ctop VS kind

This does remind me of ctop as well: https://github.com/bcicen/ctop

It also let's you look at containers, resource usage graphs, their logs and even do some actions through a TUI.

ssh, nnn, micro and ctop is all I need on my dockerhosts

My problem with ctop is, that it seems to show wrong memory usage data: https://github.com/bcicen/ctop/issues/314

When talk about interface and cli... I am a huge fan of ctop

You can use CTOP. It's like a lite portainer on CLI. You can check logs, stats, restart containers.

In the terminal, there are also a few useful projects:

  - for Docker, there is ctop: https://github.com/bcicen/ctop

> I tried portainer, awful UX experience and all good features are inside paid version.

This is interesting to me, because it doesn't quite match my experience - I've been using Portainer for around 3 years at this point and it's been pretty decent.

The worst issues that I've gotten is networking issues in some hybrid configurations with Docker Swarm (e.g. Portainer cannot reach the manager node of the cluster for a bit), or troubles configuring Traefik ingresses when managing Kubernetes (though I think the recent patch notes talked about improving the ingress section, so maybe the experience will get better with non-Nginx ingresses).

Other than that, it's been great for onboarding new people, illustrating the cluster state at a glance, easily operating with stacks and scaling/restarting services as needed, including pulling new images, viewing the logs or even connecting to containers through a web UI if need be. The webhook functionality in particular is really nice - you can just do a curl request against a given URL and that will pull the new container versions for the given image and do a redeploy, which works nicely with a variety of CI solutions.

When I last tried, initializing Nomad clusters with networking encryption was a bit less of a smooth experience (needing to essentially manage your own PKI) and the web UI felt more like a dashboard, instead of something that you could click around in, if you're a proponent of that workflow.

Rancher is probably better than both of those options, though there's a certain overhead in regards to running both that software and a full Kubernetes cluster. If Kubernetes feels like a good fit for a particular project and resources aren't an issue, definitely check it out! You can, of course, also have some success with lightweight clusters, like K3s: https://k3s.io/

I'll definitely agree that Lazydocker is a nice tool, but I wouldn't call it superior, just different (TUI vs GUI), their demo video is nice though: https://youtu.be/NICqQPxwJWw

It actually reminds me of ctop, which you might also want to check out, though it's not something that you'd manage clusters in, merely the individual containers on a node (which won't always be enough, same as Docker Compose isn't): https://github.com/bcicen/ctop

Regardless, for Kubernetes, I'm inclined to say that you'd enjoy k9s a bunch then, it has a similar TUI approach: https://k9scli.io/

However, something like ctop may be easier to use.

To get started, you'll need to install clusteradm and kubectl and start up three Kubernetes clusters. To simplify cluster administration, this article starts up three kind clusters with the following names and purposes:

Kind: is a tool for running local Kubernetes clusters using Docker container "nodes." It was primarily designed for testing Kubernetes itself but can also be used for local development or continuous integration.

Fortunately, just as projects like kind and Minikube enable developers to spin up a local Kubernetes environment in no time, CRC, also known as OpenShift Local and a recursive acronym for "CRC - Runs Containers", offers developers a local OpenShift environment by means of a pre-configured VM similar to how Minikube works under the hood.

I recently purchased a used Lenovo M900 Think Centre (i7 with 32GB RAM) from eBay to expand my mini-homelab, which was just a single Synology DS218+ plugged into my ISP's router (yuck!). Since I've been spending a big chunk of time at work playing around with Kubernetes, I figured that I'd put my skills to the test and run a k3s node on the new server. While I was familiar with k3s before starting this project, I'd never actually run it before, opting for tools like kind (and minikube before that) to run small test clusters for my local development work.

Features compared to https://kind.sigs.k8s.io/

Kind allows you to run a Kubernetes cluster inside Docker. This is incredibly useful for developing Helm charts, Operators, or even just testing out different k8s features in a safe way.

Check out KinD

If you're just messing around, just use kind (https://kind.sigs.k8s.io) or minikube if you want VMs (https://minikube.sigs.k8s.io). Both work on ARM-based platforms.

You can also use k3s; it's hella easy to get started with and it works great.

We'll install APIClarity into a Kubernetes cluster to test our API documentation. We're using a Kind cluster for demonstration purposes. Of course, if you have another Kubernetes cluster up and running elsewhere, all steps also work there.

yes I know there is lens, but it does not allow me to see logs of multiple pods at same time and what is even more important it is not friendly for ephemeral clusters - in my case with help of kind I am recreating whole cluster each time from scratch