kiosk VS kubernetes

Kiosk

Have a look at https://github.com/loft-sh/kiosk and maybe the paid version https://loft.sh/

As for the open source projects, maybe you would find Kiosk for allowing self-service namespace creation, namespace templates and cross-namespace resource limits and quotas.

# Install kiosk with helm v3 ❯ kubectl create namespace kiosk helm install kiosk --repo https://charts.devspace.sh/ kiosk --namespace kiosk --atomic namespace/kiosk created NAME: kiosk ... Learn more about using kiosk here: https://github.com/loft-sh/kiosk#getting-started #verify ❯ kubectl get pod -n kiosk NAME READY STATUS RESTARTS AGE kiosk-66dbfcf6db-5rfx2 1/1 Running 0 2m18s

Kubernetes was designed as a single-tenant platform. Sharing clusters, though, offers greater flexibility, simplifies infrastructure, and improves cost-efficiency. Therefore, it makes sense to use a multi-tenant system. To keep tenants separate and prevent compromised tenants from affecting others, you can use role-based access control (RBAC) or namespaces. Tools that assist with multi-tenancy in Kubernetes include kiosk and loft.

For simple environments I'm using klum, for bigger environments I'm using OIDC with Keycloak. Beside that kiosk also looks interesting.

https://github.com/loft-sh/kiosk (from makers of loft)

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.

Open Source and Cloud Computing: A Match Made in Heaven The cloud is accelerating OSS adoption. Cloud-native technologies like Kubernetes [https://kubernetes.io/] and Istio [https://istio.io/], both open-source projects, are revolutionizing how applications are built and deployed across cloud platforms.