Open-source MLOps · Apache-2.0
Production-readyML pipelines,on any stack.
Write a pipeline once. Run it anywhere.
- 01ingest()load & version data
- 02train()on any orchestrator
- 03evaluate()metrics & lineage
- 04deploy()serve & monitor
Stack-agnostic by design
Bring your own stack.
ZenML doesn’t replace your tools — it connects them. Choose the pieces you already run and keep the same pipeline code as your stack evolves.
Orchestrator
Cloud
Experiment tracker
orchestrator: Kubeflow
cloud: AWS
tracker: MLflow
Switch any layer later — your pipeline code stays the same. 50+ integrations and counting.
Browse all integrationsWhat the platform gives you
Production ML, without rewriting your stack.
Portable, reproducible pipelines
Write a pipeline once and run it on any orchestrator and cloud. ZenML tracks every step, artifact and model so a run from last quarter rebuilds exactly today.
- Pipelines and stacks across any cloud
- Model registry, lineage and reproducibility
- Smart caching and deduplication of steps
50+ integrations, no lock-in
Plug into the orchestrators, clouds, trackers and model registries you already use — swap any of them without touching pipeline code.
Governance, security and access
Role-based access, secrets and audit trails through ZenML Pro keep teams and regulated workloads in line.
Deploy, serve and track
Ship models to your serving stack and track every artifact, version and metric — from experiment to production, in one place.
Two products · one core
Start open source. Scale when you’re ready.
ZenML meets teams where they are: a free, self-hostable framework to begin with, and a managed control plane on top of the same open-source core when you grow.
ZenML (open source)
The open-source framework for portable, production-ready ML pipelines. Self-host the server and keep full control of your stack.
- Pipelines, stacks and artifact tracking
- Run the server on your own infrastructure
ZenML Pro
A managed control plane for teams: collaboration, pipeline monitoring, role-based access and governance on top of the open-source core.
- Team collaboration and RBAC
- Pipeline monitoring and governance
Questions, answered
Before you
book a demo.
Straight answers on licensing, lock-in and what runs where. Still curious? The docs and Slack go deeper.
Read the docsIs ZenML really open source?
Yes. The core framework is licensed under Apache-2.0 and the full server is self-hostable — see the repository at github.com/zenml-io/zenml. ZenML Pro is an optional managed control plane on top of the same open-source core.
Do I have to replace my current MLOps tools?
No. ZenML is stack-agnostic: it connects to the orchestrators, clouds, experiment trackers and model registries you already run. There are 50+ integrations including Kubeflow, Airflow, Vertex AI, MLflow and Weights & Biases.
Which clouds and orchestrators are supported?
ZenML runs on AWS, Google Cloud and Azure as well as hybrid and on-prem setups, and orchestrates with Kubeflow, Airflow, Kubernetes, Vertex AI and more. You can switch any layer later without rewriting your pipeline code.
What is the difference between ZenML and ZenML Pro?
ZenML open source is the free, self-hosted framework. ZenML Pro adds a managed control plane — team collaboration, pipeline monitoring, role-based access and governance. Pricing is published at zenml.io/pricing.
What does ZenML track for every pipeline run?
Every step, artifact, model and metric is tracked with full lineage, so runs are reproducible and a pipeline from last quarter rebuilds exactly today. Smart caching skips steps whose inputs haven’t changed.
How do I get started or talk to the team?
Read the docs at docs.zenml.io, star and clone the repo on GitHub, join the community Slack, or book a demo to see ZenML Pro with your own stack in mind.
Get started
Production ML pipelines,
on any stack.
Start with the open-source framework today, or book a demo to see ZenML Pro mapped onto the stack you already run.