>>Oh, welcome back to the cubes coverage of coop con cloud native con 2021. I'm John is the Cuba, David Nicholson, our cloud host analyst, and it's exciting to be back in person in event. So we're back. It's been two years with the cube con and Linux foundation. So scrape, it was a hybrid event and we have a great guest here, Cuban London, Nick Dirk, and CT field CTO of harness and harness.io. The URL love the.io. Good to see you. >>Thank you guys for having me on. I genuinely appreciate >>It. Thanks for coming on. You were a part of our AWS startup showcase, which you guys were featured as a fast growing mature company, uh, as cloud scales, you guys have been doing extremely well. So congratulations. But now we're in reality now, right? So, okay. Cloud native has kind of like, okay, we don't have to sell it anymore. People buying into it. Um, and now operationalizing it with cloud operations, which means you're running stuff, applications and infrastructure is code and it costs money. Yeah. Martine Casada at Andreessen Horowitz. Oh, repatriated from the cloud. So there's a lot of, there's some cost conversations starting to happen. This is what you guys are in the middle of. >>Yeah, absolutely. What's interesting is when you think about it today, we want to shift left. When you want to empower all the engineers, we want to empower people. We're not giving them the data they need, right. They get a call from the CFO 30 days later, as opposed to actually being able to look at what change I did and how it actually affected. And this is what we're bringing in. Allowing people to have is now really empowering. So throughout the whole software delivery life cycle from CGI continuous integration, continuous delivery feature flagging, and even bringing cost modeling and in cloud cost management. And even then being able to shut down, shut down the services that you're not using, how much of that is waste. We talk about it. Every single cloud conference it's how much is waste. And so being able to actually turn those on, use those accordingly and then take advantage of even the cheapest instances when you should. That's really what >>It's so funny. People almost trip over dollars to pick up pennies in the cloud business because they're so focused on innovation that they think, okay, we've got to just innovate at all costs, but at some point you can make it productive for the developers in process in the pipeline to actually manage that. >>That's exactly it. I mean, if you think about it to me in order to breach state continuous delivery, we have to automate everything. Right. But that doesn't mean stop at just delivering, you know, to production. That means to customer, which means we've got to make them happy, but then ultimately all of those resources in dev and QA and staging and UAT, we've sticker those as well. And if we're not being mindful of it, the costs are astronomical, right. And we've seen it time and time again with every company you see, you've seen every article about how they've blown through all their budgets. So bring it to the people that can affect change. That's really the difference, making it visible, looking at it. In-depth not just at the cloud level and all the spend there, but also even at the, uh, thinking about it, the Kubernetes level down to the containers, the pods and understanding where are the resources even inside of the clusters and bringing that as an aggregate, not just for visibility and, and giving recommendations, but now more importantly, because part of a pipeline start taking action. That's where it's interesting. It's not just about being able to see it and understand it and hope, right? Hope is not a strategy acting upon it is what makes it valuable. And that's part of the automate everything. >>Yeah. We'll let that at the Dawn of the age of DevOps, uh, there was a huge incentive for a developer just to get their job done, to seize control of infrastructure, the idea of infrastructure as code, you know, and it's, it's, you know, w when it was being born, it's a fantastic, I've always wondered though, you know, be careful what you wish for. Do you really want all of that responsibility? So we've got responsibility from a compliance and security perspective and of course cost. So, so where do we, where do we go from here, I guess is the question. Yeah. So >>When we look at building this all together, I think when we think about software delivery, everybody wants to go fast. We start with velocity, right? Everybody says, that's where I want to go. And to your point with governance compliance, the next roadblock to hit is weight. In order to go fast, I have to do it appropriately. I've got governing bodies that tell me how this has to work. And that becomes a challenge. >>It slows it down too. It doesn't, I mean, basically people are getting pissed off, right? This is, this general sentiment is, is that developers are moving fast with their code. And then they have to stop. Compliance has to give the green light sometimes days, correct? Uh, it used to be weeks now. It's days, it's still unacceptable. So there's like this always been that tension to the security groups or say it, or finance was like slow down and they actually want to go faster. So that has to be policy-based something. Yep. This is the future. What is your take on that? >>Take on, this is pretty simple. When everybody talks about people, process and technology, it's kind of bogus, right? It's all about confidence. If you're confident that your developers can deploy appropriately and they're not going to do something wrong, you'll let them to play all the time. Well, that requires process. But if you have tooling that literally guarantees your governance, make sure that at no point in time, can any of your developers actually do something wrong. Now you have, >>That's the key. That's the key. That's the key because you're giving them a policy-based guardrails to execute in their programs >>And that's it. So now you can free up all those pieces. So all those bottlenecks, all those waiting all those time, and this is how all of our customers, they move from, you know, change advisory boards that approve deployments. >>Can you give us some, give us some, give us some, uh, customer anecdotal examples of this inaction and kind of the love letters you get, or, or the customer you take us through a use case of how it all. >>So this is one of my favorites. So NCR national cash register. If you slide a credit card at like a Chick-fil-A or a Safeway, right? Um, traditional technology. But what was interesting is they went from doing PCI audit, which would take seven days to go to a PCI audit right now with harness, because, >>And by the way, when you and the seventh, six day, the things that you did on day one change. >>Exactly, exactly. And so now, because of using harness and everything's audited, and all the changes are, are controlled to make sure that developers again, can only do what they're allowed. They only get to broadcast two per production. If they've met all their security requirements, all their compliance, permits, all their quality checks. Now, because of that, they literally gave a re read only view of harness to their auditor. And in three hours it was over. And it's because now we're that evidence file from code commit through to production. Yeah. It's there for point of sale compliant. >>So what is the benefits to them? What's the result saves them time, saves the money. What's the good, the free up more times. I'll see the chops it down. That's the key. >>Yeah. It's actually something we didn't build in like our ROI calculators, which was, we talked to their engineers and we gave them their nights and their weekends back, which I thought was amazing. But Thursday night, when we're doing that deploy, they don't have to be up. Harness is actually managing and understanding, using machine learning to understand what normal looks like. So they don't have to, they don't have to sit and look at the knock or sit in the war room and eat the free pizza. Yeah. Right. And then when those things break, same concept rates aren't as good. So >>I got to ask you, I got you here. You know, as the software development delivery lifecycle is radically being overhauled right now, which people generally agree that that's the case, the old models are, are different. How do you see your vision around AI and automation playing into this? Because you could say, okay, we're going to have different kinds of coding styles. This batch has got an AI block here. It's very Lego block. Like yep. Okay. Services and higher level services in the cloud. What's your reaction to how this impacts automation and >>Sure. So throughout our entire platform, we've designed our AI to take care of the worst parts of anyone's job as Guinea dev ops person. If they love babysitting deployments, they don't harness handles that for them, ask your engineers that they love sitting there waiting for their tests to run. Every time they build, they go get coffee, right. Because we're waiting for all of our tests to run. Y yeah. Right. The reality >>Is sometimes they have to wait days and >>That's it. But like, if I change the gas cap on, uh, on your car, would you expect me to check every light switch and every electronic piece? No. Well, why do we do that with code? And so our AI, our ML is designed to remove all the things that people hate. It's not to remove people's jobs. It's actually to make their jobs much better. >>How do you guys feed the data? What's the training algorithm for that? How does that work? Yeah, >>Actually, it's interesting. A lot of people think it's going to take a ton of time to figure this out. The good news is we start seeing this on the second deployment. On the second bill, we have to have a baseline of what good looks like, and that's where it starts. And it goes from there. And by the way, this isn't a lot of people say AI, and this AML, I teach a class on this because ML is not standard deviation. It's not some checks. So we use a massive amount of machine learning, but we have neural networks to think about things like engineers do. Like if we looked at a log and I saw the same log with two different user IDs, you and I would know, well, it's the same thing. It's just different users, but machine learning models. Don't so we've got to build neural networks to actually think like humans. So that, >>So that's the whole expectation maximization kind of concept of people talk about, >>Well, and that's it because at the end of the day, we're like I said, I'm not trying to take people's jobs. I want to meet. >>Yeah. You want to do the crap work out of the way. And I had to do other redundant, heavy lifting that they have to do every single time we use the cloud way. We've >>Built mechanical muscle in, in the early 19 hundreds. Right. And it made everyone's jobs easier, allowed them to do more with their time. That's exactly what we're doing here. >>I mean, we've seen the big old guys in the industry trying to evolve. You got the hot startups coming out. So you got, you know, adapt or die as classic thing. We've been saying for many years, David on the cube, you know that. So it's like, this is a moment of truth. We're going to see who comes out the other side. How do you, Nick, what would you be your, your kind of guess of when that other side is, when are we gonna know the winners and the losers truly in the sense of where we are now? >>So I think what I've found is that in this space specifically, there's a constant shift and this is something with software. And the problem is, is that we see them come in ebbs and flows, right. And very few times are there businesses that actually carry the model? And what you find is that when they focus on one specific problem, it solves it. Now, if I was working on VMs a few years ago, great, but now we're, we're here at coop con, right? And that's because it's eaten, uh, that side of the world. And so I think it's the companies that can actually grow the test of time and continue to expand to where the problems are. Right. And that's one of the things that I traditionally think about harness and we've done it. We cover our customers where they were, I think the old mainframes, if you had to, where they were, where they are at their traditional, their VM. >>I mean, if you think about it, Nick, it's one of those things where it's like, that's such a common sense way to look at it evolves with a problem. So I ride the right with tech ways. But if you think about the high order bit, here is just applications. We ended the day. Companies have applications that they want to write modern. The applications of their business is going to be codified so that you just work backwards from there. Then you say, okay, what is the infrastructure as code working for me? That's an ethos of dev ops. And that's where we're at. So that's why I think that the cloud need is kind of one already, but we still have the edge devices, more complexity. This is a huge next level conversation at one point is that we just put a hard and top on the complexity. When is that coming? Because the developers are clear. They want to go fast. They want to go shift left and have all that data, get the right analytics, the telemetry and the AI. But it's too complicated still. That is a big problem. >>It's too complicated. You ask for a full-stack developer to also know infrastructure, to also know edge computing. Like it's impossible, right? And this is where tooling helps, right? Because if you can actually parameterize that and make it to the engineers and have to care, they can do what they're best at. Hey, I'm great at turning code in artifact, let them do that and have tooling take care of the rest. This is where our goal is. Again, allow people >>We'll do what they love. And this is kind of the new roles that are changing. What SRE has done. Everyone talks about the SRE and some states just as he had dev ops guy, but it's not just that there's also, uh, different roles emerging. It's, it's an architectural game. At this point, we would say, >>I'd say a hundred percent. And this is where the decisions that you make on are architecturally. If you don't know how to then roll them out, this is what we've seen. Time and time again, you go to these large companies, I've got these great architectures on planning four years later, we haven't reached it because to that point process, >>The process killed them four >>Different new tools throughout the process. Well, yeah. >>So when do we hit peak Kubernetes peak >>Kubernetes? I think we have a bit to go in and I'm excited about the networking space and really what we're doing there and, and bringing that holistic portion of the network, like when Istio was originally released, I thought that was one of the most amazing things, uh, to truly come to it. And I think there's a vast space in networking. Um, and, and so I think in the next few years, we're going to see this, you know, turn into that a hundred percent utilized across the board. This will be that where everyone's workloads continue to exist. Um, somewhat like VMs we're in >>And, and, and no, no fear of developers as code in the very near future. You're talking about automating the mundane. Correct. Uh, there have been stories recently about the three-day workweek, you know, as a, as a fan of, um, utopian science fiction, myself, as opposed to dystopian. Absolutely. I think that, you know, technology does have the opportunity to lift all boats and, uh, and it's, it's not nothing to be afraid of. You know, the fact that I put my dishes in the dishwasher and they run by themselves for three hours. It's a good thing. It's a great thing. >>I don't need to deal with that. Yeah, I agree. No, I think that's, and that's what I said in the beginning. Right. That's really where we can start empowering people. So allow them to do what they're good at and do what they're best at. And if you look at why do people quit? We don't have to go so hard to find. Yeah. Why? Because they're secondary to babysit and implement and they're told everywhere they go, they're not going to have to >>That's the line. And that's all right. We got a break, but it's great insight to have you on the Q one final question for you. Um, I got to ask about the whole data as code something that I've been riffing on for a bunch of years now. And as infrastructures could we get that, but data is now the resource everyone needs, and everyone's trying to, okay, I have the control plane for this and that, but ultimately data cannot be siloed. This is a critical architectural element. How does that get resolved in the land of the competitive advantage and lock in and whatnot? What's your take on that? >>So data's an interesting one because it has, it has gravity and this is the problem. And as we move, as I think you guys know, as you move to the edge as remove, move it places there's insights to be taken at the edge there's insights to be taken as it moves through. And I think what you'll see honestly, going forward is you'll see compute done differently to your point. It needs to be aggregated. It needs to be able to be used together, but I think you'll see people computing it on its way through it. So now even in transport, you'll start seeing insights gained in real time before you can have the larger insights. And I see that happening more and more. Um, and I think ultimately we just want to empower that >>Nick, great to have you on CTO of field CTO of harness and harness.io is a URL. Check it out. Thanks for the insight. Thank you so much. Great comments. Appreciate it. Natural cube analysts right here, Nick, of course, we've got our, our analysts right here, David Nicholson. You're good on your own. I'm John for a, you know, we have the host. Thanks for watching. Stay with two more days of coverage. We'll be back after this short break.