auth VS Concourse

This workflow will authenticate with Google Cloud using the Google Cloud auth GitHub Action and use Docker to authenticate and push to the registry. To make this workflow work (or flow?) we need to set up some Google Cloud resources and add in those values for our environment variables. Make sure to add in the value for PROJECT_ID where you have permission to create resources. The value for IMAGE_NAME can be anything — it’ll be created the first time this workflow runs:

The issue of integration with other tools is also quite strange. Of course, this is not directly related to github actions. For example, what needs to be done to use cloud run https://github.com/google-github-actions/auth#setting-up-wor...

While it is commonly associated with AWS, and their AWS IAM service, IAM is not limited to their platform. All cloud providers, such as Google Cloud and Azure DevOps, offer IAM solutions that allow users to access resources and systems. If you are looking for specific AWS IAM best practices, look no further than our AWS IAM Security Best Practices article:\ For the rest of this article, we will look at the generic best practices that have evolved over the last decade around each part of the basic question we started with, "who can access what?":

I found this but I don't quite get how it works. I haven't done all the steps yet but I get how to set it up. I just don't understand how this just magically authenticates future steps since my code still needs a token. Should I use this to authenticate the script? If so, how do I do it and what would I need in my code? If not what should I use instead?

Cloud Identity and Access Management: This service provides fine-grained control over who has access to what resources within an organization's Google Cloud environment. It can be used to quickly revoke access to compromised accounts or limit access to sensitive resources. https://cloud.google.com/iam

I use google-github-actions/auth in the first step in my job to authenticate to GCP. At this point, I have 6 different GitHub secrets to test out the concept. Each branch has two secrets with the format BRANCH_WIP and BRANCH_SA.

There are 2 core parts authentication to GCP and App Engine deployment. Authentication is performed using auth, while a deployment uses deploy-appengine.

You should have a look at using workload identity federation and OIDC tokens. There’s a guide on https://github.com/google-github-actions/auth It means you no longer need to hardcode service account credentials in GitHub secrets anymore.

Yes, there is a deploy-appengine action that automates the whole App Engine deployment process. Indeed, it uses gcloud commands underneath too. Either way, both approaches need an auth action to authenticate to GCP before any task can be performed.

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> Why bother, when Dagger caches everything automatically?

The fear with needing to run `npm ci` (or better, `pnpm install`) before running dagger is on the amount of time required to get this step to run. Sure, in the early days, trying out toy examples, when the only dependencies are from dagger upstream, very little time at all. But what happens when I start pulling more and more dependencies from the Node ecosystem to build the Dagger pipeline? Your documentation includes examples like pulling in `@google-cloud/run` as a dependency: https://docs.dagger.io/620941/github-google-cloud#step-3-cre... and similar for Azure: https://docs.dagger.io/620301/azure-pipelines-container-inst... . The more dependencies brought in - the longer `npm ci` is going to take on GitHub Actions. And it's pretty predictable that, in a complicated pipeline, the list of dependencies is going to get pretty big - at least a dependency per infrastructure provider we use, plus inevitably all the random Node dependencies that work their way into any Node project, like eslint, dotenv, prettier, testing dependencies... I think I have a reasonable fear that `npm ci` just for the Dagger pipeline will hit multiple minutes, and then developers who expect linting and similar short-run jobs to finish within 30 seconds are going to wonder why they're dealing with this overhead.

It's worth noting that one of Concourse's problems was, even with webhooks setup for GitHub to notify Concourse to begin a build, Concourse's design required it to dump the contents of the webhook and query the GitHub API for the same information (whether there were new commits) before starting a pipeline and cloning the repository (see: https://github.com/concourse/concourse/issues/2240 ). And that was for a CI/CD system where, for all YAML's faults, for sure one of its strengths is that it doesn't require running `npm ci`, with all its associated slowness. So please take it on faith that, if even a relatively small source of latency like that was felt in Concourse, for sure the latency from running `npm ci` will be felt, and Dagger's users (DevOps) will be put in an uncomfortable place where they need to defend the choice of Dagger from their users (developers) who go home and build a toy example on AlternateCI which runs what they need much faster.

> I will concede that Dagger’s clustering capabilities are not great yet

Herein my argument. It's not that I'm not convinced that building pipelines in a general-purpose programming language is a better approach compared to YAML, it's that building pipelines is tightly coupled with the infrastructure that runs the pipelines. One aspect of that is scaling up compute to meet the requirements dictated by the pipeline. But another aspect is that `npm ci` should not be run before submitting the pipeline code to Dagger, but after submitting the pipeline code to Dagger. Dagger should be responsible for running `npm ci`, just like Concourse was responsible for doing all the interpolation of the `((var))` syntax (i.e. you didn't need to run some kind of templating before submitting the YAML to Concourse). If Dagger is responsible for running `npm ci` (really, `pnpm install`), then it can maintain its own local pnpm store / pipeline dependency caching, which would be much faster, and overcome any shortcomings in the caching system of GitHub Actions or whatever else is triggering it.

> Imagine you live in a world where no part of the build has to repeat unless the changes actually impacted it. A world in which all builds happened with automatic parallelism. A world in which you could reproduce very reliably any part of the build on your laptop.

That sounds similar to https://concourse-ci.org/

I quite like it, but it never seemed to gain traction outside of Cloud Foundry.

I used Concourse[0] for a while. No real complaints, the visibility is nice but the functionality isn't anything new.

[0] https://concourse-ci.org/

We run https://concourse-ci.org/ on our own hardware at our office. (as a side note, running your own hardware, you realise just how abysmally slow most cloud servers are.)

Concourse: https://concourse-ci.org

We use https://concourse-ci.org/ at the moment and have been reasonably happy with it, however it only has support for linux containers at the moment, no windows containers. (MacOS doesn't have a containers primitive yet unfortunately)