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What job interviews taught me about Kubernetes

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Re: What job interviews taught me about Kubernetes

#81

Post by bellowsgulch »

josevalerio wrote: post #65
mikeocool wrote: post #14

I made this decision at a startup (albeit when the eng team was ~30 people, and we had a monolith with ~10 supporting services). I wouldn’t do it again, even for the reasons stated in the article. The uniformity is nice, we were moving from apps running directly ec2 instances provisioned with ansible. Each time we spun up a new service it was a process to get the ec2 instances provisioned just so. But k8s is such a p…

Dear friend, you have built a Kubernetes https://www.macchaffee.com/blog/2024/you-have-built-a-kubern...

It's a shit blog article. A shell script is what 99% of businesses need.

Re: What job interviews taught me about Kubernetes

#82

Post by johnsmith1840 »

iamcreasy wrote: post #11
xlii wrote: post #10

One year ago I might agree that Kubernetes is an overkill but today? Ask your favorite GPT to generate manifests, get primary app into cluster with telepresence or execute straight from container and switch contexts and clusters like it's 90s again. One reason I dislike Docker Compose and Docker is lack of isolation. Yes sure if you put your arm deep enough you can get it, but on local k8s I can spin cluster per work…

Interesting. I have just started reading about Kubernetes. Is there an reading material that goes over this process you just described?

Don't. Get a chatgpt subscription and spin up a minikube cluster and launch some stuff and play around.

K8s is incredibly deep and complex but with AI it's finally easy to just hello world it.

Re: What job interviews taught me about Kubernetes

#83

Post by bigstrat2003 »

hadlock wrote: post #23
xlii wrote: post #10

One year ago I might agree that Kubernetes is an overkill but today? Ask your favorite GPT to generate manifests, get primary app into cluster with telepresence or execute straight from container and switch contexts and clusters like it's 90s again. One reason I dislike Docker Compose and Docker is lack of isolation. Yes sure if you put your arm deep enough you can get it, but on local k8s I can spin cluster per work…

Strong agree, if there's one thing LLMs are excellent at, it's writing Terraform and Kubernetes deployments (and/or helm charts). What used to be half a day of research, trial and error, is now 20 seconds of AI churn and 98% of the time it nails it on the first try. And then point it at grafana and tell it to write you a dashboard for the new service/s. Easy peasy lemon squeezy. What used to require a team of 4 devop…

LLMs are pretty bad at writing those things in my experience. They will invent HCL syntax that doesn't exist, generate absurdly overwrought Helm charts, put in assumptions that don't make any sense, and so on. It's faster, and better quality, to write the stuff myself.

Re: What job interviews taught me about Kubernetes

#84

Post by bigstrat2003 »

johnsmith1840 wrote: post #82
iamcreasy wrote: post #11

Earlier quoted context omitted.

Interesting. I have just started reading about Kubernetes. Is there an reading material that goes over this process you just described?

Don't. Get a chatgpt subscription and spin up a minikube cluster and launch some stuff and play around. K8s is incredibly deep and complex but with AI it's finally easy to just hello world it.

This is absolutely terrible advice. You should never ever use LLMs to work on something you don't understand already, because you have no way to catch the machine when it screws up (and it will screw up). Just like with every other form of automation before LLMs, a smart person only automates things he already knows how to do himself.

Re: What job interviews taught me about Kubernetes

#86

Post by johnsmith1840 »

AI, managed control plane, minikube

That makes it a no brainer for me for basically any sized project.

Small project? -> minikube single node deploy it.

Tiny project? -> minimum a docker container

I cringe watching anyone build and run code on a raw machine even locally without atleast a container. The endless hours of headaches you avoid is obvious k8s is just the natural extension from this.

Re: What job interviews taught me about Kubernetes

#87

Post by zzyzxd »

packetlost wrote: post #68
zzyzxd wrote: post #49

Earlier quoted context omitted.

> One thing that I think people new to it don’t realize is that it’s not at all batteries included - to get a basic managed cluster setup, you’re still going to be installing a bunch of additional controllers (ingress, cert-manager, external dns to start). And if you can do this again, what's your solution to reverse proxy, certificate management, DNS...etc? I guess you can docker-compose some custom stack on a singl…

I use NixOS with nginx + acme / caddy, coredns and no docker anywhere. It's extremely homogeneous, easy to scale out (add another flake output, deploy to a new server, update DNS records). You could easily automate some of that with more nix, but I don't bother because that's already only like 50 lines of config. I have a strong preference for renting bare metal and it has served me extremely well.

I totally believe this works for you. But in your case, isn't NixOS just another declarative orchestration system like Kubernetes? Similarly I can just run a standalone nginx, caddy with acme, and a coredns pod in a bare minimum k8s cluster.

Personally, I think the complexity is on the same level.

Re: What job interviews taught me about Kubernetes

#88

Post by johnsmith1840 »

bigstrat2003 wrote: post #84
johnsmith1840 wrote: post #82

Earlier quoted context omitted.

Don't. Get a chatgpt subscription and spin up a minikube cluster and launch some stuff and play around. K8s is incredibly deep and complex but with AI it's finally easy to just hello world it.

This is absolutely terrible advice. You should never ever use LLMs to work on something you don't understand already, because you have no way to catch the machine when it screws up (and it will screw up). Just like with every other form of automation before LLMs, a smart person only automates things he already knows how to do himself.

Yeah no. Getting the first hello world up is more important than anything else.

Until you physically see it running learning is slow.

I learned k8s through many months of study and pain pre AI. Once I actually got it up learning was FAR easier.

This is like using a jupyter notebook to learn python and is always the first thing I point to for someone just starting to learn. Only after should you learn venv, pip install, classes ect.

100% use AI to get started on something you don't understand. I will literally never start to learn about a technical system again without first doing a hello world with AI.

Re: What job interviews taught me about Kubernetes

#90

Post by packetlost »

zzyzxd wrote: post #87
packetlost wrote: post #68

Earlier quoted context omitted.

I use NixOS with nginx + acme / caddy, coredns and no docker anywhere. It's extremely homogeneous, easy to scale out (add another flake output, deploy to a new server, update DNS records). You could easily automate some of that with more nix, but I don't bother because that's already only like 50 lines of config. I have a strong preference for renting bare metal and it has served me extremely well.

I totally believe this works for you. But in your case, isn't NixOS just another declarative orchestration system like Kubernetes? Similarly I can just run a standalone nginx, caddy with acme, and a coredns pod in a bare minimum k8s cluster. Personally, I think the complexity is on the same level.

It really isn't comparable. Sure, nixpkgs is huge, but the surface area for what you need to understand and work with is considerably smaller. They aren't even really in the same domain anyways. I was able to get very comfortable with Nix(OS) in a single weekend, but it took me months to get to a similar level with the K8s ecosystem.
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