MLflow
MLflow is a framework maintained by MLflow Project, a Series of LF Projects, LLC (Linux Foundation)458 and Databricks (creator)83, version 3.16.1. Its source code is public1 under the Apache License 2.03.
MLflow is an open-source platform for managing machine learning and generative AI development. For LLM applications and agents it provides tracing and observability (with OpenTelemetry integration), evaluation, prompt management and optimization, and an AI Gateway; for model training it provides experiment tracking, model evaluation, a model registry, and deployment tools. Databricks created MLflow, which joined the Linux Foundation in June 2020.28
- Repository: Repository (external site: github.com)
- Website: Website and documentation (external site: mlflow.org)
- License: LICENSE (external site: raw.githubusercontent.com)
- Release notes: Release v3.16.1 (external site: github.com)
Availability and license
Component reuse rights
- weights
- Unknown — no complete fact-level rights review
- code
- Unknown — no complete fact-level rights review
- data
- Unknown — no complete fact-level rights review
- documentation
- Unknown — no complete fact-level rights review
No complete system-rights review is recorded for this release.
Public materials checklist
| Item | Status | Notes and evidence |
|---|---|---|
| Source codeIs the source code publicly readable? | Public | 1 |
| DocumentationIs user documentation published? | Public | Documentation for the generative AI and model-training features is published on mlflow.org.2 |
| InstallationAre installation instructions or packages publicly available? | Public | Installable from PyPI with pip; the README's quick start runs a local tracking server with uvx mlflow server.62 |
| Supported platformsAre supported operating systems or hardware documented? | Public | PyPI lists Python 3.10 or later; the README states SDK support for Python, TypeScript/JavaScript, and Java.62 |
| Release statusAre versioned releases published? | Public | Versioned releases are published on GitHub and PyPI; 3.16.1 was released on PyPI on 2026-09-16.67 |
What it is useful for
Tracking experiments and models, tracing and evaluating LLM and agent applications, and deploying models to targets such as Docker, Kubernetes, and cloud ML services. It can run locally, on-premises, or on managed services.2
Organization context
In the news
MLflow 3.17.0 released with fine-grained permissions and TypeSafe judge support
On October 7, 2026 the MLflow project published version 3.17.0 on GitHub. The release notes list "Jev Decisions Across Evaluation, Gateway, and Tracing", which lets TypeSafe models be used in built-in scorers and custom judges, and "Fine-Grained Permissions for Shared Resources", with wildcard grants and explicit DENY for contained resource types such as runs, traces, and versions. They also describe opt-in daily summaries for trace analytics. The notes say SQL-backed servers need a coordinated
mlflow db upgradewith all writers stopped, and that mixed-version rolling upgrades are not supported. USASI has not tested these changes.Red Hat AI 3.5 becomes generally available with EvalHub and wider llm-d support
Red Hat announced on September 9, 2026 that Red Hat AI 3.5 is generally available, including as part of Red Hat AI Factory with NVIDIA. The release makes EvalHub generally available for safety benchmarking and compliance reporting before deployment, shows Garak results on evaluated catalog models, integrates NeMo Guardrails to intercept malicious tool calls, and adds AutoRAG and observability features such as per-user token metering and MLflow agentic tracing. Red Hat says llm-d distributed inference now extends beyond OpenShift to third-party Kubernetes services, generally available on CoreWeave CKS and Microsoft Azure, with Amazon EKS in technology preview. USASI has not tested Red Hat AI 3.5.
U.S. eligibility
Eligible · basis: U.S.-governed project
MLflow is governed as MLflow Project, a Series of LF Projects, LLC, under a technical charter adopted on June 2, 2020 that places technical oversight with a Technical Steering Committee; LF Projects, LLC is a Delaware series limited liability company. The Linux Foundation announced the project joining in June 2020 in a San Francisco-datelined release, and its privacy policy gives a San Francisco, California mailing address. The mlflow.org site footer names MLflow Project, a Series of LF Projects, LLC. The project was created by Databricks, whose 2018 copyright notice remains in the license file.45893
Sources
This listing is not an endorsement, a safety assessment, or a federal approval.
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APA style
USASI. (2026, September 29). MLflow. United States of America Superintelligence. https://unitedstatesofamericasuperintelligence.com/open/mlflow/
BibTeX
@misc{usasi_mlflow,
author = {{USASI}},
title = {MLflow},
year = {2026},
month = sep,
howpublished = {\url{https://unitedstatesofamericasuperintelligence.com/open/mlflow/}},
note = {United States of America Superintelligence. Last updated 2026-09-29}
}The date is when this page was last updated. Add the date you read it if your style needs one.
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