Deploying a fixed number.of instances to a fixed number of servers does not imply doing it manually.

And I didn't say that.

We had all of these problems with self developed automatisation.

It still was garbage.

K8s just solves those issues out if the box.

Your own failures do not define a model.

And?

My experience still counts for something and the example with those 700 VMS is something I didn't just saw once.

Having huge sprawling swarms of VMs is, for some teams, a problem to be solved, not a fact of life to be designed around.

Sry I'm not getting your point.

If I understand it right: VMS were not there because people needed VMS they were there because people needed compute.

We moved everything to k8s and we were able to do this because k8s can

The point is to deliver a small set of applications, not to come up with the most horizontally scalable possible deployment fabric.

I ran 1000+ VMs on a self developed orchestration mechanism for many years and it was trivial. This isn't a hard problem to solve, though many of the solutions will end up looking similar to some of the decisions made for K8S. E.g. pre-K8S we ran with an overlay network like K8S, and service discovery, like K8S, and an ingress based on Nginx like many K8S installs. There's certainly a reason why K8S looks the way it does, but K8S also has to be generic where you can often reasonably make other choices when you know your specific workload.

And you don't think k8s made your life much easier?

For me it's now much more about proper platform engineering and giving teams more flexibility again knowing that the k8s platform is significantly more stable than what I have ever seen before.

No, I don't for that setup. Trying to deploy K8S across what was a hybrid deployment across four countries and on prem, colo, managed services, and VMs would've been far.more effort than our custom system was (and the hw complexity was dictated by cost - running on AWS would've bankrupted that company)

Bro bragging about 700 VMs... Cringe.

I'm not bragging.

I'm not a 'bro' and 'cringe' this is not tiktok.

It gives context.

Don't you have anything to add to the discussion?

So you did automatisation easy. Here's one way to avoid the issues you described on bare metal:

- Only get servers with IPMI so you can remote reboot / power cycle them.

- Have said servers netboot so they always run the newest OS image.

- Make sure said OS image has a config that isn't broken so you don't get full inodes and so it cycles logs.

- Have the OS image include journalbeat to ship logs.

- Have your health checks trigger a recovery script that restarts or moves containers using one of a myriad of tools; monitoring isn't exactly a new discipline.

Yes, it means you have to have a build process for OS images. Yes, it means you need to pick a monitoring system. And yes, it means you need to decide a scheduling policy.

I wrote an orchestrator pre-K8S that was fewer LOC than the yaml config for my home test K8S cluster. Writing a custom orchestrator is often not hard, depending on your workload, - writing a generic one is.

K8S provides one opinionated version of what people build manually, and when it's a good fit, it's great. When it isn't, I all to often see people spend more time trying to figure out how to make it work for them than it would've taken them to do it from scratch.

Ansible is your friend. Btw, we're talking about the team that built Capistrano, so they certainly know how to automate deployments.

Nope Ansible is horrible in comparison to k8s.

Alone the Paradigma shift from doing things step by step vs describing what you need and than things happen on it is a game changer.

K8s is probably 100x easier than Ansible.

And Ansible also has it's bigger ecosystem like Ansible tower.

Basically your k8s control plane but in bad

> Alone the Paradigma shift from doing things step by step vs describing what you need and than things happen on it is a game changer.

I've actually used both in conjunction and it was decent: Ansible for managing accounts, directories, installed packages (the stuff you might actually need to run containers and/or an orchestrator), essentially taking care of the "infrastructure" part for on-prem nodes, so that the actual workloads can then be launched as containers.

In that mode of work, there was very little imperative about Ansible, for example:

  - name: Ensure we have a group
    ansible.builtin.group:
      name: somegroup
      gid: 2000
      state: present
  
  - name: Ensure that we have a user that belongs to the group
    ansible.builtin.user:
      name: someuser
      uid: 3000
      shell: /bin/bash
      groups: somegroup
      append: yes
      state: present

This can help you setup some monitoring for the nodes themselves, install updates, mess around with any PKI stuff you need to do and so on, everything that you could achieve either manually or by some Bash scripts running through SSH. Better yet, the people who just want to run the containers won't have to think about any of this, so it ensures separation of concerns as well.

Deploying apps through Ansible directly can work, but most of the container orchestrators might admittedly be better suited for this, if you are okay with containerized workloads. There, they all shine: Docker Swarm, Hashicorp Nomad, Kubernetes (K3s is really great) and so on...

I'm on GKE. The hosts and control plane are managed for me. All I need to do is build/test/security scan images and then promote/deploy the image (via Helm) when it goes out to prod.

Using config management and introducing config drift and management of the underlying operating system is a lot more to think about, and a lot more that can go wrong.

The difference is it's likely possible to have 7 physical servers replace those 700VMs when you have your own hardware without all the overhead.

It is much easier to maintain when you look at those numbers.

Not in my case.

Every VM had 4 cores and 20gig me.

Run on quite big blades

Your case is fine. AMD's 4th-Gen EPYC Genoa processors can do up to 192 cores and 384 threads in a single machine (2 socket) with TBs of RAM.

In most cloud environments a "core" can be just a thread.

Older machines have had 4-CPU socket based chassis with many cores as well. Definitely doable.