ml-tooling/opyrator

Finalize docker export capabilities

lukasmasuch opened this issue · 6 comments

Feature description:

Finalize capabilities to export an opyrator to a Docker image.

The export can be executed via command line:

opyrator export my_opyrator:hello_world --format=docker my-opyrator-image:latest

💡 The Docker export requires that Docker is installed on your machine.

After the successful export, the Docker image can be run as shown below:

docker run -p 8080:8080 my-opyrator-image:latest

Running your Opyrator within this Docker image has the advantage that only a single port is required to be exposed. The separation between UI and API is done via URL paths: http://localhost:8080/api (API); http://localhost:8080/ui (UI). The UI is automatically configured to use the API for all function calls.

Hi. I'm using this Opyrator well, and want to deploy my project in a Docker image. So I tried the command line as you noticed
But I only got a message.
[WIP] This feature is not finalized yet. You can track the progress and vote for the feature here: https://github.com/ml-tooling/opyrator/issues/4 :(
Is it really finalized?

@dleunji the Docker export is not ready yet for release :( But we have prioritized this feature and will update this issue as soon as it is ready for usage.

Hi, I want to collaborate on this issue, can you tell me if the logic for exporting the docker would be acceptable?

  1. pip freeze to a requirements file
  2. create docker file from python
  3. copy the opyrator file and the requirements (from the freeze)
  4. pip install the requirements (on the docker file)
  5. opyrator launch-ui and opyrator-launch-api (2 ports open on the docker 8080 and 8051)
  6. dump the docker image

Hey @amitmtrn, thanks for your thoughts! I think this looks like a good approach and looks like it would be worth trying out :) In the future we could discuss whether it could be better to have an official opyrator image (step 2) instead of using the python base image.

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Any updates on this, please?