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)

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.