mirrord VS kind

So, you've been using mirrord to simplify your development process (if you haven’t, go here!). Naturally, you want the traffic from the app you're debugging to go through the cluster environment, so your app can communicate with its clustery pals. There is a problem though: your latest change adds some new columns to the database, and you don’t want to modify the database in the cluster and affect everyone else working on it. You do have a local instance of the database that you can modify, so your app can use that, but you still want it to talk to all the other components in the cluster. So what now? The new outgoing traffic filter feature is here to solve exactly this type of problem!

I had the pleasure of talking to Eyal @ CTO at Metalbear and the maintainer of Mirrord. I got some crazy insights.

If you want to take mirrord for a spin, check out the quick start guide. We’d love to hear about your experience or just general thoughts - chat us up on our Discord or open an issue or discussion on GitHub.

We're building an open-source tool called mirrord which lets you run a local process in the context of a pod in your cloud environment. We often get asked how mirrord is different from Telepresence and so we decided to write a short blog post about it, which we hope would be valuable to those interested in local Kubernetes development:

Hands-on tutorial of mirrord.dev with the creators and Rawkode!

if you are interested in k8s, iptables, hooking libc, asm etc https://github.com/metalbear-co/mirrord

I gave my first CNCF talk in Toronto yesterday, talking about https://github.com/metalbear-co/mirrord , how all the features work, and how it's engineered!

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