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Open Source MLOps Platforms & Tools: MLflow, Kubeflow, ZenML & More

Open-source MLOps — lifecycle platforms, pipeline orchestrators and data versioning tools.

23 topics•4 categories•Updated October 2026

Lifecycle Platforms

5 entries

End-to-end tracking, packaging and deployment.

01MLflowOpen source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. Now also covers LLM/agent observability and evaluation. MLflow 3.17.2 was released on 21 October 2026, according to PyPI. 02KubeflowThe foundation of tools for AI platforms on Kubernetes, making deployment of ML workflows simple, portable, and scalable. Kubeflow Pipelines 2.17.3 was released on 22 October 2026, according to GitHub. 03MLRunOpen source AI orchestration framework to manage ML and generative AI applications from research to production-ready applications. The newest release listed is the pre-release v1.14.0-rc2, from 22 October 2026, according to GitHub. 04ZenMLA simple yet powerful open-source framework that scales your MLOps stack with your needs, from classical ML pipelines to LLM and agent workflows. 0.98.0 was released on 23 September 2026, according to GitHub. 05ClearMLOpen-source platform for experiment tracking, orchestration and data management. The clearml package 2.1.12 was released on 7 August 2026, according to GitHub.

Workflow & Pipeline Tools

5 entries

Pipelines for data and ML.

06FlyteThe workflow automation platform for complex, mission-critical data and machine learning processes at scale, authored in pure Python. v2.0.52 was released on 8 October 2026, according to GitHub. 07KedroOpen-source Python framework for creating reproducible, maintainable, and modular data engineering and data science code. 1.7.0 was released on 9 September 2026, according to GitHub. 08MetaflowA framework for real-life ML, AI, and data science that makes it quick and easy to build and manage production-grade projects. Originally built at Netflix. 2.19.39 was released on 18 August 2026, according to GitHub. 09DagsterAsset-based data and ML orchestration. dagster 1.13.26 was released on 9 October 2026, according to PyPI. 10PrefectWorkflow orchestration. prefect 3.9.0 was released on 21 October 2026, according to PyPI.

Data Versioning & CI for ML

3 entries

Version data and automate ML in CI.

11PachydermData versioning and lineage with automated, data-driven pipelines on Kubernetes, for reproducible machine learning workflows. Now owned by HPE; its source is under Pachyderm’s own license rather than an OSI-approved one, and the website could not be reached when last checked. The pachyderm.com address no longer responds; the project is on GitHub, with its last commit in January 2025. Its latest GitHub release is 2.12.2, from January 2025. 12CMLContinuous Machine Learning brings your favorite DevOps tools — GitHub, GitLab, Bitbucket CI/CD — to machine learning projects. Last commit on the default branch was in October 2024. 13DVCOpen-source data version control and experiment management. 3.67.1 was released on 14 March 2026, according to GitHub.

Related Pages

10 entries

Neighbouring pages on this site.

14MLOps PlatformsTop MLOps platforms compared. 15MLOps Workflow and Pipeline Orchestration ToolsOrchestration tools compared. 16ML Metadata Store SolutionsMetadata and lineage. 17CML FrameworksContinuous machine learning. 18Machine LearningMachine learning hub. 19LLMOpsOperating LLM applications in production. 20From MLOps to AgenticOpsHow operations practices extend to agents. 21ML Model Monitoring ToolsDrift and performance monitoring. 22ML Model Serving ToolsTools for serving models. 23Feature Store SolutionsFeature stores for training and inference.

Frequently Asked Questions

What is open-source MLOps?

Open-source MLOps tools automate the machine learning lifecycle (tracking, pipelines, deployment and monitoring) without vendor licences, usually by combining several projects.

Which platform should I start with?

MLflow is the most common tracker, Kubeflow suits Kubernetes teams, and ZenML or Metaflow offer lighter Python-first pipelines.

What happened to Pachyderm?

Its website no longer responds, so the entry links to the GitHub repository, where the last commit was in January 2025.

What changed recently among open-source MLOps platforms?

According to PyPI and GitHub in October 2026: MLflow 3.17.2 (21 October), Prefect 3.9.0 (21 October), Kubeflow Pipelines 2.17.3 (22 October), Dagster 1.13.26 (9 October), Flyte v2.0.52 (8 October) and ZenML 0.98.0 (23 September) have recent releases. CML's last commit on its default branch was in October 2024 and Pachyderm's was in January 2025.

How current is this page?

Links were checked in October 2026. Sites that block automated checks are kept and may need a manual click. Last-commit dates come from GitHub in October 2026 and show default-branch activity only; check each project's release notes before adopting it.

Which links may need a manual click?

Links were rechecked in October 2026 and all outbound links on this page returned 200 to automated checks. Release dates on the cards come from PyPI and GitHub.