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James Labocki, Red Hat & Ruchir Puri, IBM | KubeCon + CloudNativeCon Europe 2021 - Virtual


 

>>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.

Published Date : May 7 2021

SUMMARY :

It's the cube with coverage of Kublai virtual brought to you by red hat. IBM fellow and chief scientist at IBM Gentlemen, thanks for coming on the cube, So I want to ask you before we get into some of the questions around the layer which comes above it which is where all our, you know, This is the enablement moment where the fruit is coming off the tree is starting to see that first wave of you mentioned And so, um, you know, when you start talking to them at levels beyond, Can you give an example of something uh some use cases of people doing this, I don't know if you have any you want to touch on um specifically I could add on as well. complexity of the application in terms of some of the legacy code that you are seeing more the container orchestration layer, if you want become the de facto standard. of popularized the six hours framework years ago, you know, with, with, with, with that. It's not just about either lift and shift of the VM or or lift tinker and in the community that you guys are working? So you imagine you have all your you know, uh and you know, kubernetes has become a de facto standard now you are containerized already, hosting re platform and re factoring, the idea is that you want to measure your software delivery performance on Let me ask the question for the folks watching or anyone interested, how do they get involved? So, um, we have a, you know, a governance model I don't know if you have day to day problems that you are encountering as you are taking your applications to a for, you know, the class, what I call the classic enterprise, So what you guys both have your companies participated Exactly when you start on this journey, there will be 100 people who will be telling you all you have and you know, the big companies who are building their own stuff, so you start to see that transition, I mean, I think, you know, I think that the stat you always here is that And I think just to add to what James said, typically we are talking about the abstraction will get you to move up the stack in terms of automation. uh like let me just give you a brief example re factoring how you take So as these apps start to come on a P We're bringing it to you with two experts. I'm john furry with the cube.

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Ricardo Rocha, CERN | KubeCon + CloudNativeCon Europe 2021 - Virtual


 

>>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. Hello, welcome back to the cubes coverage of Kublai khan. Cloud Native Con 2021 part of the CNC. S continuing cube partnership virtual here because we're not in person soon, we'll be out of the pandemic and hopefully in person for the next event. I'm john for your host of the key. We're here with ricardo. Roach computing engineers sir. In CUBA. I'm not great to see you ricardo. Thanks for remote ng in all the way across the world. Thanks for coming in. >>Hello, Pleasure. Happy to be here. >>I saw your talk with Priyanka on linkedin and all around the web. Great stuff as always, you guys do great work over there at cern. Talk about what's going on with you and the two speaking sessions you have it coop gone pretty exciting news and exciting sessions happening here. So take us through the sessions. >>Yeah. So actually the two sessions are kind of uh showing the two types of things we do with kubernetes. We we are doing we have a lot of uh services moving to kubernetes, but the first one is more on the services we have in the house. So certain is known for having a lot of data and requests, requiring a lot of computing capacity to analyze all this data. But actually we have also very large community and we have a lot of users and people interested in the stuff we do. So the first question will actually show how we've been uh migrating our group of infrastructure into the into communities and in this case actually open shift. And uh the challenge there is to to run a very large amount of uh global websites on coordinators. Uh we run more than 1000 websites and there will be a demonstration on how we do all the management of the website um life cycle, including upgrading and deploying new new websites and an operator that was developed for this purpose. And then more on the other side will give with a colleague also talk about machine learning. Machine learning has been a big topic for us. A lot of our workloads are migrating to accelerators and can benefit a lot from machine learning. So we're giving a talk about a new service that we've deployed on top of Cuban areas where we try to manage to uh lifecycle of machine learning workloads from data preparation all the way to serving the bottles, also exploring the communities features and integrating accelerators and a lot of accelerators. >>So one part of the one session, it's a large scale deployment kubernetes key to there and now the machine learning essentially service for other people to use that. Right? Like take me through the first large scale deployment. What's the key innovation there in your opinion? >>Yeah, I think compared to the infrastructure we had before, is this notion that we can develop an operator that will uh, manage resource, in this case a website. And this is uh, something that is not always obvious when people start with kubernetes, it's not just an orchestra, it's really the ap and the capability of managing a huge amount of resources, including custom resources. So the possibility to develop this operator and then uh, manage the lifecycle of uh, something that was defined in the house and that fits our needs. Uh, There are challenges there because we have a large amount of websites and uh, they can be pretty active. Uh, we also have to some scaling issues on the storage that serves these these websites and we'll give some details uh during the talk as well, >>so kubernetes storage, this is all kind of under the covers, making this easier. Um and the machine learning, it plays nicely in that what if you take us for the machine learning use case, what's going on there, wow, what was the discovery, How did you guys put that together? What's the key elements there? >>Right, so the main challenge there has been um that machine learning is is quite popular but it's quite spread as well, so we have multiple groups focusing on this, but there's no obvious way to centralize not only the resource usage and make it more efficient, but also centralize the knowledge of how these procedures can be done. So what we are trying to do is just offer a service to all our users where we help them with infrastructure so that they don't have to focus on that and they could focus just on their workloads and we do everything from exposing the data systems that we have in the house so that they can do access to the data and data preparation and then doing um some iteration using notebooks and then doing distributed training with potentially large amount of gps and that storage and serving up the models and all of this is uh is managed with the coordinates cluster underneath. Uh We had a lot of knowledge of how to handle kubernetes and uh all the features that everyone likes scalability. The reliability out of scaling is very important for this type of workload. This is, this is key. >>Yeah, it's interesting to see how kubernetes is maturing, um congratulations on the projects. Um they're going to probably continue to scale. Remember this reminds me of when I was uh you know coming into the business in the 98 late eighties early nineties with TCP I. P. And the S. I. Model, you saw the standards evolve and get settled in and then boom innovation everywhere. And that took about a year to digest state and scale up. It's happening much faster now with kubernetes I have to ask you um what's your experience with the question that people are looking to get answered? Which is as kubernetes goes, the next generation of the next step? Um People want to integrate. So how is kubernetes exposing a. P. I. S. To say integration points for tools and other things? Can you share your experience and where this is going, what's happening now and where it goes? Because we know there's no debate. People like the kubernetes aspect of it, but now it's integration is the conversation. Can you share your thoughts on that? >>I can try. Uh So it's uh I would say it's a moving target, but I would say the fact that there's such a rich ecosystem around kubernetes with all the cloud, David projects, uh it's it's uh like a real proof that the popularity of the A. P. I. And this is also something that we after we had the first step of uh deploying and understanding kubernetes, we started seeing the potential that it's not reaching only the infrastructure itself, it's reaching all the layers, all the stack that we support in house and premises. And also it's opening up uh doors to easily scale into external resources as as well. So what we've been trying to tell our users is to rely on these integrations as much as possible. So this means like the application lifecycle being managed with things like Helmand getups, but also like the monitoring being managed with Prometheus and once you're happy with your deployment in house we have ways to scale out to external resources including public clouds. And this is really like see I don't know a proof that all these A. P. I. S are not only popular but incredibly useful because there's such a rich ecosystem around it. >>So talk about the role of data in this obviously machine learning pieces something that everyone is interested in as you get infrastructure as code and devops um and def sec ops as everything's shifting left. I love that, love that narrative day to our priests. All this is all proving mature, mature ization. Um data is critical. Right? So now you get real time information, real time data. The expectations for the apps is to integrate the data. What's your view on how this is progressing from your standpoint because machine learning and you mentioned you know acceleration or being part of another system. Cashing has always done that would say databases. Right. So you've got now is databases get slower, caches are getting faster now they're all the ones so it's all changing. So what's your thoughts on this next level data equation into kubernetes? Because you know stateless is cool but now you've got state issues. >>Yeah so uh yeah we we've always had huge needs for for data we store and I I think we are over half an exhibit of data available on the premises but we we kind of have our own storage systems which are external and that's for for like the physics data, the raw data and one particular charity that we had with our workloads until recently is that we we call them embarrassing parallel in the sense that they don't really need uh very tight connectivity between the different workloads. So if it's people always say tens of thousands of jobs to do some analysis, they're actually quite independent, they will produce a lot more data but we can store them independently. Machine learning is is posing a challenge in the sense that this is a training tends to be a lot more interconnected. Um so it can be a benefit from from um systems that we are not so familiar with. So for us it's it's maybe not so much the cashing layers themselves is really understanding how our infrastructure needs to evolve on premises to support this kind of workloads. We had some smallish uh more high performance computing clusters with things like infinite and for low latency. But this is not the bulk of our workloads. This is not what we are experts on these days. This is the transition we are doing towards uh supporting this machine learning workers >>um just as a reference for the folks watching you mentioned embarrassing parallel and that's a quote that you I read on your certain tech blog. So if you go to tech blog dot web dot search dot ch or just search cern tech blog, you'll see the post there um and good stuff there and in there you go, you lay out a bunch of other things too where you start to see the deployment services and customer resource definitions being part of this, is it going to get to the point where automation is a bigger part of the cluster management setting stuff up quicker. Um As you look at some of the innovations you're doing with machines and Coubertin databases and thousands of other point things that you're working on there, I mean I know you've got a lot going on there, it's in the post but um you know, we don't want to have the problem of it's so hard to stand up and manage and this is what people want to make simpler. How do you how do you answer that when people say say we want to make it easier? >>Yeah. So uh for us it's it's really automate everything and up to now it has been automate the deployment in the kubernetes clusters right now we are looking at automating the kubernetes clusters themselves. So there's some really interesting projects, uh So people are used to using things like terra form to manage the deployment of clusters, but there are some projects like cross playing, for example, that allows us to have the clusters themselves being resources within kubernetes. Uh and this is something we are exploring quite a bit. Uh This allows us to also abstract the kubernetes clusters themselves uh as uh as carbonated resources. So this this idea of having a central cluster that will manage a much larger infrastructure. So this is something that we're exploring the getups part is really key for us to, it's something that eases the transition from from from people that are used already to manage large scale systems but are not necessarily experts on core NATO's. Uh they see that there's an easier past there if they if they can be introduced slowly through through the centralized configuration. >>You know, you mentioned cross plane, I had some on earlier, he's awesome dude, great guy and I was smiling because you know I still have you know flashbacks and trigger episodes from the Hadoop world, you know when it was such so promising that technology but it was just so hard to stand up and managed to be like really an expert to do that. And I think you mentioned cross plane, this comes up to the whole operator notion of operating the clusters, right? So you know, this comes back down to provisioning and managing the infrastructure, which is, you know, we all know is key, right? But when you start getting into multi cloud and multiple environments, that's where it becomes challenging. And I think I like what they're doing is that something that's on your mind to around hybrid and multi cloud? Can you share your thoughts on that whole trajectory? >>Absolutely. So I actually gave an internal seminar just last week describing what we've been playing with in this area and I showed some demo of using cross plane to manage clusters on premises but also manage clusters running on public clouds. A. W. S. Uh google cloud in nature and it's really like the goal there. There are many reasons we we want to explore external resources. We are kind of used to this because we have a lot of sites around the world that collaborate with us, but specifically for public clouds. Uh there are some some motivations there. The first one is this idea that we have periodic load spikes. So we knew we have international conferences, the number of analysis and job requests goes up quite a bit, so we need to be able to like scale on demand for short periods instead of over provisioning this uh in house. The second one is again coming back to machine learning this idea of accelerators. We have a lot of Cpus, we have a lot less gPS uh so it would be nice to go on fish uh for those in the public clouds. And then there's also other accelerators that are quite interesting, like CPUs and I p u s that will definitely play a role and we probably, or maybe we will never have among premises, will only be able to to use them externally. So in that, in that respect, actually coming back to your previous question, this idea of storage then becomes quite important. So what we've been playing with is not only managing this external cluster centrally, but also managing the wall infrastructure from a central place. So this means uh, making all the clusters, whatever they are look very, very much the same, including like the monitoring and the aggregation of the monitoring centrally. And then as we talked about storage, this idea of having local storage that that will be allow us to do really quick software distribution but also access to the data, >>what you guys are doing as we say, cool. And relevant projects. I mean you got the large scale deployments and the machine learning to really kind of accelerate which will drive a lot of adoption in terms of automation. And as that kicks in when you got to get the foundational work done, I see that clearly the right trajectory, you know, reminds me ricardo, um you know, again not do a little history lesson here, but you know, back when network protocols were moving from proprietary S N A for IBM deck net for digital back in the history the old days the os I Open Systems Interconnect Standard stack was evolving and you know when TCP I P came around that really opened up this interoperability, right? And SAM and I were talking about this kind of cross cloud connections or inter clouding as lou lou tucker. And I talked that open stack in 2013 about inter networking or interconnections and it's about integration and interoperability. This is like the next gen conversation that kubernetes is having. So as you get to scale up which is happening very fast as you get machine learning which can handle data and enable modern applications really it's connecting networks and connecting systems together. This is a huge architectural innovation direction. Could you share your reaction to that? >>Yeah. So actually we are starting the easy way, I would say we are starting with the workloads that are loosely coupled that we don't necessarily have to have this uh tighten inter connectivity between the different deployments, I would say that this is this is already giving us a lot because our like the bulk of our workloads are this kind of batch, embarrassing parallel, uh and we are also doing like co location when we have large workloads that made this kind of uh close inter connectivity then we kind of co locate them in the same deployment, same clouds in region. Um I think like what you describe of having cross clouds interconnectivity, this will be like a huge topic. It is already, I would say so we started investigating a lot of service measure options to try to learn what we can gain from it. There is clearly a benefit for managing services but there will be definitely also potential to allow us to kind of more easily scale out across regions. There's we've seen this by using the public cloud. Some things that we found is for example, this idea of infinite, infinite capacity which is kind of sometimes uh it feels kind of like that even at the scale we have for Cpus But when you start using accelerators, Yeah, you start negotiating like maybe use multiple regions because there's not enough capacity in a single region and you start having to talk to the cloud providers to negotiate this. And this makes the deployments more complicated of course. So this, this interconnectivity between regions and clouds will be a big thing. >>And, and again, low hanging fruit is just a kind of existing market but has thrown the vision out there mainly to kind of talk about what what we're seeing which is the world's are distributed computer. And if you have the standards, good things happen. Open systems, open innovating in the open really could make a big difference is going to be the difference between real value for the society of global society or are we going to get into the silo world? So I think the choice is the industry and I think, you know, Cern and C and C. F and Lennox Foundation and all the companies that are investing in open really is a key inflection point for us right now. So congratulations. Thanks for coming on the cube. Yeah, appreciate it. Thank you. Okay, Ricardo, rocha computing engineer cern here in the cube coverage of the CN Cf cube con cloud, native con europe. I'm john for your host of the cube. Thanks for watching.

Published Date : May 5 2021

SUMMARY :

from around the globe. I'm not great to see you ricardo. Happy to be here. what's going on with you and the two speaking sessions you have it coop gone pretty exciting news the two types of things we do with kubernetes. So one part of the one session, it's a large scale deployment kubernetes key to there and now So the possibility to Um and the machine learning, it plays nicely in that what if you take us for the machine learning use case, the data systems that we have in the house so that they can do access to the data and data preparation in the 98 late eighties early nineties with TCP I. P. And the S. I. Model, you saw the standards that the popularity of the A. P. I. And this is also something that we So talk about the role of data in this obviously machine learning pieces something that everyone is interested in as This is the transition we are doing towards So if you go to tech blog dot web dot search dot ch Uh and this is something we are exploring quite a bit. this comes back down to provisioning and managing the infrastructure, which is, you know, we all know is key, The first one is this idea that we have periodic load spikes. and the machine learning to really kind of accelerate which will drive a lot of adoption in terms of uh it feels kind of like that even at the scale we have for Cpus But when you open innovating in the open really could make a big difference is going to be the difference

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