secrets-store-csi-driver-provider-gcp VS k3d

The driver can also sync changes to secrets. The driver currently supports Vault, AWS, Azure, and GCP providers. Secrets Store CSI Driver can also sync provider secrets as Kubernetes secrets; if required, this behavior needs to be explicitly enabled during installation.

GCP SS-CSI driver

That's interesting actually, Google provides their own rpvider for the Secrets Store CSI Driver: https://github.com/GoogleCloudPlatform/secrets-store-csi-driver-provider-gcp

Consider: if you have a tool like terraform managing your infra components including your data layer, you likely want to manage those reaources in a different lifecycle from your application code. Applications may also likely managed using a different toolset (kubectl, helm, scaffold, etc.). In this case, secret Manager acts as the secure configuration bridge between the tools, keeping the secrets out of human hands. As certs and passwords are generated on the infra side, those values can be stored as secrets in SM. Application workloads - backed by service accounts having access to read the secret - can decrypt during launch and use the secret as needed. You can use common patterns in both GKE (via thesecrets store csi driver ) and Cloud Run for consuming secrets in this way.

I prefer https://github.com/GoogleCloudPlatform/secrets-store-csi-driver-provider-gcp

K3D: is a lightweight distribution of Kubernetes designed for resource-constrained environments. It is an excellent option for running Kubernetes on virtual machines or cloud servers.

k3d is a lightweight wrapper that makes running Kubernetes (specifically, the lightweight k3s distribution) in Docker straightforward and efficient. It's designed to provide developers with a quick and easy way to test Kubernetes without the overhead of setting up a full cluster.

If you customer prefers to run the standard docker engine you could use k3d

You don’t need to run Rancher from a Kubernetes cluster, the rancher/rancher image works fine with Docker (it uses k3d, aka « k3s in docker » : https://k3d.io/).

K3d and Skaffold for local development

If you are a developer and want to learn how to deploy applications to a cluster, getting a cluster up an running can be a daunting task in it's own rights. There are many ways to do it: spinning up local virtual machines and configuring from scratch or using tools like minikube, etc. You may not care for the pain of setting up and configuring a cluster, and if that is you, then the quickest way that I have found is using k3d.