Open Source

Get Started with ZenML

Build production-ready ML pipelines with the open-source framework trusted by thousands of ML engineers worldwide.

Start in 3 simple steps

Install ZenML

Get ZenML up and running in minutes. You just need to install it
pip install zenml

Write your first pipeline

Create a simple run.py file with a basic workflow:
1from zenml import step, pipeline
2
3
4@step
5def basic_step() -> str:
6    """A simple step that returns a greeting message."""
7    return "Hello World!"
8
9
10@pipeline
11def basic_pipeline():
12    """A simple pipeline with just one step."""
13    basic_step()
14
15
16if __name__ == "__main__":
17    basic_pipeline()

Run your pipeline locally

ZenML automatically tracks the execution and stores artifacts.
python run.py
ZenML Architecture

Built on a Robust Client-Server Architecture

ZenML is a metadata layer on top of your existing infrastructure, meaning all data and compute stays on your side.
ZenML system architecture diagram showing connections between five main components: ZenML Client (Development Environment), ZenML Server, Database, MLOps Infrastructure (Cloud, Kubernetes, on-prem), and MLOps Tools (Experiment tracker, model deployer)
Projects

Start with one of our ready-made projects

Everything you need to replicate a production-grade use case - demo, video, blog, and code.

Ready for the next level?

Go beyond open source and with ZenML Pro. Get enterprise features, managed infrastructure, RBAC, enhanced security, dedicated support, and more.