This is meant to be tested for KubeFlow notebook servers, to allow interTwin use cases to access MLFlow functionalities from KubeFlow.

It appears as:

Create a new notebook server, using the image provided in this repo as custom image:

In JupyterLab, from a notebook:

import mlflow

# HTTP connection requires the server to be running!
# Namely, you executed it by clicking on the extension
# mlflow.set_tracking_uri('http://127.0.0.1:50001')

# This is a "safer" approach, although it is bound to
# the local filesystem
mlflow.set_tracking_uri('mlflow_logs')

mlflow.set_experiment('test-exp')
mlflow.start_run()
mlflow.log_metric('my_metric', 17)
mlflow.end_run()

Now go to the MLFlow server extension to see the logs.

This extension is based on Jupyter Server Proxy. Read the docs for more info.

This can be tested in a virtual environment based on Micromamba (conda).

To manage Conda environments we use micromamba, a light weight version of conda.

It is suggested to refer to the Manual installation guide.

Consider that Micromamba can eat a lot of space when building environments because packages are cached on the local filesystem after being downloaded. To clear cache you can use micromamba clean -a. Micromamba data are kept under the $HOME location. However, in some systems, $HOME has a limited storage space and it would be cleverer to install Micromamba in another location with more storage space. Thus by changing the $MAMBA_ROOT_PREFIX variable. See a complete installation example for Linux below, where the default $MAMBA_ROOT_PREFIX is overridden:

cd $HOME

# Download micromamba (This command is for Linux Intel (x86_64) systems. Find the right one for your system!)
curl -Ls https://micro.mamba.pm/api/micromamba/linux-64/latest | tar -xvj bin/micromamba

# Install micromamba in a custom directory
MAMBA_ROOT_PREFIX='my-mamba-root'
./bin/micromamba shell init $MAMBA_ROOT_PREFIX

# To invoke micromamba from Makefile, you need to add explicitly to $PATH
echo 'PATH="$(dirname $MAMBA_EXE):$PATH"' >> ~/.bashrc

Reference: Micromamba installation guide.

Create the virtual environment through the Makefile:

make

micromamba run -p ./.venv jupyter-lab