berglas VS checkout

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/

checkout

To checkout the merged commit with actions/checkout on pull_request_target event, you need to get the pull request by GitHub API and set the merge commit hash to actions/checkout input ref.

If you re-run GHA after master changes, CI is testing over different code.

You can [disable](https://github.com/actions/checkout#checkout-pull-request-head-commit-instead-of-merge-commit) on the checkout action:

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There was an outage yesterday too when the GitHub action “checkout@v3” broke when they released “checkout@v4”

Yes, they broke the ability for GitHub CI to checkout repos…

https://github.com/actions/checkout/issues/1448

The first two steps are setting up the job's environment. The checkout action will checkout out the repository at the triggering ref. The setup-python action will setup the desired Python runtime. My package supports Python 3.9+ so I'm targeting the minimum version for my build environments.

These first few steps demonstrate how you can run commands like npm install or import other workflows such as how it uses the actions/checkout to copy the contents of the repository into a working directory on the runner host. Read Reusable workflows for more about the syntax for referencing them.

Check out the repo: We will use the actions/checkout action to checkout the repository.

Take a look at the checkout action usage here https://github.com/actions/checkout

Then, we have two important initial steps to define. The first one is an official GitHub Action used to check-out a repository so a workflow can access it. The second one it's pretty more complex but, briefly, downloads and set up a requested version of Java.