--- title: MLflow | MLOps description: MLflow is an open-source platform used for managing machine learning workflows url: https://canonical.com/mlops/mlflow?format=md keywords: Mlflow, what is mlflow, mlops --- # MLflow made easy A seamless start to your machine learning journey with open source Supported with Ubuntu Pro Charmed MLFlow is a lightweight and securely designed machine learning platform for any developer. It can be deployed on your infrastructure of choice, and is backed by expert support. [Read about lightweight ML with MLflow](https://ubuntu.com/engage/lightweight-ml-mlflow) [Contact us](https://canonical.com/mlops/contact-us) --- ## Get the features of upstream MLflow Charmed MLflow, Canonical's distribution of the upstream project, comes with all the upstream features, including: --- * Experiment tracking Record and query experiments: code, data, config, and results. * Reproducible projects Package data science code in a format that enables reproducible runs on any platform. * Model registry Store, annotate, and manage models in a centralized repository. * Models deployment Deploy machine learning models in diverse serving environments. [Learn more about MLflow ›](https://ubuntu.com/blog/what-is-mlflow) --- ## With the peace of mind of a secure and supported solution In addition to upstream features, Charmed MLflow includes: --- * Integration with machine learning and big data tools * Simplified deployment on any infrastructure * Security patching * Bug fixing --- ## Use Charmed MLflow with --- ## Deploy easily on any infra, from workstations to public clouds Run Charmed MLflow on any environment. The machine learning platform is made for everyone – from enthusiasts who are just getting started to enterprises running workloads at scale. --- * Quickly deploy it on a workstation * Deploy on any CNCF-conformant Kubernetes * Run it on a public cloud [Deploy Charmed MLflow on any infra](https://documentation.ubuntu.com/charmed-mlflow) --- [Why partner with Canonical for your enterprise AI project](https://ubuntu.com/ai) --- ## MLflow services ### Managed services We manage your MLflow deployments on any cloud, including: automatically deploying, patching, optimizing and upgrading with our open source operator. --- * Backed by a Service Level Agreement (SLA) * Low cost of ownership * Expert help in application operations * 24/7 support included [Contact us ›](https://canonical.com/mlops/contact-us) --- ### Enterprise support We provide 24/7 phone and ticket support for your MLflow deployments on any environment with an [Ubuntu Pro + Support subscription](https://ubuntu.com/pro). --- * Backed by an SLA * Quickly resolve technical support issues * Expert help in applications operations, troubleshooting, and bug fixes [Learn more about enterprise support ›](https://ubuntu.com/support) --- ### Long-term security maintenance We provide long-term security maintenance for Charmed MLflow, as well as the extensive open source libraries used for model training, and other MLOps tools (including TensorFlow, PyTorch, Feast, and more), through Ubuntu Pro. Ubuntu Pro is Canonical’s comprehensive subscription for open source security, support, and compliance. --- * Reduce average CVE exposure time with timely security updates * Get up to 15 years of stability for infrastructure, OS, and applications * Comply with FedRAMP, HIPAA, and more [Learn more about security maintenance ›](https://ubuntu.com/pro) [Try a 30-day free trial ›](https://ubuntu.com/pro/free-trial) --- [Speed up your AI journey with our consulting services](https://ubuntu.com/ai/consulting) --- ## MLflow resources [Charmed MLflow docs](https://documentation.ubuntu.com/charmed-mlflow) Read more about Charmed MLflow's capabilities and follow our tutorials. --- [Intro to MLflow](https://ubuntu.com/engage/mlflow-introduction) Understand the differences between the upstream project and Canonical's distribution. --- [Kubeflow vs. MLflow](https://ubuntu.com/engage/kubeflow-vs-mlflow) Understand the differences between the most famous open source solutions. --- [Guide to MLOps](https://ubuntu.com/engage/mlops-guide) Learn how to take models to production using open source MLOps platforms. --- Start your machine learning journey with open source [Install Charmed MLflow](https://documentation.ubuntu.com/charmed-mlflow) [Contact us](https://canonical.com/mlops/contact-us) Close ### Talk to our MLOps experts --- Looking to scale your MLOps infrastructure or need consulting services to kick start your AI journey? Our experts are here to help you.