Install MLRun on a local Docker registryΒΆ

To use MLRun with your local Docker registry, run the MLRun API service, dashboard, and example Jupyter server, by using the following script.

Note

  • Using Docker is limited to local runtimes.

  • By default, the MLRun API service runs inside the Jupyter server. Set the MLRUN_DBPATH env var in Jupyter to point to an alternative service address.

  • The artifacts and DB are stored under /home/jovyan/data. Use the docker -v option to persist the content on the host (e.g. -v $(SHARED_DIR}:/home/jovyan/data).

  • If Docker is running on Windows with WSL 2, you must create a SHARED_DIR before running these commands. Provide the full path when executing (e.g. mkdir /mnt/c/mlrun-data SHARED_DIR=/mnt/c/mlrun-data).

SHARED_DIR=~/mlrun-data

docker pull mlrun/jupyter:1.0.0
docker pull mlrun/mlrun-ui:1.0.0

docker network create mlrun-network
docker run -it -p 8080:8080 -p 30040:8888 --rm -d --network mlrun-network --name jupyter -v ${SHARED_DIR}:/home/jovyan/data mlrun/jupyter:1.0.0
docker run -it -p 30050:80 --rm -d --network mlrun-network --name mlrun-ui -e MLRUN_API_PROXY_URL=http://jupyter:8080 mlrun/mlrun-ui:1.0.0

When the execution completes:

  • Open Jupyter Lab on port 30040 and run the code in the mlrun_basics.ipynb notebook.

  • Use the MLRun dashboard on port 30050.

Installing MLRun on a Kubernetes Cluster Setting a remote environment