MLFlow Notebook Integration

docs/.wordlist.txt

@@ -18,6 +18,8 @@ installable
 Jira
 JSON
 Juju
+Jupyter
+JupyterLab
 Kubeflow
 Kubernetes
 lifecycle
@@ -43,5 +45,6 @@ RTD
 subdirectories
 subtree
 UI
+URI
 TensorBoard
 VM

docs/how-to/index.rst

@@ -29,6 +29,7 @@ Integration
 
    integrate-cos
    integrate-ml-ckf-ck8s
+   integrate-notebook
 
 Upgrading
 ---------

docs/how-to/integrate-notebook.rst

@@ -0,0 +1,66 @@
+Integrate MLflow with Jupyter Notebooks
+=======================================
+
+To run Jupyter Notebooks in Charmed MLflow, JupyterLab must be deployed and a number of configurations made.
+
+Prerequisites
+-------------
+
+- You are deploying Jupyter Notebook and MLflow on a workstation running Ubuntu 20.04 (focal) or later.
+- Your workstation has at least 4 cores, 32GB RAM, and 32GB of disk space available.
+- Your workstation is connected to the internet for downloading the required snaps and charms.
+
+Deploy MLflow
+-------------
+
+Follow the steps in this tutorial to deploy MLflow on your VM: :doc:`../tutorial/mlflow`. Confirm that you can now access the MLflow UI on ``http://localhost:31380.``
+
+Deploy JupyterLab
+-----------------
+
+Install JupyterLab:
+
+.. code-block:: bash
+
+   pip install jupyterlab
+
+Run JupyterLab:
+
+.. code-block:: bash
+
+   jupyter lab
+
+Access MLflow UI
+----------------
+
+Access the MLflow UI:
+
+.. code-block:: bash
+
+   mlflow ui
+
+Configure MinIO and MLflow
+--------------------------
+
+Before you can run your first experiment, there are a couple of things to adjust — the MLflow URI and the MinIO URI. To do this:
+
+#. Open a new terminal window connected to the instance you have been using.
+
+#. Enter the following command to check the status:
+
+   .. code-block:: bash
+
+      juju status
+
+#. Now, go back to the Notebook and update the MLflow URL and MinIO URL as needed.
+
+#. Once those are updated, there is one last step you need to do. Return to the terminal and run:
+
+   .. code-block:: bash
+
+      juju run-action mlflow-server/0 get-minio-credentials — wait
+
+   This will display the secret-key and secret-access-key. Be sure to update them in the Notebook as well.
+
+Now, you are ready to run your first experiment. After finalising the run, you can go to the MLflow UI and view the experiment results.
+