k9s VS skaffold

Pierre: The first tool I recommend is K9s. It's not just a time-saver but a productivity booster. With its intuitive interface, you can speed up all the usual kubectl commands, access logs, edit resources and configurations, and more. It's like having a personal assistant for your cluster management tasks.

The last thing you really need is a common set of tools that you want fingertip access to. I really commonly use LazyGit and K9s in my day job so those are the tools I will show off in this article.

K9s is your best friend (get it? 🐶) when exploring your cluster via the terminal. It shares commonality with Vim for its interaction style using shortcuts and starting commands with: but don’t let that discourage you. K9s keeps a vigilant eye on Kubernetes activities, providing real-time information and intuitive commands for resource interaction.

k9s: brew install k9s

I would like to put in a vote for k9s, which is also on the list at Terminal Trove. [0] It's the most convenient tool I've ever found for Kubernetes management. Based on that experience I'll definitely be checking out Harlequin.

[0] https://k9scli.io/

$ wget https://github.com/derailed/k9s/releases/download/v0.29.1/k9s_Darwin_amd64.tar.gz $ tar -xzf k9s_Darwin_amd64.tar.gz $ sudo mv k9s /usr/local/bin/

All in all, run things, do some kubectl apply -f something.yml every day, install k9s, and try to configure a big one cluster at some point.

(K9s is one of my favorite tools for navigating Kubernetes clusters through the CLI).

K9s is an open-source, terminal-based UI for interacting with your Kubernetes clusters, making navigating, observing, and managing your apps easier. If you use Kubectl but wish it was easier and faster to use, K9s might be just what you're looking for!

k9s

A nice middle ground is using a tool like Google's Skaffold, which provides "Bazel-like" capabilities for composing Docker images and tagging them based on a number of strategies, including file manifests. In my case, I also use build args to explicitly set versions of external dependencies.

While I am in a Typescript environment with this setup at the moment, my personal experience that Skaffold with Docker has a lighter implementation and maintenance overhead than Bazel. (You also get the added benefit of easy deployment and automatic rebuilds.)

I quite liked using Bazel in a small Golang monorepo, but I ran into pain when trying to do things like include third-party pre-compiled binaries in the Docker builds, because of the unusual build rules convention. The advantage of Skaffold is it provides a thin build/tag/deploy/verify layer over Docker and other container types. Might be worth a look!

Kudos to the Google team building it! https://skaffold.dev

To get a similar experience of preevy up, first we’ll need to split the build and deploy using process or alternatively employ tools that orchestrate build-tag-push-update-sync flow like Skaffold/Tilt.

We will be using docker and microk8s from Canonical. For running our software during development, we will be using skaffold which is a great tool developed by Google.

To add more context, if you are developing containers in a local dev environment, the minimum you should have is the Google Cloud SDK and Skaffold. The SDK will allow you to programmatically interact with Googleapis e.g. auth, services, resources. Skaffold will allow you to build and deploy to the cloud similar to working with a local dev environment.

I have used both Skaffold and Devspace. I prefer the latter.

I wonder if it has some overlap with https://skaffold.dev/.

K3d and Skaffold for local development

skaffold.dev - build in k8s - no more asking for the database password. All the plumbing to the backend is just done so it's easier for them to test and demo any branch