KubeCon + CloudNativeCon EU 2026 | Hong Wang, Akuity

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Hong Wang

CEO

Akuity

play_circle_outline Akuity: enterprise software delivery platform commercializing Argo CD and adding capabilities.

play_circle_outline Kargo: Solving Multi-Environment GitOps From Argo CD Dominance to Controlled Promotion, Governance, and Visibility

play_circle_outline Developer workflow: AI increases productivity, parallel branches, and cognitive complexity.

play_circle_outline Prediction: Kargo adoption will accelerate; AI will become ubiquitous in tooling.

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Hong Wang, Akuity

Hong Wang

CEO Akuity

In this interview from KubeCon + CloudNativeCon EU, Hong Wang, chief executive officer of Akuity, joins theCUBE's Rebecca Knight and Rob Strechay to discuss how a decade of building the Argo project has positioned Akuity at the center of Kubernetes-scale software delivery. Wang explains how Argo CD has achieved 67% adoption across production clusters according to CNCF surveys, making GitOps effectively a solved problem for Kubernetes deployments. The missing piece, he argues, is multi-environment continuous promotion — the governed, visible progression of sof... Read more

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What is Akuity, and how is it connected to the Argo project and Argo CD? add

How does Kargo address the missing multi-environment promotion/continuous promotion problem in GitOps? add

How is the rise of AI-assisted coding (e.g., Claude, Codex) changing developer productivity, branching/CI practices, and the demand for deployment automation tools like Argo CD? add

What are the next steps for Akuity, and what do you expect people will be talking about this time next year in Barcelona? add

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Hong Wang, Akuity

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Rebecca Knight

>> Good afternoon everyone and welcome back to theCUBE's live coverage of KubeCon, the CloudNativeCon EU. I'm your host, Rebecca Knight. We are live in Amsterdam. I'm alongside Rob Strechay. Rob, this has been the end of day two. This has been another terrific day here at KubeCon.

Rob Strechay

>> It has flown by and I think the number of topics and the number of projects that we've been able to dig into today has been fantastic.

Rebecca Knight

>> Great guest and we've saved the best for last.

Rob Strechay

>> Yeah.

Rebecca Knight

>> So I would like to welcome-

Rob Strechay

>> Absolutely.

Hong Wang

>> Thank you. Thank you for having me.

Rebecca Knight

>> I would like to welcome Hong Wang, the CEO of Akuity. Thank you so much for coming on the show.

Hong Wang

>> Yeah, thank you for having me.

Rebecca Knight

>> Yeah.

Hong Wang

>> Really looking forward to this conversation.

Rebecca Knight

>> Yeah, so are we. So for those who aren't familiar, tell us a little bit about Akuity. When you were founded, why you were founded, what was the problem you were trying to solve for organizations?

Hong Wang

>> Wow. Oh my God, that's a big question. So we at Akuity, so we're providing the enterprise software delivery platform, but what people know more about us is because Argo. So me and my co-founder has been working on the Argo project for 10 years, a decade. So that's actually the beginning of the KubeCon there, so we were there. So we were already the number one GitHub solution for the Kubernetes deployment. So now our company is kind of trying to commercialize Argo CD, but also adding other capability on top. That's where we are kind of like here working with all the amazing attendee here, like trying to share what we have here.

Rob Strechay

>> So what do you see, as you were talking and you can share some stats you said about the adoption that you've gotten commercially and as well, but when you start to look at GitOps, what is still missing in GitOps? And what is it really, from that perspective, how does Kargo factor into that as well?

Hong Wang

>> Yeah. I mean, I feel the GitOps is already a solved problem by us, so. Kind of like that. Because Argo CD, by the CNCF survey, they said they already have 67 percentage adoption in the production cluster. That's amazing number. That's dominant. So right now, when I'm talking to the people here, I ask them, "Are you using Argo CD?" Very rarely I hear no. So that's kind of to me is the GitOps. Basically, if you're using the Kubernetes, if you're using the Kubernetes in a larger scale, Argo CD is the go to solution. People know the value, people learn the value, people actually trust it already in the production. So from our perspective, I think we know there's a missing piece on top because when we talking about the GitHub solution or Argo CD, it's focused on the single environment, so giving that like a top-notch experience. But what about the promotion? We are talking about the dev staging production or multiple production. How we glue things together.

Rob Strechay

>> Right.

Hong Wang

>> That is the missing piece. That's why we see a lot of opportunities there.

Rob Strechay

>> And-

Rebecca Knight

>> Yeah, go ahead.

Rob Strechay

>> How does Kargo factor into this?

Hong Wang

>> Exactly. That's why we created Kargo. We actually had this Kargo idea the moment we started the Argo CD, add into it. So however, we are very low on the resources. We actually, want moving everything from the private data center to the Kubernetes on AWS fall into it. It's a big project. So we said, let's focus on what's the most important thing, is about Argo CD, the GitHub portion. The promotion idea was there, but we have never had time to implement it. Until when we started Akuity, we say, "Hey, we have to do this now. This is kind of an innovation we have to give to the community." So Kargo is focused on the multi-environment promotion and the continuous promotion concept, is you getting whatever the software you are building as a Docker image or with the configuration. How does that getting, being promoted to the dev, validated in dev, go to the staging, validating the staging, then go to the multiple production in a very controlled with strong governance, with strong visibility? There is no solution out there.

Rebecca Knight

>> When you are talking to platform and infrastructure teams, what are some of the biggest headaches that they tell you? What's keeping them up at night?

Hong Wang

>> I think number one still basically is every increasing demand from the developers for the infrastructure. So you see how many data centers we are building now, right? In the Europe side, there are so many sovereign cloud consideration and because AI is real, AI demand is real. We see our side, last year, we actually did a 43 million deployment for our customers. It's 10 times over 2024. Why?

Rob Strechay

>> Wow.

Hong Wang

>> Because AI is kind of like accelerate the developments now. More features being developed, more bugs being fixed and more things getting deployed to the production. That's like a trend. And there's more infrastructure needs there. People asking, "Hey, where is my GPU cluster? Where do I run my inferencing? Okay, I have this new app. I coded. I need to deploy it because I need to use it for everyone." So that's kind of like ever-increasing. So for that purpose, a bigger cluster, many cluster, bigger infrastructure. However, you are not getting more SRE or platform team. So who is kind of handling the day two, day three, day four operation of the application, ensure they are running? So that's where we see, we think that AI can help. AI kind of like creating the problem.

Rebecca Knight

>> But it can also be part of the solution.

Hong Wang

>> But AI should be the solution to solve the problem also. That's where we are also adding more AI capability on top of our solution to making the platform team and SRE team to be more efficient in the day to day life.

Rob Strechay

>> Do you see that the SREs and, like you said, I always said that being an SRE is a thankless job. And same thing with platform because usually you're only noticed when things go wrong.

Hong Wang

>> That's right.

Rob Strechay

>> Are you seeing that from that perspective and the fact that continuous deployment is really becoming more and more, we see the adoption continuing that people want to deploy hourly versus daily versus weekly.

Hong Wang

>> Yeah. Yeah, more frequently.

Rob Strechay

>> Yeah, more frequently. When you look at that, do you also see people pushing towards developing in the trunk versus all these different branches and that helps with that promotion type thing where you guys are aimed at? Or is it still a lot of different branches and that's also part of what you have to manage there as well?

Hong Wang

>> I think it's even worse now.

Rob Strechay

>> Oh.

Hong Wang

>> Because nowadays people are using the Claude Code or Codex in agentic way to starting working on the issue. The average, for example, a typical tech lead or senior engineer is like five times more efficient now. That means they are working on five issues in parallel. This could be from the same branch or same product. They need multiple branches working together, make sure the CI is running, make sure when they are all down the CI portion, they can go to the production in a more automated way. That's how I see is, it's still good for us. In the end is what we are defining ourselves is we are becoming more like a foundational is, okay, you're talking about the single machine operating system. What are you thinking? Linux. You are talking about the cloud operating system. What are you thinking? Kubernetes. When you're talking about when you want to deploy to those clusters, what are you thinking? Right now is Argo CD's answer. So I think we are right in the place. We anticipate more automation are happening, a massive wave of the things to be deployed to the more infrastructures, more clusters, and we are actually way more important for the future. Yeah.

Rebecca Knight

>> Well, you talked about the developer whose now simultaneous, you said they're more productive, but they're also simultaneously working on these five issues because they're in Claude, Codex. So that sounds very taxing if you are the person in charge of that. Can you talk a little bit about the impact on a developer's day-to-day in terms of their workflow, their individual workflow with Akuity working in the background in Argo?

Hong Wang

>> It's actually a great, great question because I keep talking with my friends. My friends working at Google, Meta, like big guys, so.

Rebecca Knight

>> The who's who of the-

Hong Wang

>> Yeah, who's who, so.

Rebecca Knight

>> Technology industry.

Hong Wang

>> Actually on one side, you feel, oh, there's so much more work. So you feel it's drawing like why, kind of endless thing. But on the other side, it's kind of shifting of the human in this code development role. So you are not like writing the code. You are doing more strategic thinking and context connection. So mean their day job is becoming not like writing, stare at the screen and writing about the structure object, the API. They are more thinking a higher level is, okay, here's the architecture. Here's the feature I want to build. How could I break it down into a trueable step? And make sure it's getting enough detail, the context. When I asking fire of the AI agent at night, like it may be coding for three hours to get in the feature. It's actually get it right, getting it in the efficient way. So it's actually more, I would say that more of my friends in the field are more inspiring rather than more like more tired because they feel, oh, they can do so much now.

Rebecca Knight

>> That's heartening. That's encouraging to hear.

Hong Wang

>> It's encouraging there. Yeah.

Rebecca Knight

>> Yeah.

Rob Strechay

>> Yeah. But do you see that, has the cognitive load just increased significantly? Because like you said, you go between these environments now and you have to understand what has broken and what hasn't broken. And so maybe you're using AI to understand that and try to figure out and troubleshoot it when you've already used AI to build it. So you are getting to things faster, but sometimes that's good and bad from the cognitive load perspective.

Hong Wang

>> Yeah. I mean, that's true. Basically, there are too many things you need to worry about and that's why I think we actually thinking that's what we need to address. So what we are doing here, for example, in our product, we building this Akuity intelligence, is actually kind of like the purpose built AI agent for those continuous delivery solution. And it's actually observe your infrastructure in real time, means you don't need to do it. Let AI do it. Then it actually also, like trying to handling the instant according to the runbook written by the human as the common language by your team. So it's like more automated. So in the end, it's also taking the corrective action autonomously. So it means sure, as the human, I think you will feel like more boring if I'm doing it more like repeatable things. Oh, it's broken. For the same reason it's broken. That's kind of not interesting. But engineer as myself, I like challenging work. I like something new. For the oldest thing, I write in the run book and AI know exactly, when exactly the problem happened. It will do the auto remediation. For the new problem, I understand I need to kind of like, doing more deep diving. That's kind of my day job. But for those boring stuff, AI can do it for sure.

Rebecca Knight

>> But you do still need the human in the loop too.

Hong Wang

>> I totally think so because we run a multi-billion business sometimes in our platform. Production is no joke.

Rob Strechay

>> Yeah.

Hong Wang

>> Right. I work at Intuit. About three, four weeks later, that's our tax due date. Every 10 minutes is $10 million for Intuit. So we cannot afford any outage at that time. So I think the human still needed because AI can hallucinating. That's not the main problem it does, but AI can come up with very random ideas. Sometimes you don't like. So we do want the human in the loop to write in the runbook for us. Means that you want to be very specific and you want the outcome to be very predictable. You don't want AI to do some random stuff. More like, "Hey, here's the symptom. Here's the solution to address it." And you want that. That's why we thinking the human is still pretty tremendous value in this AI era.

Rob Strechay

>> So you see that creating those runbooks, it's like, "Hey, if I'm going to do it once, I might as well then create the runbook so that the next time it has to happen, I don't have to be involved." Almost like from a perspective. What you would do if you were an SRE and you were handing over to another SRE for the next shift and things like that.

Hong Wang

>> With junior engineer-

Rob Strechay

>> Right.

Hong Wang

>> Like for simple stuff, then they can handle it.

Rob Strechay

>> Yeah.

Hong Wang

>> Yeah.

Rob Strechay

>> And do you see that that style has been embraced, that people are like, "Yes, I'm willing to let it go and do these things for me."

Hong Wang

>> I do think it's changing. I think it's like a SRE portion. We are about the SDLC space, right? Coding, challenge, everyone started changing. I think it's like moving, shifting to the right side more. Security, about the observability, about CICD, I think those are kind of like just catching up. You never know about in another month what will happen.

Rebecca Knight

>> Well, it-

Hong Wang

>> AI is like changing every day.

Rebecca Knight

>> Indeed it is, but you are also seeing a lot of traction with enterprise customers. Can you talk a little bit about what you're seeing for adoption and some data you have on that?

Hong Wang

>> Yeah. We have over like 100 enterprise customers now and in the last 12 months, our customer number actually tripled, so which is amazing. And with really good revenue, with really good expansion, I do thinking we are benefits from this AI era. CoreWeave publicly is our biggest customer. Their revenues keep growing and they have many, many big guys and they're using us, actually doing the customer onboarding. So indirectly we are exposed to all the AI companies now. So they kind of see us. They're using Kubernetes, they're using CoreWeave. They're actually indirectly also using us. That's kind of give us a lot of exposure and a lot of growth opportunity. But our customer is coming from all the verticals like financial industry, healthcare, like entertainment industry, gaming, everywhere, so.

Rob Strechay

>> So why do those industries that you're seeing adopting your product come to you? Is it they're more mature in the way that they've handled things already, they have their runbooks built or is it, hey, they know they have this problem, they can't hire their way out of it at this point?

Hong Wang

>> So they just looking for the best of breed solution for the Kubernetes deployment. So we are. That's it. So it's not about the particular industry. It's about when they are adopting the Kubernetes in a large scale, so we are the solution.

Rob Strechay

>> Yeah.

Hong Wang

>> Yeah.

Rebecca Knight

>> All right. Closing us out, what's next for Akuity in your journey and what will we be talking about this time next year in Barcelona?

Hong Wang

>> I do think our Kargo is getting way and way more popular now. Like here we see a lot of people very interested and someone is already using in production. I think as the generic promotion engine, I think we'll see way more traction next year and which already kind of translate to our customer revenue now, like people like the solution, see it's really solving their problem. I do think that momentum will be continue. AI portion, to be honest, I feel it will be ubiquitous. So because it's embedded in our system, it's kind of like everyone will have AI. Everyone have a great experience. I feel we will still talk a lot about AI, but in the end AI will be everywhere.

Rebecca Knight

>> Famous, famous words. Okay, words to live by. Thank you so much. I really appreciate you-

Hong Wang

>> Thank you.

Rebecca Knight

>> Coming on the show Hong.

Hong Wang

>> Thank you. Thank you having me.

Rebecca Knight

>> That wraps up day two of KubeCon + CloudNativeCon EU. I'm Rebecca Knight for Rob Strechay. We will catch you tomorrow. You're watching theCUBE, the leader in enterprise tech news and analysis.