k8s

We all know the benefits of using managed Kubernetes services like GKE, EKS, AKS, etc. Given the complexity of managing the cluster infrastructure and its core components (control plane, auto-scaling, monitoring, networking, storage, etc.), using a managed Kubernetes service is generally the first choice when running workloads in production.

However, in some situations, provisioning and managing the Kubernetes cluster from scratch might be necessary. Specific product features, security & compliance, costs, vendor independency, etc. are some factors that usually justify the decision of running Kubernetes by yourself. Of course, many challenges come with managing a Kubernetes cluster and the discussion around which route - self-managed vs. managed - to take is far from simple. I want to keep this discussion out of the scope of this tutorial since it would require special attention.

Currently, the tool of choice when considering provisioning and managing a Kubernetes cluster is Cluster API. From the docs:

Cluster API is a Kubernetes sub-project focused on providing declarative APIs and tooling to simplify provisioning, upgrading, and operating multiple Kubernetes clusters.

[…] The supporting infrastructure, like virtual machines, networks, load balancers, and VPCs, as well as the Kubernetes cluster configuration are all defined in the same way that application developers operate deploying and managing their workloads. This enables consistent and repeatable cluster deployments across a wide variety of infrastructure environments.