Quick Steps to Engineer a Bespoke, Multi-Cluster Kubernetes Platform

Delivering Kubernetes on demand sounds simple. But it gets complicated fast. - Most solutions are pretty opinionated, and (for public clouds especially) hard or impossible for users to change. - Managing infrastructure (e.g., VMs) under Kubernetes still needs to be done (and for multi-cluster setups, it needs to be done a lot), which is slow and tends to be failure-prone. - Updating and lifecycle-managing multiple clusters is not a picnic -- on public clouds, okay, but on private clouds? You have 99 problems. What if we told you none of that was necessary? That you could -- in just a few steps: - Build a system to deliver bespoke Kubernetes clusters on demand, fast, with huge flexibility in cluster composition, and with wild freedom to explore use-cases demanding worker/control plane separation, workers that run remote from backplanes, workers that run on IoT hardware? - Make all these K8s clusters painlessly self-updating, self-scaling on private and/or public clouds, and easy to operate - And do all this in an entirely Kubernetes-native, declarative, infra-as-code way that leverages Kubernetes itself to keep multiple clusters healthy, secure, performant, and (as relevant) resource- and cost-optimized? You instantly gain speed, simplified operations, improved security, lower costs, and massive flexibility for new use cases. In this webinar, Daniel Virassamy from Team k0s explains: - What k0s and k0smotron are and how they work - Real life use cases for multi-cluster Kubernetes, and how they map to a k0s/k0smotron architecture on various (or multiple) infrastructures - Components required: k0s, k0smotron operator, k0s Autopilot, k0s CAPI operator - How to make it yours: Incredibly-simple automation recipes for making these moving parts work together -- all of which integrate with tools you're already using