Thanks for info, Ben.
To give more background on what I'm trying to accomplish, I'd like to have the on-prem computers perform initial processing of data which exist on their respective local storage devices (same code, different data), and then upload their respective results to a common cloud storage. The cloud VMs would then take over processing of the combined dataset. I'm definitely interested in unifying the command and control of all of these assets from end to end (local to cloud) as much as possible, but can see there are limitations.
I guess if I go the "deployment per on-prem computer" route, I would have the cloud VMs treat the common data bucket as a source asset. I would then either observe that location for changes and/or have the on-prem instances send GQL mutations to the cloud instance to create materialization records and/or instigate downstream runs to process that data?
Am I understanding correctly that I cannot create in a single deployment multiple unique Code Locations (and agents) per on-prem computer with "feigned unique" job definitions (i.e. they are actually the same logical code, but appear as differently named entities to Dagster) so that the deployment instance will route those "unique" jobs to execute only through the only code location (on-prem computer) that has them? In other words define JobA in CodeLocationA which is running on ComputerA, etc.
As another alternative, would it make any sense to have local dagster (open source) deployment instances running on each local computer, and they simply use GQL to communicate with the cloud deployment? Potentially the cloud instance can run jobs (one per on-prem computer) which simply send run requests to the on-prem instances and poll for status (mapping on-prem events to cloud). I understand that this may not benefit for the integrated/automated CICD of the cloud deployment, but that may be an acceptable tradeoff.
Is Alex's answer to another post by Zach about "_Is it possible to construct a DagsterInstance which points to a Dagster Cloud deployment from outside of a user code deployment_" relevant to constructing a solution for my use case?:
https://dagster.slack.com/archives/C02LJ7G0LAZ/p1685721897394309?thread_ts=1685663863.672669&cid=C02LJ7G0LAZ