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David Aronchick & JD Velasquez, Google | KubeCon + CloudNativeCon 2018


 

>> Announcer: Live, from Copenhagen, Denmark. It's theCUBE! Covering KubeCon and CloudNativeCon Europe 2018. Brought to you by the Cloud Native Computing Foundation, and its Ecosystem partners. >> Hi everyone, welcome back, this is theCUBE's exclusive coverage of the Linux Foundation's Cloud Native Compute Foundation KubeCon 2018 in Europe. I'm John Furrier, host of theCUBE and we're here with two Google folks. JD Velazquez who's the Product Manager for Stackdriver, got some news on that we're going to cover, and David Aronchick, who's the co-founder of Kubeflow, also with Google, news here on that. Guys, welcome to theCUBE, thanks for coming on. >> Thank you John. >> Thank you very much. >> So we're going to have Google Next coming out, theCUBE will be there this summer, looking forward to digging in to all the enterprise traction you guys have, and we had some good briefings at Google. Ton of movement on the Cloud for Google, so congratulations. >> JD: Thank you. >> Open source is not new to Google. This is a big show for you guys. What's the focus, you've got some news on Stackdriver, and Kubeflow. Kubeflow, not Cube flow, that's our flow. (laughing) David, share some of the news and then we'll get into Stackdriver. >> Absolutely, so Kubeflow is a brand new project. We launched it in December, and it is basically how to make machine learning stacks easy to use and deploy and maintain on Kubernetes. So we're not launching anything new. We support TensorFlow and PyTorch, Caffe, all the tools that you're familiar with today. But we use all the native APIs and constructs that Kubernetes rides to make it very easy and to let data scientists and researchers focus on what they do great, and let the I.T. Ops people deploy and manage these stacks. >> So simplifying the interactions and cross-functionality of the apps. Using Kubernetes. >> Exactly, when you go and talk to any researcher out there or data scientist, what you'll find is that while the model, TensorFlow, or Pytorch or whatever, that gets a little bit of the attention. 95% of the time is spent in all the other elements of the pipeline. Transforming your data, ingesting it, experimenting, visualizing. And then rolling it out toward production. What we want to do with Kubeflow is give everyone a standard way to interact with those, to interact with all those components. And give them a great workflow for doing so. >> That's great, and the Stackdriver news, what's the news we got going on? >> We're excited, we just announced the beta release of Stackdriver Kubernetes monitoring, which provides very rich and comprehensive observability for Kubernetes. So this is essentially simplifying operations for developers and operators. It's a very cool solution, it integrates many signals across the Kubernetes environment, including metrics, logs, events, as well as metadata. So what it allows is for you to really inspect your Kubernetes environment, regardless of the role, and regardless of where your deployment is running it. >> David is bringing up just the use cases. I just, my mind is exploding, 'cause you think about what Tensorflow is to a developer, and all the goodness that's going on with the app layer. The monitoring and the instrumentation is a critical piece, because Kubernetes is going to bring the people what is thousands and thousands of new services. So, how do you instrument that? I mean, you got to know, I want to provision this service dynamically, that didn't exist. How do you measure that, I mean this is, is this the challenge you guys are trying to figure out here? >> Yeah, for sure John. The great thing here is that we, and at Google primarily, many of our ancillary practices go beyond monitoring. It really is about observability, which I would describe more as a property of a system. How do you, are able to collect all these many signals to help you diagnose the production failure, and to get information about usage and so forth. So we do all of that for you in your Kubernetes environment, right. We take that toil away from the developer or the operator. Now, a cool thing is that you can also instrument your application in open source. You can use Prometheus, and we have an integration for that, so anything you've done in a Prometheus instrumentation, now you can bring into the cloud as needed. >> Tell about this notion, everyone gets that, oh my God, Google's huge. You guys are very open, you're integrating well. Talk about the guiding principles you guys have when you think about Prometheus as an example. Integrating in with these other projects. How are you guys treating these other projects? What's the standard practice? API Base? Is there integration plans? How do you guys address that question? >> Yeah, at a high level I would say, at Google, we really believe in contributing and helping grow open communities. I think that the best way to maintain a community open and portable is to help it grow. And Prometheus particularly, and Kubernetes of course, is a very vibrant community in that sense. So we are, from the start, designing our systems to be able to have integration, via APIs and so on, but also contributing directly to the projects. >> And I think that one thing that's just leveraging off that exact point, y'know, we realize what the world looks like. There's literally zero customers out there, like, "Well, I want be all in on one cloud. "Y'know, that 25 million dollar data center "I spent last year building. "Yeah, I'll toss that out so that I can get, "y'know, some special thing." The reality is, people are multi-cloud. And the only way to solve any problem is with these very open standards that work wherever people are. And that's very much core to our philosophy. >> Well, I mean, I've been critical of multi-cloud, by the definition. Statistically, if I'm on Azure, with 365, that's Azure. If I'm running something on Amazon, those are two clouds, they're not multi-cloud, by my definition. Which brings up where this is going, which is latency and portability, which you guys are really behind. How are you guys looking at that, because you mentioned observation. Let's talk about the observation space of clouds. How are you guys looking at, 'cause that's what people are talking about. When are we going to get to the future state, which is, I need to have workload portability, in real time, if I want to move something from Azure to AWS or Google Cloud, that would be cool. Can't do that today. >> That is actually the core of what we did around Kubeflow. What we are able to do is describe in code all the layers of your pipeline, all the steps of your pipeline. That works based on any conformant Kubernetes cluster. So, you have a Kubernetes conformant cluster on Azure, or on AWS, or on Google Cloud, or on your laptop, or in your private data center, that's great. And to be clear, I totally agree. I don't think that having single workloads spread across cloud, that's not just unrealistic, because of all the things you identified. Latency, variability, unknown failures, y'know. Cap theorem is a thing because, y'know, it's well-known. But what people want to do is, they want to take advantage of different clouds for the efforts that they provide. Maybe my data is here, maybe I have a legal reason, maybe this particular cloud has a unique chip, or unique service-- >> Use cases can drive it. >> Exactly, and then I can take my workload, which has been described in code and deploy it to that place where it makes sense. Keeping it within a single cloud, but as an organization I'll use multiple clouds together. >> Yeah, I agree, and the data's key, because if you can have data moving between clouds, I think that's something I would like to see, because that's going to be, because the metadata you mentioned is a real critical piece of all these apps. Whether it's instrumentation logging, and/or, y'know, provisioning new services. >> Yeah, and as soon as you have, as David is mentioning, if you have deployments on, y'know, with public or private clouds, then the difficult part is that of severability, that we were talking before. Because now you're trying to stitch together data, and tools to help you get that diagnosed, or get signals when you need them. This is what we're doing with Stackdriver Kubernetes monitoring, precisely. >> Y'know, we're early days in the cloud. It stills feels like we're 10 years in, but, y'know, a lot of people are now coming to realize cloud native, so. Y'know, I'm not a big fan of the whole, y'know, Amazon, although they do say Amazon's winning, they are doing quite well with the cloud, 'cause they're a cloud. It's early days, and you guys are doing some really specific good things with the cloud, but you don't have the breadth of services, say, Amazon has. And you guys are above board about that. You're like, "Hey, we're not trying to meet them "speed for speed on services." But you do certain things really, really well. You mentioned SRE. Site Reliability Engineers. This is a scale best practice that you guys have bringing to the table. But yet the customers are learning about Kubernetes. Some people who have never heard of it before say, "Hey, what's this Kubernetes thing?" >> Right. >> What is your perspectives on the relevance of Kubernetes at this point in history? Because it really feels like a critical mass, de facto, standard movement where everyone's getting behind Kubernetes, for all the right reasons. It feels a lot like interoperability is here. Thoughts on Kubernetes' relevance. >> Well I think that Alexis Richardson summed it up great today, the chairperson of the technical oversight committee. The reality is that what we're looking for, what operators and software engineers have been looking for forever, is clean lines between the various concerns. So as you think about the underlying infrastructure, and then you think about the applications that run on top of that, potentially services that run on top of that, then you think about applications, then you think about how that shows up to end users. Before, if you're old like me, you remember that you buy a $50,000 machine and stick it in the corner, and you'd stack everything on there, right? That never works, right? The power supply goes out, the memory goes out, this particular database goes out. Failure will happen. The only way to actually build a system that is reliable, that can meet your business needs, is by adopting something more cloud native, where if any particular component fails, your system can recover. If you have business requirements that change, you can move very quickly and adapt. Kubernetes provides a rich, portable, common set of APIs, that do work everywhere. And as a result, you're starting to see a lot of adoption, because it gives people that opportunity. But I think, y'know and let me hand off to JD here, y'know, the next layer up is about observability. Because without observing what's going on in each of those stacks, you're not going to have any kind of-- >> Well, programmability comes behind it, to your point. Talk about that, that's a huge point. >> Yeah, and just to build on what David is saying, one thing that is unique about Google is that we've been doing for more than a decade now, we've been very good at being able to provide innovative services without compromising reliability. Right, and so what we're doing is in that commitment, and you see that with Kubernetes and Istio, we're externalizing many of our, y'know, opinionated infrastructure, and platforms in that sense, but it's not just the platforms. You need those methodologies and best practices. And now the toolset. So that's what we're doing now, precisely. >> And you guys have made great strides, just to kind of point out to the folks watching, in the enterprise, I know you've got a lot more work to do but you're pedaling as fast as you can. I want to ask you specifically around this, because again, we're still early days with the cloud, if you think about it, there are now table stakes that are on the table that you got to get done. Check boxes if you will. Certainly on the government side there's like, compliance issues, and you guys are now checking those boxes. What is the key thing, 'cause you guys are operating at a scale that enterprises can't even fathom. I mean, millions of services, on and on up a huge scale. That's going to be helpful for them down the road, no doubt about it. But today, what is the Google table stakes that are done, and what are enterprises need to have for table stakes to do cloud native right, from your perspective? >> Well, I think more than anything, y'know, I agree with you. The reality is all the hyperscale cloud providers have the same table stakes, all the check boxes are checked, we're ready to go. I think what will really differentiate and move the ball forward for so many people is this adoption of cloud native. And really, how cloud native is your cloud, right? How much do you need to spin up an entire SRE team like Netflix in order to operate in the Netflix model of, y'know, complete automation and building your own services and things like that. Does your cloud help you get cloud native? And I think that's where we really want to lean in. It's not about IAS anymore, it's about does your cloud support the reliability, support the distribution, all the various services, in order to help you move even faster and achieve higher velocity. >> And standing up that is critical, because now these applications are the business model of companies, when you talk about digital. So I tweeted, I want to get your reaction to this, yesterday I got a quote I overheard from a person here in the hallways. "I need to get away from VPNs and firewalls. "I need user application layer security "with unphishable access, otherwise I'm never safe." Again this talks about the perimeterless cloud, spearphishing is really hot right now, people are getting killed with security concerns. So, I'm going to stop if I'm enterprise, I'm going to say, "Hold on, I'm not going," Y'know, I'm going to proceed with caution. What are you guys doing to take away the fear, and also the reality that as you provision all these, stand up all this infrastructure, services for customers, what are you guys doing to prevent phishing attacks from happening, security concerns, what's the Google story? >> So I think that more than anything, what we're trying to do is exactly what JD just said, which is externalize all the practices that we have. So, for example, at Google we have all sorts of internal tools that we've used, and internal practices. For example, we just published a whitepaper about our security practices where you need to have two vulnerabilities in order to break out of any system. We have all that written up there. We just published a whitepaper about encryption and how to do encryption by default, encryption between machines and so on. But I think what we're really doing is, we're helping people to operate like Google without having to spin up an entire SRE team as big as Google's to do it. An example is, we just released something internally, we have something called BeyondCorp. It's a non-firewall, non-VPN based way for you to authenticate against any Google system, using two-factor authentication, for our internal employees. Externally, we just released it, it's called, Internet, excuse me, IdentityAware proxy. You can use with literally any service that you have. You can provision a domain name, you can integrate with OAuth, you can, including Google OAuth or your own private OAuth. All those various things. That's simply a service that we offer, and so, really, y'know, I think-- >> And there's also multi, more than two-factor coming down the road, right? >> Exactly, actually IdentityAware proxy already supports two-factor. But I will say, one of the things that I always tell people, is a lot of enterprises say exactly what you said. "Jeez, this new world looks very scary to me. "I'm going to slow down." The problem is they're mistaken, under the mistaken impression that they're secure today. More than likely, they're not. They already have firewall, they already have VPN, and it's not great. In many ways, the enterprises that are going to win are the ones that lean in and move faster to the new world. >> Well, they have to, otherwise they're going to die, with IOT and all these benefits, they're exposed even as they are, just operationally. >> Yep. >> Just to support it. Okay, I want to get your thoughts, guys, on Google's role here at the Linux Foundation's CNCF KubeCon event. You guys do a lot of work in open source. You've got a lot of great fan base. I'm a fan of what you guys do, love the tech Google brings to the table. How do people get involved, what are you guys connecting with here, what's going on at the show, and how does someone get on board with the Google train? Certainly TensorFlow has been, it's like, great open source goodness, developers are loving it, what's going on? >> Well we have over almost 200 people from Google here at the show, helping and connecting with people, we have a Google booth which I invite people to stop by and tell about the different project we have. >> Yeah, and exactly like you said, we have an entire repo on Github. Anyone can jump in, all our things are open source and available for everyone to use no matter where they are. Obviously I've been on Kubernetes for a while. The Kubernetes project is on fire, Tensorflow is on fire, KubeFlow that we mentioned earlier is completely open source, we're integrating with Prometheus, which is a CNCF project. We are huge fans of these open source foundations and we think that's the direction that most software projects are going to go. >> Well congratulations, I know you guys invested a lot. I just want to highlight that. Again, to show my age, y'know these younger generation have no idea how hard open source was in the early days. I call it open bar and open source, you guys are bringing so much, y'know, everyone's drunk on all this goodness. Y'know, just these libraries you guys bringing to the table. >> David: Right. >> I mean Tensorflow is just the classic poster-child example. I mean, you're bringing a lot of stuff to the table. I mean, you invented Kubernetes. So much good stuff coming in. >> Yeah, I couldn't agree more. I hesitate to say we invented it. It really was a community effort, but yeah, absolutely-- >> But you opened it up, and you did it right, and did a good job. Congratulations. Thanks for coming on theCUBE, I'm going to see you at Google Next. theCUBE will be broadcasting live at Google Next in July. Of course we'll do a big drill-down on Google Cloud platform at that show. It's theCUBE here at KubeCon 2018 in Copenhagen, Denmark. More live coverage after this short break, stay with us. (upbeat music)

Published Date : May 2 2018

SUMMARY :

Brought to you by the Cloud Native Computing Foundation, of the Linux Foundation's Cloud Native Compute Foundation all the enterprise traction you guys have, This is a big show for you guys. and let the I.T. and cross-functionality of the apps. Exactly, when you go and talk to any researcher out there So what it allows is for you is this the challenge you guys to help you diagnose the production failure, Talk about the guiding principles you guys have is to help it grow. And the only way to solve any problem is with these How are you guys looking at that, because of all the things you identified. and deploy it to that place where it makes sense. because the metadata you mentioned Yeah, and as soon as you have, that you guys have bringing to the table. the relevance of Kubernetes at this point in history? and then you think about Well, programmability comes behind it, to your point. and you see that with Kubernetes and Istio, and you guys are now checking those boxes. in order to help you move even faster and also the reality that as you provision all these, You can use with literally any service that you have. is a lot of enterprises say exactly what you said. with IOT and all these benefits, I'm a fan of what you guys do, and tell about the different project we have. Yeah, and exactly like you said, Y'know, just these libraries you guys bringing to the table. I mean, you invented Kubernetes. I hesitate to say we invented it. I'm going to see you at Google Next.

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