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[3232.92 --> 3238.12] if you look at it from a certain perspective. So things are fairly well defined. Like, |
[3238.12 --> 3242.68] you know what you need to reach out for and how to combine things. And there's like a whole community |
[3242.68 --> 3247.48] around it. There's like so many projects which are solving specific issues. The interface is very |
[3247.48 --> 3253.00] clear. You know how to interact with it. There's an API. It's this single API by which you request |
[3253.00 --> 3258.28] anything, including other VMs, other load balancers. Do you want a SQLite instance with |
[3258.28 --> 3262.76] such and such provider? You can get that. Okay. You have to extend Kubernetes in order to benefit |
[3262.76 --> 3268.76] from these features, but it's possible. And there's only one way that you can do this. And that's very |
[3268.76 --> 3276.84] powerful. I think the separation of concerns, it gets a bit more clear. So anybody just ship us a |
[3276.84 --> 3282.52] container image. It doesn't matter what language you have. It doesn't matter what VM you're running. |
[3282.52 --> 3287.96] Ship us a container image will take care of the rest. Okay. Now I know it's too simplistic, |
[3288.92 --> 3294.84] but it works. Like Heroku, for example, shipping containers, they made it popular. You just get push |
[3294.84 --> 3300.44] and things happen. And guess what? The way the changelog is being developed hasn't changed. You get push |
[3300.44 --> 3306.12] and things happen behind the scenes. And because that contract has never been broken with the |
[3306.12 --> 3313.80] developers, everybody's happy. Yeah. Gerald would be pissed if he had to, as his agent to the servers, |
[3313.80 --> 3318.36] to set things up. There you go. Yeah. That's no good. Yeah. Do you really care about like which OS |
[3318.36 --> 3323.48] you're running? No, you don't. Do you want to switch Erlang versions? Super easy. Guess what? All you have to do is |
[3323.48 --> 3329.24] change the container. Hot code reloading? Yes, you can do it. It's hard. Maybe you don't need to. |
[3329.24 --> 3335.24] And again, it doesn't matter whether you use Erlang or Elixir or Ruby or Python or Go. It really doesn't |
[3335.24 --> 3340.68] matter. Do you want to use serverless? Well, guess what? You have all these projects which you can set |
[3340.68 --> 3347.08] up and you can run it on in the same context. And the list goes on and on. I mean, it's really, |
[3347.08 --> 3354.68] it just goes forever. And it's not like I have used Chef for many years. I was G Chef at one point, |
[3354.68 --> 3360.12] Gerhard Chef. That's like even in Oregon, GitHub. So I spent like a fair time with that knife when that |
[3360.12 --> 3365.12] was a thing. I don't think many people were using, because Chef server was so difficult. I was there. |
[3365.24 --> 3372.40] I remember that period. Ansible, I loved it when it was a thing. Certain things were difficult with it, |
[3372.40 --> 3381.38] but it was saner than Chef. Is Kubernetes saner than Ansible? I don't know. For us, |
[3381.58 --> 3386.14] it felt like the next evolution. You're right. There is a learning curve. Like Vim, there will be, |
[3386.24 --> 3393.76] or Emacs. Kubernetes is definitely a big step in some direction from Ansible. It's not just the next |
[3393.76 --> 3399.12] sort of iteration on scripting your servers. That's not what it is. It's something different. |
[3399.12 --> 3404.58] And you did ask me for a sort of hot take that you could put as the title on this. And I think, |
[3404.92 --> 3410.16] like, would it be fair to say Kubernetes is the electron of operations? |
[3410.54 --> 3415.92] It's the electron. Oh, okay. Wow. I think people are like, what is electron? That would be the |
[3415.92 --> 3417.00] first thing I would ask. What? |
[3417.52 --> 3423.28] What is electron? Which electron do you mean? Do you mean the physical one or the electron JavaScript? |
[3423.28 --> 3432.32] Oh, you're like, ooh, physics. No, I mean, yeah. I mean, in that it makes operations at the outset, |
[3432.76 --> 3442.68] a lot simpler, but it also paves over everything that you could get right in the details. I feel like, |
[3443.08 --> 3449.34] I think you have access to every little detail you would need in Kubernetes, but it doesn't |
[3449.34 --> 3456.08] particularly seem to encourage you getting into all the details. So whenever you add abstraction |
[3456.08 --> 3464.90] layers, and I think that's sort of my, my hesitance on adding more tools, especially tools that sit on |
[3464.90 --> 3475.02] top and sort of obscure what's going on is that I've come to rely on explicit things, because if you can |
[3475.02 --> 3481.18] just read the code and see what it's going to do, that's, that's very powerful. I mean, it's not |
[3481.18 --> 3488.52] declarative. People like declarative for particular things and declarative can be nice, but it also |
[3488.52 --> 3497.90] doesn't make it clear like A to B to C what is going on, what's being done. And for most server installs, |
[3497.90 --> 3500.08] they don't have to be very complicated. Yeah. |
[3500.08 --> 3505.42] And if it doesn't have to be very complicated and there's not a lot of complexity to manage, |
[3505.72 --> 3510.70] if you bring in a larger abstraction layer, which is supposed to hide a lot of complexity and |
[3510.70 --> 3518.42] make managing very complex things possible, which I think is, is a fair, fair thing to say about |
[3518.42 --> 3524.32] Kubernetes. It seems to make it possible to manage very, very complex things. If you bring that into a |
[3524.32 --> 3529.08] fairly, already fairly simple thing, I think you're shooting yourself in the foot. |
[3529.08 --> 3536.22] But, but it's, it also depends on what tools are you comfortable with? Like you've spent years and |
[3536.22 --> 3539.60] years deeply immersed in, in ops and like. |
[3539.60 --> 3541.82] Tried decades, but yes, I agree. |
[3543.42 --> 3543.94] Yeah. |
[3544.46 --> 3551.84] I've spent much more time building the actual applications. I spent a fair bit of time on servers |
[3551.84 --> 3559.68] and operations, but not nearly the majority of my time because I care much more about, |
[3559.98 --> 3567.26] about the building of the thing. And I consider the operations and a part of what I do. I don't |
[3567.26 --> 3573.16] want to hand off a container particularly to, to operations and just guess how it's going to be run. |
[3573.16 --> 3594.58] I see there's a lot of, I don't want to call it full stack, maybe end to end stack. Like I want to care about the whole and I have no idea what's going on in half of the whole. If I, if I bring in a cool like tool like Kubernetes, I definitely would use it for, and I would learn it. |
[3594.58 --> 3616.22] If I saw that I definitely had the need, if I was going to run hundreds and hundreds of instances or, or scale across continents. Yeah. It probably makes sense to bring in something that lets me take that, that overview, that like 10,000 miles view of the world. |
[3616.22 --> 3630.54] And then like, Oh yeah, we have decent performance in Asia. Oh, we're dropping performance in Antarctica. Like, but that's typically not where I operate. And it's typically not what I go for first. |
[3630.54 --> 3659.98] And on that thought, thank you, Lars, very much for joining me. This was a pleasure. I do realize that we have so much more to talk about. Dev and Ops talking finally. I think for decades, we tried to do that and it's finally happening. We have respect for each other. We know that each context is... |
[3659.98 --> 3686.64] You run this, figure out what to do with it. I think it's nicer when we agree on what the abstractions should be. Everybody benefits. And when things go wrong, because they will go wrong, people know what to do. And it's not a reactive approach. It's like a planned, you know, we kind of know what... |
[3686.98 --> 3688.86] Happy to come back. Thanks for having me. |
[3689.98 --> 3719.96] Happy to come back. |
[3720.32 --> 3725.12] Come hang with us on Slack. They're knowing posters. Everyone is welcome. |
[3725.72 --> 3730.00] Huge thanks again to our partners. Fastly, LaunchDarkly and Minout. |
[3730.34 --> 3735.04] Also, thanks to Breakmaster Cylinder for making all our awesome beats. |
[3735.50 --> 3737.76] That's it for this week. See you next week. |
[3737.76 --> 3767.74] Thank you. |
[3767.76 --> 3797.74] Thank you. |
• Introduction to a CI/CD LEGO set used by Changelog.com for production |
• New pipeline improves coding-to-prod time to at least twice as fast as before |
• Use of Dagger and CUE language in the pipeline |
• Discussion of the team's experience working on the project, including challenges and learning opportunities |
• Explanation of the new pipeline workflow, including parallel dependency builds and caching mechanisms |
• Plans for improving developer experience with BuildKit and CUE |
• Demonstration of the new pipeline and its features, including actions and parallel dependency builds. |
• BuildKit and Docker build features |
• Steps as container-based actions with inputs and outputs |
• Pipeline running in parallel with caching and speed improvements |
• Dagger integration with GitHub Actions and local machines |
• Open tracing feature for visualizing pipeline performance |
• Fine-grained step relationships enabling parallel execution |
• CI setup and environment variables configuration |
• Secrets management using SOPS encryption |
• Discussion of a pipeline's configuration and how it interacts with Docker and CUE (Configure, Unify, Execute) |
• Explanation of CUE as a configuration language that aims to be better than JSON and YAML |
• Benefits of using CUE for schema definition, data validation, and type-checking |
• Example use case: deploying serverless functions on AWS using CUE |
• Mention of future improvements with Europa, including improved DX (Developer Experience) and potential removal of hoops to jump through in the pipeline configuration |
• Discussion of the value of profiling Kubernetes workloads |
• Explanation of sampling profiling and its benefits over traditional profiling methods |
• Introduction to Parka, a tool for recording and analyzing CPU profiles |
• Demo of Parka's functionality, including visualizing CPU samples and Flame Graphs |
• Discussion of how Parka can be used to optimize code and reduce CPU usage |
• Discussion of performance spikes in Parka's profiling data |
• Symbolization and ingestion of profiling data as potential causes for performance issues |
• Optimizations to reduce performance impact, including buffer reuse and storage optimizations |
• Displaying Flame Graphs in Parka, with the ability to view different profiles and machine-compiled binaries |
• Explaining memory addresses in Flame Graphs due to stripped debug information in Postgres binary |
• Introduction of Debuginfod project for on-demand debug symbol retrieval |
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