berglas VS kubectx

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/

kubectx: brew install kubectx

default is where any actions which require a namespace will go into if one is not explicitly defined in a default setup (tools such as kubens can alter this behavior). In the context of Jenkins, namespaces are a useful way to allow isolation of individual Jenkins instances that want to utilize the same Kubernetes cluster. Creation of a namespace is a simple option to kubectl:

Here you go: https://github.com/ahmetb/kubectx and https://kubecm.cloud/

check out kubectx/kubens https://github.com/ahmetb/kubectx very handy tool to permanently switch context/namespace

kubectx + kubens v0.9.4

For a peek at what's currently possible, visit the documentation site, in particular the Usage section. For this initial release, it has feature parity with kubectx and kubens and that's about it, but there's lots of room for growth.

I also encourage you to install kubectx + kubens to navigate Kubernetes easily.