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Comment by ransom1538 | Hacker News Reader

Just running docker-compose on load balanced machines is pretty close to having all k8s features (that would give you an endpoint, scaling, running pods[containers],heartbeats and nodes[vms]). If you run Kubernetes on GCP you will see it's just a wrapper of GCP vms, load balancers, instance groups and disks. EG: GCP k8's autoscaling for the nodes isn't any better than just simple GCP load balancers and instance groups (it literally is the same thing). k8's best feature (only?): specify yaml files to declare the setup. That is great! But, you make edits to this 4 times a year - that is a ton of complexity for those 4 git commits.

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It’s pretty close to get it up and running. It’s not close to operating. You have to roll your own load balancer, health checks, method of updating and managing the underlying nodes, you don’t have operators or guarantees about the control plane, etc...

Spin up a K8S in any major cloud provider and you get all this with a consistent API, which is where the value lies.

You have to do all those things, minus the load balancer, with Kubernetes. It’s only if you don’t run on-premise Kubernetes that really start to se benefits.

Honestly, as an ops guy, I would prefer to get up at 3AM do deal with a failed VM or load balancer, compared to dealing with any kind of failure in a Kubernetes cluster at 10AM.

I can understand wanting to be able to deploy to Kubernetes, it’s extremely flexible and relatively easy. But managing and debugging Kubernetes is still a nightmare, even just monitoring it correctly isn’t exactly easy.

With Kubernetes, you can run multiple apps in the same cluster and let Kubernetes manage the capacity on GCP for you. Nice this you have shared headroom for all your apps versus an app per VM in your setup (I think?).

What is wrong with actually using Google’s hosted Kubernetes that would make you want to run compose yourself in their VMs and setup auto scaling, physical machine upgrades, etc.

You can replicate k8s featureset with plenty of other architectures.

But thats not the point.

k8s is the first infrastructure control plane in existence which is widley supported and standardized.

Can you get a managed docker swarm on aws, gcp, azure, do etc.? no.

How many kubernetes offerings do you know? I know at least 6.

Revolution doesn't need to be flashy and noisy.

Off the top of my head, deployments and sidecars are both missing, which are incredibly useful.

Change docker-compose to load balanced dokku nodes. Gives you the deployments and sidecars.

Dokku is magical. It blows my gob whenever I use it. It’s the best parts of Docker and Heroku together, and I can actually control everything that goes with my app.

I find that Dokku requires me to do too much on the machine itself, well as forcing me into a certain model.

I currently use exoframe with docker-compose files, and it's fantastic.

Haven't seen this one - it looks really good, thanks. I also like they integrated traefik in the solution.

Admiral gives you both with vanilla compose now.

Yeah, another tool, I know.

We edit yaml files everytime we update a service version, which happens multiple times per week? Is there a better way to deal with this?

Integrate it with your CI/CD pipeline. I have a Gitlab pipeline that runs kustomize and pipes the output to kubectl for every deploy to do things like setting secrets, image tags, creating ConfigMaps from config files in the repository, etc.

That's essentially what we already do. My original point was based on the fact that the config changes all the time (as opposed to 4 times a year).

What are you changing all the time in your config?

GKE uses other GCP products, but ”k8's autoscaling for the nodes isn't any better than just simple GCP load balancers and instance groups (it literally is the same thing)” isn't entirely accurate - GKE and K8S have logic that manages node pools that you won't be able to use with just instance groups.

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