Chalice-PynamoDB-Docker-Starter-Kit VS kind

If you want a starter kit to get running faster with it you might want to check out my Chalice PynamoDB starter kit which uses docker to have a great local development experience which is pretty lacking elsewhere.

Check it out: https://github.com/DevOps-Nirvana/Chalice-PynamoDB-Docker-Starter-Kit

If you want to get started with this framework, I've made a simple Docker and Docker Compose starter-kit I invite you to play with. It is Python, however. Check it out if it helps: https://github.com/DevOps-Nirvana/Chalice-PynamoDB-Docker-Starter-Kit

Here's an example Docker-compose file on an open-source example/best practices repo for using AWS, Chalice, DynamoDB, PynamoDB, and more. I guarantee this will work on your mac, because this works on both of mine. Once I run it, I can jump into my browser and use http://localhost:8001 to review the admin interface for DynamoDB. This works perfectly!

(just authored yesterday) A repository that is a starter-kit for folks to get into authoring REST APIs via AWS Lambda at very low-cost with Python and DynamoDB with my Chalice PynamoDB Docker Starter-Kit. This is something I've been playing with and using at various microservices and startups recently and figured I should open source something.

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