Whilst we work on building out native support for Google Cloud you can follow the tutorial below to deploy Platform9 Managed Kubernetes on Google Cloud using BareOS.
The full tutorial is on our docs site.
Deploy 100% Upstream Kubernetes on Google Cloud
One of the great features available with Platform 9 offers seamless integration with AWS and Azure to create and manage Kubernetes clusters. In both cases, setting up a new cluster is as simple as clicking on the Amazon AWS or Microsoft Azure buttons from within your account and following the steps provided.
But, what do you do if you want to create and manage clusters with Google Cloud? In this tutorial, we’re going to walk through steps that you can follow to set up a Platform9 supported Cluster in your Google Cloud account. You don’t need any previous experience with either Platform9 or Google Cloud, and both platforms offer a free tier that allows you to experiment without it impacting your budget.
You can sign up for the PMK (Platform Managed Kubernetes) Free Tier account here.
You can learn more and sign up for the GCP (Google Cloud Platform) Free Tier here.
Setting Up the Infrastructure
We’ll be using the Platform9 CLI and the Google Cloud CLI for most of this example. The Platform9 CLI is only available for installation on Ubuntu 16.04 at this time. If you don’t have access to an Ubuntu installation to run this example, the tutorials listed below walk you through setting up a virtual machine that lets you run this locally on a Windows or macOS system.
- Create a Single Node Cluster on VirtualBox VM on MacOS
- Getting Started with PMKFT on a Windows Machine
The first thing we’ll need for this example is a Google Cloud project. You can create a new one by logging into your Google Cloud account and navigating to the New Project page. I’ll be calling this project Platform9 Demo. The project ID appears below the project name, and we’ll keep the default value for this example. The project ID can be edited at this point if you wish.
While Google completes the setup of our project, we can enable the Compute Engine API. This API allows us to provision Google Compute resources from the CLI. You can enable the API here.
At this point, we can return to the terminal on our Ubuntu machine, and begin installing the tools for the next part of the process.