KASLIN FIELDS: Hello, and welcome to the "Kubernetes Podcast" from Google. I'm your host, Kaslin Fields.

MOFI RAHMAN: And I'm Mofi Rahman.

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KASLIN FIELDS: This week's interview was recorded live at Google Cloud Next and features Alain Régnier and Camila Martins talking about recent developments in Kubernetes and cloud-native technologies, including exploring highlights from KubeCon EU and the value of community events. But first, let's get to the news.

MOFI RAHMAN: AWS introduced a specialized Model Context Protocol, or MCP, servers for Amazon eCF, EKS, [INAUDIBLE], and AWS Serverless, providing real-time contextual responses and service-specific guidance to guide AI-assisted application development.

KASLIN FIELDS: Summer is the season of KubeCon events in Asia. KubeCon China took place June 10 to 11. KubeCon Japan was on June 16 and 17. And KubeCon India is coming up August 6 and 7. Be on the lookout for cool announcements coming out around these events.

MOFI RAHMAN: A reminder for CNCF open source project maintainers. The upcoming Maintainer Summit, co-located at KubeCon North America, has an open CFP, which closes July 20. And the maintainer track CFP for KubeCon North America closes on July 7. These opportunities are only available to CNCF project maintainers. But if you are one, make sure you take advantage of these opportunities to share the awesome work you're doing with users and fellow maintainers.

KASLIN FIELDS: A new open source project, llm-d, aims to create a well-lit path for serving Large Language Models, or LLMs, on Kubernetes. It combines vLLM with the Kubernetes Inference Gateway to enable smart, state-aware routing that dramatically improves latency for multi-turn conversations by leveraging KV caching.

MOFI RAHMAN: Speaking of Gateway API Inference Extension, a blog on Gateway API Inference Extension was published. Inference Extension aims to make serving LLMs on Kubernetes easier, with much-needed features like model identity-aware routing and request criticality.

KASLIN FIELDS: And that's the news.

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Hello, everyone. We're coming to you live from Google Cloud Next, where I'm very excited to be recording "Kubernetes Podcast" episodes for video as well as audio. So if you're listening to this on audio, there's also a video that will probably be posted on our YouTube channel. And today, I'm excited to be talking with Camila and-- could you pronounce your name for me? I didn't get to ask you.

ALAIN RÉGNIER: Alain.

KASLIN FIELDS: Alain. Would you like to introduce yourselves?

ALAIN RÉGNIER: Yes. Hello. I'm Alain Régnier. I'm a CTO of a small startup based in Paris called Kubo Labs. And we develop tools to help identify and solve issues on your Kubernetes cluster very quickly.

KASLIN FIELDS: Excellent.

CAMILA MARTINS: Yeah. My name is Camila Martins. I'm from Brazil. I'm a GDE from Google Cloud and also Modern Architecture. And I organize some DevOpsDays events, like CNCF, KCD events, meetups, the KCD Rio de Janeiro, actually, and DevOpsDays through Brazil and Latin. So, yeah, I'm so involved with the community. And also, I'm a senior SRE at Storyblok, too.

KASLIN FIELDS: Thank you both so much for being on today. I'm excited to talk about some of the things that you all have been doing recently. Let's start off with KubeCon EU. Alain, I know that you were there.

ALAIN RÉGNIER: Yes.

KASLIN FIELDS: How did it go?

ALAIN RÉGNIER: Yes, I just switched from KubeCon to Next.

KASLIN FIELDS: Right over. It was the week before.

ALAIN RÉGNIER: Exactly. No, it was great-- a lot of interesting things to find out. One of the big news for me was the NeoNephos project. I don't know if you've heard about it. They mentioned it during the keynote. It's an effort to build some sort of sovereign cloud in Europe. And this is a very major topic in Europe right now.

And I've been involved on the French side of things with what's called [? Second ?] Cloud there. And this new project that we hadn't heard about before is actually backed by the Linux Foundation. And as you can imagine, this is a big thing-- a lot of other interesting things.

So I was in Salt Lake City before that. I was in Paris before that. I've been going to KubeCon many times over the last few years. One of the thing that was very interesting to me also was the presence of OpenTelemetry everywhere, like, everywhere. And this is really a very interesting and good thing for the industry. Platform engineering was a big thing, also. There are still some solution that seems a bit complex to implement within companies, but we're getting there.

So something also that was very interesting for me in London, especially compared to the other edition, was that I attended several very technical talks. That's not always the case. Maybe I miss them on the program. But this time, a couple-- actually, a couple of sessions, I went out of the session thinking, wow, I definitely need to watch it again. Because it was very interesting, very technical, the kind that I like, and I did not get everything.

Well, that's pretty much it. Otherwise, just a regular KubeCon Europe and very similar to what took place in Paris last year or in Amsterdam two years ago.

KASLIN FIELDS: Yeah, the KubeCon schedule is so large. It's hard to judge which talks will be exactly what you want them to be. And so that's something common that I hear.

So a couple of themes from KubeCon, it sounds like-- observability, especially OpenTelemetry platform engineering, which I've seen here as well. We had a platform engineering meetup, which was really, really crowded here on the Next show floor. Excellent.

ALAIN RÉGNIER: One nice thing, also, that's a personal thing-- there was more observability than AI, I would say, as a--

KASLIN FIELDS: Oh, I did hear that it was lower.

ALAIN RÉGNIER: Yes, yes. And that was a definitive plus. Of course, we still need AI. And we want AI in observability, too. But I think there was much more related to what we actually do with our customers.

KASLIN FIELDS: A better balance?

ALAIN RÉGNIER: Yes.

KASLIN FIELDS: So with the new upcoming AI stuff, which a lot of folks aren't really doing yet, and the stuff that everyone is actually doing--

ALAIN RÉGNIER: Doing, exactly.

KASLIN FIELDS: Understandable. And KubeCon is, of course, a huge event for the cloud-native community and is used as an example for a lot of different events. And Camila, would you like to talk about that?

CAMILA MARTINS: Yeah. CNCF, and we have other events around the world, where we have a lot of different communities. So for example, we have the Docker community. Docker is right here, too. And we have the Docker community and also Docker Captains.

And we try to help people to understand containers because it's curious. But we have a lot of people that want to go inside, go deeper in the world of developer and DevOps, DevSecOps. But they do not understand, nowadays, on how to build, how to create images.

And I think the most important thing is to understand the basics. And we go to the containers. And we have other communities there. We have Elastic that-- it's also here. We have the CNCF community. So we had it right now. In the last month, we had KCD event in Rio de Janeiro.

KASLIN FIELDS: And that's Kubernetes Community Days, for anyone who doesn't know the acronym.

CAMILA MARTINS: Exactly. And we had a bunch of people almost for our community that just started on this year. And we had only three months to organize. We had 300 people. And everyone was so involved and in a place that it only supports, like, 100 and a half-- 150 people.

And so we saw people standing up and watching the talks. But it was so amazing because we have a community in Latin America that wants to help, wants to share. And I think in DevOps and communities like cloud-native, the most important thing, it's how we can help support, make people migrate to other careers. And I saw a lot of people changing their lives.

And these events, like Google Cloud Next, KubeCon that I was in Amsterdam two years ago, and also in Salt Lake last year-- they are so important to create connection, networking, and also to understand that it's not about only your journey. But we have a bunch of people that it's only in the same journey.

So you have a lot of people that can help you. So that's why I believe in the communities. And that's why I support events. So we have all of these communities-- also, the HashiCorp community. That's also here.

KASLIN FIELDS: Wow.

CAMILA MARTINS: All these companies-- they are not just in the booths. But they are trying to help these people to go deeper and go far. So it's hard work. I think people that go to the events-- I don't know if everybody understands how hard it is to do all of this.

And that's why I celebrate this. And I say to everybody that I know that work and volunteer for it, thanks. Thanks for your work. Thanks for being a volunteer because it's really hard work to do events like this. Even if it's 160 people, 50 people, a meetup for 20 people, it's really hard work because we have other things to do. But we are doing this because we believe on this.

KASLIN FIELDS: Absolutely. And you run Kubernetes Community Days Brazil. And you do events throughout Latin America? That was a lot of events.

CAMILA MARTINS: Yeah. I'm an organizer from KCD Rio de Janeiro, with other incredible people. But I'm also organizing DevOpsDays Rio de Janeiro and supporting other DevOpsDays that they are through Brazil.

And I'm a speaker in a lot of Latin America events, not only from KCD and CNCF, but also from Google. For example, we had right now-- we just ended the season of the IWD, International Women's Day, from Google. And we had in Rio.

And I'm going in the end of this-- it's ending this season. So in the end of this month, I'm going to Bogotá to talk to amazing women. And we are going to start-- we are starting right now also the Build with AI. So, yeah, Google, it's also celebrating. And we have a lot of things that-- DevRel things and stuff to do.

KASLIN FIELDS: Let's dive deeper into the content that happens with these kinds of events. What do folks want to learn? Alain, you were at KubeCon EU. You talked a little bit about some of the talks that you saw that were really technical. I'd love to hear more about those. And I'd also love to hear about a talk that I hear you gave about the 10 best practices for Kubernetes. Could you give us a little sneak peek at that? What are some of your top best practices? And then we'll come back to your favorite topic.

ALAIN RÉGNIER: Sure. Sure, yeah. So actually, it was a lightning talk regarding GKE and best practices. What can I say? For example, when you get started, you need to be very careful with your node pool, the way you create them, because they can cost you a lot more than they actually need to.

For example, you can select specifically a zone or a region where it's going to be cheaper for you. So you have to evaluate the ratio between the latency for your users and the price you're going to pay.

Something that you can do is you can purchase committed usage so that basically you say, I'm going to be using for one year, for three years. You're going to get a discount. It's a nice way to save on the cost.

You can also use a pre-emptible VM. It's now being called spot VMs on GKE, where basically, the VM can be kicked at some point. But it will be much cheaper for your usage. So if your workload can handle it, it's very nice and a nice way to save money.

Another aspect that you can also investigate is all the advanced networking features you get on GKE. And very often, people don't know them or don't know them well enough-- for example, private clusters, where you're going to get only private IP for your nodes, low security risk of someone accessing the nodes from the outside, the authorized networks where you specify which IP address can access the Kubernetes API.

What else? Also, the Dataplane V2, which is a very nice feature, where basically it's based on eBPF. And you have advanced features. One that I particularly like is, when you create network policies on your cluster, something is being prevented. Well, nice. The network policy is working. But you don't know exactly who was making a request and so on. All that, you can get the logs with Dataplane V2. That's pretty nice. So again, knowing in advance all those network features.

Another one, also, which is very nice is the IP Alias mode on GCP, which turns into what I think is called VPC-native cluster, now, on GKE, where, basically, one node will get its IP address, but also a full subnet of IP addresses that will be attached to the node. And those IP addresses will be used for the pods directly. So from a routing point of view, from an overhead point of view, this is actually much more efficient.

Well, that's the kind of thing that I think you should know when you're using GKE. And maybe a third one, which is very rarely used-- and I'm very surprised by that-- it's the GKE dashboards. The whole thing has been completely revamped. It's very powerful. You can do filtering. You can do a lot of things.

And every time I ask people, I only have a few hands that raise. Oh, I didn't know I could go there. And usually, they get the cluster, and they work with the cluster. Well, one advice is to really spend half an hour with the GKE dashboard. And then you will always get back to them.

KASLIN FIELDS: Yeah, kind of boiling it down to three points that really apply anywhere is node management, bring out what machines are in your cluster, and keeping it to the machines that you need and the sizes that you need. Fascinating area of cost optimization that I love to talk about. I might ask another question about that.

And then networking-- always good to understand how your networks work, especially if you're working in the cloud. If you're working between different regions, there can be costs associated with that. If you have to transfer data outside of the cloud, there's always costs to think about. Definitely something that you want to look into and make sure that you understand, as you're getting into wherever you're running your Kubernetes clusters. And so we've got node management--

ALAIN RÉGNIER: Networking.

KASLIN FIELDS: --networking, and observability, dashboards, ways that you can visualize what's going on in your cluster so that you can control those costs. You can't control the costs if you don't know what you're spending on.

ALAIN RÉGNIER: Yes. And don't just set up observability and forget about it. Spend the required amount of time to learn how to use them. And go back regularly to your dashboard so that you don't lose the touch. Because we also see, often, people that have not been to their observability tools for a while. And they just don't know how to use them anymore. And so they stop using it completely.

KASLIN FIELDS: Yep. And then at some point, you're like, oh, what-- didn't we have something that told me what was happening with this cluster? Where did that go? I've seen that happen before.

All right. Camila, let's talk a little bit about some of the content that you've seen in events lately. What are some of the big trends that you're seeing around Kubernetes and cloud-native? What do you think people want to learn about?

CAMILA MARTINS: A lot about observability. Like Alain said before, things like OpenTelemetry-- I'm watching a lot of these things. In Salt Lake, I saw a bunch of talks about it and a lot of trends with AI. So yeah, absolutely, AI, it's a thing.

So how we can use AI in monitoring. So how we can apply it to understand when it's a peak in monitoring and understanding if it's peak, it's normal, and it's going to be normalized. It's a thing that it's out of the monitoring. Or maybe also in documentation, AI to help to create documentation because we know that it's not everybody-- for example, me-- that we do not like to write documentation as well.

But we know that it's so important. So we have gen AI to, well, create this documentation, not only to us to understand what we did before, what we are doing, but to also document our architecture to our team, to other teams across work and in our company.

And also, I'm watching some companies that are trying to put AI as a thing to-- hey, we use AI, too. So come on. It's really a thing. And I saw a report that-- it's really interesting-- from Docker. Because it's also a thing that we are talking a lot about, like AI-- what's going to happen to us with AI?

And Docker did a report that is so interesting. Gen AI, it's helping us with our work, like, for example, to build CLI comments or commands or for to create documentation or for create tests. Because in our infrastructure environments, we know there's not every place that we create tests for our infrastructure behavior. And we know that it's a thing that we need, and also to create code and what kind of code we are creating.

So all of these models that also we are seeing right now with Gemini 2.5 and others, I think these models that are best improved. We can create code that we can go further with our infrastructure as code, so we can create best Terraform, Docker, and implement it in our cloud.

So I know that sometimes, when you get-- and also to troubleshooting. Because sometimes, when we get a thing that's going wrong, we just got there. And we're just searching in Google. And now Google is better because we have Gemini.

KASLIN FIELDS: I'm glad somebody else has figured it out!

CAMILA MARTINS: We have Gemini, too.

KASLIN FIELDS: Yeah.

CAMILA MARTINS: And right now, we have-- and it was a problem. Because sometimes that error that we had, nobody had before. So it was like, OK, so what we can do? And Gemini, it's improving us to, OK, what kind of things we can do? Because we are mixing the models with the documentation that this platform that we are trying to troubleshoot has.

So yeah, it's improving us to go best with our applications and to maintain our infrastructure. So I think all of the companies, in a way, they are trying to put AI, but to improve what they have in a way about observability or to create an infrastructure or to maintain this infrastructure. Well, but the things that I see the most, like Alain said, it's more about observability and how to work with this observability.

And like I said, a lot of OpenTelemetry. And I think that I really love that it's eBPF. I love eBPF. I just met Liz Rice. Liz Rice, if you are hearing this, I love you.

KASLIN FIELDS: We love you, Liz.

CAMILA MARTINS: We love you, Liz. And also, about these advanced networks, network policies, how to deal with different protocols, and how to work inside the Kubernetes with high performancy, a cluster mesh, service mesh, improve the service mesh. Because we are talking about service mesh for a long time, but how to improve the service mesh?

So this job with eBPF, they are going really deep dive with that, too. And it's amazing. Not only [INAUDIBLE], but other companies, too. It's so nice.

ALAIN RÉGNIER: And just to get back on what you said, I think it's important also to realize that the results we get from AI tools have considerably improved over the last couple of years.

KASLIN FIELDS: Yeah, especially over the last couple months.

ALAIN RÉGNIER: You're right.

KASLIN FIELDS: Amazing.

ALAIN RÉGNIER: And we're getting to a point where it's actually becoming really useful. And that's something to--

KASLIN FIELDS: I love the combination in what you were saying of observability and AI. I think there's something really important to point out there. You were mentioning documentation, which I love the call-out for.

AI can be such a great tool to get you past that blank page. If you need to write some documentation and you're like, oh, I don't even know where to begin, or if you're writing a blog post, or whatever you may be documenting, AI can be really useful for just getting you started. And with AI and the ability to generate these things, I think the volume of everything we're seeing is going to increase dramatically.

And being able to understand what we have when we're operating in that kind of scale and when there's that kind of scale of things to consume, observability becomes even more important again. Even though we're talking about observability of systems, I think it all works together. AI is going to explode the amount of stuff that we're looking at in all kinds of different areas.

CAMILA MARTINS: Yeah. I think AI doesn't need to be the whole thing, but a way to use starting. So for example, I don't know how to start this architecture or this documentation, but how can I start it? So it can be useful to create ideas to use. So it's really useful for-- yeah, yeah, for sure.

KASLIN FIELDS: I like to remind folks that content that exists is better than content that doesn't.

CAMILA MARTINS: Yeah, absolutely.

KASLIN FIELDS: AI is so helpful for that. But you do always have to check it. It can make things up. So you don't want to just AI-generate all of your stuff. You want to at least check that it's right. But it can get you far, fast.

ALAIN RÉGNIER: And you want to execute on production what the AI gave you, before reading it and making sure--

[AUDIO OUT]

KASLIN FIELDS: There's definitely no security problems in this code. So coming back to Alain, let's talk about some of those talks that you've seen recently. What are some of the coolest things that you've learned in talks? And we'll be quick with this one, whatever you can get off the top of your head.

ALAIN RÉGNIER: So there's one that was a subject that I wasn't very familiar with, which was the CSI, the storage interface. I attended a talk that was talking about how to extend the CSI API. But they gave a very nice overview and deep dive of how it works and why. And this was particularly interesting for me because, again, this is a subject I did not really dig before.

KASLIN FIELDS: And was that at KubeCon?

ALAIN RÉGNIER: At KubeCon.

KASLIN FIELDS: The Container Security Interface?

ALAIN RÉGNIER: No. Yeah, no, Container Storage Interface.

KASLIN FIELDS: Storage Interface. There we go. I was like, what is this? [LAUGHS]

ALAIN RÉGNIER: And I was surprised because I went to the talk just to learn a few things. And it was much more insightful than I expected.

KASLIN FIELDS: I see a tie-in to the AI thing again. It's just what's top of mind, isn't it? The prevalence of stateful applications on Kubernetes is just skyrocketing, another reason that you need to observe it more closely, and also that storage is becoming really important.

ALAIN RÉGNIER: Yes.

KASLIN FIELDS: I don't know if they made that tie-in in the talk.

ALAIN RÉGNIER: So not in that talk, but that's an interesting point. I also got to see, on a developer lounge area, a talk about-- I forget exactly the name of the project. But it basically is Postgres running directly on the cluster, not even as a stateful set, but with a redundancy, with a failover directly. And the demo they made was very impressive. So I definitely need to dig in that again.

KASLIN FIELDS: While we're talking about storage and stateful, I'll take the opportunity to go off on a slight tangent and tell everyone something that I think folks should know. If you've ever looked into Agones, it's an open source project for running game servers on Kubernetes.

When I started looking into it with Mark Mandel, who is one of the folks who-- really, the person who created it, what I noticed is that it's just a really good tool and system for running stateful workloads on Kubernetes. So if you haven't checked that out for your stateful workloads, even though they're not game servers, you might check out the structures and processes that Agones has put in place. It could be useful for all kinds of stateful workloads.

So the CSI talk. Any others come to mind?

ALAIN RÉGNIER: What else? Well, there were several on AI at different level, including here at Next, AI for Developers. Because we do development, as I mentioned. And starting from asking ChatGPT a couple years ago, how would I do that, and just finding which framework, which API, and getting some pretty good results, now we see a new mechanism, a new application, like Windsurf or Cursor and so on.

And integration in your IntelliJ IDE of something like a Gemini, those are very powerful tools. And the demo that I've seen were very interesting. That's something also that I definitely want to-- but for me, going to a conference like that, it's a good opportunity to learn about new things. And then you want to dig into them as soon as you're back. And the key aspect of all that is, are you going to be able to dig into them over the last couple of weeks after the show or months later?

KASLIN FIELDS: Yeah. [CHUCKLES] And I like-- it's always good to think about the perspective that you're looking at AI tools from. Because there are so many AI tools for the developer workflow that I think folks are really interested in how they can make their own work, as developers, much faster.

And then there's, of course, all the AI tools that you build into applications for your users. So there's a couple of different perspectives to consider there. So we're talking about developer tools that are integrating AI. Excellent.

And Camila, you've had some time to think about your top talks and topics recently. What are some things-- some of the best talks that you've seen recently?

CAMILA MARTINS: I saw some talks are really interesting. And for example, I saw on how AI helped a McDonald's in [INAUDIBLE].

KASLIN FIELDS: Oh, yeah. I love user stories.

CAMILA MARTINS: And with data governance, it was really nice how to deal with. Because I was talking about it before. It's hard to deal with events. And it's hard to deal with a huge restaurant worldwide. And they are using AI with that. And it's so interesting to see how AI is helping with different contexts. So I saw that for McDonald's, and I saw that for Target, too, to deal in the context of McDonald's with the food and Target with electronics.

And I saw also a thing that it's more academical, that it's "Gee-co" or [? Gecko. ?] I think this is the name. It was for models to images. And so how we are dealing with understand if-- it's a thing that we already have, but they are improving it-- how to understand if it's a dog or not, different dogs. But they're making it in an academical way. So it was really nice.

We had GDE conferences, so it was really amazing. And for me, the keynotes that we had, it was so nice-- the Veo 2, and also the AI agents. Because I'm more in Google Cloud stuff. But because we have a bunch of AI things, we need to learn this thing. So AI agents, for me, it was a thing.

So in the first day of the keynote, one thing that really impressed me was in the moment of-- I don't remember, but an e-commerce that you can talk with the chat and collect everything and make discounts and go to the checkout and make the whole process just talking with the website. It was a thing.

KASLIN FIELDS: So ways we interact with computers are changing.

CAMILA MARTINS: Yeah. Yeah, absolutely. And how they are now understanding us. So before, it was a thing. We talk, and sometimes they do not understood before. And now we talk, and they understand. It's like, oh, amazing. I'm talking like it's really a person. It was crazy.

And so we had a lot of new ideas and features and developer and the general keynote. It was a thing. But the AI agents and this news about the Veo 2 that-- it's a thing that I'm following since the last year in the Google I/O. It's a thing that really impressed me, for sure. And how they are helping other companies, banks and clouds and multi-cluster and multi-cloud content-- it's really a thing, for sure. Some things just Gemini does.

KASLIN FIELDS: I love keynotes at any event-- KubeCon, Next, whatever conference you may be going to-- because they always try to have the biggest themes really well-represented there. And so you get a lot out of going to one session, even though it's a very long session. I also love that you mentioned the developer keynote because I was actually backstage during the developer keynote, helping to run some of the backups.

ALAIN RÉGNIER: Wow.

KASLIN FIELDS: Fun fact-- one of the two failures in the developer keynote was real.

ALAIN RÉGNIER: Wow.

KASLIN FIELDS: So go check that out.

ALAIN RÉGNIER: OK.

[LAUGHTER]

KASLIN FIELDS: See if you can tell which one was the real failure. It was so smooth. It's hard to tell. So thank you so much, both of you, for being on today. And I'm so glad that we got to talk together at Google Cloud Next and make a video. Thank you so much.

CAMILA MARTINS: Thank you.

ALAIN RÉGNIER: Thank you.

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KASLIN FIELDS: That brings us to the end of another episode. If you enjoyed the show, please help us spread the word and tell a friend. If you have any feedback for us, you can find us on social media @kubernetespod or reach us by email at kubernetespodcast@google.com.

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