and a layer. But I'm equally as excited about what's coming in VR, interactive VR, room-scale VR, you know. The project that we have here is an interactive 360 project with a phone. >> What's that called? >> It's called On My Way. And the artist is young Jake. And the original conceit of it, is, it's Jake, there's four Jakes in a car. And every time you move the phone to a different Jake, it changes the Jake. So, as soon as it passes the quadrants. So, the four quadrant it kind of swaps the Jake. And that creates a really fun, and interesting thing. And he actually designed it for the phone, vertical. Because that's the way most people are going to experience it. >> John: That's awesome. >> But it's playing on a headset as well. >> Oh you're definitely a new creative. Love chatting with you. >> Thank you. >> Final, well, I have two questions, first one is, Sundance, what's the story this year? What's your report? If you had to go back and your friend asked you to give him a report, "Hey, what happened Ari, "what's going on at Sundance this year?" >> A combination of really interesting high-end VR projects. Some of them leaning into this kind of like more psychedelic less narrative driven stuff. Which I really like. Kind of like really embracing the fact that it's another world, and taking you there. And then the AR stuff. There's a thing called Tender, Ten Day R. Or Tendar. Which is a play on Tinder, by Tinder Claus. Which is, uses augmented reality, and emotion, and machine learning, everything that you could hope for in a really interesting way. So, that's kind of showing you where it's going. So, I think those two things. >> Psychedelic's interesting. I always, I mean this kind of tangent. But in, I've been seeing on The Cube interviews, I think we're going to have a digital hippy revolution. >> Ari: Definitely! >> And it's coming. I mean you can feel it. It's a different culture. >> When I was looking a lot of people, yeah, a lot of people are scared to, I mean, VR is a really great consciousness expanding way to go to get into other worlds. Without, you know-- >> And will all the crap going on in the world today you can almost look at this as a Sixties like movement in this modern era. Where it could be a major catalyst for massive change. >> Yeah, and there's a piece about, you know, this female shaman that grows through the tribe in Ecuador. And became the first ever female shaman for her tribe. And there's a piece called Chorus that, within it. Which is just super weird and trippy. And almost has no plot, but is amazing. >> All right Ari, you've got to run. Quick soundbite. What are you working on, what's exciting you these days? Share a little bit about what's happening. >> A variety of, again it's the full spectrum of storytelling, so it's not one thing. It's really pushing, experiential pushing, branded content pushing, original content that we're getting a lot more into that game. Long form series. VR series. Really, that's kind of the next wave for the company is to set foot, much stronger in the original space, and create our own original IP. Our own original content. >> Awesome, Ari Kuschnir managing partner and founder of Missing Pieces, check them out. Lot of great work. And again, it's a whole new game changing, from storytelling to the tech. The collision between technology and artistry, and creative, and it's happening. It's here at Sundance, at the Intel Tech Lounge. I'm John Furrier with The Cube conversation here at Sundance, which is part of our coverage. Was to look at the angle of Sundance 2018. Thanks for watching. (upbeat music)

>> Announcer: Live from Midtown Manhattan its theCUBE. Covering BigData New York City 2017. Brought to you by SiliconANGLE Media and it's ecosystem sponsors. >> His name is Jim Kobielus. >> Jim: That right, John Furrier is actually how I pronounce his name for the record. But he is Basil Faruqui. >> Basil Faruqui who's the solutions marketing manager at BMC, welcome to theCUBE. >> Basil: Thank you, good to be back on theCUBE. >> So, first of all, I heard you guys had a tough time in Houston, so hope everything's getting better and best wishes. >> Basil: Definitely in recovery mode now. >> Hopefully that can get straightened out. What's going on BMC, give us a quick update and in context to BigData NYC what's happening, what is BMC doing in the the big data space now? The AI space now, the IoT space now, the cloud space? >> Like you said you know the data space, the IoT space. the AI space. There are four components of this entire picture that literally haven't changed since the beginning of computing. If you look at those four components of a data pipeline a suggestion, storage. processing and analytics. What keeps changing around it is the infrastructure, the types of data, the volume of data and the applications that surround it. The rate of change has picked up immensely over the last few years with Hadoop coming into the picture, public cloud providers pushing it. It's obviously created a number of challenges, but one of the biggest challenges that we are seeing in the market and we're helping customers address is the challenge of automating this. And obviously the benefit of automation is in scalability as well as reliability. So when you look at this rather simple data pipeline, which is now becoming more and more complex. How do you automate all of this from a single point of control? How do you continue to absorb new technologies and not re-architect your automation strategy every time. Whether it's Hadoop, whether it's bringing in machine learning from a cloud provider. And that is the the issue we've been solving for customers. >> All right, let me jump into it. So first of all you mention some things some things that never change, ingestion storage, and what was the third one? >> Ingestions, storage, processing and eventual analytics. >> So OK, so that's cool, totally buy that. Now if you move and say hey okay so you believe that's standard but now in the modern era that we live in, which is complex, you want breadth of data, and also you want the specialization when you get down the machine learning. That's highly bound, that's where the automation it is right now. We see the trend essentially making that automation more broader as it goes into the customer environments. >> Basil: Correct. >> How do you architect that? If I'm a CXO to I'm a CDO, what's in it for me? How do I architect this because that's really the number one thing is I know what the building blocks are but they've changed in their dynamics to the marketplace. >> So the way I look at it is that what defines success and failure, and particularly in big data projects, is your ability to scale. If you start a pilot and you spend, you know, three months on it and you deliver some results. But if you cannot roll it out worldwide, nationwide, whatever it is essentially the project has failed. The analogy often give is Walmart has been testing the pick up tower, I don't know if you seen, so this is basically a giant ATM for you to go pick up an order that you placed online. They're testing this at about hundred stores today. Now that's a success and Walmart wants to roll this out nationwide. How much time do you think their IT departments can have? Is this is a five year project, ten year project? No, the management's going to want this done six months, ten months. So essentially, this is where automation becomes extremely crucial because it is now allowing you to deliver speed to market and without automation you are not going to be able to get to an operational stage in a repeatable and reliable manner. >> You're describing a very complex automation scenario. How can you automate in a hurry without sacrificing you know, the details of what needs to be, In other words, you seem to call for re purposing or reusing prior automation scripts and rules and so forth. How how can the Walmart's of the world do that fast, but also do it well? >> So we do it we go about it in two ways. One is that out of the box we provide a lot of pre built integrations to some of the most commonly used systems in an enterprise. All the way up from the mainframes, Oracle's, SAP's Hadoop, Tableau's, of the world. They're all available out of the box for you to quickly reuse these objects and build an automated data pipeline. The other challenge we saw, and particularly when we entered the big data space four years ago, was that the automation was something that was considered close to the project becoming operational. And that's where a lot of rework happened because developers have been writing their own scripts, using point solutions. So we said all right, it's time to shift automation left and allow companies to build automation as an artifact very early in the development lifecycle. About a month ago we released what we call Control-M Workbench which is essentially a Community Edition of Control-M targeted towards developers. So that instead of writing their own scripts they can use a Control-M in a completely offline manner without having to connect to an enterprise system. As they build and test and iterate, they're using Control-M to do that. So as the application progresses the development lifecycle, and all of that work can then translate easily into an Enterprise Edition of Control-M. >> So quickly, just explain what shift-left means for the folks that might not know software methodologies, left political or left alt-right, this is software development so please take a minute explain what shift-left means, and the importance of it. >> Correct, so the if you if you think of software development and as a straight line continuum you can start with building some code, you will do some testing, then unit testing, than user acceptance testing. As it moves along this chain, there was a point right before production where all of the automation used to happen. You know, developers would come in and deliver the application to ops, and ops would say, well hang on a second all this CRON tab and all these other point solutions have been using for automation, that's not what we use in production. And we need you to now. >> To test early and often. >> Test early and often. The challenge was the developers, the tools they use, we're not the tools that were being used on the production end of the cycle. And there was good reason for it because developers don't need something really heavy and with all the bells and whistles early in the development lifecycle. Control-M Workbench is a very light version which is targeted at developers and focuses on the needs that they have when they're building and developing as the application progresses through its life cycle. >> How much are you seeing Waterfall and then people shifting-left becoming more prominent now. What percentage of your customers have moved to Agile and shifting-left percentage wise? >> So we survey our customers on a regular basis. In the last survey showed that 80% of the customers have either implemented a more continuous integration delivery type of framework, or are in the process of doing it. And that's the other. >> And getting upfront costs as possible, a tipping point is reached. >> What is driving all of that is the need from the business, you know, the days of the five year implementation timelines are gone. This is something that you need to deliver every week, two weeks, and iteration. And we have also innovated in that space and the approach we call Jobs-as-Code where you can build entire, complex data pipelines in code formats so that you can enable the automation in a continuous integration and delivery framework. >> I have one quick question, Jim, and then I'll let you take the floor and got to learn to get a word in soon. But I have one final question on this BMC methodology thing. You guys have a history obviously BMC goes way back. Remember Max Watson CEO, and then in Palm Beach back in 97 we used to chat with him. Dominated that landscape, but we're kind of going back to a systems mindset, so the question for you is how do you view the issue of the this holy grail, the promised land of AI and machine learning. Where, you know, end-to-end visibility is really the goal, right. At the same time, you want bounded experiences at root level so automation can kick in to enable more activity. So it's a trade off between going for the end-to-end visibility out of the gate, but also having bounded visibility and data to automate. How do you guys look at that market because customers want the end-to-end promise, but they don't want to try to get there too fast as a dis-economies of scale potentially. How do you talk about that? >> And that's exactly the approach we've taken with Control-M Workbench the Community Edition. Because early on you don't need capabilities like SLA management and forecasting and automated promotion between environments. Developers want to be able to quickly build, and test and show value, OK. And they don't need something that, as you know, with all the bells and whistles. We're allowing you to handle that piece in that manner, through Control-M Workbench. As things progress, and the application progresses, the needs change as well. Now I'm closer to delivering this to the business, I need to be able to manage this within an SLA. I need to be able to manage this end-to-end and connect this other systems of record and streaming data and click stream data, all of that. So that we believe that there it doesn't have to be a trade off. That you don't have to compromise speed and quality and visibility and enterprise grade automation. >> You mention trade-offs so the Control-M Workbench the developer can use it offline, so what amount of testing can they possibly do on a complex data pipeline automation, when it's when the tool is off line? I mean it simply seems like the more development they do off line, the greater the risk that it simply won't work when they go into production. Give us a sense for how they mitigate that risk. >> Sure, we spent a lot of time observing how developers work and very early in the development stage, all they're doing is working off of their Mac or their laptop and they're not really connecting to any. And that is where they end up writing a lot of scripts because whatever code, business logic, that they've written the way they're going to make it run is by writing scripts. And that essentially becomes a problem because then you have scripts managing more scripts and as the the application progresses, you have this complex web of scripts and CRON tabs and maybe some open source solutions. trying to make, simply make, all of this run. And by doing this I don't know offline manner that doesn't mean that they're losing all of the other controlling capabilities. Simply, as the application progresses whatever automation that they've built in Control-M can seamlessly now flow into the next stage. So when you are ready take an application into production there is essentially no rework required from an automation perspective. All of that that was built can now be translated into the enterprise grade Control-M and that's where operations can then go in and add the other artifacts such as SLA management forecasting and other things that are important from an operational perspective. >> I'd like to get both your perspectives because you're like an analyst here. So Jim, I want you guys to comment, my question to both of you would be you know, looking at this time in history, obviously on the BMC side, mention some of the history. You guys are transforming on a new journey and extending that capability in this world. Jim, you're covering state of the art AI machine learning. What's your take of the space now? Strata Data which is now Hadoop World, which is, Cloudera went public, Hortonworks is now public. Kind of the big, the Hadoop guys kind of grew up, but the world has changed around them. It's not just about Hadoop anymore. So I want to get your thoughts on this kind of perspective. We're seeing a much broader picture in BigData NYC versus the Strata Hadoop, which seems to be losing steam. But, I mean, in terms of the focus, the bigger focus is much broader horizontally scalable your thoughts on the ecosystem right now. >> Let Basil answer first unless Basil wants me to go first. >> I think the reason the focus is changing is because of where the projects are in their life cycle. You know now what we're seeing is most companies are grappling with how do I take this to the next level. How do I scale, how do I go from just proving out one or two use cases to making the entire organization data driven and really inject data driven decision making in all facets of decision making. So that is, I believe, what's driving the change that we're seeing, that you know now you've gone from Strata Hadoop to being Strata Data, and focus on that element. Like I said earlier, these difference between success and failure is your ability to scale and operationalize. Take machine learning for example. >> And really it's not a hype market. Show me the meat on the bone, show me scale, I got operational concerns of security and whatnot. >> And machine learning you know that's one of the hottest topics. A recent survey I read which polled a number of data scientists, it revealed that they spent about less than 3% of their time in training the data models and about 80% of their time in data manipulation, data transformation and enrichment. That is obviously not the best use of the data scientists time, and that is exactly one of the problems we're solving for our customers around the world. >> And it needs to be automated to the hilt to help them to be more productive delivering fast results. >> Ecosystem perspective, Jim whats you thoughts? >> Yes everything that Basil said, and I'll just point out that many of the core use cases for AI are automation of the data pipeline. You know it's driving machine learning driven predictions, classifications, you know abstractions and so forth, into the data pipeline, into the application pipeline to drive results in a way that is contextually and environmentally aware of what's going on. The path, the history historical data, what's going on in terms of current streaming data to drive optimal outcomes, you know, using predictive models and so forth, in line to applications. So really, fundamentally then, what's going on is that automation is an artifact that needs to be driven into your application architecture as a re-purposeful resource for a variety of jobs. >> How would you even know what to automate? I mean that's the question. >> You're automating human judgment, your automating effort. Like the judgments that a working data engineer makes to prepare data for modeling and whatever. More and more that need can be automated because those are patterned, structured activities that have been mastered by smart people over many years. >> I mean we just had a customer on his with a glass company, GSK, with that scale, and his attitude is we see the results from the users then we double down and pay for it and automate it. So the automation question, it's a rhetorical question but this begs the question, which is you know who's writing the algorithms as machines get smarter and start throwing off their own real time data. What are you looking at, how do you determine you're going to need you machine learning for machine learning? You're going to need AI for AI? Who writes the algorithms for the algorithms? >> Automated machine learning is a hot hot, not only research focus, but we're seeing it more and more solution providers like Microsoft and Google and others, are going deep down doubling down and investments in exactly that area. That's a productivity play for data scientists. >> I think the data markets going to change radically in my opinion, so you're starting to see some things with blockchain some other things that are interesting. Data sovereignty, data governance are huge issues. Basil, just give your final thoughts for this segment as we wrap this up. Final thoughts on data and BMC, what should people know about BMC right now, because people might have a historical view of BMC. What's the latest, what should they know, what's the new Instagram picture of BMC? What should they know about you guys? >> I think what I would say people should know about BMC is that you know all the work that we've done over the last 25 years, in virtually every platform that came before Hadoop, we have now innovated to take this into things like big data and cloud platforms. So when you are choosing Control-M as a platform for automation, you are choosing a very very mature solution. An example of which is Navistar and their CIO is actually speaking at the keynote tomorrow. They've had Control-M for 15, 20 years and have automated virtually every business function through Control-M. And when they started their predictive maintenance project where there ingesting data from about 300 thousand vehicles today, to figure out when this vehicle might break and do predictive maintenance on it. When they started their journey they said that they always knew that they were going to use Control-M for it because that was the enterprise standard. And they knew that they could simply now extend that capability into this area. And when they started about three four years ago there were ingesting data from about a hundred thousand vehicles, that has now scaled over 325 thousand vehicles and they have not had to re-architect their strategy as they grow and scale. So, I would say that is one of the key messages that we are are taking to market, is that we are bringing innovation that has spanned over 25 years and evolving it. >> Modernizing it. >> Modernizing it and bringing it to newer platforms. >> Congratulations, I wouldn't call that a pivot, I'd call it an extensibility issue, kind of modernizing the core things. >> Absolutely. >> Thanks for coming and sharing the BMC perspective inside theCUBE here. On BigData NYC this is theCUBE. I'm John Furrier, Jim Kobielus here in New York City, more live coverage the three days we will be here, today, tomorrow and Thursday at BigData NYC. More coverage after this short break.

>> Announcer: Live, from Washington DC, it's the CUBE. Covering .conf2017. Brought to you by Splunk. >> And welcome back here on theCUBE. John Walls and Dave Vellante, we're in Washington DC for .conf2017, Splunk's annual get together coming up to the nation's capital for the first time. This is the eighth year for the show, and 7,000 plus attendees, 65 countries, quite a wide menu of activities going on here. We'll get into that a little bit later on. We're joined now by a couple of gentlemen, Michael Arahuleta who is the Vice President of Engineering at Atlassian, Michael, thank you for being with us. >> Thank you, actually it's Director of Business Development. >> John: Oh, Director of Business Development, my apologies >> He's doin' a great job >> My apologies. >> I don't need that. >> Oh very good. And Brooke Gravitt, who I believe is the VP of Engineering, >> There ya go. >> And the Chief Software Architect at Forty8Fifty. >> Yep, how ya doin'? >> No promotions or job assignments, I've gotcha on the right path there? >> Yeah, yeah. >> Good deal, alright. Thank you for joining us, both of you. First off, let's just set the stage a little bit for the folks watching at home, tell us a little bit about your company, descriptions, core competencies, and your responsibilities, and then we'll get into the intersection, of why the two of you are here. So Michael, why don't you lead off. >> So Atlassian, we, in our simplest form, right, we make team collaboration software. So our goal as a company is to really help make the tools that companies use to collaborate and communicate internally. Our primary focus, and kind of our bread and butter has always been making the tools that software companies use to turn around and make their software. Which is a great position to be in, and an increasingly we're seeing ourselves expand into providing that team collaboration software products like Jira, Confluence, BitBucket, and now, the new introduction of a product called Stride, which is a real time team collaboration product, not just for technical teams, but we're really seeing a great opportunity to empower all teams 'cause every team in every organization needs a better way to communicate and get things done. That's really what Atlassian core focus is all about. >> John: Gotcha. Brooke, if you would. >> Yeah, so Forty8Fifty Labs, we're the software development and DevOps focused subsidiary of Veristor Systems based out of Atlanta. We focus primarily on four key partners, which would be Atlassian, Splunk, QA Symphony, and Red Hat, and primarily, we do integrations and extensibility around products that these guys provide as well as hosting, training, and consulting on DevOps and Atlassian products. >> So the ideal state in your worlds is you've got -- true DevOps, Agile, infrastructure as code, I'll throw all the buzzwords out at ya, but essentially you're not tossing code from the development team into the operations team who them hacks the code, messes it up, points fingers, all that stuff is in part anyway what you're about eliminating, >> Right. >> And getting to value sooner. Okay, so that's the sort of end state Nirvana. Many companies struggle with that obviously, You got, what, Gartner has this term, bimodal IT, which everybody, you know, everybody criticizes but it's sort of true. You've got hybrid clouds, you've got, you know, different skillsets, what is the state of, Agile development, DevOps, where are we in terms of organizational maturity? Wonder if you guys could comment. >> I'll start with that right, I think -- Even though we've been talking about DevOps for a while and companies like Atlassian and Splunk, we live and breathe it. I still think when you look at the vast majority of enterprises, we're still at the early stages of effectively implementing this. I think we're still really bringing the right definition to what DevOps is, we're kind of go through those cycles where either a buzzword gets hot, everybody glams onto it, but no one really knows what it means. I think we're really getting into that truly understanding what DevOps means. I know we've been working hard at Atlassian to really define that strong ecosystem of partners. We really see ourselves as kind of in the middle of that DevOps lifecycle, and we integrate with so many great solutions around monitoring and logging, testing, other operational softwares, and things of that nature to really complete that DevOps lifecycle. I think we're really just now finally seeing it come together and finally starting to see even larger organizations, very large Fortune 100 companies talk about how they know they've got to get away from Waterfall, they've got to embrace Agile, and they've got to get to a true DevOps culture, and I think that's where Atlassian is very strong, devs have loved us for a long time. Operations teams are really learning to embrace Atlassian as well. I think we're really going to great position to be at that mesh of what truly is DevOps as it really emerges in the next couple years. >> Brooke, people come to Forty8Fifty, and they say, alright, teach me how to fish in the DevOps world, is that right? >> Yeah, absolutely. I mean, one of the challenges that you have in large enterprises is bringing these two groups of people together, and one of the easy ways is to go out and buy a tool, I think the harder and more difficult challenge that they face is the culture change that's required to really have a successful DevOps transformation. So we do a little bit of consulting in that area with workshops with folks like Gene Kim, Gary Gruver, Jez Humble that we bring in who are sort of industry icons for that sort of DevOps transformation. To assist, based on our experiences ourselves in previous companies or engagements with customers where we've been successful. >> So the cloud native guys, people who are doing predominantly cloud, or smaller companies, tech companies presumably, have glommed onto this, what about the sort of the Fortune 1000, the Global 2000, what are we seeing in terms of their adoption, I mean, you mentioned Waterfall before, you talk to some application development heads will say, well listen, we got to protect some of our Waterfall, because it's appropriate. What are you seeing in the sort of traditional enterprise? >> We see the traditional enterprise really embracing Agile in a very aggressive way. Obviously they wouldn't be working with Atlassian if they weren't, so our view is probably a little bit tilted. Companies that engage with us are the more open to that. But we're definitely seeing that the far and away the vast majority in the reports that we get from our partners like Forty8Fifty Labs is that increasingly larger and larger companies are really aggressively looking to embrace Agile, bring these methodologies in, and the other simple truth is with the way Atlassian sells -- the way we sell our products online, we have always sort of grown kind of bottoms up inside a lot of these large organizations, so where officially IT may still be doing something else, they're always countless smaller teams within the organization that have embraced Atlassian, are using Atlassian products, and then, a year down the road, or two years down the road, we tend to then emerge as the defacto solution for the organization after we kind of spread through all these different groups within the company. It's a great growth strategy, a lot are trying to replicate it. >> Okay, what's the Splunk angle? What do you guys do with Splunk, and how does it affect your business? >> Mike: Do you want to start? >> Sure, so, we're both a partner of Splunk, a customer of Splunk, and we use it in our own products in terms of our hosting, and support methodologies that we leverage at Forty8Fifty. We use the product day in and day out, and so with Atlassian, we have pulled together a connector that is -- one half of it is a Splunk app, it's available on Splunk base, and the other part is in the Atlassian marketplace, which allows us to send events from Juris Service Desk, ticketing events, over to Splunk to be indexed. You have a data model that ties in and allows you to get some metrics out of those events, and then the return trip is to -- based on real time searches, or alerts, or things that you have -- you're very interested in reports, you can trigger issues to be created inside of Jira. >> I think the only thing to add to that, so definitely, that's been a great relationship and partnership, and we're seeing an increasing number of our partners also become partners with Splunk and vice versa, which is great. The other strong side to this as well, is our own internal use of Splunk. So, we as a company, we always like to empower our different teams to pick whatever solution they want to use, and embrace that, and really give that authority to the individual teams. However, with logging, we were having a huge problem where all of our different teams were using over a whole host variety of different logging solutions, and frankly not to go into all the details, it was a mess. Our security team decided to embrace Splunk and start using Splunk, and really got a lot of value out of the solution and fell in love with the solution. Which says a lot, because our security team doesn't normally like much of anything, especially if it's not homegrown. That was a huge statement there, and then quickly Splunk now has spread to our cloud team which is growing rapidly as our cloud scales dramatically. Our developers are using it for troubleshooting, our SREs and our support team for incident management, and it's even spread to our marketplace, which is one of the larger marketplaces out there today for third party apps. Then the new product, Stride, for team collaboration is going to be very dependent on Splunk for logging as well. It's become that uniform fabric. I even heard a dev use a term which I've never heard a dev talk about logs and talk about log love, which is no PR, that is the direct statement from a developer, which I thought was amazing to hear. 'cause you know, they just want to code and make stuff, they don't want to deal when it actually breaks and have to fix it. But with Splunk they've actually -- They're telling me they actually enjoy that. So that's a great -- >> That's more than the answer is in the logs, that's there's value in our logs, right? >> Yeah, a ton of value, right? Because at the end of the day, these alerts are coming in and then we use tools like the Forty8Fifty Labs tool to get those tickets into Jira. Those logs and things are coming in, that means there's an issue and there's something to be resolved and there's customer pain. So the quicker we can resolve that, that log is that first indicator of what's going on in the cloud and in our platforms to help us figure out how do we keep that customer happy? This isn't just work, and just a task, this is about delivering customer value and that log can be that first indicator. The sooner you can get something resolved, the sooner the customer's back to getting stuff done and that's really our focus as a company, right? How do we enable people to get things done? >> Excuse me, when you are talking about your customers, what are their pain points? Today? I mean, big data's getting bigger and more capabilities, you've got all kinds of transport problems and storage problems, and security problems, so what are the pain points for the people who are just trying to get up to speed, trying to get into the game, and that the kind of services you're trying to bring to them to open their eyes. >> I think if you look at the value stream mapping and time to market for most businesses, where Splunk and Atlassian play in is getting that fast feedback. The closer in to the development side, the left hand side of value stream that you can pull in, key metrics, and get an understanding of where issues are, that actually -- it's much less expensive to fix problems in development than when they're in production, obviously. Rolling things like Splunk that can be used as a SIM to do some security analysis on, whether it be product code or business process early, rather than end up with a data breach or finding something after it's already in production. That kind of stuff, those are the challenges that a lot of the companies are facing is -- especially when the news, if you look at all the things that are goin on from a security perspective, taking these two products and being able to detect things that are going on, trends, any sort of unusual activity, and immediately having that come back for somebody in a service desk to work on either as a security incident or if it's a developer finding a bug early in the lifecycle, and augmenting your sort of infrastructure as code, the build out of the infrastructure itself. Being able to log all that data, and look at the metrics around that to help you build more robust enterprise class platforms for your teams. >> We've been sort of joking earlier about how the big data, nobody really talks about big data anymore, interestingly, Splunk who used to never talk about big data is now talking about big data, cause they're kind of living it. It's almost like same wine, new bottle with machine learning and AI and deep learning are all kind of the new big data buzzwords, but my question is, as practitioners, you were describing a situation where you can sort of identify a problem, maybe get an alert, and then manually I guess remediate that problem, how far away are we from -- so the machines automating that remediation? Thoughts on that? >> Am I first up? >> You guys kind of -- >> We've done a lot of automated remdediation. Close with remediation is what you call it. The big challenge is, it's a multi-disciplinary effort, so you might have folks that need to have expertise between network and systems and the application stack, maybe load balancing. There's a lot of different pieces there, so step one is you got to have folks that have the capacity to actually create the automation for their domain of expertise, and then you need to have sort of that cross platform DevOps mindset of being able to pull that together and the coordinator role of let's orchastrate all of the automations, and then hopefully out of that, combined with machine learning, some of the stuff that you can do in AWS, or with IBM's got out. You can take some of that analysis and be a little bit smarter about running the automation. In terms of whether that's scaling things up, or when -- For example, if you're in a financial industry and you've got a webpage that people are doing bill pay for, if you have a single website down, a web server down, out of a farm of 1000, in a traditional NOC, that would be kind of red on a dashboard. It's high, it's low priority, but it's high visibility and it's just noise, and so leveraging machine learning, people do that in Splunk to really refine what actually shows up in the NOC, that's something I think is compelling to customers. >> How are devs dealing with complexity, obviously, collaboration tools help, but I mean, the level of complexity today, versus when you think back to client server, is orders of magnitude greater for admins and developers, now you got to throw in containers and microservices, and the amount of data, is the industry keeping pace with the pace of escalation of complexity, and if so, how? >> I think we're trying. I think that's where we come into play. As this complexity increases really the only way you can solve it is through better communication and better tools to make sure that teams have the right information at their fingertips. The other challenge too is now in the world of the cloud, these teams need to be on 24/7. But you've got to kind of roll across the globe, and have your support teams in different time zones. You don't always have the right people online at the same time to be able to address, and you can't always talk directly, so that's where having the right tools and processes in place are extremely important so that team can know and know what did the team earlier do, how did they resolve this, where's the run book for this issue, and if this happens, how do we resolve it? How do we do so quickly? I think that tooling is key, and also too, this complexity is also as you guys were talking about before, being solved through some automation as well, and we're increasingly seeing that to where if this occurs and a certain thing occurs, then Jira can now automatically start to trigger some things for you, and then report back as to what it did. You're going to see more and more of that going forward as these models become more intelligent and we can redeploy, or if capacity is low, let's pull back resources, and let's not spend all this money on cloud computing platforms that we may not need because utilization is low. You're seeing all of those things start to happen and Jira as that workflow engine is that engine that's making those things happen in either an automated way at times, or just enabling people to communicate and do things in a very logical fashion. >> As ecosystem partners, how do you view the evolution of Splunk, is it becoming a application platform for you? Are you concerned about swim lanes? I wonder if you could talk about that? >> I personally, I don't see any real concerns of overlap between Splunk and Atlassian. In our view at Atlassian is, we tend to work very closely with people kind of fit into that frenemy category, and they're definitely a partner that we overlap with I think in very very few ways. If and when we ever do, I mean in a way, that's kind of something we always embrace as a company. I mean one thing we'll say a lot is overlap is better than a gap. Because if there's a gap between us and a partner, then that's going to result in customer pain. That means there's nothing that's filling that void. I'd rather have some overlap, and then give the customer the power to choose how do they want to do it. I mean, Splunk says you can probably do it this way, Atlassian says you could do it this way, as long as they can get stuff done, and that's always -- it's not a cliche from us, I mean that's a core message from Atlassian, then we're happy. Regardless if they completely embrace it our way, a little bit, a little deviation, that's not what really matters. >> Too much better than too little. >> Exactly. >> Is what it comes down to. Gentlemen, thanks for being with us. >> Thank you. >> We appreciate the time today and look forward to seeing you down the road and looking as your relationship continues. Not only between the two companies, but with Splunk as well. Thanks for being here. >> Mike: Thank you guys. >> We continue theCUBE does, live from Washington DC here at .conf2017, back with more in just a bit.

(upbeat music) >> Commentator: Live, from Orlando, Florida, it's theCUBE, covering ServiceNow Knowledge17, brought to you by ServiceNow. >> Hi everybody, welcome back to Knowledge17. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante, and I'm with my co-host Jeff Frick at our fifth Knowledge. We go out to the events. We extract the signal from the noise. Seneca Louck is here, he's the Business Process Lead at Dow Chemical. A relatively new ServiceNow customer. Welcome to theCUBE, thanks for coming on. >> Thank you guys. >> Thanks for having me. >> So you said this is your second Knowledge. >> Seneca: It is. >> And, well how do you like Orlando? >> I like it, I like it. I'm here, in Venetian, >> Sunny? >> for next year, and so I'm a Vegas guy, so I'll be happy to get back there, but Orlando's nice. >> Dave: Where's home for you? >> Originally from New Jersey. Worked in Philadelphia for 15 years and relocated to Midland, Michigan, where Dow Chemical's headquartered. >> Dave: Fantastic, ah it's great, great country, Michigan. >> Absolutely. >> So, take us through your role, start there. What do you do, >> Sure. >> at Dow Chemical? >> So, I'm a Business Process Lead for Enterprise Service Management. We could go down the ITSM route, or we can go down the BSM route and we said, "Why pick one?" Enterprise Systems Management used to be the name. We actually elevated it up, Enterprise Service Management. We're the IT Operability focus on the end. >> Okay, and you said you went live, with ServiceNow, June last year? >> June 11th last year, we started with Incident Problem Change Config. We did Change Management, sorry, a month later. And then we did Service Request catalog, rolled out for the whole rest of the year. >> How long did it take you from sort of, when you said, "All right, we're doing this. "Start the project." To actually get, you know, MVP out? >> The cake. >> Yeah, the cake. (laughs) >> To get to the cake. >> And MVP's a really important thing. Minimum Viable Product. It was a hard lesson for us to learn. Quickly we realized that we're not going to be able to do everything we want to do in a first shot. So, we did focus very heavily on MVP. ServiceNow was good enough to make sure that they bred that into us, the importance of that. And so, we started in October, with workshops. We spent probably the first four or five months before we wrote one single line of code or configured one thing in ServiceNow. You know, a lot of that work was As-Is Process. Document it, understand it, uplift it, figure out what we want that To-Be Process to look like, and then figure out how the tool's going to deliver against that. >> Did you do some of that, I mean much of that came as part of the business case, and then you just refined it, is that right? >> The business case was really more on the value side. We didn't get into the specifics around process. We had a high level idea what we wanted to do strategically. Right? >> Yeah. >> Our guiding principles were really, Industry Best Practice, we like to think we're special. But really, the industry should know. Out of the box, ServiceNow, whenever possible. And to be honest, the out-of-the-box ServiceNow should reflect Industry Best Practice fairly well. And so that was kind of the coming in position for us. We deviated only when absolutely necessary and we really tried to stick to vanilla. >> So you minimized custom mods? >> Seneca: We really tried to do that, yes. There's times where we had to deviate of course. But we really wanted to look to see if ServiceNow had an answer, and if we could tweak what was already there, then great. There's only a handful of opportunities where we had to build something net new. >> And was that related to your ERP, or when did you have to build those custom mods? >> So, in places where we might have a concept that was to bring Legacy capability from a previous system. We knew we weren't going to cut and run from the old to the new. We had to kind of pull on some of the capabilities of that platform. So, the way you guys do category, sub-category, we did through classification. And so we had to customize a couple of tables to bring classifications over to bridge that gap. >> I see, okay, and then, so then you go live. Now was it a CMDB, a single CMDB across the organization? >> So, we have HP technology, where we had large investment. We wanted to keep that for discovery purposes and it enabled us to build one big tunnel between our CMDB and ServiceNow, so it made the integration go very easily. So, we really did two key integrations, a CMDB integration and an LDAP one to get our people data. Once that was done, we were on our feet, we were stood up and we were ready to start delivering processes. >> And the Service Catalog? >> Service Catalog was an interesting one because we had it spread out in a bunch of places. We had web forums, where somebody had customized a small, little web forum that that was actually making calls into our ticketing system to create service requests. We also had Request Center, which was brought in to try and solve that world of Service Request Management, but it only did it for Service Request. And we realize ServiceNow is going to do it end-to-end. >> Seneca, when you're thinking about your investments. I like to look at 'em as you get investments to run the business, some to grow the business and some to transform the business. And you're really sort of an IT-transform expert. How do you allocate that? Are those mutually exclusive? Do they sort of blend into each other and how much of your investment is transformation, and what does that all mean? >> Yeah, so it's tough because you've got guys that are on the run side, and I actually spent the large majority of my career on the run side. So, I know what if feels like to be accountable for everything in production, regardless of how it got there. And so, I kind of oscillate back and forth. Right? If the hair's on fire and these guys are going to be dead by the time the project transforms next year's capability, there's no point in us waiting. We can't wait. So, we're bouncing in and out of transformation and dealing with, making sure operability can happen effectively, efficiently, and that these guys are around next year, and alive and well, so that we can deliver that transformational capability. >> You talked about MVP being kind of a new concept. I wonder if you could dig into that a little bit further. >> Sure, sure. >> Is that not kind of a process or methodology that you guys have done in the past, or was it a learning curve? >> So, it was a little bit of a learning curve. So, typically you know, we delivered the biggest SAP implementation in the history of the world. A billion dollars, 800 SAP systems. And it took us seven years. So, we didn't think a lot about MVP, we wanted perfection. And so we made sure that we got it. And it cost us dearly. But in the end, the results were good. In this case, we had to move fast. Right? We weren't going to be able to do it all. We knew the capabilities that you see, throughout this room, are incredible. We want to get to them. But we've got to get on to the platform first. And so, we really did hone in on trying to find, what is the minimum product that we need to get people moved over to the platform, and we'll increment from there. So, it was a little bit of a learning for us. It was a little bit of a culture change. And we kind of found that sweet spot between Agile and Waterfall, which I think we called it Wagile, or (laughs). Yeah, Wagile I think, >> Well, right. >> is the name. >> I mean your implementation >> coincided with the sort of DevOps craze, and Agile, but there's >> That's right, that's right. >> a place for Waterfall, right? >> There is, there is. >> Sometimes, you need >> that perfection. Other times, you need to break stuff and iterate. >> Absolutely. >> But so, that's interesting. You said you came up with sort of a hybrid. Sometimes, hybrids are scary. So, how did you sort of come to that point and how's it workin' for you? >> Yeah, so what we did is we front-ended a lot of the requirements. We spent, like I said, several months, just sitting and doing requirements. And then, we transitioned into two-week sprints. And we pulled out of the backlog, the requirements that we had captured in those months previous. So, that was kind of how we blended the two together. We're more a Waterfall shop but we were delivering a system of record. And so, in systems of record, we strongly believe that Agile can be dangerous. It's not necessarily the place to start. And so, we started with Waterfall, and we kind of ended with Agile. >> All right, okay, and so, what so far have been the sort of business impacts? Can you share that with us? >> Yeah absolutely, so first thing's first, we're getting consistency throughout our processes. So, many times, geographical differences or even within a geography, at a sub-activity level, people were doing things differently. So, first thing we had to do was Standardize Process. That gives us the ability to measure across the world, how that process is being executed. Whereas before, we couldn't do that one-for-one, we couldn't compare these things one-for-one. And so, now we have that vision, now we have that visibility, and we were a performance analytics customer from day one, so we started capturing data to baseline, to benchmark, from Go Live, until today, and we've got incredible data to go back then and do the continuous service improvement. >> And how much of the consistency and process was forced in your pre-deployment activities, where you kind of find, all right, we got to sit down and actually document this to put it into the system. Versus, now that you've got this tool in place, that you see the opportunity to continue to go after new processes. >> It varied, dependent upon area, so Change Management was actually not a bad process from a global perspective. On the flip side is, we actually implemented some case management capability for our Business Functions. Their processes were extremely deviated across geographies, across activities. And so it depends, but the bottom line is that before we talk about implementing on this platform, we got to talk standardization. Good news is the incident problem changed. It wasn't as much work. On the Business Process side, it was a lot more. >> How are you predominantly measured? Is it getting stuff done? Are there other sort of KPI's that you focus on? Is there one that you try to optimize? >> So, these days, we're actually operating in a little bit of a dangerous place because we're going through so much mergers and acquisition activity, that our success is, can we integrate a company in less than a year while we go on to do the biggest chemical merger in the history of the world? So, typically, we would be kind of looking at metrics, and KPI's, down at the process level. Right now, we're looking at, can I actually bring these companies together? So it's integrated. >> And not kill each other. >> And not kill each other. (laughs) That's right. That's not to say we're not doing the latter as well but I think we have to start with, can we get the big activities done so that we can figure out how to do the process improvement. >> Dave: Right. How about the show for you here? What's it been like? What are you learning? >> Yeah, so. >> Are you sharing? >> Dx Continuum I think is going to be the theme that I'm going to leave here thinking, wow, these guys did the right thing with that purchase. So, you know the artificial intelligence, the machine learning, the data lakes, that we're going to be able to take all this data that we have and pump it out to you guys. And you're going to turn around and tell us an interesting story. You're going to tell me the questions that I would never even think to ask because you're going to be able to see into that data in ways that we never even dreamed possible. So, that's the big one for me. I've heard some rumors of some other things coming, but I shouldn't know about those and so I'm not going to say anything at this point. But right now, it's about the machine learning, the artificial intelligence. >> So, what other, I mean 'cause a company the size of Dow must be doing some interesting things with Big Data and Hadoop and AI. How does what you're doing or does what you're doing with ServiceNow relate to those sort of other activities? Is there sort of a data platform strategy? >> It's an interesting question. It's something that we're actually struggling with a little bit to figure out what that strategy is going to be. I don't think the larger organization expected so many opportunities to use analytics and to use machine learning against data sets that otherwise were, this is operation stuff, for the most part, right? We're starting to get into the business side a little bit but really, we were focused on running the business from an operations perspective. And so, all of a sudden, now, we're getting attention that we wouldn't have had otherwise, from the big players, you know. The SAP Business Warehouse, Business Intelligence guys. They've got 120 people delivering their reporting service. I got a guy half-time, that's helping me with my PA reports and we've got to figure out a way to either join our strategies together or at least meet in the middle because there's data that we probably want to share from each other. >> Do you have a Chief Data Officer on staff? >> We do not, that I'm aware of, actually. But I think it is , it's a very powerful role, but in our SAP world, they kind of act as that defacto person within our organization. But they're not very interested in what we're doing yet but they are starting to get the attention of us. >> It's interesting 'cause we talk a lot about IoT Now will bridge, you know, kind of the IT and the Ops folks. And it sounds like you're having that experience really specifically built around some of the processes that you're delivering in ServiceNow. To bring those two world together. >> Yeah, so while I mentioned machine learning and Artificial Intellience, that's actually right there, second on my list. The thing I came here last year and raised my hands and said I need the most is I need the ability to bring massive amounts of data onto this platform. Raw performance data, network data, server data, utilization data, end-user data. I want to be able to bring it into this platform so that I can use it to correlate events and incidents and problems. And so, the things that you guys are doing for IoT, to bring massive data sets in, are actually going to solve my problem, but I don't think it was necessarily what you were trying to solve. But I'm very happy for that. >> So, by the way, we're independent media, so we're (laughs) like third-party guys. >> Understood, understood >> It's these guys, ServiceNow. So, we just sort of unpack, analyze. What about if you had to do it again. What would you do differently? Obviously you would have, and you did, you embraced the MVP, other things? >> So, we took a very dangerous route in that we didn't have a team built. We didn't have a competency built. We took a system integrator and we went off and we went hog wild and we implemented it quickly, while we built the team, while we built the governance, while we built the competency center. If I could do it again, I'd have that team ready, staffed, you know, well-trained up front, so that we could learn as we went, a little bit more, be a little more autonomous and self-sufficient. >> Were you one of the 100 customers that John Donahoe met with in 45 days? >> I was not actually. >> And if you weren't, then what would you tell him in terms of the piece that he said, "What can we do better?" What would you? >> Yeah. >> So, the question came up yesterday, around releases. You know, should we do more, should we do less. I mean, we're actually struggling a little bit to keep up with the two releases per year. So, the biggest thing that I see is not making it a wholesale upgrade. If I could take parts and pieces from the new capabilities that are coming without having to go through the full upgrade cycle, you know, I think that would be huge for me. So that we don't have to spend a couple of months or we're hoping to get that down to one month. But this is our first one in production. So, we're going to spend three months getting this upgrade right. We're hoping to get it down to, you know, a couple of weeks to a month. But if I can take pieces and parts of the capability that's being delivered, and not have to take it wholesale, that would be the thing. >> Yeah, so that's interesting because Multi-instance is nice. You don't have to go on the SaaS player's schedule. But you want to keep current, you know, for a lot of reasons, with maybe, with certain parts of the upgrade. Yeah, okay, that doesn't sound trivial. (laughs) >> Yeah, it's not. >> Although I know they're thinking about it so it's come up, I've heard a couple of people at least mention that it's something that they have to think about. They may not actually go that direction. But at least that they're thinking about it, that tells me that they're exploring other avenues to deliver capability. >> Dave: What's in the future for you guys? Where do you want to take this thing? >> Yeah, so our next big thing's going to be Event Management. So, we've got 45 different tools that are doing monitoring from purchase tools to somebody's script that's sitting on the mainframe that sends us an event, when some exception happens. And so we've built, you know, with a custom IT process automation tool, our Event Management framework. And it's integrated with ServiceNow. But at the heart of it is, there's some old technology, decade-old technology, that was my first entry into IT process automation. And so, as the person who built it, I'm going to be the one that ultimately unplugs it and hands it over to ServiceNow. So, for us, that's the next step for what we're going to do. >> Awesome, well listen, Seneca, thanks very much for coming to theCUBE. It's great to have you. Loved the knowledge. >> Thanks for having us. >> Dave: Rapid fire, you know, perfect for theCUBE, so thank you. >> Great, wonderful. >> Thank you, guys. >> Thanks for coming on. >> I appreciate it. >> All right, pleasure. >> All right, keep it right there, buddy. We'll be back with our next guest. This is theCUBE, we're live from Knowledge17 in Orlando. We'll be right back. (upbeat music)

>> Narrator: Live from Las Vegas, it's theCUBE, covering Oracle Modern Customer Experience 2017. Brought to you by Oracle. >> Okay, welcome back here. We're here live in Las Vegas. This is SiliconANGLE Media's theCUBE. It's our flagship program. We go out to the events and extract the signal from the noise, talk to the influencers, the experts, thought leaders, CEOs, entrepreneurs, anyone we can that has data we can share with you. I'm John Furrier, Peter Burr is my co-host for the two days here. Our next is Jay Baer from Convince and Convert, CUBE alumni, great guy, super influential, knows his marketing stuff, perfect guest to summarize and kind of package up what the hell Modern CX means here at the Oracle show. Welcome back, good to see you. >> Jay: Good to see you guys, welcome. >> So you were hosting the CMO Summit that was going on in parallel they had the Marquise Awards which is their awards dinner. >> 11th annual Marquise Awards it's like a thing. >> It's amazing, it looked like the Golden Globes. >> It was beautiful this year, it was like, legit. >> Peter: Is that the one with the O on the top? >> And they delivered an award with a drone. It was a great night. >> Awesome stuff. So give us the package, what's going on, tease out the story here. >> Yeah, I think the story is two-fold. One, Oracle's got an interesting take on the marketing software space because they really are trying to connect it between the overall customer service experience initiative, and then marketing as a piece of that. This event in particular, the Modern Customer Experience event has tracked almost full conferences for marketing, for customer service, for sales and for commerce. So all four of those are the verticals underneath this umbrella and that's a really unusual conference setup but I think it reflects where Oracle's head is at from a thought leadership standpoint. That like, look, maybe were going to get to a point where marketing and customer service really are kind of the same. Maybe we're going to get to the point where sales and marketing really are kind of the same. We're not there yet, by any stretch of the imagination. But I think we all feel that convergence coming. And my world the marketing side, CMO's are starting to get more and more responsibility inside organizations and so if that happens, maybe we do need to start to align the software as well. It's and interesting take on the market, and I think it's sort of prescient for where we're going to head. >> It's interesting you mention of all those different silos, or different departments or different functions in a digital end-to-end fabric experiences are all about the customer, it's one person, they're going to have different experiences at any given time on that life cycle, or product spectrum or solution spectrum. So the CMO has to take responsibility of that. >> Well, I feel like somebody has to be responsible for it. Mark Hurd said this in one of his remarks over the course of the show, the CEO of Oracle said look, there is no data department, everybody has to be responsible for data but somebody has to figure what the ins and the outs are and maybe that's the CMO, maybe it's the CXO, I don't think we've fully baked that cake yet. But we're going to have to get to the point where the single record of truth about the customer and their customer journey has to exist and somebody's got to figure out how to wire all those together. We're gettin' there. >> It's so funny, I was joking, not here on theCUBE, but in the hallways about the United Airlines snafu and I'm like, to me as a kind of a developer mindset software should have solved that problem. They never should have been overbooked to begin with. So if you think about just these things where the reality of a consumer at any given time is based upon their situation. I need customer support, I need this, I need that. So everyone's got to be customer ready with data. >> Talk about relevance, relevancy is the killer app, that's it, right. Relevancy is created by technology, and with people, people who actually know how to put that technology into practice in a way that the customers actually care about. So, one of the things that Mark said, he said look, here's the issue, it's not about data, nor is it about clout, it's not about any of that. It's about taking that data and creating understanding out of it. But he said a really interesting thing, he said what we have to do is push those understandings out to the front lines where somebody on the front lines can do something with it that actually benefits the customer. I think that's a really smart point because so often right now we're talking about, oh we've got these data stores, and we've got DMP's and we've got all these things. That's great but until that gets manifested at the front lines, who cares, you've just got a big pile of numbers. >> We had Katrina on from the commerce side, it's funny, she was making a retail comment look, they don't care about the tech, they don't care about blockchain and all the speed and feed, they have to do a transaction in the speak of the consumer. And the language of the customer is not technology. >> No they don't care, solve my problem right. Just solve my problem, and I don't care how you solve it, what sort of magic you have behind the scenes, if I want a sweater, I want this sweater, and I want it right now. >> OK, Jay, share with the audience watching right now and us conversation hallways you've had, that's always the best because you had a chance, I'll see ya on the big stage doing your hosting thing, but also you get approached a lot people bend your ear a lot, what's happening? >> You know what's been an interesting theme this week is we've made such great advances on the technology side and I think we're starting to bump up against okay well now we've got to make some organizational changes for that technology to actually flourish. Had a lot of conversations this week with influencers, with CMO's, with attendees about, I really want to do this I really want to sort of bring sales and marketing together or commerce and sales, et cetera. But our org chart doesn't support that. The way our company thinks, the way our people are aligned, does not support this convergence. So I think were it an inflection point where we're going to have to like break apart some silos, and not data silos, but operational, what is your job, who manages you and what is your bonus based on? There is a lot of legacy structures, especially at the enterprise that do not really facilitate. >> John: Agile. >> Cross-departmental circumstances that we're looking for. So a lot people are like, oh wow, we're going to have to do some robust organizational change and that ain't easy. Somebody's going to have to drive that. Your marketing practitioners, which is my world, they can't drive that. That's got to come from up here somewhere. >> And also people got to be ready for the change. No one likes change. But we were taking about this yesterday called Add the Agile process into development being applied to marketing, really smart. >> Oh, all the time so many marketing teams now are using Agile and daily Scrum and Stand-ups and all those kind of things as opposed to Waterfall which everybody's used forever I think it's fantastic. >> Yeah, and that's something that we're seeing and Roland Smart had to point, he had a book got a signed copy Peter and I, but this is interesting, if you of Agile, to your point, you just can't read the book you've got to have a commit to it, organizational impact is Agile. >> One of the things we had a CMO Summit, we had 125, 150 CMO's from all around the world and one of the things we talked about in that session yesterday was, jeeze, we need to start taking people or hiring people out of a software development world, people who have Agile experience and put them as PM's on a marketing team. Which is going to put that group of people have the Agile background in even greater demand. Because they won't just be doing tech roles for project management but also marketing project management and sort of teaching everybody how Agile works. I think it's really interesting. >> But they've been doing that for a while. I mean the Agile, Agile started in software development but moved broader than that when it went to the web. >> No question, but a lot of these CMO's do not have those type of skills on their team today. They're still using a Waterfall. >> Or they don't recognize that they have the skills. Because most of them will have responsibility for website, website development, so it's that they don't again, it goes back to. >> Web versus marketing. >> Yeah, they probably have it somewhere, they just don't appreciate it and elevate it. >> It's silo'd within the marketing team. >> It's silo'd within the marketing team. So there's going to be, these are the consequence of changes. We'll see the degree to which it really requires a whole bunch of organizational stuff. But at the end of the day, you're right, it's a very very important thing. What are some of the other things you see as long as we're talking about it, other than just organizational. >> Actual other sort of baseline skills. It wasn't that long ago that your social media teams and contact marketing teams, it was manifestly a written job you made things that were rooted in copy. Now we talked a lot about, you have to have like a full video team on your marketing org chart because the core of the realm now is video content and while companies are getting there it's still a struggle for a lot of them. Should we have our agency do this, should we get somebody else to do it, they're like now I got to have all these people, I got to have video editors and camera crew. >> It's expensive. >> Of course it is, yeah. Not everybody can be theCUBE. >> We'll they're tryin'. No, but I think video's been coming down to the camera level you see Facebook with VR and AR certainly the glam and the sex appeal to that. Then you got docker containers and software development apps, so I call that the app culture, you've got the glam, apps, and then you've got cloud. So those things are going on so are the marketing departments looking to fully integrate agency-like stuff in house or is the agency picking up that? What's your take on the landscape of video and some of these services? >> It depends on how real-time they're thinking about video. We're starting to Facebook Live in a public relations circumstance. You saw when Crayola announced the death of the blue crayon or whatever it was a few weeks ago. They did a press release on that, but the real impetus for that announcement was a Facebook Live video. Which puts Facebook and live video as your new PR apparatus. That's really interesting. So in those circumstances the question is do we do that with the agency, is it easier to do it in-house. I think ultimately my advice would be you have to have it in both places. You have to be able to do at least some things in-house you have to be able to turn it quickly and then maybe for things you have more a lead time, you bring in your agency. >> One of the things we're seeing and just commenting while we're on this great subject, it's our business as well, is content is hard. Good, original content is what we strive for as SiliconANGLE, wikibon and theCUBE is something that we're committed to serving the audience at the same time, we collaborate with marketers in this new, native way so that the challenge that I see, and I see in this marketing cloud, is content is a great piece of data. >> Content is data. >> Content is data. >> And it also helps you get more data because there is a lot of data exchanged. >> So a lot of companies I see that fail on the content marketing side, they don't punch it in the red zone. The ball's on the one yard line all they got to do is get it over the goal line, and that's good content, and they try to fake it. They don't have authentic content. >> Another way of saying that John. >> John: They blew it on the one yard line. >> Yeah, another way of saying that is the historically agencies have driven the notion of production value. They have driven the notion of production value, to make the content as expensive as possible because that's how they make their money. What we're talking about is when we introduce a CX orientation into this mix now we're talking about what does the customer need in context, how can video serve that need? It's going to lead to, potentially, a very very different set of production value. >> You bring up a good point, I want to get Jay's reaction on it because he sees a lot too. Context is everything so at the end of the day what is engaging, you can't buy engagement, it's got to be good. >> What serves the customer. >> John: And that is defined by the customer, there is nature of reality silver bullet there's no engagement bullet. >> Sometimes you can argue that the customer values a lower fidelity content execution because it has a greater perceived authenticity. >> You may not know this Jay, I'm going to promote us for a second. A piece of video that's highly produced in the technology industry generates attention for a minute and a half to a minute and 45 seconds. theCUBE can keep attention for 12 or 13 minutes, why? >> John: We have interesting people on. >> If we were a digital agency. >> I would say the hosts, obviously. >> The hosts, the conversation. >> It's back to relevancy. >> It informs the customer. And that's what, increasingly, these guys have to think about. So in may respects, we'll go back to your organization and I want to test you in this, is that in many respects that the CMO must heal thyself first. By starting to acknowledge that we have to focus on the customer, and not creative and not the agency, and rejigger things so that we can in fact focus on the customer and not the agency's needs for us to spend more. >> There was, one of the great conversations in the CMO Summit was this point that, look, with all this technology we have all the opportunities and darnit, all we're doing is finding other ways to send people a coupon. Like isn't there something else that we could use this technology for. And what if we just flip the script and said what do customers genuinely want? Which is knowable and certainly inferable today in a way that has never been historically why don't we use that data to give them what they want, when they want it, how they want it, instead of constantly trying to push them harder. >> Focus on value and not being annoying. >> I mean I wrote a while book about it. >> Well your key point there, is that you're going to infer and actually get signals that, we've never been there before. Chatter signals. >> But let's use them for good not evil I think is the subtext there. >> Yeah, don't jam a coupon down their throat. >> But as Mark says it's hard because CEO's are under tremendous pressure to raise top line in an environment that is not conducive to that. You're going to have to take share. The economy is not growing so fast that you can just show up and grow your company. CEO's have tons of pressure, they're then droppping that pressure on the CMO who then says you need to grow top line revenue. So the CMO says we've got all this technology I guess we'll just send out more offers we'll have a stronger call to action and as opposed to using this information, the inferences, the data, to be more customer focused. I think in some cases we're being less customer focused which, if anything is short-sighted and at worst is a cryin' shame. >> So the solution there is to use the data to craft relevant things at the right time to the right people. >> And it will work but it requires two things that a lot of organizations simply don't have. Time and courage, right. It requires time and courage to purposely push less hard. Because you know it will payoff eventually you've got to buy into that, and that ain't easy always. Sometimes it's not even your decision. >> What we don't want is we don't want to automate and accelerate bad practices. At the end of the day what CMO's are learning, this conversation came out yesterday is, jeeze maybe marketing really isn't that good. Maybe we have to learn ourselves from what this technology is telling us, what the data is telling us and start dramatically altering the way we think about marketing, the role that marketing plays. The techniques we use, the tactics we use, that will lead to organizational changes. I'm wondering, did you get a sense out of the session that they are in fact stepping back and saying we got to look in the mirror about some of this stuff. >> Absolutely, absolutely. I thought it was remarkable, considering who runs this company, Mark Hurd, came in and did a little Q&A at the CMO Summit and he said, And this is the guy who runs Oracle, who's puttin' this who thing together and is sellin' tons of marketing software and says look guys, I'm not even sure if what we're doing here is right because we've got all this technology we have been doing this for a long time, we've got all these smart people and still, what's our conversion rate, 1%? If we've got the greatest technology in the history of the world, we supposedly know all this about customer service and customer journey mapping and our conversion rate is still 1%. Maybe something identified fundamentally broken with how we think about marketing. I thought for somebody in that role to come in and just drop that on a group of CMO's, I was like whoa. >> I think he's right. >> Totally right. >> But to have a CEO of a company like this just walk in and say here's what I think. >> This is a question for you and I'll ask it by saying we try to observe progressive CMO's as a leading indicator to the comment you mentioned earlier, which is flip things upside down and see what happens. What are you seeing for those progressive CMO's that have the courage to say ya know what, we're going to flip things upside down and apply the technology and rethink it in a way that's different. What are they doing? >> One of the markers that we see on the consulting side of my business is CMO's who are thinking about retention first. Not only from a practical execution layer, but even from a strategic layer. Like, what if we just pulled back on the string here a little bit and just said how can we make sure that everyone who's already given us money, continues to give us money and moreso. And essentially really turn the marketing focus from a new customer model, to a customer retention and customer growth model, start there. Start with your current customers and then use those inisights gained and then do a better job with customer acquisition. As customer service and marketing start to converge, mostly because on online. Online customer service is very brand driven and more like marketing. As this two things are converging we're seeing smart CMO's say well what if we change the way we look at this and took care of our own first. Learn those lessons and then applied them outwardly. I think that's a real strong marking signal. >> It's a great starting point and it's almost risk free from a progressive standpoint. >> It's not always risk-free inside the organization. >> I mean it's harder to get new guinea pig customers to like see what works, but go to your existing customers and you have data to work with. >> But wouldn't you also say that the very nature of digital which is moving the value proposition from an intrinsic statement of the values in the product and caveat emptor, towards a utility orientation where the value's in the use of it, and we want to sustain use of it. We're moving more to a service to do that and digital helps us to do that. That the risk of taking your approach goes down because at the end of the day, when you're doing a service orientation you have to retain the customer because the customer has constantly got the opportunity to abandon you. >> Yes the ability to bail out is very very easy these days I completely agree. But what find is that it makes sense to us. It makes sense to us on theCUBE, but in the real world it's not. Not everybody's drinkin' that punch yet. >> John: And why? >> I don't know. >> Sounds like courage. >> It is definitely courage is one of 'em because you're essentially saying look, I've been taught to do marketing one way for 40 years or 20 years. >> Yeah, I'm going to lean on my email marketing all day long. >> Yeah, I'm going to keep pressing send. It's easy, there's almost no net cost. So there's that. And also just the pressure from above, I think. From the CEO to grow top line, net new customer revenue, I think that's certainly part of it. And some if it, I think we went back to earlier about org charting and skills and resources. There's a heck of a lot more people out there at every level of the marketing organization who are trained in customer acquisition moreso than customer retention. How many MBA's are there in customer retention are there? Zero. How many MBA's are there in marketing and sales? >> Lot of 'em at Amazon. >> A thousand? >> A lot of 'em at Apple. >> Yeah, but they were trained there. They didn't come in like that, so they trained them up. >> Jay, great to have you on theCUBE. Great insight as usual, and I think you're right on the money. I think the theme that I would just say for this show, and agree with you is that if you look at Oracle, you look at IBM, you look what Amazon is doing Microsoft in some way maybe a little bit, but those three, data's at the center of the value proposition. Oracle is clearly saying to the marketers, at least we want to say digital it's end to end if you use data, it's good for you. This is the new direction. If you think data-driven CMO, that seems to be the right strategy in my mind. >> The best quote in the CMO Summit, you guys need a CUBE bumper sticker that you can manufacture with this. Data is the new bacon. I was like, oh I love that, that's the best right. >> Who doesn't love bacon. Jay, great to see you. Real quick, what's up with you, give us a quick update on you're opportunities what you're going these days. >> Things are great, running around the country doing fantastic events just like you guys are. Working on a new content marketing master class for advanced marketers on how to take their content marketing strategy to the next level. That launches in a couple of weeks. Continue to do four or five podcasts a week, a new video show called Jay Today where I do little short snippets three minutes a day. JayToday.tv if you want to subscribe to that. >> Beautiful, Jay Baer, great on theCUBE great thought leader, great practitioner, and just a great sharer on the net, check him out. I'm John Furrier with Peter Burr here at Oracle Marketing CX more live coverage after this short break.

>> Hello, Wikibon community, and welcome to our 2017 predictions for the technology industry. We're very excited to be able to do this, today. This is one of the first times that Wikibon has undertaken something like this. I've been here since about April, 2016, and it's certainly the first time that I've been part of a gathering like this, with so many members of the Wikibon community. Today I'm joined with, or joined by, Dave Vellante, who's our co-CEO. So I'm the Chief Research Officer, here, and you can see me there on the left, that you can see this is from our being on TheCube at big data, New York City, this past September, and there's Dave on the right-hand side. Dave, you want to say hi? >> Dave: Hi everybody; welcome. >> So, there's a few things that we're going to do, here. The first thing I want to note is that we've got a couple of relatively simple webinar housekeeping issues. The first thing to note is everyone is muted. There is a Q&A option. You can hit the tab and a window will pop up and you can ask questions there. So if you hear anything that requires an answer, something we haven't covered or you'd like to hear again, by all means, hit that window, ask the question, and we'll do our best to get back to you. If you're a Wikibon customer, we'll follow up with you shortly after the call to make sure you get your question answered. If, however, you want to chat with your other members of the community, or with either Dave or myself, you want to comment, then there's also a chat option. On some of the toolbars, it's listed under the More button. So if you go to the More button, and you want to chat, you can probably find that there. Finally, we're also recording the webinar, and we will turn this into a Wikibon deliverable for the overall community. So, very excited to be doing this. Now, Dave, one of the things that we note on this slide is that we have TheCube in the lower left-hand corner. Why don't you take us through a little bit about who we are and what we're doing? >> Okay, great; thanks, Peter. So I think many of you or most of you know that SiliconANGLE Media Inc is sort of the umbrella company, and underneath SiliconAngle, we have three brands: the Wikibon research brand, which was started in the 2007 time frame. It's a community of IT practitioners. TheCube is, some people call it the ESPN of tech. We'll do 100 events this year, and we extensively use TheCUBE as a data-gathering mechanism and a way to communicate to our community. We've got some big shows coming up, pretty much every week, but of course we've got Amazon Reinvent coming up, and we'll be in London with HPE Discover. And so, we cover the world and cover technology, particularly in the enterprise, and then there's the SiliconANGLE publishing team, headed up by Rob Hoaf. It was founded by my co-CEO John Ferrier, and Rob Hoaf, former Business Week, is now leading that team. So those are the three main brands. We've got a new website coming out this month, on SiliconANGLE, so really excited about that and just thank the community for all your feedback and participation, so Peter, back to you. >> Thank you, Dave, so what you're going to hear today is what the analyst team here at Wikibon has pulled together for what we regard as some of the most interesting things that we think are going to happen over the next two years. Wikibon has been known for looking at disruptive technologies, and so while the focus, from a practical standpoint, in 2017, we do go further out. What is the overarching theme? Well, the overarching theme of our research and our conversations with the community is very simple. It's: put more data to work. The industry has developed incredible tools to gather data, to do analysis on data, to have applications use data and store data. I could go on with that list. But the data tends to be quite segmented and quite siloed to a particular application, a particular group, or a particular other activity. And the goal of digital business, in very simple terms, is to find ways to turn that data into an asset, so that it can be applied to other forms of work. That data could include customer data, operational data, financial data, virtually any data that we can imagine. And the number of sources that we're going to have over the next few years are going to be astronomical. Now, what we want to do is we want to find ways so that data can be freed up, almost like energy, in a physical sense, to dramatically improve the quality of the work that a firm produces. Whether it's from an engagement standpoint, or a customer experience standpoint, or actual operations, and increasingly automation. So that's the underlying theme. And as we go through all of these predictions, that theme will come out, and we'll reinforce that message during the course of the session. So, how are we going to do this? The first thing we're going to do is we're going to have six predictions that focus in 2017. Those six predictions are going to answer crucial questions that we're getting from the community. The first one is: what's driving system architecture? Are there new use cases, new applications, new considerations that are going to influence not only how technology companies create the systems and the storage and the networking and the database, and the middleware and the applications, but also how users are going to evolve the way they think about investing? The second one is: do micro-processor options matter? Through 20 years now, we've pretty much focused on one, limited class of micro-processor, the X386, er, the X86 architecture. But will these new workloads drive opportunities or options for new micro-processors? Do we have to worry about that? Thirdly, all this data has to be stored somewhere. Are we going to continue to store it, limited only on HDDs, or are other technologies going to come into vogue? Fourthly, in the 2017 time frame, we see the cloud, a lot's happening, professional developers have flocked to it, enterprises are starting to move to it in a big way, what does it mean to code in the cloud? What kinds of challenges are we going to face? Are they technological? Are they organizational, institutional? Are they sourcing? Related to that, obviously, is Amazon's had enormous momentum over the past few years. Do we expect that to continue? Is everybody else going to be continuing to play catch-up? And the last question for 2017 that we think is going to be very important is this notion of big data complexity. Big data has promised big things, and quite frankly has, except in some limited cases, been a little bit underwhelming. As some would argue, this last election showed. Now, we're going to move, after those six predictions, to 2022, where we'll have three predictions that we're going to focus on. One is: what is the new IT mandate? Is there a new IT mandate? Is it going to be the same old, same old, or is IT going to be asked to do new things? Secondly, when we think about Internet of Things, and we think about Augmented Reality or virtual reality, or some of these other new ways of engaging people, is that going to draw out new classes of applications? And then finally, after years of investing heavily in mobile applications, in mobile websites, and any number of other things, and thinking that there was this tight linkage where mobile equaled digital engagement, we're starting to see that maybe that's breaking, and we have to ask the question: is that all there is to digital engagement, or is there something else on the horizon that we're going to have to do? The last prediction, in 2027, we're going to take a stab here and say: will we all work for AI? So, these are the questions that we hear frequently from our clients, from our community. These are the predictions we're going to attend to and address. If you have others, let us know. If there's other things that you want us to focus on, let us know, but here's where we're starting. Alright. So let's start with 2017. What's driving system architecture? Our prediction for 2017 regarding this is very simple. The IoT edge use cases begin shaping decisions in system and application architecture. Now, the right-hand side, if you look at that chart, you can see a very, very important result of the piece of research that David Foyer recently did. And it shows IoT edge options, three-year costs. From left to right, moving all the data into the cloud over a normal data communications, telecommunications circuit, in the middle, moving that data into a central location, namely using cellular network technologies, which have different performance and security attributes, and then finally, keeping 95 percent of the data at the edge, processing it locally. We can see that the costs are overwhelming, favoring being smarter by how we design these applications and keeping more of that data local. And in fact, we think that so long as data and communications costs remain what they are, that there's going to be an irrevokeable pressure to alter key application architectures and ways of thinking to keep more of that crossing at the edge. The first point to note, here, is it means that data doesn't tend to move to the center as much as many are predicting, but rather, the cloud moves to the edge. The reason for that is that data movement isn't free. That means we're going to have even more distributed, highly autonomous apps, so none of those have to be managed in ways that sustain the firm's behavior in a branded, consistent way. And very importantly, because these apps are going to be distributed and autonomous, close to the data, it ultimately means that there's going to be a lot of operational technology players that impact the key decisions, here, that we're going to see made as we think about the new technologies that are going to be built by vendors and in the application architectures that are going to be deployed by users. >> So, Peter, let me just add to that. I think the key takeaway there is, as you mentioned, and I just don't want it to get lost, is 95 percent of the data, we're predicting, will stay at the edge. That's a much larger figure than I've seen from other firms or other commentary, and that's substantial, that's significant, it says it's not going to move. It's probably going to sit on flash, and the analytics will be done at the edge, as opposed to this sort of first bar, being cloud only. That 95 percent figure has been debated. It's somewhat controversial, but that's where we are today. Just wanted to point that out. >> Yeah, that's a great point, Dave. And the one thing to note, here, that's very important, is that this is partly driven by the cost of telecommunications or data communications, but there also are physical realities that have to be addressed. So, physics, the round trip times because of the speed of light, the need for greater autonomy and automation on the edge, OT and the decisions and the characteristics there, all of these will contribute strongly to this notion of the edge is increasingly going to drive application architectures and new technologies. So what's going to power those technologies? What's going to be behind those technologies? Let's start by looking at the CPUs. Do micro-processor options matter? Well, our prediction is that evolution in workloads, the edge, big data, which we would just, for now, put AI and machine learning, and cognitive underneath many of those big data things, almost as application forms, creates an opening for new micro-processor technologies, which are going to start grabbing market share from x86 servers in the next few years. Two to three percent next year, in 2017. And we can see a scenario where that number grows to double digits in the next three or four years, easily. Now, these micro-processors are going to come from multiple sources, but the factors driving this are, first off, the unbelievable explosion in devices served. That it's just going to require more processing power all over the place, and the processing power has to become much more cost-effective and much more tuned specifically to serving those types of devices. Data volumes and data complexity is another reason. Consumer economics is clearly driving a lot of these factors, has been for years, and it's going to continue to do so. But we will see new, ARM-based processors and other, and GPUs for big data apps, which have the advantage of being also supported in many of the consumer applications out there, driving this new trend. Now, the other two factors. Moore's Law is not out of room. We don't want to suggest that, but it's not the factor that it used to be. We can't presume that we're going to get double the performance out of a single class of technology every year or so, and that's going to remove any and all other types of micro-processor sets. So there's just not as much headroom. There's going to be an opportunity now to drive at these new workloads with more specialized technology. And the final one is: the legacy software issue's never going to go away; it's a big issue, it's going to remain a big issue. But, these new workloads are going to create so much new value in digital business settings, we believe, that it will moderate the degree to which legacy software keeps a hold on the server marketplace. So, we expect a lot of ARM-based servers that are lower cost, tuned and specialized, supporting different types of apps. A lot of significant opportunity for GPUs for big data apps, which do a great job running those kinds of graph-based data models. And a lot of room, still, for RISC in pre-packaged HCI solutions. Which we call: single managed entities. Others call: appliances. So we see a lot of room for new micro-processors in the marketplace over the next few years. >> I guess I'll add to that, and I'll be brief, just in the interest of time, the industry has marched to the cadence of Moore's Law for, as we know, many, many decades, and that's been the fundamental source of innovation. We see the innovation curve shifting and changing to become combinatorial, a combination of technologies. Peter mentioned GPU, certainly visualization's in there. AI, machine learning, deep learning, graph databases, combining to be the fundamental driver of innovation, going forward, so the answer here is: yes, they matter. Workloads are obviously the key. >> Great, Dave. So let's go to the next one. We talked about CPUs, well now, let's talk about HDDs. And more broadly, storage. So the prediction is that anything in a data center that physically moves gets less useful and loses share of wallet. Now, clearly that includes tape, but now it's starting to include HDDs. In our overall enterprise systems, storage systems revenue forecast, which is going to be published very, very shortly, we've identified that we think that the revenue attributable to HDD-based enterprise storage systems is going to drop over the next few years, while flash-based enterprise storage system revenue rises dramatically. Now, we're talking about storage system revenue here, Dave. We're not just talking about the HDDs, themselves. The HDD market starts, continues to grow, perhaps not as fast, partly because, even as the performance side of the HDD market starts to fade a bit, replaced by flash, that bulk, volume part of the HDD marketplace starts to substitute for tape. So, why is this happening? One of the main reasons it's happening is because the storage revenue, the storage systems revenue is very strongly influenced by software. And those software revenues are being bundled into the flash-based systems. Now, there's a couple reasons for this. First off, as we've predicted for quite some time, we do see a flash-only data center option on the horizon. It's coming well into focus. Number two is that, the good news is flash-based products are starting to come down and also are in sight of HDD-based products at the performance level. But very importantly, and here's one of the key notions of the value of data, and finding new ways to increase the use of data: flash, our research shows, offers superior business value, too, precisely because you can make so many copies of it and have a single set of data serve so many different applications and so many users, at scales that just aren't possible with traditional, HDD-based enterprise storage systems. Now, this applies to labor, too, Dave, doesn't it? >> Yeah, so a couple of points here. Yes, labor being one of those, sort of, areas that Peter's talking about are, ah, in jeopardy. We see about $200 billion over the next 10 years shifting from what we often refer to as non-differentiated IT labor, in provisioning and networking configuration and laying cable, et cetera, shifting from where it is today in services and/or on-prem IT labor, to vendor R&D or the cloud. So that's a very important point. I think I just wanted to add some color to what you were talking about before when you talked about HDD revenue continuing to grow, I think you were talking about, specifically, in the enterprise, in this storage systems view. And the other thing I want to add is, Peter, referenced sort of the business value of flash, as you, many of you know, David Floyer and Wikibon predicted, very early on, the impact that flash would have on spinning disk, and not only because of cost related to compression and de-duplication, but also this notion that Peter's talking about, of data sharing. The ability of development organizations to use the same data and minimize the number of copies. Now, the thing to watch, here, and kind of the wildcard is the hyperscale model. Hyperscalers, as we know, are consuming many, many, you know, exabytes and petabytes of data. They do things differently than is done in the enterprise, so that's something that we're watching very closely in terms of that model, that model being the hyperscale model, how it mimics or how it doesn't mimic what traditionally has occurred in the enterprise and how that will affect adoption of both flash and spinning disk. But as Peter said, we'll be releasing this data very shortly, and you'll be able to dig into it with is. >> And very importantly, Dave, in response to one of the comments in the chat, we're not talking about duplication of data everywhere, we're talking about the ability to provide logical and effective copies to single-data sources, so that, just because you can just drive a lot more throughput. So, that's the HDD. Now, let's turn to some of this notion of coding the cloud. What are we going to do with code in the cloud? Well our prediction is that the new cloud development stack, which is centered on containers and APIs, matures rapidly, but institutional habits in development constrain change. Now, why do we say that? I want to draw your attention to the graphic on the right-hand side. Now, this is what we think the mature, or the maturing cloud development stack looks like. As you can see, it's a lot of notions of containers, a lot of notions of other types of technologies. We'll see APIs interspersed throughout here as a primary way of getting to some of these container-based applications, services, microservices, et cetera, but this same, exact chart could be mapped back to SOA from 10 years ago, and even from some of the distributed computing environments that were put forward 20 years ago. The challenge here is that a sizable percentage, and we're estimating about 80 percent of in-house development, is still set up to work the old way. And so long as development organizations are structured to build monolithic apps or take care of monolithic apps, they will tend to create monolithic apps, with whatever technology's available to them. So, while we see these stacks becoming more vogue and more in use, we may not see, in 2017, shops being able to take full advantage of them. Precisely because the institutional work forms are going to change more slowly. Now, big data will partly contravene these habits. Why? Because big data is going to require quite different development approaches, because of the complexity associated of analytic pipelines, building analytic pipelines, managing data, figuring out how to move things from here to there, et cetera; there's some very, very complex data movement that takes place within big data applications. And some of these new application services, like Cognitive, et cetera, will require some new ways of thinking about how to do development. So, there will be a contravening force here, which we'll get to, shortly, but the last one is: ultimately, we think time-to-value metrics are going to be key. As KPI's move from project cost and taking care of the money, et cetera, and move more towards speed, as Agile starts to assert itself, as organizations start to, not only, build part of the development organization around Agile, but also Agile starts bleeding into other management locations, like even finance, then we'll start to see these new technologies really start asserting themselves and having a big impact. >> So, I would add to that, this notion of the iron triangle being these embedded processes, which as we all know, people, processes, and technology, people and process are the hardest to change, I'm interested, Peter, in your thoughts on, you hear a lot about Waterfall versus Agile; how will organizations, sort of, how will that affect organizations, in terms of their ability to adopt some of these, you know, new methodologies like Agile and Scrum? >> Well, the thing we're saying is the technology's going to happen fast, the Agile processes are being well-adopted, and are being used, certainly, in development, but I have had lots of conversations with CIOs, for example, over the last year and a half, two years ago, where they observed that they're having a very difficult time with reconciling the impedance mismatch between Agile development and non-Agile budgeting. And so, a lot of that still has to be worked out, and it's going to be tied back to how we think about the value of data, to be sure, but ultimately, again, it comes back to this notion of people, Dave, if the organization is not set up to fully take advantage of these new classes of technologies, if they're set up to deliver and maintain more monolithic applications, then that's what's going to tend to get built, and that's what's going to get, and that's what the organization is going to tend to have, and that's going to undermine some of the new value propositions that these technologies put forward. Well, what about the cloud? What kind of momentum does Amazon have? And our prediction for 2017 is that Amazon's going to have yet another banner year, but customers are going to start demanding a simplicity reset. Now, TheCUBE is going to be at Amazon Reinvent with John Ferrier and Steve Minnamon are going to be up there, I believe, Dave, and we're very excited. There's a lot of buzz happening about Reinvent. So follow us up there, through TheCUBE at Reinvent. But what I've done on the right-hand side is sent you a piece of Wikibon research. What we did is we wrote up, and we did an analysis of all of the AWS cases put forward, on their website, about how people are using AWS, and there's well over 650, or at least there were when we looked at it, and we looked at about two-thirds of them, and here's what we came up with. Somewhere in the vicinity of 80 percent, or so, of those cases are tied back to firms that we might regard as professional software delivery organizations. Whether they're stash or business services or games, provided games, or social networks. There's a smaller piece of the pie that's dedicated to traditional enterprise-type class of customers. But that's a growing and important piece, and we're not diminishing it at all, but the broad array of this pie chart, folks are relatively able to hire the people and apply the skills and devote the time necessary to learn some of the more complex, 75-plus Amazon services that are now available. The other part of the marketplace, the part that's moving into Amazon, the promise of Amazon is that it's simple, it's straightforward, and it is. Certainly more so than other options, but we anticipate that there will have to be a new type of, and Amazon's going to have to work even harder to simplify it, as it tries to attract more of that enterprise crowd. It's true that the flexibility of Amazon is certainly spawning complexity. We expect to see new tools, in fact, there are new tools on the market from companies like Appfield, for example, for handling and managing AWS billing and services, and that is, our CIOs are telling us, they're actually very helpful and very powerful in helping to manage those relationships, but the big issue here is that other folks, like VM Ware, have done research to suggest that the average shop has two to three big cloud relationships. That makes a lot of sense to us. As we start adding hybrid cloud into this and the complexities of inter-cloud communication and inter-cloud orchestration starts to become very real, that's going to even add more complexity, overall. >> So I'd add to that, just in terms of Amazon momentum, obviously those of you who follow what I read, you know, have been covering this for quite some time, but to me, the marginal economics of Amazon's model continue to be increasingly attractive. You can see it in the operating profits. Amazon's gap, operating profits, are in the mid-20s. 25, 26 percent. Just to give you a sense, EMC, who's an incredibly profitable company, its gap operating profits are in the teens. Amazon's non-gap operating profits are into 30 percent, so it's an incredibly profitable company. The more it grows, the more profitable it gets. Having said that, I think we agree with what Peter's saying in terms of complexity; think about API creep in Amazon. And different proprietary APIs for each of the data services, whether it's Kinesis or EC2 or S3 or Dynamo DB or EMR, et cetera, so the data complexity and the complexity of the data pipeline is growing, and I think that opens the door for the on-prem folks to at least mimic the public cloud experience to a great degree; as great a degree as possible. And you're seeing people, certainly, companies do that in their marketing, and starting to do that in the solutions that they're delivering. So by no means are we saying Amazon takes over the world, despite, you know, the momentum. There's a window open for those that can mimic, to the large extent, the public cloud capabilities. >> Yeah, very important point there. And as we said earlier, we do expect to see the cloud move closer to the edge, and that includes on-prem, in a managed way, as opposed to presuming that everything ends up in the cloud. Physics has something to say about that, as do some of the costs of data movement. Alright, so we've got one more 2017 prediction, and you can probably guess what it is. We've spent a lot of years and have a pretty significant place in spin big data, and we've been pretty aggressive about publishing what we think is going to happen in big data, or what is happening in big data, over the last year or so. One of the reasons why we think Amazon's momentum is going to increase is precisely because we think it's going to become a bigger target for big data. Why? Because big data complexity is a serious concern in many organizations today. Now, it's a serious concern because the spoke nature of the tools that are out there, many of which are individually extremely good, means that shops are spending an enormous amount of time just managing the underlying technology, and not as much time as they need to learning about how to solve big data problems, doing a great job of piloting applications, demonstrating to the business the financial returns are there. So as a result of this bespoked big data tool aggregates, we get multi-source, and we need to cobble it together from a lot of different technology sources, a lot of uncoordinated software and hardware updates that dramatically drive up the cost of on-prem administration. A lot of conflicting commitments, both from the business as well as from the suppliers, and very, very complex contracts. And as a result of that, we think that that's been one of the primary reasons why there's been so many pilot failures and why big data has not taken off the way that it probably should have. We think, however, that in 2017, we're going to see, and here's our prediction, we're going to see failure rates for big data pilots drop by 50 percent, as big vendors, IBM, Microsoft, AWS, and Google, amongst the chief ones, and we'll see if Oracle gets into that list, bring pre-packaged, problem-based analytic pipelines to market. And that's what we mean by this concept, here, of big data, single-managed entities. The idea that we can pull together, a company can pull together, or that it can pull together all the various elements necessary to provide the underlying infrastructure so that a shop can focus more time making sure that they understand the use-case, they understand how to go get the data necessary to serve that use-case, and understand how to pilot and deploy the application, because the underlying hardware and system software is pre-packaged and used. Now, we think that these, the SMEs, that are going to be most successful will be ones that are not predicated only on more proprietary software, but utilize a lot of open-source software. The ones that we see that are most successful today are in fact combining the pre-packaging of technology with the availability, or access, to the enormous value that the open-source market continues to build as it constructs new tools and delivers them out to big data applications. Ultimately, you've seen this before, or you've heard this before, from us: time-to-value becomes the focus. Similar to development, and we think that's one of the convergences that we have, here. We think that big data apps, or app patterns, will start to solidify. George Gilbert's done some leading-edge research on what some of those application patterns are going to be, and how those application patterns are going to drive analytic pipeline decisions, and very important, the process of building out the business capabilities necessary to build out the repeatable big data services to the business. Now, very importantly, some of these app patterns are going to be, are going to look like machine learning, cognitive AI, in many respects, all of these are part of this use-case to app trend that we see. So, we think that big data's kind of an umbrella for all of those different technology classes. It's going to be a lot of marketing done that tries to differentiate machine learning, cognitive AI. Technically, there are some differences, but from our perspective, they're all part of the effort of trying to ensure that we can pull together the technology in a more simple way so that it can be applied to complex business problems more easily. One more point I'll note, Dave, is that, and you adjust that world a lot, so I'd love to get your comments on this, but one of the more successful single-managed entities out there is, in fact, Watson from IBM, and it's actually a set of services and not just a device that you buy. >> Yeah, so a couple comments, there. One is that you can see the complexity in the market data, and we've been covering big data markets for a long time now, and there were two things that stood out when we started covering this. One is that software, as a percentage of the total revenue, is much lower than you would expect, in most markets. And that's because of the open-source contribution and the, you know, the multi-year collapse that we've seen in infrastructure software pricing. Largely due to open-source and cloud. The other piece of that is professional services, which have dominated spending within big data, because of the complexity. I think you're right, when you look at what happened at World of Watson and, you know, what IBM's trying to do, and others, in your prediction, there, are putting together a full, end-to-end data pipeline to do, you know, ingest and data wrangling and collaboration between data scientists, data engineers, and application developers and data quality people, and then bringing in the analytics piece. And essentially, you know, what many companies have done, and IBM included, they've cobbled together sets of tools and they've sort of layered on a way to interact with those tools, so the integration has still been slow in coming, but that's where the market is headed, so that we actually can build commercial, off the shelf applications. There's been a lack of those applications. I remember, probably four years ago, Mike Olsen at a (unintelligible) predicted: this will be the year of the big data app. And it still has not happened, so, and until it does, that complexity is going to reign. >> Yeah, and so it, again, as we said earlier, we anticipate that the big data, the need for developers to become more a part of the big data ecosystem, and the need for developers to get more value out of some of the other new cloud stacks are going to come together and will reinforce each other over the course of the next 24 to 36 months. So those were our 2017 predictions. Now let's take a look at our 2022 predictions, and we've got three. The first one is we do think a new IT mandate's on the horizon. Consistent with all these trends we've talked about, the idea of new ways of thinking about infrastructure and application architecture, based on the realities of the edge, new ways of thinking about how application developers need to participate in the value equation activities of big data, new ways of organizing to try to take greater advantage of the new processes, new technologies for development. We think, very strongly, that IT organizations will organize work to generate greater value from data assets by engineering proximity of applications and data. What do we mean by that? Well, proximity can mean physical proximity, but it also is something that we mean in terms of governance, tool similarity, infrastructure commonality, we think that over the next four to five years, we'll see a lot of effort to try to increase the proximity of not only data assets from a data standpoint, or the raw data, but also understanding from an infrastructure, governance skillset, et cetera, standpoint. So that we can actually do a better job of, again, generating more work out of our data by finding new and interesting ways of weaving together systems of records, big analytics, IOT, and a lot of other new application forms we see on the horizon, including one that I'll talk about in a second. Data value becomes a hot topic. We're going to have to do a better job, as a community, of talking about how data is valuable. How it creates (unintelligible) in the business, how it has to be applied, or has to be thought of as a source of value, in building out those systems. We talked earlier about the notion of people, process, and technology, well, we have to add to that: data. Data needs to be an asset that gets consumed as we think about how business changes. So data value's going to become a hot topic, and it's something we're focused on, as to what it means. We think, as Dave mentioned earlier, it's going to catalyze a true private cloud solutions for legacy applications. Now, I know Dave, you're going to want to talk about, in a second, what this might need. For example, things like the Amazon, VM Ware recent announcement. But it also means that strategic sourcing becomes reality. The idea of just going after the cheapest solution, or cost-optimized solution, which, don't get me wrong, don't get us wrong, is not going to go away, but it means that increasingly we're going to focus on new sourcing arrangements that facilitate creating greater proximity for those crucial aspects that make our shop run. >> Okay, so a couple of thoughts there, Peter. You know, there's a lot of talk, a couple years ago, and it's slowly beginning to happen, of bringing transaction and analytic systems together. What that oftentimes means is somebody takes their mainframe for the transactions and sticks it in finneban pipe into an exodata. I don't think that's what everybody envisioned when you started to sort of discuss that mean. So that's sort of happening slowly. But it's something that we're watching. This notion of data value, and shifting from, really a process economy to a data, or an insight, economy is something that's also occurring. You're seeing the emergence of the chief data officer. And our research shows that there are five things a chief data officer must do to really get started. The first is to understand data value, and how data contributes to the monetization of their company. So not monetizing the data, per se, and I think that's a mistake that a lot of people made, early on, is trying to figure out how to sell their data, but it's really to understand how data contributes to value for your organization. The second piece is how to access that data, who gets access to that data, and what data sources you have. And the third is the quality and trust of that data. And those are sequential things that our research shows a chief data officer has to do. And then the other, sort of parallel items, are relationship with the line of business and re-skilling. And those are complicated issues for most organizations to undertake, and something that's going to take, you know, many, many years to play out. The vast majorities of customers that we talk to say their data-driven, but aren't necessarily data-driven. >> Right, so, the one other thing I wanted to mention, Dave, is that we did some research, for example, on the VM Ware, Amazon relationship, and the reason why we were positive on it is quite simple. That it provides a path for VM Ware's customers, with their legacy applications running under VM Ware, to move those applications and the data associated with those applications, if they choose to, closer to some of the new, big data applications that are showing up in Amazon. So there's an example of this notion of making it more proximate, making applications and data more proximate, based on physics, based on governance, based on overall tooling and skilling, and we anticipate that that's going to become a new design center for a lot of shops over the course of the next few years. Now, coming to this notion of a new design center, the next thing we want to note is that, IoT, the Internet of Things, plus augmented reality, is going to have an impact on the marketplace. We got very excited about IoT, simply by thinking about the things, but our perspective is, increasingly, we have to recognize that people are going to always be a major feature, and perhaps the greatest value-creating feature, of systems. And augmented reality is going to emerge as a crucial actuator for the Internet of Things, and people. And that's kind of what we mean, is that augmented reality becomes an actuator for people. As will Chat Box and other types of technologies. Now, an actuator in an IoT sense is the devices or set of capabilities that take the results of models and actually turn that into a real-world behavior. So, if we think about this virtuous cycle that we have on the right-hand side, the internet, these are the three capabilities that we think people or firms are going to have to build out. They're going to have to build out an Internet of Things and People that are capable of capturing data, and turning analogue data into digital data, so that it can be moved into these big data applications. Again, with machine learning and AI and cognitive, sort of being part of that or underneath that umbrella, so that, then, we can build more models, more insights, more software that then translates into what we're calling systems of enaction. Or systems of "enaction", not "inaction". Systems of enaction. Businesses still serve customers, and these systems of enaction are going to generate real-world outcomes from these models and insights, and these real-world outcomes will certainly be associated with things, but they will also be associated with human being and people. And as a consequence of this, this we think is so powerful and is going to be so important over the course of the next five years that we anticipate that we will see a new set of disciplines focused on social discovery. Historically, in this industry, we've been very focused on turning insights or discovery about physics into hardware. Well, over the next few years, and Dave mentioned moving from the process to some new economy, we're going to see an enormous investment in understanding the social dynamics of how people work together and turn that into software. Not just how accountants do things, but how customers and enterprises come together to make markets happen, and through that social discovery, create these systems of enaction so that businesses can successfully, can successfully attend to and deliver the promises and the, ah, and the predictions that they're making through their other parts of their big data applications. >> So, Peter, you've pointed out many times that the big change, relative to processes, and historically, in the IT business, we've known what the processes are. The technology was sort of unknown, and mysterious. That's flipped. It's now, really the process is the unknown piece. That's the mysterious part. The technology is pretty well-understood. I think, as it relates to what you're talking about here with IoT and AR, what people tell us, the practitioners that are struggling with this, first of all, there's so much analogue data that people are trying to digitize, the other piece is there's a limited budget that folks have, and they're trying to figure out, alright, do I spend it on getting more data, and will that improve my data, increase my observation space? Or do I spend it on better models, and improving my models and iterating? And that's a trade-off that people have to make, and of course the answer is "both", but how those funds are allocated is something that organizations are really trying to better understand. There's a lot of trial and error going on. Because obviously, more data, in theory anyway, means you can make better decisions. But it's that iteration of that model, that trial and error and constant improvement, and both of those take significant resources. And budgets are still tight. >> Very true, Dave, and in fact, George Gilbert's research with the community is starting to demonstrate that more of the value's going to come from the models, as opposed to the raw data. We need the raw data to get to the models, but more of the value's going to come from the models. So that's where we think more people are going to focus their time and attention. Because the value will be in the insights and the models. But to go back to your point: where do you put your money? Well, you got to run these pilots, you got to keep up with your competitors, you got to serve customers better, so you're going to have to build all these models, sometimes in a bespoked way. But George is publishing an enormous amount of research right now that's very valuable to a lot of our community members that really shows how that pipeline, how those analytic pipelines or the capabilities associated with those analytic pipelines are starting to become better understood. So that we can actually start getting experience and generating efficiencies or generating a scale out of those analytic pipelines. And that's going to be a major feature underlying this basic trend. Now, this notion of people is really crucial, because as we think about the move to the Internet of Things and People, we have to ask ourselves: has digital engagement really, fully considered what it means to engage people throughout their customer journey? And the answer is: no, it hasn't. We believe that by 2022, IT will be given greater responsibility for management of demand chains. Working to unify customer journey designs and operations across all engagement functions. And by engagement functions, we mean marketing, sales, we mean product, we mean service, we mean fulfillment. That doesn't mean that they all report to IT. Don't mean that, at all. But it means that IT is going to have to, again, find ways to apply data from all these different sources so that it can, in fact, simplify and unify and bring together consistent design and operations so that all these functions can be successful and support reorganization if necessary, because the underlying systems provide that degree of unity and focus on customer success. Now, this is in strong opposition to the prediction made a few years ago, that marketing was going to emerge as the be-all and end-all, that's going to spend more than IT. That was silly, it hasn't happened, and you'd have to redefine marketing very aggressively to see that actually happening. But, when we think about this notion of putting more data to work, the first thing we note, and this is what all the digital natives have shown us, the data can transform a product into a service. That is the basis for a lot of the new business models we're talking about, a lot of these digital native business models and successes that they've had, and we think it's going to be a primary feature of the IT mandate to help business understand how data, more data can be put to work, transforming products into services. It also means, at a tactical level, that mobile applications have been way too focused on solving the seller's problems. We want to caution folks, don't presume that because your mobile application has gotten lost in some online store somewhere that that means that digital engagement's a failure. No, it means that you have to focus digital engagement on providing value throughout the customer journey, and not just from the problem to the solution, where the transaction for money takes place. Too much mobile applications, or too many mobile applications have been focused, in a limited way, on the marketers' problem within the business, of trying to generate, trying to generate awareness and demand. And it has to be, mobile has to be applied in a coherent and comprehensive way, across the entire journey. And ultimately, I hate to say this, but we think collaboration's going to make a comeback. But collaboration to serve customers. So the business can collaborate better inside, but in support of serving the customers. Major, major feature of what we think is going to happen over the course of the next couple years. >> I think the key point there is we all, there's many mobile apps that we love, and utilize, but there are a lot that are not so great. And the point that we've made to the community, quite often, is that it used to be that the brands had all the power, they had all the information, there was an asymmetry of information, the customer, the consumer didn't really know much about pricing. The web, obviously, has leveled that playing field and what many brands are trying to do is recreate that asymmetry and maybe got over their skis a little bit, before providing value to the customers. And I think your point is that, to the extent that you can provide value to that customer, that information advantage will come back to you. But you can't start with that information advantage. >> Great point, Dave. But it also means that we need to, that IT needs to look at the entire journey and see transactions and the discover, evaluate, buy, apply, use and fix throughout this entire journey and find ways of designing systems that provide value to customers at all times and in all places. So the demand chain notion, which historically has been focused on trying to optimize the value that the buyer gets in the buy process, at a cost-effective way, that notion of demand chain has to be applied to the entire engagement lifecycle. Alright, so that's 2022. Let's take a crack at our big prediction for 2027. And it's at, ah, it's on a lot of people's minds. Will we all work for AI? There've been a lot of studies done, over the course of the past year, year and a half, that have been kind of suggested that 47 percent of jobs are going to go away, for example. And that's not, that's not the only high end. Actually, folks have suggested much more, over the next 10, 15 years. Now, if you take a look at the right-hand side, you see a robot thinker. Now, you may not know this, but when The Thinker was actually first, when Rodan first constructed The Thinker, what he was envisioning was actually someone looking down into the seven levels of Hell as described by Dante. And I think that a lot of people would agree that the notion of no work is a Hell for a lot of people. We don't think that that's going to happen in the same way that most folks do. We believe that AI technology advances will far outpace the social advances. Some tasks will be totally replaced, but most jobs will only be partially replaced. We have to draw a clear distinction between the idea that a job performs only this or that task, as opposed to a job or an individual, an employee, as part of a complex community that ensures that a business is capable of serving customers. It doesn't mean we're not going to see more automation, but automation is going to focus mostly on replacing tasks. And to the degree that that task sets a particular job is replaced, then those jobs will be replaced. But ultimately, there's going to be a lot of social friction that gates how fast this happens. One of the key reasons for the social friction is something in behavioral economics that's known as loss avoidance. People are more afraid of losing something than they are of gaining something. And, whether it's a union or whether it's regulations or any number of other factors, that's going to gate the rate at which this notion that AI crushes employment occurs. AI will tend to compliment, not substitute for labor. And that's been a feature of technology for years. It doesn't, again, mean that some tasks and some task sets, sort of those in line with jobs, aren't replaced; there will be people put out of work as a consequence of this. But for the most part, we will see AI tend to compliment, not fully substitute for most jobs. Now this creates, also, a new design consideration. Historically, as technologists, we've looked at what can be done with technology, and we've asked: can we do it? And if the answer is "yes", we tend to go off and do it. And now, we need to start asking ourselves: should we do it? And this is not just a moral imperative. This has other implications, as well. So, for example, the remarkably bad impact that a lot of automated call centers have had on customer service from a customer experience standpoint. This has to become one of the features of how we think about bringing together, in these systems of enaction, all the different functions that are responsible for serving a customer. Asking ourselves: well, we can do it, from a technical standpoint, but should we do it from a customer experience, from a community relations, and even from a, ah, from a cultural imperative standpoint, as we move forward? >> Okay, I'll be brief, because we're wrapping up here, but first of all, machines have always replaced humans. When, largely with physical tasks, now we're seeing that occur with cognitive tasks. People are concerned, as Peter said. The middle class is obviously under fire. The median income in the United States has dropped from $55,000 in 1999 to just above $50,000 today. So, something's going on, and clearly you can look around and see whether it's an an airport with kiosks or billboards, electronic machines and cognitive functions are replacing human functions. Having said that, we're sanguine, because the, the story I'll tell is that the greatest chess player in the world is not a machine. When Deep Blue beat Gary Kasparov, what Gary Kasparov did is he started a competition to collaborate with other, you know, human chess players with machines, to beat the machine, and they succeeded at that, so this, again, I come back to this combination of technologies. Combinatorial technologies are really what's going to drive the innovation curve over the next, we think, 20 to 50 years. So, it's something that is far out there, in terms of our predictions, but it's also something that is relevant to the society, and obviously the technology industry. So thank you, everybody. >> So, we have one more slide, and it's Conclusions Slide, so let me hit these really quick, and before I do so, let me note that George, our big data analyst is George Gilbert. George Gilbert: G-I-L-B-E-R-T. Alright, so, very quickly, tech architecture question, we think edge IoT is going to have a major effect in how we think about architecture of the future. Micro-processor options? Yup, new micro-processor options are going to have an impact in the marketplace. Whither HDDs? For the performance side of storage, flash is coming on strong. Code in the cloud? Yes, the technologies are great, but development has to change its habits. Amazon momentum? Absolutely going to continue. Big data complexity? It's bad and we have to find ways to make it simpler so that we can focus more on the outcomes and the results, as opposed to the infrastructure and the tooling. 2022, new IT mandate? Drive the value of that data. Get more value out of your data. The Internet of Things and People is going to become the proper way of thinking about how these new systems of enaction work, and we anticipate that demand chain management is going to be crucial to extending the idea of digital engagement. Will we all work for AI? Dave just mentioned, as we said, there's going to be dislocation, there's going to be tasks that are replaced, but not by 2027. Alright, so thank you very much for your time, today. Here is how you can contact Dave and myself. We will be publishing this, the slides and this broadcast. Wikibon's going to deliver three coordinated predictions talks over the course of the next two days, so look for that. Go up to SiliconANGLE, we're up there a fair amount. Follow us on Twitter, and we want to thank you very much for staying with us during the course of this session. Have a great day.