>>Welcome welcome back to the cubes coverage of dr khan 2021. I'm john for a host of the cube. We're here to talk about observe ability in the enterprise, enabling developers. Fabian lang VP of engineering and co founder of Istana, now part of IBM. Fabian, Congratulations on everything and great to have you on the cube here for dr gone. >>Thank you. Thanks for having me. >>So I'm in Palo Alto, you're in Germany were doing the remote thing obviously virtual second year in a row for dr khan. Soon real life is coming back. Uh no real impact of developers as they continue to be more productive than ever. The hottest conversation topic being discussed, being funded by venture capitalists and private equity is observe ability. This is an area you guys are playing in aggressively and you got some product observe ability. What's the big deal about Docker con Docker containers observe ability kubernetes, Why is observe ability at the center of all these conversations and the center of the value. >>So observe ability basically means you understand what's going on and today it's more important than ever to understand what's going on because there is so much more going on. If you think back five years maybe before Dr even was featured prominently, you had very little things that you needed to control that you need to understand and then micro service and coordinative became more popular and became really more important to understand what all those moving parts are doing. And that's where observe ability was born out of what we have been doing before at that time it was called application performance monitoring A PM. It's now called observe ability. It's really understanding all those parts of your architecture, of your stack of the application and in the end of the end user experience, you want to know if a user is experiencing a slow service and what's the reason for that? Because today, so many things are moving so many things that maybe even outsourced into cloud providers, it's more important than ever to know what's going on. >>Well we're here at Dunkirk on 2021 virtual. I want to get you to take a minute if you don't mind explaining to the folks why Dr and Dr Khan is important to Astana. >>So I, I said we were founded like six years ago and at that time Doctor was the rising star. It was promoting a lot of new technology. It was giving developers new abilities to develop applications in a very agile away. Microservices were enabled by Doctor before you had to deploy those things somehow it was a city Rome and then you needed to install >>debian >>package but with microservices you have so many more things to install. So it was really, I would say instrumental to the success of microservices to have a platform like docker that was really the next gen of technology that helped to enable those applications. And for us it was really an important driver to understand the whole stack, the traditional tools where eyes are oriented to infrastructure monitoring. So you understand the quality of your host if it's running slow or to look into application of an application was throwing errors but everything was disconnected and unique functionality of Astana is to connect all those bits and pieces of the application together and for that containers. And now kubernetes is a really important part to understand because it is part of this whole picture. >>Did you talk about the problem that you guys solve? Um obviously with those availability, I mean the general concept, we kind of get that great, great overview on your part, but when you start to get into devoPS teams, you start looking at def sec off, start looking at cloud native applications. I see Docker containers provides all that goodness and kubernetes, orchestration, etcetera. What problem do you guys solve? And um what's the benefit? >>The main problem that in stana solves is getting all this understanding that I said is required to provide a good experience of to your users, to your end customers uh without requiring you to do all the instrumentation work or the capture and configuration work because in stana is very automatic, it automatically sees all the works lords that are running in your communities, for example, that are running in Dr containers, but it also connects to legacy databases, fully automatic. So no configuration required also means that with a high rate of change that some of those applications hard have is that we will see all those change happening in real time. And you can't forget to make a configuration to enable your observe ability. So it's really return of investment on the viability solution that we provide and we provide a lot of this insight uh that you can get and that enables you to provide better service for your users. >>So you guys aren't just a doctor monitoring service and company, you guys actually run on Docker. Right, is that true? >>That's correct. So we are not only monitoring doctor and all these things connected to applications, but we are running on a doctor or platform as a service. SaAS software as a service. We run for you so you don't need to operate and stana, we are running it on managed kubernetes clusters and uh, IBM cloud and amazon cloud in google cloud. We have all that and it's it's all running on docker containers and that gives us so many features that are really great with DACA. So all the configuration that specific to microservices are being baked into the images and you can just roll it out, especially for monitoring products that is dependent on the data, that the performance depends on the data our customers send. Um, these ease of scalability with doctor is just so much bigger than it would be with a traditional deployment type. We can just add worker notes to our cluster and have ports auto scale to new notes and this is functionality that wasn't there before and that's great and that's important, essential for our business. >>You know, one of the conversations that's being talked about here at dr khan and in the industry at large is this idea of happy developers and everyone wants to keep developers happy. I've been hearing that conversation, have many chats with folks, you know, productivity and innovation, um but productivity and happy developers of the concept, but also, you know, on the, on the business side or on the developer side, it's more accelerated pipeline. Right? So, so how do you manage to flow, keep that productivity going, But also enabling happy developers, what do you guys do to help there? I mean what if someone asks you, hey, how do you make my developers happier and accelerate my pipeline? >>Well, that's really dependent on what makes the developers happy. I think most developers really want to get their functionality. They are working on their passionate about into production into the hands of end users. So um, skipping out a lot of the manual configuration work that's boring and not really appealing to develop us, helps everything is pre packaged and configured automatically. So that's a big, big plus. And the standard monitoring as I said, uh, is also automatic. So you don't need to configure it, your, your application on how to monitor it. So developers can just focus on delivering features and whenever there is something we will tell them, I think they enjoy that >>innovations creates great, that's a benefit. Can you talk about the on prem version of installing a, that's something that you guys are talking about and featuring um what is that about? Can you take a minute to explain beyond prem version of in Astana for dr containers? >>Yeah, it's a, it's an interesting topic, especially at the conference like dr khan, where it's all about virtualization, container realization and going into the cloud, that there are still companies, enterprises government mental entity that are very heavily invested on an on premise solution. They want to have control or are legally required to have control over what they have been deployed. So we knew when we founded in Astana that our solution, unlike our competitors, can't be only software as a service. We want to have a fantastic software as a service product and experience, but it should be equally good on premises as well. And when we were looking at ways how to actually do it, how to deliver an architecture that a little bit complicated to on premises customers to have themselves as the solution. We saw that doctor solves a lot of problems for us. We don't need to manually petra around operating system that customers, we don't have different versions of packages installed. It's all the same and actually it's not only all the same for all the deployment of all our customers, but it's also the same technology that we run as a software. As a service customers can run it now on their own. So we have feature parity, it's not lagging behind and this is also ease of support for us. >>So why was it, what was the motivation behind that was just customer demand? Um, more efficiency? What was the motivation behind moving on, supporting the on prem version? >>Uh, so for a start up, it's all about addressing the market share. Right? So you wanna have everything you can get, you don't want to spend any extra money on it. And as I said, the enterprise market is big. There are still many players that want to have the data in house. This is potentially sensitive data that's being tracked. So an on premise solution having, it was really instrumental to the success of in Stana because we were able to target and help those customers even in a fully adapt scenario, for example where they don't even have internet access. >>Take me through the process of DACA rising the product sitting on prime product that you get the thing going on there, like okay, let's do this. What does that look like? How did that work out? >>So as I said, we looked at this from the beginning and we picked DACA as a technology from the beginning, so there wasn't really like a shift and left type of scenario that other customers might be having. We were doing it from the beginning and we were aligning our architecture so that there are no fundamental differences between an on premise solution and anti size solution. That's of course configuration, that's different. But that configuration we just put into a single configuration file and that turned out to be a great idea because this is how you nowadays configure your application kubernetes, you'll make a customer resource for example, and then have an operator run the product, any kind of product, but also in stana, you run on premises with an operator that just works on the single configuration that you give it. And this is actually great because our customers are used to operating products like that, their own software, everything customers are running in dhaka in kubernetes, they are used to operating it that way. And that helped us because our customers now get the same functionality that we offer as a, as a service on premises very easily very quickly. And that make them happier. We talked about developer happiness that makes them happy because now they are not lagging behind but it also enables us to give better quality support, lot fixes faster and helps us to no longer support very old presence because they don't exist. They are frequently updated. I think this is really a benefit of container realization is also how easy it is to upgrade because you just stop apart and start a part in the new version and then you have a new verse. >>That's also great insights may be great to chat with you on that. I got to ask you on a personal note, you've been in the industry for a while and your leader, um you know, that's a performance geek, you'll have to build fast code. I was been chatting with other VPs of engineering and we were talking about the shift in engineering and with devops you've got kind of s our reaction, you have some just straight up application coding, just modernize that cloud native applications and you've got a kind of under the devoPS as the world's shifts. It seems like there's more of an architectural systems engineering approach or a systems mindset and that seems to be changing the mindset of a developer from Iterate fast. And then the line I heard was you can iterate and pump out code fast, but it might not be good, might be crap. So, so this notion of iterating code and crafting good product because with now this module Ization with containers, you're doing a lot more design work. So craft seems to be coming back to coding. Uh, I don't think it's coming back, it's been there, but it just seems more of like, hey, let's do this, right? And it's not just ship code. What's your take on that? >>So I think this always was there. It's just that traditionally companies approached software engineering similar to how companies approach manufacturing. So somebody writing a designs back and somebody verifying it and then it's going onto the line to mass production. But software doesn't work that way. We make way more changes, it's way harder to understand it up front. So the developed the iterative and exile development that has been ongoing is really, is really what people want and develops well. There is this notion of being a being waking up in the middle of the night and that's what developers don't want. So you need to prepare your application, you need to make it resilient against that. And developers are very eager to build in functionality that helps them to troubleshoot to make their application available. With a high rate of change. There is a high rate of risk as you said and I think the ability to deploy 1000 times per day is great but you don't necessarily need to do that. I think it's also important for your users that you find the right pace of when you deliver functionality and when you deliver fixes. >>I was just talking to a friend the other day and we were just talking about organizations and teams and yeah, we always riff on the the two pizza team or having more agility and you have this democratization because of the agility is also a benefit for any developer to add value if they have the right perspective or creativity. But it kind of disrupts the kind of the old way of thinking. I'm the principal engineer is my job. No, I'm the chief architect. So you have these titles and you have roles, the roles are changing and sometimes just the arguments. Oh wait, that's my job is that I'm this kind of changes. What's your thoughts on, how do you manage that dynamic? Because as you have more, uh, I won't say surface here more democratized engineering with virtual teams and whatnot You have compose ability with, with with code. You have more of a systems are a lot more going on. It's not your standard engineering mindset. What's your thinking on this as a leader in engineering and visionary? >>Well as we know the architecture of a software full of the organization that the company has. That creates. All right. So I think what you want when you want to have a micro service architecture, you want to have a micro service teams. You want to have teams, we call him at and standard delivery teams that work more or less independently on a certain set of features and are responsible for them and to end. So my engineers, they are talking to our customers figuring out how to make a feature better. They are then designing this with our user designers and then they are developing and deploying it and this really entry and responsibility. And we don't really have those titles like architect anymore. I think those roles are still there but it's more like a shared responsibility. So you of course want an architecture, you want to have your components talk to each other in an efficient way and it's more really communities of practice that are establishing. So you will find out that you have people and your teams who have specific skills who like to work on architecture. Some of them like to work on continuous delivery systems And then you you form those cross functional teams dynamically and when it's no longer hit this bands. And I think that's a major difference to assigning a person to a road. >>Yeah and and also that with you have new trends like observe ability, enterprise observe ability you know new things are happening um And new net new things like new architecture and also new roles and responsibilities. I'll see new patterns to with the data you have services being stood up and turned down all the time. You have a lot of dynamic environment. So you know having a happy developers one eliminate the manual work what you do but also giving them good work assignments to work on some good hard problems. So what is what are those hard problems that engineers like to work on these days? Is it like design? Is it coding? I mean I know it depends as you mentioned on the personalities but generally speaking as dev ops def sec Ops becomes much more of an agile edge hybrid play. What's the hard problem? >>I think big data is not really a new term but I think this is still a very interesting territory because you can apply various aspects to it. You have this data science aspect to it to understand how to detect pattern in it. And then automation is actually artificial intelligence. Right? So you automate data science and that's very interesting because those are large scale problems and new problems and new solutions. So yes there are existing frameworks but there's so much innovation to be found and making this work efficiently is another dimension of the same problem. That's also not easy and challenging problems. Make developers happy and then you can even have people think about the financial aspects. So it should also be cheap Big data and AI is usually very expensive because it requires so much hardware. So not only tried to make it fast but maybe even make it efficient. So this whole domain is very appealing. There is new technology to be invented, tough problems and I think that's really exciting to developed. >>Fabian Lang, vice president of engineering co founder and stand a great to have you on the q Great insight. Thank you for sharing that knowledge there. And the overview of installing here at dr khan observe ability very relevant for next gen next level solutions. Thanks for coming on the cube. Right, okay. I'm john Fury with the queue here. Dr khan 2021 coverage. Thanks for watching. Mm.

>> Presenter: From around the globe, it's theCUBE with digital coverage of IBM think2021 brought to you by IBM. >> Well, good to have you here on theCUBE. We continue our conversations here as part of the IBM Think initiative. I'm John Walls, your host here on theCUBE joined today by Mirko Novakovic, who is the co-founder and CEO of Instana which is an IBM company. Is specialized in enterprise observability for cloud native applications. And Mirko joins us all the way from Germany, near Cologne, Germany. Mirko, good to see it today. How are you doing? >> I'm good. Hi, John. Nice to meet you. >> You bet yeah. Thank you for taking the time today. First off, let's just give some definitions here. Enterprise observability. What is that? What are we talking about here? >> Yes observability is basically the next generation of monitoring, which means it provides data from a system, from an application to the outside, so that people from the outset can basically judge what's happening inside of an application. So think about you're a big e-commerce provider and you have your shop application and it doesn't work. Observability gives you the ability to really deep dive and see all the relevant metrics, logs and application flows to understand why something is not working as you would expect. >> So if I'm, or just listening to this, I think, okay, I'm monitoring my applications already right. I've got to APM and enforce and and I kind of know what things are going on. What's happening, where the hiccups are, all that. How, what is the enhancement here then in terms of observability taking, it sounds like you're kind of taking APM to a much higher level. >> Absolutely. I mean that's essentially how you can think about it. And we see three things that really make us Instana and enterprise observability different. And number one is automation. So the way we gather this information is fully automated. So you don't have to configure anything. We get inside of your code. We analyze the flow up the clarification we get the arrows, the logs and the metrics fully automatic. And the second is getting context. One of the problems with monitoring is if you have all these monitoring data silos so you have metrics on the one side locks into different tool. What we built is a real context. So we tie those data automatically together so that you get real information out of all the data. And the third is that we provide actions. So basically we use AI to figure out what the problem is and then automate things. Is it a problem resolution, restarting container or resizing your cloud? That's what we suggest automatically out of all the context and data that we gathered. >> So you're talking about automation, context, intelligence you'd combine all of that into one big bundle here then basically, that's a big bundle, right? I'm not a giant vacuum. If you will, you're ingesting all this information. You're looking for, you know, performance metrics. So you're trying to find problems. What's the complexity of tying all that together instead of keeping those functions separate you know, what are what's the benefit to having all that kind of under one roof then? >> Yeah. So from the complexity point of view for the end customer it's really easy because we do it automated. For us as a vendor building this it's super complex but we wanted to make it very easy for the user and I would say the benefit is that you get, we call it the meantime to repair like the time from a problem to resolve the problem gets significantly reduced because normally you have to do that correlation of data manually. And now with that context you get this automated by a machine and we even suggest you these intelligent actions to fix the problem. >> So, I'm sorry, go ahead. >> Yeah. And by the way, one of the things why IBM acquired us and why we are so excited working together with IBM is the combination of that functionality with something like Watson AIOps, because as I said we are suggesting an action and the next step is really fully automating this action with something like Watson AIOps and the automation functionality that IBM has. So that the end user not only gets the information what to do the machine even does and fix the problem automatically. >> Well, and I'm wondering too, just about the kind of the volume that we're dealing with these days in terms of software capabilities and data. You've got obviously a lot more inputs, right? A lot more interaction going on a lot more capabilities. You've got apps they're kind of broken down into microservices now. So, I mean, you've got you've got a lot more action, basically, right? You got a lot more going on and what's the challenge to not only keeping up with that but also building for the future for building for different kinds of capabilities and different kinds of interactions that maybe we can't even predict right now. >> Absolutely. Yeah. So I'm 20 years in that space. When I started, as you said it was a very simple system, right? You had an application server like WebSphere maybe a DB2 database so that was your application. It's like today applications are broken down into hundreds of little services that communicate with each other. And you can imagine if something breaks down in a system where you have two or three components it's maybe not easy, but it's handled by a human to figure out what the problem is. If you have a thousand pieces that are somehow interconnected and something is broken it is really hard to figure that out. And that's essentially the problem that we had to solve with the contacts, with the automation, with AI to figure out how all these things are tied together and then analyze automatically for the user where issues are happening. And by the way, that's also when you look into the future I think things will get more and more complicated. You can see now that people break down from microservice into functions, we get more server less. We get more into a hybrid cloud environment where you operate on premise and in multiple clouds. So things get more complex not less complex from an architectural perspective. >> You bring up clouds too. Is this agnostic, I mean, or do you work with an exclusive cloud provider or are you open for business basically? >> We are open for business but we have to support the different cloud technologies. So we support all the big public cloud vendors from IBM to Amazon, Google, Microsoft. But on the other hand, we see with enterprises maybe there's 10, 20% of the workload in the public cloud but the rest is still on premises. And there's also a lot of legacy. So you have to bring all this together in one view and in one context, and that's one of the things we do. We not only support the modern cloud native applications we also support the legacy on premise world so that we can bring that together. And that helps customer to migrate, right? Because if they understand the workload in the on-premise world it's easier to transform that into a cloud native world but it also gives an end to end view from the end user to we always say from mobile to mainframe, right? From a mobile app down to the mainframe application we can give you an end to end view. >> Yeah, you talk about legacy. In this case, you may be cloud services that people use but they're, but that, you know a lot of these legacy applications, right, too that are running, that are they're still very useful and still highly functional but at some point they're not going to be so would it be easier for you or what do you do in terms of talking with your clients in terms of what do they leave behind? What are they bringing with them? How, what kind of transition timeframe should they be thinking about? Because I don't think you want to be supporting forever, right? I mean, you want to be evolving into newer more efficient services and solutions. And so you've got to bring them along too, I would think. Right? >> Yeah. But to be really honest I think there are two ways of thinking. One is as a vendor you would love to support only the new technologies and don't have to support all the legacy technologies. But on the other hand, the reality is especially in bigger enterprises you will find everything in every word. And so if you want to give a holistic D view into the application stacks you have to support also the older legacy parts because they are part of the business critical systems of the customer. And yes, we suggest to upgrade and go into a cloud native world, but being realistic I think for the next decade we will have to live with a world where you have legacy and new things working together. I think that's just the reality. And in 10 years, what is new today is legacy then, right? >> John: Right exactly. >> So we will always live in a kind of hybrid world between legacy and new things. >> Yeah, you've got this technological continuum going on right? That you know, what's new and shiny today's is going to be, you know old hat in five years. But that's the beauty of it all obviously >> Yes. >> Now talk about AIOps. I mean, go into that relationship a little bit if you would , I mean eventually what is observability set you up to do in terms of your artificial intelligence operations and what are the capabilities now that you're providing in terms of the observability solutions that AIOps can benefit from? >> Yeah, so the way I think about these two categories is that observability is the system of record. That's where all the data is collected and put into context. So that's what we do as Instana is we take all the data metrics, logs, traces, profiles and put it into our system of record by the way in very high granularity, it's very important. So we do not sample, we have second granularity metrics. So very high quality data in that system of record where AIOps is the system of action. This is the system where it takes the data that we have, applies machine learning, statistical analytics et cetera, on it, to figure out, for example root cause of problems or even predict problems in the future, and then suggests actions, right? What the next thing that AI does is it suggests or automates an action that you need to do to to for example, scale up the system, scale down the system scaling down because you want to save costs for example these are all things that are happening in the system of action, which is the AIOps space. >> When I think about what you're talking about in terms of observability, I think, well, who needs it? Everybody is probably the answer to that. Can you give us maybe just a couple of examples of some clients that you've worked with in terms of particular needs that they had, and then how you applied your observability platform to provide them with these kinds of solutions? >> Yeah. I remember a big e-commerce vendor in the US approaching us last October. They were approaching the black Friday, right? Where they sell a lot of goods and they had performance issues but they only had issues with certain types of customers and with their existing APM solution, they couldn't figure out where the problem is because existing solutions sample which means if you have a thousand customers you only see one of them as an example because the other 999 are not in your sample. And so they used us because we don't sample. With us, if you have, they have more than a billion requests today you see every of the 1 billion requests and after a few days they had all the problems figured out. And that's what, that was one of the things that we really do differently is providing all the needed data, not sampling and then giving the context around the problem so that you can solve issues like performance issues on your e-commerce system easily. So they switched and you can imagine switching assistant before black Friday, you only do that if it's really needed. So they were really under pressure and so they switched their APM tool to Instana to be able to fulfill the big demand they have on these black Friday days. >> All right, before I let you go you were just saying they had a high degree of confidence. How were you sweating that one out? Because that was not a small thing at all I would assume. >> Yes. It's not a small thing and to be honest, also it's very hard to predict the traffic on black Fridays. Right? And in this case, I remember our SRE team. They had almost 20 times the traffic of a normal day during that black Friday. And because we don't sample, we need to make sure that we can handle and process all these traces but we did we did pretty well. So I have a high confidence in our platform that we can really handle a big amounts of data. We have one of the biggest companies in the world. The biggest companies in these worlds they use our tool to monitor billions of requests. So I think we have proven that it works. >> Yeah, I would say you're smiling too about it. So I think it, obviously it did work. >> It did work, but yeah, I'm sweating still. Yeah. (laughs) >> Never let them see you, sweat Mirko. I think you're very good at that. And obviously very good at enterprise observability. It's an interesting concept. Certainly putting it well under practice. And thanks for the time today to talk about it here as part of IBM thing to share your company's success story. Thank you Mirko. >> Thanks for having me John. >> All Right. We've been talking about enterprise observability here. IBM Think, The initiative continues here on theCUBE. I'm John Walls and thank you for joining us. (soft music)

>>From around the globe. It's the cube with digital coverage of IBM. Think 20, 21 brought to you by IBM, everybody welcome back to the cubes. Continuous coverage of IBM think 20, 21, the virtual edition. My name is Dave Volante, and we're going to talk about observability, front and center for DevOps and developers. Things are really changing. We're going from monitoring and logs and metrics and just this mess. And now we're bringing in AI and machine intelligence and with us as Pablo Baron, who's the CTO of Instana, which is an IBM company that IBM acquired November of 2020 Pablo. Great to see you. Thanks for joining us from Munich. >>Thanks for having me. Thanks a lot. >>You're very welcome. So, you know, I always love to talk to founders and co-founders and try to understand sort of why they started their companies and congratulations on the exit. That's awesome. After, you know, five, five, I'm sure. Grinding, but relatively short years. Uh, why did you guys start in Stoneleigh and what were some of the trends that you saw and that you're seeing now in the observability space? >>Yeah, that's a very good question. So, um, the journey began, uh, as we worked in the company called code centric, the majority of the founders, and, uh, we actually specialized in troubleshooting, um, well, real hard customer performance problems. We used all different kinds of APM solutions for that. You know, we we've built expertise, uh, like, uh, collectively, maybe 300 years of the whole company. So we will go from one, um, adventure into the other and see customers suffer and to help them, you know, overcome this trouble. At some point we started seeing architectures, uh, coming up that were not well covered by the classic APM solutions. Like people went off to the suit, a suit, a suit of the virtualization, all in containers, you know, just dropping random, uh, workloads into container running this maybe in Cubanitos. Well, not, not actually not five, six ago but years ago, but you get the point we started with having continued containerization. >>And we've seen that a classic APM solution that is having the, you know, like machine oriented. And then, uh, some of them even counted by the number of CPU, et cetera, et cetera. The world very well suited for this plus all of the workloads are so dynamic. They keep coming and going. You cannot really, you know, place your agent there that is not adapting to change continuously. We've seen this coming and we really we've seen the trouble that we cannot really support the customers properly. So after looking around, we just said, Hey, uh, it's time to just implement the new one, right? This is, we started that adventure with the idea of a constant change to the AGL. If everything is containers with idea of everything goes towards cloud native people just, uh, run random, uh, um, workloads of all different versions that are linked all together that this whole microservices trend came up where people would just break down their model and resilience of, uh, literally very small components that could be deployed independently. Everything keeps changing all the time. The classic solution cannot keep up with it, >>Pick it up from there if I can. So it's interesting. Your timing is quite amazing because as you mentioned, it really wasn't cute Kubernetes when you started in the middle part of last decade, like containers have been around for a long time, but Coobernetti's, weren't that wasn't mainstream back then. So you had some foresight, uh, and, and the market has just come right into your vision, but, but maybe talk a little bit about the way APM used to work. It was, I started this talk about this. It was metrics, it was traces, it was logs. It was make your eyes bleed type of type of stuff. Um, and maybe you could talk about how, how you guys are different and how you're accommodating the rapid changes in the market today. >>Right? So, well, there is very, very many pieces to this. So first of all, we always have seen that the work that you should not be doing by hand, I mean, we already said that you should not be doing this and you shouldn't be automating as much as possible. We see this everywhere in the it industry that everything gets more and more automated and want to automate it through the whole continuous delivery cycle. Unfortunately, monitoring was the space that probably never was automated before installer came into place. So our idea was, Hey, just, just get rid of the unnecessary work because you keep people busy with stuff that they should not be doing, like manually watching dashboards, setting up agents, uh, with every single software change, like adopting configuration, et cetera, et cetera, et cetera, all of these things can be done automatically, you know, to very, very, very large extent. >>And that's what we did. We, we did this from the beginning, everything we approach, uh, we, we, we think twice about, uh, can we automate, you know, the maximum out of it. And only if we see that it's, it's, you know, too much in effort, et cetera, we will, we will problem in onto this, but otherwise we're not, we don't do this. And yet, you know, you can compromise the other, right? The other aspect is, so this is different to the classic APM world that is typically very expert heavy. The expert comes into, you know, into the project and really starts configuring, et cetera, et cetera, et cetera. This is, this is a totally different approach. The other approach is continuous change and, uh, you know, adapting to the continuous change container comes up. You need to know what this kind of workload, what kind of workload this thing is, how it is connected to all the others. >>And then at some point, probably it's gonna, it's gonna, you know, go through the change and get a new version, et cetera, et cetera. You need to capture this whole life cycle without really changing your monitoring system. Plus if you move your workloads from the classic monolith through microservices onto cause the need is you kind of trans transitioning, you know, it's a journey in this journey. You want to keep your business abstractions as stable as possible. The term application is nothing that you should be reconfiguring. Once you figured out what is payments in your system? This is a stable obstruction. It doesn't matter if you deliver it on containers. It doesn't matter if this is just a huge, you know, JVM that owns the whole box alone. It simply doesn't matter. So we, we decoupled everything infrastructure from everything logic and, uh, the foundation for this is what we call the dynamic graph. >>It's technically, it's pretty much a data structure. The regular route, the dispatcher would do no connections, uh, in, in, in multiple directions, from different nodes. But the point is that we actually decompose the whole it geography. This is the term I like to use because there is, there is no other it's infrastructure. It's typology. It is on the other hand, just, you know, same sides of the same thing. When you have a Linux process, it can be a JVM. It just, at the same time, it can be a problem with application. It's the same thing. I can give a different names and this different, you know, facets of this thing can be linked with everything else in a different way. So we're decomposing this from the beginning of the product, which allows us to, to have a very deep and hierarchical understanding of the problem when it appears so we can nail it, not down to a metric that probably doesn't make sense to any user, but really name the cause by look in this JVM, the drop wizard metric XYZ that is misbehaving. >>This indicates that this particular piece of technology is broken and here's how it's broken. So there's a built in explanation to a problem. So, um, the cloud, the classic APM, as I said, it is a very expert, heavy, um, uh, territory. We try to automate the expert. We have this guy called Stan. This is your, you know, kind of, uh, virtual dev ops engineer has AI in there. It has some, some artificial brain. It never sleeps. It observes all of the problems. It really is an amazing guy because nobody likes them because he always tells you what's broken. You don't need to invite them to the body and give them a raise. They're just there and conserving the system. >>I liked Stan. I liked Stan better than Fred. No offense to Fred, but Fred's is the guy in the lab coat that I have to call every time to help me fix my, and what you're describing is end to end visibility or observability, uh, in, in terms that the normal either normal people can understand, or certainly Stan can understand and can automate. And that kind of leads me to this notion of, of anti-patterns. Um, getting in software, we think of anti-patterns is, you know, you have software hairballs and software bloat. You've got stovepipe systems. You're, you're a data guy by background. And so you will understand, you know, stovepipe data systems, there's organizational examples of, of, of anti-patterns like micromanagement or over-analyze analysis by paralysis. If you will, how do anti-patterns fit into this world of observability? What do you see? >>Oh, there is many, I could write a whole book actually about that. Um, let, let me just list a few. So first of all, it is valid for any kind of automation. What you can automate, you should not be doing by hand. This is a very common pattern. People are just doing work by hand, just because the lazy where you know, like repetitive work or there is no kind of foundation to automate the, whatever, the reason, this is clearly an impact pattern. What we, what we also see in the monitoring space are very interesting things like normally since the problems in the observability and monitoring space are so hard, you would normally send your best people, watching rats want them to contribute to the business value rather than waste the time of serving charts. That's like 99% of them are marble. The other aspect of course, is what we also have seen is the other side of the spectrum where people just send total mobilizes into the, into the problem of ops observability and let them learn on the subject, which is also not a good thing, because you can not really, I mean, there are so many unknown unknowns for people who are not experts in this space. >>They will not catch the problem. You will go through pain, right? So it's not a learning project. It's not the research from a project. This is very essential to the operation of your business and to it. And there's many examples like that, >>Right? Yeah. So I want to end by just sort of connecting the dots. So this makes a lot of sense. And if you think about, you know, Auburn Christian said that IBM has got to win the architectural battle for hybrid cloud. And when I think of hybrid cloud, I think of on-prem connecting to public cloud, not only the IBM public cloud, but other public clouds going across clouds, going to the edge, bringing OpenShift and Kubernetes to the edge and developing new, supporting new workload. So as it is like the university keeps expanding and it gets more and more and more complicated. So to your point, humans are not going to be able to solve the classic performance problems in the classic way. Uh, they're going to need automation. So it really does fit well into IBM's hybrid cloud strategy, your, your thoughts, and I'll give you the last word. >>Yeah, totally. I mean IBM generally is of course, very far ahead in, in regards to AI and all these things, this desk, sorry, those could be combined within standard, very, very, you know, natively, right. We, we are prepared to automate using AI all of the, well, I would want to claim that all of the monitoring observability problems, of course there is manual work in some, uh, you know, in some cases you simply don't know what people want to observe, so you kind of need to give them names and that's what people come in, but this is more a creative work. Like you don't want to do the stupid work with people. It doesn't, you know, there is no, it doesn't make any sense. And IBM of course, um, requiring and Stan, I guess, you know, the foundation for all of the things that that used to be done by, by hand now fully automated, combined within starlet, combined with Watson AI ops. This is, this is huge. This is a real great story. Like the best research at the world meeting, uh, probably the best APM summit. >>That's great. Uh, Pablo really appreciate you taking us through and Stata and the trends and observability and what's going on at IBM and congratulations on your success. And thanks for hanging with us with all the craziness going on at your abode and, uh, really, it was a pleasure having you on. Thank you. Thanks a lot. Thank you for watching everybody. This is Dave Volante and the ongoing coverage of IBM. Think 2021. You're watching the cube.

>>Welcome back. You're watching the cubes coverage of AWS 2021. We're here in the Venetian, formerly the sands convention center in Las Vegas. My name is Dave Volante. Really excited to have Bob bright tell here. He's the director of SAP global alliances at IBM and Manu.. I'm going to try that again. Pro boxcar, is that correct? Rebecca Head of Linux and IBM alliances at AWS Manu. I'm sorry for bashing your name, but at least I got it right, guys. Great to see you. Thanks for coming on. >>And I'm actually now AWS partnership. I had SAP before, so it's great. I first, my first reinvest, >>I have a old DNA title. That's great. That's why I was asking you about Philly before you don't have the accent though. Bob, >>I'm not a Philly native, so cowboy >>Because you have the SAP connection there. IBM, AWS. It's like, whoa, what's going on here? >>Well, maybe I'll start and then have my new, my new, make some comments. And I'll just start by just, uh, we're real excited to be here. IBM's a diamond sponsor at, at re-invent and it's great to be in person and really appreciate AWS being able to put this event on this week and get us back in person. It really makes a difference. And I know there's a lot of people virtually as well, but, um, IBM and AWS have worked together for a number of years. Uh, maybe we could characterize it more opportunistically, um, prior, but in the last 12, 18 months, I think there's been a lot of developments that have really made us come together strategically as partners. I know we'll talk a little bit about red hat during the course of the conversation, but with IBM's >>You say opportunities like you mean in the field and the more strategic >>Relationship or strategic and with IBM's open hybrid cloud strategy. And, uh, with so many of our clients preferring AWS is their cloud. Um, we are working together now to meet clients where they're at to help them get the value of the cloud. And we're talking a little bit about coming out of the pandemic before this. Um, and one of the things that we're seeing with our clients that IBM is a lot of that low hanging fruit. The cloud was achieved, maybe the lift and shift or doing some SAS based applications, but now it's even more important to rapidly adopt hybrid cloud and cloud technologies to provide your business with flexible innovation transformation, all of those things. So that's why it has been important for us to, to partner with AWS strategically. Um, our clients are telling us that when they do move those heavier workloads to the cloud and do it in a hybrid model, they see about two and a half times the value. >>So with that, our partnership is multi-dimensional, we're doing a lot with IBM consulting. My new we'll talk a little bit about IBM software and red hat. Just one example, Dave, with IBM consulting, we now are up to almost 10,000 certifications and 10 plus AWS competencies. So that competency chart that shows we're knocking them all out on the, on the checkerboard there to get them to IBM consulting competencies. And we just had the energy one announced this week. So IBM consulting is in area software's big too. In my news, been helping us with that part of the partner. >>Well, it's, you know, to your point, you can't pick whatever cliche you want. You can't fight fashion. The trend is your friend. You have a lot of, a lot of people want to be on AWS. So rather than fighting, oh, we have our own cloud. No, you've got to meet customers where they are, right >>David, this is where this takes us. You know, the analogy we use between Bob and I, IBM boss spoke about IBM consulting, which we know has been a strategic partnership for the last two, two and a half years. I think I'm going to share the best kept secret in the cloud phase right now. IBM software and AWS now are working together. The analogy we use is IBM software and AWS. I like peanut butter and jelly better together. And over the last 12 months, the two companies have accelerated working together around three key dimensions. Number one, around product, number two around making sure our customers, joint customers successful. And number three, around building a robust ecosystem of partners. One thing that we have realized is just helping customers modernize. Migrate is challenging. And on the product side, now we have about 15 products on AWS marketplace. >>I think about trusty or verify insecurity, cloud Pak for data, uh, uh, Cognos data DataStage over the next 12 months, we plan to land all of the cloud packs. These are containerized version of IBM software on AWS and the marketplace. In addition, many of our customers are now using the managed red hat, OpenShift servers. We launched it earlier in April. This year, we are seeing tremendous customer feedback, tremendous, uh, growth there that is also informing that customers really like the open shirt model managed services one-click deployment. And so our goal is over the next 12 months, launched many more IBM software as a managed service offering. So that's kind of like what we're doing on the product side, on the customer success. A great example is somebody is helping a big oil and gas customers managed with this energy transition that we're working through. Um, Schlumberger software around simulation runs on OpenShift on Amazon in a hybrid environment, especially critical as we have a lot of oil and gas data that needs to have maybe sit on premises, uh, because of data residency requirements. >>I think the third piece is around building an ecosystem of partners for our red hat OpenShift services, which we launched April. We already have 30 partners that are helping customers not only to modernize, but to migrate on AWS. We know modernization is challenging, moving to containers is difficult. So we need this robust ecosystem of partners and Bob and I, and you know, the IBM and AWS team are investing heavily. We have cash credit to do financial incentives plus also technical content so that our customers so that our partners can help customers to be successful. Yeah, >>So the cloud packs are cool. That makes a lot of sense. And now the acquisition of red hat makes it easier. It's a catalyst gets IBM, much more closely aligned to developers and it makes it easier for things like cloud packs to be migrated to the cloud and being running cloud native. How did that acquisition affect from your standpoint menu and Bob I'd love your thoughts and your relationship. >>The red hat acquisition by IBM is a net positive red hat. And AWS have been working together for 14 years now. And we have tens of thousands of customers that are running mission critical workloads, such as SAP, Oracle databases. And there's a lot of trust that is engendered by working in the field for 14 years, uh, supporting mission critical customers, mission critical workloads. And so that relationship has provided a lot of tailwinds to our partnership with IBM software. I think a lot of the stuff we spoke about a lot of the progress you've made in the last six to eight to 12 months, a big function is that the trust that we have engendered working together with red hat. >>Yeah. I'll add Dave that, um, I, I agree with my new comments on the red hat. Red hat really is the epitome of openness right. Of open source software and the history that Manu described with AWS, there has been excellent adoption of red hat on AWS, red hat, enterprise Linux, and then most recently, um, red hat OpenShift on AWS. And just to give another example to the ecosystem point, just this morning, red hat with IBM, with a major ISV named Solonus announced that Solonus will be running one of their key, uh, applications and releasing it on Rossa on AWS. And all this means for our clients is faster adoption and acceleration and being able to innovate, um, in a hybrid way. So that's really the value that red hat is helping, um, to bring to the table in our cloud packs are available on open shift and rose as an option as well. So we're excited about the red hat partnership. It's really essential to our partnership into our, our hybrid cloud strategy. >>You mentioned up front, you know, happy that AWS decided to have this show. Of course, a lot of people watching online and you can get massive scale online, but there's nothing like the live event, you know, and when you make announcements at a live event, there's a little buzz going on and you get feedback. So are you making any hard news here? What, what announcements can you >>Share? Yeah, well, the one we had, um, on, um, uh, Solonus earlier with red hat and to do roasts on top of red hat was one and there's just an advance of, um, of re-invent. Um, we announced something in the data and AI space. So that's another big area of our partnership is data and AI. So we're in, we announced that in the oil industry and in the, um, uh, in that area that we are partnering together with AWS to be able to get insights on data so that we could get clean and reusable energy solutions out there. And there's so much untapped data. We know data is such an important resource, that that's an area that we're going to partner on with our cloud Pak for data on AWS. And of course underlying everything is open shifts. So that's one big announcement. We're also doing a lot in security for IBM and my news has been working closely with this. So my new, I, I know you're close to the integrations we're doing with AWS. So I'll let you comment maybe on some of the things in security. >>I mean, everybody's a security company these days, right? I mean, >>And then we continue to work and making sure that a lot of the IBM security products are integrating with our native services. So the customers have a seamless experience. And as he you'll see a lot of the same investments happening over 2022 as we grow the >>Partnership. So what like a QRadar or something like that >>Are, for example, integrating with security hub. That would be great example. >>I mean, it's the, it's the number one topic for CEO's that has been for a while and still will be okay. So give us a little roadmap, you know, maybe Bob, you could start, where do you want to see this relationship go? Um, what can we expect in the, in the coming 12 months? Yeah, well, >>Again, we're super excited about our partnership with AWS. I think we're just scratching the surface of how we're going to add value to our clients on this, on this hybrid cloud journey that they're all going through. And IBM, and this has been in our financial reports and in our earnings and everything, we're investing over a billion dollars in the ecosystem. And so partners like AWS are critical to provide that platform of growth for our clients and innovation for our clients. So all of the things that I talked about in money talked about today, whether it be our IBM consulting capabilities or our IBM software, our red hat, we're going to continue to invest. We talked about the red hat acquisition. IBM has made a few other acquisitions that help drive this partnership and drive value to our clients for adoption, from Instana to Turbonomic X, to some really innovative cloud consulting companies like Knorr cloud in towels. So we're going to continue to make investments. And I think we're just on the tip of the iceberg and we invite everybody at re-invent, either in person, which is exciting or virtually to learn more about our partnership and how we can help you and my new, any additional comments to that. >>Thanks, Bob V have a golden child hair with red hat OpenShift on Amazon. That'd be launched in April. We are seeing tremendous customer adoption. So we suspect that in next year, we'll continue to see solid adoption around red hat OpenShift. That VocaliD is also informing how customers want a more native experience for IBM software on AWS. And so we, um, we are targeting to, to launch many more IBM software in a native format on edema. So that would be the big team for next year. Uh, in addition, again, I'll call to action to our partner community. There's a huge opportunity to help our joint customers to modernize and migrate on AWS via both IBM, AWS are leaning in, we have cash credit to give financial incentives to partners, to help our customers, to migrate and modernize as well as we are also creating a lot of technical content that is not freely available so that a lot of our partners can start this. IBM focus on AWS practice >>Guys. Thanks so much for coming on the cube. Congratulations, and look at, you know, I often say the next 10 years is not going to be like the last 10 years. The cloud is expanding is a really good example. So thank you for your time. Appreciate your time. All right. You're watching the cube, the leader in high tech coverage at AWS reinvent 2021

>> Voice Over: From around the globe. It's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Okay. Welcome back everyone. To theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, host of theCUBE. We've got a great segment here on the power of hybrid cloud and AI. And I'm excited to have Rob Thomas, Senior Vice President of IBM's cloud and Data platform, CUBE alumni. Been on going back years and years talking about data. Rob, great to see you, a leader at IBM. Thanks for joining. >> John. Great to see you hope everybody is safe and well and great to be with you again. >> Yeah, love the progress, love the Hybrid Cloud distributed computing, meets operating systems, meets modern applications at the center of it is the new cloud equation. And of course data continues to be the value proposition as the platform. And as you quoted many times and I love your favorite quote. There's no AI without IA. So you got to have the architecture. So that still rings true today and it's just so evergreen and so relevant and cooler than ever with machine learning and AI operations. So let's just jump in. IBM's announced, host a new products and updates at Think. Tell us what you're most excited about and what should people pay attention to. >> Maybe I'll connect two thoughts here. There is no AI without IA, still true today. Meaning, customers that want to do AI need an information architecture. There was an IDC report just last year that said, "Despite all the progress on data, still 90% of data in organizations is either unused or underutilized." So what's amazing is after all the time we've been talking John, we're still really just getting started. Then that kind of connects to another thought, which is I still believe that AI is not going to replace managers, but managers that use AI will replace the managers that do not. And I'd say that's the backdrop for all the announcements that we're doing this week. It's things like auto SQL. How do you actually automate the creation of SQL queries in a large distributed data warehouse? It's never been done before, now we're doing it. It's things like Watson Orchestrate which is super powers in the hands of any business user, just to ask for something to get done. Just ask for a task to get completed. Watson Orchestrator will do that for you. It's maximo mobile. So anybody working in the field now has access to an AI system on their device for how they're managing their assets. So this is all about empowering people and users that use these products are going to have an advantage over the users that are not, that's what I'm really excited about. >> So one of the things that's coming out as Cloud Pak for Data, AI powered automation these are kind of two that you kind of touched upon the SQL thing their. Cloud Pak is there, you got it for Data and this automation trend. What is that about? Why is it important? Can you share with us the relevance of those two things? >> Let's talk broadly about automation. There's two huge markets here. There's the market for RPA business process, $30 billion market. There's the market for AIOps, which is growing 22%, that's on its way to $40 billion. These are enormous markets. Probably the biggest bet IBM has made in the last year is in automation. Explicitly in Watson AIOps. Last June in Think we announced Watson AIOps, then we did the acquisition of Instana, then we announced our intent to acquire Turbonomic. At this point, we're the only company that has all the pieces for automating how you run your IT systems. That's what I mean when I say AIOps. So really pleased with the progress that we've made there. But again, we're just getting started. >> Yeah. Congratulations on the Turbonomic. I was just commenting on that when that announced. IBM buying into the Cloud and the Hybrid cloud is interesting because the shift has happened. It's Public Cloud, it's on premises as Edge. Those two things as a system, it's more important ever than the modernization of the apps that you guys are talking about and having the under the cover capabilities. So as Cloud and Data merge, this kind of control plane concept, this architecture, as you'd said IA. You can't have AI without IA. What is that architecture look like? Can you break down the elements of what's involved? I know there's predictive analytics, there's automation and security. What are the pillars of this architecture? What are the four concepts? If you can explain that. >> Yeah, let's start with the basics. So Hybrid Cloud is about you build your software runs once and you run it anywhere you want, any public cloud,any private cloud. That assumes containers are important to the future of software. We are a hundred percent convinced that is true. OpenShift is the platform that we build on and that many software companies in the world are now building on because it gives you portability for your applications. So then you start to think about if you have that common fabric for Hybrid Cloud, how do you deliver value to customers in addition to the platform? To me, that's four big things. It's automation, we talked about that. It's security, it's predictions. How do you actually make predictions on your data? And then it's modernization. Meaning, how do you actually help customers modernize their applications and get to the Cloud? So those are the things we always talk about, automate, secure, modernize, predict. I think those are the four most important things for every company that's thinking about Cloud and AI. >> Yeah, it's interesting. I love the security side is one of the big conversations in AIOps and day two operations or whatever it's called is shifting left, getting security into the Cloud native kind of development pipeline. But speaking of secure, you have a customer that was talking about this Dow Chemical. About IB empowering Dow zero trust architecture. Could you explain that deal and how that's working? Because that's again, huge enterprise customer, very big scale at scale, zero trust is big, part of it. What is this? >> Let's start with the basics. So what is zero trust mean? It means to have a secure business, you have to start with the assumption that nothing can be trusted. That means you have to think about all aspects of your security practice. How do you align on a security strategy? How do you protect your data assets? How do you manage security threats? So we always talk about a line, protect, manage back to modernize, which is how do you bring all your systems forward to do this? That's exactly what we're doing with the Dow as you heard in that session, which is they've kind of done that whole journey from how they built a security strategy that was designed with zero trust in mind, they're protecting data assets, they're managing cyber threats in real time with a relatively low number of false positives which are the issue that most companies have. They're a tremendous example of a company that jumped on this and has had a really big impact. And they've done it without interfering with their business operations, meaning anybody can lock everything down but then you can't really run your business if you're doing that. They've done it, I think in a really intelligent way. >> That's awesome. We always talk about the big waves. You always give great color commentary on the trends. Right now though, the tsunami seems to be a confluence of many things coming together. What are some of the big trends in waves you're seeing now specifically on the tech side, on the technology side, as well as the business side right now? 'Cause coming out of post COVID, it's pretty clear cloud-native is powering a new growth strategy for customers. Dow was one of them, you just commented on it but there's a bigger wave happening here, both on the tech theater and in the business theater. Can you share your views on and your opinions and envision on these trends? >> I think there's three profound trends that are actually pretty simple to understand. One is, technology is going to decentralize again. We've always gone from centralized architectures to decentralized. Mainframe was centralized, internet mobile decentralized. The first version of public cloud was centralized, meaning bringing everything to one place. Technology is decentralized and again, with Hybrid Cloud, with Edge, pretty straight forward I think that's a trend that we can ride and lead for the next decade. Next is around automation that we talked about. There was a McKinsey report that said, "120 billion hours a year are going to be automated with things like Watson Orchestrator, Watson AIOps." What we're doing around Cloud Pak for automation, we think that time is now. We think you can start to automate in your business today and you may have seen the--example where we're doing customer care and they're now automating 70% of their inbound customer inquiries. It's really amazing. And then the third is around data. The classical problem, I mentioned 90% is still unused or underutilized. This trend on data is not about to slow down because the data being collected is still multiplying 10 X every year and companies have to find a way to organize that data as they collected. So that's going to be a trend that continues. >> You know, I just kind of pinched myself sometimes and hearing you talk with some of our earlier conversations in theCUBE, people who have been on this data mindset have really been successful because it's evolving and growing and it's changing and it's adding more input into the system and the technology is getting better. There's more cloud scales. You mentioned automation and scale are huge. And I think this really kind of wakes everyone up. And certainly the pandemic has woken everyone up to the fact that this is driving new experiences for users and businesses, right? So this is, and then those experiences become expectations. This is the classic UX paradigm that grows from new things. So I got to ask you, with the pandemic what is the been the most compelling ways you seen people operate, create new expectations? Because new things are coming, new big things, and new incremental things are happening. So evolution and revolutionary capabilities. Can you share some examples and your thoughts? >> We've collected a decent bit of data on this. And what's interesting is how much AI has accelerated since the pandemic started. And it's really in five areas, it's customer care that we talked about, virtual agents, customer service, how you do that. It's employee experience. So somewhere to customer care but how do you take care of your employees using AI? Third is around AIOps, we talked about that. Fourth is around regulatory compliance and fifth is around financial planning and budgeting. These are the five major use cases of AI that are getting into production in companies over the last year that's going to continue to accelerate. So I think it's actually fairly clarifying now that we really understand these are the five big things. I encourage anybody watching, pick one of these, get started, then pick the second, then pick the third. If you are not doing all five of these, 12, 18, 24 months from now, you are going to be behind. >> So give us an example of some things that have surprised you in the pandemic and things that blew you away. Like, wow, I didn't see that coming. Can you share on things that you've seen evolve? Cause you're a year ahead of the business units of Cloud and Data, big part of IBM and you see customer examples. Just quickly share some notable use cases or just anecdotal examples of just things that jumped out at you that said, "Wow, that's going to be a double-down moment or that's not going to be anymore." Exposes, the pandemic exposes the good, bad and the ugly. I mean, people got caught off guard, some got a tailwind, some had a headwind, some are retooling. What's your thoughts on what you can you share any examples? >> Like everybody, many things have surprised me in the last year. I am encouraged at how fast many companies were able to adjust and adapt for this world. So that's a credit to all the resiliency that they built into their processes, their systems and their people over time. Related to that, the thing that really sticks out to me again, is this idea of using AI to serve your customers and to serve your employees. We had a hundred customers that went live with one of those two use cases in the first 35 days of the pandemic. Just think about that acceleration. I think without the pandemic, for those hundred it might've taken three years and it happened in 35 days. It's proof that the technology today is so powerful. Sometimes it just takes the initiative to get started and to do something. And all those companies have really benefited from this. So it's great to see. >> Great. Rob, great to have you on. Great to have your commentary on theCUBE. Could you just quickly share in 30 seconds, what is the most important thing people should pay attention to and Think this year from your perspective? What's the big aha moment that you think they could walk away with? >> We have intentionally made this a very technology centric event. Just go look at the demos, play with the technology. I think you will be impressed and start to see, let's say a bit of a new IBM in terms of how we're making technology accessible and easy for anybody to use. >> All right. Rob Thomas, Senior Vice President of IBM cloud and Data platform. Great to have you on and looking forward to seeing more of you this year and hopefully in person. Thanks for coming on theCUBE virtual. >> Thanks, John. >> Okay. I'm John Furrier with theCUBE. Keep coverage of IBM Think 2021. Thank you for watching. (soft music)

(soft music) >> Voice Over: From around the globe. It's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Okay. Welcome back everyone. To theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, host of theCUBE. We've got a great segment here on the power of hybrid cloud and AI. And I'm excited to have Rob Thomas, Senior Vice President of IBM's cloud and Data platform, CUBE alumni. Been on going back years and years talking about data. Rob, great to see you, a leader at IBM. Thanks for joining. >> John. Great to see you hope everybody is safe and well and great to be with you again. >> Yeah, love the progress, love the Hybrid Cloud distributed computing, meets operating systems, meets modern applications at the center of it is the new cloud equation. And of course data continues to be the value proposition as the platform. And as you quoted many times and I love your favorite quote. There's no AI without IA. So you got to have the architecture. So that still rings true today and it's just so evergreen and so relevant and cooler than ever with machine learning and AI operations. So let's just jump in. IBM's announced, host a new products and updates at Think. Tell us what you're most excited about and what should people pay attention to. >> Maybe I'll connect two thoughts here. There is no AI without IA, still true today. Meaning, customers that want to do AI need an information architecture. There was an IDC report just last year that said, "Despite all the progress on data, still 90% of data in organizations is either unused or underutilized." So what's amazing is after all the time we've been talking John, we're still really just getting started. Then that kind of connects to another thought, which is I still believe that AI is not going to replace managers, but managers that use AI will replace the managers that do not. And I'd say that's the backdrop for all the announcements that we're doing this week. It's things like auto SQL. How do you actually automate the creation of SQL queries in a large distributed data warehouse? It's never been done before, now we're doing it. It's things like Watson Orchestrate which is super powers in the hands of any business user, just to ask for something to get done. Just ask for a task to get completed. Watson Orchestrator will do that for you. It's Maximo Mbo. So anybody working in the field now has access to an AI system on their device for how they're managing their assets. So this is all about empowering people and users that use these products are going to have an advantage over the users that are not, that's what I'm really excited about. >> So one of the things that's coming out as Cloud Pak for Data, AI powered automation these are kind of two that you kind of touched upon the SQL thing their. Cloud Pak is there, you got it for Data and this automation trend. What is that about? Why is it important? Can you share with us the relevance of those two things? >> Let's talk broadly about automation. There's two huge markets here. There's the market for RPA business process, $30 billion market. There's the market for AIOps, which is growing 22%, that's on its way to $40 billion. These are enormous markets. Probably the biggest bet IBM has made in the last year is in automation. Explicitly in Watson AIOps. Last June in Think we announced Watson AIOps, then we did the acquisition of Instana, then we announced our intent to acquire Turbonomic. At this point, we're the only company that has all the pieces for automating how you run your IT systems. That's what I mean when I say AIOps. So really pleased with the progress that we've made there. But again, we're just getting started. >> Yeah. Congratulations on the Turbonomic. I was just commenting on that when that announced. IBM buying into the Cloud and the Hybrid cloud is interesting because the shift has happened. It's Public Cloud, it's on premises as Edge. Those two things as a system, it's more important ever than the modernization of the apps that you guys are talking about and having the under the cover capabilities. So as Cloud and Data merge, this kind of control plane concept, this architecture, as you'd said IA. You can't have AI without IA. What is that architecture look like? Can you break down the elements of what's involved? I know there's predictive analytics, there's automation and security. What are the pillars of this architecture? What are the four concepts? If you can explain that. >> Yeah, let's start with the basics. So Hybrid Cloud is about you build your software runs once and you run it anywhere you want, any public cloud,any private cloud. That assumes containers are important to the future of software. We are a hundred percent convinced that is true. OpenShift is the platform that we build on and that many software companies in the world are now building on because it gives you portability for your applications. So then you start to think about if you have that common fabric for Hybrid Cloud, how do you deliver value to customers in addition to the platform? To me, that's four big things. It's automation, we talked about that. It's security, it's predictions. How do you actually make predictions on your data? And then it's modernization. Meaning, how do you actually help customers modernize their applications and get to the Cloud? So those are the things we always talk about, automate, secure, modernize, predict. I think those are the four most important things for every company that's thinking about Cloud and AI. >> Yeah, it's interesting. I love the security side is one of the big conversations in AIOps and day two operations or whatever it's called is shifting left, getting security into the Cloud native kind of development pipeline. But speaking of secure, you have a customer that was talking about this Dow Chemical. About IB empowering Dow zero trust architecture. Could you explain that deal and how that's working? Because that's again, huge enterprise customer, very big scale at scale, zero trust is big, part of it. What is this? >> Let's start with the basics. So what is zero trust mean? It means to have a secure business, you have to start with the assumption that nothing can be trusted. That means you have to think about all aspects of your security practice. How do you align on a security strategy? How do you protect your data assets? How do you manage security threats? So we always talk about a line, protect, manage back to modernize, which is how do you bring all your systems forward to do this? That's exactly what we're doing with the Dow as you heard in that session, which is they've kind of done that whole journey from how they built a security strategy that was designed with zero trust in mind, they're protecting data assets, they're managing cyber threats in real time with a relatively low number of false positives which are the issue that most companies have. They're a tremendous example of a company that jumped on this and has had a really big impact. And they've done it without interfering with their business operations, meaning anybody can lock everything down but then you can't really run your business if you're doing that. They've done it, I think in a really intelligent way. >> That's awesome. We always talk about the big waves. You always give great color commentary on the trends. Right now though, the tsunami seems to be a confluence of many things coming together. What are some of the big trends in waves you're seeing now specifically on the tech side, on the technology side, as well as the business side right now? 'Cause coming out of post COVID, it's pretty clear cloud-native is powering a new growth strategy for customers. Dow was one of them, you just commented on it but there's a bigger wave happening here, both on the tech theater and in the business theater. Can you share your views on and your opinions and envision on these trends? >> I think there's three profound trends that are actually pretty simple to understand. One is, technology is going to decentralize again. We've always gone from centralized architectures to decentralized. Mainframe was centralized, internet mobile decentralized. The first version of public cloud was centralized, meaning bringing everything to one place. Technology is decentralized and again, with Hybrid Cloud, with Edge, pretty straight forward I think that's a trend that we can ride and lead for the next decade. Next is around automation that we talked about. There was a McKinsey report that said, "120 billion hours a year are going to be automated with things like Watson Orchestrator, Watson AIOps." What we're doing around Cloud Pak for automation, we think that time is now. We think you can start to automate in your business today and you may have seen the C QVS example where we're doing customer care and they're now automating 70% of their inbound customer inquiries. It's really amazing. And then the third is around data. The classical problem, I mentioned 90% is still unused or underutilized. This trend on data is not about the slow down because the data being collected is still multiplying 10 X every year and companies have to find a way to organize that data as they collected. So that's going to be a trend that continues. >> You know, I just kind of pinched myself sometimes and hearing you talk with some of our earlier conversations in theCUBE, people who have been on this data mindset have really been successful because it's evolving and growing and it's changing and it's adding more input into the system and the technology is getting better. There's more cloud scales. You mentioned automation and scale are huge. And I think this really kind of wakes everyone up. And certainly the pandemic has woken everyone up to the fact that this is driving new experiences for users and businesses, right? So this is, and then those experiences become expectations. This is the classic UX paradigm that grows from new things. So I got to ask you, with the pandemic what is the been the most compelling ways you seen people operate, create new expectations? Because new things are coming, new big things, and new incremental things are happening. So evolution and revolutionary capabilities. Can you share some examples and your thoughts? >> We've collected a decent bit of data on this. And what's interesting is how much AI has accelerated since the pandemic started. And it's really in five areas, it's customer care that we talked about, virtual agents, customer service, how you do that. It's employee experience. So somewhere to customer care but how do you take care of your employees using AI? Third is around AIOps, we talked about that. Fourth is around regulatory compliance and fifth is around financial planning and budgeting. These are the five major use cases of AI that are getting into production in companies over the last year that's going to continue to accelerate. So I think it's actually fairly clarifying now that we really understand these are the five big things. I encourage anybody watching, pick one of these, get started, then pick the second, then pick the third. If you are not doing all five of these, 12, 18, 24 months from now, you are going to be behind. >> So give us an example of some things that have surprised you in the pandemic and things that blew you away. Like, wow, I didn't see that coming. Can you share on things that you've seen evolve? Cause you're a year ahead of the business units of Cloud and Data, big part of IBM and you see customer examples. Just quickly share some notable use cases or just anecdotal examples of just things that jumped out at you that said, "Wow, that's going to be a double-down moment or that's not going to be anymore." Exposes, the pandemic exposes the good, bad and the ugly. I mean, people got caught off guard, some got a tailwind, some had a headwind, some are retooling. What's your thoughts on what you can you share any examples? >> Like everybody, many things have surprised me in the last year. I am encouraged at how fast many companies were able to adjust and adapt for this world. So that's a credit to all the resiliency that they built into their processes, their systems and their people over time. Related to that, the thing that really sticks out to me again, is this idea of using AI to serve your customers and to serve your employees. We had a hundred customers that went live with one of those two use cases in the first 35 days of the pandemic. Just think about that acceleration. I think without the pandemic, for those hundred it might've taken three years and it happened in 35 days. It's proof that the technology today is so powerful. Sometimes it just takes the initiative to get started and to do something. And all those companies have really benefited from this. So it's great to see. >> Great. Rob, great to have you on. Great to have your commentary on theCUBE. Could you just quickly share in 30 seconds, what is the most important thing people should pay attention to and Think this year from your perspective? What's the big aha moment that you think they could walk away with? >> We have intentionally made this a very technology centric event. Just go look at the demos, play with the technology. I think you will be impressed and start to see, let's say a bit of a new IBM in terms of how we're making technology accessible and easy for anybody to use. >> All right. Rob Thomas, Senior Vice President of IBM cloud and Data platform. Great to have you on and looking forward to seeing more of you this year and hopefully in person. Thanks for coming on theCUBE virtual. >> Thanks, John. >> Okay. I'm John Furrier with theCUBE. Keep coverage of IBM Think 2021. Thank you for watching. (soft music)