Kubernetes Clusters Network Security

When (day):
17:00 - 18:00

Session Video

About this session

Description: Learn how to secure network communications and segments within Kubernetes clusters to thwart unknown threats at the network level.


  • Implementing network policies in Kubernetes.
  • Network segmentation for enhanced security.
  • Monitoring and analyzing network traffic for anomalies


Dinis Cruz - 00:00 You. Hi. Welcome to this open Security Summit in October 2023. And I’m here with Nathan, and Mario is going to join in for a bit, right? And we’re going to be talking about Kubernetes Clusters network security, or I guess Kubernetes security, right? Because that’s really the key topic. So, Nathan, why don’t you kick us off?

Nathan Case - 00:22 So I guess the question becomes, like, as we look at this whole thing, first of all, hey, I’m Nate. Secondly, my views are my own. Yada, yada. Not the company, all of that. But today, as we speak about this, the real question becomes kind of this discussion about what is security and what is network security in Kubernetes? And what can you expect? What should you expect, what should you hope mean? When you asked me to do mean, like, honestly, I kind of sat back and okay, like, I just did a talk about Cubeshark. We can totally talk about Cubeshark. The company I’m working for, CORSIA, has a new product called Cast, which is kind of an extension of Cubeshark. And there are new things that you can do there. There are a handful of stuff on open source projects we can look at online.

Nathan Case - 01:05 But when it comes to actual security, I mean, what do you guys think? It feels like the network security of days gone by when I used to play with switches and hubs and routers and coax connections, all of that’s gone. And I think we end up with this really interesting, logical setup that, frankly, hasn’t existed before.

Dinis Cruz - 01:25 One of the things I’ve done, which I still feel it worked quite spectacularly, was to build a large number of very small clusters. And I arrived there from a point of view of having the least amount of moving parts by having lots of problems with scaling, right? And this was a project where I had to go from small amount to file spring process to large amount of files. And there’s this interesting spot where you start to fight Kubernetes, right? You start to fight the system, and then it’s kind of like this thing where eventually everything starts to break, right? Because you either struggle with the backplane, you struggle with the network, you struggle with the ability to start new pods.

Dinis Cruz - 02:15 It’s almost become, in a weird way, I felt this anti pattern that suddenly the more stable things become, the more locked things become, the more solid they were. But I was like, hold on. The whole point of Kubernetes is this dynamic load, right? It’s go up, go down, go up or down. So I started to go into this mode of, okay, what’s the smallest cluster that I can do? Because in a way, the irony is that it’s almost like you go, okay, you need multi nodes, you need multiple big clusters, because you get resilience. And I start saying, yeah, but I’m actually losing quite a lot, so I start going, okay. So I got to the point where we created one node, and it was one node cluster that had one, basically deployment. We had very small number of pods that were per application.

Dinis Cruz - 03:08 And then the thing that was really interesting is that from a design point of view, it really forced you to think, where do you store things? What’s persistent, what’s not persistent? There was tons of problems that existed. It’s like the HS two. I don’t know if you’re in the UK or not. Are you in the UK?

Nathan Case - 03:25 No.

Dinis Cruz - 03:26 Yeah, there’s a big shit show here because we had this massive megalomial project of building one thing super big, right? And then of course, he blew up. Costs got bigger and bigger because the complexity got bigger and bigger with the project. Right. When I was basically thinking about this was like, small clusters actually have lots of advantages because you can scale up and down very easily. The only question there’s a bit of state. But in a weird way, I like that problem because it forced me to take state away for sometimes parts of the cluster which actually make the cluster itself disposable, because it’s almost like, think about it, we take Kubernetes, the parts should be disposable, but then are the nodes disposable and is the cluster themselves disposable?

Dinis Cruz - 04:14 Because or else you end up with this gigantic cluster that by the time it’s up, nobody really understands how the cluster is actually being set up, right?

Nathan Case - 04:25 To me being the old guy and saying that to two old guys, but rolling this all the way back to the day when we used to have Sans and deal with a Brocade fabric infrastructure and deal with VMs that would sit on top of that. And then you deal with network switches and blade switches that would have to sit on top of that. As we start looking at resilience and we start trying to understand what security is, and I say this because it feels right to me, and push back, please, if you think I’m wrong. And like, you would never but still, the concept being that one of the things that was always really hard was to understand the impact of all of the pieces, parts that went into the whole thing that you were building and we used to have to deal with.

Nathan Case - 05:11 This is my backplane. And my backplane is going to support 20 gigs. And if we have a 20 gig backplane, that means that I can sacrifice ten gigs for network and ten gigs for storage. And then all of these things start coming in and it feels like we’re back to almost the exact same thing with Kubernetes, where I’ve got a Kubernetes cluster and now I’ve got to figure out what are the actual resources that I’ve got the ability to begin to architect with. And if I start to build out an application that goes over those resource bounds, then it doesn’t really matter anymore.

Speaker 3 - 05:42 I think there’s a few things from my perspective, what I see these days is that obviously Kubernetes has a layer of abstraction, but people do not intimately understand because you have a number of layers. You have the whole container security. You have container networking security, and then you have obviously host supporting the container security. So people do not understand that. How do you apply security context at the container level? Then you go into something like Open Policy Agent Apparm, or how do you secure intercontainer communication? And then you go into runtime security, something like Falco deployments. There is a lack of knowledge and understanding because most of the containers building is done either via DevOps or developers themselves.

Speaker 3 - 06:34 So having we discussed in previous sessions how we can build those security reusable blocks, so how we can whitelist a number of container images that has specific security solutions already built in. So you say just use this. There’s a big disconnect, I think, especially when you start leveraging things like AKS. If you run a production cluster, you get obviously Microsoft image that’s quite secure. But then if you run the dev clusters, you use all sorts of images. There’s obviously riddle with vulnerabilities. How do you address the change between development cluster and production? Because obviously people testing code in various environments, but if they don’t match but.

Dinis Cruz - 07:15 That’S the beauty, but even beauty of small clusters. See, the beauty of small clusters is that you can run them locally. So you have the same cluster throughout, right? I always felt that the only difference between local pre prod, so local dev, QA preprod prod, the only difference should be scale.

Nathan Case - 07:38 That’s why I’m pushing back to the resource question, though, frankly, because as you start looking at deploying into Azure, you look at deploying into a cloud provider, take your pick of who all of a sudden you’ve deployed to two data centers, and those data centers might be 100 miles, 150 miles apart. So now, as we look at if we’re looking at security from the vulnerability question that you just brought up, or the question generally that Marius just talked about, where we start looking at the images and all the other pieces that go into your Kubernetes cluster, what does it become? Does it become possible for me to evaluate network availability, latency things that I normally would have looked at in a networking implementation for a larger enterprise?

Dinis Cruz - 08:21 Not really. Well, see, this is the thing. If you have smaller clusters, right, you can simulate all of that because and by the way, smaller could be two, three, four, or five nodes, because the cluster or the cluster of clusters, right? That environment is the app, right? So the thing about that, for example, that particular example is that if you can spin up your environment, you can now run your simulations, right? You can say, okay, now give me this traffic, now do this so what was very interesting is that were able to build very focused testing tools. Again using kubernetes, right? Actually, using lambda functions actually was really cool to scale up. That could generate an insane amount of traffic. But we able to test, you know what we found? We found that check this out, right?

Dinis Cruz - 09:12 There was a moment where I was deploying the same Kubernetes. Remember, this is one node per, but each EC two instance is a Kubernetes node. Each one, right? Each EC two instance is a Kubernetes node. We did this test where I was running, I think it was about 150 EC two instances. So I had 150 clusters across. I think it was five data centers. And then you had 15, right? Basically, because I got to the point where I built a command line. It was very scary, right? Because I had a command line, I was like, spin this up. How many regions? How many easy to instance per image? And it was the same image everywhere, right? We will run it. You know what happened? After a while, we start to detect wild inconsistencies in AWS infrastructure, right?

Dinis Cruz - 09:59 So you would have literally the same request sent to 150 instances, right? And every now and then and we will keep turning the volume up, right? So we keep finding the point where they were really hot, right? And there was instances that were fine all the time. There was instances that had a wobble and there was instance that had fucking leisure heart attacks, right? And then when I realized and I remember chatting the AWS guys on it’s like, yeah, because it depends on the neighbors. But think about it.

Nathan Case - 10:31 Neighbors and a whole bunch of other infrastructure.

Dinis Cruz - 10:35 But think about what that means. It means that we had to add code to our clusters to be aware of your environment. So even if you think you have 20 gigs, you might not have 20 gigs.

Nathan Case - 10:47 And that’s exactly what I was getting at, was plan the resource plan outright.

Dinis Cruz - 10:52 But no, but this is the difference. It’s not even planning is your cluster has to adapt itself. So we had a mode where and, you know, the beauty of this architecture is you put load balances in front. You know, what was the solution? Actually, eventually, the solution was kill it. Literally, we got to the point where once the health checks got to a point, reduce the traffic. So take it off from the load balancer, let it die off and kill it. And even AWS guy says, yeah, that’s the better way. Because if you start a new one, you’re going to a different location, right?

Nathan Case - 11:23 Yeah. And that’s the point, is that in many cases, really, what you want to do is set up this setup where you’re looking at multiple points in your application. And if there’s a particular instance that’s not working correctly, you need to know. And that might be just setting up a simple I mean, I’ve done it before with pings. If you can’t ping X or you can’t get an Http response from just kill it.

Dinis Cruz - 11:44 Yeah. But try doing that at node level and it’s very hard.

Nathan Case - 11:48 It’s hard, yeah.

Dinis Cruz - 11:49 That’s why the smaller again, the cluster. And then for me, the solution here was to actually create clusters of clusters, even app, because then you can say, what are all the resources?

Nathan Case - 12:02 But then I’m going to push back and say, at what point have you gone too far? At what point have we abstracted to the point of just the silly? Would it have been easier to just use, I’m going to say elastic beanstalk.

Dinis Cruz - 12:16 Well, there’s a point where lambdas might be perfectly fine, right, but that’s a very valid point. There’s a point where, in a way, there should be an evolution, right. There’s a point where lambdas are not good enough or too expensive, right. Then that’s when you go containers. And there’s a point where containers gets too big, that’s where you go to the cluster and the moment where in a way, I think it’s almost like we try to optimize something that should not be optimized, which is this idea that, oh, I have one cluster, I have five clusters. Usually people don’t have five clusters. They have one big fuck off one and a couple of redundancy ones. Right. At least that’s what I’ve seen a lot. It’s very risky, right?

Dinis Cruz - 12:54 It’s very risky because it means every time you push a new update, you risk blowing up your entire cluster.

Nathan Case - 13:00 I think Marius has got a point here, but after Marius goes, then I’ve got a point back to you.

Speaker 3 - 13:04 I think that’s where you mentioned kind of I think if you discussing Kubernetes deployments, obviously it comes down to cost, but you need to get to the point where you can ultimately run a proper chaos shop, where you can inject faults continuously to evaluate where the problems occur. So being proactivity then, instead of reactive, and then you can plan, because obviously you foresee particular growth, whether it’s traffic, customer acquisition and things like that, where you can potentially get ahead of the curve where the problems might occur. And that will feed into your design questions, essentially.

Nathan Case - 13:47 Yep. And I think you’re hitting exactly what I was going to hit Marius, and apologies, I’m a little under the weather today, but I completely agree with you. This is security and resilience by design. You can’t just pretend that it’s going to be OK because you’re using Kubernetes and building your application so that it is aware of both the infrastructure that it’s on and frankly, the limits of the infrastructure that it’s on. And if it realizes that, you know what, I really can’t get to this machine over here, maybe it’s time to spin up another alternative because I’m not working right.

Dinis Cruz - 14:21 I think the bit I like to expand more in terms of security is I always find that the less moving parts, the better, right? So if you take that to an extreme and this is where I feel there’s a potential that we haven’t fully fulfilled here, which is that we should be absolutely brutal, for example, with the size of images, absolutely brutal with what’s inside the containers, even what’s inside Kubernetes. It’s not because the normal Kubernetes deployment has these features that you wanted. It’s almost like, what is the minimal viable deployment that you can do? But here’s the problem. This is the thing that I don’t think you experience until you really experience kubernetes as a disposable unit is that if you can spin up kubernetes clusters super easy.

Dinis Cruz - 15:08 And by the way, at the moment, last time I checked, AWS clusters or azure clusters still take, like, minutes, and I’m like, what the hell are they doing playing chess, right? A cluster should start, right? So if your cluster doesn’t just start super quickly, you can’t experiment, right? Think about it, every experiment takes ten minutes, 2 hours, whatever, and you can’t do that so you can’t lock things down because you need the interactivity of the experimentation.

Nathan Case - 15:36 Let’s be honest, I mean, it’s expensive to experiment that way sometimes. Just in full disclosure, I have four clusters in my house right now, so it is what it is, and it’s just what I’m running here at home, and that’s fun and I’m enjoying it. There’s no real reason for me to run Kubernetes in the house. I mean, come on, that’s just silly, but at the same time, it adds value, right?

Dinis Cruz - 15:58 You can experiment, right.

Nathan Case - 16:02 But back to your point, and to the point that in general, I think there’s some point at which we’re going to have to start looking at what is the minimum viable container that we can actually run. So it’s become more and more concerning to me as we’ve talked about different software supply chain attacks and seen different reality as we look at network security, that’s fine. But the reality is, if my implementation, if my image is so bloated with, I’ve got a full installation of Take Your Pick of OS, and then I’m running my little app inside of it.

Dinis Cruz - 16:34 I really like those light images. Right.

Nathan Case - 16:37 Well, the hardened images, yeah, I think we need get to the point where we just automatically run a script at the end of it and it looks at it and goes, oh, I see you’re just using these three things and rips out.

Dinis Cruz - 16:45 So here I’m going to bring the good old these days, gen AI, right? And LLMs, that’s another area where I think it can add crazy value. Imagine a world where we take an image, we feed it to a Gen Tweaked, an agent that’s been tweaked for understanding that, and we say, Start removing things, right?

Nathan Case - 17:05 I don’t even know if we need Gen AI to do it. I mean, can’t we just do it with a basic process, call and figure out what’s running because you need contact.

Dinis Cruz - 17:11 Okay, I think you could do it like that, but that’s very complex, very fast because I think you need a level of reasoning, you need a level of logic that is very hard to code. And I could see how having an LLM that has a series of prompts and maybe not one, maybe two, three, four or five LLMs working together, I could see how that’s much more usable and practical than trying to code. Because to be honest, I think people have tried to do it. The problem is you need a degree of context, you need a degree of understanding and even what’s the objective that is very hard to code.

Speaker 3 - 17:50 Yeah, I think you can leverage Geni in a few things because as we discussed in the beginning, things like mapping of the traffic between the specific containers. So Genai potentially could help you build a map. Who needs to talk with what? But I think, as Nathan mentioned, I think we need to take up a notch because the one thing that is always missed yes, we do in agile sort of deployment and agile code changes and all of that, but drift Analysis, it’s one sort of area that’s always neglected.

Dinis Cruz - 18:31 What do you mean?

Speaker 3 - 18:32 Leveraging something like Open Policy Agent where we can define how our production clusters should look like to make sure that we are alerted from people a making mistakes and B just going berserk on some new innovation that they decided, oh, just deploy and see what happens.

Nathan Case - 18:54 Even if it’s just a basic like I’m using this open source library and today it changed from A to 8.1 and all of a sudden it’s pulling in a bunch of other stuff. I mean, just the drift associated with that alone is significant. And not looking at the packages, not really understanding what the packages do or not understanding some of the impact of those subs is going to be an issue. And it’s great to say I’ve got my S bomb and yay, but if you’re not actually running it while if you’re not getting an S bomb that actually includes all of these other things, I’m not sure it really matters much.

Speaker 3 - 19:28 It’s not even that. I think what you just mentioned, it’s a very important area to address. I think loads of developers do not understand even how to build a secure image. What’s the best practice in terms of building as minimal image as possible, making sure that it doesn’t run unnecessary updates and just pulls the correct packages that it only needs to run. That’s another area where supply chain is a massive task at hand.

Nathan Case - 20:00 It’s true.

Dinis Cruz - 20:03 And that is an area that I think the new generation or the next generation of bots can make a massive difference. Right, because understanding that context is really hard and I feel that being able to explain the intent, like you just said, imagine Nathan, take that simple case. You want to be able to describe. This is a mission critical system. It has his properties. I expect this, I expect his blast radius. I expect that is something that we can now start to describe, to try to codify that will be crazy difficult. We can describe that behavior. And then we say, by the way, here’s a Kubernetes config file. By the way, here’s a helm chart. Is that helm chart going to break this particular situation? Look, I’ve fed TCP dumps, even git commit. Have you fed a git commit to Jtpt?

Nathan Case - 20:57 No, actually I haven’t ever tried that.

Dinis Cruz - 20:58 Dude, it’s freaking awesome. Look. So we’re now using it to create change requests, right? And then to describe pull requests. So imagine a flow. You know what I found really interesting is as a developer, I actually enjoy reading that because I found that it described nicely what I was better than developer. And sometimes I go, oh, shit, yeah, I missed that one. Actually, I did change that in the code. But also, even when you make a little mistake, it doesn’t matter. You tweak it, right? So it’s still your text, it’s still your pull request, it’s still your commit, but the quality and you can also say, give me a business analysis. Give me a technical analysis. Give me in fact, can you say, give me a security analysis of that? So imagine that world where imagine that for a helm chart.

Dinis Cruz - 21:46 Imagine having a helm chart that describes that.

Nathan Case - 21:49 Now timeout before we tell everybody that’s ever going to watch this video to go out and find yourself an LLM and ask it to look at your git commit and your code. Please make sure you’ve talked to your CISO, looked at your internal governance policies, and made sure that you’re allowed to do this so that information doesn’t accidentally fall into the wrong.

Speaker 3 - 22:07 Property.

Dinis Cruz - 22:08 Have Pet open source project that you can do that solves that problem.

Nathan Case - 22:12 Sorry.

Dinis Cruz - 22:13 No, that was good. Exactly. Yes. Don’t go and face their confidential disclaimer into Chat.

Nathan Case - 22:20 Well, actually, I feel like I need to say this now. Sorry.

Dinis Cruz - 22:23 Well, but to be honest, I think we can already say that these days you really should have private models. Right? Look, Azura has pushed bedrock.

Nathan Case - 22:29 That’s a great thing to say, but man, the private models aren’t nearly as good as the public ones. And it’s always going to be that type of thing.

Dinis Cruz - 22:37 Yeah, well, Azure OpenAI is not that bad. I think it’s treadling really close. Yes. Chat GPT. By the way, have you tried the model one where you can upload an image?

Nathan Case - 22:50 No, I have not yet.

Dinis Cruz - 22:52 Simon Worley was like that’s the game changer. I think it was really a game changer before that. But I agree that’s a game changer. Dude, you can now do an architecture diagram, go to Chatty bikini and says, give me an idea, transcribe this, give me a flowchart, give me this in plan to ML, give me this in thing, right? It is pretty freaking cool, right? It’s a big game changer, right? But I think the point were just talking, which is how do you create a small possible Kubernetes cluster, for example, or a small possible image? I think in the past that was really difficult to do because you couldn’t explain intent. And I think we’re going to be able to start describing intent, right? And in fact, you’ll be able to start describing even an image.

Dinis Cruz - 23:39 Imagine being able to build an image where you say I want this image to be unusable apart from port 80 and apart from Nodes or Python or Go or this binary. And that’s it. That’s all you should have. You should have what is the minimum viable Linux environment that is required? Start deleting everything else, right? In fact, experiment, do chaos on top of it, run it, run your tests and then start deleting stuff that you don’t think could be usable, right? But imagine doing that in a way that we can describe it, right? And imagine that the next generation of an Llam that actually understands the Linux kernel.

Nathan Case - 24:18 Well, yeah, I was going to say, I mean, go so far as to say that I’ve done my Git push and we’ve gone through the whole thing at this point. And instead of the build that we would normally do, it actually goes over to the LLM. The LLM builds out the image that would be appropriate to what you just asked for. And it’s only those things as opposed to everything else and there’s really no interaction whatsoever. I mean, none of this stuff is rocket science as such.

Dinis Cruz - 24:42 The only thing I would say there the caveat, I would add, and I think this is where I think some people I think are flipping. So I don’t think the LLM builds it. I think the LLM analyze creates the pull request.

Nathan Case - 24:56 I was going to say propose a.

Dinis Cruz - 24:57 Modification and then there’s a build pipeline.

Nathan Case - 25:01 That was I would go so far as to the hardening scripts, almost, and I would agree with you where you’re just looking at the hardening scripts.

Dinis Cruz - 25:06 And then the other variable here, I think discussion sometimes is that like, for example, even in this workflow, if you think about it, I’m not saying that you let an LLM loose it does his magic and then come back tomorrow and go, hey, here’s your build. What I’m saying is that the LLM is going to have a conversation of commits, pull requests, changes, et cetera, that is completely logged, is completely justified, that we can then go back and analyze. And Mario, this is where I’m tying up almost all the sessions. This is where when you then look at our situation awareness and instance response, we should be able to go back and I missed this bit. Oh, this should not supposed to be there. And the big paradigm shift for me, let me show you this image, right?

Dinis Cruz - 25:50 Because I did a presentation on what’s it called, on why everything should be a cyber expert. But there’s one picture that I showed in there that for me was the big game changer, which is this. Can you see my screen? So that one why everyone needs to be an AI expert. So I presented this. But the screen I really want to show is this one here. Have you seen this image?

Speaker 3 - 26:21 No.

Dinis Cruz - 26:21 Have you seen this one? Okay. This was the one, ironically, was a visual, but was the one that made me really understand the power of generative is that the square in the middle is the original painting. The rest was created by Gen AI. The same way that, for example, here, you got the Mona Lisa and then you got the expansion, you got Nirvana and you got expansion, you got, for fun, metallica on a cake.

Speaker 3 - 26:54 I think the point is what we’re talking about and what you mentioned is having all of the deployment and all of the builds and all of it in LLM. Because what we discussed, I think, and the main topic today is we don’t have enough context normally to make right decisions.

Nathan Case - 27:14 Well, and roll back to the Metallica image, to Marius’s point here. Roll back to the Metallica image. Yeah. Neither does Marius’s Point. Metallica is not right. That is not a cake. If the LLM gets the wrong idea here, Marius, that’s going to look bad, right?

Dinis Cruz - 27:33 No, it will. But you know what the power of this is that let’s say even this happened, right? Okay, so let’s take the analogy, right? This happens. Somebody builds a cake, right, with the Metallica logo, right? In the past, the cost of creating that in a different scenario will be massive, right? In fact, will be as big, if not more than creating the cake. And that visual, right? The power of the way the generative works is that cake is one of billions that you could have done based on the input that we provide. So when we come around and maybe on an incident we discovered, oh, it’s a cake, it should not be a cake. You can go back and you can now modify the prompt and say, actually it’s like this. Like this. Like this. Like this, right?

Dinis Cruz - 28:21 So that for me is the big paradigm shift. The big paradigm shift is that what the generative bit does. It means the creation is now cheap or the modification based on the prompt that we can then test and we can validate and we can diff. We can do all that stuff that.

Nathan Case - 28:39 Assumes a human catches it, though. I mean, that’s the issue, right? Like to Marius’s point, and I apologize, marius, I feel like I cut you off there pretty hard. Is that where you were.

Speaker 3 - 28:50 Was. Yeah, exactly. Because the point is, as you say, yes, it’s cheap to experiment, but if you push the cake into production, what’s the outcome? My point is that, yes, we can use LLM, but as long as we said enough context and we used it in the background while we did a number of commits, number of builds and then they build a context. Of what we need from security, what developers need, what’s the business goals, and then we only start slowly saying, oh, it has enough data, it has enough context to know where it should be driving towards. Because if you just ask to build, say, today, I just plug it in and say, build me a secure image, it’s going to build you a cape.

Dinis Cruz - 29:37 But see, here’s where I would draw the line today. See, I would argue today you don’t want the LLM to create the cape. Right? You don’t want the LLM to create the output that ends up being in production. You want to use the LLM to aid the human, to augment the visibility, to augment the understanding of what’s there. And that’s a very different proposition. And that’s where hallucinations become less of a problem because there’s enough checks and balances in the system. So if I ask an LLM to say, here’s a bit of code and analyze this for me, whoever wrote that or whoever’s in this loop can say that’s right? That’s wrong. Right? And then even if you do analysis on top of it, eventually you’re going to figure out, well, that analysis was wrong. So you can modify it if you’ve.

Speaker 3 - 30:25 Got checks and balances in place. Yes, that’s the point. What we discussed earlier, you said you don’t want the LLM to build, you want the pipeline to build. But if it just goes automatically by the pipeline build into the production, then.

Dinis Cruz - 30:37 Obviously we have yeah, but we shouldn’t allow that. By the way, that’s already happening today anyway. How much commit today happens on your pipelines that nobody really checked properly? Right? If you have dev team shipping 2030 5000 times a day, how many of those commits have been looked at from the security team? Yeah. Even if you have static analysis and dynamic analysis, right. The percentage, even if you have is still that is already happening today.

Nathan Case - 31:04 Right?

Dinis Cruz - 31:04 We’re already shipping to production code. But I’m not saying we should allow the LLMs to do that, even with automation. I’m saying we should be using them is in the steps in the middle to allow us to understand context.

Nathan Case - 31:18 I think as we go there and we push back to the original topic that were supposed to be talking about, which is networking in Kubernetes, if we can look at these things that actually build out the build scripts for us, if you will, that will allow us to build out the cluster that we’re going to get in the end and deploy the application. It would be really great if we could then go ahead and comma. And could you give me a network security mapping or detection system that would allow me to see things that are not supposed?

Dinis Cruz - 31:45 Can you write the rules for me? Can you give me the error rules?

Nathan Case - 31:47 Can you give me the for example, it’s basically Iptables. Why is this a hard thing?

Dinis Cruz - 31:53 Because it’s because until you have an LLM, the cost of engineering was great.

Nathan Case - 31:59 I understand that. What I’m saying is, as you talk to the LLM, this is just IP tables.

Dinis Cruz - 32:05 It is, but the level of complexity is too high. If I go to you and say, can you take your helm charts, your live processes, your execution logs, your IP tables, your flow data or your analysis of it? Can you mash it up and give me a view and inconsistencies you turn around and going, Great. Give me two to $5 million of development and I build it for you. And even what you build might be highly freaking locked in and customized. That. Question with an LLM, you can now look at that problem very differently. You can look at creating abstraction layers at every point and then connecting the dots and connecting the intents.

Dinis Cruz - 32:44 And I think there’s going to be a huge amount of innovation there because we now can ask these questions in ways I think we can now start to ask questions, say, can you start to output data in ways that are easy to understand? Can you start to output intent from your information? Which we’re going to have other vulnerabilities and we’re going to have to deal with it, et cetera, but at least that can be checked. At least we can start to learn to trust or not to trust some of these analysis. And, you know, at that moment in time, the smaller the LLM, the less scope he has, the better it will be. I want an LLM that only understands IP tables. That’s it all he does.

Dinis Cruz - 33:23 I want an LLM that only understands network diagrams, blah, blah, has a very small subset, doesn’t need to write poetry, doesn’t need to know about NIST, doesn’t need to know all that shit. Just needs to have enough context that we can then prove with behavior, with analysis, with battle hardened, and with idea, with evidence eventually that it does that really well.

Nathan Case - 33:47 Totally agree with the thought. Please, go ahead.

Speaker 3 - 33:49 Question nathan, I wanted to pick your brains a bit. So we discussed about correct image builds. Some things like app armor, open policy agent and things like that. How we build secure clusters from the get go. What’s your vision about? People might miss or might not know how to do these things, so instead they say, oh, let’s plug in runtime protection. Something like Sysdig or whatever datadog or any other sort of company that uses runtime protection and just see how they can help secure us. Kubernetes from the other angle, what’s your view between the two thoughts of.

Nathan Case - 34:36 So, a long time ago, in a galaxy far away, I worked at AWS, and we released some really interesting stuff in Lambda. And a company that no longer exists. I believe it got acquired. And a friend over in England actually wrote a script that would strip everything out of the lambda container that you didn’t need. And it would just automatically, like, you would push your script, it would run, it would strip everything out of the lambda container that you didn’t need, and it would remove all of the AWS permissions that it didn’t need to have. And it was cool.

Dinis Cruz - 35:13 That’s cool. Where’s that feature? Where’s that feature? In AWS. I want it.

Nathan Case - 35:20 I don’t know. I stopped working at AWS a while ago. I apologize. But it was one of the coolest things that I’ve seen Dave do in a long time, and it was really legitimately helpful. And I Think What I’d Like To See, to Answer The Question in Sort Of A Roundabout Way, marius Is More This Concept Of and Kind Of Going All The Way Back To in Days Of Yor And Yonder when we used to have to build out a sand and plan out what the backplane was going to do and understand all of the implications for all of the different drive speeds and how the fiber channel was going to interact with all of these things.

Nathan Case - 35:56 I think there’s something to be said for it would be really nice if we could get Kubernetes to just load up and go, hey, you’re using this and you don’t need that, and automatically strip it out. I don’t care who it is. Honestly, it’d be really nice if we could just accept the fact that realistically, we don’t need 90% of the container we just uploaded. And even if I can just run a function that spends a day running it through a significant number of different interactions on the API layer and then gives me a list of, hey, these are the things you actually need, versus These are the things you actually have, it doesn’t strike me like it’s that much of a walk to do it. I think Netflix had something called Goat for a while, didn’t they?

Nathan Case - 36:38 That did a very similar sort of a thing. And it’s one of those things where, from a security geek point of view, it would be really nice to be able to build out my hardening scripts that way, as opposed to having to hand jam the whole thing.

Speaker 3 - 36:50 Dennis, you ready to build a company? We just got an idea.

Dinis Cruz - 36:55 Yeah, I feel it starts to be doable now. Right?

Nathan Case - 37:02 I think we’re on the edge. Yeah, I think we’re right at the precipice of you could do that.

Dinis Cruz - 37:06 So he’s an interesting question. That’s why one of the slides I have on that presentation is that everybody should either be panicked, be very excited or a lot of people are ignoring it. Right. But what I think is interesting in the next couple of years is going to be which industry is going to innovate more? Is it the security industry or, for example, the developer industry? Because, for example, what you describe could be done by a dev tool or by a security tool. We don’t care. We just want one of them to do it. Right.

Nathan Case - 37:31 I disagree. I completely and utterly disagree.

Dinis Cruz - 37:34 What do you mean?

Nathan Case - 37:36 I think security is smoke. I think as a security geek, I kid you not. I think security is just development that we’ve tried to make special and different. And the reality is development.

Dinis Cruz - 37:48 We live on the outskirts of inefficiency of industries.

Nathan Case - 37:51 I really think that we should just embrace the fact that security is development and it should be a development tool, and that’s just good development.

Dinis Cruz - 37:58 I agree with that. No, I’m saying that which side is going to innovate? Are you going to do this from a security angle?

Nathan Case - 38:05 I would hope that we do it.

Dinis Cruz - 38:06 From a development or you do it from a development angle? Where that?

Nathan Case - 38:09 I would hope we do it from a development angle and we grow towards security.

Dinis Cruz - 38:12 I agree.

Speaker 3 - 38:14 Angle. It’s more chances to succeed. Because if we’ll be done from security angle, the marketing will be, oh, we make your Kubernetes 100% secure. We 100% protect from breaches and all DA DA. And it will become a snake oil, and nobody’s going to use it.

Dinis Cruz - 38:30 Yeah, but what we should be doing in security is saying, we make your product faster. Resilient. A read only container is super resilient. Right. Like the ability to diff the containers, the ability to, like I said, measure that delta. The thing about security is that we do have a bit of a different perspective. In fact, when I was a CTO, I argued that my understanding of what was possible is very different. Like the Kubernetes model that I described to you guys. I arrived there from both I was CISO and CTO. I arrived there from two hats. I wanted a small possible container from a security point of view. Small possible development. I want to lock it down easily, and I want the small possible piece from engineering point of view. Right.

Dinis Cruz - 39:14 I had to argue with Kubernetes experts because they said that’s not how Kubernetes supposed to work. Literally. They just didn’t have the mental bandwidth to take a little step back and going, okay, maybe that’s what I was designed. Yes, you master and slave are not in the same box, but maybe that’s not a bad thing. Right. But it was funny. Cool.

Nathan Case - 39:34 That’s why I go back to the discussion about, like, forever ago, when we used to have to think about all those little pieces. You were going to build out a data center and you had to know, where do all those go?

Dinis Cruz - 39:44 Now? It should be disposable right now.

Nathan Case - 39:46 It’s all this big, and the data center is literally yeah, but our Clusters are massive. The intel nuck in my basement.

Dinis Cruz - 39:52 Yeah, but our clusters are massive at the moment.

Nathan Case - 39:54 They are? Yeah.

Dinis Cruz - 39:56 So are they a pets? They should not, but they are. When was last time they got rebuilt? When was last time? Can you go and delete it all?

Nathan Case - 40:06 Let’s see. Last time they got rebuilt from scratch. From scratch? Let me check. Hang on. They’ve been up for one day.

Dinis Cruz - 40:15 Good. What about your production in your company? The production?

Nathan Case - 40:19 That’s a different question. That’s none of my business. I don’t ask those questions right now. It’s all good.

Dinis Cruz - 40:27 Cool. I think it’s a good session. I think any final remarks, comments on this?

Speaker 3 - 40:35 I would say that Kubernetes security is becoming more and more prominent question that needs addressing. And I think what we just discussed in terms of we need more fresh ideas, looking at different angles and stepping away from what is needed. I think sometimes we do security and development through not necessarily of security, but we make it more complicated than it has to be. And it becomes sort of a barrier to entry where we border ourselves and saying, oh, we do this very complicated things that nobody could understand. Therefore we lack innovation and perspective from different angles. I think that’s where we need to.

Nathan Case - 41:16 And we get into diversity there too. Not that we don’t have three white guys talking on this, but at the same point, diversity of thought and diversity in general in doing this type of thing is desperately important. Because if you don’t do that, the only thing you come up with is the exact same idea over and over.

Dinis Cruz - 41:36 And I think there’s a couple of startups we already described on this presentation. Right. I do feel that the Gen AI is the game changer here. It brings capabilities that before were just too complex to do, but not to make the cake to analyze on the way to the output. Cool. Brilliant guys. Thank you. See you around later.