>>Good morning live from Chicago. It's the cube on the floor at Ansible Fast 2022. This is day two of our wall to wall coverage. Lisa Martin here with John Furrier. John, we're gonna be talking next in the segment with two alumni about what Red Hat and IBM are doing to give Ansible users AI superpowers. As one of our alumni guests said, just off the keynote stage, we're nearing an inflection point in ai. >>The power of AI with Ansible is really gonna be an innovative, I think an inflection point for a long time because Ansible does such great things. This segment's gonna explore that innovation, bringing AI and making people more productive and more importantly, you know, this whole low code, no code, kind of right in the sweet spot of the skills gap. So should be a great segment. >>Great segment. Please welcome back two of our alumni. Perry is here, the Chief scientist, IBM Research and IBM Fellow. And Tom Anderson joins us once again, VP and general manager at Red Hat. Gentlemen, great to have you on the program. We're gonna have you back. >>Thank you for having >>Us and thanks for joining us. Fresh off the keynote stage. Really enjoyed your keynote this morning. Very exciting news. You have a project called Project Wisdom. We're talking about this inflection point in ai. Tell the audience, the viewers, what is Project Wisdom And Wisdom differs from intelligence. How >>I think Project Wisdom is really about, as I said, sort of combining two major forces that are in many ways disrupting and, and really constructing many a aspects of our society, which are software and AI together. Yeah. And I truly believe it's gonna result in a se shift on how not just enterprises, but society carries forefront. And as I said, intelligence is, is, I would argue at least artificial intelligence is more, in some ways mechanical, if I may say it, it's about algorithms, it's about data, it's about compute. Wisdom is all about what is truly important to bring out. It's not just about when you bring out a, a insight, when you bring out a decision to be able to explain that decision as well. It's almost like humans have wisdom. Machines have intelligence and, and it's about project wisdom. That's why we called it wisdom. >>Because it is about being a, a assistant augmenting humans. Just like be there with the humans and, and almost think of it as behave and interact with them as another colleague will versus intelligence, which is, you know, as I said, more mechanical is about data. Computer algorithms crunch together and, and we wanna bring the power of project wisdom and artificial intelligence to developers to, as you said, close the skills gap to be able to really make them more productive and have wisdom for Ansible be their assistant. Yeah. To be able to get things for them that they would find many ways mundane, many ways hard to find and again, be an assistant and augmented, >>You know, you know what's interesting, I want to get into the origin, how it all happened, but interesting IBM research, well known for the deep tech, big engineering. And you guys have been doing this for a long time, so congratulations. But it's interesting here at this event, even on stage here event, you're starting to see the automation come in. So the question comes up, scale. So what happens, IBM buys Red Hat, you go raid the, the raid, the ip, Trevor Treasure trove of ai. I mean this cuz this is kind of like bringing two killer apps together. The Ansible configuration automation layer with ai just kind of a, >>Yeah, it's an amazing relationship. I was gonna say marriage, but I don't wanna say marriage cause I may be >>Last. I didn't mean say raid the Treasure Trobe, but the kind of >>Like, oh my God. An amazing relationship where we bring all this expertise around automation, obviously around IP and application infrastructure automation and IBM research, Richie and his team bring this amazing capacity and experience around ai. Bring those two things together and applying AI to automation for our teams is so incredibly fantastic. I just can't contain my enthusiasm about it. And you could feel it in the keynote this morning that Richie was doing the energy in the room and when folks saw that, it's just amazing. >>The geeks are gonna love it for sure. But here I wanna get into the whole evolution. Computers on computers, remember the old days thinking machines was a company generations ago that I think they've sold or went outta business, but self-learning, learning machines, computers, programming, computers was actually on your slide you kind of piece out this next wave of AI and machine learning, starting with expert systems really kind of, I'm almost say static, but like okay programs. Yeah, yeah. And then now with machine learning and that big debate was unsupervised, supervised, which is not really perfect. Deep learning, which now explores some things, but now we're at another wave. Take, take us through the thought there explaining what this transition looks like and why. >>I think we are, as I said, we are really at an inflection point in the journey of ai. And if ai, I think it's fair to say data is the pain of ai without data, AI doesn't exist. But if I were to train AI with what is known as supervised learning or or data that is labeled, you are almost sort of limited because there are only so many people who have that expertise. And interestingly, they all have day jobs. So they're not just gonna sit around and label this for you. Some people may be available, but you know, this is not, again, as I as Tom said, we are really trying to apply it to some very sort of key domains which require subject matter expertise. This is not like labeling cats and dogs that everybody else in the board knows there are, the community's very large, but still the skills to go around are not that many. >>And I truly believe to apply AI to the, to the word of, you know, enterprises information technology automation, you have to have unsupervised learning and that's the only way to skate. Yeah. And these two trends really about, you know, information technology percolating across every enterprise and unsupervised learning, which is learning on this very large amount of data with of course know very large compute with some very powerful algorithms like transformer architectures and others which have been disrupting the, the domain of natural language as well are coming together with what I described as foundation models. Yeah. Which anybody who plays with it, you'll be blown away. That's literally blown away. >>And you call that self supervision at scale, which is kind of the foundation. So I have to ask you, cuz this comes up a lot with cloud, cloud scale, everyone tells horizontally scalable cloud, but vertically specialized applications where domain expertise and data plays. So the better the data, the better the self supervision, better the learning. But if it's horizontally scalable is a lot to learn. So how do you create that data ops where it's where the machines are gonna be peaked to maximize what's addressable, but what's also in the domain too, you gotta have that kind of diversity. Can you share your thoughts on that? >>Absolutely. So in, in the domain of foundation models, there are two main stages I would say. One is what I'll describe as pre-training, which is think of it as the, the machine in this particular case is knowledgeable about the domain of code in general. It knows syntax of Python, Java script know, go see Java and so, so on actually, and, and also Yammel as well, which is obviously one would argue is the domain of information technology. And once you get to that level, it's a, it's almost like having a developer who knows all of this but may not be an expert at Ansible just yet. He or she can be an expert at Ansible but is not there yet. That's what I'll call background knowledge. And also in the, in the case of foundation models, they are very adept at natural language as well. So they can connect natural language to code, but they are not yet expert at the domain of Ansible. >>Now there's something called, the second stage of learning is called fine tuning, which is about this data ops where I take data, which is sort of the SME data in this particular case. And it's curated. So this is not just generic data, you pick off GitHub, you don't know what exists out there. This is the data which is governed, which we know is of high quality as well. And you think of it as you specialize the generic AI with pre-trained AI with that data. And those two stages, including the governance of that data that goes into it results in this sort of really breakthrough technology that we've been calling Project Wisdom for. Our first application is Ansible, but just watch out that area. There are many more to come and, and we are gonna really, I'm really excited about this partnership with Red Hat because across IBM and research, I think where wherever we, if there is one place where we can find excited, open source, open developer community, it is Right. That's, >>Yeah. >>Tom, talk about the, the role of open source and Project Wisdom, the involvement of the community and maybe Richard, any feedback that you've gotten since coming off stage? I'm sure you were mobbed. >>Yeah, so for us this is, it's called Project Wisdom, not Product Wisdom. Right? Sorry. Right. And so, no, you didn't say that but I wanna just emphasize that it is a project and for us that is a key word in the upstream community that this is where we're inviting the community to jump on board with us and bring their expertise. All these people that are here will start to participate. They're excited in it. They'll bring their expertise and experience and that fine tuning of the model will just get better and better. So we're really excited about introducing this now and involving the community because it's super nuts. Everything that Red Hat does is around the community and this is no different. And so we're really excited about Project Wisdom. >>That's interesting. The project piece because if you see in today's world the innovation strategy before where we are now, go back to say 15 years ago it was of standard, it's gotta have standard bodies. You can still innovate and differentiate, but yet with open source and community, it's a blending of research and practitioners. I think that to me is a big story here is that what you guys are demonstrating is the combination of research and practitioners in the project. Yes. So how does this play out? Cuz this is kind of like how things are gonna get done in the cloud cuz Amazon's not gonna just standardize their stack at at higher level services, nor is Azure and they might get some plumbing commonalities below, but for Project Project Wisdom to be successful, they can, it doesn't need to have standards. If I get this right, if I can my on point here, what do you guys think about that? React to that? Yeah, >>So I definitely, I think standardization in terms of what we will call ML ops pipeline for models to be deployed and managed and operated. It's like models, like any other code, there's standardization on DevOps ops pipeline, there's standardization on machine learning pipeline. And these models will be deployed in the cloud because they need to scale. The only way to scale to, you know, thousands of users is through cloud. And there is, there are standard pipelines that we are working and architecting together with the Red Hat community leveraging open source packages. Yeah. Is really to, to help scale out the AI models of wisdom together. And another point I wanted to pick up on just what Tom said, I've been sort of in the area of productizing AI for for long now having experience with Watson as well. The only scenario where I've seen AI being successful is in this scenario where, what I describe as it meets the criteria of flywheel of ai. >>What do I mean by flywheel of ai? It cannot be some research people build a model. It may be wowing, but you roll it out and there's no feedback. Yeah, exactly. Okay. We are duh. So what actually, the only way the more people use these models, the more they give you feedback, the better it gets because it knows what is right and what is not right. It will never be right the first time. Actually, you know, the data it is trained on is a depiction of reality. Yeah. It is not a reality in itself. Yeah. The reality is a constantly moving target and the only way to make AI successful is to close that loop with the community. And that's why I just wanted to reemphasize the point on why community is that important >>Actually. And what's interesting Tom is this is a difference between standards bodies, old school and communities. Because developers are very efficient in their feedback. Yes. They jump to patterns that serve their needs, whether it's self-service or whatever. You can kind of see what's going on. Yeah. It's either working or not. Yeah, yeah, >>Yeah. We get immediate feedback from the community and we know real fast when something isn't working, when something is working, there are no problems with the flow of data between the members of the community and, and the developers themselves. So yeah, it's, I'm it's great. It's gonna be fantastic. The energy around Project Wisdom already. I bet. We're gonna go down to the Project Wisdom session, the breakout session, and I bet you the room will be overflowed. >>How do people get involved real quick? Get, get a take a minute to explain how I would get involved. I'm a community member. Yep. I'm watching this video, I'm intrigued. This has got me enthusiastic. How do I get more confident with this opportunity? >>So you go to, first of all, you go to red hat.com/project Wisdom and you register your interests and you wanna participate. We're gonna start growing this process, bringing people in, getting ready to make the service available to people to start using and to experiment with. Start getting their feedback. So this is the beginning of, of a journey. This isn't the, you know, this isn't the midpoint of a journey, this is the begin. You know, even though the work has been going on for a year, this is the beginning of the community journey now. And so we're gonna start working together through channels like Discord and whatnot to be able to exchange information and bring people in. >>What are some of the key use cases, maybe Richie are starting with you that, that you think maybe dream use cases that you think the community will help to really uncover as we're looking at Project Wisdom really helping in this transformation of ai. >>So if I focus on let's say Ansible itself, there are much wider use cases, but Ansible itself and you know, I, I would say I had not realized, I've been working on AI for Good for long, but I had not realized the excitement and the power of Ansible community itself. It's very large, it's very bottom sum, which I love actually. But as I went to lot of like CTOs and CIOs of lot of our customers as well, it was becoming clear the use cases of, you know, I've got thousand Ansible developers or IT or automation experts. They write code all the time. I don't know what all of this code is about. So the, the system administrators, managers, they're trying to figure out sort of how to organize all of this together and think of it as Google for finding all of these automation code automation content. >>And I'm very excited about not just the use cases that we demonstrated today, that is beginning of the journey, but to be able to help enterprises in finding the right code through natural language interfaces, generating the code, helping Del us debug their code as well. Giving them predictive insights into this may happen. Just watch out for it when you deploy this. Something like that happened before, just watch out for it as well. So I'm, I'm excited about the entire life cycle of IT automation, Not just about at the build time, but also at the time of deployment. At the time of management. This is just a start of a journey, but there are many exciting use cases abound for Ansible and beyond. >>It's gonna be great to watch this as it unfolds. Obviously just announcing this today. We thank you both so much for joining us on the program, talking about Project wisdom and, and sharing how the community can get involved. So you're gonna have to come back next year. We're gonna have to talk about what's going on. Cause I imagine with the excitement of the community and the volume of the community, this is just the tip of the iceberg. Absolutely. >>This is absolutely exactly. You're excited about. >>Excellent. And you should be. Congratulations. Thank, thanks again for joining us. We really appreciate your insights. Thank you. Thank >>You for having >>Us. For our guests and John Furrier, I'm Lisa Barton and you're watching The Cube Lie from Chicago at Ansible Fest 22. This is day two of wall to wall coverage on the cube. Stick around. Our next guest joins us in just a minute.

>>from around the globe. It's the cube with coverage of Kublai >>Khan and Cloud Native Con, Europe 2021 >>virtual brought to you by red hat. The cloud Native >>computing foundation >>and ecosystem partners. >>Welcome back to the cubes coverage everyone of Coop Con 2021 Cloud Native Con 21 virtual europe. I'm john for your host of the cube. We've got two great guests here, James Labaki, senior Director of Product management, Red Hat and Richer Puree. IBM fellow and chief scientist at IBM Gentlemen, thanks for coming on the cube, appreciate it. >>Thank you for having us. >>So, um, got an IBM fellow and Chief scientist, Senior Director Product management. You guys have the keys to the kingdom on cloud Native. All right, it's gonna be fun. So let's just jump into it. So I want to ask you before we get into some of the questions around the projects, what you guys take of cube con this year, in terms of the vibe, I know it's virtual in europe north America, we looked like we might be in person but this year with the pandemic cloud native just seems to have a spring to its step, it's got more traction. I've seen the cloud native piece even more than kubernetes in a way. So scott cooper diseases continues to have traction, but it's always about kubernetes now. It's more cloud native. I what do you guys think about that? >>Yeah, I'm sure you have thoughts and I could add on >>Yes, I I think well I would really think of it as almost sequential in some ways. Community is too cold now there's a layer which comes above it which is where all our, you know, clients and enterprises realize the value, which is when the applications really move. It's about the applications and what they can deliver to their end customers. And the game now is really about moving those applications and making them cloud native. That's when the value of that software infrastructure will get realized and that's why you are seeing that vibe in the, in the clients and enterprises and at two corners. Well, >>yeah, I mean, I think it's exciting. I've been covering this community since the beginning as you guys know the cube. This is the enablement moment where the fruit is coming off the tree is starting to see that first wave of you mentioned that enablement, it's happening and you can see it in the project. So I want to get into the news here, the conveyor community. What is this about? Can you take a minute to explain what is the conveyor community? >>Yeah, yeah. I think uh, you know, uh, what, what we discovered is we were starting to work with a lot of end users and practitioners. Is that what we're finding is that they kind of get tired of hearing about digital transformation and from multiple vendors and and from sales folks and these sorts of things. And when you speak to the practitioners, they just want to know what are the practical implications of moving towards a more collaborative architecture. And so, um, you know, when you start talking to them at levels beyond, uh, just generic kind of, you know, I would say marketing speak and even the business cases, the developers and sys admins need to know what it is they need to do to their application architecture is the ways they're working for to successfully modernize their applications. And so the idea behind the conveyor community was really kind of two fold. One was to help with knowledge sharing. So we started running meetups where people can come and share their knowledge of what they've done around specific topics like strangling monoliths or carving offside containers or things that sidecar containers are things that they've done successfully uh to help uh kind of move things forward. So it's really about knowledge sharing. And then the second piece we discovered was that there's really no place where you can find open source tools to help you re host re platform and re factor your applications to kubernetes. And so that's really where we're trying to fill that void is provide open source options in that space and kind of inviting everybody else to collaborate with us on that. >>Can you give an example of something uh some use cases of people doing this, why the need the drivers? It makes sense. Right. As a growing, you've got, you have to move applications. People want to have um applications moved to communities. I get that. But what are some of the use cases that were forcing this? >>Yeah, absolutely, for sure. I don't know if you have any you want to touch on um specifically I could add on as well. >>Yeah, I think some of the key use cases, I would really say it will be. So let let me just, I think James just talked about re host, re hosting, re platform ng and re factoring, I'm gonna put some numbers on it and then they talk about the use case a little bit as well. I would really say 30 virtual machines movement. That's it. That's the first one to happen. Easy, easier one, relatively speaking. But that's the first one to happen. The re platform in one where you are now really sort of changing the stack as well but not changing the application in any major way yet. And the hardest one happened around re factoring, which is, you are, you know, this is when we start talking about cloud native, you take a monolithic application which you know legacy applications which have been running for a long time and try to re factor them so that you can build microservices out of them. The very first, I would say set of clients that we are seeing at the leading edge around this will be around banking and insurance. Legacy applications, banking is obviously finances a large industry and that's the first movement you start seeing which is where the complexity of the application in terms of some of the legacy code that you are seeing more onto the, into the cloud. That for a cloud native implementation as well as their as well as a diversity of scenarios from a re hosting and re platform ng point of view. And we'll talk about some of the tools that we are putting in the community uh to help the users and uh and the developer community in many of these enterprises uh move into a cloud native implementation lot of their applications. And also from the point of view of helping them in terms of practice, is what I describe as best practices. It is not just about tools, it's about the community coming together. How do I do this? How do I do that? Actually, there are best practices that we as a community have gathered. It's about that sharing as well, James. >>Yeah, I think you hit the nail on the head. Right. So you re hosting like for example, you might have uh an application that was delivered, you buy an SV that is not available containerized yet. You need to bring that over as a VM. So you can bring that into Q Bert, you know, and actually bring that and just re hosted. You can, you might have some things that you've already containerized but they're sitting on a container orchestration layer that is no longer growing, right? So the innovation has kind of left that platform and kind of kubernetes has become kind of that standard one, the container orchestration layer, if you want become the de facto standard. And so you want to re platform that that takes massaging and transforming metadata to do that to create the right objects and so on and so forth. So there's a bunch of different use cases around that that kind of fall into that re host tree platform all the way up to re factoring >>So just explain for the audience and I know I love I love the three things re hosting re platform in and re factoring what's the difference between re platform NG and re factoring specifically, what's the nuance there? >>Yeah, yeah, so so a lot of times I think people have a lot of people, you know, I think obviously amazon kind of popularized the six hours framework years ago, you know, with, with, with, with that. And so if you look at what they kind of what they popularize it was replied corn is really kind of like a lift tinker and shift. So maybe it's, I, I'm not just taking my VM and putting it on new infrastructure, I'm gonna take my VM, maybe put on new infrastructure, but I'm gonna switch my observer until like a lighter weight observer or something like that at the same time. So that would fall into like a re platform or in the case, you know, one of the things we're seeing pretty heavily right now is the move from cloud foundry to kubernetes for example, where people are looking to take their application and actually transform it and run it on kubernetes, which requires you to really kind of re platform as well. And re factoring >>is what specific I get the >>report re factoring is, I think just following on to what James said re factoring is really about um the complexity of the application, which was mainly a monolithic large application, many of these legacy applications which have so many times, actually hundreds of millions of dollars of assets for these uh these enterprises, it's about taking the code and re factoring it in terms of dividing it into uh huh different pieces of court which can themselves be spun as microservices. So then it becomes true, it takes starting advantage of agility or development in a cloud native environment as well. It's not just about either lift and shift of the VM or or lift tinker and shift from a, from a staff point of view. It's really about not taking applications and dividing them so that we can spin microservices and it has the identity of the development of a cloud. >>I totally got a great clarification, really want to get that out there because re platform ng is really a good thing to go to the cloud. Hey, I got reticent open source, I'll use that, I can do this over here and then if we use that vendor over there, use open source over there. Really good way to look at it. I like the factory, it's like a complete re architecture or re factoring if you will. So thank you for the clarification. Great, great topic. Uh, this is what practitioners think about. So I gotta ask the next question, what projects are involved in in the community that you guys are working? It seems like a really valuable service uh and group. Um can you give an overview and what's going on in the community specifically? >>Yeah, so there's really right now, there's kind of five projects that are in the community and they're all in different, I would say different stages of maturity as well. So, um there's uh when you look at re hosting, there's two kind of primary projects focused on that. One is called forklift, which is about migrating your virtual machines into cuba. So covert is a way that you can run virtual machines orchestrated by kubernetes. We're seeing kind of a growth in demand there where people want to have a common orchestration for both their VMS and containers running on bare metal. And so forklift helps you actually mass migrate VMS into that environment. Um The second one on the re hosting side is called Crane. So Crane is really a tool that helps you migrate applications between kubernetes clusters. So you imagine you have all your you know, you might have persistent data and one kubernetes cluster and you want to migrate a name space from one cluster to another. Um That's where Crane comes in and actually helps you migrate between those um on the re platforms that we have moved to cube, which actually came from the IBM research team. So they actually open source that uh you sure you want to speak about uh moved to >>cube. Yeah, so so moved to cuba is really as we discuss the re platform scenario already, it is about, you know, if you are in a docker environment or hungry environment uh and you know, kubernetes has become a de facto standard now you are containerized already, but you really are actually moving into the communities based environment as the name implies, It's about moved to cuba back to me and this is one of the things we were looking at and as we were looking, talking to a lot of, a lot of users, it became evident to us that they are adapting now the de facto standard. Uh and it's a tool that helps you enable your applications in that new environment and and move to the new stuff. >>Yeah. And then the the the only other to our tackle which is uh probably like the one of the newest projects which is focused on kind of assessment and analysis of applications for container reservation. So actually looking at and understanding what the suitability is of an application for being containerized and start to be like being re factored into containers. Um and that's that's uh, you know, we have kind of engineers across both uh Red hat IBM research as well as uh some folks externally that are starting to become interested in that project as well. Um and the last, the last project is called Polaris, which is a tool to help you measure your software delivery performance. So this might seem a little odd to have in the community. But when you think about re hosting re platform and re factoring, the idea is that you want to measure your software delivery performance on top of kubernetes and that's what this does. It kind of measures the door metrics. If you're familiar with devops realization metrics. Um so things like, you know, uh you know, your change failure rate and other things on top of their to see are you actually improving as you're making these changes? >>Great. Let me ask the question for the folks watching or anyone interested, how do they get involved? Who can contribute, explain how people get involved? Is our site, is there up location slack channel? What's out there? >>Yeah, yeah, all of the above. So we have a, we have, we have a slack channel, we're on slack dot kubernetes dot io on town conveyor, but if you go to www dot conveyor dot io conveyor with a K. Uh, not like the cube with a C. Uh, but like cube with a K. Uh, they can go to a conveyor to Ohio and um, there they can find everything they need. So, um, we have a, you know, a governance model that's getting put in place, contributor ladder, all the things you'd expect. We're kind of talking into the C N C F around the gap delivery groups to kind of understand if we can um, how we can align ourselves so that in the future of these projects take off, they can become kind of sandbox projects. Um and uh yeah, we would welcome any and all kind of contribution and collaboration >>for sure. I don't know if you have >>anything to add on that, I >>think you covered it at the point has already um, just to put a plug in for uh we have already been having meetups, so on the best practices you will find the community, um, not just on convert or die. Oh, but as you start joining the community and those of meet ups and the help you can get whether on the slack channel, very helpful on the day to day problems that you are encountering as you are taking your applications to a cloud native environment. >>So, and I can see this being a big interest enterprises as they have a mix and match environment and with container as you can bring and integrate old legacy. And that's the beautiful thing about hybrid cloud that I find fascinating right now is that with all the goodness of stade Coubertin and cloud native, if you've got a legacy environments, great fit now. So you don't have to kill the old to bring in the news. So this is gonna be everything a real popular project for, you know, the class, what I call the classic enterprise, So what you guys both have your companies participated in. So with that is that the goal is that the gulf of this community is to reach out to the classic enterprise or open source because certainly and users are coming in like, like, like you read about, I mean they're coming in fast into the community. >>What's the goal for the community really is to provide assistant and help and guidance to the users from a community point of view. It's not just from us whether it is red hat or are ideal research, but it's really enterprises start participating and we're already seeing that interest from the enterprises because there was a big gap in this area, a lot of vendor. Exactly when you start on this journey, there will be 100 people who will be telling you all you have to do is this Yeah, that's easy. All you have to do. I know there is a red flag goes up, >>it's easy just go cloud native all the way everything is a service. It's just so easy. Just you know, just now I was going to brian gracefully, you get right on that. I want to just quickly town tangent here, brian grazer whose product strategist at red hat, you're gonna like this because he's like, look at the cloud native pieces expanding because um, the enterprises now are, are in there and they're doing good work before you saw projects like envoy come from the hyper scales like lift and you know, the big companies who are building their own stuff, so you start to see that transition, it's no longer the debate on open source and kubernetes and cloud native. It's the discussion is integration legacy. So this is the big discussion this week. Do you guys agree with that? And what would, what would be your reaction? >>Yeah, no, I, I agree with you. Right. I mean, I think, you know, I think that the stat you always here is that the 1st 20 of kind of cloud happened and now there's all the rest of it. Right? And, and modernization is going to be the big piece right? You have to be able to modernize those applications and those workloads and you know, they're, I think they're gonna fall in three key buckets, right? Re host free platform re factor and dependent on your business justification and you know, your needs, you're going to choose one of those paths and we just want to be able to provide open tools and a community based approach to those folks too to help that certainly will have and just, you know, just like it always does, you know, upstream first and then we'll have enterprise versions of these migration tool kits based on these projects, but you know, we really do want to kind of build them, you know, and make sure we have the best solution to the problem, which we believe community is the way to do that. >>And I think just to add to what James said, typically we are talking about enterprises, these enterprises will have thousands of applications, so we're not talking about 10 40 number. We're talking thousands or 20% is not a small number is still 233 400. But man, the work is remaining and that's why they are getting excited about cloud negative now, okay, now we have seen the benefit but this little bit here, but now, let's get, you know serious about about that transformation and this is about helping them in a cloud native uh in an open source way, which is what red hat. XL Sad. Let's bring the community together. >>I'm actually doing a story on that. You brought that up with thousands of applications because I think it's, it's under underestimate, I think it's going to be 1000s and thousands more because businesses now, software driven everywhere and observe ability has pointed this out. And I was talking to the founder of uh Ravana project and it's like, how many thousands of dashboards you're gonna need? Roads are So so this is again, this is the problems and the opportunities are coming together, the abstraction will get you to move up the stack in terms of automation. So it's kind of fascinating when you start thinking about the impact as this goes the next level. And so I have to ask your roaches since you're an IBM fellow and chief scientist, which by the way, is a huge distinction. Congratulations. Being an IBM fellow is is a big deal. Uh IBM takes that very seriously. Only a few of them. You've seen many waves and cycles of innovation. How would you categorize this one now? Because maybe I'm getting old and and loving this right now. But this seems like everything kind of coming together in one flash 10.1 major inflection point. All the other waves combined seemed to be like in this one movement very fast. What's your what's your take on this wave that we're in? >>Yes, I would really say there is a lot of technology has been developed but that technology needs to have its value unleashed and that's exactly where the intersection of those applications and that technology occurs. Um I'm gonna put in yet another. You talked about everything becoming software. This was Anderson I think uh Jack Lee said the software is eating the world another you know, another wave that has started as a i eating software as well. And I do believe these two will go inside uh to uh like let me just give you a brief example re factoring how you take your application and smart ways of using ai to be able to recommend the right microservices for you is another one that we've been working towards and some of those capabilities will actually come in this community as well. So when we talk about innovations in this area, We are we are bringing together the best of IBM research as well. As we are hoping the community actually uh joints as well and enterprises are already starting to join to bring together the latest of the innovations bringing their applications and the best practices together to unleash that value of the technology in moving the rest of that 80%. And to be able to seamlessly bridge from my legacy environment to the cloud native environment. >>Yeah. And hybrid cloud is gonna be multi cloud really is the backbone and operating system of business and life society. So as these apps start to come on a P i is an integration, all of these things are coming together. So um yeah, this conveyor project and conveyor community looks like a really strong approach. Congratulations. Good >>job bob. >>Yeah, great stuff. Kubernetes, enabling companies is enabling all kinds of value here in the cube. We're bringing it to you with two experts. Uh, James Richard, thanks for coming on the Cuban sharing. Thank you. >>Thank you. >>Okay, cube con and cloud native coverage. I'm john furry with the cube. Thanks for watching. Yeah.

(melodious music) >> Voiceover: From around the globe. It's theCUBE with digital coverage of IBM Think 2021. Brought to you by IBM. >> Hi and welcome back to theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, host of theCUBE. We're a virtual this year. But we'll be in real life soon, right around the corner, as we come out of COVID. We got a great guest, a CUBE alumni, Jerry Cuomo, IBM Fellow VP, CTO for IBM automation. Jerry, great to see you. Been on since almost since the early days of theCUBE. Good to see you >> Yeah, John. Thrilled to be back again. Thank you. >> What I love about our conversations, one is you're super technical. You've got patents under your belt. You're on the cutting edge. You've been involved in web services and web technologies for a long, long time. You're constantly riding the wave. And also you're a creator of a great podcast called "The Art of Automation", which is the subject of this discussion. As automation becomes central in cloud operations and Hybrid Cloud, which is the main theme of this event this year and the industry. So great to see you. First give us a little background for the folks that may not know you, about your history with IBM and who you are. >> Yeah. So thanks John. So I'm Jerry Cuomo. I've been with IBM for about three decades and I started my career at IBM research in Yorktown at the dawn of the internet. And I've been incredibly fortunate as you mentioned, to be on the forefront of many technology trends over the last three decades, internet software, middleware, including being one of the founding fathers of WebSphere software. I recently helped launch the IBM blockchain initiative and now all about AI powered automation. Which actually brings me back to my roots of studying AI in graduate school. So it's kind of come full circle for me, really enjoying the topic. >> It's funny you mentioned AI in graduate school. I was really kind of into AI when I was an undergraduate and get a master's degree in Computer Science. I kind of went the MBA route. But if you think about what was going on in the eighties during those systems times, a lot of the concepts of systems programming and cloud operations kind of gel well together. So you got this confluence of computer science and engineering AKA now DevOps, DevSecOps, coming together. This is actually a really unique time to bring back the best of the best concepts. Whether it's AI and systems and computer science and engineering into automation. Could you share your view on this? Because you're in a unique position, you've been there done that, now you're on the cutting edge. What's your thoughts? >> Yeah, absolutely John. And just when you think of automation and time, automation is not new. That literally, if you go into Wikipedia and you look up automation, you see patents and references to like steam engine regulators at the dawn of the industrial era, right? So automation has been around and in its simplest form, automation whether it was back then, whether it was in the eighties or today it's about applying technology that uses technology software to perform tasks that were once exclusively done by us, humans. But now what we're seeing is AI coming into the picture and changing the landscape in an interesting way. But I think at its essence, automation is this two-step dance of both eliminating repetitive mundane tasks that help reduce errors and free up our time. So we get back the gift of time, but also helps. It's not about taking jobs away at that point, it's a sentence of two-step dance. That's step one. But if you stop there, you're not getting the full value. Step two is to augment our skills. And to use automation, to help augment our skills. And we get speed, we get quality, we get lower costs, we get improved user experience. So whether it was back in the steam engine times or today with AI, automation is evolving with technology. >> And it's interesting too, as a student of the history of the computer industry, as you are and now a creator with your podcast, which we'll get to in a second. You're starting to see the intersection of these concerts and not bespoke as much as they used to be. You got transformation, digital transformation and innovation are connected and scale. If you think about those three concepts, they don't stand alone anymore. They can stand alone, but they work better together. Transformation. And it is the innovation, innovation provides cloud scale. So if you think about automation, automation is powering this dynamic of taking all that undifferentiated heavy lifting and moving the creativity and the skillset into higher integrated areas. Can you share your thoughts? >> Yeah, no, right on there. When you talk about transformation, jeez, look around us. The pandemic has made, transformation and specifically digital transformation, the default. So everything is digital. Whether it's ordering a pizza, visiting a doctor through telemedicine, or this zoom WebEx based workplace that we live in. But picture a telemedicine environment, talking about transformation and going digital. With 10 X more users, they can't hire 10 X more support staff. And think about it. I forgot my password, does this work on my version of the Apple iPhone or all of that kind of stuff? So their support desks are lit up, right? So as they scale digitally, automation is the relief that that comes into play, which is just in time. So the digital transformation needs automation. And John, I think about it like this, businesses like cars have become computers. So they're programmable. So automation software just like in the cars, it makes the car self-driving. I think about the Tesla model three, which I recently test drove. So with this digital acceleration, digital opens the door for automation. And now we can muse about self-driving business. We can muse about maybe that's step one, right? That's the remove repetitive work, but maybe we can actually augment business to have an autopilot. So it doesn't need us there all the time to drive. And that's the scale that you talked about. That's the scale we need. So automation is really like the peanut butter and chocolate. Digital is the peanut butter automation is the chocolate. They go well together and they produce amazing tastes. >> Yeah. That's a really interesting insight. And I was just put an exclamation point on that because you mentioned self-driving business you're implying, you said the business is a computer. So if you just think about that mind blowing concept for a second. If it's a computer, what's the operating system and what's the suite of applications that are on top of it? So, okay. Let's go in the old days you had a windows machine and you had office, which was a system software, applications software construct. If you map that to the entire company, you're talking about Red Hat and IBM will kind of come working together. Kind of connects the dots a little bit on what Red Hat could, because they're not breaking system company. So if Hybrid Cloud is the system, edge, hybrid, then you got the application suite is all software for the business. >> That's right. That's right. And if you listen to anything these days about what IBM stands for, it's Hybrid Cloud and think Red Hat as kind of the core element of that with OpenShift and AI. And both of those really matter in terms of automation and maybe I'll come back to the Hybrid Cloud or Red Hat thing in a second, but let's just talk about Watson and AI, which is the application. You mentioned scale, which I'm so glad you did. AI could help scale automation. And the trick is, is that automation sometimes gets stuck. It gets stuck when it's working with data that is noisy or unstructured. So there's a lot of structured data in your organization. With that, we can breeze through automation. But if there is more ambiguous data, unstructured, noisy, you need a human in the loop. And when you get a human in the loop, it slows things down. So what AI can start to do, AI and its subordinates, machine learning, natural language processing, computer vision. We can start to make sense of both unstructured and structured data together and we can make a big deal going forward. So that's the AI part. You mentioned Red Hat and, and Hybrid Cloud Park. Well, think about it this way, when you shop, how many stores do you... You don't just shop in one store, right? You go to specialty stores to pick up that special catsup, I don't know or mustard. (audio cuts) In one store and maybe do shopping in another store. Customers using clouds John, aren't very different. They have their specialty places to go. Maybe they're going to be running workloads in Google, involving search and AI related to search. And they're going to be using other clouds for more specialty things. From that perspective, that's a view of hybrid. Customers today, take that shopping analogy. They're going to be using Salesforce or Servicenow, IBM cloud, they have a private cloud. So when you think about automating that world, it's the real world. It's how we shop, whether it's for groceries or for cloud. The Hybrid Cloud is a reality. And how do you make sense of that? Because when an average customer has five clouds, how do you deal with five things? How do you make it easy, normalize? And that's what Red hat really does. >> It's interesting. I'll just share with you though. When I interviewed Arvin, who is now the CEO of IBM when he was at Red Hat summit 2019 in San Francisco. Before he made the acquisition, I was peppering him with questions. Like, you need to get this cloud and he loves cloud, you know, he loves cloud. So he was smiling. He just wanted to say it, he wanted to just say it. And I think Red hat brings that operating kind of mindset where the clouds are just subsystems in the OS of the middleware, which is now software which is software defined business. And this kind of is the talk of your views. Now you have a podcast called "Art of Automation". We want to get that in there, for the folks watching. Search for the podcast, "Art of Automation". This is the stories that you tell. Tell us some stories, from this phenomena. What's the impact of automation for the holistic picture? >> Well, it starts with a lot of, I guess it starts with customers. The stories start with the customer. So we're hearing from customers that AI and automation is where they're investing in 2021. For all the reasons we briefly mentioned, and IBM has a lot to offer there. So we've made AI powered automation a priority. But John, in the pursuit of making it a priority, I've started talking with many of our subject matter experts and was floored by their knowledge, their energy, their passion, and their stories. And I said, we can't keep this to ourselves. We can't keep this locked away. We have to share it. We have to let it out. So basically this is what started the podcast around that. And since then, we've had many industry luminaries from IBM and outside. Starting with customers. We had Klaus Jensen who is the CIO of Memorial Clones Kettering Hospital to talk about automation in healthcare. And he shared great stories. You need to listen to them, about automation is not going to take the place of doctors. But automation will help better read x-rays and look at those shades of gray on the x-ray and interpret it much better than we can. And be able to ingest all of the up-to-date medical research to provide pointers and make connections that the human may not be able to do in that moment. So the two working together are better than any individual. Carol Polson recently joined me to talk, and she's the CIO for Cooperators, to talk about automation and insurance. And she had some great stories too. So John, with that, a bunch of IBM, great IBM fellows like Rama Akkiraju, who is one of Forbes top 20 women in AI research. Talking about AI ops. And also Ruchir Puri talking, and Ruchir has been working on Watson since jeopardy to tell stories about ultimately now how we're teaching AI to code and all the modern programming languages. And really automating application modernization and the like. Four keyed episodes in, we have those under our belt. About 6,000 downloads so far. So it's coming along pretty well. Thanks for asking, John. >> The key is you're a content creator now, as well as a fellow. And this is the democratization, as we say direct to audience, share those stories. Also here, I think you released an ebook. Tell us a little quickly about that. We've got one minute left, give a quick plug for the ebook. >> The book echoes the podcast. Chapters relate to the episodes of the book. We're dropping the first five chapters plus forward for free on the IBM website. Other chapters will become available and drop as they become available. The book makes the content searchable on the internet. We go into more detail with advice on how to get started. You get to hear the topics and the voice of those subject matter experts. And I really suggest you go out and check it out. >> All right, Jerry Cuomo. IBM fellow VP, CTO, IBM automation. Also a content creator, podcast "Art of Automation." Jerry, we're going to list it out on our Silicon angle and our cube sites, gets you some extra love on that. Love the podcast, love the focus on sharing from experts in the field. Thanks for coming on. >> Yeah. Thank you so much for having me again, John. >> Okay, I'm John Furrier with theCUBE. Here for IBM Think 2021. Thanks for watching.