bitnami/mlflow
Bitnami container image for MLFlow
100K+
MLflow is an open-source platform designed to manage the end-to-end machine learning lifecycle. It allows you to track experiments, package code into reproducible runs, and share and deploy models.
Overview of MLflow Trademarks: This software listing is packaged by Bitnami. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.
docker run -it --name mlflow bitnami/mlflow:latest
Looking to use MLflow in production? Try VMware Tanzu Application Catalog, the commercial edition of the Bitnami catalog.
Non-root container images add an extra layer of security and are generally recommended for production environments. However, because they run as a non-root user, privileged tasks are typically off-limits. Learn more about non-root containers in our docs.
Starting December 10th 2024, only the latest stable branch of any container will receive updates in the free Bitnami catalog. To access up-to-date releases for all upstream-supported branches, consider upgrading to Bitnami Premium. Previous versions already released will not be deleted. They are still available to pull from DockerHub.
Please check the Bitnami Premium page in our partner Arrow Electronics for more information.
Dockerfile
linksLearn more about the Bitnami tagging policy and the difference between rolling tags and immutable tags in our documentation page.
You can see the equivalence between the different tags by taking a look at the tags-info.yaml
file present in the branch folder, i.e bitnami/ASSET/BRANCH/DISTRO/tags-info.yaml
.
Subscribe to project updates by watching the bitnami/containers GitHub repo.
The recommended way to get the Bitnami Mlflow Docker Image is to pull the prebuilt image from the Docker Hub Registry.
docker pull bitnami/mlflow:latest
To use a specific version, you can pull a versioned tag. You can view the list of available versions in the Docker Hub Registry.
docker pull bitnami/mlflow:[TAG]
If you wish, you can also build the image yourself by cloning the repository, changing to the directory containing the Dockerfile and executing the docker build
command. Remember to replace the APP
, VERSION
and OPERATING-SYSTEM
path placeholders in the example command below with the correct values.
git clone https://github.com/bitnami/containers.git
cd bitnami/APP/VERSION/OPERATING-SYSTEM
docker build -t bitnami/APP:latest .
By default, running this image will drop you into the Python REPL, where you can interactively test and try things out with MLflow in Python.
docker run -it --name mlflow bitnami/mlflow
The default work directory for the MLflow image is /app
. You can mount a folder from your host here that includes your MLflow script, and run it normally using the python
command.
docker run -it --name mlflow -v /path/to/app:/app bitnami/mlflow \
python script.py
If your MLflow app has a requirements.txt
defining your app's dependencies, you can install the dependencies before running your app.
docker run -it --name mlflow -v /path/to/app:/app bitnami/mlflow \
sh -c "pip install -r requirements.txt && python script.py"
Further Reading:
Bitnami provides up-to-date versions of MLflow, including security patches, soon after they are made upstream. We recommend that you follow these steps to upgrade your container.
Step 1: Get the updated image
docker pull bitnami/mlflow:latest
Step 2: Remove the currently running container
docker rm -v mlflow
Step 3: Run the new image
Re-create your container from the new image.
docker run --name mlflow bitnami/mlflow:latest
docker-compose.yaml
file has been removed, as it was solely intended for internal testing purposes.We'd love for you to contribute to this Docker image. You can request new features by creating an issue or submitting a pull request with your contribution.
If you encountered a problem running this container, you can file an issue. For us to provide better support, be sure to fill the issue template.
Copyright © 2025 Broadcom. The term "Broadcom" refers to Broadcom Inc. and/or its subsidiaries.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.