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

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

Secret Manager: secure storage for sensitive data e.g passwords.

Google Secret Manager

API keys are easy to "leak" or compromise, so best to not only use the restrictions presented to you when you create them but physically protect them as well. Don't code them in plain-text, don't check them into GitHub, etc. Store them in a secure database or use a service like GCP Secret Manager.

I've been looking at Google Secret Manager which sounds promising but I've not been able to find any examples or tutorials that help with the actual practical details of best practice or getting this working. I'm currently reading about Cloud Functions which also sound promising but again, I'm just going deeper and deeper into GCP without feeling like I'm gaining any useful insights.

In this post, I described how to build secure GitHub Actions workflows by pull_request_target event instead of pull_request event. Using pull_request_target, you can prevent malicious codes from being executed in CI. And by managing secrets in secrets management services such as AWS Secrets Manager and Google Secret Manager and access them via OIDC, you can restrict the access to secrets securely. To migrate pull_request to pull_request_target, several modifications are needed. And pull_request_target has a drawback that it's difficult to test changes of workflows, so it's good to introduce pull_request_target to repositories that require strong permissions in CI. For example, a Terraform Monorepo tends to require strong permissions for CI, so it's good to introduce pull_request_target to it.

If you want to make these secrets more secure and get versioning and access logs for them, you may want to switch to Secret Manager later on. They can still be exposed as environment variables to your code. It's a little more setup work, so start with the simple approach at the top.

https://cloud.google.com/secret-manager https://aws.amazon.com/secrets-manager/