enhancements
k3d
enhancements | k3d | |
---|---|---|
58 | 76 | |
3,257 | 5,079 | |
0.7% | 1.0% | |
9.7 | 8.4 | |
6 days ago | 9 days ago | |
Go | Go | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
enhancements
-
IBM to buy HashiCorp in $6.4B deal
> was always told early on that although they supported vault on kubernetes via a helm chart, they did not recommend using it on anything but EC2 instances (because of "security" which never really made sense their reasoning).
The reasoning is basically that there are some security and isolation guarantees you don't get in Kubernetes that you do get on bare metal or (to a somewhat lesser extent) in VMs.
In particular for Kubernetes, Vault wants to run as a non-root user and set the IPC_LOCK capability when it starts to prevent its memory from being swapped to disk. While in Docker you can directly enable this by adding capabilities when you launch the container, Kubernetes has an issue because of the way it handles non-root container users specified in a pod manifest, detailed in a (long-dormant) KEP: https://github.com/kubernetes/enhancements/blob/master/keps/... (tl;dr: Kubernetes runs the container process as root, with the specified capabilities added, but then switches it to the non-root UID, which causes the explicitly-added capabilities to be dropped).
You can work around this by rebuilding the container and setting the capability directly on the binary, but the upstream build of the binary and the one in the container image don't come with that set (because the user should set it at runtime if running the container image directly, and the systemd unit sets it via systemd if running as a systemd service, so there's no need to do that except for working around Kubernetes' ambient-capability issue).
> It always surprised me how these conversations went. "Well we don't really recommend kubernetes so we won't support (feature)."
-
Exploring cgroups v2 and MemoryQoS With EKS and Bottlerocket
0 is not the request we've defined. And that makes sense. Memory QoS has been in alpha since Kubernetes 1.22 (August 2021) and according to the KEP data was still in alpha as of 1.27.
-
Jenkins Agents On Kubernetes
Note: There's actually a Structured Authentication Config established via KEP-3331. It's in v1.28 as a feature flag gated option and removes the limitation of only having one OIDC provider. I may look into doing an article on it, but for now I'll deal with the issue in a manner that should work even with a bit older versions versions of Kubernetes.
-
Isint release cycle becoming a bit crazy with monthly releases and deprecations ?
Kubernetes supports a skew policy of n+2 between API server and kubelet. This means if your CP and DP are both on 1.20, you could upgrade your control plane twice (1.20 -> 1.21 -> 1.22) before you need to upgrade your data plane. And when it comes time to upgrade your data plane you can jump from 1.20 to 1.22 to minimize update churn. In the future, this skew will be opened to n+3 https://github.com/kubernetes/enhancements/tree/master/keps/sig-architecture/3935-oldest-node-newest-control-plane
-
Kubernetes SidecarContainers feature is merged
The KEP (Kubernetes Enhancement Proposal) is linked to in the PR [1]. From the summary:
> Sidecar containers are a new type of containers that start among the Init containers, run through the lifecycle of the Pod and don’t block pod termination. Kubelet makes a best effort to keep them alive and running while other containers are running.
[1] https://github.com/kubernetes/enhancements/tree/master/keps/...
-
What's there in K8s 1.27
This is where the new feature of mutable scheduling directives for jobs comes into play. This feature enables the updating of a job's scheduling directives before it begins. Essentially, it allows custom queue controllers to influence pod placement without needing to directly handle the assignment of pods to nodes themselves. To learn more about this check out the Kubernetes Enhancement Proposal 2926.
-
Dependencies between Services
What your asking is a (vanilla) Kubernetes non-goal, others have mentioned fluxcd and other add ons that provide primitives for dependency aware deployments. The problem space is so large, that it's unreasonable to to address these concerns in Kubernetes itself, instead, make it extensible... Look at this KEP for example: https://github.com/kubernetes/enhancements/issues/753 Sidecar containers have existed, and been named as such since WAY before that KEP's inception, defining what these things should and shouldn't do is largely arbitrary. Aka: your use-case is niche, if you don't like the behavior, use flux or argo, or write something yourself.
- When you learn the Sidecar Container KEP got dropped from the Kubernets release. Again.
-
Kubernetes 1.27 will be out next week! - Learn what's new and what's deprecated - Group volume snapshots - Pod resource updates - kubectl subcommands … And more!
If further interested, I may recommend checking out the KEP. I love how they document the decision making, and all these edge cases :).
-
How can I force assign an IP to my Load Balancer ingress in “status.loadBalancer”?
See https://kubernetes.io/docs/reference/kubectl/conventions/#subresources and https://github.com/kubernetes/enhancements/issues/2590
k3d
-
15 Options To Build A Kubernetes Playground (with Pros and Cons)
K3D: is a lightweight distribution of Kubernetes designed for resource-constrained environments. It is an excellent option for running Kubernetes on virtual machines or cloud servers.
-
Why You Should Use k3d for Local Development. A Developer's Guide
k3d is a lightweight wrapper that makes running Kubernetes (specifically, the lightweight k3s distribution) in Docker straightforward and efficient. It's designed to provide developers with a quick and easy way to test Kubernetes without the overhead of setting up a full cluster.
- Turning my laptop into a one-node k8s-cluster?
- Single node K8S distribution for little production
-
Distributing containers to run locally?
If you customer prefers to run the standard docker engine you could use k3d
-
Unable to launch older version (v2.6.8) of Rancher
You don’t need to run Rancher from a Kubernetes cluster, the rancher/rancher image works fine with Docker (it uses k3d, aka « k3s in docker » : https://k3d.io/).
- Blog: KWOK: Kubernetes WithOut Kubelet
-
Building a RESTful API With Functions
K3d and Skaffold for local development
-
Local Kubernetes Playground Made Easy
If you are a developer and want to learn how to deploy applications to a cluster, getting a cluster up an running can be a daunting task in it's own rights. There are many ways to do it: spinning up local virtual machines and configuring from scratch or using tools like minikube, etc. You may not care for the pain of setting up and configuring a cluster, and if that is you, then the quickest way that I have found is using k3d.
- Despliega un clúster de Kubernetes en segundos con k3sup
What are some alternatives?
kubeconform - A FAST Kubernetes manifests validator, with support for Custom Resources!
kind - Kubernetes IN Docker - local clusters for testing Kubernetes
spark-operator - Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.
lima - Linux virtual machines, with a focus on running containers
kubernetes-json-schema - Schemas for every version of every object in every version of Kubernetes
k0s - k0s - The Zero Friction Kubernetes
klipper-lb - Embedded service load balancer in Klipper
k3sup - bootstrap K3s over SSH in < 60s 🚀
Hey - HTTP load generator, ApacheBench (ab) replacement
k3s - Lightweight Kubernetes
connaisseur - An admission controller that integrates Container Image Signature Verification into a Kubernetes cluster
microk8s - MicroK8s is a small, fast, single-package Kubernetes for datacenters and the edge.