You're not dumb, you're just new to it, and it's fundamentally hard stuff anyways, and if you can find a higher-level abstraction that lets you get work done faster, then all the better. However, the question is comparing Kubernetes to traditional VM-based infrastructure (especially with pet nodes) whereas you're comparing Kubernetes to a higher-level abstraction.

For what it's worth, deploying in Kubernetes is pretty easy once you figure it out (and often finding the information is the hardest part). All you need to do is update the Deployment resource's "image" parameter. You can do that with `kubectl patch` like so:

    kubectl patch deployment foo -p '{"spec":{"containers":[{"name":"main","image":"new-image"}]}}'

Kubernetes will handle bringing up a new replicaset, validating health checks, draining the old replicaset, etc.

I hear you about feeling dumb. I think some early decisions in the k8s ecosystem led to a lot of wasted time and effort, and this frustration.

YAML: significant whitespace is always unwelcome but YAML also introduces unexpected problems, like how it deals with booleans. For example, say you have this array:

    foo:
    - x
    - y
    - z

You might think this is an array of strings, but you'd be wrong.

It's also difficult to read through a YAML config and understand the parent of each key, especially in code reviews or just on GH.

I believe k8s life would have been easier with JSON configs, where it's impossible to confuse e.g. booleans for strings and where it's easier to understand the object's hierarchy.

Helm's use of gotpl: this choice exacerbates the problems with YAML. Now you're treating a structured language with a text template library. You have to spend energy thinking about indentation levels and how the values will be interpreted by both the templater and k8s.

I think helm would be less frustrating if they chose some templating library that made objects first class citizens. Where you can inject values at specific locations with one-liners or simple blocks of code (e.g. `ingress.spec.rules[0].append(yadda yadda)`)

I'm sure there was debate about these choices early on and I don't have any unique ideas here, so I don't want to be too critical. These are just a couple of pain points I've personally experienced.

And you probably didn't even get to TLS and or authenticated communication between containers, CI/CD, canary deployments, observability, monitoring etc.

What we need is a Next.js for Kubernetes. Something that delivers a full stack solution on top of base Kubernetes.

The core system is great, but we need to replace these DevOps with a framework or platform.

Container instances are pretty good really, the app service for containers is pretty good too. I’ve been playing with k8s because that’s what everyone thinks they want and need to be able to speak to it, and use it when the time comes, but I’ve yet to run into a case where I really thought it was necessary, for the platform I work on (millions of users, big number of transactions per second).

Similarly, we switched from self-managed k8s on EC2 to Fargate. Took about 2 months part-time with some consultants to get thing squared away.

Once we deployed, we ran into all sorts of SRE-issues. Turns out AWS sets all those “sane limits” that our own folks never did. Still hunting ghosts from the rollout 6 months ago.

Makes for good resume fodder, and makes me laugh at the prestigious titles and positions the folks who built this system went on to receive at big name firms.

Guess it is someone else’s management problem now. :shrug:

Azure is generally the worst (their new container offering looks better though)

If you try digital ocean k8s offering it's fairly straightforward.

Google cloud was the first to offer a decent k8s as a service, if I recall correctly. We didn't have DevOps back in 2015 and we were on GCloud.

Personally I don't pick k8s just because it's heavy to run and I don't want to waste machines (plain docker is good enough for a large part of what people actually need). Sometimes in a project when I can't figure something out with just docker, I just bite the bullet and install k0s.

I feel you. Took me 2 years of dabbling with k8s every once in a while on the side to finally "get" it. and if I stop looking for a few months, suddenly it already gained another set of features and deprecating some other.

Definitely a pain point I've seen in my past work as well. Even though spinning up a basic cluster has gotten easier with canned services like EKS, deploying and developing on the cluster is a major challenging for most developers without a higher level framework.

My cofounders and I are working on a solution to this at https://www.jetpack.io/. If you're interested in early access, we'd love your feedback!

There are tools that let you convert a running docker/podman container to a kubernetes deployment manifest which you can then deploy with one line command to your cluster. Kubernetes is the new data center and I don’t expect anyone with <10 years of enterprise experience to master it. Certainly one can use it and deploy things to it if you work at a place where there are mature pipelines, but deploying your own cluster and all associated services plus networking plus security is the domain of experienced/senior engineers. How quickly one achieves that “status” is up to the individual. It took me 15 years before I could build an enterprise network from scratch. It took me two years to understand how to do the same with K8s.