Using code envs with container execution¶
Container-based execution is compatible with code environments for:
- Python recipes
- R recipes
- Custom in-memory machine learning models
- Deep learning models
When you “update” a code env from the code env administration page, a corresponding Docker image for the code env. Each time you run a recipe or model using this code env, this Docker image will be used.
In order to make a code env “usable” for container execution, you need to select the container configuration(s) for which the code env Docker image must be available. This is configured in the “Container exec” tab of the code env settings.