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k3d-io
k3d
Go2019–2025
k3d-io / k3d

k3d

Little helper to run CNCF's k3s in Docker

8Distinct people
8Mentions
0Explicit recommenders
6.6KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Little helper to run CNCF's k3s in Docker

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year8 dated mentions

Observed mentions: 2019-11-27 23:28:33 UTC to 2025-12-11 15:55:05 UTC.

0123452019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 5 mentions; 2 submissions, 3 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC523
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101

What Hacker News says

8 sources
Only on mac though, because docker has extra overhead due to running on a vm there. I run kubernetes all the time in my linux desktop and it consume <5% cpu on idle, and that's with more than a dozen pods running in the background (postgres, postgis, mysql, redis, memcached, a bunch of django webapps, some test wordpress instances, multiple sftp instances, and a pihole instance). I got fed up with the performance on mac and tried using https://github.com/rancher/k3d instead, which seems to cut the idle cpu usage by half.
In Kubernetes at Home with K3s
There are a number of resources that may be useful for your curriculum for this project listed in "Is there a program like codeacademy but for learning sysadmin?" https://news.ycombinator.com/item?id=19469266 : > [ http://www.opsschool.org/ , https://github.com/kahun/awesome-sysadmin/blob/master/README... , https://github.com/stack72/ops-books , https://landing.google.com/sre/books/ , https://response.pagerduty.com/ (Incident Response training)] To that I'd add that K3D (based on K3S, which is now a CNCF project) runs Kubernetes (k8s) in Docker containers. https://github.com/rancher/k3d For zero-downtime (HA: High availability) deployments, "Zero-Downtime Deployments To a Docker Swarm Cluster" describes Rolling Updates and Blue-Green Deployments; with illustrations: https://github.com/vfarcic/vfarcic.github.io/blob/master/doc... For git
Read the rest
-push style deployment with more of a least privileges approach (which also has more moving parts) you could take a look at: https://github.com/dokku/dokku-scheduler-kubernetes#function... And also reference ansible molecule and testinfra for writing sysadmin tests and the molecule vagrant driver for testing docker configurations. https://www.jeffgeerling.com/blog/2018/testing-your-ansible-... https://molecule.readthedocs.io/en/latest/ https://testinfra.readthedocs.io/en/latest/ : > With Testinfra you can write unit tests in Python to test actual state of your servers configured by management tools like Salt, Ansible, Puppet, Chef and so on. > Testinfra aims to be a Serverspec equivalent in python and is written as a plugin to the powerful Pytest test engine. I wasn't able to find a syllabus or a list of all of the daily posts? Are you focusing on DevOps and/or DevSecOps skills? EDIT: The lessons are Markdown files in a Git repo: https://github.com/snori74/linuxupskillchallenge Links to each lesson, the title and/or subjects of the lesson, and the associated reddit posts might be useful in a Table of Contents in the README.md.
In Show HN: Linux sysadmin course, eight years on
There are a lot of projects these days that aim to use Kubernetes as a docker-compose environment. I personally use http://skaffold.dev/ with either a local Kubernetes cluster built with https://github.com/rancher/k3d or https://github.com/kubernetes-sigs/kind. I think there's a very easy argument to be made that says that running K8s locally is overkill, but what I will say is that if you run your applications locally in K8s, that's one step closer to having your local environment mirror the production environment. Couple that with things like running https://github.com/localstack/localstack locally and you get even closer.
In Do I Need Kubernetes?
Disclaimer: k3s creator Kind is intended to be a development tool to run fully upstream clusters using kubeadm in Docker containers. k3s is a custom distro that is oriented towards lightweight environments. The scope of k3s and kind are different (distro vs tool to run k8s in docker). There is another project called k3d (https://github.com/rancher/k3d) that more directly compares to kind. k3d will run k3s clusters in Docker. k3d creates clusters significantly faster and uses less mem/cpu resources than kind.
In Everything I know about Kubernetes I learned from a cluster of Raspberry Pis

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