cni VS kubernetes

The CNI is language-agnostic and there are many different plugins available.

Read more about the architecture of CRI-O here. The networking of the pod is set up through CNI, and CRI-O can be used with any CNI plugin.

In generic Kubernetes network policies, there is no action field. The Calico CNI plugin (Kubernetes network plugin that implements the Container Network Interface) provides this functionality, and in particular provides logging even for allowed traffic. And this worked when we tried it in our test clusters and in our own back end.

There is a CNI spec: https://github.com/containernetworking/cni/blob/main/SPEC.md which allows for custom network plugins. Thats how AWS/EKS nodes are able to assign VPC routable IPs to containers running on them.

um, they aren't missing anything (but see below). they are k8s.

so if you want to get the genuine original mainline experience you go to the project's github repo, they have releases, and mention that the detailed changelog has links to the binaries. yeey. (https://github.com/kubernetes/kubernetes/blob/master/CHANGEL... .. the client is the kubectl binary, the server has the control plane components the node binaries have the worker node stuff), you then have the option to set those up according to the documentation (generate TLS certs, specify the IP address range for pods (containers), install dependencies like etcd, and a CNI compatible container network layer provider -- if you have setup overlay networking eg. VXLAN or geneve or something fancy with openvswitch's OVN -- then the reference CNI plugin is probably sufficient)

at the end of this process you'll have the REST API (kube-apiserver) up and running and you can start submitting jobs (that will be persisted into etcd, eventually picked up by the scheduler control loop that calculates what should run where and persists it back to etcd, then a control loop on a particular worker will notice that something new is assigned to it, and it'll do the thing, allocate a pod, call CNI to allocate IP, etc.)

of course if you don't want to do all this by hand you can use a distribution that helps you with setup.

microk8s is a low-memory low-IO k8s distro by Canonical (Ubuntu folks) and they run dqlite (distributed sqlite) instead of etcd (to lower I/O and memory requirements), many people don't like it because it uses snaps

k3s is started by Rancher folks (and mostly still developed by them?),

there's k0s (for bare metal ... I have no idea what that means though), kind (kubernetes in docker), there's also k3d (k3s in docker)

these distributions work by consuming/wrapping the k8s components as go libraries - https://github.com/kubernetes/kubernetes/blob/master/staging...

...

then there's the whole zoo of various k8s plugins/addons/tools for networking (CNI - https://github.com/containernetworking/cni#3rd-party-plugins), storage (CSI - https://kubernetes-csi.github.io/docs/drivers.html), helm for package management, a ton of security-related things that try to spot errors in all this circus ... and so on.

#! /usr/bin/bash # Update apt-get repository and install dependencies apt-get update && apt-get install -y --no-install-recommends dmsetup openssh-client git binutils # Install containerd if it's not present -- prevents breaking docker-ce installations which containerd || apt-get install -y --no-install-recommends containerd # Installing CNI # Current version from https://github.com/containernetworking/cni/releases export CNI_VERSION=v1.0.1 ARCH=$([ "$(uname -m)" = "x86_64" ] && echo amd64 || echo arm64) export ARCH sudo mkdir -p /opt/cni/bin curl -sSL "https://github.com/containernetworking/plugins/releases/download/${CNI_VERSION}/cni-plugins-linux-${ARCH}-${CNI_VERSION}.tgz" | sudo tar -xz -C /opt/cni/bin # Installing Ignite # Get the current version from https://github.com/weaveworks/ignite/releases export VERSION=v0.10.0 GOARCH=$(go env GOARCH 2>/dev/null || echo "amd64") export GOARCH for binary in ignite ignited; do echo "Installing ${binary}..." curl -sfLo ${binary} "https://github.com/weaveworks/ignite/releases/download/${VERSION}/${binary}-${GOARCH}" chmod +x ${binary} sudo mv ${binary} /usr/local/bin done # Check if the installation was successful ignite version

The Container Network Interface (CNI) includes a specification for writing network plugins to configure network interfaces. This allows you to create overlay networks that satisfy Pod-to-Pod communication requirements.

In this lab you will bootstrap three Kubernetes worker nodes. The following components will be installed on each node: runc, container networking plugins, containerd, kubelet, and kube-proxy.

CNI type plugins follow the Container Network Interface spec and are used by the community to create advanced featured plugins. On the other hand, Kubenet utilizes bridge and host-local CNI plugins and has basic features.

In the field of software development, efficiency and agility are always sought after. In the era of cloud-native apps, traditional deployment techniques—which are frequently laborious and prone to errors—are starting to become obstacles. This is when Kubernetes and GitOps come in handy.

Are you looking for a hassle-free way to deploy Moodle™ Learning Management Systems (LMS) on Kubernetes? Look no further! Krestomatio presents the LMS Moodle Operator, an open-source Kubernetes Operator designed to simplify the deployment and management of Moodle instances on Kubernetes clusters. Let's dive into what makes this tool a great choice for Moodle administrators and developers alike.

Securing access to your Kubernetes clusters is crucial as inadequate security measures can lead to unauthorized access and potential data breaches. However, navigating the complexities of Kubernetes access security, especially when setting up strong authentication, authorization, and network policies, can be challenging.

Deploying AI models into production requires tools that can package applications and manage them at scale. Docker simplifies the deployment of AI applications by containerizing them, ensuring that the application runs smoothly in any environment. Kubernetes, an orchestration system for Docker containers, allows for the automated deployment, scaling, and management of containerized applications, essential for AI applications that need to scale across multiple servers or cloud environments.

To learn more, you can start by exploring the official Kubernetes documentation.

With the containerized Node.js/Express API, I could run multiple containers, scaling to handle more traffic. Using a tool called minikube, we can easily spin up a local Kubernetes cluster to horizontally scale Docker containers. It was possible to keep one shared instance of the database, and many APIs were routed with an internal Kubernetes load balancer.

This package is widely used for powerful CLI builds, it is used for example for Kubernetes CLI and GitHub CLI, in addition to offering some cool features such as automatic completion of shell, automatic recognition of flags (the tags) , and you can use -h or -help for example, among other facilities.

We closely monitor Kubernetes and cloud providers' updates by following official changelogsand using RSS feeds, allowing us to anticipate potential issues and adapt our infrastructure proactively.

"You are holding it wrong", huh?

From the homepage https://kubernetes.io/:

"Kubernetes, also known as K8s, is an open-source system for automating deployment, scaling, and management of containerized applications."

Do you see "not recommended for smaller-scale applications" anywhere? Including on the entire home page? Looking for "small", "big" and "large" also yields nothing.