Hello everyone ! Would you know if it's possible to run a gRPC server by not using a given .py file but, like for the cmd

dagster dev

being able to use the

workspace.yaml

? So having a commanding like that:

dagster api grpc --workspace myproject/workspace.yaml

My need would be to use the same process with

dagster dev

&

dagster api grpc

(but perhaps I misunderstood something in this page) Thanks !

Hey Justin - this isn't currently possible because a gRPC server maps to one code location / Python environment, and a workspace.yaml can contain multiple code locations. It should be possible to map each line in the workspace.yaml to a single

dagster api grpc

call though. I don't totally understand your use case, can you elaborate?

Thank you for your answer Daniel ! So I could do sthg like

dagster api grpc --python-file docker/file1.py, docker/file2.py, docker/file3.py

My use case is to use always the same source of truth, and so to have everything in

workspace.yaml

so if I want to do the same in my gRPC server I don't "forget" anything as I would have been running this file, and not added manually in my query all files it should run

If you're running your own grpc server I would expect your workspace.yaml to look something more like this: https://docs.dagster.io/concepts/code-locations/workspace-files#initializing-the-server

load_from:
  - grpc_server:
      host: localhost
      port: 4266
      location_name: "my_grpc_server"

Oh ok I understand better what you meant ! In fact my

workspace.yaml

is more like this for now:

load_from:
  - python_file: testPipeline/assets.py

If that's the case i'm curious why you want to run your own grpc server - with a workspace.yaml like that, dagit will do it for you

I already have a dagit running and want to have the possibility to add new pipelines running in different dockers (because of python versions and to avoid dependencies), but it's not impossible that I misunderstood something haha

you can point dagit at a grpc server that you're running separately, but if you do, the entry in workspace.yaml would need to say

grpc_server

not

python_file

Just so you know what we did is the k8s deployement (I know just this)

(or it won't know how to find the grpc server that you're runnign separately)

Oooooh !

@daniel Hello ! We are trying to deploy dagster (dagit + grpc server) using your provided Helm Charts, and as we have multiple dagit deployments to manage, we wanted to use the

user-deployments

option (is there any other way?) That’s why we need to understand how to run grpc server. The project’s structure is quite common I think :

.
├── README.md
├── batchAPIs.py
├── batchPipeline
│   ├── Dockerfile.prod
│   ├── README.md
│   ├── batchPipeline
│   │   ├── __init__.py
│   │   ├── __pycache__
│   │   ├── assets.py
│   │   ├── resources.py
│   │   ├── run_pipeline.py
│   │   └── testDynamicAssets.py
│   ├── batchPipeline_tests
│   │   ├── __init__.py
│   │   └── test_assets.py
│   ├── pyproject.toml
│   ├── schedules
│   │   └── schedules.db
│   ├── setup.cfg
│   ├── setup.py
│   └── workspace.yaml
├── ...
└── requirements.txt

And to launch a user deployment using your helm, as I understood, we need to launch

dagster grpc api <parameters>

do you have an idea on the parameters I need to specify to launch the server ?

Max can you make a new post for this question? Our support oncall will be able to help you out

Ok thank you very much ! (I thought it was easier to understand regarding if I posted in this thread to have the context)