 Good afternoon, cloud natives, and welcome back to KubeCon, cloud native con. We're here in the Windy City. My name's Savannah Peterson, joined by my co-host, John Furrier. John, how's Chicago treating you? Doing great, I love this place, love the weather here. It's beautiful outside. We got a balmy Chicago trip. We got lucky. It was sunny when I came in this morning. Little rain yesterday, little wind. Little, shocking. I wonder where that came from. I know my hair is holding up. I was worried about that here in the Windy City and it actually held up in that fantastic Daft Punk helmet that you may have seen. We've got Ian, the CTO of Chronosphere, joining us. Not wearing the Daft Punk helmet. We get to see that handsome face. How are you doing, Ian? Great, it's great to be back. Yeah, good, good. And how's the show been for you? It's been really interesting seeing everyone come back and seeing the new crop of startups and all kinds of interesting perspectives. Definitely think in-person conferences are back with a mighty force. I know, it's a nice feeling, isn't it? I think we all missed each other and there's nothing like doing business in person. I know you had a lot of customer conversations. Yes. Tell us some of the themes. I definitely think there's a lot of interest, obviously, in open telemetry, but it's tipped over from the interest perspective to the we have to implement this now. There's definitely a lot- Sense of urgency then. Yeah, and organizations who, we've been waiting a little bit. Definitely, I think, a little more enthusiastic with some of those 1.0 announcements, which are really important. Stability is key, right? Yeah. But then, the mass adoption across open source technology and backends, as well as vendors as well. But there's definitely a lot of, how are we going to do this? How are we going into this brave new era? We've been talking about Cloud Native for a while. Let's start really digging into it. Yes, I feel like there's a theme of maturity to a degree in evolution, both within the projects, as well as all the different companies. Observability, very hot topic. Do you think that customers are nervous about Kubernetes still, or do you think they're now? I don't think so. I think it's become, this is stable. This is something that we can derive, potentially, a lot of really great business impact from. We can even, I even see excitement from what you might call larger enterprises or legacy businesses of, oh, this could be transformative, right? We can start attracting this really next key batch of talent and start innovating and disrupting in ways that maybe we're constrained when we're running our own data center and all these other things. So, microservices architectures on top of Kubernetes and all the interesting new technologies, definitely a lot of interest from smaller startups all the way up to the spectrum. Ian, talk about the change with AI now on the landscape. Everyone's talking about their AI. Observability is key to security. Container security, data coming out of observers. You're in the crosshairs of the AI wave. What are customers? What are you seeing? What's the story? What's the real story there? What's real? Kind of hype at this point. Sure, so I think there are two parts to it. One is from an observability perspective, a lot of customers obviously themselves experimenting with observability, sorry, AI, generative AI, even building their own large language models. And so they want to observe those workloads. And I liken it to, say for example, when we adopted GraphQL, right? Massive explosion of data needing to sift through it. It's not just, oh, I need to store it, but I need to make sense of it. I need to be able to highlight what matters. And people weren't used to GraphQL at all. They're like, well, I don't actually know how to debug these things. And so there's a learning curve of the vendors themselves helping to identify, but also the engineering organizations themselves, like how do I optimize? What should I be looking for? And so I think the same pattern is going to repeat itself again with a lot of this AI stuff. But then there's sort of a subsection, which is, well, those organizations who are relying on sort of a third party provider to do a lot of the heavy lifting for them. Obviously, you know, there's some pretty key names in the room. But like anything, it's an external dependency that you need to be able to be clear about what's happening in my environment, what's happening in that environment. And then if I do need to go raise a ticket or urgently call the CEO of my AI vendor or my workload vendor, I need to be able to express like exactly what's happening and what I'm seeing from our end and sharing, right? Like context and sharing so we can all work together. Obviously the second piece is that for a long time, just with the complexity of observability, we've obviously had AI ops for a while and this new search has been, well, what else can we do with AI here? Will it supplant AI ops? Will it support these things? And as things like query languages and datasets have gotten more complex, can they be more consumable? Can my inputs and my outputs be there? One of the things from a consumer perspective, particularly large enterprises is, and you mentioned security, there's a concern of, well, how are these things implemented on the vendor side? Are we pulling things together too quickly? Are my prompts, are my queries being sent to a third party vendor? So there's some concerns there, but I think in general on the vendor side of things, trying to make sure that those concerns are well met and we're experimenting but not just rushing forward into that. Yeah, we've been seeing a lot of people say, you got to have the observability, you got to instrument things like software supply chain without observability, that's kind of a standalone problem that's not fully solved and all these other questions come up. I got to ask you because the observability space was super overpopulated with vendors and companies funded and customers are clearly looking and voting with their wallets right now in choices. How does a customer figure out who's a player and a pretender in the observability space? What are some of the key things that are table stakes but also advantages for customers who are looking at figuring out what their observability play should be? Right, I mean it's a double-edged sword, right? Wide selection of options, but having to pick what's right for you and I think that in past years and even at companies that I worked for before, a lot of the mantra from the vendors and the industry as a whole was essentially your observability strategy can just be tool selection. If I pick a vendor and they tell me the data that I should be generating and they give me the pipeline, they give me the storage, they give me the dashboards and the alerts, then that's all taken care of but things are getting more complex, right? Yeah. Like all the things we talked about, Kubernetes, large language models, all this is. So I would argue that observability strategy no longer can be just tool selection and so there's a lot of choice out there and I don't think there are some hard and fast rules but I think you really have to look at it through the lens of how does my tool selection feed into my observability strategy and my observability strategy, I don't even call that things like open telemetry, right? Why is open telemetry so exciting to people? It's not just because it's cool technology but it's the purpose that it serves. It allows you to own your data and do things that you couldn't do when you were sort of single vendor before. You might be able to take a whole bunch of data, put it in cold storage for compliance. Observability companies generally aren't super focused on compliance, right? You can go put some of it into one vendor, put it into another vendor, tie those things together and now you have choice and if I decide to move from one vendor to another one, my migration friction is a lot less and so that feeds into observability strategy. I can mitigate my risks, I can make sure that I can look past this next vendor selection and I can make sure that I'm setting myself up for the future but all of this has to tie into what's my technology and product strategy? What is my business strategy? So I think to come back to your question, what you really need to be thinking is what do I need from a vendor to support that strategy and ultimately the business outcomes and if I'm getting hard pitches about features and functions, maybe that vendor doesn't have my sort of bigger interest in mind. I mean the complex system now that is the enterprise is distributed computing paradigms is the instrumentation's got to be flexible and have optionality for the customer. I mean at the end of the day. Flexibility is such a thing this week. Yeah, big time. Big time. One of the cornerstones of Chronosphere's business has been cross control and value. How imperative is that right now? Obviously in the current economic conditions, that is key and in a way that's something that's been very consistent for us and the marketers really said, oh, hold on, that is important. And to link it back to what I said before, observability strategy, it's like, well, if before everyone's probably heard some stories about a certain vendor and a certain crypto company who, 60 plus million dollar bill, is that a good example of observability strategy? You might have had the money, but is it reasonable to think we will always have that money to be able to spend on observability in sort of maybe not the most robust way? And so tying that back into all the things that we're doing around cost control, cost control and value is a really important aspect of the strategy, which is, what are we expecting out of observability and what do we need to trade off? Because you can't just spend money infinitely and you can't have every single feature and function and deal with every stakeholder. And that's important because stakeholders can range nowadays from FinOps to the individual developers to the executive audience. Yeah, absolutely. You've talked a lot about observability strategy, but I'm not sure that, well, actually I'm curious, do you find that most companies have a robust observability strategy or are you also educating them on what that strategy should look like? It's a great point. So I think that there's, in the conversations I've had, particularly over the last six to nine months, I don't hear the words observability strategy, but I start to hear things like, could we have a conversation about the bigger picture? I like what you're showing me from a product perspective, but what about data that you don't take? What about data that can't leave my environment? How should I be treating that? What about things before it touches your service? Are there ways that we could better optimize, better utilize what we're doing? And in my role, I'm fortunate enough to be able to have those great conversations up and down the spectrum. And again, it feeds into, say for example, larger, older organizations who may be in the position of, hey, we have to move out of our data center. What do you need from observability to help support that? And so ultimately, if you think from a top-down perspective, what are we trying to accomplish as a business, it needs to feed in. There's not like a giant gap of business outcome tool selection, because you can't go to a vendor and say, well, that's all. So you need to become informed and come with a strong opinion and challenge your vendor, for example. So that strategy needs to feed into, what am I doing with instrumentation? Who are my stakeholders? What do I want from these things? And what maybe am I willing to trade off a little bit in the pursuit of maybe better economics, or faster developer velocity, or the ability to better exceed my customer expectations? Ian, as a field CTO, you're out there talking to customers. Share with the audience what you've seen this past year. What are some of the notable things you guys have done? What's the coolest thing you've worked on this year that you could share as the environment's changing? What are some of the highlights? I think what's interesting to me is tying back to some of the things we said before is the transformations of these larger organizations, complex organizations, really trying to centralize and get behind a very specific point of view. Things like we want to own our instrumentation and our data. We want to be in control of these things and the costs. And so elevating away from maybe point solutions and maybe assortment of open source things. And it's very interesting as well with the current pressures seeing companies who are famous for building some of their own in-house technology around observability, going, it's not a differentiator anymore. The market is caught up and we can align to open source standards and we can collectively take advantage of the work that's been going on across the industry. So there's I think a convergence on things like we want one place to start looking at our problems. We might store the data in a bunch of different places but there's also an understanding that if we do this we can't be reliant on the most senior engineers who also are the bottleneck on innovation to be the bottleneck on our reliability and delighting our customers from a performance perspective. So leveraging the talent and not wasting talent on what could be managed by getting more from everything. Develop a productivity and letting the humans actually get creative and innovate rather than worrying about what's going wrong. I mean, I think it really does matter. So we look forward to having you on the show hopefully in Paris as well. What do you hope that you can say in Paris that we haven't been able to say yet at this show? I think we would love to see that we've gotten to the point where things like observability strategy are common for us to be talking about openly, right? And getting a little away from who got to generative AI first. Yeah. And being able to deliver those key values. And I definitely want to see a lot of the convergence on open telemetry, logs, metrics and now, sorry, metrics tracing and now logs together and seeing what you can do with those data sets together and a common point, right? Can we cross-link these things? Can we get into a more intelligent place where we're less, hey, how do I query my logs directly and more can I derive those insights that I need so that every developer in my organization can be on call successfully? Yep. They can be empowered. Our limited resources can be used more effectively. I love it. Well, we look forward to having that conversation there. I agree with you. I think the observability strategy will be good. We'll keep our ears out for it on the show and see who's talking about it. Ian, thank you so much for being here. Thank you so much. Really appreciate it. John, always a pleasure. And thank you for tuning in to day three here at KubeCon, CloudNativeCon in Chicago. My name's Savannah Peterson and you're watching theCUBE, the leading source for technology news.