Earlier quoted context omitted.
> 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 ecosyst…
> 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. I was going to reply that you misunderstand how Dagger works: that your pipeline logic typically requires very few dependencies, if any, since it can already hav…
Great :D
I read a lot more of the documentation this morning, in general I really like what I see, but the clustering bit is the key missing point for me at the moment. My current employer produces an Electron desktop application - we need to run 90% of the tests on Linux (most cost-effective), and 5% each on a Windows and macOS machine. I see the Dagger CLI runs on both macOS and Windows, but the architecture as it stands today expects that the Dagger pipeline will run all its workloads on the same VM. If I want to run pipeline tasks on other VMs, I can do it from Dagger, treating the Dagger Engine as the orchestration layer which makes some kind of an IaaS or PaaS call to schedule the workload on a separate macOS or Windows VM, outside the Dagger architecture. But... today I expect that workload scheduling to happen within the CI/CD architecture (it's trivially expressible within GitHub Actions, particularly as GitHub Actions hosts both Windows and macOS runners), and needing to hoist it outside the CI/CD architecture in order to use Dagger is a needless complication.